Golly script coding practice

[dvgrn]

I wasn't terribly surprised by the lack of response to my offer here --

If anyone wants to learn how to build the salvos for the NW or SE Corderfleets, just let me know -- I don't necessarily want to be the only person having fun with slsparse.

-- but I'm going to go ahead and start a new thread anyway, and see if anyone expresses any interest here. To keep making progress on the RCT Grand Plan, here are three small sub-projects that I'm going to be working on as I have time:

1) just for fun, write a script to make a list of PASTET commands to show the 2881-glider salvo that the ECCA will produce to clean up the repetitive GPSE ash in the southwest, as a LifeViewer animation (DONE);

2) write a script to take a slow salvo lane list as input, and create a slow^2 salvo lane list as output -- to be used for cleaning up the big splotch of non-repetitive GPSE startup ash in the far southwest;

3) Build a slow salvo to be prepended to the SW Corderfleet-making slow salvo, to clean up the SE and then NW repetitive GPSE ash, including its occasional blips of extra ash from Bit-Reading Glider crashes and resulting retrograde gliders and so on (in progress, below).

The SW salvo was only twenty-two Corderships, which could be done with two sets of eleven identical recipes (well, the way I did it, there were two tiny exceptions, one in the first Cordership seed and one in the last, but they weren't necessary exceptions). I found it useful to build that slow salvo partly by hand, to understand the whole process well enough to automate it.

Now it seems to make sense to automate everything that can be automated, so here's my current plan:

Code: Select all

3.1) Make a list of relative coordinates for SE-traveling Corderships, and then for NW-traveling Corderships
3.2) Write a Python script to create a different infile.mc for each set of relative coordinates
3.3) Write a batch file to run slsparse on each input, then copy each resulting output to a separate outfileN.mc
3.4) Write a Python script to find and move the target block in each outfileN.mc,
   then run the modified outfileN.mc to get the slow salvo instead of the single-channel recipe,
   then find and remove the elbow block,
   then rotate the gliders as needed and put the target block at (0,0),
   then get the lane list and minimize recipe,
   then add the trigger glider at the correct offset,
   then save the resulting recipeN.mc and optionally record the lane list
3.5) Write a Python script to string together the recipeN.mc subpatterns

This is all single-use code that will probably only ever be used to create these two Corderfleets, totalling I think 84 Corderships... still worth doing the coding, though, to avoid doing any more of what I did by hand for the slow salvo for the SW Corderfleet.

Level of Interest Survey
There are a couple of ways to get through these various subprojects. One, I can just post each script here when it's done, and post the output over on the ECCA or Goucher-Grankovskiy threads.

If anyone is interested in the coding details of the problem-solving process, though, please post a response here -- could be either multiple posts, or some number of likes added to an initial response post.

If there's enough interest from people that want to learn some useful Golly scripting but so far just haven't managed to get started ... I can easily do more of a walkthrough in this thread of each subproject, showing the stages of code development and the various bits and pieces of functionality that turn out to need testing along the way, to get to the final end result.

(I'll probably just use Python, even though lifelib could ultimately do some of these tasks a little bit easier, just to reduce the number of dependencies. Come to think of it, for some of them, or the first one anyway, I'll use Lua instead, so that the only requirement is Golly running on a desktop, plus a text editor.)

[dvgrn]

Confirmed the procedure that I'll be coding up for item #2 above, for the SEward Corderfleet:

Code: Select all

x = 9554, y = 11155, rule = LifeSuper
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426.2S$425.S2.S$426.2S$379.S$379.S$379.S$390.S$389.S.S$389.2S2$352.2S
$352.2S66.S$419.S.S$419.S2.S$420.2S4$348.2S$348.2S40.2S$389.S2.S$390.
2S2$386.3S2$390.S$390.S$390.S$358.2S$357.S.S32.2S$357.2S33.2S$402.3S$
458.2S$457.S2.S$458.2S$411.S$411.S$411.S$422.S$421.S.S$421.2S2$384.2S
$384.2S66.S$451.S.S$451.S2.S$452.2S4$380.2S$380.2S40.2S$421.S2.S$422.
2S2$418.3S2$422.S$422.S$422.S$390.2S$389.S.S32.2S$389.2S33.2S$434.3S$
490.2S$489.S2.S$490.2S$443.S$443.S$443.S$454.S$453.S.S$425.2S26.2S$
425.2S2.2S$416.2S11.2S$416.2S66.S$483.S.S$483.S2.S$484.2S4$412.2S$
412.2S40.2S$453.S2.S$454.2S2$450.3S2$454.S$454.S$454.S$429.2S$429.2S
2.2S21.2S$433.2S21.2S$466.3S$522.2S$521.S2.S$436.2S84.2S$436.2S37.S$
475.S$475.S$486.S$485.S.S$415.2S68.2S$414.S.S9.2S$415.S10.2S$516.S$
515.S.S$515.S2.S$440.3S73.2S2$415.2T$415.2T$452.S$452.S33.2S$452.S32.
S2.S$426.2S58.2S$426.2S10.S$438.S17.2S24.3S$413.2S23.S17.2S$413.2S71.
S$424.2S8.3S3.3S43.S$424.2S60.S2$488.2S$488.2S$431.3S64.3S$554.2S$
553.S2.S$554.2S$447.2S58.S$447.2S58.S$443.2S62.S$443.2S73.S$517.S.S$
517.2S2$480.2S$480.2S66.S$547.S.S$547.S2.S$417.S130.2S$417.S$417.S2$
476.2S$476.2S40.2S$517.S2.S$518.2S$434.2S$433.S2.S77.3S$434.2S$518.S$
518.S$518.S$486.2S$485.S.S32.2S$485.2S33.2S$379.S.S.S.S.S142.3S$586.
2S$385.S.S197.S2.S$586.2S$383.S3.S151.S$539.S$381.S5.S151.S$550.S$
379.S7.S161.S.S$549.2S$377.S$512.2S$375.S136.2S66.S$579.S.S$373.S205.
S2.S$580.2S$371.S2$369.S$508.2S$367.S140.2S40.2S$549.S2.S$365.S184.2S
2$363.S182.3S2$361.S188.S$550.S$359.S190.S$518.2S$357.S159.S.S32.2S$
517.2S33.2S$355.S206.3S$618.2S$353.S263.S2.S$618.2S$351.S219.S$571.S$
349.S221.S$582.S$347.S233.S.S$581.2S$345.S$544.2S$343.S200.2S66.S$
611.S.S$341.S269.S2.S$612.2S$339.S2$337.S$540.2S$335.S204.2S40.2S$
581.S2.S$582.2S2$578.3S2$582.S$582.S$582.S$550.2S$549.S.S32.2S$549.2S
33.2S$594.3S$650.2S$649.S2.S$650.2S$603.S$603.S$603.S$614.S$613.S.S$
585.2S26.2S$585.2S2.2S$576.2S11.2S$576.2S66.S$643.S.S$643.S2.S$644.2S
4$572.2S$572.2S40.2S$613.S2.S$614.2S2$610.3S2$614.S$614.S$614.S$589.
2S$589.2S2.2S21.2S$593.2S21.2S$626.3S$682.2S$681.S2.S$596.2S84.2S$
596.2S37.S$635.S$635.S$646.S$645.S.S$575.2S68.2S$574.S.S9.2S$575.S10.
2S$676.S$675.S.S$675.S2.S$600.3S73.2S2$575.2S$575.2S$612.S$612.S33.2S
$612.S32.S2.S$586.2S58.2S$586.2S10.S$598.S17.2S24.3S$573.2S23.S17.2S$
573.2S71.S$584.2S8.3S3.3S43.S$584.2S60.S2$648.2S$648.2S$591.3S64.3S$
714.2S$713.S2.S$714.2S$607.2S58.S$607.2S58.S$603.2S62.S$603.2S73.S$
677.S.S$677.2S2$640.2S$640.2S66.S$707.S.S$707.S2.S$577.S130.2S$577.S$
577.S2$636.2S$636.2S40.2S$677.S2.S$678.2S$594.2S$593.S2.S77.3S$594.2S
$678.S$678.S$678.S$646.2S$645.S.S32.2S$645.2S33.2S$690.3S$746.2S$745.
S2.S$746.2S$699.S$527.S.S.S.S.S163.S$699.S$533.S.S174.S$709.S.S$531.S
3.S173.2S2$529.S5.S136.2S$672.2S66.S$527.S7.S203.S.S$739.S2.S$525.S
214.2S2$523.S2$521.S146.2S$668.2S40.2S$519.S189.S2.S$710.2S$517.S$
706.3S$515.S$710.S$513.S196.S$710.S$511.S166.2S$677.S.S32.2S$509.S
167.2S33.2S$722.3S$507.S270.2S$777.S2.S$505.S272.2S$731.S$503.S227.S$
731.S$501.S240.S$741.S.S$499.S241.2S2$497.S206.2S$704.2S66.S$495.S
275.S.S$771.S2.S$493.S278.2S2$491.S2$489.S210.2S$700.2S40.2S$487.S
253.S2.S$742.2S$485.S$738.3S$483.S$742.S$742.S$742.S$710.2S$709.S.S
32.2S$709.2S33.2S$754.3S$810.2S$809.S2.S$744.S65.2S$743.S.S17.S$743.S
2.S16.S$744.2S17.S$774.S$773.S.S$773.2S3$804.S$732.2S10.S58.S.S$731.S
2.S9.S58.S2.S$732.2S10.S59.2S2$740.3S3$774.2S$743.2S28.S2.S$743.2S3.S
25.2S$747.S.S$747.S.S20.3S$748.S$733.2S39.S$733.2S39.S$774.S2$776.2S$
776.2S$733.2S51.3S$733.2S13.S93.2S$747.S.S91.S2.S$744.S3.2S92.2S$744.
S50.S$733.2S9.S50.S$733.2S60.S$806.S$805.S.S$805.2S2$749.2S$749.2S85.
S$782.2S51.S.S$733.2S47.2S51.S2.S$733.2S16.S84.2S$750.S.S$749.S2.S36.
2S$750.2S37.2S$761.2S$761.2S43.2S$745.2S58.S2.S$744.S2.S58.2S$722.2S
21.2S$722.S.S77.3S$723.2S$806.S$763.2S41.S$745.3S15.2S41.S2$757.2S49.
2S$757.2S49.2S$818.3S$774.2S98.2S$774.2S97.S2.S$874.2S$827.S$827.S$
827.S$838.S$837.S.S$837.2S2$800.2S$800.2S66.S$867.S.S$687.S.S.S.S.S
171.S2.S$868.2S$693.S.S2$691.S3.S$796.2S$689.S5.S100.2S40.2S$837.S2.S
$687.S7.S142.2S2$685.S148.3S2$683.S154.S$838.S$681.S156.S$806.2S$679.
S125.S.S32.2S$805.2S33.2S$677.S172.3S$906.2S$675.S229.S2.S$906.2S$
673.S185.S$859.S$671.S187.S$870.S$669.S199.S.S$869.2S$667.S$832.2S$
665.S166.2S66.S$899.S.S$663.S235.S2.S$900.2S$661.S2$659.S$828.2S$657.
S170.2S40.2S$869.S2.S$655.S214.2S2$653.S212.3S2$651.S218.S$870.S$649.
S220.S$838.2S$647.S189.S.S32.2S$837.2S33.2S$645.S236.3S$938.2S$643.S
293.S2.S$938.2S$891.S$891.S$891.S$902.S$901.S.S$901.2S2$864.2S$864.2S
66.S$931.S.S$931.S2.S$932.2S4$860.2S$860.2S40.2S$901.S2.S$902.2S2$
898.3S2$902.S$902.S$902.S$870.2S$869.S.S32.2S$869.2S33.2S$914.3S$970.
2S$969.S2.S$970.2S$923.S$923.S$923.S$934.S$933.S.S$933.2S2$896.2S$
896.2S66.S$963.S.S$963.S2.S$964.2S4$892.2S$892.2S40.2S$933.S2.S$934.
2S2$930.3S2$934.S$934.S$934.S$902.2S$901.S.S32.2S$901.2S33.2S$946.3S$
1002.2S$1001.S2.S$936.S65.2S$935.S.S17.S$935.S2.S16.S$936.2S17.S$966.
S$965.S.S$965.2S3$996.S$924.2S10.S58.S.S$923.S2.S9.S58.S2.S$924.2S10.
S59.2S2$932.3S3$966.2S$935.2S28.S2.S$935.2S3.S25.2S$939.S.S$939.S.S
20.3S$940.S$925.2S39.S$925.2S39.S$966.S2$968.2S$968.2S$925.2S51.3S$
925.2S13.S93.2S$939.S.S91.S2.S$936.S3.2S92.2S$936.S50.S$925.2S9.S50.S
$925.2S60.S$998.S$997.S.S$997.2S2$941.2S$941.2S85.S$974.2S51.S.S$925.
2T47.2S51.S2.S$925.2T16.S84.2S$942.S.S$941.S2.S36.2S$942.2S37.2S$953.
2S$953.2S43.2S$937.2S58.S2.S$936.S2.S58.2S$914.2S21.2S$914.S.S77.3S$
915.2S$998.S$955.2S41.S$937.3S15.2S41.S2$949.2S49.2S$949.2S49.2S$
1010.3S$966.2S98.2S$966.2S97.S2.S$1066.2S$1019.S$1019.S$1019.S$1030.S
$1029.S.S$1029.2S2$992.2S$992.2S66.S$1059.S.S$1059.S2.S$1060.2S$884.S
.S.S.S.S2$890.S.S$988.2S$888.S3.S95.2S40.2S$1029.S2.S$886.S5.S137.2S
2$884.S7.S133.3S2$882.S147.S$1030.S$880.S149.S$998.2S$878.S118.S.S32.
2S$997.2S33.2S$876.S165.3S$1098.2S$874.S222.S2.S$1098.2S$872.S178.S$
1051.S$870.S180.S$1062.S$868.S192.S.S$1061.2S$866.S$1024.2S$864.S159.
2S66.S$1091.S.S$862.S228.S2.S$1092.2S$860.S2$858.S$1020.2S$856.S163.
2S40.2S$1061.S2.S$854.S207.2S2$852.S205.3S2$850.S211.S$1062.S$848.S
213.S$1030.2S$846.S182.S.S32.2S$1029.2S33.2S$844.S229.3S$1130.2S$842.
S286.S2.S$1130.2S$840.S242.S$1083.S$1083.S$1094.S$1093.S.S$1093.2S2$
1056.2S$1056.2S66.S$1123.S.S$1123.S2.S$1124.2S4$1052.2S$1052.2S40.2S$
1093.S2.S$1094.2S2$1090.3S2$1094.S$1094.S$1094.S$1062.2S$1061.S.S32.
2S$1061.2S33.2S$1106.3S$1162.2S$1161.S2.S$1162.2S$1115.S$1115.S$1115.
S$1126.S$1125.S.S$1125.2S2$1088.2S$1088.2S66.S$1155.S.S$1155.S2.S$
1156.2S4$1084.2S$1084.2S40.2T$1125.T2.T$1126.2T2$1122.3T2$1126.T$
1126.T$1126.T$1094.2S$1093.S.S32.2T$1093.2S33.2T$1138.3S$1194.2S$
1193.S2.S$1194.2S$1147.S$1147.S$1147.S$1158.S$1157.S.S$1157.2S2$1120.
2S$1120.2S66.S$1187.S.S$1187.S2.S$1188.2S4$1116.2S$1116.2S40.2S$1157.
S2.S$1158.2S2$1154.3S2$1158.S$1158.S$1158.S$1126.2S$1125.S.S32.2S$
1125.2S33.2S$1170.3S$1226.2S$1225.S2.S$1226.2S$1179.S$1179.S$1179.S$
1190.S$1189.S.S$1189.2S2$1152.2S$1152.2S66.S$1219.S.S$1219.S2.S$1220.
2S4$1061.S.S.S.S.S78.2S$1148.2S40.2S$1067.S.S119.S2.S$1190.2S$1065.S
3.S$1186.3S$1063.S5.S$1190.S$1061.S7.S120.S$1190.S$1059.S98.2S$1157.S
.S32.2S$1057.S99.2S33.2S$1202.3S$1055.S202.2S$1257.S2.S$1053.S204.2S$
1211.S$1051.S159.S$1211.S$1049.S172.S$1221.S.S$1047.S173.2S2$1045.S
138.2S$1184.2S66.S$1043.S207.S.S$1251.S2.S$1041.S210.2S2$1039.S2$
1037.S142.2S$1180.2S40.2S$1035.S185.S2.S$1222.2S$1033.S$1218.3S$1031.
S$1222.S$1029.S192.S$1222.S$1027.S162.2S$1189.S.S32.2S$1025.S163.2S
33.2S$1234.3S$1023.S266.2S$1289.S2.S$1021.S268.2S$1243.S$1019.S223.S$
1243.S$1017.S236.S$1253.S.S$1253.2S2$1216.2S$1216.2S66.S$1283.S.S$
1283.S2.S$1284.2S4$1212.2S$1212.2S40.2T$1253.T2.T$1254.2T2$1250.3T2$
1253.Q$1252.Q.Q$1253.2Q$1222.2S$1221.S.S32.2Q$1221.2S33.2Q$1266.3S$
1322.2S$1321.S2.S$1322.2S$1275.S$1275.S$1275.S$1286.S$1285.S.S$1285.
2S2$1248.2S$1248.2S66.S$1315.S.S$1315.S2.S$1316.2S4$1244.2S$1244.2S
40.2S$1285.S2.S$1286.2S2$1282.3S2$1286.S$1286.S$1286.S$1254.2S$1253.S
.S32.2S$1253.2S33.2S$1298.3S$1354.2S$1353.S2.S$1354.2S$1307.S$1307.S$
1307.S$1318.S$1317.S.S$1317.2S2$1280.2S$1280.2S66.S$1347.S.S$1347.S2.
S$1348.2S4$1189.S.S.S.S.S78.2S$1276.2S40.2S$1195.S.S119.S2.S$1318.2S$
1193.S3.S$1314.3S$1191.S5.S$1318.S$1189.S7.S120.S$1318.S$1187.S98.2S$
1285.S.S32.2S$1185.S99.2S33.2S$1330.3S$1183.S202.2S$1385.S2.S$1181.S
204.2S$1339.S$1179.S159.S$1339.S$1177.S172.S$1349.S.S$1175.S173.2S2$
1173.S138.2S$1312.2S66.S$1171.S207.S.S$1379.S2.S$1169.S210.2S2$1167.S
2$1165.S142.2S$1308.2S40.2S$1163.S185.S2.S$1350.2S$1161.S$1346.3S$
1159.S$1350.S$1157.S192.S$1350.S$1155.S162.2S$1317.S.S32.2S$1153.S
163.2S33.2S$1362.3S$1151.S2$1149.S$1371.S$1147.S223.S$1371.S$1145.S
236.S$1381.S.S$1381.2S2$1344.2S$1344.2S7$1340.2S$1340.2S40.2S$1381.S
2.S$1382.2S2$1378.3S2$1382.S$1382.S$1382.S$1350.2S$1349.S.S32.2S$
1349.2S33.2S$1394.3S100.W$1496.W.W$1496.W.W$1491.2W4.W$1490.W2.W$
1491.2W6$1376.2S$1376.2S5$1490.2W$1490.2W$1372.2S$1372.2S7$1506.W$
1505.W.W$1382.2S121.W.W$1381.S.S116.2W4.W$1381.2S116.W2.W$1500.2W12$
1499.2W$1499.2W!
#C [[ MAXGRIDSIZE 14 ]]

Again, if anyone is interested in a more detailed walkthrough of how I'm working through these problems, this thread would be a good place to say so. These won't be particularly elegant solutions, but they'll be simple code that anybody can run, and they will let us cross off a couple more items from the list of remaining RCT tasks.

The infile.mc that I'm using as a base for these slsparse runs looks like this:

Code: Select all

x = 140, y = 138, rule = LifeHistory
19.A$18.A.A15.A$18.2A15.A.A$35.2A3$15.2A$15.2A2$34.2A$33.A.A$34.A3$7.
2A$7.2A$39.A$38.A.A$39.A6$21.2A$.A19.2A$A.A$.2A30.2A$33.2A18.A$7.2A3.
2A38.A.A$6.A.A2.A.A38.2A$7.A4.A3$25.2A$24.A.A$25.A3$25.2A9.2D$24.A.A
9.2D3.2A$25.A15.2A4$28.2A$28.A.A$29.A86$135.A$134.A.A.2A$133.A2.A.2A$
133.A.A$134.A!

The orientation is 90 degrees off from the actual orientation in the RCT. That's for the convenience of the next script, which expects slow salvos to be heading northwest toward a target. The slsparse output looks like this

Code: Select all

x = 114362, y = 114453, rule = B3/S23
114258b2o$114258b2o94$114360b2o$114360b2o2$114353b3o$114355bo$114354bo
25$114326b2o$114327b2o$114326bo21$114303b3o$114305bo$114304bo21$
114280b2o$114279bobo$114281bo21$114257b2o$114258b2o$114257bo20$114235b
o$114235b2o$114234bobo22$114211bo$114211b2o$114210bobo21$114188b2o$
114189b2o$114188bo21$114165b3o$114167bo$114166bo34$114129b2o$114128bob
o$114130bo58$114069b2o$114068bobo$114070bo25$114042bo$114042b2o$
114041bobo21$114019b2o$114018bobo$114020bo22$113995b3o$113997bo$
113996bo20$113973bo$113973b2o$113972bobo21$113950b2o$113949bobo$
113951bo21$113927b2o$113926bobo$113928bo21$113904b3o$113906bo$113905bo
33$113869bo$113869b2o$113868bobo21$113846b2o$113847b2o$113846bo21$
113823b3o$113825bo$113824bo37$113784b2o$113783bobo$113785bo21$113761b
3o$113763bo$113762bo25$113734b2o$113735b2o$113734bo20$113712bo$113712b
2o$113711bobo22$113688b3o$113690bo$113689bo20$113666bo$113666b2o$
113665bobo21$113643b2o$113644b2o$113643bo22$113619b3o$113621bo$113620b
o20$113597bo$113597b2o$113596bobo21$113574b2o$113573bobo$113575bo25$
113547bo$113547b2o$113546bobo21$113524b2o$113523bobo$113525bo21$
113501b3o$113503bo$113502bo20$113479b2o$113478bobo$113480bo21$113456b
2o$113457b2o$113456bo23$113431b3o$113433bo$113432bo20$113409b2o$
113408bobo$113410bo23$113384b3o$113386bo$113385bo20$113362b2o$113361bo
bo$113363bo21$113339b3o$113341bo$113340bo27$113310b2o$113309bobo$
113311bo21$113287b2o$113288b2o$113287bo20$113265bo$113265b2o$113264bob
o21$113242b2o$113243b2o$113242bo20$113220bo$113220b2o$113219bobo21$
113197b2o$113198b2o$113197bo20$113175bo$113175b2o$113174bobo26$113147b
3o$113149bo$113148bo20$113125b2o$113124bobo$113126bo22$113101b2o$
113102b2o$113101bo59$113040b2o$113039bobo$113041bo21$113017b3o$113019b
o$113018bo29$112986b2o$112985bobo$112987bo50$112934b2o$112933bobo$
112935bo30$112902b2o$112901bobo$112903bo21$112879b3o$112881bo$112880bo
22$112855b3o$112857bo$112856bo20$112833bo$112833b2o$112832bobo21$
112810b2o$112811b2o$112810bo20$112788bo$112788b2o$112787bobo21$112765b
2o$112764bobo$112766bo21$112742b2o$112743b2o$112742bo21$112719b3o$
112721bo$112720bo20$112697bo$112697b2o$112696bobo23$112672bo$112672b2o
$112671bobo21$112649b2o$112650b2o$112649bo20$112627bo$112627b2o$
112626bobo21$112604b2o$112605b2o$112604bo25$112577b2o$112576bobo$
112578bo21$112554b2o$112555b2o$112554bo21$112531b2o$112530bobo$112532b
o21$112508b3o$112510bo$112509bo33$112473b3o$112475bo$112474bo35$
112436b2o$112435bobo$112437bo26$112408bo$112408b2o$112407bobo21$
112385b2o$112386b2o$112385bo20$112363bo$112363b2o$112362bobo21$112340b
2o$112341b2o$112340bo20$112318bo$112318b2o$112317bobo21$112295b2o$
112294bobo$112296bo32$112261b2o$112260bobo$112262bo28$112231b2o$
112232b2o$112231bo30$112199b3o$112201bo$112200bo20$112177b2o$112176bob
o$112178bo37$112138b3o$112140bo$112139bo33$112103b2o$112102bobo$
112104bo31$112070b2o$112069bobo$112071bo21$112047b2o$112048b2o$112047b
o21$112024b3o$112026bo$112025bo20$112002b2o$112001bobo$112003bo29$
111971b2o$111970bobo$111972bo30$111939b3o$111941bo$111940bo20$111917bo
$111917b2o$111916bobo21$111894b2o$111895b2o$111894bo20$111872bo$
111872b2o$111871bobo21$111849b2o$111848bobo$111850bo21$111826b3o$
111828bo$111827bo20$111804b2o$111803bobo$111805bo39$111763b2o$111762bo
bo$111764bo46$111715bo$111715b2o$111714bobo21$111692b2o$111691bobo$
111693bo21$111669b3o$111671bo$111670bo20$111647b2o$111646bobo$111648bo
29$111616b2o$111615bobo$111617bo22$111592b2o$111593b2o$111592bo21$
111569b3o$111571bo$111570bo37$111530b3o$111532bo$111531bo20$111508b2o$
111507bobo$111509bo21$111485b3o$111487bo$111486bo29$111454b2o$111453bo
bo$111455bo21$111431b3o$111433bo$111432bo20$111409b2o$111408bobo$
111410bo25$111382bo$111382b2o$111381bobo21$111359b2o$111360b2o$111359b
o27$111330b2o$111329bobo$111331bo21$111307b2o$111308b2o$111307bo29$
111276b2o$111277b2o$111276bo29$111245bo$111245b2o$111244bobo21$111222b
2o$111221bobo$111223bo21$111199b3o$111201bo$111200bo20$111177b2o$
111176bobo$111178bo21$111154b2o$111155b2o$111154bo20$111132bo$111132b
2o$111131bobo21$111109b2o$111110b2o$111109bo39$111068b2o$111069b2o$
111068bo46$111020b2o$111019bobo$111021bo21$110997b2o$110998b2o$110997b
o20$110975bo$110975b2o$110974bobo21$110952b2o$110953b2o$110952bo29$
110921b2o$110922b2o$110921bo22$110897b3o$110899bo$110898bo20$110875bo$
110875b2o$110874bobo37$110836bo$110836b2o$110835bobo21$110813b2o$
110814b2o$110813bo20$110791bo$110791b2o$110790bobo30$110759b2o$110760b
2o$110759bo20$110737bo$110737b2o$110736bobo21$110714b2o$110715b2o$
110714bo25$110687b2o$110686bobo$110688bo21$110664b3o$110666bo$110665bo
27$110635b2o$110636b2o$110635bo21$110612b3o$110614bo$110613bo25$
110585b2o$110586b2o$110585bo21$110562b3o$110564bo$110563bo21$110539b2o
$110540b2o$110539bo21$110516b3o$110518bo$110517bo34$110480b2o$110481b
2o$110480bo52$110426b3o$110428bo$110427bo24$110400b2o$110399bobo$
110401bo21$110377b3o$110379bo$110378bo20$110355b2o$110354bobo$110356bo
21$110332b2o$110333b2o$110332bo21$110309b3o$110311bo$110310bo41$
110266b2o$110265bobo$110267bo21$110243b3o$110245bo$110244bo37$110204b
2o$110203bobo$110205bo21$110181b3o$110183bo$110182bo20$110159b2o$
110158bobo$110160bo21$110136b3o$110138bo$110137bo20$110114bo$110114b2o
$110113bobo33$110079b3o$110081bo$110080bo20$110057b2o$110056bobo$
110058bo21$110034b2o$110035b2o$110034bo30$110002b3o$110004bo$110003bo
20$109980b2o$109979bobo$109981bo25$109953bo$109953b2o$109952bobo21$
109930b2o$109929bobo$109931bo22$109906b3o$109908bo$109907bo20$109884bo
$109884b2o$109883bobo21$109861b2o$109860bobo$109862bo32$109827b2o$
109826bobo$109828bo21$109804b2o$109805b2o$109804bo20$109782bo$109782b
2o$109781bobo21$109759b2o$109758bobo$109760bo24$109733b2o$109732bobo$
109734bo21$109710b3o$109712bo$109711bo20$109688b2o$109687bobo$109689bo
21$109665b3o$109667bo$109666bo25$109638b2o$109637bobo$109639bo21$
109615b3o$109617bo$109616bo20$109593b2o$109592bobo$109594bo23$109568b
3o$109570bo$109569bo20$109546b2o$109545bobo$109547bo25$109519bo$
109519b2o$109518bobo21$109496b2o$109495bobo$109497bo21$109473bo$
109473b2o$109472bobo21$109450b2o$109449bobo$109451bo34$109414bo$
109414b2o$109413bobo52$109360b2o$109359bobo$109361bo25$109333b3o$
109335bo$109334bo20$109311b2o$109310bobo$109312bo21$109288b3o$109290bo
$109289bo20$109266bo$109266b2o$109265bobo21$109243b2o$109242bobo$
109244bo42$109199b3o$109201bo$109200bo20$109177b2o$109176bobo$109178bo
38$109137b3o$109139bo$109138bo20$109115b2o$109114bobo$109116bo21$
109092b3o$109094bo$109093bo20$109070b2o$109069bobo$109071bo21$109047b
2o$109048b2o$109047bo32$109013b2o$109012bobo$109014bo21$108990b3o$
108992bo$108991bo20$108968bo$108968b2o$108967bobo30$108936b2o$108935bo
bo$108937bo21$108913b3o$108915bo$108914bo25$108886b2o$108887b2o$
108886bo21$108863b3o$108865bo$108864bo21$108840b2o$108841b2o$108840bo
21$108817b3o$108819bo$108818bo22$108793b2o$108794b2o$108793bo21$
108770b3o$108772bo$108771bo20$108748bo$108748b2o$108747bobo25$108721b
2o$108722b2o$108721bo21$108698b3o$108700bo$108699bo20$108676b2o$
108675bobo$108677bo21$108653b3o$108655bo$108654bo20$108631b2o$108630bo
bo$108632bo21$108608b3o$108610bo$108609bo20$108586b2o$108585bobo$
108587bo21$108563b2o$108564b2o$108563bo39$108522b3o$108524bo$108523bo
20$108500b2o$108499bobo$108501bo21$108477b3o$108479bo$108478bo24$
108451b3o$108453bo$108452bo20$108429bo$108429b2o$108428bobo26$108401b
3o$108403bo$108402bo20$108379bo$108379b2o$108378bobo22$108355b3o$
108357bo$108356bo20$108333bo$108333b2o$108332bobo21$108310bo$108310b2o
$108309bobo21$108287b2o$108288b2o$108287bo22$108263b2o$108262bobo$
108264bo21$108240b2o$108241b2o$108240bo27$108211b2o$108212b2o$108211bo
21$108188b3o$108190bo$108189bo27$108159bo$108159b2o$108158bobo21$
108136b2o$108137b2o$108136bo20$108114bo$108114b2o$108113bobo21$108091b
2o$108090bobo$108092bo24$108065b2o$108064bobo$108066bo23$108040b2o$
108041b2o$108040bo20$108018bo$108018b2o$108017bobo21$107995bo$107995b
2o$107994bobo22$107971b2o$107972b2o$107971bo21$107948b3o$107950bo$
107949bo22$107924b2o$107925b2o$107924bo21$107901b3o$107903bo$107902bo
21$107878b3o$107880bo$107879bo20$107856bo$107856b2o$107855bobo23$
107831b2o$107832b2o$107831bo20$107809bo$107809b2o$107808bobo26$107781b
3o$107783bo$107782bo20$107759bo$107759b2o$107758bobo22$107735b3o$
107737bo$107736bo20$107713bo$107713b2o$107712bobo35$107676b3o$107678bo
$107677bo51$107623bo$107623b2o$107622bobo25$107596b2o$107597b2o$
107596bo20$107574bo$107574b2o$107573bobo21$107551b2o$107552b2o$107551b
o21$107528b3o$107530bo$107529bo20$107506bo$107506b2o$107505bobo42$
107462b2o$107463b2o$107462bo20$107440bo$107440b2o$107439bobo38$107400b
2o$107401b2o$107400bo20$107378bo$107378b2o$107377bobo21$107355b2o$
107356b2o$107355bo20$107333bo$107333b2o$107332bobo21$107310b2o$107309b
obo$107311bo32$107276bo$107276b2o$107275bobo21$107253b2o$107254b2o$
107253bo21$107230b3o$107232bo$107231bo29$107199bo$107199b2o$107198bobo
21$107176b2o$107177b2o$107176bo25$107149b2o$107148bobo$107150bo21$
107126b2o$107127b2o$107126bo21$107103b2o$107102bobo$107104bo21$107080b
2o$107081b2o$107080bo41$107037bo$107037b2o$107036bobo21$107014b2o$
107015b2o$107014bo21$106991b3o$106993bo$106992bo20$106969b2o$106968bob
o$106970bo35$106932b2o$106931bobo$106933bo21$106909b3o$106911bo$
106910bo23$106884b2o$106885b2o$106884bo39$106843b3o$106845bo$106844bo
34$106807b2o$106806bobo$106808bo21$106784b3o$106786bo$106785bo33$
106749bo$106749b2o$106748bobo21$106726b2o$106725bobo$106727bo21$
106703b2o$106704b2o$106703bo20$106681bo$106681b2o$106680bobo29$106650b
2o$106649bobo$106651bo21$106627b3o$106629bo$106628bo20$106605bo$
106605b2o$106604bobo31$106572bo$106572b2o$106571bobo23$106547bo$
106547b2o$106546bobo26$106519b3o$106521bo$106520bo20$106497b2o$106496b
obo$106498bo21$106474bo$106474b2o$106473bobo21$106451b2o$106450bobo$
106452bo21$106428b3o$106430bo$106429bo21$106405bo$106405b2o$106404bobo
21$106382b2o$106381bobo$106383bo21$106359b2o$106360b2o$106359bo25$
106332b2o$106331bobo$106333bo21$106309b2o$106310b2o$106309bo20$106287b
o$106287b2o$106286bobo21$106264b2o$106265b2o$106264bo21$106241b3o$
106243bo$106242bo22$106217bo$106217b2o$106216bobo21$106194b2o$106195b
2o$106194bo22$106170bo$106170b2o$106169bobo21$106147b2o$106148b2o$
106147bo20$106125bo$106125b2o$106124bobo28$106095b2o$106096b2o$106095b
o21$106072b3o$106074bo$106073bo20$106050b2o$106049bobo$106051bo21$
106027b3o$106029bo$106028bo20$106005b2o$106004bobo$106006bo21$105982b
3o$105984bo$105983bo20$105960b2o$105959bobo$105961bo25$105933bo$
105933b2o$105932bobo21$105910b2o$105909bobo$105911bo22$105886b3o$
105888bo$105887bo20$105864bo$105864b2o$105863bobo21$105841b2o$105840bo
bo$105842bo21$105818b2o$105817bobo$105819bo21$105795b3o$105797bo$
105796bo22$105771b2o$105772b2o$105771bo21$105748b3o$105750bo$105749bo
20$105726b2o$105725bobo$105727bo21$105703b2o$105704b2o$105703bo20$
105681bo$105681b2o$105680bobo36$105643b3o$105645bo$105644bo20$105621b
2o$105620bobo$105622bo23$105596b3o$105598bo$105597bo20$105574bo$
105574b2o$105573bobo21$105551b2o$105552b2o$105551bo22$105527b3o$
105529bo$105528bo20$105505b2o$105504bobo$105506bo25$105478bo$105478b2o
$105477bobo21$105455b2o$105454bobo$105456bo21$105432bo$105432b2o$
105431bobo21$105409b2o$105408bobo$105410bo34$105373bo$105373b2o$
105372bobo52$105319b2o$105318bobo$105320bo25$105292b3o$105294bo$
105293bo20$105270b2o$105269bobo$105271bo21$105247b3o$105249bo$105248bo
20$105225bo$105225b2o$105224bobo21$105202b2o$105201bobo$105203bo42$
105158b3o$105160bo$105159bo20$105136b2o$105135bobo$105137bo38$105096b
3o$105098bo$105097bo20$105074b2o$105073bobo$105075bo21$105051b3o$
105053bo$105052bo20$105029b2o$105028bobo$105030bo21$105006b2o$105007b
2o$105006bo32$104972b2o$104971bobo$104973bo21$104949b3o$104951bo$
104950bo20$104927bo$104927b2o$104926bobo30$104895b2o$104894bobo$
104896bo21$104872b3o$104874bo$104873bo25$104845b2o$104846b2o$104845bo
21$104822b3o$104824bo$104823bo21$104799b2o$104798bobo$104800bo21$
104776b2o$104777b2o$104776bo21$104753b3o$104755bo$104754bo32$104719b3o
$104721bo$104720bo20$104697bo$104697b2o$104696bobo21$104674b2o$104675b
2o$104674bo21$104651b3o$104653bo$104652bo33$104616b3o$104618bo$104617b
o21$104593b2o$104592bobo$104594bo26$104565b2o$104564bobo$104566bo21$
104542b2o$104543b2o$104542bo30$104510b2o$104509bobo$104511bo21$104487b
3o$104489bo$104488bo20$104465b2o$104464bobo$104466bo21$104442b2o$
104441bobo$104443bo21$104419b3o$104421bo$104420bo23$104394b3o$104396bo
$104395bo20$104372b2o$104371bobo$104373bo27$104343b2o$104344b2o$
104343bo21$104320b3o$104322bo$104321bo20$104298bo$104298b2o$104297bobo
22$104274b3o$104276bo$104275bo20$104252bo$104252b2o$104251bobo26$
104224b3o$104226bo$104225bo20$104202bo$104202b2o$104201bobo22$104178b
3o$104180bo$104179bo20$104156bo$104156b2o$104155bobo30$104124b2o$
104123bobo$104125bo21$104101b2o$104102b2o$104101bo20$104079bo$104079b
2o$104078bobo27$104050b3o$104052bo$104051bo20$104028b2o$104027bobo$
104029bo21$104005b3o$104007bo$104006bo26$103977bo$103977b2o$103976bobo
21$103954b2o$103955b2o$103954bo35$103917b2o$103916bobo$103918bo21$
103894b3o$103896bo$103895bo22$103870b2o$103869bobo$103871bo21$103847b
3o$103849bo$103848bo20$103825bo$103825b2o$103824bobo24$103799b2o$
103798bobo$103800bo21$103776b3o$103778bo$103777bo20$103754b2o$103753bo
bo$103755bo32$103720b2o$103721b2o$103720bo31$103687bo$103687b2o$
103686bobo21$103664b2o$103665b2o$103664bo20$103642bo$103642b2o$103641b
obo22$103618b3o$103620bo$103619bo20$103596b2o$103595bobo$103597bo25$
103569bo$103569b2o$103568bobo21$103546b2o$103545bobo$103547bo22$
103522b3o$103524bo$103523bo20$103500bo$103500b2o$103499bobo21$103477b
2o$103476bobo$103478bo21$103454b2o$103453bobo$103455bo21$103431b3o$
103433bo$103432bo22$103407b2o$103408b2o$103407bo21$103384b3o$103386bo$
103385bo20$103362b2o$103361bobo$103363bo21$103339b2o$103340b2o$103339b
o20$103317bo$103317b2o$103316bobo39$103276b3o$103278bo$103277bo20$
103254bo$103254b2o$103253bobo21$103231b2o$103230bobo$103232bo21$
103208b2o$103209b2o$103208bo21$103185b3o$103187bo$103186bo20$103163bo$
103163b2o$103162bobo24$103137b2o$103136bobo$103138bo31$103104b3o$
103106bo$103105bo25$103077b2o$103078b2o$103077bo20$103055bo$103055b2o$
103054bobo22$103031b3o$103033bo$103032bo20$103009bo$103009b2o$103008bo
bo21$102986b2o$102985bobo$102987bo32$102952b2o$102953b2o$102952bo21$
102929b3o$102931bo$102930bo34$102893b3o$102895bo$102894bo20$102871b2o$
102870bobo$102872bo21$102848b3o$102850bo$102849bo28$102818bo$102818b2o
$102817bobo21$102795b2o$102794bobo$102796bo21$102772b3o$102774bo$
102773bo28$102742b3o$102744bo$102743bo20$102720b2o$102719bobo$102721bo
21$102697b2o$102698b2o$102697bo21$102674b3o$102676bo$102675bo20$
102652bo$102652b2o$102651bobo39$102611b2o$102610bobo$102612bo21$
102588b3o$102590bo$102589bo21$102565bo$102565b2o$102564bobo21$102542b
2o$102541bobo$102543bo32$102508b3o$102510bo$102509bo20$102486bo$
102486b2o$102485bobo26$102458b3o$102460bo$102459bo20$102436b2o$102435b
obo$102437bo21$102413bo$102413b2o$102412bobo21$102390b2o$102389bobo$
102391bo21$102367b2o$102368b2o$102367bo20$102345bo$102345b2o$102344bob
o21$102322b2o$102323b2o$102322bo23$102297b2o$102298b2o$102297bo20$
102275bo$102275b2o$102274bobo21$102252b2o$102253b2o$102252bo34$102216b
o$102216b2o$102215bobo22$102192bo$102192b2o$102191bobo21$102169b2o$
102170b2o$102169bo20$102147bo$102147b2o$102146bobo23$102122b2o$102121b
obo$102123bo39$102081bo$102081b2o$102080bobo21$102058b2o$102059b2o$
102058bo20$102036bo$102036b2o$102035bobo21$102013b2o$102012bobo$
102014bo21$101990b2o$101991b2o$101990bo20$101968bo$101968b2o$101967bob
o21$101945b2o$101944bobo$101946bo21$101922b3o$101924bo$101923bo20$
101900b2o$101899bobo$101901bo21$101877b2o$101878b2o$101877bo21$101854b
3o$101856bo$101855bo25$101827b2o$101828b2o$101827bo21$101804b3o$
101806bo$101805bo21$101781b2o$101782b2o$101781bo21$101758b3o$101760bo$
101759bo29$101727bo$101727b2o$101726bobo21$101704b2o$101703bobo$
101705bo21$101681b3o$101683bo$101682bo26$101653b2o$101654b2o$101653bo
20$101631bo$101631b2o$101630bobo21$101608b2o$101609b2o$101608bo27$
101579b3o$101581bo$101580bo20$101557b2o$101556bobo$101558bo35$101520bo
$101520b2o$101519bobo21$101497b2o$101498b2o$101497bo22$101473bo$
101473b2o$101472bobo21$101450b2o$101451b2o$101450bo21$101427b3o$
101429bo$101428bo23$101402bo$101402b2o$101401bobo21$101379b2o$101380b
2o$101379bo20$101357bo$101357b2o$101356bobo32$101323b2o$101322bobo$
101324bo32$101289b3o$101291bo$101290bo20$101267b2o$101266bobo$101268bo
21$101244b3o$101246bo$101245bo21$101221b2o$101222b2o$101221bo20$
101199bo$101199b2o$101198bobo26$101171b3o$101173bo$101172bo20$101149bo
$101149b2o$101148bobo22$101125b3o$101127bo$101126bo20$101103bo$101103b
2o$101102bobo42$101059b2o$101060b2o$101059bo20$101037bo$101037b2o$
101036bobo21$101014b2o$101013bobo$101015bo21$100991b2o$100992b2o$
100991bo20$100969bo$100969b2o$100968bobo21$100946b2o$100947b2o$100946b
o21$100923b3o$100925bo$100924bo28$100893b3o$100895bo$100894bo20$
100871bo$100871b2o$100870bobo21$100848b2o$100849b2o$100848bo37$100809b
2o$100808bobo$100810bo21$100786b3o$100788bo$100787bo23$100761b2o$
100762b2o$100761bo21$100738b3o$100740bo$100739bo20$100716bo$100716b2o$
100715bobo28$100686b2o$100685bobo$100687bo21$100663b3o$100665bo$
100664bo20$100641b2o$100640bobo$100642bo21$100618b3o$100620bo$100619bo
20$100596b2o$100595bobo$100597bo21$100573b3o$100575bo$100574bo20$
100551b2o$100550bobo$100552bo25$100524bo$100524b2o$100523bobo21$
100501b2o$100502b2o$100501bo21$100478b2o$100477bobo$100479bo21$100455b
2o$100456b2o$100455bo21$100432b3o$100434bo$100433bo31$100399bo$100399b
2o$100398bobo21$100376b2o$100375bobo$100377bo34$100340b2o$100339bobo$
100341bo21$100317b3o$100319bo$100318bo20$100295b2o$100294bobo$100296bo
29$100264b2o$100265b2o$100264bo21$100241b3o$100243bo$100242bo20$
100219b2o$100218bobo$100220bo28$100189b2o$100188bobo$100190bo21$
100166b3o$100168bo$100167bo20$100144bo$100144b2o$100143bobo21$100121b
2o$100120bobo$100122bo21$100098b2o$100099b2o$100098bo39$100057b3o$
100059bo$100058bo20$100035b2o$100034bobo$100036bo22$100011b2o$100012b
2o$100011bo21$99988b3o$99990bo$99989bo31$99955b2o$99954bobo$99956bo21$
99932b2o$99933b2o$99932bo25$99905b2o$99904bobo$99906bo21$99882b2o$
99883b2o$99882bo21$99859bo$99859b2o$99858bobo21$99836b2o$99835bobo$
99837bo21$99813b2o$99814b2o$99813bo32$99779b2o$99780b2o$99779bo21$
99756b3o$99758bo$99757bo20$99734b2o$99733bobo$99735bo21$99711b2o$
99712b2o$99711bo33$99676b3o$99678bo$99677bo22$99652b2o$99651bobo$
99653bo21$99629b3o$99631bo$99630bo21$99606b2o$99605bobo$99607bo21$
99583b3o$99585bo$99584bo21$99560bo$99560b2o$99559bobo21$99537b2o$
99538b2o$99537bo21$99514b3o$99516bo$99515bo27$99485b2o$99484bobo$
99486bo50$99433b2o$99434b2o$99433bo21$99410b2o$99409bobo$99411bo21$
99387b3o$99389bo$99388bo25$99360b2o$99361b2o$99360bo20$99338bo$99338b
2o$99337bobo22$99314b3o$99316bo$99315bo20$99292bo$99292b2o$99291bobo
21$99269b2o$99268bobo$99270bo23$99244b3o$99246bo$99245bo20$99222b2o$
99221bobo$99223bo21$99199b3o$99201bo$99200bo21$99176b2o$99177b2o$
99176bo21$99153b3o$99155bo$99154bo20$99131b2o$99130bobo$99132bo21$
99108b3o$99110bo$99109bo20$99086b2o$99085bobo$99087bo60$99024b3o$
99026bo$99025bo20$99002b2o$99001bobo$99003bo25$98975bo$98975b2o$98974b
obo21$98952b2o$98951bobo$98953bo21$98929b2o$98928bobo$98930bo21$98906b
3o$98908bo$98907bo20$98884b2o$98883bobo$98885bo21$98861b3o$98863bo$
98862bo21$98838b2o$98839b2o$98838bo21$98815b3o$98817bo$98816bo25$
98788b2o$98789b2o$98788bo21$98765b3o$98767bo$98766bo21$98742b2o$98741b
obo$98743bo21$98719b2o$98720b2o$98719bo21$98696b3o$98698bo$98697bo21$
98673b3o$98675bo$98674bo20$98651b2o$98650bobo$98652bo22$98627bo$98627b
2o$98626bobo21$98604b2o$98603bobo$98605bo21$98581b3o$98583bo$98582bo
20$98559bo$98559b2o$98558bobo21$98536b2o$98537b2o$98536bo38$98496b2o$
98495bobo$98497bo21$98473b2o$98474b2o$98473bo21$98450b3o$98452bo$
98451bo20$98428bo$98428b2o$98427bobo21$98405b2o$98404bobo$98406bo21$
98382b2o$98383b2o$98382bo24$98356b3o$98358bo$98357bo30$98324b2o$98323b
obo$98325bo25$98297bo$98297b2o$98296bobo21$98274b2o$98275b2o$98274bo
21$98251b2o$98250bobo$98252bo21$98228b2o$98229b2o$98228bo21$98205b3o$
98207bo$98206bo21$98182b3o$98184bo$98183bo20$98160b2o$98159bobo$98161b
o21$98137b3o$98139bo$98138bo20$98115bo$98115b2o$98114bobo21$98092b2o$
98093b2o$98092bo25$98065bo$98065b2o$98064bobo21$98042b2o$98043b2o$
98042bo20$98020bo$98020b2o$98019bobo21$97997b2o$97996bobo$97998bo29$
97966b2o$97965bobo$97967bo31$97933bo$97933b2o$97932bobo21$97910b2o$
97911b2o$97910bo21$97887b3o$97889bo$97888bo26$97859b2o$97860b2o$97859b
o20$97837bo$97837b2o$97836bobo21$97814b2o$97815b2o$97814bo21$97791b3o$
97793bo$97792bo25$97764b2o$97765b2o$97764bo21$97741b3o$97743bo$97742bo
21$97718b2o$97719b2o$97718bo21$97695b3o$97697bo$97696bo29$97664bo$
97664b2o$97663bobo21$97641b2o$97640bobo$97642bo21$97618b3o$97620bo$
97619bo26$97590b2o$97591b2o$97590bo20$97568bo$97568b2o$97567bobo21$
97545b2o$97546b2o$97545bo27$97516b3o$97518bo$97517bo20$97494b2o$97493b
obo$97495bo35$97457bo$97457b2o$97456bobo21$97434b2o$97435b2o$97434bo
22$97410bo$97410b2o$97409bobo21$97387b2o$97388b2o$97387bo21$97364b3o$
97366bo$97365bo23$97339bo$97339b2o$97338bobo21$97316b2o$97317b2o$
97316bo20$97294bo$97294b2o$97293bobo32$97260b2o$97259bobo$97261bo32$
97226b3o$97228bo$97227bo20$97204b2o$97203bobo$97205bo21$97181b3o$
97183bo$97182bo21$97158b2o$97159b2o$97158bo21$97135b3o$97137bo$97136bo
25$97108b2o$97109b2o$97108bo21$97085b3o$97087bo$97086bo21$97062b2o$
97061bobo$97063bo21$97039b2o$97040b2o$97039bo21$97016b3o$97018bo$
97017bo42$96972bo$96972b2o$96971bobo21$96949b2o$96950b2o$96949bo21$
96926b3o$96928bo$96927bo21$96903b2o$96902bobo$96904bo21$96880b2o$
96881b2o$96880bo23$96855bo$96855b2o$96854bobo21$96832b2o$96831bobo$
96833bo41$96789b2o$96790b2o$96789bo21$96766b3o$96768bo$96767bo25$
96739b2o$96738bobo$96740bo21$96716b2o$96717b2o$96716bo37$96677b2o$
96678b2o$96677bo20$96655bo$96655b2o$96654bobo28$96625b2o$96624bobo$
96626bo21$96602b3o$96604bo$96603bo20$96580b2o$96579bobo$96581bo21$
96557b3o$96559bo$96558bo20$96535b2o$96534bobo$96536bo21$96512b2o$
96513b2o$96512bo20$96490bo$96490b2o$96489bobo26$96462b3o$96464bo$
96463bo20$96440bo$96440b2o$96439bobo22$96416b3o$96418bo$96417bo20$
96394bo$96394b2o$96393bobo23$96369b3o$96371bo$96370bo20$96347b2o$
96346bobo$96348bo21$96324b3o$96326bo$96325bo28$96294b2o$96293bobo$
96295bo21$96271b2o$96272b2o$96271bo31$96238b2o$96239b2o$96238bo20$
96216bo$96216b2o$96215bobo23$96191b2o$96192b2o$96191bo21$96168b3o$
96170bo$96169bo20$96146bo$96146b2o$96145bobo25$96119b3o$96121bo$96120b
o20$96097bo$96097b2o$96096bobo21$96074b2o$96075b2o$96074bo27$96045b2o$
96046b2o$96045bo20$96023bo$96023b2o$96022bobo26$95995bo$95995b2o$
95994bobo21$95972b2o$95971bobo$95973bo25$95945bo$95945b2o$95944bobo21$
95922b2o$95921bobo$95923bo21$95899bo$95899b2o$95898bobo21$95876b2o$
95875bobo$95877bo34$95840bo$95840b2o$95839bobo52$95786b2o$95785bobo$
95787bo25$95759b3o$95761bo$95760bo20$95737b2o$95736bobo$95738bo21$
95714b3o$95716bo$95715bo20$95692bo$95692b2o$95691bobo21$95669b2o$
95668bobo$95670bo42$95625b3o$95627bo$95626bo20$95603b2o$95602bobo$
95604bo38$95563b3o$95565bo$95564bo20$95541b2o$95540bobo$95542bo21$
95518b3o$95520bo$95519bo20$95496b2o$95495bobo$95497bo21$95473b2o$
95474b2o$95473bo32$95439b2o$95438bobo$95440bo21$95416b3o$95418bo$
95417bo20$95394bo$95394b2o$95393bobo30$95362b2o$95361bobo$95363bo21$
95339b3o$95341bo$95340bo25$95312b2o$95313b2o$95312bo20$95290bo$95290b
2o$95289bobo22$95266b3o$95268bo$95267bo20$95244bo$95244b2o$95243bobo
21$95221b2o$95220bobo$95222bo32$95187b2o$95188b2o$95187bo21$95164b3o$
95166bo$95165bo34$95128b3o$95130bo$95129bo20$95106b2o$95105bobo$95107b
o21$95083b3o$95085bo$95084bo28$95053bo$95053b2o$95052bobo21$95030b2o$
95029bobo$95031bo21$95007b3o$95009bo$95008bo28$94977b3o$94979bo$94978b
o20$94955b2o$94954bobo$94956bo21$94932b2o$94933b2o$94932bo21$94909b3o$
94911bo$94910bo20$94887bo$94887b2o$94886bobo39$94846b2o$94845bobo$
94847bo21$94823b3o$94825bo$94824bo21$94800bo$94800b2o$94799bobo21$
94777b2o$94776bobo$94778bo32$94743b3o$94745bo$94744bo20$94721b2o$
94720bobo$94722bo25$94694bo$94694b2o$94693bobo21$94671b2o$94670bobo$
94672bo21$94648bo$94648b2o$94647bobo21$94625b2o$94626b2o$94625bo41$
94582b2o$94581bobo$94583bo21$94559b3o$94561bo$94560bo20$94537b2o$
94536bobo$94538bo21$94514b3o$94516bo$94515bo20$94492b2o$94491bobo$
94493bo21$94469b3o$94471bo$94470bo33$94434b2o$94435b2o$94434bo20$
94412bo$94412b2o$94411bobo21$94389b2o$94390b2o$94389bo22$94365b2o$
94366b2o$94365bo21$94342b3o$94344bo$94343bo31$94309b3o$94311bo$94310bo
20$94287b2o$94286bobo$94288bo23$94262b2o$94261bobo$94263bo21$94239b3o$
94241bo$94240bo20$94217bo$94217b2o$94216bobo28$94187b2o$94186bobo$
94188bo21$94164b3o$94166bo$94165bo20$94142b2o$94141bobo$94143bo21$
94119b3o$94121bo$94120bo25$94092b2o$94093b2o$94092bo21$94069b3o$94071b
o$94070bo21$94046b2o$94045bobo$94047bo21$94023b2o$94024b2o$94023bo21$
94000b3o$94002bo$94001bo21$93977b3o$93979bo$93978bo20$93955b2o$93954bo
bo$93956bo22$93931bo$93931b2o$93930bobo21$93908b2o$93907bobo$93909bo
21$93885b3o$93887bo$93886bo20$93863bo$93863b2o$93862bobo21$93840b2o$
93841b2o$93840bo38$93800b2o$93799bobo$93801bo21$93777b2o$93778b2o$
93777bo21$93754b3o$93756bo$93755bo20$93732bo$93732b2o$93731bobo21$
93709b2o$93708bobo$93710bo21$93686b2o$93687b2o$93686bo24$93660b3o$
93662bo$93661bo30$93628b2o$93627bobo$93629bo25$93601bo$93601b2o$93600b
obo21$93578b2o$93577bobo$93579bo21$93555bo$93555b2o$93554bobo21$93532b
2o$93531bobo$93533bo37$93493b2o$93492bobo$93494bo21$93470b2o$93471b2o$
93470bo21$93447b3o$93449bo$93448bo29$93416b2o$93415bobo$93417bo21$
93393b3o$93395bo$93394bo20$93371bo$93371b2o$93370bobo21$93348b2o$
93347bobo$93349bo21$93325b2o$93326b2o$93325bo35$93288b3o$93290bo$
93289bo20$93266b2o$93265bobo$93267bo26$93238bo$93238b2o$93237bobo21$
93215b2o$93216b2o$93215bo23$93190bo$93190b2o$93189bobo21$93167b2o$
93168b2o$93167bo21$93144b3o$93146bo$93145bo20$93122bo$93122b2o$93121bo
bo26$93094b3o$93096bo$93095bo20$93072b2o$93071bobo$93073bo21$93049bo$
93049b2o$93048bobo21$93026b2o$93025bobo$93027bo21$93003b2o$93004b2o$
93003bo33$92968bo$92968b2o$92967bobo21$92945b2o$92946b2o$92945bo25$
92918b2o$92917bobo$92919bo21$92895b2o$92896b2o$92895bo21$92872b2o$
92873b2o$92872bo20$92850bo$92850b2o$92849bobo21$92827bo$92827b2o$
92826bobo21$92804b2o$92805b2o$92804bo27$92775bo$92775b2o$92774bobo21$
92752b2o$92751bobo$92753bo21$92729b2o$92730b2o$92729bo20$92707bo$
92707b2o$92706bobo21$92684b2o$92685b2o$92684bo28$92654b3o$92656bo$
92655bo20$92632b2o$92631bobo$92633bo25$92605bo$92605b2o$92604bobo21$
92582b2o$92581bobo$92583bo22$92558b3o$92560bo$92559bo20$92536bo$92536b
2o$92535bobo21$92513b2o$92512bobo$92514bo21$92490b2o$92489bobo$92491bo
21$92467b3o$92469bo$92468bo22$92443b2o$92444b2o$92443bo21$92420b3o$
92422bo$92421bo20$92398b2o$92397bobo$92399bo21$92375b2o$92376b2o$
92375bo20$92353bo$92353b2o$92352bobo39$92312b3o$92314bo$92313bo20$
92290bo$92290b2o$92289bobo21$92267b2o$92266bobo$92268bo21$92244b2o$
92245b2o$92244bo21$92221b3o$92223bo$92222bo20$92199bo$92199b2o$92198bo
bo24$92173b2o$92172bobo$92174bo31$92140b3o$92142bo$92141bo25$92113b2o$
92114b2o$92113bo20$92091bo$92091b2o$92090bobo22$92067b3o$92069bo$
92068bo20$92045bo$92045b2o$92044bobo21$92022b2o$92021bobo$92023bo21$
91999b3o$92001bo$92000bo20$91977b2o$91976bobo$91978bo23$91952b2o$
91951bobo$91953bo21$91929b3o$91931bo$91930bo20$91907b2o$91906bobo$
91908bo35$91870b3o$91872bo$91871bo22$91846b3o$91848bo$91847bo20$91824b
2o$91823bobo$91825bo21$91801b3o$91803bo$91802bo22$91777bo$91777b2o$
91776bobo40$91735b3o$91737bo$91736bo20$91713b2o$91712bobo$91714bo21$
91690b3o$91692bo$91691bo20$91668bo$91668b2o$91667bobo21$91645b2o$
91644bobo$91646bo21$91622b3o$91624bo$91623bo20$91600bo$91600b2o$91599b
obo21$91577b2o$91578b2o$91577bo20$91555bo$91555b2o$91554bobo21$91532b
2o$91531bobo$91533bo21$91509b2o$91510b2o$91509bo25$91482b2o$91481bobo$
91483bo21$91459b2o$91460b2o$91459bo21$91436bo$91436b2o$91435bobo21$
91413b2o$91412bobo$91414bo21$91390b2o$91391b2o$91390bo21$91367b2o$
91368b2o$91367bo20$91345bo$91345b2o$91344bobo23$91320b3o$91322bo$
91321bo20$91298bo$91298b2o$91297bobo21$91275b2o$91276b2o$91275bo21$
91252b3o$91254bo$91253bo20$91230b2o$91229bobo$91231bo35$91193bo$91193b
2o$91192bobo21$91170b2o$91171b2o$91170bo22$91146bo$91146b2o$91145bobo
21$91123b2o$91122bobo$91124bo21$91100b3o$91102bo$91101bo21$91077bo$
91077b2o$91076bobo21$91054b2o$91055b2o$91054bo25$91027b2o$91026bobo$
91028bo21$91004b2o$91005b2o$91004bo21$90981bo$90981b2o$90980bobo21$
90958b2o$90957bobo$90959bo21$90935b2o$90936b2o$90935bo22$90911b2o$
90912b2o$90911bo20$90889bo$90889b2o$90888bobo32$90855b2o$90854bobo$
90856bo21$90832b3o$90834bo$90833bo25$90805b2o$90806b2o$90805bo21$
90782b3o$90784bo$90783bo21$90759b2o$90758bobo$90760bo21$90736b2o$
90737b2o$90736bo21$90713b3o$90715bo$90714bo24$90687b2o$90688b2o$90687b
o21$90664b3o$90666bo$90665bo20$90642b2o$90641bobo$90643bo21$90619b2o$
90620b2o$90619bo22$90595bo$90595b2o$90594bobo21$90572b2o$90571bobo$
90573bo21$90549b3o$90551bo$90550bo29$90518bo$90518b2o$90517bobo41$
90475bo$90475b2o$90474bobo21$90452bo$90452b2o$90451bobo21$90429b2o$
90428bobo$90430bo25$90402bo$90402b2o$90401bobo21$90379b2o$90378bobo$
90380bo22$90355b3o$90357bo$90356bo20$90333bo$90333b2o$90332bobo21$
90310b2o$90309bobo$90311bo32$90276b2o$90275bobo$90277bo21$90253b2o$
90254b2o$90253bo20$90231bo$90231b2o$90230bobo21$90208b2o$90207bobo$
90209bo40$90166b2o$90165bobo$90167bo21$90143b3o$90145bo$90144bo20$
90121b2o$90120bobo$90122bo22$90097bo$90097b2o$90096bobo21$90074b2o$
90073bobo$90075bo21$90051b2o$90052b2o$90051bo21$90028b3o$90030bo$
90029bo20$90006b2o$90005bobo$90007bo27$89977b2o$89976bobo$89978bo21$
89954b3o$89956bo$89955bo20$89932b2o$89931bobo$89933bo21$89909b3o$
89911bo$89910bo20$89887b2o$89886bobo$89888bo21$89864b3o$89866bo$89865b
o20$89842b2o$89841bobo$89843bo25$89815bo$89815b2o$89814bobo21$89792b2o
$89791bobo$89793bo22$89768b3o$89770bo$89769bo20$89746bo$89746b2o$
89745bobo21$89723b2o$89722bobo$89724bo22$89699b2o$89698bobo$89700bo21$
89676b3o$89678bo$89677bo22$89652b2o$89653b2o$89652bo21$89629b3o$89631b
o$89630bo20$89607bo$89607b2o$89606bobo31$89574b2o$89575b2o$89574bo21$
89551bo$89551b2o$89550bobo21$89528b2o$89529b2o$89528bo24$89502b2o$
89501bobo$89503bo21$89479b3o$89481bo$89480bo21$89456bo$89456b2o$89455b
obo34$89420b2o$89419bobo$89421bo23$89395b2o$89396b2o$89395bo25$89368b
2o$89367bobo$89369bo21$89345b2o$89346b2o$89345bo21$89322b2o$89321bobo$
89323bo21$89299b3o$89301bo$89300bo36$89261bo$89261b2o$89260bobo25$
89234b2o$89235b2o$89234bo20$89212bo$89212b2o$89211bobo21$89189b2o$
89190b2o$89189bo21$89166b2o$89167b2o$89166bo21$89143b3o$89145bo$89144b
o25$89116b2o$89117b2o$89116bo20$89094bo$89094b2o$89093bobo22$89070b3o$
89072bo$89071bo20$89048bo$89048b2o$89047bobo21$89025b2o$89026b2o$
89025bo23$89000b2o$89001b2o$89000bo29$88969b2o$88970b2o$88969bo20$
88947bo$88947b2o$88946bobo26$88919b3o$88921bo$88920bo20$88897b2o$
88896bobo$88898bo21$88874bo$88874b2o$88873bobo21$88851b2o$88850bobo$
88852bo21$88828b3o$88830bo$88829bo21$88805bo$88805b2o$88804bobo21$
88782b2o$88781bobo$88783bo21$88759b2o$88760b2o$88759bo32$88725bo$
88725b2o$88724bobo38$88685b3o$88687bo$88686bo22$88661b3o$88663bo$
88662bo20$88639b2o$88638bobo$88640bo28$88609b2o$88608bobo$88610bo21$
88586b2o$88587b2o$88586bo22$88562b2o$88561bobo$88563bo25$88535b2o$
88536b2o$88535bo20$88513bo$88513b2o$88512bobo21$88490b2o$88491b2o$
88490bo21$88467b2o$88466bobo$88468bo45$88420b2o$88419bobo$88421bo25$
88393bo$88393b2o$88392bobo21$88370b2o$88369bobo$88371bo22$88346b3o$
88348bo$88347bo20$88324bo$88324b2o$88323bobo21$88301b2o$88300bobo$
88302bo29$88270b2o$88269bobo$88271bo21$88247b2o$88248b2o$88247bo24$
88221b2o$88220bobo$88222bo21$88198b3o$88200bo$88199bo24$88172b2o$
88171bobo$88173bo26$88144b2o$88143bobo$88145bo25$88117b2o$88116bobo$
88118bo21$88094b2o$88095b2o$88094bo25$88067b2o$88066bobo$88068bo21$
88044b3o$88046bo$88045bo21$88021b2o$88022b2o$88021bo21$87998b3o$88000b
o$87999bo20$87976b2o$87975bobo$87977bo22$87952b2o$87953b2o$87952bo21$
87929b3o$87931bo$87930bo20$87907bo$87907b2o$87906bobo26$87879b3o$
87881bo$87880bo20$87857bo$87857b2o$87856bobo21$87834b2o$87835b2o$
87834bo20$87812bo$87812b2o$87811bobo21$87789b2o$87788bobo$87790bo23$
87764b2o$87765b2o$87764bo20$87742bo$87742b2o$87741bobo23$87717b2o$
87718b2o$87717bo20$87695bo$87695b2o$87694bobo21$87672b2o$87673b2o$
87672bo27$87643bo$87643b2o$87642bobo21$87620b2o$87619bobo$87621bo21$
87597b3o$87599bo$87598bo20$87575b2o$87574bobo$87576bo21$87552b3o$
87554bo$87553bo20$87530b2o$87529bobo$87531bo21$87507b3o$87509bo$87508b
o25$87480b2o$87481b2o$87480bo20$87458bo$87458b2o$87457bobo22$87434b2o$
87433bobo$87435bo59$87373bo$87373b2o$87372bobo21$87350b2o$87351b2o$
87350bo29$87319bo$87319b2o$87318bobo50$87267bo$87267b2o$87266bobo30$
87235bo$87235b2o$87234bobo21$87212b2o$87213b2o$87212bo22$87188b2o$
87189b2o$87188bo21$87165b3o$87167bo$87166bo20$87143b2o$87142bobo$
87144bo21$87120b3o$87122bo$87121bo20$87098bo$87098b2o$87097bobo21$
87075b2o$87074bobo$87076bo21$87052b2o$87053b2o$87052bo21$87029b3o$
87031bo$87030bo23$87004b3o$87006bo$87005bo20$86982b2o$86981bobo$86983b
o21$86959b3o$86961bo$86960bo20$86937bo$86937b2o$86936bobo26$86909b3o$
86911bo$86910bo20$86887b2o$86886bobo$86888bo21$86864bo$86864b2o$86863b
obo21$86841b2o$86840bobo$86842bo21$86818b3o$86820bo$86819bo21$86795bo$
86795b2o$86794bobo21$86772b2o$86771bobo$86773bo21$86749b2o$86750b2o$
86749bo32$86715bo$86715b2o$86714bobo38$86675b3o$86677bo$86676bo22$
86651b3o$86653bo$86652bo20$86629b2o$86628bobo$86630bo28$86599b2o$
86598bobo$86600bo21$86576b2o$86577b2o$86576bo22$86552b2o$86551bobo$
86553bo25$86525b2o$86526b2o$86525bo20$86503bo$86503b2o$86502bobo21$
86480b2o$86481b2o$86480bo21$86457b2o$86456bobo$86458bo45$86410b2o$
86409bobo$86411bo25$86383bo$86383b2o$86382bobo21$86360b2o$86359bobo$
86361bo21$86337bo$86337b2o$86336bobo21$86314b2o$86315b2o$86314bo29$
86283b3o$86285bo$86284bo20$86261b2o$86260bobo$86262bo24$86235bo$86235b
2o$86234bobo21$86212b2o$86213b2o$86212bo20$86190bo$86190b2o$86189bobo
26$86162b2o$86161bobo$86163bo21$86139b3o$86141bo$86140bo26$86111b3o$
86113bo$86112bo20$86089bo$86089b2o$86088bobo21$86066b2o$86067b2o$
86066bo22$86042bo$86042b2o$86041bobo21$86019b2o$86020b2o$86019bo22$
85995b2o$85996b2o$85995bo24$85969b2o$85970b2o$85969bo21$85946b3o$
85948bo$85947bo20$85924bo$85924b2o$85923bobo21$85901b2o$85902b2o$
85901bo25$85874b3o$85876bo$85875bo43$85829b2o$85830b2o$85829bo25$
85802b2o$85801bobo$85803bo21$85779b3o$85781bo$85780bo21$85756b2o$
85757b2o$85756bo21$85733b3o$85735bo$85734bo20$85711bo$85711b2o$85710bo
bo23$85686b2o$85687b2o$85686bo20$85664bo$85664b2o$85663bobo21$85641b2o
$85642b2o$85641bo21$85618b2o$85617bobo$85619bo21$85595b2o$85596b2o$
85595bo20$85573bo$85573b2o$85572bobo21$85550b2o$85551b2o$85550bo20$
85528bo$85528b2o$85527bobo60$85466b2o$85467b2o$85466bo20$85444bo$
85444b2o$85443bobo26$85416b3o$85418bo$85417bo20$85394bo$85394b2o$
85393bobo21$85371bo$85371b2o$85370bobo21$85348b2o$85349b2o$85348bo20$
85326bo$85326b2o$85325bobo21$85303b2o$85304b2o$85303bo21$85280b2o$
85279bobo$85281bo21$85257b3o$85259bo$85258bo25$85230b2o$85231b2o$
85230bo20$85208bo$85208b2o$85207bobo22$85184b2o$85183bobo$85185bo59$
85123bo$85123b2o$85122bobo21$85100b2o$85101b2o$85100bo29$85069bo$
85069b2o$85068bobo50$85017bo$85017b2o$85016bobo30$84985bo$84985b2o$
84984bobo21$84962b2o$84963b2o$84962bo22$84938b2o$84939b2o$84938bo21$
84915b3o$84917bo$84916bo20$84893b2o$84892bobo$84894bo21$84870b3o$
84872bo$84871bo20$84848bo$84848b2o$84847bobo21$84825b2o$84824bobo$
84826bo21$84802b2o$84803b2o$84802bo21$84779b3o$84781bo$84780bo23$
84754b3o$84756bo$84755bo20$84732b2o$84731bobo$84733bo21$84709b3o$
84711bo$84710bo20$84687b2o$84686bobo$84688bo25$84660bo$84660b2o$84659b
obo21$84637b2o$84638b2o$84637bo21$84614b2o$84613bobo$84615bo21$84591b
2o$84592b2o$84591bo20$84569bo$84569b2o$84568bobo23$84544bo$84544b2o$
84543bobo31$84511b2o$84510bobo$84512bo23$84486bo$84486b2o$84485bobo21$
84463b2o$84464b2o$84463bo26$84435b2o$84434bobo$84436bo22$84411b2o$
84412b2o$84411bo25$84384b2o$84383bobo$84385bo21$84361b3o$84363bo$
84362bo21$84338b2o$84339b2o$84338bo21$84315b3o$84317bo$84316bo20$
84293bo$84293b2o$84292bobo21$84270b2o$84271b2o$84270bo20$84248bo$
84248b2o$84247bobo21$84225b2o$84224bobo$84226bo21$84202b2o$84203b2o$
84202bo20$84180bo$84180b2o$84179bobo21$84157b2o$84158b2o$84157bo21$
84134b3o$84136bo$84135bo20$84112b2o$84111bobo$84113bo21$84089b3o$
84091bo$84090bo21$84066b2o$84065bobo$84067bo21$84043b3o$84045bo$84044b
o20$84021b2o$84020bobo$84022bo25$83994bo$83994b2o$83993bobo21$83971b2o
$83970bobo$83972bo21$83948bo$83948b2o$83947bobo21$83925b2o$83924bobo$
83926bo22$83901bo$83901b2o$83900bobo21$83878b2o$83879b2o$83878bo20$
83856bo$83856b2o$83855bobo29$83825b2o$83826b2o$83825bo21$83802b3o$
83804bo$83803bo31$83769b3o$83771bo$83770bo20$83747b2o$83746bobo$83748b
o23$83722b3o$83724bo$83723bo20$83700bo$83700b2o$83699bobo21$83677b2o$
83676bobo$83678bo24$83651bo$83651b2o$83650bobo21$83628b2o$83627bobo$
83629bo21$83605b3o$83607bo$83606bo27$83576b3o$83578bo$83577bo20$83554b
2o$83553bobo$83555bo26$83526b2o$83525bobo$83527bo21$83503b3o$83505bo$
83504bo25$83476b2o$83477b2o$83476bo21$83453b3o$83455bo$83454bo21$
83430b2o$83429bobo$83431bo21$83407b2o$83408b2o$83407bo21$83384b3o$
83386bo$83385bo29$83353b3o$83355bo$83354bo20$83331bo$83331b2o$83330bob
o25$83304b3o$83306bo$83305bo20$83282b2o$83281bobo$83283bo25$83255b3o$
83257bo$83256bo26$83227b3o$83229bo$83228bo25$83200b3o$83202bo$83201bo
20$83178bo$83178b2o$83177bobo26$83150b3o$83152bo$83151bo20$83128b2o$
83127bobo$83129bo21$83105bo$83105b2o$83104bobo21$83082b2o$83081bobo$
83083bo21$83059b2o$83060b2o$83059bo22$83035bo$83035b2o$83034bobo21$
83012b2o$83013b2o$83012bo20$82990bo$82990b2o$82989bobo22$82966b3o$
82968bo$82967bo20$82944bo$82944b2o$82943bobo21$82921b2o$82922b2o$
82921bo20$82899bo$82899b2o$82898bobo21$82876b2o$82877b2o$82876bo59$
82815bo$82815b2o$82814bobo21$82792b2o$82793b2o$82792bo25$82765b2o$
82764bobo$82766bo21$82742b2o$82743b2o$82742bo21$82719b2o$82720b2o$
82719bo20$82697bo$82697b2o$82696bobo21$82674b2o$82675b2o$82674bo20$
82652bo$82652b2o$82651bobo22$82628b3o$82630bo$82629bo20$82606bo$82606b
2o$82605bobo26$82578b3o$82580bo$82579bo20$82556bo$82556b2o$82555bobo
22$82532b3o$82534bo$82533bo20$82510bo$82510b2o$82509bobo21$82487bo$
82487b2o$82486bobo21$82464b2o$82465b2o$82464bo22$82440b2o$82439bobo$
82441bo21$82417b2o$82418b2o$82417bo27$82388b2o$82389b2o$82388bo21$
82365b3o$82367bo$82366bo24$82339b2o$82338bobo$82340bo21$82316b3o$
82318bo$82317bo20$82294b2o$82293bobo$82295bo23$82269b2o$82270b2o$
82269bo21$82246b3o$82248bo$82247bo34$82210b2o$82209bobo$82211bo22$
82186b2o$82185bobo$82187bo21$82163b3o$82165bo$82164bo20$82141b2o$
82140bobo$82142bo36$82103bo$82103b2o$82102bobo21$82080b2o$82079bobo$
82081bo21$82057b2o$82056bobo$82058bo21$82034b3o$82036bo$82035bo26$
82006b2o$82007b2o$82006bo22$81982b3o$81984bo$81983bo20$81960bo$81960b
2o$81959bobo26$81932b3o$81934bo$81933bo20$81910bo$81910b2o$81909bobo
22$81886b2o$81887b2o$81886bo21$81863b3o$81865bo$81864bo20$81841bo$
81841b2o$81840bobo21$81818bo$81818b2o$81817bobo21$81795b2o$81796b2o$
81795bo22$81771b2o$81770bobo$81772bo21$81748b2o$81749b2o$81748bo20$
81726bo$81726b2o$81725bobo21$81703b2o$81702bobo$81704bo21$81680b3o$
81682bo$81681bo38$81640b2o$81641b2o$81640bo21$81617b3o$81619bo$81618bo
20$81595bo$81595b2o$81594bobo21$81572b2o$81571bobo$81573bo21$81549b2o$
81550b2o$81549bo21$81526b3o$81528bo$81527bo23$81501bo$81501b2o$81500bo
bo31$81468b2o$81469b2o$81468bo25$81441b2o$81440bobo$81442bo21$81418b3o
$81420bo$81419bo21$81395b2o$81396b2o$81395bo21$81372b3o$81374bo$81373b
o20$81350bo$81350b2o$81349bobo34$81314b2o$81315b2o$81314bo20$81292bo$
81292b2o$81291bobo26$81264b3o$81266bo$81265bo20$81242bo$81242b2o$
81241bobo21$81219bo$81219b2o$81218bobo21$81196b2o$81197b2o$81196bo21$
81173b2o$81174b2o$81173bo20$81151bo$81151b2o$81150bobo28$81121b2o$
81122b2o$81121bo21$81098b3o$81100bo$81099bo20$81076bo$81076b2o$81075bo
bo21$81053b2o$81054b2o$81053bo20$81031bo$81031b2o$81030bobo28$81001b2o
$81000bobo$81002bo21$80978b3o$80980bo$80979bo25$80951b2o$80952b2o$
80951bo21$80928b3o$80930bo$80929bo21$80905b2o$80904bobo$80906bo21$
80882b2o$80883b2o$80882bo21$80859b3o$80861bo$80860bo21$80836b3o$80838b
o$80837bo20$80814b2o$80813bobo$80815bo22$80790bo$80790b2o$80789bobo21$
80767b2o$80766bobo$80768bo21$80744b3o$80746bo$80745bo20$80722bo$80722b
2o$80721bobo21$80699b2o$80700b2o$80699bo38$80659b2o$80658bobo$80660bo
21$80636b2o$80637b2o$80636bo21$80613b3o$80615bo$80614bo20$80591bo$
80591b2o$80590bobo21$80568b2o$80567bobo$80569bo21$80545b2o$80546b2o$
80545bo24$80519b3o$80521bo$80520bo30$80487b2o$80486bobo$80488bo25$
80460bo$80460b2o$80459bobo21$80437b2o$80436bobo$80438bo22$80413b3o$
80415bo$80414bo20$80391bo$80391b2o$80390bobo21$80368b2o$80367bobo$
80369bo32$80334b2o$80333bobo$80335bo21$80311b2o$80312b2o$80311bo20$
80289bo$80289b2o$80288bobo21$80266b2o$80265bobo$80267bo33$80231b2o$
80230bobo$80232bo22$80207b3o$80209bo$80208bo26$80179b3o$80181bo$80180b
o20$80157bo$80157b2o$80156bobo31$80124b3o$80126bo$80125bo20$80102b2o$
80101bobo$80103bo21$80079b3o$80081bo$80080bo21$80056b3o$80058bo$80057b
o20$80034b2o$80033bobo$80035bo23$80009b2o$80008bobo$80010bo21$79986b3o
$79988bo$79987bo26$79958bo$79958b2o$79957bobo21$79935b2o$79934bobo$
79936bo21$79912b2o$79913b2o$79912bo21$79889b2o$79888bobo$79890bo21$
79866b2o$79867b2o$79866bo25$79839b2o$79838bobo$79840bo21$79816b2o$
79817b2o$79816bo21$79793b2o$79792bobo$79794bo21$79770b2o$79771b2o$
79770bo26$79742b2o$79741bobo$79743bo21$79719b2o$79720b2o$79719bo31$
79686b2o$79687b2o$79686bo21$79663b3o$79665bo$79664bo20$79641bo$79641b
2o$79640bobo32$79607b3o$79609bo$79608bo20$79585bo$79585b2o$79584bobo
21$79562b2o$79563b2o$79562bo22$79538bo$79538b2o$79537bobo21$79515b2o$
79514bobo$79516bo21$79492b3o$79494bo$79493bo30$79460bo$79460b2o$79459b
obo21$79437b2o$79438b2o$79437bo26$79409b2o$79410b2o$79409bo31$79376b2o
$79377b2o$79376bo20$79354bo$79354b2o$79353bobo21$79331b2o$79332b2o$
79331bo25$79304b2o$79303bobo$79305bo21$79281b2o$79282b2o$79281bo21$
79258b2o$79257bobo$79259bo21$79235b2o$79236b2o$79235bo22$79211b2o$
79210bobo$79212bo21$79188b3o$79190bo$79189bo20$79166b2o$79165bobo$
79167bo29$79135b3o$79137bo$79136bo20$79113bo$79113b2o$79112bobo31$
79080bo$79080b2o$79079bobo21$79057b2o$79058b2o$79057bo22$79033bo$
79033b2o$79032bobo21$79010b2o$79009bobo$79011bo21$78987b2o$78988b2o$
78987bo24$78961b2o$78960bobo$78962bo21$78938b2o$78939b2o$78938bo20$
78916bo$78916b2o$78915bobo27$78887bo$78887b2o$78886bobo21$78864b2o$
78865b2o$78864bo26$78836b2o$78837b2o$78836bo20$78814bo$78814b2o$78813b
obo26$78786b3o$78788bo$78787bo20$78764bo$78764b2o$78763bobo22$78740b3o
$78742bo$78741bo20$78718b2o$78717bobo$78719bo29$78687b2o$78688b2o$
78687bo20$78665bo$78665b2o$78664bobo25$78638b3o$78640bo$78639bo20$
78616b2o$78615bobo$78617bo21$78593b3o$78595bo$78594bo25$78566bo$78566b
2o$78565bobo21$78543b2o$78544b2o$78543bo26$78515b2o$78516b2o$78515bo
21$78492b3o$78494bo$78493bo20$78470b2o$78469bobo$78471bo23$78445b3o$
78447bo$78446bo20$78423b2o$78422bobo$78424bo22$78399b2o$78398bobo$
78400bo24$78373b2o$78372bobo$78374bo21$78350b2o$78351b2o$78350bo21$
78327b3o$78329bo$78328bo20$78305b2o$78304bobo$78306bo25$78278b2o$
78279b2o$78278bo43$78233b2o$78232bobo$78234bo25$78206bo$78206b2o$
78205bobo21$78183b2o$78182bobo$78184bo21$78160bo$78160b2o$78159bobo21$
78137b2o$78136bobo$78138bo34$78101bo$78101b2o$78100bobo52$78047b2o$
78046bobo$78048bo25$78020b3o$78022bo$78021bo20$77998b2o$77997bobo$
77999bo21$77975b3o$77977bo$77976bo20$77953bo$77953b2o$77952bobo21$
77930b2o$77929bobo$77931bo42$77886b3o$77888bo$77887bo20$77864b2o$
77863bobo$77865bo38$77824b3o$77826bo$77825bo20$77802b2o$77801bobo$
77803bo21$77779b3o$77781bo$77780bo20$77757b2o$77756bobo$77758bo21$
77734b2o$77735b2o$77734bo32$77700b2o$77699bobo$77701bo21$77677b3o$
77679bo$77678bo20$77655bo$77655b2o$77654bobo30$77623b2o$77622bobo$
77624bo21$77600b3o$77602bo$77601bo25$77573b2o$77574b2o$77573bo21$
77550b3o$77552bo$77551bo21$77527b2o$77528b2o$77527bo20$77505bo$77505b
2o$77504bobo29$77474b2o$77473bobo$77475bo21$77451b3o$77453bo$77452bo
24$77425b2o$77426b2o$77425bo20$77403bo$77403b2o$77402bobo21$77380b2o$
77381b2o$77380bo26$77352b3o$77354bo$77353bo20$77330b2o$77329bobo$
77331bo26$77302b2o$77301bobo$77303bo21$77279b2o$77280b2o$77279bo20$
77257bo$77257b2o$77256bobo23$77232b2o$77233b2o$77232bo20$77210bo$
77210b2o$77209bobo22$77186bo$77186b2o$77185bobo24$77160bo$77160b2o$
77159bobo21$77137b2o$77136bobo$77138bo21$77114b2o$77115b2o$77114bo20$
77092bo$77092b2o$77091bobo25$77065b2o$77064bobo$77066bo43$77020bo$
77020b2o$77019bobo26$76992b3o$76994bo$76993bo20$76970bo$76970b2o$
76969bobo22$76946b2o$76947b2o$76946bo21$76923b3o$76925bo$76924bo20$
76901b2o$76900bobo$76902bo22$76877b2o$76876bobo$76878bo21$76854b3o$
76856bo$76855bo20$76832bo$76832b2o$76831bobo35$76795b2o$76796b2o$
76795bo58$76735b2o$76736b2o$76735bo25$76708b2o$76707bobo$76709bo21$
76685b2o$76686b2o$76685bo21$76662bo$76662b2o$76661bobo21$76639b2o$
76638bobo$76640bo21$76616b2o$76617b2o$76616bo21$76593b2o$76594b2o$
76593bo20$76571bo$76571b2o$76570bobo34$76535b2o$76534bobo$76536bo21$
76512b3o$76514bo$76513bo20$76490bo$76490b2o$76489bobo38$76450b2o$
76451b2o$76450bo21$76427b3o$76429bo$76428bo25$76400b2o$76401b2o$76400b
o21$76377b3o$76379bo$76378bo21$76354b2o$76355b2o$76354bo20$76332bo$
76332b2o$76331bobo33$76297bo$76297b2o$76296bobo36$76259b2o$76260b2o$
76259bo26$76231b2o$76230bobo$76232bo21$76208b3o$76210bo$76209bo20$
76186b2o$76185bobo$76187bo21$76163b3o$76165bo$76164bo20$76141b2o$
76140bobo$76142bo21$76118b2o$76119b2o$76118bo32$76084b2o$76085b2o$
76084bo28$76054b3o$76056bo$76055bo29$76023bo$76023b2o$76022bobo21$
76000b2o$76001b2o$76000bo36$75962bo$75962b2o$75961bobo34$75926b2o$
75927b2o$75926bo31$75893b2o$75894b2o$75893bo21$75870b3o$75872bo$75871b
o20$75848bo$75848b2o$75847bobo21$75825b2o$75826b2o$75825bo25$75798b2o$
75797bobo$75799bo21$75775b3o$75777bo$75776bo21$75752b2o$75753b2o$
75752bo21$75729b3o$75731bo$75730bo20$75707bo$75707b2o$75706bobo21$
75684bo$75684b2o$75683bobo21$75661b2o$75662b2o$75661bo20$75639bo$
75639b2o$75638bobo21$75616b2o$75615bobo$75617bo21$75593b3o$75595bo$
75594bo25$75566b2o$75565bobo$75567bo21$75543b3o$75545bo$75544bo20$
75521b2o$75520bobo$75522bo21$75498b2o$75499b2o$75498bo29$75467b2o$
75468b2o$75467bo31$75434b2o$75433bobo$75435bo21$75411b3o$75413bo$
75412bo20$75389bo$75389b2o$75388bobo27$75360b3o$75362bo$75361bo20$
75338b2o$75337bobo$75339bo21$75315b3o$75317bo$75316bo20$75293bo$75293b
2o$75292bobo26$75265b3o$75267bo$75266bo20$75243bo$75243b2o$75242bobo
22$75219b2o$75220b2o$75219bo21$75196b3o$75198bo$75197bo20$75174bo$
75174b2o$75173bobo32$75140bo$75140b2o$75139bobo21$75117b2o$75116bobo$
75118bo21$75094b3o$75096bo$75095bo20$75072bo$75072b2o$75071bobo33$
75037bo$75037b2o$75036bobo22$75013b2o$75014b2o$75013bo39$74972bo$
74972b2o$74971bobo21$74949b2o$74950b2o$74949bo20$74927bo$74927b2o$
74926bobo21$74904b2o$74903bobo$74905bo22$74880b3o$74882bo$74881bo23$
74855b2o$74856b2o$74855bo20$74833bo$74833b2o$74832bobo26$74805b3o$
74807bo$74806bo20$74783bo$74783b2o$74782bobo22$74759b2o$74760b2o$
74759bo21$74736b3o$74738bo$74737bo20$74714bo$74714b2o$74713bobo43$
74669b2o$74668bobo$74670bo21$74646b3o$74648bo$74647bo20$74624bo$74624b
2o$74623bobo22$74600b2o$74601b2o$74600bo21$74577b3o$74579bo$74578bo23$
74552b2o$74551bobo$74553bo21$74529b2o$74530b2o$74529bo41$74486b3o$
74488bo$74487bo20$74464bo$74464b2o$74463bobo26$74436b2o$74437b2o$
74436bo21$74413b3o$74415bo$74414bo37$74374b3o$74376bo$74375bo20$74352b
2o$74351bobo$74353bo28$74322b2o$74323b2o$74322bo20$74300bo$74300b2o$
74299bobo21$74277b2o$74278b2o$74277bo20$74255bo$74255b2o$74254bobo21$
74232b2o$74233b2o$74232bo21$74209b3o$74211bo$74210bo20$74187b2o$74186b
obo$74188bo25$74160bo$74160b2o$74159bobo21$74137b2o$74136bobo$74138bo
21$74114bo$74114b2o$74113bobo21$74091b2o$74090bobo$74092bo34$74055bo$
74055b2o$74054bobo52$74001b2o$74000bobo$74002bo24$73975b2o$73974bobo$
73976bo21$73952b3o$73954bo$73953bo20$73930b2o$73929bobo$73931bo21$
73907b3o$73909bo$73908bo20$73885b2o$73884bobo$73886bo21$73862b3o$
73864bo$73863bo23$73837b2o$73836bobo$73838bo21$73814b2o$73813bobo$
73815bo21$73791b3o$73793bo$73792bo20$73769b2o$73768bobo$73770bo21$
73746b3o$73748bo$73747bo24$73720b2o$73719bobo$73721bo37$73681b2o$
73682b2o$73681bo35$73644bo$73644b2o$73643bobo21$73621b2o$73622b2o$
73621bo25$73594b2o$73593bobo$73595bo21$73571b2o$73572b2o$73571bo21$
73548b2o$73547bobo$73549bo21$73525b2o$73526b2o$73525bo22$73501b2o$
73500bobo$73502bo21$73478b3o$73480bo$73479bo20$73456b2o$73455bobo$
73457bo29$73425b3o$73427bo$73426bo20$73403bo$73403b2o$73402bobo31$
73370bo$73370b2o$73369bobo21$73347b2o$73348b2o$73347bo22$73323bo$
73323b2o$73322bobo21$73300b2o$73299bobo$73301bo21$73277b2o$73278b2o$
73277bo24$73251b2o$73250bobo$73252bo21$73228b2o$73229b2o$73228bo20$
73206bo$73206b2o$73205bobo27$73177bo$73177b2o$73176bobo21$73154b2o$
73155b2o$73154bo26$73126b2o$73127b2o$73126bo21$73103b3o$73105bo$73104b
o25$73076b2o$73077b2o$73076bo21$73053b3o$73055bo$73054bo21$73030b2o$
73029bobo$73031bo21$73007b2o$73008b2o$73007bo21$72984b3o$72986bo$
72985bo32$72950b3o$72952bo$72951bo20$72928bo$72928b2o$72927bobo21$
72905b2o$72906b2o$72905bo21$72882b3o$72884bo$72883bo24$72856b3o$72858b
o$72857bo20$72834b2o$72833bobo$72835bo21$72811b3o$72813bo$72812bo20$
72789b2o$72788bobo$72790bo26$72761b3o$72763bo$72762bo20$72739b2o$
72738bobo$72740bo21$72716b3o$72718bo$72717bo22$72692b2o$72691bobo$
72693bo21$72669b2o$72670b2o$72669bo25$72642b2o$72641bobo$72643bo21$
72619b2o$72620b2o$72619bo21$72596b2o$72595bobo$72597bo21$72573b2o$
72574b2o$72573bo34$72537b2o$72536bobo$72538bo52$72483b2o$72484b2o$
72483bo24$72457bo$72457b2o$72456bobo21$72434b2o$72435b2o$72434bo20$
72412bo$72412b2o$72411bobo21$72389b2o$72388bobo$72390bo21$72366b2o$
72367b2o$72366bo41$72323bo$72323b2o$72322bobo21$72300b2o$72301b2o$
72300bo37$72261bo$72261b2o$72260bobo21$72238b2o$72239b2o$72238bo20$
72216bo$72216b2o$72215bobo21$72193b2o$72194b2o$72193bo21$72170b3o$
72172bo$72171bo32$72136b2o$72137b2o$72136bo20$72114bo$72114b2o$72113bo
bo21$72091b2o$72090bobo$72092bo30$72059b2o$72060b2o$72059bo20$72037bo$
72037b2o$72036bobo26$72009b3o$72011bo$72010bo20$71987bo$71987b2o$
71986bobo22$71963b3o$71965bo$71964bo20$71941b2o$71940bobo$71942bo30$
71909bo$71909b2o$71908bobo35$71872bo$71872b2o$71871bobo21$71849b2o$
71848bobo$71850bo26$71821b2o$71820bobo$71822bo33$71786b2o$71785bobo$
71787bo26$71758bo$71758b2o$71757bobo21$71735b2o$71734bobo$71736bo25$
71708b3o$71710bo$71709bo20$71686bo$71686b2o$71685bobo21$71663b2o$
71662bobo$71664bo28$71633bo$71633b2o$71632bobo21$71610b2o$71611b2o$
71610bo24$71584b3o$71586bo$71585bo53$71529b2o$71530b2o$71529bo34$
71493bo$71493b2o$71492bobo21$71470b2o$71471b2o$71470bo30$71438b2o$
71439b2o$71438bo36$71400bo$71400b2o$71399bobo21$71377b2o$71378b2o$
71377bo21$71354b3o$71356bo$71355bo20$71332bo$71332b2o$71331bobo26$
71304b3o$71306bo$71305bo20$71282b2o$71281bobo$71283bo21$71259bo$71259b
2o$71258bobo21$71236b2o$71235bobo$71237bo21$71213b3o$71215bo$71214bo
21$71190bo$71190b2o$71189bobo21$71167b2o$71166bobo$71168bo21$71144b2o$
71145b2o$71144bo32$71110bo$71110b2o$71109bobo38$71070b3o$71072bo$
71071bo22$71046b3o$71048bo$71047bo20$71024b2o$71023bobo$71025bo28$
70994b2o$70993bobo$70995bo21$70971b2o$70972b2o$70971bo22$70947b2o$
70946bobo$70948bo25$70920b2o$70921b2o$70920bo20$70898bo$70898b2o$
70897bobo21$70875b2o$70876b2o$70875bo21$70852b2o$70851bobo$70853bo45$
70805b2o$70804bobo$70806bo25$70778bo$70778b2o$70777bobo21$70755b2o$
70754bobo$70756bo21$70732bo$70732b2o$70731bobo21$70709b2o$70708bobo$
70710bo22$70685bo$70685b2o$70684bobo21$70662b2o$70663b2o$70662bo20$
70640bo$70640b2o$70639bobo29$70609b2o$70610b2o$70609bo21$70586b3o$
70588bo$70587bo31$70553b3o$70555bo$70554bo20$70531b2o$70530bobo$70532b
o23$70506b3o$70508bo$70507bo20$70484bo$70484b2o$70483bobo21$70461b2o$
70460bobo$70462bo24$70435bo$70435b2o$70434bobo21$70412b2o$70411bobo$
70413bo21$70389b3o$70391bo$70390bo27$70360b3o$70362bo$70361bo20$70338b
2o$70337bobo$70339bo26$70310b2o$70309bobo$70311bo21$70287b3o$70289bo$
70288bo25$70260b2o$70261b2o$70260bo21$70237b3o$70239bo$70238bo21$
70214b2o$70213bobo$70215bo21$70191b2o$70192b2o$70191bo21$70168b3o$
70170bo$70169bo29$70137b3o$70139bo$70138bo20$70115bo$70115b2o$70114bob
o25$70088b3o$70090bo$70089bo20$70066b2o$70065bobo$70067bo25$70039b3o$
70041bo$70040bo26$70011b3o$70013bo$70012bo25$69984b3o$69986bo$69985bo
20$69962b2o$69961bobo$69963bo25$69935bo$69935b2o$69934bobo21$69912b2o$
69911bobo$69913bo21$69889bo$69889b2o$69888bobo21$69866b2o$69865bobo$
69867bo26$69838bo$69838b2o$69837bobo21$69815b2o$69814bobo$69816bo31$
69782b2o$69781bobo$69783bo21$69759b2o$69760b2o$69759bo21$69736b3o$
69738bo$69737bo31$69703b2o$69704b2o$69703bo21$69680b3o$69682bo$69681bo
20$69658b2o$69657bobo$69659bo23$69633b3o$69635bo$69634bo20$69611bo$
69611b2o$69610bobo21$69588b2o$69589b2o$69588bo31$69555b3o$69557bo$
69556bo20$69533b2o$69532bobo$69534bo26$69505b2o$69504bobo$69506bo31$
69472b2o$69471bobo$69473bo21$69449b3o$69451bo$69450bo20$69427b2o$
69426bobo$69428bo25$69400bo$69400b2o$69399bobo21$69377b2o$69378b2o$
69377bo21$69354b2o$69353bobo$69355bo21$69331b2o$69332b2o$69331bo21$
69308b3o$69310bo$69309bo31$69275bo$69275b2o$69274bobo21$69252b2o$
69251bobo$69253bo34$69216b2o$69215bobo$69217bo21$69193b3o$69195bo$
69194bo20$69171b2o$69170bobo$69172bo29$69140b2o$69141b2o$69140bo21$
69117b3o$69119bo$69118bo20$69095b2o$69094bobo$69096bo28$69065b2o$
69064bobo$69066bo21$69042b3o$69044bo$69043bo20$69020bo$69020b2o$69019b
obo21$68997b2o$68996bobo$68998bo21$68974b2o$68975b2o$68974bo39$68933b
3o$68935bo$68934bo20$68911b2o$68910bobo$68912bo22$68887b2o$68888b2o$
68887bo21$68864b3o$68866bo$68865bo31$68831b2o$68830bobo$68832bo21$
68808b2o$68809b2o$68808bo25$68781b2o$68780bobo$68782bo21$68758b2o$
68759b2o$68758bo21$68735bo$68735b2o$68734bobo21$68712b2o$68711bobo$
68713bo21$68689b2o$68690b2o$68689bo32$68655b2o$68656b2o$68655bo21$
68632b3o$68634bo$68633bo20$68610b2o$68609bobo$68611bo21$68587b2o$
68588b2o$68587bo40$68545b2o$68546b2o$68545bo20$68523bo$68523b2o$68522b
obo21$68500b2o$68501b2o$68500bo22$68476b2o$68475bobo$68477bo21$68453b
2o$68454b2o$68453bo21$68430b3o$68432bo$68431bo20$68408bo$68408b2o$
68407bobo21$68385b2o$68386b2o$68385bo27$68356b2o$68357b2o$68356bo20$
68334bo$68334b2o$68333bobo21$68311b2o$68312b2o$68311bo20$68289bo$
68289b2o$68288bobo21$68266b2o$68267b2o$68266bo20$68244bo$68244b2o$
68243bobo21$68221b2o$68220bobo$68222bo25$68194bo$68194b2o$68193bobo21$
68171b2o$68170bobo$68172bo22$68147b3o$68149bo$68148bo20$68125bo$68125b
2o$68124bobo21$68102b2o$68101bobo$68103bo32$68068b2o$68067bobo$68069bo
21$68045b3o$68047bo$68046bo20$68023b2o$68022bobo$68024bo21$68000b2o$
68001b2o$68000bo41$67957b3o$67959bo$67958bo23$67932b3o$67934bo$67933bo
27$67903b2o$67902bobo$67904bo21$67880b3o$67882bo$67881bo20$67858b2o$
67857bobo$67859bo25$67831bo$67831b2o$67830bobo21$67808b2o$67807bobo$
67809bo21$67785bo$67785b2o$67784bobo21$67762b2o$67761bobo$67763bo37$
67723b2o$67722bobo$67724bo21$67700b2o$67701b2o$67700bo21$67677b3o$
67679bo$67678bo29$67646b2o$67645bobo$67647bo21$67623b3o$67625bo$67624b
o20$67601bo$67601b2o$67600bobo21$67578b2o$67577bobo$67579bo21$67555b2o
$67556b2o$67555bo35$67518b3o$67520bo$67519bo20$67496b2o$67495bobo$
67497bo26$67468bo$67468b2o$67467bobo21$67445b2o$67446b2o$67445bo23$
67420bo$67420b2o$67419bobo21$67397b2o$67398b2o$67397bo21$67374b3o$
67376bo$67375bo20$67352b2o$67351bobo$67353bo25$67325bo$67325b2o$67324b
obo21$67302b2o$67301bobo$67303bo21$67279bo$67279b2o$67278bobo21$67256b
2o$67255bobo$67257bo42$67212b3o$67214bo$67213bo20$67190b2o$67189bobo$
67191bo21$67167b2o$67168b2o$67167bo21$67144b3o$67146bo$67145bo20$
67122b2o$67121bobo$67123bo21$67099b3o$67101bo$67100bo20$67077bo$67077b
2o$67076bobo28$67047bo$67047b2o$67046bobo21$67024b2o$67023bobo$67025bo
21$67001b3o$67003bo$67002bo37$66962b2o$66963b2o$66962bo20$66940bo$
66940b2o$66939bobo24$66914b3o$66916bo$66915bo20$66892bo$66892b2o$
66891bobo21$66869b2o$66868bobo$66870bo28$66839b2o$66840b2o$66839bo20$
66817bo$66817b2o$66816bobo21$66794b2o$66795b2o$66794bo20$66772bo$
66772b2o$66771bobo21$66749b2o$66750b2o$66749bo20$66727bo$66727b2o$
66726bobo21$66704b2o$66705b2o$66704bo25$66677b2o$66676bobo$66678bo21$
66654b2o$66655b2o$66654bo21$66631b2o$66630bobo$66632bo21$66608b2o$
66609b2o$66608bo34$66572b2o$66571bobo$66573bo52$66518b2o$66519b2o$
66518bo24$66492bo$66492b2o$66491bobo21$66469b2o$66470b2o$66469bo20$
66447bo$66447b2o$66446bobo21$66424b2o$66423bobo$66425bo21$66401b2o$
66402b2o$66401bo41$66358bo$66358b2o$66357bobo21$66335b2o$66336b2o$
66335bo37$66296bo$66296b2o$66295bobo21$66273b2o$66274b2o$66273bo20$
66251bo$66251b2o$66250bobo21$66228b2o$66229b2o$66228bo21$66205b3o$
66207bo$66206bo32$66171b2o$66172b2o$66171bo20$66149bo$66149b2o$66148bo
bo21$66126b2o$66125bobo$66127bo30$66094b2o$66095b2o$66094bo20$66072bo$
66072b2o$66071bobo26$66044b3o$66046bo$66045bo20$66022bo$66022b2o$
66021bobo22$65998b3o$66000bo$65999bo20$65976bo$65976b2o$65975bobo21$
65953bo$65953b2o$65952bobo21$65930b2o$65931b2o$65930bo22$65906b2o$
65905bobo$65907bo21$65883b2o$65884b2o$65883bo27$65854b2o$65855b2o$
65854bo21$65831b3o$65833bo$65832bo27$65802bo$65802b2o$65801bobo21$
65779b2o$65780b2o$65779bo20$65757bo$65757b2o$65756bobo21$65734b2o$
65733bobo$65735bo24$65708b2o$65707bobo$65709bo23$65683b2o$65684b2o$
65683bo20$65661bo$65661b2o$65660bobo21$65638bo$65638b2o$65637bobo22$
65614b2o$65615b2o$65614bo21$65591b3o$65593bo$65592bo22$65567b2o$65568b
2o$65567bo21$65544b3o$65546bo$65545bo21$65521b3o$65523bo$65522bo20$
65499bo$65499b2o$65498bobo23$65474b2o$65475b2o$65474bo21$65451b3o$
65453bo$65452bo25$65424b2o$65425b2o$65424bo21$65401b3o$65403bo$65402bo
21$65378b2o$65379b2o$65378bo21$65355b3o$65357bo$65356bo34$65319b2o$
65320b2o$65319bo52$65265b3o$65267bo$65266bo24$65239b2o$65238bobo$
65240bo21$65216b3o$65218bo$65217bo20$65194b2o$65193bobo$65195bo21$
65171b2o$65172b2o$65171bo21$65148b3o$65150bo$65149bo41$65105b2o$65104b
obo$65106bo21$65082b3o$65084bo$65083bo37$65043b2o$65042bobo$65044bo21$
65020b3o$65022bo$65021bo20$64998b2o$64997bobo$64999bo21$64975b3o$
64977bo$64976bo20$64953bo$64953b2o$64952bobo33$64918b3o$64920bo$64919b
o20$64896b2o$64895bobo$64897bo21$64873b2o$64874b2o$64873bo30$64841b3o$
64843bo$64842bo20$64819b2o$64818bobo$64820bo25$64792bo$64792b2o$64791b
obo21$64769b2o$64768bobo$64770bo21$64746bo$64746b2o$64745bobo21$64723b
2o$64722bobo$64724bo42$64679b3o$64681bo$64680bo20$64657b2o$64656bobo$
64658bo21$64634b2o$64635b2o$64634bo20$64612bo$64612b2o$64611bobo35$
64575bo$64575b2o$64574bobo21$64552b2o$64553b2o$64552bo23$64527b2o$
64526bobo$64528bo39$64486b2o$64487b2o$64486bo34$64450bo$64450b2o$
64449bobo21$64427b2o$64428b2o$64427bo34$64391b3o$64393bo$64392bo20$
64369bo$64369b2o$64368bobo21$64346b2o$64345bobo$64347bo21$64323b3o$
64325bo$64324bo28$64293bo$64293b2o$64292bobo21$64270b2o$64271b2o$
64270bo21$64247b3o$64249bo$64248bo31$64214b3o$64216bo$64215bo22$64190b
o$64190b2o$64189bobo26$64162b3o$64164bo$64163bo20$64140bo$64140b2o$
64139bobo22$64116b3o$64118bo$64117bo20$64094b2o$64093bobo$64095bo33$
64059b2o$64058bobo$64060bo36$64021b3o$64023bo$64022bo26$63993b2o$
63994b2o$63993bo20$63971bo$63971b2o$63970bobo21$63948b2o$63949b2o$
63948bo20$63926bo$63926b2o$63925bobo21$63903b2o$63904b2o$63903bo21$
63880b3o$63882bo$63881bo32$63846b3o$63848bo$63847bo27$63817bo$63817b2o
$63816bobo30$63785b2o$63784bobo$63786bo21$63762b3o$63764bo$63763bo36$
63724b2o$63723bobo$63725bo34$63688b3o$63690bo$63689bo31$63655b3o$
63657bo$63656bo20$63633bo$63633b2o$63632bobo21$63610b2o$63609bobo$
63611bo21$63587b3o$63589bo$63588bo25$63560b2o$63561b2o$63560bo20$
63538bo$63538b2o$63537bobo22$63514b3o$63516bo$63515bo20$63492bo$63492b
2o$63491bobo21$63469b2o$63468bobo$63470bo21$63446b2o$63445bobo$63447bo
21$63423b3o$63425bo$63424bo20$63401b2o$63400bobo$63402bo21$63378b2o$
63379b2o$63378bo20$63356bo$63356b2o$63355bobo26$63328b2o$63329b2o$
63328bo20$63306bo$63306b2o$63305bobo21$63283b2o$63284b2o$63283bo21$
63260b3o$63262bo$63261bo29$63229b3o$63231bo$63230bo31$63196b2o$63197b
2o$63196bo20$63174bo$63174b2o$63173bobo21$63151b2o$63150bobo$63152bo
26$63123bo$63123b2o$63122bobo21$63100b2o$63101b2o$63100bo20$63078bo$
63078b2o$63077bobo21$63055b2o$63056b2o$63055bo25$63028b2o$63027bobo$
63029bo21$63005b2o$63006b2o$63005bo21$62982b2o$62981bobo$62983bo21$
62959b3o$62961bo$62960bo28$62929bo$62929b2o$62928bobo21$62906b2o$
62907b2o$62906bo24$62880b2o$62879bobo$62881bo21$62857b3o$62859bo$
62858bo20$62835b2o$62834bobo$62836bo26$62807b2o$62808b2o$62807bo20$
62785bo$62785b2o$62784bobo26$62757bo$62757b2o$62756bobo21$62734b2o$
62733bobo$62735bo21$62711b3o$62713bo$62712bo22$62687b2o$62686bobo$
62688bo21$62664b3o$62666bo$62665bo22$62640b3o$62642bo$62641bo24$62614b
3o$62616bo$62615bo20$62592bo$62592b2o$62591bobo21$62569b2o$62568bobo$
62570bo21$62546b3o$62548bo$62547bo24$62520bo$62520b2o$62519bobo44$
62474b3o$62476bo$62475bo25$62447b2o$62448b2o$62447bo21$62424b3o$62426b
o$62425bo21$62401b2o$62402b2o$62401bo21$62378b3o$62380bo$62379bo34$
62342b2o$62343b2o$62342bo52$62288b3o$62290bo$62289bo24$62262b2o$62261b
obo$62263bo21$62239b3o$62241bo$62240bo20$62217b2o$62216bobo$62218bo21$
62194b2o$62195b2o$62194bo21$62171b3o$62173bo$62172bo41$62128b2o$62127b
obo$62129bo21$62105b3o$62107bo$62106bo37$62066b2o$62065bobo$62067bo21$
62043b3o$62045bo$62044bo20$62021b2o$62020bobo$62022bo21$61998b3o$
62000bo$61999bo20$61976bo$61976b2o$61975bobo33$61941b3o$61943bo$61942b
o20$61919b2o$61918bobo$61920bo21$61896b2o$61897b2o$61896bo30$61864b3o$
61866bo$61865bo20$61842b2o$61841bobo$61843bo25$61815bo$61815b2o$61814b
obo21$61792b2o$61791bobo$61793bo22$61768b3o$61770bo$61769bo20$61746bo$
61746b2o$61745bobo21$61723b2o$61722bobo$61724bo43$61678b2o$61679b2o$
61678bo20$61656bo$61656b2o$61655bobo21$61633b2o$61632bobo$61634bo22$
61609b3o$61611bo$61610bo20$61587bo$61587b2o$61586bobo24$61561b2o$
61562b2o$61561bo21$61538b3o$61540bo$61539bo40$61496bo$61496b2o$61495bo
bo21$61473b2o$61472bobo$61474bo26$61445b3o$61447bo$61446bo20$61423bo$
61423b2o$61422bobo37$61384bo$61384b2o$61383bobo21$61361b2o$61362b2o$
61361bo28$61331b3o$61333bo$61332bo20$61309b2o$61308bobo$61310bo21$
61286b3o$61288bo$61287bo20$61264b2o$61263bobo$61265bo21$61241b3o$
61243bo$61242bo20$61219bo$61219b2o$61218bobo21$61196b2o$61197b2o$
61196bo25$61169b2o$61168bobo$61170bo21$61146b2o$61147b2o$61146bo21$
61123b2o$61122bobo$61124bo21$61100b2o$61101b2o$61100bo37$61061b3o$
61063bo$61062bo24$61035b2o$61034bobo$61036bo21$61012b2o$61013b2o$
61012bo20$60990bo$60990b2o$60989bobo33$60955b2o$60954bobo$60956bo21$
60932b2o$60933b2o$60932bo24$60906b2o$60907b2o$60906bo21$60883b3o$
60885bo$60884bo20$60861b2o$60860bobo$60862bo21$60838bo$60838b2o$60837b
obo24$60812bo$60812b2o$60811bobo21$60789b2o$60788bobo$60790bo21$60766b
2o$60767b2o$60766bo34$60730b3o$60732bo$60731bo20$60708bo$60708b2o$
60707bobo26$60680b2o$60681b2o$60680bo36$60642b2o$60641bobo$60643bo39$
60601b3o$60603bo$60602bo20$60579b2o$60578bobo$60580bo21$60556b2o$
60557b2o$60556bo21$60533b2o$60532bobo$60534bo39$60492b2o$60493b2o$
60492bo25$60465b2o$60464bobo$60466bo21$60442b2o$60443b2o$60442bo21$
60419b2o$60418bobo$60420bo21$60396b2o$60397b2o$60396bo21$60373b2o$
60374b2o$60373bo20$60351bo$60351b2o$60350bobo23$60326b3o$60328bo$
60327bo20$60304bo$60304b2o$60303bobo27$60275bo$60275b2o$60274bobo21$
60252b2o$60251bobo$60253bo28$60222b2o$60223b2o$60222bo20$60200bo$
60200b2o$60199bobo21$60177b2o$60178b2o$60177bo21$60154b3o$60156bo$
60155bo24$60128b3o$60130bo$60129bo22$60104bo$60104b2o$60103bobo21$
60081b2o$60082b2o$60081bo21$60058b2o$60059b2o$60058bo21$60035bo$60035b
2o$60034bobo21$60012b2o$60011bobo$60013bo22$59988bo$59988b2o$59987bobo
21$59965b2o$59964bobo$59966bo21$59942b2o$59941bobo$59943bo21$59919b2o$
59920b2o$59919bo22$59895bo$59895b2o$59894bobo21$59872b2o$59871bobo$
59873bo25$59845bo$59845b2o$59844bobo21$59822b2o$59821bobo$59823bo21$
59799bo$59799b2o$59798bobo21$59776b2o$59775bobo$59777bo34$59740bo$
59740b2o$59739bobo52$59686b2o$59685bobo$59687bo25$59659b3o$59661bo$
59660bo20$59637b2o$59636bobo$59638bo21$59614b3o$59616bo$59615bo20$
59592bo$59592b2o$59591bobo21$59569b2o$59568bobo$59570bo42$59525b3o$
59527bo$59526bo20$59503b2o$59502bobo$59504bo38$59463b3o$59465bo$59464b
o20$59441b2o$59440bobo$59442bo21$59418b3o$59420bo$59419bo20$59396b2o$
59395bobo$59397bo21$59373b2o$59374b2o$59373bo32$59339b2o$59338bobo$
59340bo21$59316b3o$59318bo$59317bo20$59294bo$59294b2o$59293bobo30$
59262b2o$59261bobo$59263bo21$59239b3o$59241bo$59240bo25$59212b2o$
59213b2o$59212bo21$59189b3o$59191bo$59190bo21$59166b2o$59165bobo$
59167bo21$59143b2o$59144b2o$59143bo21$59120b3o$59122bo$59121bo32$
59086b3o$59088bo$59087bo20$59064bo$59064b2o$59063bobo21$59041b2o$
59042b2o$59041bo21$59018b3o$59020bo$59019bo33$58983b3o$58985bo$58984bo
21$58960b2o$58959bobo$58961bo26$58932b2o$58931bobo$58933bo21$58909b2o$
58910b2o$58909bo30$58877b2o$58876bobo$58878bo21$58854b3o$58856bo$
58855bo20$58832b2o$58831bobo$58833bo21$58809b2o$58808bobo$58810bo21$
58786b3o$58788bo$58787bo23$58761b3o$58763bo$58762bo20$58739b2o$58738bo
bo$58740bo27$58710b2o$58711b2o$58710bo21$58687b3o$58689bo$58688bo20$
58665bo$58665b2o$58664bobo22$58641b3o$58643bo$58642bo20$58619b2o$
58618bobo$58620bo25$58592bo$58592b2o$58591bobo21$58569b2o$58568bobo$
58570bo21$58546bo$58546b2o$58545bobo21$58523b2o$58522bobo$58524bo26$
58495bo$58495b2o$58494bobo21$58472b2o$58471bobo$58473bo31$58439b2o$
58438bobo$58440bo21$58416b2o$58417b2o$58416bo21$58393b3o$58395bo$
58394bo31$58360b2o$58361b2o$58360bo21$58337b3o$58339bo$58338bo20$
58315b2o$58314bobo$58316bo23$58290b3o$58292bo$58291bo20$58268bo$58268b
2o$58267bobo21$58245b2o$58246b2o$58245bo31$58212b3o$58214bo$58213bo20$
58190b2o$58189bobo$58191bo26$58162b2o$58161bobo$58163bo31$58129b2o$
58128bobo$58130bo21$58106b3o$58108bo$58107bo20$58084b2o$58083bobo$
58085bo25$58057bo$58057b2o$58056bobo21$58034b2o$58033bobo$58035bo21$
58011bo$58011b2o$58010bobo21$57988b2o$57987bobo$57989bo22$57964bo$
57964b2o$57963bobo21$57941b2o$57942b2o$57941bo20$57919bo$57919b2o$
57918bobo29$57888b2o$57889b2o$57888bo21$57865b3o$57867bo$57866bo31$
57832b3o$57834bo$57833bo20$57810b2o$57809bobo$57811bo23$57785b3o$
57787bo$57786bo20$57763bo$57763b2o$57762bobo21$57740b2o$57739bobo$
57741bo24$57714bo$57714b2o$57713bobo21$57691b2o$57690bobo$57692bo21$
57668b3o$57670bo$57669bo27$57639b3o$57641bo$57640bo20$57617b2o$57616bo
bo$57618bo26$57589b2o$57588bobo$57590bo21$57566b2o$57567b2o$57566bo25$
57539b2o$57538bobo$57540bo21$57516b2o$57517b2o$57516bo21$57493bo$
57493b2o$57492bobo21$57470b2o$57469bobo$57471bo21$57447b2o$57448b2o$
57447bo32$57413b2o$57414b2o$57413bo21$57390b3o$57392bo$57391bo20$
57368b2o$57367bobo$57369bo21$57345b2o$57346b2o$57345bo24$57319b2o$
57320b2o$57319bo20$57297bo$57297b2o$57296bobo21$57274b2o$57275b2o$
57274bo20$57252bo$57252b2o$57251bobo26$57224b2o$57225b2o$57224bo20$
57202bo$57202b2o$57201bobo21$57179b2o$57180b2o$57179bo22$57155bo$
57155b2o$57154bobo21$57132b2o$57133b2o$57132bo25$57105b2o$57104bobo$
57106bo21$57082b2o$57083b2o$57082bo21$57059bo$57059b2o$57058bobo21$
57036b2o$57035bobo$57037bo21$57013b2o$57014b2o$57013bo22$56989b2o$
56990b2o$56989bo20$56967bo$56967b2o$56966bobo23$56942b3o$56944bo$
56943bo20$56920bo$56920b2o$56919bobo21$56897b2o$56896bobo$56898bo31$
56864b3o$56866bo$56865bo21$56841b2o$56840bobo$56842bo21$56818b3o$
56820bo$56819bo24$56792b2o$56793b2o$56792bo20$56770bo$56770b2o$56769bo
bo22$56746b2o$56745bobo$56747bo34$56710b2o$56711b2o$56710bo23$56685b3o
$56687bo$56686bo25$56658b2o$56659b2o$56658bo21$56635b3o$56637bo$56636b
o21$56612b2o$56613b2o$56612bo20$56590bo$56590b2o$56589bobo31$56557b3o$
56559bo$56558bo35$56520b3o$56522bo$56521bo20$56498bo$56498b2o$56497bob
o26$56470bo$56470b2o$56469bobo33$56435bo$56435b2o$56434bobo27$56406b3o
$56408bo$56407bo20$56384bo$56384b2o$56383bobo25$56357b2o$56358b2o$
56357bo21$56334b3o$56336bo$56335bo20$56312bo$56312b2o$56311bobo29$
56281b3o$56283bo$56282bo20$56259b2o$56258bobo$56260bo24$56233b2o$
56234b2o$56233bo53$56178b2o$56177bobo$56179bo35$56141b3o$56143bo$
56142bo20$56119b2o$56118bobo$56120bo30$56087b2o$56086bobo$56088bo37$
56048b3o$56050bo$56049bo20$56026b2o$56025bobo$56027bo21$56003b2o$
56004b2o$56003bo20$55981bo$55981b2o$55980bobo26$55953b3o$55955bo$
55954bo20$55931bo$55931b2o$55930bobo22$55907b3o$55909bo$55908bo20$
55885bo$55885b2o$55884bobo35$55848b3o$55850bo$55849bo51$55795bo$55795b
2o$55794bobo25$55768b2o$55769b2o$55768bo20$55746bo$55746b2o$55745bobo
21$55723b2o$55724b2o$55723bo21$55700b3o$55702bo$55701bo20$55678bo$
55678b2o$55677bobo42$55634b2o$55635b2o$55634bo20$55612bo$55612b2o$
55611bobo38$55572b2o$55573b2o$55572bo20$55550bo$55550b2o$55549bobo21$
55527b2o$55528b2o$55527bo20$55505bo$55505b2o$55504bobo21$55482b2o$
55481bobo$55483bo32$55448bo$55448b2o$55447bobo21$55425b2o$55426b2o$
55425bo21$55402b3o$55404bo$55403bo29$55371bo$55371b2o$55370bobo21$
55348b2o$55349b2o$55348bo25$55321b2o$55320bobo$55322bo21$55298b2o$
55299b2o$55298bo21$55275bo$55275b2o$55274bobo21$55252b2o$55251bobo$
55253bo21$55229b2o$55230b2o$55229bo43$55184b3o$55186bo$55185bo20$
55162b2o$55161bobo$55163bo21$55139b2o$55140b2o$55139bo21$55116bo$
55116b2o$55115bobo21$55093b2o$55092bobo$55094bo24$55067b3o$55069bo$
55068bo20$55045bo$55045b2o$55044bobo41$55002b2o$55001bobo$55003bo21$
54979b2o$54980b2o$54979bo25$54952bo$54952b2o$54951bobo21$54929b2o$
54928bobo$54930bo37$54890b2o$54889bobo$54891bo21$54867b3o$54869bo$
54868bo27$54838bo$54838b2o$54837bobo21$54815b2o$54816b2o$54815bo20$
54793bo$54793b2o$54792bobo21$54770b2o$54771b2o$54770bo20$54748bo$
54748b2o$54747bobo21$54725b2o$54724bobo$54726bo21$54702b3o$54704bo$
54703bo25$54675b2o$54676b2o$54675bo20$54653bo$54653b2o$54652bobo22$
54629b3o$54631bo$54630bo20$54607bo$54607b2o$54606bobo21$54584b2o$
54585b2o$54584bo23$54559b2o$54560b2o$54559bo31$54526b3o$54528bo$54527b
o23$54501b2o$54502b2o$54501bo20$54479bo$54479b2o$54478bobo27$54450b3o$
54452bo$54451bo21$54427bo$54427b2o$54426bobo26$54399b3o$54401bo$54400b
o20$54377bo$54377b2o$54376bobo22$54353b3o$54355bo$54354bo20$54331bo$
54331b2o$54330bobo21$54308bo$54308b2o$54307bobo21$54285b2o$54286b2o$
54285bo22$54261b2o$54260bobo$54262bo21$54238b2o$54239b2o$54238bo27$
54209b2o$54210b2o$54209bo21$54186b3o$54188bo$54187bo27$54157bo$54157b
2o$54156bobo21$54134b2o$54135b2o$54134bo20$54112bo$54112b2o$54111bobo
21$54089b2o$54088bobo$54090bo24$54063b2o$54062bobo$54064bo23$54038b2o$
54039b2o$54038bo20$54016bo$54016b2o$54015bobo21$53993bo$53993b2o$
53992bobo22$53969b2o$53970b2o$53969bo21$53946b3o$53948bo$53947bo22$
53922b2o$53923b2o$53922bo21$53899b3o$53901bo$53900bo21$53876b3o$53878b
o$53877bo20$53854bo$53854b2o$53853bobo23$53829b2o$53830b2o$53829bo20$
53807bo$53807b2o$53806bobo26$53779b3o$53781bo$53780bo20$53757b2o$
53756bobo$53758bo21$53734bo$53734b2o$53733bobo21$53711b2o$53710bobo$
53712bo21$53688b3o$53690bo$53689bo21$53665bo$53665b2o$53664bobo21$
53642b2o$53641bobo$53643bo21$53619b2o$53620b2o$53619bo32$53585bo$
53585b2o$53584bobo38$53545b3o$53547bo$53546bo22$53521b3o$53523bo$
53522bo20$53499b2o$53498bobo$53500bo28$53469b2o$53468bobo$53470bo21$
53446b2o$53447b2o$53446bo22$53422b2o$53421bobo$53423bo25$53395b2o$
53396b2o$53395bo20$53373bo$53373b2o$53372bobo21$53350b2o$53351b2o$
53350bo21$53327b2o$53326bobo$53328bo45$53280b2o$53279bobo$53281bo25$
53253bo$53253b2o$53252bobo21$53230b2o$53229bobo$53231bo22$53206b3o$
53208bo$53207bo20$53184bo$53184b2o$53183bobo21$53161b2o$53160bobo$
53162bo21$53138b2o$53137bobo$53139bo21$53115b3o$53117bo$53116bo22$
53091b2o$53092b2o$53091bo21$53068b3o$53070bo$53069bo20$53046b2o$53045b
obo$53047bo21$53023b2o$53024b2o$53023bo20$53001bo$53001b2o$53000bobo
39$52960b3o$52962bo$52961bo20$52938bo$52938b2o$52937bobo21$52915b2o$
52914bobo$52916bo21$52892b2o$52893b2o$52892bo21$52869b3o$52871bo$
52870bo20$52847bo$52847b2o$52846bobo24$52821b2o$52820bobo$52822bo31$
52788b3o$52790bo$52789bo25$52761b2o$52762b2o$52761bo21$52738b3o$52740b
o$52739bo21$52715b2o$52714bobo$52716bo21$52692b2o$52693b2o$52692bo21$
52669b3o$52671bo$52670bo32$52635b3o$52637bo$52636bo20$52613bo$52613b2o
$52612bobo21$52590b2o$52591b2o$52590bo21$52567b3o$52569bo$52568bo33$
52532b3o$52534bo$52533bo21$52509b2o$52508bobo$52510bo26$52481b2o$
52480bobo$52482bo21$52458b2o$52459b2o$52458bo30$52426b2o$52425bobo$
52427bo21$52403b3o$52405bo$52404bo20$52381b2o$52380bobo$52382bo21$
52358b2o$52357bobo$52359bo21$52335b3o$52337bo$52336bo23$52310b3o$
52312bo$52311bo20$52288b2o$52287bobo$52289bo27$52259b2o$52260b2o$
52259bo21$52236b3o$52238bo$52237bo20$52214bo$52214b2o$52213bobo22$
52190b3o$52192bo$52191bo20$52168bo$52168b2o$52167bobo26$52140b3o$
52142bo$52141bo20$52118bo$52118b2o$52117bobo22$52094b3o$52096bo$52095b
o20$52072bo$52072b2o$52071bobo30$52040b2o$52039bobo$52041bo21$52017b2o
$52018b2o$52017bo20$51995bo$51995b2o$51994bobo27$51966b3o$51968bo$
51967bo20$51944b2o$51943bobo$51945bo21$51921b3o$51923bo$51922bo26$
51893bo$51893b2o$51892bobo21$51870b2o$51871b2o$51870bo35$51833b2o$
51832bobo$51834bo21$51810b3o$51812bo$51811bo22$51786b2o$51785bobo$
51787bo21$51763b3o$51765bo$51764bo20$51741bo$51741b2o$51740bobo24$
51715b2o$51714bobo$51716bo21$51692b3o$51694bo$51693bo20$51670b2o$
51669bobo$51671bo32$51636b2o$51637b2o$51636bo31$51603bo$51603b2o$
51602bobo21$51580b2o$51581b2o$51580bo20$51558bo$51558b2o$51557bobo22$
51534b3o$51536bo$51535bo20$51512bo$51512b2o$51511bobo26$51484b3o$
51486bo$51485bo20$51462bo$51462b2o$51461bobo22$51438b3o$51440bo$51439b
o20$51416bo$51416b2o$51415bobo27$51387b3o$51389bo$51388bo20$51365bo$
51365b2o$51364bobo31$51332bo$51332b2o$51331bobo21$51309b2o$51308bobo$
51310bo21$51286b2o$51287b2o$51286bo31$51253b2o$51252bobo$51254bo21$
51230b2o$51231b2o$51230bo20$51208bo$51208b2o$51207bobo23$51183b2o$
51184b2o$51183bo21$51160b3o$51162bo$51161bo20$51138b2o$51137bobo$
51139bo31$51105b2o$51106b2o$51105bo20$51083bo$51083b2o$51082bobo26$
51055bo$51055b2o$51054bobo31$51022bo$51022b2o$51021bobo21$50999b2o$
51000b2o$50999bo20$50977bo$50977b2o$50976bobo26$50949b3o$50951bo$
50950bo20$50927b2o$50926bobo$50928bo21$50904bo$50904b2o$50903bobo21$
50881b2o$50880bobo$50882bo21$50858b2o$50859b2o$50858bo32$50824b3o$
50826bo$50825bo20$50802bo$50802b2o$50801bobo34$50766bo$50766b2o$50765b
obo21$50743b2o$50744b2o$50743bo20$50721bo$50721b2o$50720bobo29$50690b
2o$50689bobo$50691bo21$50667b2o$50668b2o$50667bo20$50645bo$50645b2o$
50644bobo28$50615bo$50615b2o$50614bobo21$50592b2o$50593b2o$50592bo21$
50569b3o$50571bo$50570bo20$50547bo$50547b2o$50546bobo21$50524b2o$
50523bobo$50525bo39$50483b2o$50484b2o$50483bo20$50461bo$50461b2o$
50460bobo22$50437b2o$50436bobo$50438bo21$50414b2o$50415b2o$50414bo31$
50381bo$50381b2o$50380bobo21$50358b2o$50359b2o$50358bo25$50331b2o$
50330bobo$50332bo21$50308b3o$50310bo$50309bo21$50285b2o$50286b2o$
50285bo21$50262b3o$50264bo$50263bo20$50240bo$50240b2o$50239bobo23$
50215b2o$50216b2o$50215bo20$50193bo$50193b2o$50192bobo21$50170b2o$
50171b2o$50170bo23$50145b2o$50146b2o$50145bo20$50123bo$50123b2o$50122b
obo21$50100b2o$50101b2o$50100bo21$50077b3o$50079bo$50078bo20$50055bo$
50055b2o$50054bobo30$50023b2o$50024b2o$50023bo20$50001bo$50001b2o$
50000bobo27$49972bo$49972b2o$49971bobo21$49949b2o$49950b2o$49949bo20$
49927bo$49927b2o$49926bobo37$49888bo$49888b2o$49887bobo21$49865b2o$
49864bobo$49866bo23$49840bo$49840b2o$49839bobo21$49817b2o$49816bobo$
49818bo24$49791b2o$49790bobo$49792bo21$49768b3o$49770bo$49769bo26$
49740b2o$49739bobo$49741bo21$49717b3o$49719bo$49718bo25$49690b2o$
49691b2o$49690bo21$49667b3o$49669bo$49668bo21$49644b2o$49643bobo$
49645bo21$49621b2o$49622b2o$49621bo21$49598b3o$49600bo$49599bo21$
49575b3o$49577bo$49576bo20$49553b2o$49552bobo$49554bo22$49529bo$49529b
2o$49528bobo21$49506b2o$49505bobo$49507bo21$49483b3o$49485bo$49484bo
20$49461bo$49461b2o$49460bobo21$49438b2o$49439b2o$49438bo38$49398b2o$
49397bobo$49399bo21$49375b2o$49376b2o$49375bo21$49352b3o$49354bo$
49353bo20$49330bo$49330b2o$49329bobo21$49307b2o$49306bobo$49308bo21$
49284b2o$49285b2o$49284bo24$49258b3o$49260bo$49259bo30$49226b2o$49225b
obo$49227bo25$49199bo$49199b2o$49198bobo21$49176b2o$49175bobo$49177bo
22$49152b3o$49154bo$49153bo20$49130bo$49130b2o$49129bobo21$49107b2o$
49106bobo$49108bo32$49073b2o$49072bobo$49074bo21$49050b2o$49051b2o$
49050bo20$49028bo$49028b2o$49027bobo21$49005b2o$49004bobo$49006bo33$
48970b2o$48969bobo$48971bo22$48946b3o$48948bo$48947bo26$48918b3o$
48920bo$48919bo20$48896bo$48896b2o$48895bobo31$48863b3o$48865bo$48864b
o20$48841b2o$48840bobo$48842bo21$48818b3o$48820bo$48819bo21$48795b3o$
48797bo$48796bo20$48773b2o$48772bobo$48774bo23$48748b2o$48747bobo$
48749bo21$48725b3o$48727bo$48726bo26$48697bo$48697b2o$48696bobo21$
48674b2o$48673bobo$48675bo21$48651b2o$48652b2o$48651bo21$48628b2o$
48627bobo$48629bo21$48605b2o$48606b2o$48605bo25$48578b2o$48577bobo$
48579bo21$48555b2o$48556b2o$48555bo21$48532bo$48532b2o$48531bobo21$
48509b2o$48508bobo$48510bo21$48486b2o$48487b2o$48486bo32$48452b2o$
48453b2o$48452bo21$48429b3o$48431bo$48430bo20$48407b2o$48406bobo$
48408bo21$48384b2o$48385b2o$48384bo24$48358b2o$48359b2o$48358bo20$
48336bo$48336b2o$48335bobo21$48313b2o$48314b2o$48313bo20$48291bo$
48291b2o$48290bobo26$48263b2o$48264b2o$48263bo20$48241bo$48241b2o$
48240bobo21$48218b2o$48219b2o$48218bo22$48194bo$48194b2o$48193bobo21$
48171b2o$48170bobo$48172bo25$48144bo$48144b2o$48143bobo21$48121b2o$
48120bobo$48122bo21$48098bo$48098b2o$48097bobo21$48075b2o$48074bobo$
48076bo42$48031b3o$48033bo$48032bo20$48009b2o$48008bobo$48010bo21$
47986b2o$47987b2o$47986bo20$47964bo$47964b2o$47963bobo35$47927bo$
47927b2o$47926bobo21$47904b2o$47905b2o$47904bo23$47879b2o$47878bobo$
47880bo39$47838b2o$47839b2o$47838bo28$47808b2o$47807bobo$47809bo21$
47785b2o$47786b2o$47785bo34$47749b2o$47750b2o$47749bo20$47727bo$47727b
2o$47726bobo31$47694b3o$47696bo$47695bo20$47672b2o$47671bobo$47673bo
27$47643b2o$47644b2o$47643bo20$47621bo$47621b2o$47620bobo28$47591bo$
47591b2o$47590bobo21$47568b2o$47567bobo$47569bo23$47543bo$47543b2o$
47542bobo21$47520b2o$47519bobo$47521bo25$47493bo$47493b2o$47492bobo21$
47470b2o$47469bobo$47471bo22$47446b3o$47448bo$47447bo20$47424bo$47424b
2o$47423bobo21$47401b2o$47400bobo$47402bo21$47378b2o$47377bobo$47379bo
21$47355b3o$47357bo$47356bo22$47331b2o$47332b2o$47331bo21$47308b3o$
47310bo$47309bo20$47286b2o$47285bobo$47287bo21$47263b2o$47264b2o$
47263bo20$47241bo$47241b2o$47240bobo36$47203b3o$47205bo$47204bo20$
47181b2o$47180bobo$47182bo23$47156b3o$47158bo$47157bo20$47134bo$47134b
2o$47133bobo21$47111b2o$47112b2o$47111bo22$47087b3o$47089bo$47088bo20$
47065b2o$47064bobo$47066bo25$47038bo$47038b2o$47037bobo21$47015b2o$
47014bobo$47016bo21$46992bo$46992b2o$46991bobo21$46969b2o$46968bobo$
46970bo37$46930b2o$46931b2o$46930bo24$46904bo$46904b2o$46903bobo21$
46881b2o$46880bobo$46882bo21$46858b3o$46860bo$46859bo32$46824bo$46824b
2o$46823bobo21$46801b2o$46800bobo$46802bo24$46775b2o$46774bobo$46776bo
21$46752b2o$46753b2o$46752bo20$46730bo$46730b2o$46729bobo22$46706b3o$
46708bo$46707bo24$46680b3o$46682bo$46681bo20$46658bo$46658b2o$46657bob
o21$46635b2o$46634bobo$46636bo34$46599b2o$46600b2o$46599bo21$46576b3o$
46578bo$46577bo25$46549b2o$46548bobo$46550bo36$46511bo$46511b2o$46510b
obo39$46470b2o$46471b2o$46470bo20$46448bo$46448b2o$46447bobo21$46425b
2o$46424bobo$46426bo21$46402bo$46402b2o$46401bobo39$46361b2o$46360bobo
$46362bo25$46334bo$46334b2o$46333bobo21$46311b2o$46312b2o$46311bo21$
46288b2o$46287bobo$46289bo21$46265b2o$46266b2o$46265bo21$46242b3o$
46244bo$46243bo20$46220b2o$46219bobo$46221bo21$46197b3o$46199bo$46198b
o21$46174bo$46174b2o$46173bobo21$46151b2o$46150bobo$46152bo21$46128b3o
$46130bo$46129bo20$46106bo$46106b2o$46105bobo29$46075b2o$46074bobo$
46076bo21$46052b3o$46054bo$46053bo20$46030b2o$46029bobo$46031bo21$
46007b3o$46009bo$46008bo20$45985b2o$45984bobo$45986bo27$45956bo$45956b
2o$45955bobo21$45933b2o$45932bobo$45934bo21$45910b3o$45912bo$45911bo
20$45888b2o$45887bobo$45889bo21$45865b2o$45866b2o$45865bo21$45842b3o$
45844bo$45843bo20$45820bo$45820b2o$45819bobo25$45793bo$45793b2o$45792b
obo21$45770b2o$45769bobo$45771bo25$45743bo$45743b2o$45742bobo21$45720b
2o$45719bobo$45721bo22$45696b3o$45698bo$45697bo20$45674bo$45674b2o$
45673bobo21$45651b2o$45650bobo$45652bo21$45628b2o$45627bobo$45629bo21$
45605b3o$45607bo$45606bo27$45576bo$45576b2o$45575bobo21$45553b2o$
45554b2o$45553bo20$45531bo$45531b2o$45530bobo26$45503b3o$45505bo$
45504bo20$45481bo$45481b2o$45480bobo22$45457b2o$45458b2o$45457bo21$
45434b3o$45436bo$45435bo20$45412bo$45412b2o$45411bobo21$45389bo$45389b
2o$45388bobo21$45366b2o$45367b2o$45366bo34$45330b3o$45332bo$45331bo20$
45308b2o$45307bobo$45309bo21$45285b2o$45286b2o$45285bo37$45246bo$
45246b2o$45245bobo21$45223b2o$45222bobo$45224bo25$45196bo$45196b2o$
45195bobo21$45173b2o$45172bobo$45174bo22$45149b3o$45151bo$45150bo20$
45127bo$45127b2o$45126bobo21$45104b2o$45103bobo$45105bo21$45081b2o$
45080bobo$45082bo21$45058b3o$45060bo$45059bo22$45034b2o$45035b2o$
45034bo21$45011b3o$45013bo$45012bo20$44989b2o$44988bobo$44990bo21$
44966b2o$44967b2o$44966bo20$44944bo$44944b2o$44943bobo39$44903b3o$
44905bo$44904bo20$44881bo$44881b2o$44880bobo21$44858b2o$44857bobo$
44859bo21$44835b2o$44836b2o$44835bo21$44812b3o$44814bo$44813bo20$
44790bo$44790b2o$44789bobo24$44764b2o$44763bobo$44765bo31$44731b3o$
44733bo$44732bo25$44704b2o$44705b2o$44704bo20$44682bo$44682b2o$44681bo
bo22$44658b3o$44660bo$44659bo20$44636bo$44636b2o$44635bobo21$44613b2o$
44612bobo$44614bo21$44590b2o$44589bobo$44591bo21$44567b3o$44569bo$
44568bo20$44545b2o$44544bobo$44546bo21$44522b2o$44523b2o$44522bo20$
44500bo$44500b2o$44499bobo26$44472b2o$44473b2o$44472bo20$44450bo$
44450b2o$44449bobo21$44427b2o$44428b2o$44427bo21$44404b3o$44406bo$
44405bo29$44373b3o$44375bo$44374bo31$44340b2o$44341b2o$44340bo20$
44318bo$44318b2o$44317bobo21$44295b2o$44294bobo$44296bo26$44267bo$
44267b2o$44266bobo21$44244b2o$44245b2o$44244bo20$44222bo$44222b2o$
44221bobo21$44199b2o$44198bobo$44200bo25$44172bo$44172b2o$44171bobo21$
44149b2o$44148bobo$44150bo22$44125b3o$44127bo$44126bo20$44103bo$44103b
2o$44102bobo21$44080b2o$44079bobo$44081bo22$44056b2o$44055bobo$44057bo
21$44033b3o$44035bo$44034bo22$44009b2o$44010b2o$44009bo21$43986b3o$
43988bo$43987bo20$43964bo$43964b2o$43963bobo31$43931b2o$43932b2o$
43931bo21$43908bo$43908b2o$43907bobo21$43885b2o$43886b2o$43885bo24$
43859b2o$43858bobo$43860bo21$43836b3o$43838bo$43837bo21$43813bo$43813b
2o$43812bobo34$43777b2o$43776bobo$43778bo23$43752b2o$43753b2o$43752bo
25$43725b2o$43724bobo$43726bo21$43702b2o$43703b2o$43702bo21$43679bo$
43679b2o$43678bobo21$43656b2o$43655bobo$43657bo21$43633b2o$43634b2o$
43633bo32$43599b2o$43600b2o$43599bo21$43576b3o$43578bo$43577bo20$
43554b2o$43553bobo$43555bo21$43531b2o$43532b2o$43531bo33$43496b2o$
43497b2o$43496bo21$43473bo$43473b2o$43472bobo40$43431b2o$43432b2o$
43431bo20$43409bo$43409b2o$43408bobo21$43386b2o$43387b2o$43386bo21$
43363b3o$43365bo$43364bo21$43340b2o$43339bobo$43341bo23$43315bo$43315b
2o$43314bobo21$43292b2o$43293b2o$43292bo25$43265b2o$43264bobo$43266bo
21$43242b3o$43244bo$43243bo21$43219b2o$43220b2o$43219bo21$43196b3o$
43198bo$43197bo20$43174b2o$43173bobo$43175bo23$43149b2o$43148bobo$
43150bo31$43116b2o$43117b2o$43116bo23$43091b2o$43090bobo$43092bo21$
43068b3o$43070bo$43069bo26$43040b2o$43041b2o$43040bo22$43016b3o$43018b
o$43017bo25$42989b2o$42990b2o$42989bo21$42966b3o$42968bo$42967bo21$
42943b2o$42942bobo$42944bo21$42920b2o$42921b2o$42920bo21$42897b3o$
42899bo$42898bo32$42863b3o$42865bo$42864bo20$42841b2o$42840bobo$42842b
o21$42818b3o$42820bo$42819bo20$42796b2o$42795bobo$42797bo29$42765b2o$
42764bobo$42766bo21$42742b3o$42744bo$42743bo20$42720bo$42720b2o$42719b
obo25$42693b2o$42694b2o$42693bo35$42656bo$42656b2o$42655bobo36$42618b
3o$42620bo$42619bo20$42596b2o$42595bobo$42597bo21$42573b3o$42575bo$
42574bo26$42545b2o$42544bobo$42546bo21$42522b3o$42524bo$42523bo32$
42488b2o$42489b2o$42488bo38$42448b2o$42449b2o$42448bo21$42425b3o$
42427bo$42426bo21$42402b3o$42404bo$42403bo20$42380b2o$42379bobo$42381b
o25$42353bo$42353b2o$42352bobo21$42330b2o$42329bobo$42331bo22$42306b3o
$42308bo$42307bo20$42284bo$42284b2o$42283bobo21$42261b2o$42260bobo$
42262bo21$42238b2o$42237bobo$42239bo21$42215b3o$42217bo$42216bo22$
42191b2o$42192b2o$42191bo21$42168b3o$42170bo$42169bo20$42146b2o$42145b
obo$42147bo21$42123b2o$42124b2o$42123bo20$42101bo$42101b2o$42100bobo
36$42063b3o$42065bo$42064bo20$42041b2o$42040bobo$42042bo23$42016b3o$
42018bo$42017bo20$41994bo$41994b2o$41993bobo21$41971b2o$41972b2o$
41971bo22$41947b3o$41949bo$41948bo20$41925b2o$41924bobo$41926bo25$
41898bo$41898b2o$41897bobo21$41875b2o$41874bobo$41876bo21$41852bo$
41852b2o$41851bobo21$41829b2o$41830b2o$41829bo33$41794b2o$41795b2o$
41794bo35$41757bo$41757b2o$41756bobo31$41724bo$41724b2o$41723bobo51$
41671bo$41671b2o$41670bobo24$41645b2o$41644bobo$41646bo21$41622b3o$
41624bo$41623bo24$41596b2o$41595bobo$41597bo21$41573b2o$41574b2o$
41573bo20$41551bo$41551b2o$41550bobo21$41528b2o$41529b2o$41528bo39$
41487b2o$41486bobo$41488bo26$41459b3o$41461bo$41460bo28$41429b3o$
41431bo$41430bo20$41407b2o$41406bobo$41408bo21$41384b3o$41386bo$41385b
o21$41361b3o$41363bo$41362bo20$41339b2o$41338bobo$41340bo21$41316b3o$
41318bo$41317bo20$41294bo$41294b2o$41293bobo21$41271b2o$41272b2o$
41271bo27$41242b2o$41241bobo$41243bo21$41219b3o$41221bo$41220bo25$
41192b2o$41193b2o$41192bo21$41169b3o$41171bo$41170bo21$41146b2o$41145b
obo$41147bo21$41123b2o$41124b2o$41123bo21$41100b3o$41102bo$41101bo21$
41077b3o$41079bo$41078bo20$41055b2o$41054bobo$41056bo22$41031bo$41031b
2o$41030bobo21$41008b2o$41007bobo$41009bo21$40985b3o$40987bo$40986bo
20$40963bo$40963b2o$40962bobo21$40940b2o$40941b2o$40940bo38$40900b2o$
40899bobo$40901bo21$40877b2o$40878b2o$40877bo21$40854b3o$40856bo$
40855bo20$40832bo$40832b2o$40831bobo21$40809b2o$40808bobo$40810bo21$
40786b2o$40787b2o$40786bo24$40760b3o$40762bo$40761bo30$40728b2o$40727b
obo$40729bo25$40701bo$40701b2o$40700bobo21$40678b2o$40679b2o$40678bo
21$40655b2o$40654bobo$40656bo21$40632b2o$40633b2o$40632bo20$40610bo$
40610b2o$40609bobo22$40586b2o$40585bobo$40587bo21$40563b2o$40564b2o$
40563bo21$40540b3o$40542bo$40541bo25$40513b2o$40514b2o$40513bo21$
40490b3o$40492bo$40491bo20$40468b2o$40467bobo$40469bo21$40445b3o$
40447bo$40446bo20$40423bo$40423b2o$40422bobo23$40398b2o$40397bobo$
40399bo21$40375b3o$40377bo$40376bo22$40351b2o$40350bobo$40352bo21$
40328b3o$40330bo$40329bo20$40306b2o$40305bobo$40307bo28$40276b3o$
40278bo$40277bo20$40254bo$40254b2o$40253bobo21$40231b2o$40232b2o$
40231bo20$40209bo$40209b2o$40208bobo21$40186b2o$40187b2o$40186bo20$
40164bo$40164b2o$40163bobo21$40141b2o$40140bobo$40142bo25$40114bo$
40114b2o$40113bobo21$40091b2o$40090bobo$40092bo22$40067b3o$40069bo$
40068bo20$40045bo$40045b2o$40044bobo21$40022b2o$40021bobo$40023bo21$
39999b2o$39998bobo$40000bo21$39976b3o$39978bo$39977bo22$39952b2o$
39953b2o$39952bo21$39929b3o$39931bo$39930bo20$39907b2o$39906bobo$
39908bo21$39884b2o$39885b2o$39884bo20$39862bo$39862b2o$39861bobo39$
39821b3o$39823bo$39822bo20$39799bo$39799b2o$39798bobo21$39776b2o$
39775bobo$39777bo21$39753b2o$39754b2o$39753bo21$39730b3o$39732bo$
39731bo20$39708bo$39708b2o$39707bobo24$39682b2o$39681bobo$39683bo31$
39649b3o$39651bo$39650bo25$39622b2o$39623b2o$39622bo20$39600bo$39600b
2o$39599bobo22$39576b3o$39578bo$39577bo20$39554bo$39554b2o$39553bobo
21$39531b2o$39532b2o$39531bo22$39507b3o$39509bo$39508bo20$39485bo$
39485b2o$39484bobo21$39462b2o$39461bobo$39463bo25$39435bo$39435b2o$
39434bobo21$39412b2o$39411bobo$39413bo21$39389b3o$39391bo$39390bo20$
39367b2o$39366bobo$39368bo21$39344b2o$39345b2o$39344bo23$39319b3o$
39321bo$39320bo20$39297b2o$39296bobo$39298bo23$39272b3o$39274bo$39273b
o20$39250b2o$39249bobo$39251bo21$39227b3o$39229bo$39228bo27$39198b2o$
39197bobo$39199bo21$39175b2o$39176b2o$39175bo20$39153bo$39153b2o$
39152bobo21$39130b2o$39131b2o$39130bo20$39108bo$39108b2o$39107bobo21$
39085b2o$39086b2o$39085bo20$39063bo$39063b2o$39062bobo26$39035b3o$
39037bo$39036bo20$39013bo$39013b2o$39012bobo22$38989b3o$38991bo$38990b
o20$38967b2o$38966bobo$38968bo33$38932b2o$38931bobo$38933bo36$38894b3o
$38896bo$38895bo26$38866b2o$38867b2o$38866bo20$38844bo$38844b2o$38843b
obo21$38821b2o$38822b2o$38821bo20$38799bo$38799b2o$38798bobo21$38776b
2o$38777b2o$38776bo21$38753b3o$38755bo$38754bo32$38719b3o$38721bo$
38720bo27$38690bo$38690b2o$38689bobo30$38658b2o$38657bobo$38659bo21$
38635b3o$38637bo$38636bo36$38597b2o$38596bobo$38598bo34$38561b3o$
38563bo$38562bo31$38528b3o$38530bo$38529bo20$38506bo$38506b2o$38505bob
o21$38483b2o$38482bobo$38484bo21$38460b3o$38462bo$38461bo25$38433b2o$
38434b2o$38433bo20$38411bo$38411b2o$38410bobo22$38387b3o$38389bo$
38388bo20$38365bo$38365b2o$38364bobo21$38342b2o$38341bobo$38343bo21$
38319b2o$38318bobo$38320bo21$38296b3o$38298bo$38297bo20$38274b2o$
38273bobo$38275bo21$38251b2o$38252b2o$38251bo20$38229bo$38229b2o$
38228bobo26$38201b2o$38202b2o$38201bo20$38179bo$38179b2o$38178bobo21$
38156b2o$38157b2o$38156bo21$38133b3o$38135bo$38134bo29$38102b3o$38104b
o$38103bo31$38069b2o$38070b2o$38069bo20$38047bo$38047b2o$38046bobo21$
38024b2o$38023bobo$38025bo26$37996bo$37996b2o$37995bobo21$37973b2o$
37974b2o$37973bo20$37951bo$37951b2o$37950bobo21$37928b2o$37927bobo$
37929bo25$37901bo$37901b2o$37900bobo21$37878b2o$37879b2o$37878bo21$
37855b2o$37854bobo$37856bo21$37832b2o$37833b2o$37832bo21$37809b3o$
37811bo$37810bo31$37776bo$37776b2o$37775bobo21$37753b2o$37752bobo$
37754bo34$37717b2o$37716bobo$37718bo21$37694b3o$37696bo$37695bo20$
37672b2o$37671bobo$37673bo29$37641b2o$37642b2o$37641bo21$37618b3o$
37620bo$37619bo20$37596b2o$37595bobo$37597bo28$37566b2o$37565bobo$
37567bo21$37543b3o$37545bo$37544bo20$37521bo$37521b2o$37520bobo21$
37498b2o$37497bobo$37499bo21$37475b2o$37476b2o$37475bo39$37434b3o$
37436bo$37435bo20$37412b2o$37411bobo$37413bo22$37388b2o$37389b2o$
37388bo21$37365b3o$37367bo$37366bo31$37332b2o$37331bobo$37333bo21$
37309b3o$37311bo$37310bo25$37282b2o$37283b2o$37282bo21$37259b3o$37261b
o$37260bo21$37236b2o$37235bobo$37237bo21$37213b2o$37214b2o$37213bo21$
37190b3o$37192bo$37191bo22$37166b3o$37168bo$37167bo20$37144b2o$37143bo
bo$37145bo32$37110b2o$37111b2o$37110bo20$37088bo$37088b2o$37087bobo26$
37060b3o$37062bo$37061bo20$37038bo$37038b2o$37037bobo22$37014b2o$
37015b2o$37014bo21$36991b3o$36993bo$36992bo20$36969bo$36969b2o$36968bo
bo25$36942b3o$36944bo$36943bo20$36920bo$36920b2o$36919bobo21$36897b2o$
36898b2o$36897bo21$36874b3o$36876bo$36875bo22$36850b2o$36849bobo$
36851bo21$36827b2o$36828b2o$36827bo20$36805bo$36805b2o$36804bobo30$
36773b2o$36772bobo$36774bo41$36730b2o$36729bobo$36731bo21$36707b2o$
36706bobo$36708bo21$36684b3o$36686bo$36685bo25$36657b2o$36658b2o$
36657bo21$36634b3o$36636bo$36635bo21$36611b2o$36610bobo$36612bo21$
36588b2o$36589b2o$36588bo21$36565b3o$36567bo$36566bo32$36531b3o$36533b
o$36532bo20$36509bo$36509b2o$36508bobo21$36486b2o$36487b2o$36486bo21$
36463b3o$36465bo$36464bo40$36421b3o$36423bo$36422bo20$36399b2o$36398bo
bo$36400bo21$36376b3o$36378bo$36377bo22$36352b2o$36353b2o$36352bo21$
36329b3o$36331bo$36330bo20$36307bo$36307b2o$36306bobo21$36284b2o$
36283bobo$36285bo21$36261b3o$36263bo$36262bo27$36232b3o$36234bo$36233b
o20$36210b2o$36209bobo$36211bo21$36187b3o$36189bo$36188bo20$36165b2o$
36164bobo$36166bo21$36142b3o$36144bo$36143bo20$36120b2o$36119bobo$
36121bo21$36097b3o$36099bo$36098bo25$36070b2o$36071b2o$36070bo21$
36047b3o$36049bo$36048bo21$36024b2o$36025b2o$36024bo21$36001b3o$36003b
o$36002bo29$35970bo$35970b2o$35969bobo21$35947b2o$35946bobo$35948bo21$
35924b3o$35926bo$35925bo26$35896b2o$35897b2o$35896bo20$35874bo$35874b
2o$35873bobo21$35851b2o$35852b2o$35851bo26$35823b3o$35825bo$35824bo20$
35801b2o$35800bobo$35802bo26$35773b2o$35774b2o$35773bo21$35750b3o$
35752bo$35751bo20$35728bo$35728b2o$35727bobo21$35705b2o$35704bobo$
35706bo21$35682b3o$35684bo$35683bo25$35655b2o$35656b2o$35655bo21$
35632b3o$35634bo$35633bo21$35609b2o$35608bobo$35610bo21$35586b2o$
35587b2o$35586bo21$35563b3o$35565bo$35564bo32$35529b3o$35531bo$35530bo
20$35507bo$35507b2o$35506bobo21$35484b2o$35485b2o$35484bo21$35461b3o$
35463bo$35462bo23$35436b2o$35437b2o$35436bo20$35414bo$35414b2o$35413bo
bo21$35391b2o$35392b2o$35391bo20$35369bo$35369b2o$35368bobo21$35346bo$
35346b2o$35345bobo21$35323b2o$35324b2o$35323bo34$35287b2o$35288b2o$
35287bo20$35265bo$35265b2o$35264bobo21$35242b2o$35241bobo$35243bo21$
35219b3o$35221bo$35220bo20$35197b2o$35196bobo$35198bo30$35165b3o$
35167bo$35166bo20$35143bo$35143b2o$35142bobo26$35115b3o$35117bo$35116b
o20$35093bo$35093b2o$35092bobo22$35069b3o$35071bo$35070bo20$35047bo$
35047b2o$35046bobo21$35024bo$35024b2o$35023bobo21$35001b2o$35002b2o$
35001bo20$34979bo$34979b2o$34978bobo21$34956b2o$34957b2o$34956bo36$
34918b3o$34920bo$34919bo21$34895b2o$34896b2o$34895bo20$34873bo$34873b
2o$34872bobo34$34837b2o$34836bobo$34838bo32$34803b3o$34805bo$34804bo
21$34780b2o$34779bobo$34781bo21$34757b3o$34759bo$34758bo20$34735b2o$
34734bobo$34736bo21$34712b3o$34714bo$34713bo25$34685b2o$34686b2o$
34685bo21$34662b3o$34664bo$34663bo20$34640b2o$34639bobo$34641bo25$
34613bo$34613b2o$34612bobo21$34590b2o$34589bobo$34591bo21$34567bo$
34567b2o$34566bobo21$34544b2o$34543bobo$34545bo37$34505b2o$34504bobo$
34506bo21$34482b2o$34483b2o$34482bo21$34459b3o$34461bo$34460bo29$
34428b2o$34427bobo$34429bo21$34405b3o$34407bo$34406bo20$34383bo$34383b
2o$34382bobo21$34360b2o$34359bobo$34361bo21$34337b2o$34338b2o$34337bo
35$34300b3o$34302bo$34301bo20$34278b2o$34277bobo$34279bo26$34250bo$
34250b2o$34249bobo21$34227b2o$34228b2o$34227bo23$34202bo$34202b2o$
34201bobo21$34179b2o$34180b2o$34179bo21$34156b3o$34158bo$34157bo20$
34134bo$34134b2o$34133bobo26$34106b3o$34108bo$34107bo20$34084bo$34084b
2o$34083bobo22$34060b3o$34062bo$34061bo20$34038bo$34038b2o$34037bobo
30$34006b2o$34005bobo$34007bo21$33983b2o$33984b2o$33983bo20$33961bo$
33961b2o$33960bobo27$33932b3o$33934bo$33933bo20$33910b2o$33909bobo$
33911bo21$33887b3o$33889bo$33888bo26$33859bo$33859b2o$33858bobo21$
33836b2o$33837b2o$33836bo35$33799b2o$33798bobo$33800bo21$33776b3o$
33778bo$33777bo22$33752b2o$33751bobo$33753bo21$33729b3o$33731bo$33730b
o20$33707bo$33707b2o$33706bobo24$33681b2o$33680bobo$33682bo21$33658b3o
$33660bo$33659bo20$33636b2o$33635bobo$33637bo32$33602b2o$33603b2o$
33602bo31$33569bo$33569b2o$33568bobo21$33546b2o$33547b2o$33546bo20$
33524bo$33524b2o$33523bobo22$33500b3o$33502bo$33501bo20$33478bo$33478b
2o$33477bobo26$33450b3o$33452bo$33451bo20$33428bo$33428b2o$33427bobo
22$33404b3o$33406bo$33405bo20$33382bo$33382b2o$33381bobo37$33343b2o$
33342bobo$33344bo25$33316b3o$33318bo$33317bo20$33294bo$33294b2o$33293b
obo21$33271b2o$33272b2o$33271bo33$33236b3o$33238bo$33237bo20$33214bo$
33214b2o$33213bobo24$33188bo$33188b2o$33187bobo21$33165b2o$33164bobo$
33166bo21$33142b3o$33144bo$33143bo21$33119b2o$33120b2o$33119bo24$
33093b2o$33094b2o$33093bo21$33070b3o$33072bo$33071bo20$33048bo$33048b
2o$33047bobo34$33012b2o$33011bobo$33013bo21$32989b2o$32990b2o$32989bo
25$32962bo$32962b2o$32961bobo37$32923b3o$32925bo$32924bo38$32883b2o$
32882bobo$32884bo21$32860b3o$32862bo$32861bo20$32838bo$32838b2o$32837b
obo22$32814b3o$32816bo$32815bo38$32774bo$32774b2o$32773bobo26$32746b3o
$32748bo$32747bo20$32724b2o$32723bobo$32725bo21$32701bo$32701b2o$
32700bobo21$32678b2o$32677bobo$32679bo21$32655b2o$32656b2o$32655bo22$
32631bo$32631b2o$32630bobo21$32608b2o$32609b2o$32608bo20$32586bo$
32586b2o$32585bobo22$32562b3o$32564bo$32563bo20$32540bo$32540b2o$
32539bobo21$32517b2o$32518b2o$32517bo20$32495bo$32495b2o$32494bobo21$
32472b2o$32473b2o$32472bo59$32411bo$32411b2o$32410bobo21$32388b2o$
32389b2o$32388bo25$32361b2o$32360bobo$32362bo21$32338b2o$32339b2o$
32338bo21$32315b2o$32316b2o$32315bo20$32293bo$32293b2o$32292bobo21$
32270b2o$32271b2o$32270bo20$32248bo$32248b2o$32247bobo22$32224b3o$
32226bo$32225bo20$32202b2o$32201bobo$32203bo25$32175bo$32175b2o$32174b
obo21$32152b2o$32151bobo$32153bo22$32128b3o$32130bo$32129bo20$32106bo$
32106b2o$32105bobo21$32083b2o$32082bobo$32084bo21$32060b2o$32059bobo$
32061bo21$32037b3o$32039bo$32038bo22$32013b2o$32014b2o$32013bo21$
31990b3o$31992bo$31991bo20$31968b2o$31967bobo$31969bo21$31945b2o$
31946b2o$31945bo20$31923bo$31923b2o$31922bobo39$31882b3o$31884bo$
31883bo20$31860bo$31860b2o$31859bobo21$31837b2o$31836bobo$31838bo21$
31814b2o$31815b2o$31814bo21$31791b3o$31793bo$31792bo20$31769bo$31769b
2o$31768bobo24$31743b2o$31742bobo$31744bo31$31710b3o$31712bo$31711bo
25$31683b2o$31684b2o$31683bo20$31661bo$31661b2o$31660bobo22$31637b3o$
31639bo$31638bo20$31615bo$31615b2o$31614bobo21$31592b2o$31593b2o$
31592bo22$31568b3o$31570bo$31569bo20$31546bo$31546b2o$31545bobo21$
31523b2o$31522bobo$31524bo25$31496bo$31496b2o$31495bobo21$31473b2o$
31472bobo$31474bo21$31450b3o$31452bo$31451bo20$31428b2o$31427bobo$
31429bo21$31405b2o$31406b2o$31405bo23$31380b3o$31382bo$31381bo20$
31358b2o$31357bobo$31359bo23$31333b3o$31335bo$31334bo20$31311b2o$
31310bobo$31312bo21$31288b3o$31290bo$31289bo27$31259b2o$31258bobo$
31260bo21$31236b2o$31237b2o$31236bo20$31214bo$31214b2o$31213bobo21$
31191b2o$31192b2o$31191bo20$31169bo$31169b2o$31168bobo21$31146b2o$
31147b2o$31146bo21$31123b3o$31125bo$31124bo25$31096b2o$31097b2o$31096b
o20$31074bo$31074b2o$31073bobo22$31050b3o$31052bo$31051bo20$31028bo$
31028b2o$31027bobo21$31005b2o$31006b2o$31005bo22$30981b3o$30983bo$
30982bo20$30959bo$30959b2o$30958bobo21$30936b2o$30935bobo$30937bo33$
30901b3o$30903bo$30902bo37$30862b2o$30863b2o$30862bo22$30838b2o$30839b
2o$30838bo20$30816bo$30816b2o$30815bobo28$30786bo$30786b2o$30785bobo
21$30763b2o$30762bobo$30764bo22$30739bo$30739b2o$30738bobo25$30712b2o$
30711bobo$30713bo21$30689b3o$30691bo$30690bo20$30667b2o$30666bobo$
30668bo21$30644bo$30644b2o$30643bobo45$30597bo$30597b2o$30596bobo26$
30569b3o$30571bo$30570bo20$30547bo$30547b2o$30546bobo22$30523b3o$
30525bo$30524bo20$30501bo$30501b2o$30500bobo21$30478bo$30478b2o$30477b
obo21$30455b2o$30456b2o$30455bo22$30431b2o$30430bobo$30432bo21$30408b
2o$30409b2o$30408bo27$30379b2o$30380b2o$30379bo21$30356b3o$30358bo$
30357bo24$30330b2o$30329bobo$30331bo21$30307b3o$30309bo$30308bo20$
30285b2o$30284bobo$30286bo23$30260b2o$30261b2o$30260bo21$30237b3o$
30239bo$30238bo34$30201b2o$30200bobo$30202bo22$30177b2o$30176bobo$
30178bo21$30154b3o$30156bo$30155bo20$30132b2o$30131bobo$30133bo36$
30094bo$30094b2o$30093bobo21$30071b2o$30070bobo$30072bo21$30048b2o$
30047bobo$30049bo21$30025b3o$30027bo$30026bo26$29997b2o$29998b2o$
29997bo22$29973b3o$29975bo$29974bo20$29951bo$29951b2o$29950bobo26$
29923b3o$29925bo$29924bo20$29901b2o$29900bobo$29902bo21$29878bo$29878b
2o$29877bobo21$29855b2o$29854bobo$29856bo21$29832b2o$29833b2o$29832bo
33$29797bo$29797b2o$29796bobo21$29774b2o$29773bobo$29775bo25$29747bo$
29747b2o$29746bobo21$29724b2o$29725b2o$29724bo21$29701b2o$29702b2o$
29701bo20$29679bo$29679b2o$29678bobo23$29654bo$29654b2o$29653bobo21$
29631b2o$29632b2o$29631bo20$29609bo$29609b2o$29608bobo39$29568b2o$
29567bobo$29569bo42$29524bo$29524b2o$29523bobo21$29501b2o$29502b2o$
29501bo20$29479bo$29479b2o$29478bobo21$29456b2o$29457b2o$29456bo28$
29426b2o$29425bobo$29427bo21$29403b2o$29404b2o$29403bo21$29380b3o$
29382bo$29381bo22$29356b3o$29358bo$29357bo20$29334bo$29334b2o$29333bob
o34$29298b2o$29297bobo$29299bo21$29275b2o$29276b2o$29275bo25$29248b2o$
29247bobo$29249bo21$29225b2o$29226b2o$29225bo21$29202bo$29202b2o$
29201bobo21$29179b2o$29178bobo$29180bo21$29156b2o$29157b2o$29156bo21$
29133b2o$29134b2o$29133bo20$29111bo$29111b2o$29110bobo23$29086b3o$
29088bo$29087bo20$29064bo$29064b2o$29063bobo21$29041b2o$29042b2o$
29041bo21$29018b3o$29020bo$29019bo20$28996b2o$28995bobo$28997bo38$
28956bo$28956b2o$28955bobo21$28933b2o$28932bobo$28934bo21$28910b2o$
28911b2o$28910bo21$28887b3o$28889bo$28888bo20$28865bo$28865b2o$28864bo
bo21$28842b2o$28841bobo$28843bo24$28816b2o$28817b2o$28816bo30$28784bo$
28784b2o$28783bobo26$28756b3o$28758bo$28757bo20$28734b2o$28733bobo$
28735bo21$28711bo$28711b2o$28710bobo21$28688b2o$28687bobo$28689bo21$
28665b2o$28666b2o$28665bo32$28631b3o$28633bo$28632bo20$28609bo$28609b
2o$28608bobo34$28573bo$28573b2o$28572bobo21$28550b2o$28551b2o$28550bo
20$28528bo$28528b2o$28527bobo29$28497b2o$28496bobo$28498bo21$28474b2o$
28475b2o$28474bo20$28452bo$28452b2o$28451bobo28$28422bo$28422b2o$
28421bobo21$28399b2o$28400b2o$28399bo21$28376b3o$28378bo$28377bo20$
28354bo$28354b2o$28353bobo21$28331b2o$28330bobo$28332bo39$28290b2o$
28291b2o$28290bo20$28268bo$28268b2o$28267bobo22$28244b2o$28243bobo$
28245bo21$28221b2o$28222b2o$28221bo31$28188bo$28188b2o$28187bobo21$
28165b2o$28164bobo$28166bo25$28138bo$28138b2o$28137bobo21$28115b2o$
28114bobo$28116bo22$28091b3o$28093bo$28092bo20$28069bo$28069b2o$28068b
obo21$28046b2o$28045bobo$28047bo21$28023b2o$28022bobo$28024bo21$28000b
3o$28002bo$28001bo22$27976b2o$27977b2o$27976bo21$27953b3o$27955bo$
27954bo20$27931b2o$27930bobo$27932bo21$27908b2o$27909b2o$27908bo20$
27886bo$27886b2o$27885bobo39$27845b3o$27847bo$27846bo20$27823bo$27823b
2o$27822bobo21$27800b2o$27799bobo$27801bo21$27777b2o$27778b2o$27777bo
21$27754b3o$27756bo$27755bo20$27732bo$27732b2o$27731bobo24$27706b2o$
27705bobo$27707bo31$27673b3o$27675bo$27674bo25$27646b2o$27647b2o$
27646bo20$27624bo$27624b2o$27623bobo22$27600b3o$27602bo$27601bo20$
27578bo$27578b2o$27577bobo21$27555b2o$27554bobo$27556bo21$27532b3o$
27534bo$27533bo20$27510b2o$27509bobo$27511bo23$27485b2o$27484bobo$
27486bo21$27462b3o$27464bo$27463bo20$27440b2o$27439bobo$27441bo35$
27403b3o$27405bo$27404bo22$27379b3o$27381bo$27380bo20$27357b2o$27356bo
bo$27358bo21$27334b3o$27336bo$27335bo22$27310bo$27310b2o$27309bobo40$
27268b3o$27270bo$27269bo20$27246b2o$27245bobo$27247bo21$27223b3o$
27225bo$27224bo20$27201bo$27201b2o$27200bobo21$27178b2o$27177bobo$
27179bo21$27155b3o$27157bo$27156bo20$27133bo$27133b2o$27132bobo21$
27110b2o$27111b2o$27110bo20$27088bo$27088b2o$27087bobo21$27065b2o$
27064bobo$27066bo21$27042b2o$27043b2o$27042bo25$27015b2o$27014bobo$
27016bo21$26992b2o$26993b2o$26992bo21$26969bo$26969b2o$26968bobo21$
26946b2o$26945bobo$26947bo21$26923b2o$26924b2o$26923bo32$26889b2o$
26890b2o$26889bo20$26867bo$26867b2o$26866bobo21$26844b2o$26845b2o$
26844bo20$26822bo$26822b2o$26821bobo29$26791bo$26791b2o$26790bobo21$
26768b2o$26769b2o$26768bo21$26745b3o$26747bo$26746bo24$26719b2o$26718b
obo$26720bo36$26681b3o$26683bo$26682bo35$26644b2o$26645b2o$26644bo20$
26622bo$26622b2o$26621bobo21$26599b2o$26600b2o$26599bo26$26571bo$
26571b2o$26570bobo21$26548b2o$26549b2o$26548bo32$26514b2o$26513bobo$
26515bo38$26474b2o$26473bobo$26475bo21$26451b2o$26452b2o$26451bo21$
26428b2o$26429b2o$26428bo20$26406bo$26406b2o$26405bobo26$26378b3o$
26380bo$26379bo20$26356bo$26356b2o$26355bobo22$26332b3o$26334bo$26333b
o20$26310bo$26310b2o$26309bobo21$26287bo$26287b2o$26286bobo21$26264b2o
$26265b2o$26264bo22$26240b2o$26239bobo$26241bo21$26217b2o$26218b2o$
26217bo27$26188b2o$26189b2o$26188bo21$26165b3o$26167bo$26166bo27$
26136bo$26136b2o$26135bobo21$26113b2o$26114b2o$26113bo20$26091bo$
26091b2o$26090bobo21$26068b2o$26067bobo$26069bo24$26042b2o$26041bobo$
26043bo23$26017b2o$26018b2o$26017bo20$25995bo$25995b2o$25994bobo21$
25972bo$25972b2o$25971bobo22$25948b2o$25949b2o$25948bo21$25925b3o$
25927bo$25926bo22$25901b2o$25902b2o$25901bo21$25878b3o$25880bo$25879bo
21$25855b3o$25857bo$25856bo20$25833bo$25833b2o$25832bobo23$25808b2o$
25809b2o$25808bo20$25786bo$25786b2o$25785bobo26$25758b3o$25760bo$
25759bo20$25736bo$25736b2o$25735bobo22$25712b3o$25714bo$25713bo20$
25690bo$25690b2o$25689bobo35$25653b3o$25655bo$25654bo51$25600bo$25600b
2o$25599bobo25$25573b2o$25574b2o$25573bo20$25551bo$25551b2o$25550bobo
21$25528b2o$25529b2o$25528bo21$25505b3o$25507bo$25506bo20$25483bo$
25483b2o$25482bobo42$25439b2o$25440b2o$25439bo20$25417bo$25417b2o$
25416bobo38$25377b2o$25378b2o$25377bo20$25355bo$25355b2o$25354bobo21$
25332b2o$25333b2o$25332bo20$25310bo$25310b2o$25309bobo21$25287b2o$
25286bobo$25288bo32$25253bo$25253b2o$25252bobo21$25230b2o$25231b2o$
25230bo21$25207b3o$25209bo$25208bo29$25176bo$25176b2o$25175bobo21$
25153b2o$25154b2o$25153bo25$25126b2o$25125bobo$25127bo21$25103b2o$
25104b2o$25103bo21$25080b2o$25079bobo$25081bo21$25057b2o$25058b2o$
25057bo41$25014bo$25014b2o$25013bobo21$24991b2o$24992b2o$24991bo21$
24968b3o$24970bo$24969bo20$24946b2o$24945bobo$24947bo35$24909b2o$
24908bobo$24910bo21$24886b3o$24888bo$24887bo23$24861b2o$24862b2o$
24861bo39$24820b3o$24822bo$24821bo34$24784b2o$24783bobo$24785bo21$
24761b3o$24763bo$24762bo33$24726bo$24726b2o$24725bobo21$24703b2o$
24702bobo$24704bo21$24680b2o$24681b2o$24680bo20$24658bo$24658b2o$
24657bobo29$24627b2o$24626bobo$24628bo21$24604b3o$24606bo$24605bo20$
24582bo$24582b2o$24581bobo31$24549bo$24549b2o$24548bobo23$24524b2o$
24523bobo$24525bo25$24497bo$24497b2o$24496bobo21$24474b2o$24475b2o$
24474bo21$24451b2o$24450bobo$24452bo21$24428b2o$24429b2o$24428bo21$
24405b3o$24407bo$24406bo33$24370b2o$24369bobo$24371bo21$24347b3o$
24349bo$24348bo25$24320b2o$24321b2o$24320bo21$24297b3o$24299bo$24298bo
21$24274b3o$24276bo$24275bo20$24252b2o$24251bobo$24253bo21$24229b2o$
24228bobo$24230bo21$24206b3o$24208bo$24207bo27$24177b2o$24176bobo$
24178bo21$24154b2o$24155b2o$24154bo21$24131b3o$24133bo$24132bo20$
24109b2o$24108bobo$24110bo21$24086b3o$24088bo$24087bo27$24057bo$24057b
2o$24056bobo21$24034b2o$24033bobo$24035bo25$24007bo$24007b2o$24006bobo
21$23984b2o$23983bobo$23985bo21$23961bo$23961b2o$23960bobo21$23938b2o$
23937bobo$23939bo34$23902bo$23902b2o$23901bobo52$23848b2o$23847bobo$
23849bo25$23821b3o$23823bo$23822bo20$23799b2o$23798bobo$23800bo21$
23776b3o$23778bo$23777bo20$23754bo$23754b2o$23753bobo21$23731b2o$
23730bobo$23732bo42$23687b3o$23689bo$23688bo20$23665b2o$23664bobo$
23666bo38$23625b3o$23627bo$23626bo20$23603b2o$23602bobo$23604bo21$
23580b3o$23582bo$23581bo20$23558b2o$23557bobo$23559bo21$23535b2o$
23536b2o$23535bo32$23501b2o$23500bobo$23502bo21$23478b3o$23480bo$
23479bo20$23456bo$23456b2o$23455bobo30$23424b2o$23423bobo$23425bo21$
23401b3o$23403bo$23402bo25$23374b2o$23375b2o$23374bo21$23351b3o$23353b
o$23352bo21$23328b2o$23329b2o$23328bo20$23306bo$23306b2o$23305bobo42$
23262b3o$23264bo$23263bo20$23240b2o$23239bobo$23241bo21$23217b3o$
23219bo$23218bo20$23195b2o$23194bobo$23196bo21$23172b3o$23174bo$23173b
o20$23150b2o$23149bobo$23151bo33$23115bo$23115b2o$23114bobo21$23092b2o
$23093b2o$23092bo20$23070bo$23070b2o$23069bobo22$23046bo$23046b2o$
23045bobo21$23023b2o$23022bobo$23024bo31$22990b2o$22989bobo$22991bo21$
22967b3o$22969bo$22968bo23$22942b3o$22944bo$22943bo20$22920b2o$22919bo
bo$22921bo21$22897b2o$22898b2o$22897bo28$22867b3o$22869bo$22868bo20$
22845b2o$22844bobo$22846bo21$22822b3o$22824bo$22823bo20$22800b2o$
22799bobo$22801bo25$22773bo$22773b2o$22772bobo21$22750b2o$22749bobo$
22751bo21$22727bo$22727b2o$22726bobo21$22704b2o$22703bobo$22705bo22$
22680bo$22680b2o$22679bobo21$22657b2o$22656bobo$22658bo21$22634b2o$
22635b2o$22634bo24$22608bo$22608b2o$22607bobo21$22585b2o$22584bobo$
22586bo21$22562b3o$22564bo$22563bo20$22540b2o$22539bobo$22541bo21$
22517b3o$22519bo$22518bo20$22495b2o$22494bobo$22496bo21$22472b3o$
22474bo$22473bo20$22450bo$22450b2o$22449bobo39$22409b2o$22408bobo$
22410bo21$22386b3o$22388bo$22387bo20$22364b2o$22363bobo$22365bo24$
22338b2o$22337bobo$22339bo21$22315b2o$22316b2o$22315bo25$22288b2o$
22287bobo$22289bo21$22265b2o$22266b2o$22265bo21$22242b2o$22241bobo$
22243bo21$22219b2o$22220b2o$22219bo34$22183b2o$22182bobo$22184bo52$
22129b2o$22130b2o$22129bo24$22103bo$22103b2o$22102bobo21$22080b2o$
22081b2o$22080bo20$22058bo$22058b2o$22057bobo21$22035b2o$22034bobo$
22036bo21$22012b2o$22013b2o$22012bo41$21969bo$21969b2o$21968bobo21$
21946b2o$21947b2o$21946bo37$21907bo$21907b2o$21906bobo21$21884b2o$
21885b2o$21884bo20$21862bo$21862b2o$21861bobo21$21839b2o$21840b2o$
21839bo21$21816b3o$21818bo$21817bo32$21782b2o$21783b2o$21782bo20$
21760bo$21760b2o$21759bobo21$21737b2o$21736bobo$21738bo30$21705b2o$
21706b2o$21705bo20$21683bo$21683b2o$21682bobo26$21655b3o$21657bo$
21656bo20$21633bo$21633b2o$21632bobo22$21609b3o$21611bo$21610bo20$
21587bo$21587b2o$21586bobo30$21555b2o$21554bobo$21556bo21$21532b2o$
21533b2o$21532bo20$21510bo$21510b2o$21509bobo27$21481b3o$21483bo$
21482bo20$21459b2o$21458bobo$21460bo21$21436b3o$21438bo$21437bo26$
21408bo$21408b2o$21407bobo21$21385b2o$21386b2o$21385bo35$21348b2o$
21347bobo$21349bo21$21325b3o$21327bo$21326bo22$21301b2o$21300bobo$
21302bo21$21278b3o$21280bo$21279bo20$21256bo$21256b2o$21255bobo24$
21230b2o$21229bobo$21231bo21$21207b3o$21209bo$21208bo20$21185b2o$
21184bobo$21186bo32$21151b2o$21152b2o$21151bo31$21118bo$21118b2o$
21117bobo21$21095b2o$21096b2o$21095bo20$21073bo$21073b2o$21072bobo22$
21049b3o$21051bo$21050bo20$21027bo$21027b2o$21026bobo26$20999b3o$
21001bo$21000bo20$20977bo$20977b2o$20976bobo22$20953b2o$20954b2o$
20953bo21$20930b3o$20932bo$20931bo20$20908bo$20908b2o$20907bobo21$
20885bo$20885b2o$20884bobo21$20862b2o$20863b2o$20862bo22$20838b2o$
20837bobo$20839bo21$20815b2o$20816b2o$20815bo20$20793bo$20793b2o$
20792bobo21$20770b2o$20769bobo$20771bo21$20747b3o$20749bo$20748bo38$
20707b2o$20708b2o$20707bo21$20684b3o$20686bo$20685bo20$20662bo$20662b
2o$20661bobo21$20639b2o$20638bobo$20640bo21$20616b2o$20617b2o$20616bo
21$20593b3o$20595bo$20594bo23$20568bo$20568b2o$20567bobo31$20535b2o$
20536b2o$20535bo25$20508b2o$20507bobo$20509bo21$20485b3o$20487bo$
20486bo21$20462b2o$20463b2o$20462bo21$20439b3o$20441bo$20440bo20$
20417bo$20417b2o$20416bobo32$20383b2o$20382bobo$20384bo21$20360b2o$
20361b2o$20360bo34$20324b2o$20325b2o$20324bo20$20302bo$20302b2o$20301b
obo21$20279b2o$20280b2o$20279bo29$20248b3o$20250bo$20249bo20$20226bo$
20226b2o$20225bobo21$20203b2o$20204b2o$20203bo28$20173b2o$20174b2o$
20173bo20$20151bo$20151b2o$20150bobo21$20128b2o$20127bobo$20129bo21$
20105b2o$20106b2o$20105bo21$20082b3o$20084bo$20083bo38$20042bo$20042b
2o$20041bobo21$20019b2o$20020b2o$20019bo22$19995b3o$19997bo$19996bo20$
19973bo$19973b2o$19972bobo32$19939b2o$19940b2o$19939bo21$19916b3o$
19918bo$19917bo25$19889b2o$19890b2o$19889bo21$19866b3o$19868bo$19867bo
21$19843b2o$19844b2o$19843bo20$19821bo$19821b2o$19820bobo31$19788b3o$
19790bo$19789bo35$19751b3o$19753bo$19752bo20$19729bo$19729b2o$19728bob
o26$19701bo$19701b2o$19700bobo33$19666bo$19666b2o$19665bobo27$19637b3o
$19639bo$19638bo20$19615bo$19615b2o$19614bobo25$19588b2o$19589b2o$
19588bo21$19565b3o$19567bo$19566bo20$19543bo$19543b2o$19542bobo29$
19512b3o$19514bo$19513bo20$19490b2o$19489bobo$19491bo24$19464b2o$
19465b2o$19464bo53$19409b2o$19408bobo$19410bo35$19372b3o$19374bo$
19373bo20$19350b2o$19349bobo$19351bo30$19318b2o$19317bobo$19319bo37$
19279b3o$19281bo$19280bo20$19257b2o$19256bobo$19258bo21$19234b2o$
19235b2o$19234bo21$19211b3o$19213bo$19212bo25$19184b2o$19185b2o$19184b
o21$19161b3o$19163bo$19162bo21$19138b2o$19137bobo$19139bo21$19115b2o$
19116b2o$19115bo21$19092b3o$19094bo$19093bo21$19069b3o$19071bo$19070bo
20$19047b2o$19046bobo$19048bo22$19023bo$19023b2o$19022bobo21$19000b2o$
18999bobo$19001bo21$18977b3o$18979bo$18978bo20$18955bo$18955b2o$18954b
obo21$18932b2o$18933b2o$18932bo38$18892b2o$18891bobo$18893bo21$18869b
2o$18870b2o$18869bo21$18846b3o$18848bo$18847bo20$18824bo$18824b2o$
18823bobo21$18801b2o$18800bobo$18802bo21$18778b2o$18779b2o$18778bo24$
18752b3o$18754bo$18753bo30$18720b2o$18719bobo$18721bo25$18693bo$18693b
2o$18692bobo21$18670b2o$18671b2o$18670bo21$18647b2o$18646bobo$18648bo
21$18624b2o$18625b2o$18624bo20$18602bo$18602b2o$18601bobo22$18578b2o$
18577bobo$18579bo21$18555b2o$18556b2o$18555bo21$18532b3o$18534bo$
18533bo25$18505b2o$18506b2o$18505bo21$18482b3o$18484bo$18483bo20$
18460b2o$18459bobo$18461bo21$18437b3o$18439bo$18438bo20$18415bo$18415b
2o$18414bobo23$18390b2o$18389bobo$18391bo21$18367b3o$18369bo$18368bo
22$18343b2o$18342bobo$18344bo21$18320b3o$18322bo$18321bo20$18298b2o$
18297bobo$18299bo28$18268b3o$18270bo$18269bo20$18246bo$18246b2o$18245b
obo21$18223b2o$18224b2o$18223bo20$18201bo$18201b2o$18200bobo21$18178b
2o$18179b2o$18178bo20$18156bo$18156b2o$18155bobo21$18133b2o$18134b2o$
18133bo25$18106b2o$18105bobo$18107bo21$18083b2o$18084b2o$18083bo21$
18060bo$18060b2o$18059bobo21$18037b2o$18036bobo$18038bo21$18014b2o$
18015b2o$18014bo21$17991b2o$17992b2o$17991bo20$17969bo$17969b2o$17968b
obo23$17944b3o$17946bo$17945bo20$17922bo$17922b2o$17921bobo21$17899b2o
$17900b2o$17899bo21$17876b3o$17878bo$17877bo20$17854b2o$17853bobo$
17855bo35$17817bo$17817b2o$17816bobo21$17794b2o$17795b2o$17794bo22$
17770bo$17770b2o$17769bobo21$17747b2o$17746bobo$17748bo21$17724b3o$
17726bo$17725bo21$17701bo$17701b2o$17700bobo21$17678b2o$17679b2o$
17678bo25$17651b2o$17650bobo$17652bo21$17628b2o$17629b2o$17628bo21$
17605bo$17605b2o$17604bobo21$17582b2o$17581bobo$17583bo21$17559b2o$
17560b2o$17559bo22$17535b2o$17536b2o$17535bo20$17513bo$17513b2o$17512b
obo23$17488b3o$17490bo$17489bo20$17466bo$17466b2o$17465bobo21$17443b2o
$17442bobo$17444bo31$17410b3o$17412bo$17411bo21$17387b2o$17386bobo$
17388bo21$17364b3o$17366bo$17365bo24$17338b2o$17339b2o$17338bo20$
17316bo$17316b2o$17315bobo22$17292b2o$17291bobo$17293bo34$17256b2o$
17257b2o$17256bo23$17231b3o$17233bo$17232bo25$17204b2o$17205b2o$17204b
o21$17181b3o$17183bo$17182bo21$17158b2o$17159b2o$17158bo20$17136bo$
17136b2o$17135bobo31$17103b3o$17105bo$17104bo35$17066b3o$17068bo$
17067bo20$17044bo$17044b2o$17043bobo26$17016bo$17016b2o$17015bobo33$
16981bo$16981b2o$16980bobo27$16952b3o$16954bo$16953bo20$16930bo$16930b
2o$16929bobo25$16903b2o$16904b2o$16903bo21$16880b3o$16882bo$16881bo20$
16858bo$16858b2o$16857bobo29$16827b3o$16829bo$16828bo20$16805b2o$
16804bobo$16806bo24$16779b2o$16780b2o$16779bo53$16724b2o$16723bobo$
16725bo35$16687b3o$16689bo$16688bo20$16665b2o$16664bobo$16666bo30$
16633b2o$16632bobo$16634bo37$16594b3o$16596bo$16595bo20$16572b2o$
16571bobo$16573bo21$16549b2o$16550b2o$16549bo21$16526b3o$16528bo$
16527bo25$16499b2o$16500b2o$16499bo20$16477bo$16477b2o$16476bobo22$
16453b2o$16452bobo$16454bo59$16392bo$16392b2o$16391bobo21$16369b2o$
16370b2o$16369bo29$16338bo$16338b2o$16337bobo50$16286bo$16286b2o$
16285bobo30$16254bo$16254b2o$16253bobo21$16231b2o$16232b2o$16231bo22$
16207b2o$16208b2o$16207bo21$16184b3o$16186bo$16185bo20$16162b2o$16161b
obo$16163bo21$16139b3o$16141bo$16140bo20$16117bo$16117b2o$16116bobo21$
16094b2o$16093bobo$16095bo21$16071b2o$16072b2o$16071bo21$16048b3o$
16050bo$16049bo23$16023b3o$16025bo$16024bo20$16001b2o$16000bobo$16002b
o21$15978b3o$15980bo$15979bo20$15956b2o$15955bobo$15957bo25$15929bo$
15929b2o$15928bobo21$15906b2o$15905bobo$15907bo22$15882b3o$15884bo$
15883bo20$15860bo$15860b2o$15859bobo21$15837b2o$15836bobo$15838bo21$
15814b2o$15813bobo$15815bo21$15791b3o$15793bo$15792bo22$15767b2o$
15768b2o$15767bo21$15744b3o$15746bo$15745bo20$15722b2o$15721bobo$
15723bo21$15699b2o$15700b2o$15699bo20$15677bo$15677b2o$15676bobo39$
15636b3o$15638bo$15637bo20$15614bo$15614b2o$15613bobo21$15591b2o$
15590bobo$15592bo21$15568b2o$15569b2o$15568bo21$15545b3o$15547bo$
15546bo20$15523bo$15523b2o$15522bobo24$15497b2o$15496bobo$15498bo31$
15464b3o$15466bo$15465bo25$15437b2o$15438b2o$15437bo21$15414b3o$15416b
o$15415bo21$15391b2o$15390bobo$15392bo21$15368b2o$15369b2o$15368bo20$
15346bo$15346b2o$15345bobo22$15322bo$15322b2o$15321bobo21$15299b2o$
15300b2o$15299bo21$15276b3o$15278bo$15277bo34$15240b2o$15239bobo$
15241bo58$15180b2o$15179bobo$15181bo25$15153bo$15153b2o$15152bobo21$
15130b2o$15129bobo$15131bo22$15106b3o$15108bo$15107bo20$15084bo$15084b
2o$15083bobo21$15061b2o$15060bobo$15062bo21$15038b2o$15037bobo$15039bo
21$15015b3o$15017bo$15016bo33$14980bo$14980b2o$14979bobo21$14957b2o$
14958b2o$14957bo21$14934b3o$14936bo$14935bo37$14895b2o$14894bobo$
14896bo21$14872b2o$14873b2o$14872bo25$14845b2o$14844bobo$14846bo21$
14822b2o$14823b2o$14822bo21$14799bo$14799b2o$14798bobo21$14776b2o$
14775bobo$14777bo21$14753b2o$14754b2o$14753bo21$14730b2o$14731b2o$
14730bo20$14708bo$14708b2o$14707bobo23$14683b3o$14685bo$14684bo20$
14661bo$14661b2o$14660bobo21$14638b2o$14639b2o$14638bo21$14615b3o$
14617bo$14616bo20$14593b2o$14592bobo$14594bo38$14553bo$14553b2o$14552b
obo21$14530b2o$14529bobo$14531bo21$14507b2o$14508b2o$14507bo21$14484b
3o$14486bo$14485bo20$14462bo$14462b2o$14461bobo21$14439b2o$14438bobo$
14440bo24$14413b2o$14414b2o$14413bo30$14381bo$14381b2o$14380bobo26$
14353b3o$14355bo$14354bo20$14331bo$14331b2o$14330bobo22$14307b3o$
14309bo$14308bo20$14285bo$14285b2o$14284bobo23$14260b3o$14262bo$14261b
o20$14238b2o$14237bobo$14239bo21$14215b3o$14217bo$14216bo28$14185b2o$
14184bobo$14186bo21$14162b2o$14163b2o$14162bo31$14129b2o$14130b2o$
14129bo20$14107bo$14107b2o$14106bobo23$14082b2o$14083b2o$14082bo21$
14059b3o$14061bo$14060bo20$14037bo$14037b2o$14036bobo25$14010b3o$
14012bo$14011bo20$13988bo$13988b2o$13987bobo21$13965b2o$13966b2o$
13965bo27$13936b2o$13937b2o$13936bo20$13914bo$13914b2o$13913bobo26$
13886bo$13886b2o$13885bobo21$13863b2o$13862bobo$13864bo25$13836bo$
13836b2o$13835bobo21$13813b2o$13814b2o$13813bo21$13790b2o$13789bobo$
13791bo21$13767b2o$13768b2o$13767bo21$13744b3o$13746bo$13745bo21$
13721b3o$13723bo$13722bo20$13699b2o$13698bobo$13700bo21$13676b3o$
13678bo$13677bo20$13654bo$13654b2o$13653bobo21$13631b2o$13632b2o$
13631bo25$13604bo$13604b2o$13603bobo21$13581b2o$13582b2o$13581bo20$
13559bo$13559b2o$13558bobo21$13536b2o$13535bobo$13537bo29$13505b2o$
13504bobo$13506bo31$13472bo$13472b2o$13471bobo21$13449b2o$13450b2o$
13449bo21$13426b3o$13428bo$13427bo26$13398b2o$13399b2o$13398bo20$
13376bo$13376b2o$13375bobo21$13353b2o$13354b2o$13353bo20$13331bo$
13331b2o$13330bobo26$13303b3o$13305bo$13304bo20$13281bo$13281b2o$
13280bobo22$13257b3o$13259bo$13258bo20$13235bo$13235b2o$13234bobo37$
13196b2o$13195bobo$13197bo25$13169b3o$13171bo$13170bo20$13147bo$13147b
2o$13146bobo21$13124b2o$13125b2o$13124bo33$13089b3o$13091bo$13090bo20$
13067bo$13067b2o$13066bobo24$13041bo$13041b2o$13040bobo21$13018b2o$
13017bobo$13019bo21$12995b3o$12997bo$12996bo21$12972b2o$12973b2o$
12972bo24$12946b2o$12947b2o$12946bo21$12923b3o$12925bo$12924bo20$
12901bo$12901b2o$12900bobo34$12865b2o$12864bobo$12866bo21$12842b2o$
12843b2o$12842bo25$12815bo$12815b2o$12814bobo37$12776b3o$12778bo$
12777bo38$12736b2o$12735bobo$12737bo21$12713b3o$12715bo$12714bo20$
12691bo$12691b2o$12690bobo22$12667b3o$12669bo$12668bo38$12627bo$12627b
2o$12626bobo26$12599b3o$12601bo$12600bo20$12577bo$12577b2o$12576bobo
22$12553b3o$12555bo$12554bo20$12531bo$12531b2o$12530bobo42$12487b2o$
12488b2o$12487bo20$12465bo$12465b2o$12464bobo21$12442b2o$12441bobo$
12443bo21$12419b2o$12420b2o$12419bo20$12397bo$12397b2o$12396bobo21$
12374b2o$12375b2o$12374bo21$12351b3o$12353bo$12352bo28$12321b3o$12323b
o$12322bo20$12299bo$12299b2o$12298bobo21$12276b2o$12277b2o$12276bo37$
12237b2o$12236bobo$12238bo21$12214b3o$12216bo$12215bo23$12189b2o$
12190b2o$12189bo21$12166b3o$12168bo$12167bo20$12144bo$12144b2o$12143bo
bo28$12114b2o$12113bobo$12115bo21$12091b3o$12093bo$12092bo20$12069b2o$
12068bobo$12070bo21$12046b3o$12048bo$12047bo20$12024b2o$12023bobo$
12025bo21$12001b3o$12003bo$12002bo20$11979bo$11979b2o$11978bobo26$
11951b3o$11953bo$11952bo20$11929b2o$11928bobo$11930bo22$11905b2o$
11906b2o$11905bo59$11844b2o$11843bobo$11845bo21$11821b3o$11823bo$
11822bo29$11790b2o$11789bobo$11791bo50$11738b2o$11737bobo$11739bo30$
11706b2o$11705bobo$11707bo21$11683b3o$11685bo$11684bo22$11659b3o$
11661bo$11660bo20$11637bo$11637b2o$11636bobo21$11614b2o$11615b2o$
11614bo20$11592bo$11592b2o$11591bobo21$11569b2o$11568bobo$11570bo21$
11546b2o$11547b2o$11546bo21$11523b3o$11525bo$11524bo20$11501bo$11501b
2o$11500bobo23$11476bo$11476b2o$11475bobo21$11453b2o$11454b2o$11453bo
20$11431bo$11431b2o$11430bobo21$11408b2o$11409b2o$11408bo25$11381b2o$
11380bobo$11382bo21$11358b2o$11359b2o$11358bo21$11335b2o$11334bobo$
11336bo21$11312b2o$11313b2o$11312bo34$11276b2o$11275bobo$11277bo52$
11222b2o$11223b2o$11222bo24$11196bo$11196b2o$11195bobo21$11173b2o$
11174b2o$11173bo20$11151bo$11151b2o$11150bobo21$11128b2o$11127bobo$
11129bo21$11105b2o$11106b2o$11105bo41$11062bo$11062b2o$11061bobo21$
11039b2o$11040b2o$11039bo37$11000bo$11000b2o$10999bobo21$10977b2o$
10978b2o$10977bo20$10955bo$10955b2o$10954bobo21$10932b2o$10933b2o$
10932bo21$10909b3o$10911bo$10910bo32$10875b2o$10876b2o$10875bo20$
10853bo$10853b2o$10852bobo21$10830b2o$10829bobo$10831bo30$10798b2o$
10799b2o$10798bo20$10776bo$10776b2o$10775bobo26$10748b3o$10750bo$
10749bo20$10726bo$10726b2o$10725bobo22$10702b2o$10703b2o$10702bo21$
10679b3o$10681bo$10680bo20$10657bo$10657b2o$10656bobo43$10612b2o$
10611bobo$10613bo21$10589b3o$10591bo$10590bo20$10567bo$10567b2o$10566b
obo22$10543b2o$10544b2o$10543bo21$10520b3o$10522bo$10521bo23$10495b2o$
10494bobo$10496bo21$10472b2o$10473b2o$10472bo41$10429b3o$10431bo$
10430bo20$10407bo$10407b2o$10406bobo26$10379b2o$10380b2o$10379bo21$
10356b3o$10358bo$10357bo37$10317b3o$10319bo$10318bo20$10295b2o$10294bo
bo$10296bo28$10265b2o$10266b2o$10265bo20$10243bo$10243b2o$10242bobo21$
10220b2o$10221b2o$10220bo20$10198bo$10198b2o$10197bobo21$10175b2o$
10176b2o$10175bo21$10152b3o$10154bo$10153bo20$10130bo$10130b2o$10129bo
bo26$10102b3o$10104bo$10103bo20$10080b2o$10079bobo$10081bo21$10057bo$
10057b2o$10056bobo21$10034b2o$10033bobo$10035bo21$10011b3o$10013bo$
10012bo23$9986b3o$9988bo$9987bo30$9954bo$9954b2o$9953bobo24$9928b3o$
9930bo$9929bo20$9906b2o$9905bobo$9907bo26$9878bo$9878b2o$9877bobo22$
9854b2o$9853bobo$9855bo25$9827bo$9827b2o$9826bobo21$9804b2o$9803bobo$
9805bo22$9780b3o$9782bo$9781bo20$9758bo$9758b2o$9757bobo21$9735b2o$
9734bobo$9736bo21$9712b2o$9711bobo$9713bo21$9689b3o$9691bo$9690bo22$
9665b2o$9666b2o$9665bo21$9642b3o$9644bo$9643bo20$9620b2o$9619bobo$
9621bo21$9597b2o$9598b2o$9597bo20$9575bo$9575b2o$9574bobo36$9537b3o$
9539bo$9538bo20$9515b2o$9514bobo$9516bo23$9490b3o$9492bo$9491bo20$
9468bo$9468b2o$9467bobo21$9445b2o$9446b2o$9445bo22$9421b3o$9423bo$
9422bo20$9399bo$9399b2o$9398bobo26$9371b3o$9373bo$9372bo20$9349bo$
9349b2o$9348bobo22$9325b3o$9327bo$9326bo20$9303b2o$9302bobo$9304bo33$
9268b2o$9267bobo$9269bo36$9230b3o$9232bo$9231bo31$9197b3o$9199bo$9198b
o51$9144b3o$9146bo$9145bo23$9119bo$9119b2o$9118bobo21$9096b2o$9097b2o$
9096bo24$9070bo$9070b2o$9069bobo21$9047b2o$9046bobo$9048bo21$9024b3o$
9026bo$9025bo20$9002b2o$9001bobo$9003bo39$8961bo$8961b2o$8960bobo26$
8933b2o$8934b2o$8933bo28$8903b2o$8904b2o$8903bo20$8881bo$8881b2o$8880b
obo21$8858b2o$8859b2o$8858bo21$8835b2o$8836b2o$8835bo20$8813bo$8813b2o
$8812bobo21$8790b2o$8791b2o$8790bo21$8767b3o$8769bo$8768bo20$8745b2o$
8744bobo$8746bo27$8716bo$8716b2o$8715bobo21$8693b2o$8694b2o$8693bo25$
8666b2o$8665bobo$8667bo21$8643b3o$8645bo$8644bo21$8620b2o$8621b2o$
8620bo21$8597b3o$8599bo$8598bo20$8575b2o$8574bobo$8576bo22$8551b2o$
8552b2o$8551bo21$8528b3o$8530bo$8529bo20$8506bo$8506b2o$8505bobo33$
8471b2o$8472b2o$8471bo37$8432b2o$8431bobo$8433bo22$8408b2o$8407bobo$
8409bo21$8385b3o$8387bo$8386bo28$8355b3o$8357bo$8356bo20$8333bo$8333b
2o$8332bobo23$8308b3o$8310bo$8309bo24$8282bo$8282b2o$8281bobo21$8259b
2o$8260b2o$8259bo20$8237bo$8237b2o$8236bobo22$8213b3o$8215bo$8214bo45$
8166b3o$8168bo$8167bo25$8139b2o$8140b2o$8139bo20$8117bo$8117b2o$8116bo
bo22$8093b3o$8095bo$8094bo20$8071bo$8071b2o$8070bobo21$8048b2o$8047bob
o$8049bo23$8023b3o$8025bo$8024bo20$8001b2o$8000bobo$8002bo21$7978b3o$
7980bo$7979bo21$7955b2o$7956b2o$7955bo21$7932b3o$7934bo$7933bo20$7910b
2o$7909bobo$7911bo21$7887b3o$7889bo$7888bo20$7865b2o$7864bobo$7866bo
60$7803b3o$7805bo$7804bo20$7781b2o$7780bobo$7782bo25$7754bo$7754b2o$
7753bobo21$7731b2o$7730bobo$7732bo21$7708b2o$7707bobo$7709bo21$7685b3o
$7687bo$7686bo20$7663b2o$7662bobo$7664bo21$7640b3o$7642bo$7641bo21$
7617b2o$7618b2o$7617bo20$7595bo$7595b2o$7594bobo26$7567b3o$7569bo$
7568bo20$7545bo$7545b2o$7544bobo22$7521b3o$7523bo$7522bo20$7499b2o$
7498bobo$7500bo33$7464b2o$7463bobo$7465bo36$7426b3o$7428bo$7427bo26$
7398b2o$7399b2o$7398bo20$7376bo$7376b2o$7375bobo21$7353b2o$7354b2o$
7353bo20$7331bo$7331b2o$7330bobo21$7308b2o$7309b2o$7308bo21$7285b3o$
7287bo$7286bo32$7251b3o$7253bo$7252bo27$7222bo$7222b2o$7221bobo30$
7190b2o$7189bobo$7191bo21$7167b3o$7169bo$7168bo36$7129b2o$7128bobo$
7130bo34$7093b3o$7095bo$7094bo31$7060b3o$7062bo$7061bo20$7038bo$7038b
2o$7037bobo21$7015b2o$7014bobo$7016bo21$6992b3o$6994bo$6993bo25$6965b
2o$6966b2o$6965bo20$6943bo$6943b2o$6942bobo22$6919b3o$6921bo$6920bo20$
6897bo$6897b2o$6896bobo21$6874b2o$6873bobo$6875bo21$6851b2o$6850bobo$
6852bo21$6828b3o$6830bo$6829bo20$6806b2o$6805bobo$6807bo21$6783b2o$
6784b2o$6783bo20$6761bo$6761b2o$6760bobo26$6733b2o$6734b2o$6733bo20$
6711bo$6711b2o$6710bobo21$6688b2o$6689b2o$6688bo21$6665b3o$6667bo$
6666bo29$6634b3o$6636bo$6635bo31$6601b2o$6602b2o$6601bo20$6579bo$6579b
2o$6578bobo21$6556b2o$6555bobo$6557bo26$6528bo$6528b2o$6527bobo21$
6505b2o$6506b2o$6505bo20$6483bo$6483b2o$6482bobo21$6460b2o$6459bobo$
6461bo25$6433bo$6433b2o$6432bobo21$6410b2o$6409bobo$6411bo22$6386b3o$
6388bo$6387bo20$6364bo$6364b2o$6363bobo21$6341b2o$6340bobo$6342bo43$
6296b2o$6297b2o$6296bo20$6274bo$6274b2o$6273bobo21$6251b2o$6250bobo$
6252bo22$6227b3o$6229bo$6228bo20$6205bo$6205b2o$6204bobo24$6179b2o$
6180b2o$6179bo21$6156b3o$6158bo$6157bo40$6114bo$6114b2o$6113bobo21$
6091b2o$6090bobo$6092bo26$6063b3o$6065bo$6064bo20$6041bo$6041b2o$6040b
obo37$6002bo$6002b2o$6001bobo21$5979b2o$5980b2o$5979bo28$5949b3o$5951b
o$5950bo20$5927b2o$5926bobo$5928bo21$5904b3o$5906bo$5905bo20$5882b2o$
5881bobo$5883bo21$5859b3o$5861bo$5860bo20$5837bo$5837b2o$5836bobo21$
5814b2o$5815b2o$5814bo25$5787b2o$5786bobo$5788bo21$5764b2o$5765b2o$
5764bo21$5741b2o$5740bobo$5742bo21$5718b2o$5719b2o$5718bo37$5679b3o$
5681bo$5680bo24$5653b2o$5652bobo$5654bo21$5630b2o$5631b2o$5630bo20$
5608bo$5608b2o$5607bobo33$5573b2o$5572bobo$5574bo21$5550b2o$5551b2o$
5550bo24$5524b2o$5525b2o$5524bo21$5501b3o$5503bo$5502bo20$5479b2o$
5478bobo$5480bo21$5456bo$5456b2o$5455bobo24$5430bo$5430b2o$5429bobo21$
5407b2o$5406bobo$5408bo21$5384b2o$5385b2o$5384bo34$5348b3o$5350bo$
5349bo20$5326bo$5326b2o$5325bobo26$5298b2o$5299b2o$5298bo36$5260b2o$
5259bobo$5261bo39$5219b3o$5221bo$5220bo20$5197b2o$5196bobo$5198bo21$
5174b2o$5175b2o$5174bo21$5151b2o$5150bobo$5152bo39$5110b2o$5111b2o$
5110bo25$5083b2o$5082bobo$5084bo21$5060b2o$5061b2o$5060bo21$5037b2o$
5036bobo$5038bo21$5014b2o$5015b2o$5014bo21$4991b2o$4992b2o$4991bo20$
4969bo$4969b2o$4968bobo23$4944b3o$4946bo$4945bo20$4922bo$4922b2o$4921b
obo27$4893bo$4893b2o$4892bobo21$4870b2o$4869bobo$4871bo28$4840b2o$
4841b2o$4840bo20$4818bo$4818b2o$4817bobo21$4795b2o$4796b2o$4795bo21$
4772b3o$4774bo$4773bo24$4746b3o$4748bo$4747bo22$4722bo$4722b2o$4721bob
o21$4699b2o$4700b2o$4699bo21$4676b2o$4677b2o$4676bo21$4653bo$4653b2o$
4652bobo21$4630b2o$4629bobo$4631bo22$4606bo$4606b2o$4605bobo21$4583b2o
$4582bobo$4584bo21$4560b2o$4559bobo$4561bo21$4537b2o$4538b2o$4537bo22$
4513bo$4513b2o$4512bobo21$4490b2o$4489bobo$4491bo25$4463bo$4463b2o$
4462bobo21$4440b2o$4441b2o$4440bo21$4417b2o$4416bobo$4418bo21$4394b2o$
4395b2o$4394bo20$4372bo$4372b2o$4371bobo22$4348b2o$4347bobo$4349bo21$
4325b2o$4326b2o$4325bo21$4302b3o$4304bo$4303bo32$4268b2o$4267bobo$
4269bo37$4229bo$4229b2o$4228bobo22$4205bo$4205b2o$4204bobo21$4182b2o$
4183b2o$4182bo28$4152b2o$4153b2o$4152bo21$4129b3o$4131bo$4130bo22$
4105b2o$4106b2o$4105bo25$4078b3o$4080bo$4079bo20$4056b2o$4055bobo$
4057bo21$4033b3o$4035bo$4034bo21$4010b2o$4011b2o$4010bo45$3963b2o$
3964b2o$3963bo25$3936b2o$3935bobo$3937bo21$3913b2o$3914b2o$3913bo21$
3890bo$3890b2o$3889bobo21$3867b2o$3866bobo$3868bo21$3844b2o$3845b2o$
3844bo32$3810b2o$3811b2o$3810bo21$3787b3o$3789bo$3788bo20$3765b2o$
3764bobo$3766bo21$3742b2o$3743b2o$3742bo23$3717b2o$3716bobo$3718bo21$
3694b3o$3696bo$3695bo20$3672b2o$3671bobo$3673bo21$3649b3o$3651bo$3650b
o21$3626b3o$3628bo$3627bo20$3604b2o$3603bobo$3605bo34$3568b2o$3567bobo
$3569bo21$3545b3o$3547bo$3546bo20$3523bo$3523b2o$3522bobo21$3500b2o$
3501b2o$3500bo20$3478bo$3478b2o$3477bobo30$3446b2o$3447b2o$3446bo20$
3424bo$3424b2o$3423bobo26$3396b3o$3398bo$3397bo20$3374b2o$3373bobo$
3375bo21$3351bo$3351b2o$3350bobo21$3328b2o$3327bobo$3329bo21$3305b3o$
3307bo$3306bo23$3280b3o$3282bo$3281bo30$3248bo$3248b2o$3247bobo24$
3222b3o$3224bo$3223bo20$3200b2o$3199bobo$3201bo26$3172bo$3172b2o$3171b
obo22$3148b2o$3147bobo$3149bo25$3121bo$3121b2o$3120bobo21$3098b2o$
3097bobo$3099bo22$3074b3o$3076bo$3075bo20$3052bo$3052b2o$3051bobo21$
3029b2o$3028bobo$3030bo21$3006b2o$3005bobo$3007bo21$2983b3o$2985bo$
2984bo27$2954bo$2954b2o$2953bobo21$2931b2o$2932b2o$2931bo20$2909bo$
2909b2o$2908bobo26$2881b3o$2883bo$2882bo20$2859bo$2859b2o$2858bobo22$
2835b2o$2836b2o$2835bo21$2812b3o$2814bo$2813bo20$2790bo$2790b2o$2789bo
bo21$2767bo$2767b2o$2766bobo21$2744b2o$2745b2o$2744bo34$2708b3o$2710bo
$2709bo20$2686b2o$2685bobo$2687bo21$2663b2o$2664b2o$2663bo37$2624bo$
2624b2o$2623bobo21$2601b2o$2600bobo$2602bo25$2574bo$2574b2o$2573bobo
21$2551b2o$2550bobo$2552bo22$2527b3o$2529bo$2528bo20$2505bo$2505b2o$
2504bobo21$2482b2o$2481bobo$2483bo32$2448b2o$2447bobo$2449bo21$2425b3o
$2427bo$2426bo20$2403b2o$2402bobo$2404bo21$2380b3o$2382bo$2381bo29$
2349b3o$2351bo$2350bo20$2327b2o$2326bobo$2328bo21$2304b2o$2305b2o$
2304bo24$2278bo$2278b2o$2277bobo36$2240b2o$2241b2o$2240bo35$2203b2o$
2202bobo$2204bo21$2180b3o$2182bo$2181bo20$2158b2o$2157bobo$2159bo27$
2129b3o$2131bo$2130bo20$2107b2o$2106bobo$2108bo32$2073bo$2073b2o$2072b
obo38$2033bo$2033b2o$2032bobo21$2010b2o$2009bobo$2011bo21$1987b2o$
1986bobo$1988bo21$1964b2o$1965b2o$1964bo25$1937b2o$1936bobo$1938bo21$
1914b2o$1915b2o$1914bo21$1891b2o$1890bobo$1892bo21$1868b3o$1870bo$
1869bo33$1833b3o$1835bo$1834bo35$1796b2o$1795bobo$1797bo26$1768bo$
1768b2o$1767bobo21$1745b2o$1746b2o$1745bo20$1723bo$1723b2o$1722bobo21$
1700b2o$1701b2o$1700bo20$1678bo$1678b2o$1677bobo21$1655b2o$1654bobo$
1656bo32$1621b2o$1620bobo$1622bo28$1591b2o$1592b2o$1591bo30$1559b3o$
1561bo$1560bo20$1537b2o$1536bobo$1538bo37$1498b3o$1500bo$1499bo33$
1463b2o$1462bobo$1464bo31$1430b2o$1429bobo$1431bo21$1407b2o$1408b2o$
1407bo21$1384b3o$1386bo$1385bo20$1362b2o$1361bobo$1363bo29$1331b2o$
1330bobo$1332bo30$1299b3o$1301bo$1300bo20$1277bo$1277b2o$1276bobo21$
1254b2o$1255b2o$1254bo20$1232bo$1232b2o$1231bobo21$1209b2o$1208bobo$
1210bo21$1186b3o$1188bo$1187bo20$1164b2o$1163bobo$1165bo39$1123b2o$
1122bobo$1124bo46$1075bo$1075b2o$1074bobo21$1052b2o$1051bobo$1053bo21$
1029b3o$1031bo$1030bo20$1007b2o$1006bobo$1008bo29$976b2o$975bobo$977bo
22$952b2o$953b2o$952bo21$929b3o$931bo$930bo37$890b3o$892bo$891bo20$
868b2o$867bobo$869bo21$845b3o$847bo$846bo29$814b2o$813bobo$815bo21$
791b3o$793bo$792bo20$769b2o$768bobo$770bo25$742bo$742b2o$741bobo21$
719b2o$720b2o$719bo27$690b2o$689bobo$691bo21$667b3o$669bo$668bo25$640b
2o$641b2o$640bo21$617b3o$619bo$618bo21$594b2o$595b2o$594bo21$571b3o$
573bo$572bo32$537b2o$538b2o$537bo21$514b3o$516bo$515bo20$492bo$492b2o$
491bobo30$460b3o$462bo$461bo41$417b3o$419bo$418bo25$390b3o$392bo$391bo
20$368b2o$367bobo$369bo25$341bo$341b2o$340bobo21$318b2o$317bobo$319bo
23$293bo$293b2o$292bobo28$263bo$263b2o$262bobo21$240b2o$241b2o$240bo
20$218bo$218b2o$217bobo26$190b3o$192bo$191bo20$168bo$168b2o$167bobo22$
144b2o$145b2o$144bo21$121b3o$123bo$122bo20$99bo$99b2o$98bobo21$76bo$
76b2o$75bobo21$53b2o$54b2o$53bo28$23b3o$25bo$24bo20$b2o$obo$2bo!

-- helpfully providing the single-channel recipe (which we don't need for the RCT project, which doesn't use single-channel technology) but not providing the list of slow-salvo lanes (which we do want). The manual way to collect the actual slow salvo is to move the northernmost block say (-120000,-120000) in Golly, then run 480K ticks or so, delete the leftover elbow block in the far southeast, Ctrl+A Ctrl+C Ctrl+Shift+O (copy all and paste into a new universe) and run this script:

Code: Select all

# recipe-minimizer-binary-Python3.py
#
# version 1: first Python3 version
# version 2: remove requirement that a non-empty pattern is being constructed
# version 3: slight changes from the "recipe-minimizer-binary.py" in
#   https://github.com/dvgrn/b3s23life/blob/main/singlechannel/recipe-minimizer-binary.py
#                 to avoid over-compression of recipes. The key "magic numbers" to look for are
#                 the "32" in          mindelta, maxdelta = 32, sep
#                 (the previous value was -100, which allowed gliders to change order if their effects are independent)
#
# In Golly, orient a slow salvo so that it's moving northwest,
# with some target in the far northwest corner.
# This code is intended to shrink the distances between slow salvo gliders to some reasonable minimum
# (but with following gliders not advanced _too_ far ahead of the gliders ahead of them,
#  even if they're in unrelated areas of the pattern and could be advanced farther --
#  the relevant magic number is the initial "-100" mindelta.)
# When it's done, the script places a report of the slow-salvo lane list and the minimum distance
# between each glider and the next, into the clipboard.
#
# "12345679" is an arbitraily chosen constant representing an empty universe.
# The "8" is missing on purpose, because the number multiplies by 7 so much more nicely that way.

import golly as g

def getbackground(clist):
   g.setrule("B12345678/S")
   background = g.evolve(clist, 1)
   g.setrule("B3/S23")
   return background

class Glider:
  def __init__(self, rlestr, timeoffset, laneoffset):
    self.dt = timeoffset
    self.dx = laneoffset
    cells = g.parse(rlestr)
    self.clist = g.transform(cells,-cells[0],0)
    self.background = getbackground(self.clist)

def matches(glider, x, y):
  for i in range(0, len(glider.clist), 2):
    if g.getcell(glider.clist[i]+x, glider.clist[i+1]+y) == 0: return 0
  bkg = glider.background
  for i in range(0, len(bkg), 2):
    if g.getcell(bkg[i]+x, bkg[i+1]+y) == 1:  return 0
  return 1

def makerecipe(background, gliderlist):
  g.new("Recipe")
  g.putcells(background)
  offset = max(background[1::2])+4
  for glider, delta in gliderlist:
    clist, lane = glider
    g.putcells(clist, (lane+1)//2+offset, offset)
    offset += delta

g.setalgo("HashLife")

glist = [ Glider("3o$o$bo!",0,0), Glider("bo$2o$obo!",1,-2), \
          Glider("2o$obo$o!",2,-1), Glider("b2o$2o$2bo!",3,-1) ]
gliderE, gliderO = g.transform(glist[0].clist,-glist[0].dx,0), g.transform(glist[1].clist,-glist[1].dx,0)   # glist[0].clist, glist[1].clist

if g.numstates()>2: g.exit("Please use a two-state rule.")

r=g.getrect()
if len(r)==0: g.exit("No pattern found.")

nongliderpat, ngp3, recipelist, recipe, remainder, count = [], [], [], "", g.getcells(r), 0
all = remainder

while len(remainder):
  matchflag = 0
  for index in range(len(glist)):
    glider = glist[index]
    if g.getkey() == "q": g.exit()
    TLx, TLy = remainder[0],remainder[1]
    matchflag = matches(glider, TLx, TLy)
    if matchflag:
      # remove the matched pattern from the universe
      count+=1
      g.putcells(glider.clist, TLx, TLy, 1, 0, 0, 1, "xor")
      g.update()
      g.show("Found glider #" + str(glider.dt) + " at " + str([TLx,TLy]))
      if recipe!="": recipe+=" "
      recipe+="E" if  glider.dt%2==0 else "O"
      lane = (TLx-TLy+glider.dx)*2-1
      recipe+=str(lane)
      recipelist+=[[(gliderE if glider.dt%2==0 else gliderO),lane]]
      nomatch = 0
      break
  if matchflag==0:
    nongliderpat+=[TLx, TLy]
    ngp3 +=[TLx, TLy, 3]
    g.setcell(TLx, TLy, 0)
  remainder = g.getcells(g.getrect())

# g.setclipstr(str(recipe) + "\n"+ str(recipelist))
# g.exit()
if len(ngp3)%2 == 0: ngp3+=[0] # mark as three-state pattern

LONG_ENOUGH = 1024*(len(recipelist)+1) # extra time for the unknown non-glider pattern

g.show("Running pattern...")
g.putcells(all)
g.run(LONG_ENOUGH)
output = g.getrect()
if len(output)==0:
  hash = 12345679
else:
  hash = g.hash(output)
g.show("Restoring pattern...")
g.select(output)
try:
  g.clear(0)
except:
  pass
g.putcells(all)

# g.note(str([len(recipelist),recipelist]))
g.addlayer()

# first find the shortest fixed-width separation between gliders
minsep, sep=3, 256

while 1:
  midpoint = int(minsep + (sep-minsep)/2)
  offset=max(nongliderpat[1::2])+4
  g.show("Regenerating pattern at midpoint = " +str(midpoint) + ", minsep = " + str(minsep) + ", sep = "+ str(sep))
  g.new("Results")
  g.putcells(nongliderpat)
  for clist, lane in recipelist:
    g.putcells(clist, (lane+1)//2+offset, offset)
    offset += midpoint
  g.run(LONG_ENOUGH)
  g.fit()
  g.update()
  output = g.getrect()
  if len(output)==0:
    newhash = 12345679
  else:
    newhash = g.hash(output)
  if newhash == hash:
    # g.show("Hashes matched at midpoint = " +str(midpoint) + ", minsep = " + str(minsep) + ", sep = " + str(sep))
    sep = midpoint
  else:
    # g.show("Hashes did not match at midpoint = " +str(midpoint) + ", minsep = " + str(minsep) + ", sep = "+ str(sep))
    if minsep == midpoint: break  # binary search has found a minimum
    minsep = midpoint
if sep != minsep+1: g.exit("Assertion failed -- sep vs. minsep," + str([sep, minsep]))

# g.note(str(len(recipelist))+" gliders to place.")

deltalist = [sep]*len(recipelist)
# deltalist[0] = max(nongliderpat[1::2])+4
makerecipe(nongliderpat, zip(recipelist, deltalist))
g.run(LONG_ENOUGH)
output = g.getrect()
if len(output)==0:
  hash = 12345679
else:
  hash = g.hash(output)

LONG_ENOUGH = 2**12
while LONG_ENOUGH<len(deltalist)*4*sep+4000: LONG_ENOUGH*=2

ptr=0
while ptr<len(deltalist):
  mindelta, maxdelta = 32, sep
  newlist = deltalist[:]
  while 1:
    midpoint = int(mindelta + (maxdelta-mindelta)/2)
    newlist[ptr] = midpoint
    g.show(str([len(deltalist)-ptr,newlist]).replace(" ",""))
    makerecipe(nongliderpat, zip(recipelist, newlist))
    g.run(LONG_ENOUGH)
    output = g.getrect()
    if len(output)==0:
      newhash = 12345679
    else:
      newhash = g.hash(output)
    if hash == newhash:
      if maxdelta == midpoint: break
      maxdelta = midpoint
    else:
      if mindelta == midpoint: break
      mindelta = midpoint
  deltalist[ptr]=mindelta+1  # take the last good one and continue
  makerecipe(nongliderpat, zip(recipelist, deltalist))
  g.fit()
  g.update()
  ptr+=1

g.note("Done. Click OK to copy the lane list to the clipboard.")
g.setclipstr(recipe+"\n\n"+str(deltalist))
g.show("Done.")

When optimization is complete, the clipboard will be updated with the list of lanes in the usual quarter-diagonal "EO" format.

The resulting pattern in Golly will be something along the following lines. I've switched to LifeSuper, to be able to mark the end location of the target block (same as the start location) without ending up with history cells everywhere:

Code: Select all

x = 4547, y = 4512, rule = LifeSuper
2G$2G4$11.M$10.2M$10.M.M31$47.M$46.2M$46.M.M31$72.M$71.2M$71.M.M31$
119.3M$119.M$120.M31$148.M$147.2M$147.M.M31$170.M$169.2M$169.M.M31$
200.3M$200.M$201.M31$236.3M$236.M$237.M31$271.3M$271.M$272.M31$303.3M
$303.M$304.M31$339.3M$339.M$340.M45$394.3M$394.M$395.M31$430.3M$430.M
$431.M31$473.3M$473.M$474.M31$499.3M$499.M$500.M31$521.M$520.2M$520.M
.M31$568.3M$568.M$569.M31$577.3M$577.M$578.M31$606.3M$606.M$607.M31$
641.M$640.2M$640.M.M31$677.M$676.2M$676.M.M31$717.M$716.2M$716.M.M31$
735.M$734.2M$734.M.M31$760.M$759.2M$759.M.M31$818.3M$818.M$819.M31$
855.M$854.2M$854.M.M31$895.M$894.2M$894.M.M31$922.M$921.2M$921.M.M31$
943.M$942.2M$942.M.M31$986.M$985.2M$985.M.M31$1016.M$1015.2M$1015.M.M
43$1065.3M$1065.M$1066.M31$1118.3M$1118.M$1119.M31$1161.3M$1161.M$
1162.M31$1194.3M$1194.M$1195.M31$1219.3M$1219.M$1220.M31$1266.3M$
1266.M$1267.M31$1299.3M$1299.M$1300.M31$1336.3M$1336.M$1337.M31$1290.
3M$1290.M$1291.M31$1320.3M$1320.M$1321.M31$1355.3M$1355.M$1356.M31$
1382.3M$1382.M$1383.M31$1426.M$1425.2M$1425.M.M42$1452.3M$1452.M$
1453.M31$1485.M$1484.2M$1484.M.M31$1519.M$1518.2M$1518.M.M31$1552.3M$
1552.M$1553.M31$1582.3M$1582.M$1583.M31$1615.3M$1615.M$1616.M31$1639.
M$1638.2M$1638.M.M31$1689.3M$1689.M$1690.M31$1722.M$1721.2M$1721.M.M
31$1763.M$1762.2M$1762.M.M31$1786.M$1785.2M$1785.M.M31$1825.3M$1825.M
$1826.M31$1855.3M$1855.M$1856.M31$1896.3M$1896.M$1897.M31$1919.M$
1918.2M$1918.M.M31$1953.M$1952.2M$1952.M.M31$1997.M$1996.2M$1996.M.M
36$2052.3M$2052.M$2053.M31$2089.M$2088.2M$2088.M.M31$2118.M$2117.2M$
2117.M.M31$2148.M$2147.2M$2147.M.M31$2186.M$2185.2M$2185.M.M31$2219.
3M$2219.M$2220.M31$2240.3M$2240.M$2241.M31$2271.3M$2271.M$2272.M31$
2312.3M$2312.M$2313.M31$2331.3M$2331.M$2332.M31$2364.3M$2364.M$2365.M
31$2393.3M$2393.M$2394.M31$2460.3M$2460.M$2461.M31$2496.3M$2496.M$
2497.M31$2537.M$2536.2M$2536.M.M31$2559.3M$2559.M$2560.M31$2610.3M$
2610.M$2611.M31$2643.3M$2643.M$2644.M31$2669.3M$2669.M$2670.M31$2709.
3M$2709.M$2710.M31$2721.3M$2721.M$2722.M31$2757.3M$2757.M$2758.M31$
2800.M$2799.2M$2799.M.M31$2838.M$2837.2M$2837.M.M31$2860.M$2859.2M$
2859.M.M31$2891.3M$2891.M$2892.M31$2933.3M$2933.M$2934.M31$2968.M$
2967.2M$2967.M.M31$3009.M$3008.2M$3008.M.M31$3025.M$3024.2M$3024.M.M
31$3059.3M$3059.M$3060.M31$3090.3M$3090.M$3091.M31$3129.3M$3129.M$
3130.M31$3172.3M$3172.M$3173.M31$3185.M$3184.2M$3184.M.M31$3219.M$
3218.2M$3218.M.M31$3237.3M$3237.M$3238.M57$3264.3M$3264.M$3265.M31$
3319.M$3318.2M$3318.M.M31$3376.3M$3376.M$3377.M31$3395.M$3394.2M$
3394.M.M31$3428.M$3427.2M$3427.M.M31$3476.M$3475.2M$3475.M.M31$3495.
3M$3495.M$3496.M31$3524.3M$3524.M$3525.M31$3559.3M$3559.M$3560.M31$
3592.3M$3592.M$3593.M31$3622.M$3621.2M$3621.M.M31$3657.3M$3657.M$
3658.M31$3694.3M$3694.M$3695.M31$3739.M$3738.2M$3738.M.M31$3755.3M$
3755.M$3756.M31$3805.M$3804.2M$3804.M.M31$3841.M$3840.2M$3840.M.M31$
3872.3M$3872.M$3873.M31$3904.3M$3904.M$3905.M31$3946.M$3945.2M$3945.M
.M31$3975.M$3974.2M$3974.M.M31$4008.M$4007.2M$4007.M.M31$4038.3M$
4038.M$4039.M31$4065.M$4064.2M$4064.M.M31$4089.3M$4089.M$4090.M31$
4122.3M$4122.M$4123.M37$4172.M$4171.2M$4171.M.M31$4229.M$4228.2M$
4228.M.M31$4257.M$4256.2M$4256.M.M31$4290.M$4289.2M$4289.M.M31$4323.
3M$4323.M$4324.M31$4365.3M$4365.M$4366.M31$4389.3M$4389.M$4390.M31$
4422.M$4421.2M$4421.M.M31$4466.3M$4466.M$4467.M72$4544.3pA$4544.pA$
4545.pA!

I added the trigger glider in state-25 pink, in the far southeast -- slsparse doesn't know about that, and it can't be included while the optimization script is running, because the script has a very limited mindset ... it assumes that the final object is some kind of constellation or oscillator -- an unmoving object.

[otismo]

Thank You !

My "level of interest" is High, but I have not even coded a single GollyScript yet...

I have not even done more than a "skim-thru" of our TextBook, either...

I blame it on a) this accursed inflation and b) my will to survive

( don't survive, can't do nuthin', right ? )

I really appreciate the fact that this thread is here, though -

perhaps other "Code Gods" will also participate -

for the benefit of all us "noob coderz"...

Cheers !

[dvgrn]

perhaps other "Code Gods" will also participate -

for the benefit of all us "noob coderz"...

Code Gods would certainly be welcome here. I'm not one of those myself -- maybe more like a "code imp", hoping one day to be promoted to code monkey.

The next task is to write a script to process this set of locations

Code: Select all

x = 2070, y = 2222, rule = LifeSuper
2068.2pA$2068.2pA38$2032.2M$2032.2M44$1994.2M$1994.2M42$1951.2M$1951.
2M45$1914.2M$1914.2M42$1880.2M$1880.2M40$1840.2W$1840.2W43$1797.2M$
1797.2M41$1756.2W$1756.2W44$1715.2M$1715.2M38$1677.2M$1677.2M41$1637.
2M$1637.2M39$1598.2M$1598.2M36$1561.2W$1561.2W44$1519.2M$1519.2M39$
1480.2M$1480.2M40$1440.2W$1440.2W38$1402.2W$1402.2W40$1362.2M$1362.2M
42$1320.2M$1320.2M41$1280.2M$1280.2M39$1241.2M$1241.2M41$1200.2pA$
1200.2pA38$1162.2M$1162.2M42$1120.2M$1120.2M45$1077.2M$1077.2M44$
1032.2W$1032.2W41$992.2M$992.2M35$955.2M$955.2M43$916.2M$916.2M42$
874.2M$874.2M40$832.2M$832.2M40$792.2pA$792.2pA41$751.2M$751.2M36$
715.2W$715.2W39$676.2W$676.2W44$633.2W$633.2W44$599.2M$599.2M30$561.
2pA$561.2pA46$521.2M$521.2M38$483.2M$483.2M44$440.2M$440.2M39$400.2M$
400.2M37$363.2M$363.2M46$322.2M$322.2M37$285.2W$285.2W47$244.2M$244.
2M39$205.2W$205.2W40$167.2pA$167.2pA47$127.2M$127.2M35$91.2M$91.2M48$
67.2M$67.2M37$29.2M$29.2M46$2M$2M!

which is just the topmost block in each Cordership in the SE Corderfleet, rotated 90 degrees clockwise to match the orientation of infile.mc -- the first Cordership in the Corderfleet is represented by the southwesternmost block. Or ... a little XOR and AND pasting in Golly gets us a simpler reference pattern:

Code: Select all

x = 2070, y = 2222, rule = LifeSuper
2068.2pA$2068.2pA39$2032.M45$1994.M43$1951.M46$1914.M43$1880.M41$
1840.W44$1797.M42$1756.W45$1715.M39$1677.M42$1637.M40$1598.M37$1561.W
45$1519.M40$1480.M41$1440.W39$1402.W41$1362.M43$1320.M42$1280.M40$
1241.M42$1200.pA39$1162.M43$1120.M46$1077.M45$1032.W42$992.M36$955.M
44$916.M43$874.M41$832.M41$792.pA42$751.M37$715.W40$676.W45$633.W45$
599.M31$561.pA47$521.M39$483.M45$440.M40$400.M38$363.M47$322.M38$285.
W48$244.M40$205.W41$167.pA48$127.M36$91.M49$67.M38$29.M47$M!

-- with the state-13 and state-23 (white and green) cells representing Corderships that can be sent out with even parity, and the state-25 (pink/red) cells representing odd-parity Corderships.

The next idea is to find out how far to move the red block in the infile.mc from the last post, before running slsparse to get the slow-salvo recipe for each new Cordership.

If a following Cordership was following exactly behind the previous one, and it was a multiple of 8 cells away, then we could use the default infile.mc, without changing it at all -- since that produces its output block directly on top of the input block, once the trigger glider is sent in to activate the Cordership seed. If we kept re-sending that same recipe indefinitely, nothing would change and we'd end up with a Cordership gun.

But we won't ever really need to do that, since a second Cordership following right in the tracks of the first one probably won't have any work to do -- the first Cordership would already have done it. What will usually happen is that each new Cordership will have to be built just a little bit farther away from the slow-salvo source than the last one was.

We also have to get the mod-8 location right, along the diagonal the Corderships are traveling on. It's okay to move any of these Corderships SW or NE by 8N cells; this is a slow Corderfleet, so it will still do its job just fine as long as the mod-8 location doesn't change, as long as the Corderships don't actually run into each other. So we'll just find whatever value of N moves a following Cordership (-8N, 8N) in Golly coordinates, to the point closest to overlapping with the Cordership immediately before it.

Brief Pause for Review and Questions
If anyone is actually following along so far, questions would be helpful at this point, before I start posting the data-collection code.

infile.mc is the input file for slsparse, which is used to generate the long string of slow salvos that we're going to need to build all these Corderfleets.

The pseudo-still-life mango on block marks where we're telling slsparse to put its initial elbow block, relative to the Cordership seed constellation that we're building.

The ever-helpful mango just shows what direction gliders will be coming from to activate the elbow block. I've set this up to be the same orientation that the ECCA will use to generate these slow salvos -- though it doesn't really matter in this case! Ultimately we'd get the same slow salvo out, even if the mango were set up in mirror-image on the other side of the block. We won't be using the single-channel salvo that slsparse automatically sets up for us -- we'll immediately use up those gliders to extract the actual slow salvo.

The red block location in infile.mc marks where the target block will be placed at the start of the recipe. The exact distance between the block-and-mango pseudo-object and the target doesn't matter at all -- just needs to be big enough that there's no interference with slsparse's default single-channel construction arm while the slow salvo is being generated.

For more practice and background on slsparse, see the LifeWiki slsparse tutorial.

[dvgrn]

... a little XOR and AND pasting in Golly gets us a simpler reference pattern...

Okay, I got the reference pattern a little bit wrong -- there was an extra complete block at the northeast end. I found that out by writing the following script (Python, not Lua, sorry -- I think in Python these days and have to translate to get to Lua.)

Code: Select all

import golly as g

# g.parse() produces a cell list, with no rule information attached to it --
# so the header line isn't needed.  In fact, g.parse() does very weird things
# if you include the header line -- quite possibly we should fix that.
offsetspat = g.parse("""2068.pA39$2032.M45$1994.M43$1951.M46$1914.M43$1880.M41$1840.W44$1797.
M42$1756.W45$1715.M39$1677.M42$1637.M40$1598.M37$1561.W45$1519.M40$
1480.M41$1440.W39$1402.W41$1362.M43$1320.M42$1280.M40$1241.M42$1200.pA
39$1162.M43$1120.M46$1077.M45$1032.W42$992.M36$955.M44$916.M43$874.M
41$832.M41$792.pA42$751.M37$715.W40$676.W45$633.W45$599.M31$561.pA47$
521.M39$483.M45$440.M40$400.M38$363.M47$322.M38$285.W48$244.M40$205.W
41$167.pA48$127.M36$91.M49$67.M38$29.M47$M!
""")

s, parities="",""
# this is a multistate cell list, so coordinates are in (x, y, state) triplets
for i in range(0,len(offsetspat)-1,3):
  s += str( [ offsetspat[i],offsetspat[i+1] ] )+"\n"
  if offsetspat[i+2]== 25:
    parities += "O"
  else:
    parities += "E"
g.setclipstr(s + "\n" + parities)

This collects and copies to the clipboard both a list of coordinates and a string of parities --
OEEEEEEEEEEEEEEEEEEEEEOEEEEEEEEEOEEEEEOEEEEEEEEEOEEEEE
--representing which Corderships have to be triggered at T={odd}, vs. the ones that can be triggered at T={even}. (For most of the Corderships it doesn't matter, so we'll just go with T={even} by default, unless T={odd} is required.)

When I tried this with the original reference pattern, the first four coordinates were obviously right next to each other, so I figured out which cells should have been deleted and deleted them. Probably it will be good to remember that I did this. If we're all done with this project, and all the Corderships end up in the correct place except for the last one, this would be the most likely reason why.

Tangential paragraph about how annoying coding is if you're not careful
The general rule here is to keep writing little bits of code that can be run to check the work so far. Problems are much easier to find if they are forced to show up one at a time, as opposed to waiting until everything is coded up and it theoretically might Just Work. In practice, that's when you get the most hideous and exhausting bugs, which are the result of half a dozen subtle mistakes that interact to produce what ought to be completely impossible results.

Multi-state vs. single-state cell lists
Time for another confession: my original code said

Code: Select all

for i in range(0,len(offsetspat),3):

but that caused an error once I removed the three extra cells in the cell list -- because there's an extra "0" appended to multistate cell lists whenever the total length is even, meaning there are an even number of cells in the list. With the optional extra 0 trick, Golly can reliably mark a cell list as multi-state by making the list an odd length, and conversely know that a list is a single-state list (coordinate pairs but no state values) if the list is even-length.

Changing the code to len(offsetspat)-1 still works for multistate cell lists with an odd number of cells, but now also works for multistate cell lists with an even number of cells. The effect is that it ignores the trailing "0" without missing the last cell in the list.

If this isn't clear, it's worth spending some time to convince yourself that it's true. This is a weird rule about Golly cell lists that will get you into all kinds of trouble if you don't understand it clearly. For example, the odd appended zero is why you end up with messed-up cell lists -- but only sometimes! -- if you append multistate cell lists together directly rather than using g.join... but single-state cell lists can be directly appended to each other with no problem.

Figure Out What The Offsets Need to Be
Okay, back to the problem at hand: programmatically convert that list of cell locations to a different list that tells us exactly what (dx, dy) offset to use, to adjust infile.mc to build each new Cordership, relative to the one before.

It makes sense to calculate the "relative to the one before" coordinates rather than the absolute coordinates, because we're going to be ending up with a leftover target block after each Cordership seed is triggered, that's always in the same place relative to that launched Cordership. So that's the location we'll be starting from to launch the next Cordership.

Digression about An Alternative Option
There's no particular reason why we _have_ to do things this way. For example, we could instead use an infile.mc that looks like this:

Code: Select all

x = 213, y = 203, rule = LifeHistory
2C$2C64$92.A$91.A.A15.A$91.2A15.A.A$108.2A3$88.2A$88.2A2$107.2A$106.A
.A$107.A3$80.2A$80.2A$112.A$111.A.A$112.A6$94.2A$74.A19.2A$73.A.A$74.
2A30.2A$106.2A18.A$80.2A3.2A38.A.A$79.A.A2.A.A38.2A$80.A4.A3$98.2A$
97.A.A$98.A3$98.2A13.2A$97.A.A13.2A$98.A4$101.2A$101.A.A$102.A86$208.
A$207.A.A.2A$206.A2.A.2A$206.A.A$207.A!

Instead of a red block marking the start position for the target block, now there's a white one -- meaning, it's both a target block and part of the target constellation: slsparse would go ahead and rebuild the target block in exactly the same location as it was before. And when this seed gets activated, no extra block would be left behind:

Code: Select all

x = 134, y = 113, rule = LifeHistory
2C$2C64$92.A$91.A.A15.A$91.2A15.A.A$108.2A3$88.2A$88.2A2$107.2A$106.A
.A$107.A3$80.2A$80.2A$112.A$111.A.A$112.A6$94.2A$74.A19.2A35.2C$73.A.
A55.C.C$74.2A30.2A23.C$106.2A18.A$80.2A3.2A38.A.A$79.A.A2.A.A38.2A$
80.A4.A3$98.2A$97.A.A$98.A3$98.2A13.2A$97.A.A13.2A$98.A4$101.2A$101.A
.A$102.A!

To build the early Corderships, slsparse would have to waste a few gliders splitting off a movable target from the initial block, and pulling it forward a long way before building that Cordership's seed. But for the last few Corderships it wouldn't have to pull a target forward very far at all.

Under that model, we'd want to collect absolute coordinates instead of relative coordinates, because the target block would always be starting in the same exact place. Maybe the total combined recipe would even come out to be a little cheaper if we did it that way -- someone could put that slow salvo together and find out. But meanwhile I'm not doing things that way, so I need to collect relative coordinates.

Lots of Explanation for a Little Bit of Code
A little rewriting to find out how many cells there are, and to check that that hasn't introduced any new dumb mistakes:

Code: Select all

import golly as g

# g.parse() produces a cell list, with no rule information attached to it --
# so the header line isn't needed.  In fact, g.parse() does very weird things
# if you include the header line -- quite possibly we should fix that.
offsetspat = g.parse("""2068.pA39$2032.M45$1994.M43$1951.M46$1914.M43$1880.M41$1840.W44$1797.
M42$1756.W45$1715.M39$1677.M42$1637.M40$1598.M37$1561.W45$1519.M40$
1480.M41$1440.W39$1402.W41$1362.M43$1320.M42$1280.M40$1241.M42$1200.pA
39$1162.M43$1120.M46$1077.M45$1032.W42$992.M36$955.M44$916.M43$874.M
41$832.M41$792.pA42$751.M37$715.W40$676.W45$633.W45$599.M31$561.pA47$
521.M39$483.M45$440.M40$400.M38$363.M47$322.M38$285.W48$244.M40$205.W
41$167.pA48$127.M36$91.M49$67.M38$29.M47$M!
""")

coordlist = []
# this is a multistate cell list, so coordinates are in (x, y, state) triplets
# and there will be a trailing '0' at the end if there's an even number of cells in the list
if len(offsetspat)%3 != 0:
  if offsetspat[-1] == 0:
    offsetspat = offsetspat[:-1]  # remove trailing zero
if len(offsetspat)%3 != 0:
  # this shouldn't ever happen, so send this problem back to the coder
  g.exit("Input multistate list seems to be in an invalid format.")

# Now the list is no longer necessarily a valid Golly multistate list,
#   but we don't care -- we know how many cells are in it, because we
#   got rid of any marker '0's at the end.
numcells = len(offsetspat)//3
g.note( "Number of cells to process: " + str(numcells) )

... If I thought that it would ever be useful for anything again, I'd think about maybe wrapping those lines doing "len(offsetspat)%3" mod-3 tests, into a nice function called something understandable like "RemoveTrailingZeroesFromGollyMultistateCellList". But it takes more time to type that name than to just rewrite the whole function if I need it, so I'll just stick with my old procedural-programming bad habits this time.

Now it's time to work backwards through the list, and find out the closest "equivalent distance" for each cell -- the location plus or minus (8N, -8N) that puts the new Cordership start location closest to the previous one. Let's see how that works out:

Code: Select all

import golly as g

# g.parse() produces a cell list, with no rule information attached to it --
# so the header line isn't needed.  In fact, g.parse() does very weird things
# if you include the header line -- quite possibly we should fix that.
offsetspat = g.parse("""2068.pA39$2032.M45$1994.M43$1951.M46$1914.M43$1880.M41$1840.W44$1797.
M42$1756.W45$1715.M39$1677.M42$1637.M40$1598.M37$1561.W45$1519.M40$
1480.M41$1440.W39$1402.W41$1362.M43$1320.M42$1280.M40$1241.M42$1200.pA
39$1162.M43$1120.M46$1077.M45$1032.W42$992.M36$955.M44$916.M43$874.M
41$832.M41$792.pA42$751.M37$715.W40$676.W45$633.W45$599.M31$561.pA47$
521.M39$483.M45$440.M40$400.M38$363.M47$322.M38$285.W48$244.M40$205.W
41$167.pA48$127.M36$91.M49$67.M38$29.M47$M!
""")

coordlist = []
# this is a multistate cell list, so coordinates are in (x, y, state) triplets
# and there will be a trailing '0' at the end if there's an even number of cells in the list
if len(offsetspat)%3 != 0:
  if offsetspat[-1] == 0:
    offsetspat = offsetspat[:-1]  # remove trailing zero
if len(offsetspat)%3 != 0:
  # this shouldn't ever happen, so send this problem back to the coder
  g.exit("Input multistate list seems to be in an invalid format.")

# Now the list is no longer necessarily a valid Golly multistate list,
#   but we don't care -- we know how many cells are in it, because we
#   got rid of any marker '0's at the end.
numcells = len(offsetspat)//3
g.show( "Number of cells to process: " + str(numcells) )

locations = []
# Reading top to bottom, the last cell's coordinates will be the one corresponding to the first Cordership.
# The next Cordership's location, given by the second-to-last cell in the list,
# has to be calculated relative to the previous location, all the way through the list.
prevlocx, prevlocy = offsetspat[numcells*3 - 3], offsetspat[numcells*3 - 2]
for i in range(numcells-2, -1, -1):
  # g.note(str([offsetspat[i*3],offsetspat[i*3+1]]))
  newlocx,newlocy = offsetspat[i*3],offsetspat[i*3+1]
  dx, dy = newlocx - prevlocx, newlocy - prevlocy
  g.note(str(["dx",dx,"dy",dy, "prevlocx", prevlocx, "prevlocy", prevlocy, "newlocx", newlocx, "newlocy", newlocy]))
  while 1:
    dxadj, dyadj = dx - 8, dy + 8
    # is the adjusted location closer to the previous Cordership's location? (i.e., closer to (0,0) )
    if dxadj**2 + dyadj**2 < dx**2 + dy**2:
      # if so, use that location instead
      g.note(str(["Cordership #",i,"was",[dx,dy],"next trial",[dxadj,dyadj]]))
      dx, dy = dxadj, dyadj
    else:
      g.note(str([dx,dy]) + " is as close as we're going to get.")
      break  # can't keep getting closer to zero forever, so eventually we'll escape this loop
  locations.append([dx,dy])
  
  # Now -- very important -- we have to update (prevlocx, prevlocy) to do the next calculation relative to
  #   the (newlocx, newlocy) Cordership.  Otherwise we end up with absolute coordinates, not relative ones.
  prevlocx, prevlocy = newlocx, newlocy
g.setclipstr(str(locations))

With all the debug messages in there, the code appears to be doing what I want it to do. Commenting out the g.note() commands gets me the following in the clipboard:

Code: Select all

[[-11, -7], [-2, 2], [-16, -9], [4, -4], [0, -8], [-2, -1], [-1, 0], [-7, 0], [-3, 2], [1, -7], [-3, 2], [0, 0], [3, -5], [-2, 1], [0, -7], [6, 1], [-6, -5], [3, -5], [-1, 0], [-4, 3], [1, -2], [0, -1], [2, -1], [2, -3], [-1, -4], [-3, 4], [0, -2], [-3, 3], [-5, 2], [2, -3], [-2, 1], [1, -2], [-1, 0], [0, -2], [2, -3], [0, -1], [-2, 1], [0, -1], [-1, 0], [2, -5], [-3, 3], [-1, 0], [0, -2], [-2, 1], [1, -5], [1, -2], [3, -4], [0, -1], [-6, -3], [-3, -6], [3, -3], [-2, -5], [-4, 1]]

Final check: is it right? I can try a few adjustments by hand and see if I get the same answers as the script... and yes, indeedy, I do. The third Cordership, for example, should be built at an offset of (-2, 2) from the second Cordership, and the last Cordership can be built [-4,-1] away from the second-to-last Cordership.

Done with 3.1, On to 3.2
To be continued --

[dvgrn]

3.2 is an easy one. We're starting with the template

Code: Select all

x = 140, y = 138, rule = LifeHistory
19.A$18.A.A15.A$18.2A15.A.A$35.2A3$15.2A$15.2A2$34.2A$33.A.A$34.A3$7.
2A$7.2A$39.A$38.A.A$39.A6$21.2A$.A19.2A$A.A$.2A30.2A$33.2A18.A$7.2A3.
2A38.A.A$6.A.A2.A.A38.2A$7.A4.A3$25.2A$24.A.A$25.A3$25.2A$24.A.A14.2A
$25.A15.2A4$28.2A$28.A.A$29.A86$135.A$134.A.A.2A$133.A2.A.2A$133.A.A$
134.A!

but for each new Cordership we're building, the red location for the start position of the target block will be wherever it needs to be to produce the correct offset, relative to the output target block location from the previous Cordership.

The default location is at (36,39) -- i.e., that's the target block location where a following Cordership would be built in the exact same location as the previous one. If we want the following Cordership to be built at an offset of, say, (-11,-7), then we need to move the target block (+11,+7) away from the default location. That way slsparse will have to push the target block (-11,-7) farther away from the slow-salvo source, before starting construction.

We'll go ahead and build 54 different RLE files to be copied in to infile.mc. Let's see how that works out:

Code: Select all

import golly as g

# today's weird discovery is that slsparse accepts LifeSuper format but doesn't recognize red state 4 blocks
#  as valid marked starting positions, for some reason.  Better be specific about the rule here:
g.setrule("LifeHistory")

# avoid needing a subroutine or complicated logic by making a lookup table
#  that gives the right output state value to mark a target block cell, no matter if
#  the cell is already ON or not
# If a cell is already state 3, 4, 5, or 6, the attempted lookup will cause errors --
#   which is what we want, because the template pattern should definitely not
#    contain any such thing.
lookup = [4,3]

offsetslist = [[-11, -7], [-2, 2], [-16, -9], [4, -4], [0, -8], [-2, -1], [-1, 0], [-7, 0], [-3, 2], [1, -7], [-3, 2], [0, 0], [3, -5], [-2, 1], [0, -7], [6, 1], [-6, -5], [3, -5], [-1, 0], [-4, 3], [1, -2], [0, -1], [2, -1], [2, -3], [-1, -4], [-3, 4], [0, -2], [-3, 3], [-5, 2], [2, -3], [-2, 1], [1, -2], [-1, 0], [0, -2], [2, -3], [0, -1], [-2, 1], [0, -1], [-1, 0], [2, -5], [-3, 3], [-1, 0], [0, -2], [-2, 1], [1, -5], [1, -2], [3, -4], [0, -1], [-6, -3], [-3, -6], [3, -3], [-2, -5], [-4, 1]]

baserle = g.parse("""19.A$18.A.A15.A$18.2A15.A.A$35.2A3$15.2A$15.2A2$34.2A$33.A.A$34.A3$7.
2A$7.2A$39.A$38.A.A$39.A6$21.2A$.A19.2A$A.A$.2A30.2A$33.2A18.A$7.2A3.
2A38.A.A$6.A.A2.A.A38.2A$7.A4.A3$25.2A$24.A.A$25.A3$25.2A$24.A.A14.2A
$25.A15.2A4$28.2A$28.A.A$29.A86$135.A$134.A.A.2A$133.A2.A.2A$133.A.A$
134.A!""")
count = 0
for item in offsetslist:
  dx, dy = item
  g.new("infile"+str(count))
  g.putcells(baserle)
  
  # mark the four cells in the target block
  for y in range(39-dy,41-dy):
    for x in range(36-dx, 38-dx):
      g.setcell(x, y, lookup[g.getcell(x,y)])
  g.save("C:/path/to/infiles/infile" + str(count) + ".mc","mc")
  count += 1

(replace "C:/path/to/infiles/" in the second-to-last line with wherever you want to put the generated infiles).

Then for the next task, 3.3, we just need a batch file generated that can run slsparse against all of those generated infiles, one after another. slspsarse doesn't let you pass in an input filename (that I recall) -- it just expects a file called "infile.mc", even though it can actually be in RLE format rather than macrocell format. So we'll have to copy each of the generated infiles to the infile.mc location, call slsparse, and then copy output.mc to a safe location so it doesn't get overwritten by the next call to slsparse.

Code: Select all

with open ("C:/users/{username}/Desktop/outfiles/batchfile.bat","w") as f:

  for i in range(53):
    f.write("cp C:/path/to/infiles/infile" + str(i) + ".mc C:/path/to/slmake/infile.mc\n")
    f.write("slsparse\n")
    f.write("cp C:/path/to/slmake/infile.mc C:/path/to/outfiles/outfile"+str(i)+".mc\n")

This is Linux-style copying and slsparse-calling, so it can be invoked just by putting the path to the resulting file into a Linux bash prompt (or Cygwin, if you're running that). Paths need to be updated to match your own system, if you're following along.

It will take quite a while to run through 53 slsparse calls, so I'll leave this overnight to finish processing... after double-checking that the first two outputs seem to be lining up correctly, if I stick the two slow salvos together.

That double-check turned out to be a very good idea, given that I had accidentally generated all of the infiles using "LifeSuper" as the rule instead of "LifeHistory" -- and it turns out that slsparse doesn't throw any errors when you do that, but also doesn't produce output that we can use. No harm catching that kind of thing early.

[dvgrn]

The batch file seemed to work. The manual sanity check that everything is working the way it's supposed to looks like this:

outfile0, outfile1, and outfile2, if the target block is moved (-120000,-120000) in each, then run for 475136 ticks in Golly (I had the step size set to 2^13) ... look like this once the elbow block is removed and the trigger glider is added for each Cordership seed:

Code: Select all

x = 354373, y = 119971, rule = B3/S23
2o117761b2o116619b2o$2o117761b2o116619b2o1852$236241b3o$236241bo$
236242bo79$1931bo$1930b2o$1930bobo7$119703bo$119702b2o$119702bobo375$
2318bo$2317b2o$2317bobo211$120289b2o$120288b2o$120290bo532$237446b2o$
237446bobo$237446bo374$3442b2o$3441b2o$3443bo113$121323bo$121322b2o$
121322bobo337$3886bo$3885b2o$3885bobo181$121827b3o$121827bo$121828bo
24$238494b2o$238494bobo$238494bo1024$122887bo$122886b2o$122886bobo50$
5178b2o$5178bobo$5178bo60$239629b3o$239629bo$239630bo538$123551b2o$
123550b2o$123552bo66$5849b3o$5849bo$5850bo395$240637b2o$240636b2o$
240638bo189$124198b3o$124198bo$124199bo527$241353b2o$241352b2o$241354b
o122$7088b2o$7088bobo$7088bo368$125224b3o$125224bo$125225bo150$241990b
3o$241990bo$241991bo613$8224b3o$8224bo$8225bo287$126282b3o$126282bo$
126283bo354$243254b2o$243253b2o$243255bo281$9153b3o$9153bo$9154bo467$
127390b2o$127390bobo$127390bo55$9683b2o$9683bobo$9683bo130$244196bo$
244195b2o$244195bobo581$244782b2o$244782bobo$244782bo148$128315b2o$
128315bobo$128315bo281$10833b2o$10833bobo$10833bo193$245396bo$245395b
2o$245395bobo561$129363b3o$129363bo$129364bo21$245990b2o$245990bobo$
245990bo183$11797b3o$11797bo$11798bo254$246434b2o$246434bobo$246434bo
658$247095b3o$247095bo$247096bo193$12912b2o$12912bobo$12912bo34$
130721b3o$130721bo$130722bo338$247665b3o$247665bo$247666bo205$13503b2o
$13503bobo$13503bo232$248109b3o$248109bo$248110bo54$131569b2o$131569bo
bo$131569bo303$14101b2o$14101bobo$14101bo714$132583b2o$132583bobo$
132583bo120$14948b3o$14948bo$14949bo67$249385b3o$249385bo$249386bo647$
250038b2o$250038bobo$250038bo301$15962b3o$15962bo$15963bo128$133844bo$
133843b2o$133843bobo652$134512b3o$134512bo$134513bo37$251173b3o$
251173bo$251174bo448$17223b2o$17222b2o$17224bo137$135117b2o$135117bobo
$135117bo31$251788b3o$251788bo$251789bo479$17892b2o$17892bobo$17892bo
14$135642b3o$135642bo$135643bo150$252426bo$252425b2o$252425bobo417$
136215bo$136214b2o$136214bobo40$18496b3o$18496bo$18497bo191$253094b3o$
253094bo$253095bo334$19022b2o$19022bobo$19022bo290$253699b2o$253699bob
o$253699bo158$137241bo$137240b2o$137240bobo118$19594b2o$19593b2o$
19595bo248$254224b3o$254224bo$254225bo285$137905bo$137904b2o$137904bob
o282$254797bo$254796b2o$254796bobo200$20620b2o$20619b2o$20621bo169$
138546b2o$138545b2o$138547bo484$21284b2o$21283b2o$21285bo21$139048bo$
139047b2o$139047bobo139$255823bo$255822b2o$255822bobo490$21926bo$
21925b2o$21925bobo163$256487bo$256486b2o$256486bobo343$22427b2o$22426b
2o$22428bo120$140338b3o$140338bo$140339bo188$257128b2o$257127b2o$
257129bo384$140917b2o$140916b2o$140918bo121$257630bo$257629b2o$257629b
obo441$23718b2o$23718bobo$23718bo445$141938bo$141937b2o$141937bobo127$
24297bo$24296b2o$24296bobo244$258920b3o$258920bo$258921bo103$142412bo$
142411b2o$142411bobo469$259499b2o$259498b2o$259500bo190$25317b2o$
25316b2o$25318bo468$143532b2o$143531b2o$143533bo8$25791b2o$25790b2o$
25792bo339$260520bo$260519b2o$260519bobo87$143983bo$143982b2o$143982bo
bo389$260994bo$260993b2o$260993bobo224$144597bo$144596b2o$144596bobo
83$26912bo$26911b2o$26911bobo439$27362b2o$27361b2o$27363bo89$145218b3o
$145218bo$145219bo288$262114b2o$262113b2o$262115bo234$27976b2o$27975b
2o$27977bo202$262565bo$262564b2o$262564bobo160$146131b2o$146131bobo$
146131bo248$28598b2o$28598bobo$28598bo203$263179bo$263178b2o$263178bob
o376$146974b2o$146974bobo$146974bo237$263800b3o$263800bo$263801bo69$
29510b3o$29510bo$29511bo290$147576b2o$147576bobo$147576bo527$264713b2o
$264713bobo$264713bo10$30353b3o$30353bo$30354bo28$148138b3o$148138bo$
148139bo570$30955b3o$30955bo$30956bo217$265556b2o$265556bobo$265556bo
316$149261b3o$149261bo$149262bo31$31518b2o$31518bobo$31518bo249$
266158b2o$266158bobo$266158bo279$149826b3o$149826bo$149827bo288$
266720b3o$266720bo$266721bo284$150406b3o$32641b2o117763bo$32641bobo
117763bo$32641bo563$33206b2o$33206bobo$33206bo255$267843b3o$267843bo$
267844bo317$33786b2o$33786bobo$33786bo36$151508b2o$151508bobo$151508bo
206$268408b3o$268408bo$268409bo104$151818b3o$151818bo$151819bo468$
268988b3o$268988bo$268989bo109$152402b2o$152402bobo$152402bo246$34887b
3o$34887bo$34888bo311$35198b2o$35198bobo$35198bo89$153047b3o$153047bo$
153048bo415$270090b2o$270090bobo$270090bo72$35781b3o$35781bo$35782bo
238$270400b3o$270400bo$270401bo239$154029b2o$154028b2o$154030bo168$
36427b2o$36427bobo$36427bo168$270984b2o$270984bobo$270984bo650$271629b
3o$271629bo$271630bo128$155135b2o$155135bobo$155135bo18$37409bo$37408b
2o$37408bobo820$272611b2o$272610b2o$272612bo205$156182b2o$156181b2o$
156183bo92$38514b3o$38514bo$38515bo489$156768b2o$156767b2o$156769bo
328$273717b2o$273717bobo$273717bo225$39562bo$39561b2o$39561bobo583$
40148bo$40147b2o$40147bobo69$157983b2o$157983bobo$157983bo164$274764b
2o$274763b2o$274765bo415$158562b3o$158562bo$158563bo166$275350b2o$
275349b2o$275351bo390$41362b3o$41362bo$41363bo574$159699b2o$159699bobo
$159699bo4$41942b2o$41942bobo$41942bo237$276565b2o$276565bobo$276565bo
208$160143b2o$160142b2o$160144bo371$277144b3o$277144bo$277145bo288$
160824b3o$160824bo$160825bo23$43078b3o$43078bo$43079bo452$43523bo$
43522b2o$43522bobo365$278281b2o$278281bobo$278281bo227$161898b2o$
161897b2o$161899bo65$44204b2o$44204bobo$44204bo157$278725b2o$278724b2o
$278726bo183$162317b2o$162316b2o$162318bo476$279406b3o$279406bo$
279407bo251$45278bo$45277b2o$45277bobo409$45697bo$45696b2o$45696bobo
220$163672bo$163671b2o$163671bobo187$280480b2o$280479b2o$280481bo409$
280899b2o$280898b2o$280900bo439$164720b2o$164720bobo$164720bo100$
47051b2o$47050b2o$47052bo210$165030b3o$165030bo$165031bo607$282254bo$
282253b2o$282253bobo218$48099b3o$48099bo$48100bo311$48410b2o$48410bobo
$48410bo34$166217b2o$166217bobo$166217bo470$283302b2o$283302bobo$
283302bo110$166790bo$166789b2o$166789bobo200$283612b3o$283612bo$
283613bo355$49596b3o$49596bo$49597bo302$167654bo$167653b2o$167653bobo
278$50169b2o$50168b2o$50170bo235$284799b2o$284799bobo$284799bo128$
168312bo$168311b2o$168311bobo452$285372bo$285371b2o$285371bobo40$
51033b2o$51032b2o$51034bo645$51691b2o$51690b2o$51692bo84$169559b2o$
169559bobo$169559bo86$286236bo$286235b2o$286235bobo645$286894bo$
286893b2o$286893bobo406$52938b3o$52938bo$52939bo157$170863b2o$170862b
2o$170864bo660$288141b2o$288141bobo$288141bo448$171971b2o$171970b2o$
171972bo28$54243bo$54242b2o$54242bobo556$172557bo$172556b2o$172556bobo
262$289445b2o$289444b2o$289446bo288$55351bo$55350b2o$55350bobo587$
55936b2o$55935b2o$55937bo137$173844bo$173843b2o$173843bobo92$290553b2o
$290552b2o$290554bo586$291139bo$291138b2o$291138bobo459$57223b2o$
57222b2o$57224bo151$175140b3o$175140bo$175141bo666$292426bo$292425b2o$
292425bobo472$58520b2o$58520bobo$58520bo134$176406b3o$176406bo$176407b
o684$293722b3o$293722bo$293723bo360$177453b2o$177453bobo$177453bo92$
59786b2o$59786bobo$59786bo315$177872b2o$177872bobo$177872bo503$294988b
3o$294988bo$294989bo225$60832b3o$60832bo$60833bo409$61251b3o$61251bo$
61252bo34$179036b3o$179036bo$179037bo372$296035b2o$296035bobo$296035bo
409$296454b2o$296454bobo$296454bo355$62416b2o$62416bobo$62416bo138$
180319b2o$180319bobo$180319bo680$297618b3o$297618bo$297619bo183$
181182b2o$181182bobo$181182bo274$63698b3o$63698bo$63699bo819$298901b2o
$298901bobo$298901bo44$64561b3o$64561bo$64562bo519$182879b3o$182879bo$
182880bo298$299764b2o$299764bobo$299764bo347$183532b2o$183532bobo$
183532bo491$66259b2o$66259bobo$66259bo648$66911b3o$66911bo$66912bo24$
184708bo$184707b2o$184707bobo144$301461b3o$301461bo$301462bo470$
185316b2o$185316bobo$185316bo175$302114b2o$302114bobo$302114bo346$
68087b2o$68086b2o$68088bo599$186460b2o$186460bobo$186460bo15$68695b3o$
68695bo$68696bo201$303290bo$303289b2o$303289bobo185$186867b2o$186867bo
bo$186867bo429$303898b2o$303898bobo$303898bo228$187520b3o$187520bo$
187521bo73$69839b3o$69839bo$69840bo381$187985b3o$187985bo$187986bo22$
70246b3o$70246bo$70247bo412$305042b2o$305042bobo$305042bo244$70900b2o$
70900bobo$70900bo159$305449b2o$305449bobo$305449bo295$71365b2o$71365bo
bo$71365bo158$189266b3o$189266bo$189267bo202$306102b3o$306102bo$
306103bo339$189815b2o$189815bobo$189815bo115$306567b3o$306567bo$
306568bo478$72646b2o$72646bobo$72646bo427$190849b2o$190848b2o$190850bo
115$73194b3o$73194bo$73195bo274$307848b3o$307848bo$307849bo506$191756b
o$191755b2o$191755bobo35$308397b2o$308397bobo$308397bo202$74229bo$
74228b2o$74228bobo668$192655b2o$192654b2o$192656bo150$309431b2o$
309430b2o$309432bo78$75135b2o$75134b2o$75136bo221$193109b3o$193109bo$
193110bo596$310338bo$310337b2o$310337bobo87$76035bo$76034b2o$76034bobo
5$193813b2o$193813bobo$193813bo446$76489b2o$76489bobo$76489bo365$
311237b2o$311236b2o$311238bo286$194917bo$194916b2o$194916bobo38$77192b
3o$77192bo$77193bo125$311691b3o$311691bo$311692bo692$312395b2o$312395b
obo$312395bo216$196003b2o$196002b2o$196004bo62$78296b2o$78295b2o$
78297bo819$313499bo$313498b2o$313498bobo241$197114b2o$197113b2o$
197115bo12$79383bo$79382b2o$79382bobo619$197752b2o$197752bobo$197752bo
199$314585b2o$314584b2o$314586bo304$80494bo$80493b2o$80493bobo84$
198343b2o$198343bobo$198343bo548$81131b3o$81131bo$81132bo64$198965b2o$
198965bobo$198965bo118$315696b2o$315695b2o$315697bo288$199384b3o$
199384bo$199385bo115$81722b3o$81722bo$81723bo226$316334b2o$316334bobo$
316334bo188$199898b2o$199897b2o$199899bo196$82344b3o$82344bo$82345bo
203$316925b2o$316925bobo$316925bo202$82764b2o$82764bobo$82764bo403$
200912bo$200911b2o$200911bobo5$317547b2o$317547bobo$317547bo121$83278b
o$83277b2o$83277bobo285$317966b3o$317966bo$317967bo231$201548b2o$
201548bobo$201548bo300$318480b2o$318479b2o$318481bo189$84291b2o$84290b
2o$84292bo648$84927b3o$84927bo$84928bo131$202792b2o$202792bobo$202792b
o36$319494bo$319493b2o$319493bobo648$320130b2o$320130bobo$320130bo394$
203896b2o$203895b2o$203897bo57$86171b3o$86171bo$86172bo819$321374b2o$
321374bobo$321374bo260$87276bo$87275b2o$87275bobo29$205094b3o$205094bo
$205095bo657$205739bo$205738b2o$205738bobo130$322478b2o$322477b2o$
322479bo349$88474b2o$88474bobo$88474bo651$206875bo$206874b2o$206874bob
o5$89118b2o$89117b2o$89119bo160$323676b3o$323676bo$323677bo657$324321b
o$324320b2o$324320bobo284$208003b2o$208002b2o$208004bo27$90254b2o$
90253b2o$90255bo591$208613b2o$208613bobo$208613bo226$325457bo$325456b
2o$325456bobo290$91383bo$91382b2o$91382bobo88$209219b2o$209219bobo$
209219bo531$91992b3o$91992bo$91993bo197$326585b2o$326584b2o$326586bo
409$92598b3o$92598bo$92599bo157$210522b3o$210522bo$210523bo50$327195b
2o$327195bobo$327195bo410$210987b2o$210987bobo$210987bo196$327801b2o$
327801bobo$327801bo478$93902b2o$93902bobo$93902bo463$94366b3o$94366bo$
94367bo83$212211bo$212210b2o$212210bobo270$329104b3o$329104bo$329105bo
217$212704b3o$212704bo$212705bo243$329569b2o$329569bobo$329569bo405$
95590b2o$95589b2o$95591bo488$96084b2o$96084bobo$96084bo148$214001b2o$
214001bobo$214001bo179$330793bo$330792b2o$330792bobo489$331286b3o$
331286bo$331287bo452$215137b2o$215136b2o$215138bo15$97380b3o$97380bo$
97381bo677$215817b3o$215817bo$215818bo140$332583b2o$332583bobo$332583b
o302$98517bo$98516b2o$98516bobo629$216911bo$216910b2o$216910bobo63$
99197b2o$99197bobo$99197bo124$333719b2o$333718b2o$333720bo248$217355bo
$217354b2o$217354bobo444$334399b3o$334399bo$334400bo254$100290b2o$
100289b2o$100291bo439$100734b2o$100733b2o$100735bo22$218520b3o$218520b
o$218521bo354$335493bo$335492b2o$335492bobo212$219089b3o$219089bo$
219090bo225$335937bo$335936b2o$335936bobo343$101900b2o$101900bobo$
101900bo501$220172b2o$220171b2o$220173bo65$102469b2o$102469bobo$
102469bo250$337102b3o$337102bo$337103bo568$337671b3o$337671bo$337672bo
123$221183bo$221182b2o$221182bobo126$103552bo$103551b2o$103551bobo399$
221712bo$221711b2o$221711bobo419$338754b2o$338753b2o$338755bo191$
104562b2o$104561b2o$104563bo527$105091b2o$105090b2o$105092bo214$
223068b3o$223068bo$223069bo74$339765bo$339764b2o$339764bobo492$223632b
o$223631b2o$223631bobo33$340294bo$340293b2o$340293bobo535$106448b2o$
106448bobo$106448bo569$107011b2o$107010b2o$107012bo139$224907b3o$
224907bo$224908bo108$341650b3o$341650bo$341651bo568$342214bo$342213b2o
$342213bobo30$225619b3o$225619bo$225620bo428$108287b2o$108287bobo$
108287bo262$226324bo$226323b2o$226323bobo446$108999b2o$108999bobo$
108999bo108$343489b3o$343489bo$343490bo558$227466bo$227465b2o$227465bo
bo23$109703b2o$109702b2o$109704bo125$344201b3o$344201bo$344202bo692$
344906bo$344905b2o$344905bobo286$228594b2o$228593b2o$228595bo7$110845b
2o$110844b2o$110846bo646$229252bo$229251b2o$229251bobo171$346048bo$
346047b2o$346047bobo310$111974bo$111973b2o$111973bobo656$112631b2o$
112630b2o$112632bo151$230548b3o$230548bo$230549bo9$347176b2o$347175b2o
$347177bo655$347834bo$347833b2o$347833bobo417$231645b2o$231645bobo$
231645bo53$113928b2o$113928bobo$113928bo760$232453b2o$232453bobo$
232453bo58$349130b3o$349130bo$349131bo264$115024b3o$115024bo$115025bo
303$233083bo$233082b2o$233082bobo510$115832b3o$115832bo$115833bo2$
350227b2o$350227bobo$350227bo625$116462b2o$116461b2o$116463bo141$
234381b2o$234381bobo$234381bo45$351035b2o$351035bobo$351035bo629$
351665bo$351664b2o$351664bobo463$117760b3o$117760bo$117761bo819$
352963b2o$352963bobo$352963bo1401$354370b2o$354370bobo$119991b2o
234377bo$119991bobo$119991bo7$237763b2o$237763bobo$237763bo!

If I string these together with an initial Cordership seed, such that the leftover output block of each seed becomes the target block of the next recipe, then the four resulting Corderships should be able to do the job of the first four Corderships in the SE Corderfleet.

A little rearrangement of recipes with Shift+S and experimental run-and-undo cycles in Golly lets me locate where the recipes should be pasted in relation to each other -- see purple marked locations. Paste the middle recipe's target block onto the left recipe's purple block, then the right recipe's target block onto the middle recipe's purple block -- and then just remove those ex-purple blocks so they don't cause trouble:

Code: Select all

x = 970384, y = 375967, rule = LifeSuper
2H$2H6$11.2M237761.2M356619.2M$11.2M237761.2M356619.2M$237772.2H$
237772.2H1931$1942.M$1941.2M$1941.M.M384$2329.M$2328.2M$2328.M.M1121$
3453.2M$3452.2M$3454.M452$3897.M$3896.2M$3896.M.M1285$5189.2M$5189.M.
M$5189.M668$5860.3M$5860.M$5861.M1239$7099.2M$7099.M.M$7099.M1135$
8235.3M$8235.M$8236.M926$9164.3M$9164.M$9165.M524$9694.2M$9694.M.M$
9694.M1146$10844.2M$10844.M.M$10844.M964$11808.3M$11808.M$11809.M
1109$12923.2M$12923.M.M$12923.M581$13514.2M$13514.M.M$13514.M593$
14112.2M$14112.M.M$14112.M836$14959.3M$14959.M$14960.M1019$15973.3M$
15973.M$15974.M1271$17234.2M$17233.2M$17235.M651$17903.2M$17903.M.M$
17903.M627$18507.3M$18507.M$18508.M527$19033.2M$19033.M.M$19033.M570$
19605.2M$19604.2M$19606.M1021$20631.2M$20630.2M$20632.M655$21295.2M$
21294.2M$21296.M654$21937.M$21936.2M$21936.M.M508$22438.2M$22437.2M$
22439.M1262$23729.2M$23729.M.M$23729.M574$24308.M$24307.2M$24307.M.M
1012$25328.2M$25327.2M$25329.M478$25802.2M$25801.2M$25803.M1130$
26923.M$26922.2M$26922.M.M439$27373.2M$27372.2M$27374.M615$27987.2M$
27986.2M$27988.M614$28609.2M$28609.M.M$28609.M891$29521.3M$29521.M$
29522.M831$30364.3M$30364.M$30365.M600$30966.3M$30966.M$30967.M568$
31529.2M$31529.M.M$31529.M1107$32652.2M$32652.M.M$32652.M563$33217.2M
$33217.M.M$33217.M574$33797.2M$33797.M.M$33797.M1179$34898.3M$34898.M
$34899.M311$35209.2M$35209.M.M$35209.M580$35792.3M$35792.M$35793.M
649$36438.2M$36438.M.M$36438.M970$37420.M$37419.2M$37419.M.M1121$
38525.3M$38525.M$38526.M1046$39573.M$39572.2M$39572.M.M583$40159.M$
40158.2M$40158.M.M1212$41373.3M$41373.M$41374.M580$41953.2M$41953.M.M
$41953.M1135$43089.3M$43089.M$43090.M452$43534.M$43533.2M$43533.M.M
661$44215.2M$44215.M.M$44215.M1073$45289.M$45288.2M$45288.M.M409$
45708.M$45707.2M$45707.M.M1363$47062.2M$47061.2M$47063.M1039$48110.3M
$48110.M$48111.M311$48421.2M$48421.M.M$48421.M1177$49607.3M$49607.M$
49608.M582$50180.2M$50179.2M$50181.M861$51044.2M$51043.2M$51045.M645$
51702.2M$51701.2M$51703.M1227$52949.3M$52949.M$52950.M1299$54254.M$
54253.2M$54253.M.M1110$55362.M$55361.2M$55361.M.M587$55947.2M$55946.
2M$55948.M1280$57234.2M$57233.2M$57235.M1293$58531.2M$58531.M.M$
58531.M1276$59797.2M$59797.M.M$59797.M1047$60843.3M$60843.M$60844.M
409$61262.3M$61262.M$61263.M1176$62427.2M$62427.M.M$62427.M1281$
63709.3M$63709.M$63710.M865$64572.3M$64572.M$64573.M1661$66270.2M$
66270.M.M$66270.M648$66922.3M$66922.M$66923.M1167$68098.2M$68097.2M$
68099.M616$68706.3M$68706.M$68707.M1124$69850.3M$69850.M$69851.M405$
70257.3M$70257.M$70258.M658$70911.2M$70911.M.M$70911.M456$71376.2M$
71376.M.M$71376.M1300$72657.2M$72657.M.M$72657.M544$73205.3M$73205.M$
73206.M1023$74240.M$74239.2M$74239.M.M900$75146.2M$75145.2M$75147.M
908$76046.M$76045.2M$76045.M.M453$76500.2M$76500.M.M$76500.M693$
77203.3M$77203.M$77204.M1101$78307.2M$78306.2M$78308.M1076$79394.M$
79393.2M$79393.M.M1126$80505.M$80504.2M$80504.M.M634$81142.3M$81142.M
$81143.M591$81733.3M$81733.M$81734.M614$82355.3M$82355.M$82356.M407$
82775.2M$82775.M.M$82775.M533$83289.M$83288.2M$83288.M.M1011$84302.2M
$84301.2M$84303.M648$84938.3M$84938.M$84939.M1274$86182.3M$86182.M$
86183.M1081$87287.M$87286.2M$87286.M.M1171$88485.2M$88485.M.M$88485.M
658$89129.2M$89128.2M$89130.M1134$90265.2M$90264.2M$90266.M1111$
91394.M$91393.2M$91393.M.M621$92003.3M$92003.M$92004.M608$92609.3M$
92609.M$92610.M1299$93913.2M$93913.M.M$93913.M463$94377.3M$94377.M$
94378.M1226$95601.2M$95600.2M$95602.M488$96095.2M$96095.M.M$96095.M
1291$97391.3M$97391.M$97392.M1123$98528.M$98527.2M$98527.M.M694$
99208.2M$99208.M.M$99208.M1076$100301.2M$100300.2M$100302.M439$
100745.2M$100744.2M$100746.M1164$101911.2M$101911.M.M$101911.M568$
102480.2M$102480.M.M$102480.M1073$103563.M$103562.2M$103562.M.M1013$
104573.2M$104572.2M$104574.M527$105102.2M$105101.2M$105103.M1356$
106459.2M$106459.M.M$106459.M569$107022.2M$107021.2M$107023.M1281$
108298.2M$108298.M.M$108298.M710$109010.2M$109010.M.M$109010.M693$
109714.2M$109713.2M$109715.M1116$110856.2M$110855.2M$110857.M1131$
111985.M$111984.2M$111984.M.M656$112642.2M$112641.2M$112643.M1293$
113939.2M$113939.M.M$113939.M1086$115035.3M$115035.M$115036.M815$
115843.3M$115843.M$115844.M629$116473.2M$116472.2M$116474.M1284$
117771.3M$117771.M$117772.M2224$120002.2M$120002.M.M$120002.M9982$
367714.M$367713.2M$367713.M.M588$368300.2M$368299.2M$368301.M1023$
369334.M$369333.2M$369333.M.M520$369838.3M$369838.M$369839.M1050$
370898.M$370897.2M$370897.M.M652$371562.2M$371561.2M$371563.M654$
372209.3M$372209.M$372210.M1021$373235.3M$373235.M$373236.M1054$
374293.3M$374293.M$374294.M1106$375401.2M$375401.M.M$375401.M920$
376326.2M$376326.M.M$376326.M1039$377374.3M$377374.M$377375.M1353$
378732.3M$378732.M$378733.M835$379580.2M$379580.M.M$379580.M1019$
380594.2M$380594.M.M$380594.M1271$381855.M$381854.2M$381854.M.M652$
382523.3M$382523.M$382524.M626$383128.2M$383128.M.M$383128.M528$
383653.3M$383653.M$383654.M569$384226.M$384225.2M$384225.M.M1021$
385252.M$385251.2M$385251.M.M655$385916.M$385915.2M$385915.M.M655$
386557.2M$386556.2M$386558.M507$387059.M$387058.2M$387058.M.M1263$
388349.3M$388349.M$388350.M574$388928.2M$388927.2M$388929.M1011$
389949.M$389948.2M$389948.M.M478$390423.M$390422.2M$390422.M.M1131$
391543.2M$391542.2M$391544.M438$391994.M$391993.2M$391993.M.M615$
392608.M$392607.2M$392607.M.M615$393229.3M$393229.M$393230.M890$
394142.2M$394142.M.M$394142.M831$394985.2M$394985.M.M$394985.M600$
395587.2M$395587.M.M$395587.M569$396149.3M$396149.M$396150.M1107$
397272.3M$397272.M$397273.M563$397837.3M$397837.M$397838.M574$398417.
3M$398417.M$398418.M1178$399519.2M$399519.M.M$399519.M312$399829.3M$
399829.M$399830.M579$400413.2M$400413.M.M$400413.M650$401058.3M$
401058.M$401059.M970$402040.2M$402039.2M$402041.M1120$403146.2M$
403146.M.M$403146.M1047$404193.2M$404192.2M$404194.M583$404779.2M$
404778.2M$404780.M1211$405994.2M$405994.M.M$405994.M581$406573.3M$
406573.M$406574.M1134$407710.2M$407710.M.M$407710.M453$408154.2M$
408153.2M$408155.M661$408835.3M$408835.M$408836.M1073$409909.2M$
409908.2M$409910.M409$410328.2M$410327.2M$410329.M1362$411683.M$
411682.2M$411682.M.M1039$412731.2M$412731.M.M$412731.M312$413041.3M$
413041.M$413042.M1176$414228.2M$414228.M.M$414228.M582$414801.M$
414800.2M$414800.M.M861$415665.M$415664.2M$415664.M.M645$416323.M$
416322.2M$416322.M.M1227$417570.2M$417570.M.M$417570.M1300$418874.2M$
418873.2M$418875.M1110$419982.2M$419981.2M$419983.M586$420568.M$
420567.2M$420567.M.M1280$421855.M$421854.2M$421854.M.M1294$423151.3M$
423151.M$423152.M1276$424417.3M$424417.M$424418.M1046$425464.2M$
425464.M.M$425464.M409$425883.2M$425883.M.M$425883.M1177$427047.3M$
427047.M$427048.M1280$428330.2M$428330.M.M$428330.M865$429193.2M$
429193.M.M$429193.M1662$430890.3M$430890.M$430891.M647$431543.2M$
431543.M.M$431543.M1167$432719.M$432718.2M$432718.M.M616$433327.2M$
433327.M.M$433327.M1124$434471.2M$434471.M.M$434471.M405$434878.2M$
434878.M.M$434878.M659$435531.3M$435531.M$435532.M456$435996.3M$
435996.M$435997.M1300$437277.3M$437277.M$437278.M543$437826.2M$
437826.M.M$437826.M1024$438860.2M$438859.2M$438861.M899$439767.M$
439766.2M$439766.M.M909$440666.2M$440665.2M$440667.M453$441120.3M$
441120.M$441121.M692$441824.2M$441824.M.M$441824.M1101$442928.M$
442927.2M$442927.M.M1077$444014.2M$444013.2M$444015.M1126$445125.2M$
445124.2M$445126.M633$445763.2M$445763.M.M$445763.M591$446354.2M$
446354.M.M$446354.M614$446976.2M$446976.M.M$446976.M408$447395.3M$
447395.M$447396.M533$447909.2M$447908.2M$447910.M1010$448923.M$
448922.2M$448922.M.M648$449559.2M$449559.M.M$449559.M1274$450803.2M$
450803.M.M$450803.M1082$451907.2M$451906.2M$451908.M1171$453105.3M$
453105.M$453106.M657$453750.M$453749.2M$453749.M.M1134$454886.M$
454885.2M$454885.M.M1112$456014.2M$456013.2M$456015.M620$456624.2M$
456624.M.M$456624.M608$457230.2M$457230.M.M$457230.M1300$458533.3M$
458533.M$458534.M462$458998.2M$458998.M.M$458998.M1226$460222.M$
460221.2M$460221.M.M489$460715.3M$460715.M$460716.M1290$462012.2M$
462012.M.M$462012.M1124$463148.2M$463147.2M$463149.M694$463828.3M$
463828.M$463829.M1075$464922.M$464921.2M$464921.M.M439$465366.M$
465365.2M$465365.M.M1165$466531.3M$466531.M$466532.M568$467100.3M$
467100.M$467101.M1073$468183.2M$468182.2M$468184.M1012$469194.M$
469193.2M$469193.M.M527$469723.M$469722.2M$469722.M.M1357$471079.3M$
471079.M$471080.M568$471643.M$471642.2M$471642.M.M1282$472918.3M$
472918.M$472919.M710$473630.3M$473630.M$473631.M692$474335.M$474334.
2M$474334.M.M1116$475477.M$475476.2M$475476.M.M1132$476605.2M$476604.
2M$476606.M655$477263.M$477262.2M$477262.M.M1294$478559.3M$478559.M$
478560.M1085$479656.2M$479656.M.M$479656.M815$480464.2M$480464.M.M$
480464.M629$481094.M$481093.2M$481093.M.M1284$482392.2M$482392.M.M$
482392.M3376$485774.2M$485774.M.M$485774.M9883$852252.3M$852252.M$
852253.M1212$853457.2M$853457.M.M$853457.M1037$854505.2M$854505.M.M$
854505.M1138$855640.3M$855640.M$855641.M1003$856648.2M$856647.2M$
856649.M718$857364.2M$857363.2M$857365.M644$858001.3M$858001.M$
858002.M1258$859265.2M$859264.2M$859266.M939$860207.M$860206.2M$
860206.M.M581$860793.2M$860793.M.M$860793.M626$861407.M$861406.2M$
861406.M.M584$862001.2M$862001.M.M$862001.M439$862445.2M$862445.M.M$
862445.M658$863106.3M$863106.M$863107.M569$863676.3M$863676.M$863677.
M439$864120.3M$864120.M$864121.M1266$865396.3M$865396.M$865397.M647$
866049.2M$866049.M.M$866049.M1124$867184.3M$867184.M$867185.M620$
867799.3M$867799.M$867800.M647$868437.M$868436.2M$868436.M.M652$
869105.3M$869105.M$869106.M626$869710.2M$869710.M.M$869710.M528$
870235.3M$870235.M$870236.M569$870808.M$870807.2M$870807.M.M1021$
871834.M$871833.2M$871833.M.M655$872498.M$872497.2M$872497.M.M655$
873139.2M$873138.2M$873140.M507$873641.M$873640.2M$873640.M.M1263$
874931.3M$874931.M$874932.M574$875510.2M$875509.2M$875511.M1011$
876531.M$876530.2M$876530.M.M478$877005.M$877004.2M$877004.M.M1131$
878125.2M$878124.2M$878126.M438$878576.M$878575.2M$878575.M.M615$
879190.M$879189.2M$879189.M.M615$879811.3M$879811.M$879812.M890$
880724.2M$880724.M.M$880724.M831$881567.2M$881567.M.M$881567.M600$
882169.2M$882169.M.M$882169.M569$882731.3M$882731.M$882732.M1107$
883854.3M$883854.M$883855.M563$884419.3M$884419.M$884420.M574$884999.
3M$884999.M$885000.M1178$886101.2M$886101.M.M$886101.M312$886411.3M$
886411.M$886412.M579$886995.2M$886995.M.M$886995.M650$887640.3M$
887640.M$887641.M970$888622.2M$888621.2M$888623.M1120$889728.2M$
889728.M.M$889728.M1047$890775.2M$890774.2M$890776.M583$891361.2M$
891360.2M$891362.M1211$892576.2M$892576.M.M$892576.M581$893155.3M$
893155.M$893156.M1134$894292.2M$894292.M.M$894292.M453$894736.2M$
894735.2M$894737.M661$895417.3M$895417.M$895418.M1073$896491.2M$
896490.2M$896492.M409$896910.2M$896909.2M$896911.M1362$898265.M$
898264.2M$898264.M.M1039$899313.2M$899313.M.M$899313.M312$899623.3M$
899623.M$899624.M1176$900810.2M$900810.M.M$900810.M582$901383.M$
901382.2M$901382.M.M861$902247.M$902246.2M$902246.M.M645$902905.M$
902904.2M$902904.M.M1227$904152.2M$904152.M.M$904152.M1300$905456.2M$
905455.2M$905457.M1110$906564.2M$906563.2M$906565.M586$907150.M$
907149.2M$907149.M.M1280$908437.M$908436.2M$908436.M.M1294$909733.3M$
909733.M$909734.M1276$910999.3M$910999.M$911000.M1046$912046.2M$
912046.M.M$912046.M409$912465.2M$912465.M.M$912465.M1177$913629.3M$
913629.M$913630.M1280$914912.2M$914912.M.M$914912.M865$915775.2M$
915775.M.M$915775.M1662$917472.3M$917472.M$917473.M647$918125.2M$
918125.M.M$918125.M1167$919301.M$919300.2M$919300.M.M616$919909.2M$
919909.M.M$919909.M1124$921053.2M$921053.M.M$921053.M405$921460.2M$
921460.M.M$921460.M659$922113.3M$922113.M$922114.M456$922578.3M$
922578.M$922579.M1300$923859.3M$923859.M$923860.M543$924408.2M$
924408.M.M$924408.M1024$925442.2M$925441.2M$925443.M899$926349.M$
926348.2M$926348.M.M909$927248.2M$927247.2M$927249.M453$927702.3M$
927702.M$927703.M692$928406.2M$928406.M.M$928406.M1101$929510.M$
929509.2M$929509.M.M1077$930596.2M$930595.2M$930597.M1126$931707.2M$
931706.2M$931708.M633$932345.2M$932345.M.M$932345.M591$932936.2M$
932936.M.M$932936.M614$933558.2M$933558.M.M$933558.M408$933977.3M$
933977.M$933978.M533$934491.2M$934490.2M$934492.M1010$935505.M$
935504.2M$935504.M.M648$936141.2M$936141.M.M$936141.M1274$937385.2M$
937385.M.M$937385.M1082$938489.2M$938488.2M$938490.M1171$939687.3M$
939687.M$939688.M657$940332.M$940331.2M$940331.M.M1134$941468.M$
941467.2M$941467.M.M1112$942596.2M$942595.2M$942597.M620$943206.2M$
943206.M.M$943206.M608$943812.2M$943812.M.M$943812.M1300$945115.3M$
945115.M$945116.M462$945580.2M$945580.M.M$945580.M1226$946804.M$
946803.2M$946803.M.M489$947297.3M$947297.M$947298.M1290$948594.2M$
948594.M.M$948594.M1124$949730.2M$949729.2M$949731.M694$950410.3M$
950410.M$950411.M1075$951504.M$951503.2M$951503.M.M439$951948.M$
951947.2M$951947.M.M1165$953113.3M$953113.M$953114.M568$953682.3M$
953682.M$953683.M1073$954765.2M$954764.2M$954766.M1012$955776.M$
955775.2M$955775.M.M527$956305.M$956304.2M$956304.M.M1357$957661.3M$
957661.M$957662.M568$958225.M$958224.2M$958224.M.M1282$959500.3M$
959500.M$959501.M710$960212.3M$960212.M$960213.M692$960917.M$960916.
2M$960916.M.M1116$962059.M$962058.2M$962058.M.M1132$963187.2M$963186.
2M$963188.M655$963845.M$963844.2M$963844.M.M1294$965141.3M$965141.M$
965142.M1085$966238.2M$966238.M.M$966238.M815$967046.2M$967046.M.M$
967046.M629$967676.M$967675.2M$967675.M.M1284$968974.2M$968974.M.M$
968974.M1401$970381.2M$970381.M.M$970381.M!

... Yup, looks like it works:

Code: Select all

x = 376178, y = 378322, rule = LifeSuper
376176.M$376175.M$376175.3M1405$374773.M$374772.M$374772.3M1297$
373488.M$373486.2M$373487.2M627$372856.M$372855.M$372855.3M806$
372039.M$372038.M$372038.3M1095$370951.M$370951.M.M$370951.2M1295$
369657.M$369655.2M$369656.2M656$368998.M.M$368998.2M$368999.M1126$
367866.M$367864.2M$367865.2M1140$366748.M$366746.2M$366747.2M702$
366052.M$366052.M.M$366052.2M710$365340.M$365340.M.M$365340.2M1274$
364058.M$364056.2M$364057.2M561$363486.M$363486.M.M$363486.2M1355$
362129.M$362127.2M$362128.2M527$361600.M$361598.2M$361599.2M1009$
360584.M.M$360584.2M$360585.M1080$359509.M$359509.M.M$359509.2M567$
358939.M$358939.M.M$358939.2M1164$357774.M$357772.2M$357773.2M442$
357333.M$357331.2M$357332.2M1091$356254.M$356254.M.M$356254.2M679$
355558.M.M$355558.2M$355559.M1133$354433.M$354432.M$354432.3M1295$
353140.M$353140.M.M$353140.2M492$352651.M$352649.2M$352650.2M1221$
351422.M$351421.M$351421.3M463$350957.M$350957.M.M$350957.2M1301$
349656.M$349655.M$349655.3M604$349046.M$349045.M$349045.3M609$348423.
M.M$348423.2M$348424.M1126$347311.M$347309.2M$347310.2M1134$346175.M$
346173.2M$346174.2M642$345514.M$345514.M.M$345514.2M1197$344341.M.M$
344341.2M$344342.M1101$343258.M$343257.M$343257.3M1242$341982.M$
341981.M$341981.3M635$341333.M$341331.2M$341332.2M1012$340319.M.M$
340319.2M$340320.M511$339784.M$339784.M.M$339784.2M417$339375.M$
339374.M$339374.3M620$338759.M$338758.M$338758.3M589$338166.M$338165.
M$338165.3M637$337530.M.M$337530.2M$337531.M1109$336402.M.M$336402.2M
$336403.M1084$335325.M$335323.2M$335324.2M1101$334221.M$334220.M$
334220.3M702$333526.M$333526.M.M$333526.2M453$333071.M.M$333071.2M$
333072.M897$332162.M$332160.2M$332161.2M905$331259.M.M$331259.2M$
331260.M1031$330234.M$330233.M$330233.3M547$329688.M$329688.M.M$
329688.2M1279$328386.M$328386.M.M$328386.2M463$327928.M$327928.M.M$
327928.2M651$327268.M$327267.M$327267.3M405$326861.M$326860.M$326860.
3M1142$325735.M$325734.M$325734.3M607$325118.M$325116.2M$325117.2M
1173$323948.M$323947.M$323947.3M651$323298.M$323298.M.M$323298.2M
1695$321635.M$321634.M$321634.3M861$320768.M$320767.M$320767.3M1281$
319485.M$319485.M.M$319485.2M1162$318307.M$318306.M$318306.3M417$
317896.M$317895.M$317895.3M1045$316847.M$316847.M.M$316847.2M1264$
315569.M$315569.M.M$315569.2M1295$314275.M$314273.2M$314274.2M1285$
312993.M$312991.2M$312992.2M584$312403.M.M$312403.2M$312404.M1106$
311291.M.M$311291.2M$311292.M1301$309990.M$309989.M$309989.3M1246$
308762.M$308760.2M$308761.2M656$308115.M$308113.2M$308114.2M862$
307252.M$307250.2M$307251.2M570$306667.M$306666.M$306666.3M1185$
305488.M$305488.M.M$305488.2M308$305175.M$305174.M$305174.3M1047$
304135.M$304133.2M$304134.2M1353$302769.M.M$302769.2M$302770.M417$
302358.M.M$302358.2M$302359.M1071$301283.M$301283.M.M$301283.2M680$
300620.M.M$300620.2M$300621.M441$300166.M$300165.M$300165.3M1135$
299029.M$299029.M.M$299029.2M577$298447.M$298446.M$298446.3M1214$
297233.M.M$297233.2M$297234.M584$296648.M.M$296648.2M$296649.M1044$
295600.M$295599.M$295599.3M1105$294477.M.M$294477.2M$294478.M979$
293505.M$293505.M.M$293505.2M643$292854.M$292853.M$292853.3M582$
292272.M$292272.M.M$292272.2M308$291959.M$291958.M$291958.3M1100$
290778.M$290778.M.M$290778.2M578$290202.M$290202.M.M$290202.2M563$
289637.M$289637.M.M$289637.2M1121$288528.M$288528.M.M$288528.2M560$
287958.M$287957.M$287957.3M600$287356.M$287355.M$287355.3M841$286523.
M$286522.M$286522.3M911$285630.M$285630.M.M$285630.2M620$285015.M$
285013.2M$285014.2M612$284398.M$284396.2M$284397.2M449$283956.M.M$
283956.2M$283957.M1118$282825.M$282823.2M$282824.2M472$282345.M$
282343.2M$282344.2M1019$281330.M.M$281330.2M$281331.M576$280754.M$
280754.M.M$280754.2M1289$279491.M$279489.2M$279490.2M500$278980.M.M$
278980.2M$278981.M639$278325.M$278323.2M$278324.2M662$277668.M$
277666.2M$277667.2M1024$276645.M$276643.2M$276644.2M570$276072.M$
276072.M.M$276072.2M523$275543.M$275542.M$275542.3M603$274914.M$
274914.M.M$274914.2M667$274262.M$274260.2M$274261.2M635$273611.M$
273611.M.M$273611.2M613$272989.M$272989.M.M$272989.2M1133$271864.M$
271863.M$271863.3M651$271214.M$271214.M.M$271214.2M1274$269946.M$
269946.M.M$269946.2M442$269505.M$269505.M.M$269505.2M568$268934.M$
268934.M.M$268934.2M659$268275.M$268274.M$268274.3M442$267834.M$
267833.M$267833.3M593$267249.M$267247.2M$267248.2M611$266620.M$
266619.M$266619.3M585$266038.M$266036.2M$266037.2M940$265095.M.M$
265095.2M$265096.M1261$263835.M$263835.M.M$263835.2M636$263189.M.M$
263189.2M$263190.M714$262469.M.M$262469.2M$262470.M1005$261464.M$
261464.M.M$261464.2M1133$260325.M$260324.M$260324.3M1046$259286.M$
259285.M$259285.3M1203$258071.M$258071.M.M$258071.2M9853$248185.M$
248184.M$248184.3M3380$244807.M$244806.M$244806.3M1297$243522.M$
243520.2M$243521.2M627$242890.M$242889.M$242889.3M806$242073.M$
242072.M$242072.3M1095$240985.M$240985.M.M$240985.2M1295$239691.M$
239689.2M$239690.2M656$239032.M.M$239032.2M$239033.M1126$237900.M$
237898.2M$237899.2M1140$236782.M$236780.2M$236781.2M702$236086.M$
236086.M.M$236086.2M710$235374.M$235374.M.M$235374.2M1274$234092.M$
234090.2M$234091.2M561$233520.M$233520.M.M$233520.2M1355$232163.M$
232161.2M$232162.2M527$231634.M$231632.2M$231633.2M1009$230618.M.M$
230618.2M$230619.M1080$229543.M$229543.M.M$229543.2M567$228973.M$
228973.M.M$228973.2M1164$227808.M$227806.2M$227807.2M442$227367.M$
227365.2M$227366.2M1091$226288.M$226288.M.M$226288.2M679$225592.M.M$
225592.2M$225593.M1133$224467.M$224466.M$224466.3M1295$223174.M$
223174.M.M$223174.2M492$222685.M$222683.2M$222684.2M1221$221456.M$
221455.M$221455.3M463$220991.M$220991.M.M$220991.2M1301$219690.M$
219689.M$219689.3M604$219080.M$219079.M$219079.3M609$218457.M.M$
218457.2M$218458.M1126$217345.M$217343.2M$217344.2M1134$216209.M$
216207.2M$216208.2M642$215548.M$215548.M.M$215548.2M1197$214375.M.M$
214375.2M$214376.M1101$213292.M$213291.M$213291.3M1242$212016.M$
212015.M$212015.3M635$211367.M$211365.2M$211366.2M1012$210353.M.M$
210353.2M$210354.M511$209818.M$209818.M.M$209818.2M417$209409.M$
209408.M$209408.3M620$208793.M$208792.M$208792.3M589$208200.M$208199.
M$208199.3M637$207564.M.M$207564.2M$207565.M1109$206436.M.M$206436.2M
$206437.M1084$205359.M$205357.2M$205358.2M1101$204255.M$204254.M$
204254.3M702$203560.M$203560.M.M$203560.2M453$203105.M.M$203105.2M$
203106.M897$202196.M$202194.2M$202195.2M905$201293.M.M$201293.2M$
201294.M1031$200268.M$200267.M$200267.3M547$199722.M$199722.M.M$
199722.2M1279$198420.M$198420.M.M$198420.2M463$197962.M$197962.M.M$
197962.2M651$197302.M$197301.M$197301.3M405$196895.M$196894.M$196894.
3M1142$195769.M$195768.M$195768.3M607$195152.M$195150.2M$195151.2M
1173$193982.M$193981.M$193981.3M651$193332.M$193332.M.M$193332.2M
1695$191669.M$191668.M$191668.3M861$190802.M$190801.M$190801.3M1281$
189519.M$189519.M.M$189519.2M1162$188341.M$188340.M$188340.3M417$
187930.M$187929.M$187929.3M1045$186881.M$186881.M.M$186881.2M1264$
185603.M$185603.M.M$185603.2M1295$184309.M$184307.2M$184308.2M1285$
183027.M$183025.2M$183026.2M584$182437.M.M$182437.2M$182438.M1106$
181325.M.M$181325.2M$181326.M1301$180024.M$180023.M$180023.3M1246$
178796.M$178794.2M$178795.2M656$178149.M$178147.2M$178148.2M862$
177286.M$177284.2M$177285.2M570$176701.M$176700.M$176700.3M1185$
175522.M$175522.M.M$175522.2M308$175209.M$175208.M$175208.3M1047$
174169.M$174167.2M$174168.2M1353$172803.M.M$172803.2M$172804.M417$
172392.M.M$172392.2M$172393.M1071$171317.M$171317.M.M$171317.2M680$
170654.M.M$170654.2M$170655.M441$170200.M$170199.M$170199.3M1135$
169063.M$169063.M.M$169063.2M577$168481.M$168480.M$168480.3M1214$
167267.M.M$167267.2M$167268.M584$166682.M.M$166682.2M$166683.M1044$
165634.M$165633.M$165633.3M1105$164511.M.M$164511.2M$164512.M979$
163539.M$163539.M.M$163539.2M643$162888.M$162887.M$162887.3M582$
162306.M$162306.M.M$162306.2M308$161993.M$161992.M$161992.3M1100$
160812.M$160812.M.M$160812.2M578$160236.M$160236.M.M$160236.2M563$
159671.M$159671.M.M$159671.2M1121$158562.M$158562.M.M$158562.2M560$
157992.M$157991.M$157991.3M600$157390.M$157389.M$157389.3M841$156557.
M$156556.M$156556.3M911$155664.M$155664.M.M$155664.2M620$155049.M$
155047.2M$155048.2M612$154432.M$154430.2M$154431.2M449$153990.M.M$
153990.2M$153991.M1118$152859.M$152857.2M$152858.2M472$152379.M$
152377.2M$152378.2M1019$151364.M.M$151364.2M$151365.M576$150788.M$
150788.M.M$150788.2M1289$149525.M$149523.2M$149524.2M500$149014.M.M$
149014.2M$149015.M639$148359.M$148357.2M$148358.2M662$147702.M$
147700.2M$147701.2M1024$146679.M$146677.2M$146678.2M570$146106.M$
146106.M.M$146106.2M523$145577.M$145576.M$145576.3M603$144948.M$
144948.M.M$144948.2M667$144296.M$144294.2M$144295.2M1258$143022.M$
143021.M$143021.3M1012$142001.M$142000.M$142000.3M846$141163.M$
141163.M.M$141163.2M1356$139808.M$139808.M.M$139808.2M1046$138768.M$
138767.M$138767.3M923$137846.M$137845.M$137845.3M1106$136737.M$
136737.M.M$136737.2M1056$135681.M$135681.M.M$135681.2M1024$134658.M$
134658.M.M$134658.2M646$134002.M.M$134002.2M$134003.M662$133350.M$
133348.2M$133349.2M1057$132296.M$132296.M.M$132296.2M503$131776.M$
131774.2M$131775.2M1032$130749.M.M$130749.2M$130750.M584$130161.M$
130159.2M$130160.2M9935$120183.M$120182.M$120182.3M2229$117956.M$
117956.M.M$117956.2M1297$116670.M.M$116670.2M$116671.M627$116039.M$
116039.M.M$116039.2M806$115222.M$115222.M.M$115222.2M1094$114135.M$
114134.M$114134.3M1296$112839.M.M$112839.2M$112840.M655$112183.M$
112181.2M$112182.2M1127$111048.M.M$111048.2M$111049.M1140$109930.M.M$
109930.2M$109931.M701$109236.M$109235.M$109235.3M710$108524.M$108523.
M$108523.3M1275$107240.M.M$107240.2M$107241.M560$106670.M$106669.M$
106669.3M1356$105311.M.M$105311.2M$105312.M527$104782.M.M$104782.2M$
104783.M1008$103769.M$103767.2M$103768.2M1080$102693.M$102692.M$
102692.3M567$102123.M$102122.M$102122.3M1165$100956.M.M$100956.2M$
100957.M442$100515.M.M$100515.2M$100516.M1090$99438.M$99437.M$99437.
3M679$98743.M$98741.2M$98742.2M1134$97616.M$97616.M.M$97616.2M1294$
96324.M$96323.M$96323.3M493$95833.M.M$95833.2M$95834.M1221$94605.M$
94605.M.M$94605.2M462$94141.M$94140.M$94140.3M1302$92839.M$92839.M.M$
92839.2M604$92229.M$92229.M.M$92229.2M608$91608.M$91606.2M$91607.2M
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M$77404.2M701$76710.M$76709.M$76709.3M453$76256.M$76254.2M$76255.2M
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$61490.2M417$61079.M$61079.M.M$61079.2M1044$60031.M$60030.M$60030.3M
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56175.M.M$56175.2M$56176.M583$55588.M$55586.2M$55587.2M1106$54476.M$
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M$33385.M$33385.3M563$32821.M$32820.M$32820.3M1121$31712.M$31711.M$
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841$29706.M$29706.M.M$29706.2M910$28814.M$28813.M$28813.3M621$28197.M
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$19828.M569$19256.M$19255.M$19255.3M524$18726.M$18726.M.M$18726.2M
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M$14312.3M596$13718.M$13717.M$13717.3M589$13135.M$13134.M$13134.3M
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4$36.H.H$35.H3.H$34.H5.H$23.H10.3H4.H$22.2H.H9.H.2H.H$23.H.2H$24.H7$
14.H.H$15.H$14.H20.H$13.2H13.2H5.H$13.2H13.2H10.3H$5.H.2H.H30.H$.6H3.
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100.2H13.2H10.3H$92.H.2H.H30.H$88.6H3.H22.H6.3H$87.H4.H.H25.4H4.5H$
87.H5.H2.2H21.H3.4H.2H$88.H.2H.H2.2H22.H4.2H$91.H4.2H30.2H$95.2H3$
103.3H$95.2H6.H2.H$95.2H6.H13.3H$116.H2.2H$106.H.H.2H4.H2.H.2H$107.2H
3.H6.H.H.2H$108.4H7.H.H2.H$103.3H3.2H8.H4.H$119.H3.H$120.3H14$221.A$
221.A.A$221.2A15$213.A$212.A.A$213.2A10$224.2A$224.2A$201.A$200.A.A$
201.A$186.A36.2H$185.A.A35.3H$186.2A5.2A$193.A.A15.2A$194.A16.2A3$
230.A$229.A.A$229.2A2$218.2A3.2A$218.A.A2.A.A$219.A4.A2$208.2A$208.2A
$185.A$184.A.A$185.2A$247.2H$190.2A55.2H$190.2A2$213.2A$213.A.A34.2H$
214.A35.3H$249.H.H.2H$237.H10.3H.3H$198.2A13.2A22.3H12.H2.H$198.2A13.
A.A21.H.H$214.A24.H4$210.2A$209.A.A$210.A17.H.H$228.H.H$229.H$249.2H$
227.2H13.2H4.H$227.2H13.2H9.H.2H$222.2H24.H6.H$218.3H.3H30.H2.H$214.
4H3.H.H23.4H4.H2.H$214.4H3.H.H22.H.H2.H.3H2.H$217.3H3.H23.H4.H2.H$
221.H.H31.2H$222.2H3$231.H$222.2H6.3H$222.2H6.H.2H10.2H$233.3H7.H.2H$
233.H3.2H4.H2.H.2H$234.H3.H5.H.H.H.H$231.H3.4H7.H3.2H$231.H14.2H.2H$
231.H15.3H$248.H81$305.2S$304.S2.S$305.2S9$299.S$298.S.S$298.S2.S$
299.2S18$337.2S$336.S2.S$337.2S$290.S$290.S$290.S$301.S$300.S.S$300.
2S3$331.S$330.S.S$330.S2.S$331.2S5$301.2S$300.S2.S$301.2S2$297.3S2$
301.S$301.S$301.S2$303.2S$303.2S$313.3S$369.2S$368.S2.S$369.2S$322.S$
322.S$322.S$333.S$332.S.S$332.2S2$295.2S$295.2S66.S$362.S.S$362.S2.S$
363.2S4$291.2S$291.2S40.2S$332.S2.S$333.2S2$329.3S2$333.S$333.S$333.S
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354.S$354.S$365.S$364.S.S$364.2S2$327.2S$327.2S66.S$394.S.S$394.S2.S$
395.2S4$323.2S$323.2S40.2S$364.S2.S$365.2S2$361.3S2$365.S$365.S$365.S
$333.2S$332.S.S32.2S$332.2S33.2S$377.3S$433.2S$432.S2.S$433.2S$386.S$
386.S$386.S$397.S$396.S.S$396.2S2$359.2S$359.2S66.S$426.S.S$426.S2.S$
427.2S4$355.2S$355.2S40.2S$396.S2.S$397.2S2$393.3S2$397.S$397.S$397.S
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459.2S4$387.2S$387.2S40.2S$428.S2.S$429.2S2$425.3S2$429.S$429.S$429.S
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491.2S4$419.2S$419.2S40.2S$460.S2.S$461.2S2$457.3S2$461.S$461.S$461.S
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148.3S2$850.S154.S$1005.S$848.S156.S$973.2S$846.S125.S.S32.2S$972.2S
33.2S$844.S172.3S$1073.2S$842.S229.S2.S$1073.2S$840.S185.S$1026.S$
838.S187.S$1037.S$836.S199.S.S$1036.2S$834.S$999.2S$832.S166.2S66.S$
1066.S.S$830.S235.S2.S$1067.2S$828.S2$826.S$995.2S$824.S170.2S40.2S$
1036.S2.S$822.S214.2S2$820.S212.3S2$818.S218.S$1037.S$816.S220.S$
1005.2S$814.S189.S.S32.2S$1004.2S33.2S$812.S236.3S$1105.2S$810.S293.S
2.S$1105.2S$1058.S$1058.S$1058.S$1069.S$1068.S.S$1068.2S2$1031.2S$
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3$1163.S$1091.2S10.S58.S.S$1090.S2.S9.S58.S2.S$1091.2S10.S59.2S2$
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2$1420.Q$1419.Q.Q$1420.2Q$1389.2S$1388.S.S32.2Q$1388.2S33.2Q$1433.3S$
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1452.S.S32.2S$1352.S99.2S33.2S$1497.3S$1350.S202.2S$1552.S2.S$1348.S
204.2S$1506.S$1346.S159.S$1506.S$1344.S172.S$1516.S.S$1342.S173.2S2$
1340.S138.2S$1479.2S66.S$1338.S207.S.S$1546.S2.S$1336.S210.2S2$1334.S
2$1332.S142.2S$1475.2S40.2S$1330.S185.S2.S$1517.2S$1328.S$1513.3S$
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1516.2S33.2S$1561.3S100.W$1663.W.W$1663.W.W$1658.2W4.W$1657.W2.W$
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1839.W2.W$1840.2W12$1839.2W$1839.2W6$1863.W$1862.W.W$1862.W.W$1857.2W
4.W$1856.W2.W$1857.2W5$1880.W$1879.W.W$1879.W.W$1874.2W4.W$1873.W2.W$
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1885.2W4.W$1884.W2.W$1885.2W8$1902.W$1901.W.W$1901.W.W$1896.2W4.W$
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$1936.W2.W$1937.2W11$1958.W$1936.2W19.W.W$1936.2W19.W.W$1952.2W4.W$
1951.W2.W$1952.2W9$1973.W$1972.W.W$1972.W.W$1951.2W14.2W4.W$1951.2W
13.W2.W$1967.2W9$1986.W$1985.W.W$1985.W.W$1966.2W12.2W4.W$1966.2W11.W
2.W$1980.2W12$1979.2W17.W$1979.2W16.W.W$1997.W.W$1992.2W4.W$1991.W2.W
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2W$1991.2W9$2024.W$2003.2W18.W.W$2003.2W18.W.W$2018.2W4.W$2017.W2.W$
2018.2W6$2035.W$2034.W.W$2034.W.W$2029.2W4.W$2028.W2.W$2029.2W$2017.
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12$2051.2W$2051.2W22.W$2074.W.W$2074.W.W$2069.2W4.W$2068.W2.W$2069.2W
10$2089.W$2088.W.W$2068.2W18.W.W$2068.2W13.2W4.W$2082.W2.W$2083.2W12$
2082.2W21.W$2082.2W20.W.W$2104.W.W$2099.2W4.W$2098.W2.W$2099.2W11$
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2147.W$2125.2W19.W.W$2125.2W19.W.W$2141.2W4.W$2140.W2.W$2141.2W12$
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2179.W$2157.2W19.W.W$2157.2W19.W.W$2173.2W4.W$2172.W2.W$2173.2W12$
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2247.W$2226.2W18.W.W$2226.2W18.W.W$2241.2W4.W$2240.W2.W$2241.2W12$
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12.2W12$2353.2W$2353.2W3$2391.2C$2390.C2.C$2391.2C3$2379.W$2378.W.W$
2378.W.W$2373.2W4.W$2372.W2.W$2373.2W7$2388.C$2387.C.C$2387.C.C$2382.
2C4.C$2381.C2.C$2372.2W8.2C$2372.2W11$2381.2C$2381.2C!

The Next Step is a Big One
Okay, looks like step 3.4 has been reached -- just have to programmatically string together the recipes that are hidden in these slsparse output files:

outfiles.zip

output generated by step 3.3 batch file

(1.03 MiB) Downloaded 25 times

The stringing-together task _could_ be done manually, but it shouldn't be, because we're going to have to do this all over again for the NW Corderfleet, and if all the steps are automated we can re-use the same scripts and everything should Just Work.

Seeing as this thread is a construction-practice thread, does anyone else want to try their hand at step 3.4 and/or 3.5? If I don't hear anything in a few days, I'll start working through the substeps. But I'd be just as happy to troubleshoot someone else's code -- or, even better, watch while someone else who writes better code than I do shows how easy all this would be to do with, say, lifelib.

Code: Select all

3.4) Write a Python script to find and move the target block in each outfileN.mc,
   then run the modified outfileN.mc to get the slow salvo instead of the single-channel recipe,
   then find and remove the elbow block,
   then transform the pattern to put the target block at (0,0),
   then get the lane list and minimize recipe,
   then add the trigger glider at the correct offset,
   then save the resulting slowsalvoN.mc
3.5)  Run previous code to record each lane list,
  then write a new script to string together the slowsalvoN.mc subpatterns

[dvgrn]

Seeing as this thread is a construction-practice thread, does anyone else want to try their hand at step 3.4 and/or 3.5? If I don't hear anything in a few days, I'll start working through the substeps. But I'd be just as happy to troubleshoot someone else's code -- or, even better, watch while someone else who writes better code than I do shows how easy all this would be to do with, say, lifelib.

Bah, nobody wants to have any fun.

Small Tangential Grumble
All you people out there ... I think there are more than two, so I can't just say "both of you people out there" ... who say you don't know how to write Golly scripts, but you wish you did -- it's not like this is rocket surgery or anything, but wishing isn't going to do any good. On the other hand, if every time a little problem like this turns up, you get some good practice in, then pretty soon you will know how to write Golly scripts.

Okay, On to the Next Subtask...
Here's some code to take care of item 3.4 above:

Code: Select all

# slowsalvo-from-outfile.py

import golly as g

SAFE_DISTANCE = 160000
for i in range(53):
  fname = "C:/Users/greedd/Desktop/Desktop-DMG-August/outfiles/outfile"+str(i)+".mc"
  g.open(fname)
  
  pat = g.getcells(g.getrect())
  
  # because of the orientation, the target block will always be the first four cells in the cell list --
  # so let's go ahead and move them
  for n in range(8):
    pat[n]-= 160000
  
  # now run the resulting pattern long enough to convert the single-channel recipe to a slow salvo
  g.new("Convert to slow salvo")
  g.putcells(pat)
  g.run(SAFE_DISTANCE*4)
  
  # now the first four cells in the pattern will be the target "hand" block,
  # and the last four cells will be the single-channel elbow block.  Get rid of the elbow:
  pat = g.getcells(g.getrect())[:-8]
  g.new("Slow salvo")
  
  # paste the pattern at (0,0), so the slow salvo recognizer code can extract a reasonable lane list
  g.putcells(pat,-pat[0],-pat[1])
  pat = g.getcells(g.getrect())
  
  # once we find out where the pattern below is going to end up,
  # relative to the (0,0) target block, then we'll know where to drop in the trigger glider
  # x = 55, y = 48, rule = B3/S23
  # 19bo$18bobo15bo$18b2o15bobo$35b2o3$15b2o$15b2o2$34b2o$33bobo$34bo3$7b
  # 2o$7b2o$39bo$38bobo$39bo6$21b2o$bo19b2o$obo$b2o30b2o$33b2o18bo$7b2o3b
  # 2o38bobo$6bobo2bobo38b2o$7bo4bo3$25b2o$24bobo$25bo3$25b2o$24bobo14b2o$
  # 25bo15b2o4$28b2o$28bobo$29bo!
  #
  # A 3o$o$bo! glider will get dropped in at (38+N,6+N) relative to the upper left corner
  # of the seed's bounding box -- and the new target block will show up at (36,39).
  # N is just the length of the full pattern, plus an arbitrary short distance.
  g.run(SAFE_DISTANCE*4)
  r = g.getrect()
  x, y = r[0], r[1]
  g.new("Recipe with trigger glider")
  g.putcells(pat)
  fullrect = g.getrect()
  width, height = fullrect[2],fullrect[3]
  safedist = max(width, height) + 64
  g.putcells(g.parse("3o$o$bo!"), x + 38 + safedist, y + 6 + safedist)
  g.show(fname)
  g.save("C:/Users/greedd/Desktop/Desktop-DMG-August/slowsalvo/slowsalvo"+str(i)+".mc","mc")
g.show("Done")

slowsalvo-files.zip

(267.59 KiB) Downloaded 18 times

Here are the output files. The only remaining task is to string them together:

Code: Select all

3.5)  Run a version of previous posted slow salvo recognizer/optimizer code to record each lane list,
  then write a new script to string together the slowsalvoN.mc subpatterns

I'll tackle 3.5 toward the end of the weekend unless someone else wants to give it a try.

Then it's just a matter of doing it all over again -- but this time the code is all written already, so we'll just need a different initial input for the NW Corderfleet.

[dvgrn]

Okay, time for a progress report. Working through item 3.5, I ended up with

Code: Select all

# recipe-stringer-togetherer.py
#
# 9/10/2022:  adapt recipe-minimizer-binary-Python3.py to string together slow salvo recipes
# 9/13/2022:  add cordership_parity to the GetSlowSalvoRecipe subroutine

import golly as g

def getbackground(clist):
   g.setrule("B12345678/S")
   background = g.evolve(clist, 1)
   g.setrule("B3/S23")
   return background

class Glider:
  def __init__(self, rlestr, timeoffset, laneoffset):
    self.dt = timeoffset
    self.dx = laneoffset
    cells = g.parse(rlestr)
    self.clist = g.transform(cells,-cells[0],0)
    self.background = getbackground(self.clist)

def matches(glider, x, y):
  for i in range(0, len(glider.clist), 2):
    if g.getcell(glider.clist[i]+x, glider.clist[i+1]+y) == 0: return 0
  bkg = glider.background
  for i in range(0, len(bkg), 2):
    if g.getcell(bkg[i]+x, bkg[i+1]+y) == 1:  return 0
  return 1

def makerecipe(background, gliderlist):
  g.new("Recipe")
  g.putcells(background)
  offset = max(background[1::2])+4
  for glider, delta in gliderlist:
    clist, lane = glider
    g.putcells(clist, (lane+1)//2+offset, offset)
    offset += delta

g.setalgo("HashLife")

glist = [ Glider("3o$o$bo!",0,0), Glider("bo$2o$obo!",1,-2), \
          Glider("2o$obo$o!",2,-1), Glider("b2o$2o$2bo!",3,-1) ]
gliderE, gliderO = g.transform(glist[0].clist,-glist[0].dx,0), g.transform(glist[1].clist,-glist[1].dx,0)   # glist[0].clist, glist[1].clist

def getSlowSalvoRecipe(cordership_parity):
  if g.numstates()>2: g.exit("Please use a two-state rule.")

  r=g.getrect()
  if len(r)==0: g.exit("No pattern found.")

  nongliderpat, ngp3, recipelist, rlist, recipe, remainder, count = [], [], [], [], "", g.getcells(r), 0
  all = remainder

  while len(remainder):    
    matchflag = 0
    for index in range(len(glist)):
      glider = glist[index]
      if g.getkey() == "q": g.exit()
      TLx, TLy = remainder[0],remainder[1]
      matchflag = matches(glider, TLx, TLy)
      if matchflag:
        # remove the matched pattern from the universe
        count+=1
        g.putcells(glider.clist, TLx, TLy, 1, 0, 0, 1, "xor")
        g.update()
        g.show("Found glider #" + str(glider.dt) + " at " + str([TLx,TLy]))
        if recipe!="": recipe+=" "
        recipe+="E" if  glider.dt%2==0 else "O"
        lane = (TLx-TLy+glider.dx)*2-1
        recipe+=str(lane)
        recipelist+=[[(gliderE if glider.dt%2==0 else gliderO),lane]]
        rlist+=[[lane,glider.dt%2]]
        nomatch = 0
        break
    if matchflag==0:
      nongliderpat+=[TLx, TLy]
      ngp3 +=[TLx, TLy, 3]
      g.setcell(TLx, TLy, 0)
    remainder = g.getcells(g.getrect())
  # if the slowsalvoN inputs aren't set up exactly the way we expect them to be, fail and exit
  if str(nongliderpat) != "[0, 0, 1, 0, 0, 1, 1, 1]":
    g.note("Complaint:  this pattern's target block isn't at (0,0) where it's supposed to be.\n"+str(nongliderpat))
    g.exit()
  g.new("Original")
  g.putcells(all)  # put things back the way they were
  g.run(8*r[3])  # twice as long as needed
  g.select([-1000,-1000,2000,2000])
  g.shrink()

  return rlist

parities = "OEEEEEEEEEEEEEEEEEEEEEOEEEEEEEEEOEEEEEOEEEEEEEEEOEEEE"
completelist = []
xloc, yloc, laneoffset = 0, 0, 0
for i in range(53):
  fname = "C:/path/to/slowsalvo"+str(i)+".mc"
  g.open(fname)
  g.show(fname)
  g.fit()
  g.update()
  cordership_parity = parities[-1]
  parities = parities[:-1]
  outlist = getSlowSalvoRecipe(cordership_parity)  # this will collect the slow salvo lanes, run the pattern, and select the output target block
  blockloc = g.getselrect()
  if blockloc[2]!=2 or blockloc[3]!=2:
    g.note("Complaint:  this pattern's output target block appears to not be a block.\n"+str(blockloc)+"\n"+str(g.getrect(blockloc)))
    g.exit()
  xloc += blockloc[0]
  yloc += blockloc[1]
  for item in outlist:
    parity = item[1]
    # if the required parity of the Cordership is "O", reverse all parities for this recipe
    if cordership_parity=="O":
      parity = 1-parity
    completelist.append([item[0]+laneoffset,parity])
  laneoffset += (blockloc[0] - blockloc[1]) * 2
g.show("Done.")
g.setclipstr(str(completelist))

which takes the slowsalvo{n}.mc files as input, and aims each salvo at the previous salvo's output block.

Notice I updated this code three days after posting it, to add parity handling. The update is noted with the date in the comments at the top of the script. Generally it's a very good idea to do this as a bare minimum, especially if you're not checking your updates into a code repository as you go along... but even if you are, it's often extremely helpful to be able to see at a glance the main features that have been added. Another very good habit to get into is to mention and track a version number in those header comments.

The resulting numbers -- these are the ones that were generated before the script was patched -- look good, so I can put them into a separate much simpler script to build a trial pattern:

Code: Select all

# build-final-slow-salvo.py

import golly as g

gliderE = g.parse("3o$o$bo!")
gliderO = g.parse("b2o$2o$2bo!")
glist = [gliderE, gliderO]

g.setalgo("HashLife")

if g.numstates()>2: g.exit("Please use a two-state rule.")

# the following nested-list string is the clipboard output of recipe-stringer-togetherer.py:
data = [[-11, 1], [-9, 1], [-5, 1], [-27, 1], [-15, 0], [-11, 0], [-17, 0], [-17, 0], [-15, 0], [-9, 0], [-5, 0], [-7, 0], [-1, 0], [15, 0], [21, 0], [41, 0], [27, 0], [1, 1], [33, 0], [-15, 0], [-23, 0], [-23, 1], [-17, 1], [-3, 1], [-33, 1], [-49, 1], [5, 0], [9, 1], [23, 1], [11, 1], [-13, 1], [7, 1], [1, 1], [13, 0], [53, 0], [73, 0], [73, 0], [57, 0], [85, 0], [85, 0], [93, 0], [-65, 0], [-71, 0], [-67, 0], [-79, 0], [-61, 1], [-93, 0], [-97, 1], [-95, 1], [-91, 0], [-97, 0], [-97, 0], [-119, 1], [-81, 0], [-85, 1], [-69, 1], [-89, 1], [-73, 0], [-79, 0], [-63, 0], [-87, 1], [-85, 1], [-63, 1], [-25, 0], [-21, 1], [-29, 1], [-35, 1], [-25, 1], [-21, 0], [-45, 0], [-49, 0], [-33, 0], [-61, 0], [-61, 0], [-69, 0], [-1, 0], [5, 0], [17, 1], [-1, 0], [35, 0], [35, 0], [21, 0], [35, 0], [-7, 0], [-1, 0], [15, 1], [25, 1], [3, 1], [3, 0], [21, 0], [21, 1], [37, 1], [3, 1], [9, 0], [5, 0], [17, 0], [37, 0], [-7, 1], [-5, 1], [-31, 0], [-95, 0], [-55, 1], [-3, 0], [-35, 1], [-35, 1], [-5, 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offset = 16
g.new("Results")
g.putcells(g.parse("2o$2o!"))
for lane, parity in data:
  g.putcells(glist[parity], (lane+1)//2+offset, offset)
  offset += 1024
g.show("Done.")

It works! The output pattern starts with a block, and builds one Cordership after another, heading southwest. Let's rotate it back 90 degrees counterclockwise and put it in context, and see if it cleans up the ash trail the way it's supposed to.

Code: Select all

[M2] (golly 4.2b1)
#R LifeSuper
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6 0 0 8246 0
3 0 0 0 8120
4 0 8248 0 0
5 8249 7881 0 7896
4 7885 0 7887 0
3 8042 8043 0 0
4 0 0 0 8252
3 0 0 8046 0
3 8047 0 0 0
4 8254 0 8255 0
5 8251 0 8253 8256
3 0 0 7883 8057
4 0 8258 0 0
4 0 0 0 7987
4 0 0 0 7999
5 8259 8260 0 8261
6 8250 8257 0 8262
4 7983 0 7989 0
3 0 0 0 8106
3 0 8097 0 0
3 8098 8107 0 0
4 0 8265 8266 8267
5 8264 0 8268 0
6 0 0 8269 0
7 8247 0 8263 8270
3 0 7910 0 0
4 7952 8021 8272 7947
4 0 7885 7880 7887
4 7895 0 0 0
5 8273 8274 0 8275
4 8152 8153 0 0
5 0 0 8277 0
4 8158 0 0 0
4 8214 8179 0 0
3 0 8000 0 8117
4 8226 0 0 8281
5 8279 8280 0 8282
6 8276 8278 0 8283
3 0 8120 0 0
4 0 0 0 8285
5 0 8286 0 0
6 0 8287 0 0
7 0 8284 0 8288
8 8240 8271 0 8289
9 0 8290 0 0
10 0 8291 0 0
11 0 8292 0 0
3 7978 8124 7869 0
4 0 0 8294 0
5 0 0 8295 0
6 0 0 8296 0
4 0 7952 0 0
4 8231 0 8234 0
5 0 0 8298 8299
4 0 8235 0 0
3 0 7957 0 8197
4 8236 8302 0 0
3 0 8201 0 0
4 0 8304 0 0
5 8301 8303 0 8305
3 8196 7979 0 0
4 8307 0 0 0
5 8308 0 8168 8177
6 8300 0 8306 8309
1 0 0 3 3
1 0 3 0 0
2 0 8311 8312 8311
1 3 0 0 0
2 0 0 8314 0
3 0 0 8313 8315
4 8316 0 0 0
5 0 0 8317 0
6 0 0 8318 0
7 8297 0 8310 8319
8 0 0 8320 0
1 0 3 3 0
2 0 0 0 8322
3 0 0 0 8323
1 0 0 0 3
1 0 0 3 0
1 3 0 0 3
2 8325 8326 8327 8322
2 0 8327 0 0
3 8328 8329 0 0
4 0 8324 8179 8330
2 0 0 8311 0
3 0 0 8332 0
1 3 3 0 0
2 8334 0 0 0
3 8335 0 0 0
4 0 8333 0 8336
5 8171 8331 0 8337
6 0 8338 0 0
2 0 0 8326 0
3 0 0 8340 0
2 8314 0 0 0
3 8342 0 0 0
4 8341 0 8343 0
5 8344 0 0 0
6 8345 0 0 0
7 8339 8346 0 0
8 8347 0 0 0
9 8321 0 8348 0
10 8349 0 0 0
11 8350 0 0 0
12 8293 8351 0 0
13 8225 0 8352 0
14 8353 0 0 0
15 7471 7474 8354 0
16 8355 0 0 0
17 7449 7464 8356 0
18 7347 7415 8357 0
19 7122 7315 8358 0
20 6721 7088 8359 0
21 8360 0 0 0
22 6100 6686 8361 0
23 2414 5185 8362 0
24 0 30 0 8363

Disaster!
... Which looks good for the first Cordership or two, but then completely blows up. On a closer inspection, even the second Cordership is wrong: it's constructed at a (9,-9) offset from where it should be, so it doesn't affect the ash trail at all. And then the third Cordership just crashes into the part of the trail that it's supposed to clean up -- it's not even close.

So what did I do wrong?

Debugging: Don't Get Mad, Get A Hypothesis
This took me a little while to sort out, and I had to remember to keep breathing in a steady and even manner, rather than shouting rude things at the walls or at my computer or kicking or screaming or throwing things or what have you... while forcing my brain to keep thinking of new theories about what could possibly have gone wrong.

The first theory was that the Corderships' relative placement was correct, but that I'd put the initial block in the wrong place. That turned out to be sort of true, but even after several experimental corrections, the test pattern would still mysteriously blow up after a while.

The second theory was that the parity of my target pattern was wrong -- if the blinkers were all in the opposite phase from what the Corderfleet expected, things would presumably turn out rather badly when the first Cordership started trying to clean up a blinker. That turned out to be sort of true, too, but even after I changed the phase of the target pattern, the cleanup proceeded through several more Cordership launches... and then blew up anyway.

So I needed more theories, but for a while there didn't seem to be any more available. At times like these it's very difficult to keep in mind that the computer is doing exactly what I'm telling it to do, and therefore that I must be telling it something subtly wrong. The bug is generally hiding in plain sight, it's just that sometimes I'm not smart enough to see it... at which point the best bet is usually to add a bunch of debugging lines to check that various details that Must Obviously Be True, at various stages of the various programs' execution, really _are_ true.

The Moral of the Story
When I get toward the end of a project, I start hoping to be able to run through the last few stages all at once and have the whole thing Just Work. The step-by-step methodical testing of each stage tends to suffer -- which is when it's most likely that multiple simultaneous bugs will creep in and wreak havoc, or at least major puzzlement. One bug can produce very mysterious effects, but it's usually possible to do some testing and figure out what's going wrong. But two or more unrelated bugs working together can produce results that seem to be provably impossible.

Here, when I was testing a revised hypothesis about the parity bug, I found I could fix the first few problems by changing the parity of the Cordership... but then after manually modifying the trigger glider for several Cordership constructions and successfully avoiding any explosions, I got to one Cordership that still exploded no matter which phase I put it in.

-- It turned out that I had incorrectly given a pass to the Cordership before that one: it so happened that when it was in the wrong phase, it still cleaned something up in a healthy-looking way, but it was cleaning up the wrong thing...!

I don't think I'll have to backtrack any further than recipe-stringer-togetherer.py, to patch up the two completely unrelated bugs that produced this apparently hideously un-repairable Corderfleet-building recipe. I'll explain better in the next post, once I've gotten everything working.

[dvgrn]

In case it wasn't clear, the two independent bugs mentioned in the last post were

1) there were only 53 relative-gaps-between-Corderships to be measured in the reference pattern, so we ended up with only 53 compiled Cordership-seed-building slow salvos. But there have to be 54 Corderships! So when I put the first constructed Cordership from my series of 53, into the location where the first-of-54-Corderships was supposed to go, of course things didn't line up right.

Easy fix: start with a first Cordership seed recipe already in place -- with the target block in any starting position that's convenient, it doesn't much matter -- and aim the 53-Cordership slow salvo to that Cordership seed's output block.

2) With the above change, the Corderships start out working just fine, but after the first five or six, there's a sudden explosion. Not coincidentally, "after the first five or six" is approximately the location in the Corderfleet where the first Cordership appears that has to be triggered at T={odd} (because its job is to clean up blinkers rather than P1 ash like blocks and loaves and so on).

I had remembered to pay attention to the parities of the individual gliders in a recipe, but had totally forgotten that for those few Corderships colored in state 25 in the original reference pattern, the entire set of parities has to be reversed to avoid disaster. Or, well, really only the final glider (the trigger glider) parity actually has to change, since the Cordership seed is all stable stuff -- but it's just as easy to reverse the parity of the whole recipe. I've edited that change in to recipe-stringer-togetherer.py in the previous post.

Running that revised script, and feeding in the resulting set of coordinates to build-final-slow-salvo.py, produces a test pattern where everything works:

Code: Select all

# build-final-slow-salvo.py

import golly as g

gliderE = g.parse("3o$o$bo!")
gliderO = g.parse("b2o$2o$2bo!")
glist = [gliderE, gliderO]

g.setalgo("HashLife")

if g.numstates()>2: g.exit("Please use a two-state rule.")

# the following nested-list string is the clipboard output of recipe-stringer-togetherer.py:
data = [[-11, 1], [-9, 1], [-5, 1], [-27, 1], [-15, 0], [-11, 0], [-17, 0], [-17, 0], [-15, 0], [-9, 0], [-5, 0], [-7, 0], [-1, 0], [15, 0], [21, 0], [41, 0], [27, 0], [1, 1], [33, 0], [-15, 0], [-23, 0], [-23, 1], [-17, 1], [-3, 1], [-33, 1], [-49, 1], [5, 0], [9, 1], [23, 1], [11, 1], [-13, 1], [7, 1], [1, 1], [13, 0], [53, 0], [73, 0], [73, 0], [57, 0], [85, 0], [85, 0], [93, 0], [-65, 0], [-71, 0], [-67, 0], [-79, 0], [-61, 1], [-93, 0], [-97, 1], [-95, 1], [-91, 0], [-97, 0], [-97, 0], [-119, 1], [-81, 0], [-85, 1], [-69, 1], [-89, 1], [-73, 0], [-79, 0], [-63, 0], [-87, 1], [-85, 1], [-63, 1], [-25, 0], [-21, 1], [-29, 1], [-35, 1], [-25, 1], [-21, 0], [-45, 0], [-49, 0], [-33, 0], [-61, 0], [-61, 0], [-69, 0], [-1, 0], [5, 0], [17, 1], [-1, 0], [35, 0], [35, 0], [21, 0], [35, 0], [-7, 0], [-1, 0], [15, 1], [25, 1], [3, 1], [3, 0], [21, 0], [21, 1], [37, 1], [3, 1], [9, 0], [5, 0], [17, 0], [37, 0], [-7, 1], [-5, 1], [-31, 0], [-95, 0], [-55, 1], [-3, 0], [-35, 1], [-35, 1], [-5, 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[71, 1], [69, 1], [83, 0], [75, 0], [75, 0], [73, 1], [57, 0], [43, 1], [43, 1], [61, 0], [109, 0], [99, 0], [99, 0], [103, 1], [121, 1], [103, 1], [99, 0], [125, 1], [133, 1]]
offset = 16
g.new("Results")
g.putcells(g.parse("2o$2o!"))
for lane, parity in data:
  g.putcells(glist[parity], (lane+1)//2+offset, offset)
  offset += 1024
g.show("Done.")

Code: Select all

[M2] (golly 4.2b1)
#R LifeSuper
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4 8038 8042 0 0
3 0 7926 0 7887
4 8044 0 0 0
3 0 0 0 7817
3 7701 7820 7818 7711
4 8046 8047 0 0
5 8043 0 8045 8048
6 8034 8035 8036 8049
3 0 7824 0 7825
4 8051 0 0 0
5 0 8052 0 0
6 0 8053 0 0
3 0 0 0 7701
3 0 0 7703 7708
3 0 7710 0 0
3 7711 0 0 0
4 8055 8056 8057 8058
3 0 0 0 7716
4 8060 0 0 0
4 8003 8006 8004 8007
5 8059 0 8061 8062
4 8009 0 0 0
5 0 8064 0 0
3 0 0 7744 7745
3 0 7742 0 0
3 7746 7747 0 0
4 0 8066 8067 8068
3 0 0 0 7750
4 8070 0 0 0
4 7868 7871 7869 0
5 8069 0 8071 8072
6 8063 0 8065 8073
7 8050 0 8054 8074
8 8016 8021 8026 8075
9 7946 7959 0 8076
3 7949 7952 0 0
4 7874 8078 0 7704
3 7760 7747 0 0
4 0 8080 0 0
5 0 8079 0 8081
6 0 8082 0 0
7 0 8083 0 0
8 0 8084 0 0
9 0 8085 0 0
10 0 8077 0 8086
11 7644 7807 0 8087
3 0 0 7951 0
4 0 0 8089 0
5 0 0 8090 0
6 0 0 8091 0
7 0 0 8092 0
8 0 0 8093 0
9 0 0 8094 0
3 7953 0 0 0
4 8096 0 0 0
4 7741 0 0 0
5 8097 7722 7732 8098
3 0 0 7703 0
4 0 0 8100 0
5 0 0 8101 0
3 7876 7877 7887 0
4 0 8103 0 0
3 7889 0 0 0
4 0 8105 0 0
5 7738 8104 0 8106
3 7881 0 0 0
4 8108 0 0 0
4 0 7830 0 0
4 7833 0 0 0
5 8109 0 8110 8111
6 8099 8102 8107 8112
4 0 7837 0 0
3 0 7926 0 7928
3 7808 7931 7747 0
4 8115 8116 0 0
3 0 7935 0 0
4 8118 0 0 0
5 8114 8117 0 8119
6 0 8120 0 0
4 0 0 0 7721
4 7731 7741 0 0
4 0 0 7987 0
5 8122 0 8123 8124
4 7737 7985 0 7990
4 7988 0 7947 8055
4 0 8057 0 8060
5 8126 8127 0 8128
4 0 0 8056 0
4 8058 0 0 0
5 8130 0 8131 0
6 8125 0 8129 8132
7 8113 0 8121 8133
3 0 0 7949 7952
4 0 8135 0 0
3 7951 0 7953 0
4 8137 0 0 0
3 7701 7703 7760 7747
4 0 8139 0 0
5 8136 8138 8140 0
4 0 8067 0 8070
5 0 8142 0 0
6 0 8141 0 8143
7 0 8144 0 0
4 0 0 8066 0
5 0 0 8146 0
3 0 0 8037 8040
4 8068 0 0 8148
3 8039 0 8041 0
4 0 0 8150 0
3 7926 0 7887 0
4 0 0 0 8152
5 8149 8151 8153 0
1 0 0 3 3
2 0 0 8155 0
3 0 0 8156 0
4 0 0 8157 0
5 0 0 0 8158
6 8147 0 8154 8159
5 0 8005 0 8010
1 0 3 0 0
2 0 8162 0 0
3 0 8163 0 0
4 8006 8164 8007 0
1 3 0 0 0
2 8155 8166 0 0
3 8167 0 0 0
4 8168 0 0 0
1 0 0 0 3
2 0 0 0 8170
1 3 0 0 3
2 0 8172 0 0
3 0 8171 0 8173
1 0 0 3 0
2 0 0 8175 0
1 0 3 3 0
2 8177 8175 8172 8166
2 8177 0 0 0
3 8176 8178 8179 0
4 8174 8180 0 0
5 8165 8169 8181 0
1 3 3 0 0
2 0 8155 0 8183
3 0 8184 0 0
4 8185 0 0 0
5 8186 0 0 0
6 8161 8182 0 8187
7 8160 0 8188 0
8 8134 0 8145 8189
9 8190 0 0 0
10 8095 0 8191 0
11 0 0 8192 0
12 7459 0 8088 8193
13 8194 0 0 0
14 6975 4851 8195 0
15 8196 0 0 0
16 8197 0 0 0
17 8198 0 0 0
18 8199 0 0 0
19 8200 0 0 0
20 8201 0 0 0
21 8202 0 0 0
22 8203 0 0 0
23 8204 0 0 0
24 0 6476 0 8205

[dvgrn]

Now that we have a ridiculously long slow salvo to work with, it's suddenly clear that the recipe-minimizer-binary-Python3.py posted above... is in serious need of a rewrite. It does both the recognizing and the optimizing of a slow-salvo pattern in a seriously suboptimal way.

Here's what the script currently does in the "recognizing" section:
1) for each cell in the current universe in turn, starting from the upper left corner and scanning down by rows, it checks to see if the cell is part of an exact match for any orientation of a glider.
1a) If the cell is part of a glider, the script removes all of the glider's cells from the current universe, re-scans the universe to get a new list of cells, and repeats.
1b) If the cell isn't part of a glider, it must be part of the initial target -- so the script removes the single cell from the current universe, adds it to the "nongliderpat" cell list, re-scans the universe to get a new list of cells, and repeats.

For the reasonable-sized slow salvos that I've been running through this optimizing script up to now, the recognition stage usually happens very quickly, and the optimization stage doesn't take long either. It's all even kind of fun to watch. But with 5257 gliders to optimize, it's like watching paint dry to see the script struggle through repeated calls to

Code: Select all

remainder = g.getcells(g.getrect())

And there's no reason to do things that way. With just one call to g.getcells(g.getrect()), we have the full list of cells -- it should really only be necessary to run through it once, to divide it up into target cells and NW-traveling gliders.

Here's what the script does in the "optimizing" section, once it has a lane list to work with:

1) First the script uses a binary search to find out what the minimum fixed-width separation between gliders is for the current recipe. It rebuilds the slow salvo at different separations and checks to see whether the correct object is constructed at the end (after the resulting recipe is run for LONG_ENOUGH).
2) The script then uses a binary search for each individual glider in the new "fixed-width-minimized" recipe, to see how much closer it can be moved to the glider that's it's following, without changing the final constructed output of the recipe.
3 After each trial change in the position of each glider, the full recipe is run to completion and then checked against the reference output (which is whatever you get if you run the recipe with no optimization at all).

This is a fairly silly way to implement this part, too. There's no need to run the whole recipe to find out if an adjustment works; you really only need to add one glider at a time and run the pattern until the target stabilizes, both before and after the adjustment, and make sure the same pattern shows up in both cases. My only excuses are A) that the current algorithm was fast enough for the purposes I needed the script for when I wrote it, B) it's a little tricky to know where to start the search from (you can't just start with a single glider and the stabilized intermediate target, because there might well be sparks that would get in the way that aren't apparent in the stabilized target, and C) when I tried to write a smarter faster optimizer script, I introduced some wonderfully obscure bugs that I was never able to find and fix.

Let's see how it goes this time, now that I really need a faster optimizer.

- The script should only use g.getcells(g.getrect()) once, because that's a slow operation when the bounding box of the pattern in Golly's universe is millions of cells on a side.
- The script should process that cell list without making any changes to Golly's universe. g.setcell(), onc cell at a time, is also slow -- or at least slower than not doing it at all!
- New simplifying requirement for input patterns: The script can assume that IF the first cell in the cell list is part of a glider, the next four cells in the cell list will be the rest of that glider. In other words, the slow-salvo gliders won't have any cells on the same rows as the cells in the target pattern, and gliders will be on completely different sets of rows from each other as well. The current script can work even on patterns that don't match this assumption, and that slows down the speed of processing by a lot.
- Another new simplifying assumption: the output of this script will also match the above requirement, plus a little bit. Gliders will never be advanced closer than 19 ticks vertically from the previous glider, meaning there will always be at least two blank rows between optimized gliders.
- We'll use 3o$o$bo! and b2o$2o$2bo! as the even and odd phases of gliders, so even where the above limitation doesn't come into play, it might be possible to advance gliders three ticks further than the position found by this script.

With these new assumptions, the target pattern will move forward in time as the optimization proceeds -- possibly by moving the target pattern southwestward rather than moving the slow salvo gliders northeastward. To determine the right location for the next glider, again, we only have to run that one glider to the next (p2) stable point for the target pattern -- but we need to start from before the time of collision of the _previous_ glider (which may also be a time before final stabilization of the target pattern for one or more gliders before that).

Here's how I'll try coding it:

1) Start with current target object, place next glider a safe distance away (+258, +258) from the last occupied row (which will usually be a glider, but not the first time).
2) With a binary search, see if the final result is the same if next glider is placed halfway closer to the target. After eight tests, a closest safe locatin will be known.
3) Evolve the target object in steps of 4, N times, checking at each step that the glider is still the last five cells in the cell list. The new current target object will be the last cell list for which that is true. Record N so that we can accurately adjust the offsets list for the final recipe.
4) Go back to #1 to place the next glider. Repeat until complete recipe is known.

First, let's adapt recipe-minimizer-binary-Python3.py to just collect the slow-salvo EO lane list we need (i.e., lane numbers and parities). The simplest adaptation would be just running the first part of the script:

Code: Select all

# slow-salvo-recipe-collector.py


import golly as g

def getbackground(clist):
   g.setrule("B12345678/S")
   background = g.evolve(clist, 1)
   g.setrule("B3/S23")
   return background

class Glider:
  def __init__(self, rlestr, timeoffset, laneoffset):
    self.dt = timeoffset
    self.dx = laneoffset
    cells = g.parse(rlestr)
    self.clist = g.transform(cells,-cells[0],0)
    self.background = getbackground(self.clist)

def matches(glider, x, y):
  for i in range(0, len(glider.clist), 2):
    if g.getcell(glider.clist[i]+x, glider.clist[i+1]+y) == 0: return 0
  bkg = glider.background
  for i in range(0, len(bkg), 2):
    if g.getcell(bkg[i]+x, bkg[i+1]+y) == 1:  return 0
  return 1

def makerecipe(background, gliderlist):
  g.new("Recipe")
  g.putcells(background)
  offset = max(background[1::2])+4
  for glider, delta in gliderlist:
    clist, lane = glider
    g.putcells(clist, (lane+1)//2+offset, offset)
    offset += delta

g.setalgo("HashLife")

glist = [ Glider("3o$o$bo!",0,0), Glider("bo$2o$obo!",1,-2), \
          Glider("2o$obo$o!",2,-1), Glider("b2o$2o$2bo!",3,-1) ]
gliderE, gliderO = g.transform(glist[0].clist,-glist[0].dx,0), g.transform(glist[1].clist,-glist[1].dx,0)   # glist[0].clist, glist[1].clist

if g.numstates()>2: g.exit("Please use a two-state rule.")

r=g.getrect()
if len(r)==0: g.exit("No pattern found.")

nongliderpat, ngp3, recipelist, recipe, remainder, count = [], [], [], "", g.getcells(r), 0
all = remainder

while len(remainder):
  matchflag = 0
  for index in range(len(glist)):
    glider = glist[index]
    if g.getkey() == "q": g.exit()
    TLx, TLy = remainder[0],remainder[1]
    matchflag = matches(glider, TLx, TLy)
    if matchflag:
      # remove the matched pattern from the universe
      count+=1
      g.putcells(glider.clist, TLx, TLy, 1, 0, 0, 1, "xor")
      g.update()
      g.show("Found glider #" + str(glider.dt) + " at " + str([TLx,TLy]))
      if recipe!="": recipe+=" "
      recipe+="E" if  glider.dt%2==0 else "O"
      lane = (TLx-TLy+glider.dx)*2-1
      recipe+=str(lane)
      recipelist+=[[(gliderE if glider.dt%2==0 else gliderO),lane]]
      nomatch = 0
      break
  if matchflag==0:
    nongliderpat+=[TLx, TLy]
    ngp3 +=[TLx, TLy, 3]
    g.setcell(TLx, TLy, 0)
  remainder = g.getcells(g.getrect())

g.setclipstr(str(recipe) + "\n"+ str(recipelist))
g.show("Done.  Check the clipboard.")

But for 5000+ gliders, that turns out to be way too slow, as described above. Time for a rewrite! This is just the part that quickly extracts slow-salvo information from a (very large) Golly pattern:

Code: Select all

# recipe-minimizer-binary-better-part-1-only.py
#
# version 1: rework all code from recipe-minimizer-binary-Python3.py to improve speed
#
# In Golly, orient a slow salvo so that it's moving northwest,
# with some target in the far northwest corner.
# This code is intended to shrink the distances between slow salvo gliders to some reasonable minimum.
#
# When it's done, the script places a report of the slow-salvo lane list and the minimum distance
# between each glider and the next, into the clipboard.
#
# "12345679" is an arbitraily chosen constant representing an empty universe.
# The "8" is missing on purpose, because the number multiplies by 7 so much more nicely that way.
#
# New simplifying requirement for input patterns:  The script can assume that [b]IF[/b] the first cell
# in the cell list is part of a glider, the next four cells in the cell list will be the rest of that
# glider.  In other words, the slow-salvo gliders won't have any cells on the same rows as the cells
# in the target pattern, and gliders will be on completely different sets of rows from each other as well.
#
# Furthermore, if we work from the end of the cell list to the front, the last five cells will always 
# match one of the phases of a glider, until the only thing that's left is the non-glider target.

import golly as g

# only need this right at the end
# def makerecipe(background, gliderlist):
#   g.new("Recipe")
#   g.putcells(background)
#   offset = max(background[1::2])+4
#   for glider, delta in gliderlist:
#     clist, lane = glider
#     g.putcells(clist, (lane+1)//2+offset, offset)
#     offset += delta

def glidermatch(clist):
  count = 0
  for glider in glist:
    match = 1
    # remember that glider[0] and glider[1] are always zero
    x, y = clist[0],clist[1]
    # we could just do all the calculations and compare the whole list --
    #   offsetclist = [0,0,clist[2]-x,clist[3]-y,clist[4]-x,clist[5]-y,clist[6]-x,clist[7]-y,clist[8]-x,clist[9]-y]
    # -- but it might be very slightly faster to stop comparing at the first mismatch, so let's do that.
    for i in range(1,5): # check to see if any of the other four cells fail to match the template glider from glist
      if glider[2*i] != clist[2*i]-x or glider[2*i+1] != clist[2*i+1]-y:
        match = 0
        break
    if match == 1: # all cells matched
      return count
    count +=1
  return -1   # this will happen only if none of the four gliders are a match for the five cells in clist

g.setalgo("HashLife")

# glist = [ g.parse("3o$o$bo!",0,0), g.parse("bo$2o$obo!",1,-2), \
#           g.parse("2o$obo$o!",2,-1), g.parse("b2o$2o$2bo!",3,-1) ]
glist = [ g.parse("3o$o$bo!",0,0), g.parse("bo$2o$obo!",-1,0), \
          g.parse("2o$obo$o!",0,0), g.parse("b2o$2o$2bo!",-1,0) ]
glistoffsets = [0, 4, 2, 2]  # how far to the right each glider in glist is, in quarter-diagonals, compared to reference lane

if g.numstates()>2: g.exit("Please use a two-state rule.")

r=g.getrect()
if len(r)==0: g.exit("No pattern found.")

all = g.getcells(g.getrect())
lanes, parities = [], []

ptr = len(all) - 10
target = []
while target == []:
  whichglider = glidermatch(all[ptr:])
  if whichglider == -1:
    target = all[:ptr+10]
  else:
    lanes.append((all[ptr]-all[ptr+1])*2 + 1 - glistoffsets[whichglider])
    parities.append(whichglider % 2)
    # Let's say it's okay to not have a target object at all,
    # in which case the cell list will process correctly all the way to ptr=0.
    # Otherwise, we need to check for the case where the target is something with less than 5 cells, like a block
    if ptr < 10:
      target = all[:ptr]  # break out of the loop
    else:
      ptr -= 10
# for speed reasons we're reading the cell list from the end to the beginning,
#   so we'll have to report the final lists in reverse order
lanes.reverse()
parities.reverse()
g.setclipstr("Lanes = " + str(lanes)+"\nParities = "+str(parities)+"\nRemainder (target) = " + str(target))
g.show("Done.  See clipboard for results.")

To test this out -- always gotta have a good sanity check! -- let's build a small sample slow salvo and see if the script identifies it correctly:

Code: Select all

x = 97, y = 103, rule = B3/S23
2o$2o4$10b2o$9b2o$11bo12$15b2o$15bobo$15bo4$30b2o$30bobo$30bo12$36bo$
35b2o$35bobo4$50b2o$49b2o$51bo12$55b2o$55bobo$55bo4$71bo$70b2o$70bobo
13$75b3o$75bo$76bo3$92bo$91b2o$91bobo13$94b3o$94bo$95bo!

This test pattern has all the possible glider phases of gliders on the symmetrical honeyfarm-making lanes on either side of a target block -- plus two more gliders at the end that are offset by one lane to the outside in each direction. It's not actually a valid slow-salvo recipe, but this script isn't going to care about that. The key is that if the math is done right, the script should report a bunch of "-9" and "+9" values, and one set of "-11" and "+11" at the end.

Code: Select all

Lanes = [9, -9, 9, -9, 9, -9, 9, -9, 11, -11]
Parities = [1, 0, 0, 1, 1, 0, 1, 0, 1, 0]
Remainder (target) = [0, 0, 1, 0, 0, 1, 1, 1]

Side note: these weird quarter-diagonal measurements are traditional for recording slow salvos, just because they make it trivial to mirror a slow salvo across X=Y (in Golly coordinates) just by taking the negation of every lane number. That might be confusing at first, and maybe it's not really all that good a reason to measure lane numbers in quarter-diagonals -- but that's the way the "EO format" does things, so we're just going to keep doing that.

Okay, time to test against the big salvo:

Code: Select all

Lanes = [9, 15, -1, 31, 19, -3, -5, 1, 5, 3, 9, 25, 31, 51, 37, 11, 43, -5, -13, -13, -7, 7, -23, -39, 15, 19, 33, 21, -3, 17, 11, 23, 63, 83, 83, 67, 95, 95, 103, -55, -61, -57, -69, -51, -83, -87, -85, -81, -87, -87, -109, -71, -75, -59, -79, -63, -69, -53, -77, -75, -53, -15, -11, -19, -25, -15, -11, -35, -39, -23, -51, -51, -59, 9, 15, 27, 9, 45, 45, 31, 45, 3, 9, 25, 35, 13, 13, 31, 31, 47, 13, 19, 15, 27, 47, 3, 5, -21, -85, -45, 7, -25, -25, 5, -19, -27, -23, -23, -33, -25, -17, 3, -27, 3, 9, 9, 7, 21, 13, 13, 11, -5, -19, -19, -1, 47, 37, 37, 41, 59, 41, 37, 63, 71, -9, -7, -3, -25, -13, -9, -15, -15, -13, -7, -3, -5, 1, 17, 23, 43, 29, 3, 35, -13, -21, -21, -15, -1, -31, -47, 7, 11, 25, 13, -11, 9, 3, 15, 55, 75, 75, 59, 87, 87, 95, -63, -69, -65, -77, -59, -91, -95, -93, -89, -95, -95, -117, -79, -83, -67, -87, -71, -77, -61, -85, -83, -61, -23, -19, -27, -33, -23, -19, -43, -47, -31, -59, -59, -67, 1, 7, 19, 1, 37, 37, 23, 37, -5, 1, 17, 27, 5, 5, 23, 23, 39, 5, 11, 7, 19, 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Remainder (target) = [0, 0, 1, 0, 0, 1, 1, 1]

That ran in well under five seconds, whereas the old script would have needed an overnight run. Yes, it has now been officially confirmed: the old script was an absolutely terrible design, but the terribleness only showed up for very long salvos.

Before we continue (in the next post) we'll have to test the above output by rebuilding the big salvo and trying it out, using some of the standard code from previous posts. But so far it looks like the rewrite is in working order!

[dvgrn]

I should probably mention that the code for the slow-salvo recognizer script, while it was taking the big step forward of being a million times faster, took a big step backward in terms of being less properly Pythonic. I took out the Glider class from the old code, and just did everything in terms of simple cell lists.

I suspect that that simplification doesn't make things run any slower, and I personally think it also makes the code easier to understand -- at least, it's easier if you have a clear mental picture of how cell lists are stored in Golly Python... and it's probably a good idea to work with cell lists until all of that is very clear. Other people's opinions may differ. I freely admit to being a lousy programmer, much given to writing stream-of-consciousness procedural programs instead of properly designed code made out of small testable pieces.

But speaking of testable pieces -- might as well throw together the chunk of code that rebuilds the slow salvo that was just extracted by the previous script:

Code: Select all

# reconstitute-slow-salvo-not-quite-right.py
import golly as g

EOlist = [ g.parse("3o$o$bo!"), g.parse("bo$2o$obo!") ]
lanes = [9, -9, 9, -9, 9, -9, 9, -9, 11, -11]
parities = [1, 0, 0, 1, 1, 0, 1, 0, 1, 0]

g.new("Test salvo")
g.putcells(g.parse("2o$2o!"))
offset = 10
s=""
paritystrs = ["E","O"]
for item in zip(lanes, parities):
  lane, parity = item
  s += paritystrs[parity] + str(lane) + " "
  g.putcells(EOlist[parity],(lane+1)//2+offset, offset)
  offset += 64
g.setclipstr(s)
g.show("Done. Check clipboard for EO-format recipe.")

-- Nope, not quite right -- the odd-parity gliders are showing up in the right place, but the even-parity ones should be placed one cell farther to the left. Now the question is whether I should fix this script, or if the previous script is reporting those even-parity lane numbers wrong.

Well... this new script reconstitutes the even-parity gliders wrong, given the output from the test pattern with all the -9 and 9 gliders, which we know are the correct lanes. So I can safely make the following change to the EOlist definition, without thinking too much about it, and try it on the full 5000-odd-glider slow salvo... oops, a gap of 64 cells isn't anywhere near enough to let Corderships escape sideways, so let's bump the offset value up too:

Code: Select all

# reconstitute-slow-salvo.py
import golly as g

delta = 256

EOlist = [ g.parse("3o$o$bo!",-1,0), g.parse("bo$2o$obo!") ]
lanes = [9, 15, -1, 31, 19, -3, -5, 1, 5, 3, 9, 25, 31, 51, 37, 11, 43, -5, -13, -13, -7, 7, -23, -39, 15, 19, 33, 21, -3, 17, 11, 23, 63, 83, 83, 67, 95, 95, 103, -55, -61, -57, -69, -51, -83, -87, -85, -81, -87, -87, -109, -71, -75, -59, -79, -63, -69, -53, -77, -75, -53, -15, -11, -19, -25, -15, -11, -35, -39, -23, -51, -51, -59, 9, 15, 27, 9, 45, 45, 31, 45, 3, 9, 25, 35, 13, 13, 31, 31, 47, 13, 19, 15, 27, 47, 3, 5, -21, -85, -45, 7, -25, -25, 5, -19, -27, -23, -23, -33, -25, -17, 3, -27, 3, 9, 9, 7, 21, 13, 13, 11, -5, -19, -19, -1, 47, 37, 37, 41, 59, 41, 37, 63, 71, -9, -7, -3, -25, -13, -9, -15, -15, -13, -7, -3, -5, 1, 17, 23, 43, 29, 3, 35, -13, -21, -21, -15, -1, -31, -47, 7, 11, 25, 13, -11, 9, 3, 15, 55, 75, 75, 59, 87, 87, 95, -63, -69, -65, -77, -59, -91, -95, -93, -89, -95, -95, -117, -79, -83, -67, -87, -71, -77, -61, -85, -83, -61, -23, -19, -27, -33, -23, -19, -43, -47, -31, -59, -59, -67, 1, 7, 19, 1, 37, 37, 23, 37, -5, 1, 17, 27, 5, 5, 23, 23, 39, 5, 11, 7, 19, 39, -5, -3, -29, -93, -53, -1, -33, -33, -3, -27, -35, -31, -31, -41, -33, -25, -5, -35, -5, 1, 1, -1, 13, 5, 5, 3, -13, -27, -27, -9, 39, 29, 29, 33, 51, 33, 29, 55, 63, -17, -23, -7, -39, -27, -5, -21, -15, -11, -13, -7, 9, 15, 35, 21, -5, 27, -21, -29, -29, -23, -9, -39, -55, -1, 3, 17, 5, -19, 1, -5, 7, 47, 67, 67, 51, 79, 79, 87, -71, -77, -73, -85, -67, -99, -103, -101, -97, -103, -103, -125, -87, -91, -75, -95, -79, -85, -69, -93, -91, -69, -31, -27, -35, -41, -31, -27, -51, -55, -39, -67, -67, -75, -7, -1, 11, -7, 29, 29, 15, 29, -13, -7, 9, 19, -3, -3, 15, 15, 31, -3, 3, -1, 11, 31, -13, -11, -37, -101, -61, -9, -41, -41, -11, -35, -43, -39, -39, -49, -41, -33, -13, -43, -13, -7, -7, -9, 5, -3, -3, -5, -21, -35, -35, -17, 31, 21, 21, 25, 43, 25, 21, 47, 55, -7, -27, -9, -17, -13, -21, -37, -31, -31, -23, -53, -35, -29, -25, -27, -21, -5, 1, 21, 7, -19, 13, -35, -43, -43, -37, -23, -53, -69, -15, -11, 3, -9, -33, -13, -19, -7, 33, 53, 53, 37, 65, 65, 73, -85, -91, -87, -99, -81, -113, -117, -115, -111, -117, -117, -139, -101, -105, -89, -109, -93, -99, -83, -107, -105, -83, -45, -41, -49, -55, -45, -41, -65, -69, -53, -81, -81, -89, -21, -15, -3, -21, 15, 15, 1, 15, -27, -21, -5, 5, -17, -17, 1, 1, 17, -17, -11, -15, -3, 17, -27, -25, -51, -115, -75, -23, -55, -55, -25, -49, -57, -53, -53, -63, -55, -47, -27, -57, -27, -21, -21, -23, -9, -17, -17, -19, -35, -49, -49, -31, 17, 7, 7, 11, 29, 11, 7, 33, 41, -21, -3, -3, 5, -15, -15, -1, -19, -13, -9, -11, -5, 11, 17, 37, 23, -3, 29, -19, -27, -27, -21, -7, -37, -53, 1, 5, 19, 7, -17, 3, -3, 9, 49, 69, 69, 53, 81, 81, 89, -69, -75, -71, -83, -65, -97, -101, -99, -95, -101, -101, -123, -85, -89, -73, -93, -77, -83, -67, -91, -89, -67, -29, -25, -33, -39, -29, -25, -49, -53, -37, -65, -65, -73, -5, 1, 13, -5, 31, 31, 17, 31, -11, -5, 11, 21, -1, -1, 17, 17, 33, -1, 5, 1, 13, 33, -11, -9, -35, -99, -59, -7, -39, -39, -9, -33, -41, -37, -37, -47, -39, -31, -11, -41, -11, -5, -5, -7, 7, -1, -1, -3, -19, -33, -33, 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g.new("Test salvo")
g.putcells(g.parse("2o$2o!"))
offset = 10
s=""
paritystrs = ["E","O"]
for item in zip(lanes, parities):
  lane, parity = item
  s += paritystrs[parity] + str(lane) + " "
  g.putcells(EOlist[parity],(lane+1)//2+offset, offset)
  offset += delta
g.setclipstr(s)
g.show("Done. Check clipboard for EO-format recipe.")

... And it works! Next up, for some future post: make the binary-search minimizing part of the script also run a whole lot faster than the previous script.

[dvgrn]

... And it works! Next up, for some future post: make the binary-search minimizing part of the script also run a whole lot faster than the previous script.

Haven't had a whole lot of time to work on this lately. But short steps are best anyway... I think this is a successful addition of a binary search for the first glider position, with a couple of TODOs after that to explain what else needs to be done to complete the optimizer script:

Code: Select all

# new-binary-slow-salvo-optimizer.py
import golly as g

LONG_ENOUGH = 4096               # running each intermediate target plus a single glider for this long should produce the next intermediate target
MIN_DELTA = 5                    # only optimize down to a safe distance (two blank lanes between adjacent slow gliders)
INITIAL_DELTA = MIN_DELTA + 256  # it should be safe (producing the desired output) to build the entire slow salvo at this offset
                                 # the distance between min and initial might as well be a power of two, but it's not necessary
offset = 0

EOlist = [ g.parse("3o$o$bo!",-1,0), g.parse("bo$2o$obo!") ]
lanes = [9, 15, -1, 31, 19, -3, -5, 1, 5, 3, 9, 25, 31, 51, 37, 11, 43, -5, -13, -13, -7, 7, -23, -39, 15, 19, 33, 21, -3, 17, 11, 23, 63, 83, 83, 67, 95, 95, 103, -55, -61, -57, -69, -51, -83, -87, -85, -81, -87, -87, -109, -71, -75, -59, -79, -63, -69, -53, -77, -75, -53, -15, -11, -19, -25, -15, -11, -35, -39, -23, -51, -51, -59, 9, 15, 27, 9, 45, 45, 31, 45, 3, 9, 25, 35, 13, 13, 31, 31, 47, 13, 19, 15, 27, 47, 3, 5, -21, -85, -45, 7, -25, -25, 5, -19, -27, -23, -23, -33, -25, -17, 3, -27, 3, 9, 9, 7, 21, 13, 13, 11, -5, -19, -19, -1, 47, 37, 37, 41, 59, 41, 37, 63, 71, -9, -7, -3, -25, -13, -9, -15, -15, -13, -7, -3, -5, 1, 17, 23, 43, 29, 3, 35, -13, -21, -21, -15, -1, -31, -47, 7, 11, 25, 13, -11, 9, 3, 15, 55, 75, 75, 59, 87, 87, 95, -63, -69, -65, -77, -59, -91, -95, -93, -89, -95, -95, -117, -79, -83, -67, -87, -71, -77, -61, -85, -83, -61, -23, -19, -27, -33, -23, -19, -43, -47, -31, -59, -59, -67, 1, 7, 19, 1, 37, 37, 23, 37, -5, 1, 17, 27, 5, 5, 23, 23, 39, 5, 11, 7, 19, 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-15, 33, 23, 23, 27, 45, 27, 23, 49, 57, -23, -29, 1, 19, 5, -27, 13, -3, 3, 7, 5, 11, 27, 33, 53, 39, 13, 45, -3, -11, -11, -5, 9, -21, -37, 17, 21, 35, 23, -1, 19, 13, 25, 65, 85, 85, 69, 97, 97, 105, -53, -59, -55, -67, -49, -81, -85, -83, -79, -85, -85, -107, -69, -73, -57, -77, -61, -67, -51, -75, -73, -51, -13, -9, -17, -23, -13, -9, -33, -37, -21, -49, -49, -57, 11, 17, 29, 11, 47, 47, 33, 47, 5, 11, 27, 37, 15, 15, 33, 33, 49, 15, 21, 17, 29, 49, 5, 7, -19, -83, -43, 9, -23, -23, 7, -17, -25, -21, -21, -31, -23, -15, 5, -25, 5, 11, 11, 9, 23, 15, 15, 13, -3, -17, -17, 1, 49, 39, 39, 43, 61, 43, 39, 65, 73, 11, 17, 33, 11, 1, -31, -5, 1, 5, 3, 9, 25, 31, 51, 37, 11, 43, -5, -13, -13, -7, 7, -23, -39, 15, 19, 33, 21, -3, 17, 11, 23, 63, 83, 83, 67, 95, 95, 103, -55, -61, -57, -69, -51, -83, -87, -85, -81, -87, -87, -109, -71, -75, -59, -79, -63, -69, -53, -77, -75, -53, -15, -11, -19, -25, -15, -11, -35, -39, -23, -51, -51, -59, 9, 15, 27, 9, 45, 45, 31, 45, 3, 9, 25, 35, 13, 13, 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# TODO:  I ended up inlining this test, since it's probably more efficient to not pass all these lists around
#            Either remove this, or make a more useful version that makes the binary-search code more readable...
# def checkoffset(targetpat, expectedoutcome, testglider, ticks):
#   outcome = g.evolve(g.join(targetpat, testglider), ticks)
#  return (str(outcome) == str(expectedoutcome))  # TODO: does it work without the str()? List comparisons can be weird.
    
g.new("Test salvo")
targetpat = g.parse("2o$2o!")
for item in zip(lanes, parities):
  lane, parity = item
  highdelta, lowdelta = INITIAL_DELTA, MIN_DELTA - 1   # we always know that the optimal glider position is somewhere between lowdelta and highdelta
                                                     # -- and when lowdelta and highdelta are the same value, we're done
  # whatever happens when the glider is delayed by {delta} cells diagonally ...
  #   is what we want to be sure continues to happen in exactly the same way when we reduce the offset.
  #   So we'll start by defining the desired outcome to be whatever happens at the high end of the range.
  #
  # Let's say that the lowdelta variable will always contain the highest value that's known to not work
  ticks = highdelta * 4 + LONG_ENOUGH
  gliderpat = g.transform(EOlist[parity],(lane+1)//2+highdelta, highdelta)
  expectedoutcome = g.evolve(g.join(targetpat, gliderpat), ticks)
  while highdelta != lowdelta + 1:
    newdelta = (lowdelta + 1 + highdelta) // 2  # bias toward the high side, since newdelta should never equal lowdelta
    gliderpat = g.transform(EOlist[parity],(lane+1)//2+newdelta, newdelta)
    outcome = g.evolve(g.join(targetpat, gliderpat), ticks)
    if str(outcome)==str(expectedoutcome):
      # the tested value is the new high value; rinse and repeat
      g.putcells(outcome)
      g.putcells(outcome)
      g.fit()
      g.update()
      g.note("Still good at " + str(newdelta))
      highdelta = newdelta
    else:
      # the tested value is the new low value; rinse and repeat
      g.putcells(outcome)
      g.fit()
      g.update()
      g.note("No good at " + str(newdelta))
      lowdelta = newdelta
  # We'll need a separate binary (?) search to determine how far we can advance the new targetpat+gliderpat pattern
  #   to produce a new targetpat and new expected outcome.  It should be roughly the last tick before the
  #   gliderpat glider interacts with the previous targetpat -- but it can be a few ticks before that,
  #   if that makes it faster to check for the collision.
  # Let's just try stepping forward by 16 ticks at a time and ensuring that the gliderpat is still the same shape,
  #   offset by 2N cells... but we won't worry about whether there are ON cells around the glider.
  # I could imagine that there might be weird ways that this could cause optimization failures, but
  #   they would be very few and far between if we just stepped back to the previous 16-tick step before
  #   the final "passing" step.
  
  offset += highdelta
  # TODO:  continue with next glider,
  #        but only after adjusting the target pattern until the current glider is almost ready to crash
  # TODO:  collect optimized recipe deltas, adjusting for the above adjustment!
  g.exit()

EDIT: Here's a first attempt at getting through a complete optimization. It can be sped up a lot by removing the diagnostic g.new(), g.putcells(), g.fit() and g.update() commands:

Code: Select all

# new-binary-slow-salvo-optimizer.py
import golly as g

LONG_ENOUGH = 4096               # running each intermediate target plus a single glider for this long should produce the next intermediate target
MIN_DELTA = 5                    # only optimize down to a safe distance (two blank lanes between adjacent slow gliders)
INITIAL_DELTA = MIN_DELTA + 256  # it should be safe (producing the desired output) to build the entire slow salvo at this offset
                                 # the distance between min and initial might as well be a power of two, but it's not necessary
EOlist = [ g.parse("3o$o$bo!",-1,0), g.parse("bo$2o$obo!") ]
lanes = [9, 15, -1, 31, 19, -3, -5, 1, 5, 3, 9, 25, 31, 51, 37, 11, 43, -5, -13, -13, -7, 7, -23, -39, 15, 19, 33, 21, -3, 17, 11, 23, 63, 83, 83, 67, 95, 95, 103, -55, -61, -57, -69, -51, -83, -87, -85, -81, -87, -87, -109, -71, -75, -59, -79, -63, -69, -53, -77, -75, -53, -15, -11, -19, -25, -15, -11, -35, -39, -23, -51, -51, -59, 9, 15, 27, 9, 45, 45, 31, 45, 3, 9, 25, 35, 13, 13, 31, 31, 47, 13, 19, 15, 27, 47, 3, 5, -21, -85, -45, 7, -25, -25, 5, -19, -27, -23, -23, -33, -25, -17, 3, -27, 3, 9, 9, 7, 21, 13, 13, 11, -5, -19, -19, -1, 47, 37, 37, 41, 59, 41, 37, 63, 71, -9, -7, -3, -25, -13, -9, -15, -15, -13, -7, -3, -5, 1, 17, 23, 43, 29, 3, 35, -13, -21, -21, -15, -1, -31, -47, 7, 11, 25, 13, -11, 9, 3, 15, 55, 75, 75, 59, 87, 87, 95, -63, -69, -65, -77, -59, -91, -95, -93, -89, -95, -95, -117, -79, -83, -67, -87, -71, -77, -61, -85, -83, -61, -23, -19, -27, -33, -23, -19, -43, -47, -31, -59, -59, -67, 1, 7, 19, 1, 37, 37, 23, 37, -5, 1, 17, 27, 5, 5, 23, 23, 39, 5, 11, 7, 19, 39, -5, -3, -29, -93, -53, -1, -33, -33, -3, -27, -35, -31, -31, -41, -33, -25, -5, -35, -5, 1, 1, -1, 13, 5, 5, 3, -13, -27, -27, -9, 39, 29, 29, 33, 51, 33, 29, 55, 63, -17, -23, -7, -39, -27, -5, -21, -15, -11, -13, -7, 9, 15, 35, 21, -5, 27, -21, -29, -29, -23, -9, -39, -55, -1, 3, 17, 5, -19, 1, -5, 7, 47, 67, 67, 51, 79, 79, 87, -71, -77, -73, -85, -67, -99, -103, -101, -97, -103, -103, -125, -87, -91, -75, -95, -79, -85, -69, -93, -91, -69, -31, -27, -35, -41, -31, -27, -51, -55, -39, -67, -67, -75, -7, -1, 11, -7, 29, 29, 15, 29, -13, -7, 9, 19, -3, -3, 15, 15, 31, -3, 3, -1, 11, 31, -13, -11, -37, -101, -61, -9, -41, -41, -11, -35, -43, -39, -39, -49, -41, -33, -13, -43, -13, -7, -7, -9, 5, -3, -3, -5, -21, -35, -35, -17, 31, 21, 21, 25, 43, 25, 21, 47, 55, -7, -27, -9, -17, -13, -21, -37, -31, -31, -23, -53, -35, -29, -25, -27, -21, -5, 1, 21, 7, -19, 13, -35, -43, -43, -37, -23, -53, -69, -15, -11, 3, -9, -33, -13, -19, -7, 33, 53, 53, 37, 65, 65, 73, -85, -91, -87, -99, -81, -113, -117, -115, -111, -117, -117, -139, -101, -105, -89, -109, -93, -99, -83, -107, -105, -83, -45, -41, -49, -55, -45, -41, -65, -69, -53, -81, -81, -89, -21, -15, -3, -21, 15, 15, 1, 15, -27, -21, -5, 5, -17, -17, 1, 1, 17, -17, -11, -15, -3, 17, -27, -25, -51, -115, -75, -23, -55, -55, -25, -49, -57, -53, -53, -63, -55, -47, -27, -57, -27, -21, -21, -23, -9, -17, -17, -19, -35, -49, -49, -31, 17, 7, 7, 11, 29, 11, 7, 33, 41, -21, -3, -3, 5, -15, -15, -1, -19, -13, -9, -11, -5, 11, 17, 37, 23, -3, 29, -19, -27, -27, -21, -7, -37, -53, 1, 5, 19, 7, -17, 3, -3, 9, 49, 69, 69, 53, 81, 81, 89, -69, -75, -71, -83, -65, -97, -101, -99, -95, -101, -101, -123, -85, -89, -73, -93, -77, -83, -67, -91, -89, -67, -29, -25, -33, -39, -29, -25, -49, -53, -37, -65, -65, -73, -5, 1, 13, -5, 31, 31, 17, 31, -11, -5, 11, 21, -1, -1, 17, 17, 33, -1, 5, 1, 13, 33, -11, -9, -35, -99, -59, -7, -39, -39, -9, -33, -41, -37, -37, -47, -39, -31, -11, -41, -11, -5, -5, -7, 7, -1, -1, -3, -19, -33, -33, -15, 33, 23, 23, 27, 45, 27, 23, 49, 57, -23, -29, 1, 19, 5, -27, 13, -3, 3, 7, 5, 11, 27, 33, 53, 39, 13, 45, -3, -11, -11, -5, 9, -21, -37, 17, 21, 35, 23, -1, 19, 13, 25, 65, 85, 85, 69, 97, 97, 105, -53, -59, -55, -67, -49, -81, -85, -83, -79, -85, -85, -107, -69, -73, -57, -77, -61, -67, -51, -75, -73, -51, -13, -9, -17, -23, -13, -9, -33, -37, -21, -49, -49, -57, 11, 17, 29, 11, 47, 47, 33, 47, 5, 11, 27, 37, 15, 15, 33, 33, 49, 15, 21, 17, 29, 49, 5, 7, -19, -83, -43, 9, -23, -23, 7, -17, -25, -21, -21, -31, -23, -15, 5, -25, 5, 11, 11, 9, 23, 15, 15, 13, -3, -17, -17, 1, 49, 39, 39, 43, 61, 43, 39, 65, 73, 11, 17, 33, 11, 1, -31, -5, 1, 5, 3, 9, 25, 31, 51, 37, 11, 43, -5, -13, -13, -7, 7, -23, -39, 15, 19, 33, 21, -3, 17, 11, 23, 63, 83, 83, 67, 95, 95, 103, -55, -61, -57, -69, -51, -83, -87, -85, -81, -87, -87, -109, -71, -75, -59, -79, -63, -69, -53, -77, -75, -53, -15, -11, -19, -25, -15, -11, -35, -39, -23, -51, -51, -59, 9, 15, 27, 9, 45, 45, 31, 45, 3, 9, 25, 35, 13, 13, 31, 31, 47, 13, 19, 15, 27, 47, 3, 5, -21, -85, -45, 7, -25, -25, 5, -19, -27, -23, -23, -33, -25, -17, 3, -27, 3, 9, 9, 7, 21, 13, 13, 11, -5, -19, -19, -1, 47, 37, 37, 41, 59, 41, 37, 63, 71, -9, -3, 1, -9, -1, -7, -1, 3, 1, 7, 39, 23, 29, 49, 35, 9, 41, -7, -15, -15, -9, 5, -25, -41, 13, 17, 31, 19, -5, 15, 9, 21, 61, 81, 81, 65, 93, 93, 101, -57, -63, -59, -71, -53, -85, -89, -87, -83, -89, -89, -111, -73, -77, -61, -81, -65, -71, -55, -79, -77, -55, -17, -13, -21, -27, -17, -13, -37, -41, -25, -53, -53, -61, 7, 13, 25, 7, 43, 43, 29, 43, 1, 7, 23, 33, 11, 11, 29, 29, 45, 11, 17, 13, 25, 45, 1, 3, -23, -87, -47, 5, -27, -27, 3, -21, -29, -25, -25, -35, -27, -19, 1, -29, 1, 7, 7, 5, 19, 11, 11, 9, -7, -21, -21, -3, 45, 35, 35, 39, 57, 39, 35, 61, 69, -11, -5, -11, -19, -17, -13, -19, 7, -25, -45, -15, -9, -21, -15, -11, -13, -7, 9, 15, 35, 21, -5, 27, -21, -29, -29, -23, -9, -39, -55, -1, 3, 17, 5, -19, 1, -5, 7, 47, 67, 67, 51, 79, 79, 87, -71, -77, -73, -85, -67, -99, -103, -101, -97, -103, -103, -125, -87, -91, -75, -95, -79, -85, -69, -93, -91, -69, -31, -27, -35, -41, -31, -27, -51, -55, -39, -67, -67, -75, -7, -1, 11, -7, 29, 29, 15, 29, -13, -7, 9, 19, -3, -3, 15, 15, 31, -3, 3, -1, 11, 31, -13, -11, -37, -101, -61, -9, -41, -41, -11, -35, -43, -39, -39, -49, -41, -33, -13, -43, -13, -7, -7, -9, 5, -3, -3, -5, -21, -35, -35, -17, 31, 21, 21, 25, 43, 25, 21, 47, 55, -25, -19, -29, -45, -23, -27, -31, -25, -21, -23, -17, -1, 5, 25, 11, -15, 17, -31, -39, -39, -33, -19, -49, -65, -11, -7, 7, -5, -29, -9, -15, -3, 37, 57, 57, 41, 69, 69, 77, -81, -87, -83, -95, -77, -109, -113, -111, -107, -113, -113, -135, -97, -101, -85, -105, -89, -95, -79, -103, -101, -79, -41, -37, -45, -51, -41, -37, -61, -65, -49, -77, -77, -85, -17, -11, 1, -17, 19, 19, 5, 19, -23, -17, -1, 9, -13, -13, 5, 5, 21, -13, -7, -11, 1, 21, -23, -21, -47, -111, -71, -19, -51, -51, -21, -45, -53, -49, -49, -59, -51, -43, -23, -53, -23, -17, -17, -19, -5, -13, -13, -15, -31, -45, -45, -27, 21, 11, 11, 15, 33, 15, 11, 37, 45, -17, -13, -13, -17, -43, -21, -13, -15, -9, -5, -7, -1, 15, 21, 41, 27, 1, 33, -15, -23, -23, -17, -3, -33, -49, 5, 9, 23, 11, -13, 7, 1, 13, 53, 73, 73, 57, 85, 85, 93, -65, -71, -67, -79, -61, -93, -97, -95, -91, -97, -97, -119, -81, -85, -69, -89, -73, -79, -63, -87, -85, -63, -25, -21, -29, -35, -25, -21, -45, -49, -33, -61, -61, -69, -1, 5, 17, -1, 35, 35, 21, 35, -7, -1, 15, 25, 3, 3, 21, 21, 37, 3, 9, 5, 17, 37, -7, -5, -31, -95, -55, -3, -35, -35, -5, -29, -37, -33, -33, -43, -35, -27, -7, -37, -7, -1, -1, -3, 11, 3, 3, 1, -15, -29, -29, -11, 37, 27, 27, 31, 49, 31, 27, 53, 61, -19, -13, -23, -39, -17, -21, -25, -19, -15, -17, -11, 5, 11, 31, 17, -9, 23, -25, -33, -33, -27, -13, -43, -59, -5, -1, 13, 1, -23, -3, -9, 3, 43, 63, 63, 47, 75, 75, 83, -75, -81, -77, -89, -71, -103, -107, -105, -101, -107, -107, -129, -91, -95, -79, -99, -83, -89, -73, -97, -95, -73, -35, -31, -39, -45, -35, -31, -55, -59, -43, -71, -71, -79, -11, -5, 7, -11, 25, 25, 11, 25, -17, -11, 5, 15, -7, -7, 11, 11, 27, -7, -1, -5, 7, 27, -17, -15, -41, -105, -65, -13, -45, -45, -15, -39, -47, -43, -43, -53, -45, -37, -17, -47, -17, -11, -11, -13, 1, -7, -7, -9, -25, -39, -39, -21, 27, 17, 17, 21, 39, 21, 17, 43, 51, -11, -5, -21, 11, -1, -23, -25, -19, -15, -17, -11, 5, 11, 31, 17, -9, 23, -25, -33, -33, -27, -13, -43, -59, -5, -1, 13, 1, -23, -3, -9, 3, 43, 63, 63, 47, 75, 75, 83, -75, -81, -77, -89, -71, -103, -107, -105, -101, -107, -107, -129, -91, -95, -79, -99, -83, -89, -73, -97, -95, -73, -35, -31, -39, -45, -35, -31, -55, -59, -43, -71, -71, -79, -11, -5, 7, -11, 25, 25, 11, 25, -17, -11, 5, 15, -7, -7, 11, 11, 27, -7, -1, -5, 7, 27, -17, -15, -41, -105, -65, -13, -45, -45, -15, -39, -47, -43, -43, -53, -45, -37, -17, -47, -17, -11, -11, -13, 1, -7, -7, -9, -25, -39, -39, -21, 27, 17, 17, 21, 39, 21, 17, 43, 51, -11, -19, -35, -19, -9, -27, -9, -3, 1, -1, 5, 21, 27, 47, 33, 7, 39, -9, -17, -17, -11, 3, -27, -43, 11, 15, 29, 17, -7, 13, 7, 19, 59, 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49, 31, 27, 53, 61, -1, 17, 3, -17, -1, -3, -1, 5, 9, 7, 13, 29, 35, 55, 41, 15, 47, -1, -9, -9, -3, 11, -19, -35, 19, 23, 37, 25, 1, 21, 15, 27, 67, 87, 87, 71, 99, 99, 107, -51, -57, -53, -65, -47, -79, -83, -81, -77, -83, -83, -105, -67, -71, -55, -75, -59, -65, -49, -73, -71, -49, -11, -7, -15, -21, -11, -7, -31, -35, -19, -47, -47, -55, 13, 19, 31, 13, 49, 49, 35, 49, 7, 13, 29, 39, 17, 17, 35, 35, 51, 17, 23, 19, 31, 51, 7, 9, -17, -81, -41, 11, -21, -21, 9, -15, -23, -19, -19, -29, -21, -13, 7, -23, 7, 13, 13, 11, 25, 17, 17, 15, -1, -15, -15, 3, 51, 41, 41, 45, 63, 45, 41, 67, 75, -5, -19, -3, 23, 33, 9, 15, 19, 17, 23, 39, 45, 65, 51, 25, 57, 9, 1, 1, 7, 21, -9, -25, 29, 33, 47, 35, 11, 31, 25, 37, 77, 97, 97, 81, 109, 109, 117, -41, -47, -43, -55, -37, -69, -73, -71, -67, -73, -73, -95, -57, -61, -45, -65, -49, -55, -39, -63, -61, -39, -1, 3, -5, -11, -1, 3, -21, -25, -9, -37, -37, -45, 23, 29, 41, 23, 59, 59, 45, 59, 17, 23, 39, 49, 27, 27, 45, 45, 61, 27, 33, 29, 41, 61, 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0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1]

reverse_salvo = -1
def checkoffset(targetpat, expectedoutcome, testglider, ticks):
  outcome = g.evolve(g.join(targetpat, testglider), ticks)
  return (str(outcome) == str(expectedoutcome))  # TODO: does it work without the str()? List comparisons can be weird.

targetpat = g.parse("2o$2o!")
targetpat = g.parse("""814b2o$814b2o11$805b2o$805b2o8b2o$814bo2bo$815b2o4bo$820bobo$820bobo$
821bo7$806b2o$805bo2bo$806b2o4bo$811bobo$811bobo$812bo3$824b2o$823bo2b
o$824b2o3$786b2o$786b2o12$773b2o12b2o$773b2o11bo2bo$787b2o4bo$792bobo$
792bobo$793bo8$774b2o$773bo2bo$774b2o4bo$779bobo$779bobo$780bo9$755b2o
$755b2o12$756b2o$755bo2bo$756b2o4bo$761bobo$761bobo$762bo4$742b2o$742b
2o12$743b2o$742bo2bo$743b2o4bo$727b2o19bobo$727b2o19bobo$749bo11$715b
2o11b2o$715b2o10bo2bo$728b2o4bo$733bobo$733bobo$734bo8$716b2o$715bo2bo
$701b2o13b2o4bo$701b2o18bobo$721bobo$722bo10$702b2o$701bo2bo$690b2o10b
2o4bo$690b2o15bobo$707bobo$708bo10$691b2o$690bo2bo$691b2o4bo$696bobo$
696bobo$673b2o22bo$673b2o12$674b2o$673bo2bo$674b2o4bo$659b2o18bobo$
659b2o18bobo$680bo11$660b2o$659bo2bo$660b2o4bo$665bobo$643b2o20bobo$
643b2o21bo10$632b2o$632b2o$644b2o$643bo2bo$644b2o4bo$649bobo$649bobo$
650bo6$633b2o$621b2o9bo2bo$621b2o10b2o4bo$638bobo$638bobo$639bo9$622b
2o$621bo2bo$622b2o4bo$627bobo$605b2o20bobo$605b2o21bo12$606b2o$605bo2b
o$606b2o4bo$590b2o19bobo$590b2o19bobo$612bo11$591b2o$590bo2bo$591b2o4b
o$596bobo$596bobo$573b2o22bo$573b2o12$574b2o$573bo2bo$574b2o4bo$558b2o
19bobo$558b2o19bobo$580bo11$559b2o$545b2o11bo2bo$545b2o12b2o4bo$564bob
o$564bobo$565bo9$546b2o$545bo2bo$546b2o4bo$531b2o18bobo$531b2o18bobo$
552bo11$532b2o$531bo2bo$532b2o4bo$537bobo$515b2o20bobo$515b2o21bo12$
516b2o$515bo2bo$501b2o13b2o4bo$501b2o18bobo$521bobo$522bo10$502b2o$
501bo2bo$502b2o4bo$507bobo$507bobo$484b2o22bo$484b2o12$485b2o$471b2o
11bo2bo$471b2o12b2o4bo$490bobo$490bobo$491bo9$461b2o9b2o$461b2o8bo2bo$
472b2o4bo$477bobo$477bobo$478bo6$450b2o$450b2o$462b2o$461bo2bo$462b2o
4bo$467bobo$467bobo$468bo6$451b2o$450bo2bo$451b2o4bo$436b2o18bobo$436b
2o18bobo$457bo9$424b2o$424b2o$437b2o$436bo2bo$437b2o4bo$442bobo$442bob
o$443bo6$425b2o$424bo2bo$425b2o4bo$430bobo$412b2o16bobo$412b2o17bo12$
413b2o$399b2o11bo2bo$399b2o12b2o4bo$418bobo$418bobo$419bo9$400b2o$384b
2o13bo2bo$384b2o14b2o4bo$405bobo$405bobo$406bo9$385b2o$384bo2bo$385b2o
4bo$369b2o19bobo$369b2o19bobo$391bo11$370b2o$369bo2bo$355b2o13b2o4bo$
355b2o18bobo$375bobo$376bo9$344b2o$344b2o10b2o$355bo2bo$356b2o4bo$361b
obo$361bobo$362bo7$345b2o$344bo2bo$345b2o4bo$350bobo$328b2o20bobo$328b
2o21bo12$317b2o10b2o$317b2o9bo2bo$329b2o4bo$334bobo$334bobo$335bo8$
318b2o$317bo2bo$318b2o4bo$323bobo$323bobo$324bo4$306b2o$306b2o9$289b2o
$289b2o2$307b2o$306bo2bo$307b2o4bo$312bobo$312bobo$313bo5$290b2o$289bo
2bo$290b2o4bo$295bobo$295bobo$296bo6$272b2o$272b2o12$273b2o$272bo2bo$
273b2o4bo$278bobo$278bobo$255b2o22bo$255b2o12$244b2o10b2o$244b2o9bo2bo
$256b2o4bo$261bobo$261bobo$262bo8$245b2o$244bo2bo$245b2o4bo$228b2o20bo
bo$228b2o20bobo$251bo9$218b2o$218b2o$229b2o$228bo2bo$229b2o4bo$234bobo
$234bobo$235bo6$219b2o$218bo2bo$219b2o4bo$224bobo$224bobo$225bo5$201b
2o$201b2o10$191b2o$191b2o$202b2o$201bo2bo$202b2o4bo$207bobo$207bobo$
208bo6$192b2o$191bo2bo$192b2o4bo$197bobo$197bobo$198bo5$175b2o$175b2o
12$176b2o$175bo2bo$176b2o4bo$181bobo$159b2o20bobo$159b2o21bo12$160b2o$
159bo2bo$160b2o4bo$165bobo$165bobo$144b2o20bo$144b2o12$145b2o$144bo2bo
$145b2o4bo$150bobo$150bobo$151bo6$128b2o$128b2o11$116b2o$116b2o11b2o$
128bo2bo$129b2o4bo$134bobo$134bobo$135bo7$117b2o$116bo2bo$117b2o4bo$
122bobo$122bobo$123bo14$109b2o$109b2o9$99b2o$99b2o2$110b2o$109bo2bo$
110b2o4bo$115bobo$115bobo$116bo5$100b2o$99bo2bo$100b2o4bo$105bobo$105b
obo$106bo9$90b2o$90b2o12$91b2o$90bo2bo$91b2o4bo$96bobo$96bobo$97bo108$
2o$2o!""",0,-1002)
optimized_offsets = []
evolved_delta = 0  # this will increase as we fast-forward the target pattern while always
               #   leaving the previous glider in place, about to strike --
               #   can't advance to stability, because then we wouldn't know about temporary sparks
               #   that extend salvo-source-wards, that might make the optimization unworkable
for item in zip(lanes, parities):
  lane, parity = item
  lane *= reverse_salvo
  # we always know that the optimal glider position is somewhere between lowdelta and highdelta
  # -- and when lowdelta and highdelta are the same value, we're done
  # An assumption here is that the target object won't travel farther from its initial position,
  #   away from the slow-salvo source, than the distance between MIN_DELTA and INITIAL_DELTA.
  #   Increase INITIAL_DELTA if it seems possible that the target region will travel farther than this.
  highdelta, lowdelta = INITIAL_DELTA, MIN_DELTA*2 - 1 - INITIAL_DELTA
  # whatever happens when the glider is delayed by {delta} cells diagonally ...
  #   is what we want to be sure continues to happen in exactly the same way when we reduce the offset.
  #   So we'll start by defining the desired outcome to be whatever happens at the high end of the range.
  #
  # Let's say that the lowdelta variable will always contain the highest value that's known to not work
  ticks = highdelta * 4 + LONG_ENOUGH
  gliderpat = g.transform(EOlist[parity],(lane+1)//2+highdelta, highdelta)
  expectedoutcome = g.evolve(g.join(targetpat, gliderpat), ticks)
  while highdelta != lowdelta + 1:
    newdelta = (lowdelta + 1 + highdelta) // 2  # bias toward the high side, since newdelta should never equal lowdelta
    gliderpat = g.transform(EOlist[parity],(lane+1)//2+newdelta, newdelta)
    outcome = g.evolve(g.join(targetpat, gliderpat), ticks)
    if str(outcome)==str(expectedoutcome):
      # the tested value is the new high value; rinse and repeat
      # g.new("Still good")
      # g.putcells(g.join(targetpat, gliderpat))
      # g.fit()
      # g.update()
      # g.note("Still good at " + str(newdelta))
      highdelta = newdelta
    else:
      # the tested value is the new low value; rinse and repeat
      # g.new("No good")
      # g.putcells(g.join(targetpat,gliderpat))
      # g.fit()
      # g.update()
      # g.note("No good at " + str(newdelta))
      lowdelta = newdelta
  
  # it's possible that the binary search will find a value that's lower than
  #   the minimum optimization that we're allowing, 5 rows below the previous glider
  #   Strange things can happen when a slow glider arrives before its predecessor,
  #   so to keep things simple let's just set the minimum to 5.
  if optimized_offsets!=[]:
    if highdelta + evolved_delta - optimized_offsets[-1] < 5:
      evolved_delta = optimized_offsets[-1] + 5 - highdelta
  
  # At this point, lowdelta will contain the highest non-working glider location (that we're allowing),
  #   and highdelta will contain the lowest working glider location --
  #   with some possible exceptions:  for example, an unusual spark from a previously colliding glider
  #   _could_ mean that some later glider locations (that we didn't happen to check) are unworkable.
  #   For these optimization purposes, this doesn't matter --
  #   we're only guaranteeing that the salvo is a slow salvo if we add 256 to each glider position.
  optimized_offsets.append(highdelta+evolved_delta)
  
  # We'll need a separate binary (?) search to determine how far we can advance the new targetpat+gliderpat pattern
  #   to produce a new targetpat and new expected outcome.  It should be roughly the last tick before the
  #   gliderpat glider interacts with the previous targetpat -- but it can be a few ticks before that,
  #   if that makes it faster to check for the collision.
  # To make the test faster, we can simply advance the combined target + glider pattern four ticks at a time,
  #   checking at each step whether the last cell in the cell list has a y value that has decreased by one.
  #   If no spark or explosion is moving slow-salvo-sourcewards yet, and the glider has not passed any
  #   stationary ash objects, then it's safe to advance that far. As soon as that's not true, stop.
  testtargetpat = g.evolve(g.join(targetpat, g.transform(EOlist[parity],(lane+1)//2+highdelta, highdelta)), 4)
  time_added = 0
  southmost_y_value = testtargetpat[-1]  # this is safe because we're working with two-state lists, no added zeroes at end of cell list
  target_y_value = southmost_y_value
  while target_y_value == southmost_y_value:
    time_added += 4
    newtargetpat = testtargetpat
    testtargetpat = g.evolve(newtargetpat,4)
    target_y_value -= 1
    southmost_y_value = testtargetpat[-1]
    g.new("Now testing time_added = " + str(time_added+4))
    g.putcells(testtargetpat)
    g.fit()
    g.update()
    # g.note("Southmost Y value = " + str(lowest_y_value))
  # now newtargetpat contains the most advanced "safe" phase of the target pattern plus the latest glider,
  #   and time_added contains the number of ticks that the combined pattern was advanced
  evolved_delta += time_added//4
  targetpat = newtargetpat
  # g.note("optimized offsets = " + str(optimized_offsets))
  g.show(str(len(optimized_offsets)))
  if len(optimized_offsets)>255:
    break
g.show("Done.")
g.setclipstr(str(optimized_offsets))

This correctly finds the optimized locations I'm looking for, as evidenced by the fact that all the Corderships are generated in the right places. However, it doesn't give me quite the right list of deltas -- when I try "reconstituting" them with another script, the salvo works for a while, then succumbs to some kind of subtle timing failure.

The next task is to troubleshoot and find out why. If anyone is following along with this thread, let me know if any questions are coming up that I'm not answering. I'm including some comments in the code, but am not really sure if they're useful to my audience (because I'm not sure I have an audience.)

[dvgrn]

A quick temporary switch to another subject: an easy way to make a slow^2 salvo compiler would be to use the following four-glider slow salvo to create a sideways glider from a honeyfarm, and then move the honeyfarm around to wherever it's needed next using a standard honeyfarm-move table.

Code: Select all

x = 59, y = 33, rule = B3/S23
56bo$56bobo$56b2o3$22bo7bo$22bobo5bobo$22b2o6b2o$56bo$56bobo$56b2o3$
16bo29bo$16bobo27bobo$16b2o28b2o5$6bo29bo$5bobo27bobo$5bobo27bobo$6bo
8bo20bo8bo$15bobo27bobo$b2o7b2o3b2o14b2o7b2o3b2o$o2bo5bo2bo17bo2bo5bo
2bo$b2o7b2o19b2o7b2o2$6bo29bo$5bobo27bobo$5bobo27bobo$6bo29bo!

-- Well, ahem, there isn't actually a standard honeyfarm-move table -- but as calcyman advised on Discord, it's easy to make one from slmake's block-move table:

The first glider impact is either:
(1) a block-to-HF;
(2) a knight-pull.
Keep moving the first glider to the end of the recipe until it's (1), and then you're done.

The only failure mode is when you have a block-pull composed entirely of (2)s.

Okay, so a good place to start is to make sure that we can read the block-move table correctly:

Code: Select all

import golly as g

with open("C:/repos/slmake/data/longmove/xs4_33", "r") as f:
  blockmovedata = f.readlines()

for item in blockmovedata:
  if item[:4] == "GOOD":
    good, cost, offset, recipe, parity = [s.strip() for s in item.split(":")]
    g.note(str([good,cost,offset,recipe,parity]))  # print the first line's data and exit, just to make sure we're doing it right
    g.exit()

So far so good:

Code: Select all

Golly note:
['GOOD', '1', '(1, 2)O', '-11E', 'even']

A little more parsing and we're almost ready to process this data:

Code: Select all

import golly as g

with open("C:/repos/slmake/data/longmove/xs4_33", "r") as f:
  blockmovedata = f.readlines()

count=0

for item in blockmovedata:
  if item[:4] == "GOOD":
    count += 1
    good, cost, offset, recipe, parity = [s.strip() for s in item.split(":")]
    cost = int(cost)
    offset = offset.replace("O","").replace("T","").replace("(","").replace(")","")
    offsetx, offsety = [int(delta) for delta in offset.split(", ")]
    recipelist = recipe.split(" ")
    parsedrecipe = []
    for lanestr in recipelist:
      lane = int(lanestr[:-1])
      parity = lanestr[-1:]
      parsedrecipe.append([lane,parity])
    if count == 256:
      g.note(str(["cost=",cost,"delta=",offsetx,offsety,"recipe=",parsedrecipe,"parity=",parity]))
      g.exit()

Code: Select all

Golly note:
['cost=', 5, 'delta=', 4, 0, 'recipe=', [[-9, 'E'], [-3, 'E'], [11, 'E'], [-9, 'E'], [7, 'E']], 'parity=', 'E']

Okay, now put in some comments to outline what's left to do, and gradually replace them with actual code. For the sixteenth recipe in the slmake block-move table, for example, we want to turn the left-side recipe into the right-side recipe:

Code: Select all

x = 160, y = 63, rule = B3/S23
4b2o$2o2bobo$2o2bo2$83bo$82bobo$82bobo$83bo2$78b2o7b2o$77bo2bo5bo2bo$
78b2o7b2o2$83bo$82bobo$82bobo$83bo4$13b2o68b2o$13bobo67bobo$13bo69bo
18$43b2o68b2o$43bobo67bobo$43bo69bo18$157b2o$157bobo$157bo!

Code: Select all

import golly as g

with open("C:/repos/slmake/data/longmove/xs4_33", "r") as f:
  blockmovedata = f.readlines()

count=0

for item in blockmovedata:
  if item[:4] == "GOOD":
    count += 1
    good, cost, offset, recipe, parity = [s.strip() for s in item.split(":")]
    cost = int(cost)
    offset = offset.replace("O","").replace("T","").replace("(","").replace(")","")
    offsetx, offsety = [int(delta) for delta in offset.split(", ")]
    recipelist = recipe.split(" ")
    parsedrecipe = []
    for lanestr in recipelist:
      validrecipeflag = good
      lane = int(lanestr[:-1])
      parity = lanestr[-1:]
      parsedrecipe.append([lane,parity])
    
    # Now we just have to
    #   1) throw out pi-explosion recipes, since they won't contain a honeyfarm stage (they start with -7E or 7E)
    #   2) move the initial -11E or 11E or -9E or 9E glider to the end of the recipe
    #   3) if the moved glider was a -9E or 9E glider, then stop.
    #   4) otherwise, as long as the new initial glider is a -11E or 11E or -9E or 9E (block move), move it to the end also
    #   5) if you've moved a number of gliders equal to the cost of the recipe and no -9E or 9E has appeared, stop and discard the recipe
    
    hfrecipe = []
    firstgliderlane, firstgliderparity = parsedrecipe[0]
    if firstgliderlane not in [-11,-9,9,11]:
      validrecipeflag = "NO GOOD"
    else:
    
      # When a glider moves from beginning to end, it has to be lined up with the new end target location
      #  -- and we can calculate the necessary offset using offsetx and offsety.
      #  If offsetx == offsety, the new block is on the same lane as the old block and no offset is needed.
      #  The recipes are given in quarter-diagonals, so we'll calculate the necessary delta in qd.
      deltaqd = (offsetx-offsety)*2
      
      shuffledrecipe = parsedrecipe[1:] + [[firstgliderlane+deltaqd, firstgliderparity]]
      if count == 16:
        g.note(str([parsedrecipe, shuffledrecipe]))
        g.exit()

Code: Select all

[code]Golly note:
[[color=red][[9, 'E'], [-13, 'E'], [7, 'E']][/color], [color=green][[-13, 'E'], [7, 'E'], [55, 'E']][/color]]

So far so good -- a recipe of "9E -13E 7E 55E" will indeed turn a block at (0,0) into a honeyfarm, then into two blocks, then into one block, then into a honeyfarm again. But this brings up a little problem.

When we hit a block with a honeyfarm-making glider, it turns it into a honeyfarm that's not centered on (0,0) -- it's offset one way or the other by 8qd, but we can't instantly tell which by looking at the new "-13E 7E 55E" recipe. Similarly, hitting a block with a block-pulling glider will change the target's location by 2qd in one direction or the other.

So we'll have to track how far away from the (0,0) line the target gets, and adjust all the lane numbers by that amount to get back to a standardized recipe centered around (0,0). But this time the recipe will be aimed at a honeyfarm centered along lane 0 rather than a block along lane 0.

The processing here is going to be so fast that efficiency doesn't much matter, so let's go ahead and write a subroutine that adjusts a recipe back to lane 0 after every glider we move. It might be faster to save up the offsets and do them all just once at the end ... by about a millisecond, maybe ... but then it might not be as easy to troubleshoot and find bugs (if I should be so careless as to introduce any).

Code: Select all

import golly as g

def moverecipe(inputlist, d):
  outlist = []
  for item in inputlist:
    l, p = item
    outlist.append([l+d,p])
  return outlist

with open("C:/repos/slmake/data/longmove/xs4_33", "r") as f:
  blockmovedata = f.readlines()

count=0
# dictionary saying how far to move the "zero line" of the recipe for each type of glider moved to the end
offsetdict = {-11:2, -9:8, 9:-8, 11:-2}
for item in blockmovedata:
  if item[:4] == "GOOD":
    count += 1
    good, cost, offset, recipe, parity = [s.strip() for s in item.split(":")]
    cost = int(cost)
    offset = offset.replace("O","").replace("T","").replace("(","").replace(")","")
    offsetx, offsety = [int(delta) for delta in offset.split(", ")]
    recipelist = recipe.split(" ")
    parsedrecipe = []
    for lanestr in recipelist:
      validrecipeflag = good
      lane = int(lanestr[:-1])
      parity = lanestr[-1:]
      parsedrecipe.append([lane,parity])
    
    # Now we just have to
    #   1) throw out pi-explosion recipes, since they won't contain a honeyfarm stage (they start with -7E or 7E)
    #   2) move the initial -11E or 11E or -9E or 9E glider to the end of the recipe
    #   3) if the moved glider was a -9E or 9E glider, then stop.
    #   4) otherwise, as long as the new initial glider is a -11E or 11E or -9E or 9E (block move), move it to the end also
    #   5) if you've moved a number of gliders equal to the cost of the recipe and no -9E or 9E has appeared, stop and discard the recipe
    
    hfrecipe = []
    firstgliderlane, firstgliderparity = parsedrecipe[0]
    if firstgliderlane not in [-11,-9,9,11]:
      validrecipeflag = "NO GOOD"
    else:
    
      # When a glider moves from beginning to end, it has to be lined up with the new end target location
      #  -- and we can calculate the necessary offset using offsetx and offsety.
      #  If offsetx == offsety, the new block is on the same lane as the old block and no offset is needed.
      #  The recipes are given in quarter-diagonals, so we'll calculate the necessary delta in qd.
      deltaqd = (offsetx-offsety)*2
      
      shuffledrecipe = parsedrecipe[1:] + [[firstgliderlane+deltaqd, firstgliderparity]]
      correctedshuffledrecipe = moverecipe(shuffledrecipe, offsetdict[firstgliderlane])
      if count == 16:
        g.note("parsedrecipe = " + str(parsedrecipe) +"\nshuffledrecipe = " + str(shuffledrecipe) + "\ncorrectedshuffledrecipe = "+str(correctedshuffledrecipe))
        g.exit()

Code: Select all

Golly note:
parsedrecipe = [[9, 'E'], [-13, 'E'], [7, 'E']]
shuffledrecipe = [[-13, 'E'], [7, 'E'], [55, 'E']]
correctedshuffledrecipe = [[-21, 'E'], [-1, 'E'], [47, 'E']]

This corrected "-21E -1E 47E" recipe comes out to

Code: Select all

x = 96, y = 73, rule = LifeHistory
6.A$5.A.A$5.A.A$6.A2$.2A7.2A$A2.A5.A2.A$.2A7.2A2$6.A$5.A.A$5.A.A$6.A
8$9.3A$9.A$10.A28$49.3A$49.A$50.A18$93.3A$93.A$94.A!

which appears to be correct.

[dvgrn]

Okay, here's some code to complete the conversion from the last post. It takes a couple of seconds to get through all 92,767 recipes.

Code: Select all

# script corrected 10/30/2022 to fix a rare problem with recipes based on pi explosions
import golly as g

def moverecipe(inputlist, d):
  outlist = []
  for item in inputlist:
    l, p = item
    outlist.append([l+d,p])
  return outlist

with open("C:/repos/slmake/data/longmove/xs4_33", "r") as f:
  blockmovedata = f.readlines()

count=0
# dictionary saying how far to move the "zero line" of the recipe for each type of glider moved to the end
offsetdict = {-11:2, -9:8, 9:-8, 11:-2}

with open ("C:/repos/slmake/data/longmove/hf_move_table.txt", "w") as f:
  for item in blockmovedata:
    if item[:4] == "GOOD":
      count += 1
      good, cost, offset, recipe, parity = [s.strip() for s in item.split(":")]
      cost = int(cost)
      offset = offset.replace("O","").replace("T","").replace("(","").replace(")","")
      offsetx, offsety = [int(delta) for delta in offset.split(", ")]
      recipelist = recipe.split(" ")
      parsedrecipe = []
      for lanestr in recipelist:
        validrecipeflag = good
        lane = int(lanestr[:-1])
        parity = lanestr[-1:]
        parsedrecipe.append([lane,parity])
    
      # Now we just have to
      #   1) throw out pi-explosion recipes, since they won't contain a honeyfarm stage (they start with -7E or 7E)
      #   2) move the initial -11E or 11E or -9E or 9E glider to the end of the recipe
      #   3) if the moved glider was a -9E or 9E glider, then stop.
      #   4) otherwise, as long as the new initial glider is a -11E or 11E or -9E or 9E (block move), move it to the end also
      #   5) if you've moved a number of gliders equal to the cost of the recipe and no -9E or 9E has appeared, stop and discard the recipe
    
      glidersremaining = cost
      correctedshuffledrecipe = []
      while glidersremaining>0:
        glidersremaining -= 1
        firstgliderlane, firstgliderparity = parsedrecipe[0]
        if firstgliderlane not in [-11,-9,9,11]:
          validrecipeflag = "NO GOOD"
          # g.note("This one must be a pi explosion:" + str(parsedrecipe))
          break
        else:
          # When a glider moves from beginning to end, it has to be lined up with the new end target location
          #  -- and we can calculate the necessary offset using offsetx and offsety.
          #  If offsetx == offsety, the new block is on the same lane as the old block and no offset is needed.
          #  The recipes are given in quarter-diagonals, so we'll calculate the necessary delta in qd.
          deltaqd = (offsetx-offsety)*2
          
          shuffledrecipe = parsedrecipe[1:] + [[firstgliderlane+deltaqd, firstgliderparity]]
          correctedshuffledrecipe = moverecipe(shuffledrecipe, offsetdict[firstgliderlane])
          
          # g.note("count, glidersremaining = " + str([count, glidersremaining]) + "\nparsedrecipe = " + str(parsedrecipe) +"\nshuffledrecipe = " + str(shuffledrecipe) + "\ncorrectedshuffledrecipe = "+str(correctedshuffledrecipe))
  
          if firstgliderlane in [-9,9]:
            # we've found the honeyfarm-making glider
            validrecipeflag = "COMPLETE"
            # g.note("Found the HF-maker!")
            break
          parsedrecipe=correctedshuffledrecipe[:]  # be careful to make a copy of the new recipe, not a pointer to it!
          # ... and go around the loop again and see if we can escape next time...
    
      # Okay, we've escaped from the loop one way or another --
      if (glidersremaining == 0 and validrecipeflag != "COMPLETE") or correctedshuffledrecipe == []:
        # g.note("Shuffled all the gliders and never found a HF-maker, or hit a NO GOOD un-shuffle-able recipe")
        pass
      else:
        recipestr = str(correctedshuffledrecipe).replace("[[","").replace(", '","").replace("'], ["," ").replace("']]","")
        f.write(offset+":" + recipestr + "\n")
        g.show(str(92767-count))
    
      # if count == 16:
      #   g.note("Result for reaction #16:\nparsedrecipe = " + str(parsedrecipe) +"\nshuffledrecipe = " + str(shuffledrecipe) + "\ncorrectedshuffledrecipe = "+str(correctedshuffledrecipe))
      #   g.exit()

A good coding challenge for interested readers would be to write a script to go through all the lines of the attached file, and check to see that they all produce an output honeyfarm in the advertised location.

I just tested one randomly chosen recipe by hand --

-2, 0:5E 1E -1O -5E

which comes out to

Code: Select all

x = 47, y = 50, rule = LifeHistory
6.C$5.C.C$5.C.C$6.C2$.2C7.2C$C2.C5.C2.C$.2C7.2C2$6.C$5.C.C$5.C.C$6.C
5$19.3A$19.A$20.A8$27.3A$27.A$28.A7$37.A$36.2AB$36.A.A$37.B8$44.3A$
44.A$45.A!

Good enough for tonight!

hf_move_table.txt

Slow salvo honeyfarm-move table, corrected 10/30/2022 to remove pi-explosion recipes

(6.9 MiB) Downloaded 17 times

[dvgrn]

Anyone who downloaded the HF-move table and didn't check it exhaustively, the joke is on you. About one recipe in 1000 was wrong, due to a bug involving the rare pi-explosion slow salvos. That bug should not have been able to exist, but I missed a trick with my pi-explodey-exclusion code.

The file attached to the previous post has now been corrected. And since this is a coding practice thread, here's the code that tests all of the recipes and confirms that they now all work as advertised:

Code: Select all

import golly as g

delta = 256
gliderE = g.parse("3o$o$bo!")
gliderO = g.parse("b2o$2o$2bo!")
gdict = {"E":gliderE, "O":gliderO}
g.setalgo("HashLife")

if g.numstates()>2: g.exit("Please use a two-state rule.")

with open ("C:/repos/slmake/data/longmove/hf_move_table.txt", "r") as f:
  datalist = f.readlines()

count = 0
for item in datalist:
  offset,recipestr = item.replace("\n","").split(":")
  offsetx, offsety = [int(s) for s in offset.replace(" ","").split(",")]
  # g.note(str([offsetx,offsety,recipestr]))
  offset = 16

  hf = g.parse("6bo$5bobo$5bobo$6bo2$b2o7b2o$o2bo5bo2bo$b2o7b2o2$6bo$5bobo$5bobo$6bo!")
  g.new("Results")
  g.putcells(hf) # honefarm target
  recipe = recipestr.split(" ")
  for item in recipe:
    g.putcells(gdict[item[-1:]], (int(item[:-1])-1)//2+offset, offset)
    offset += delta
  g.run(1024*(len(recipe)+2))
  g.putcells(hf,offsetx,offsety,1,0,0,1,"xor")
  pop = g.getpop()
  if pop != "0":
    g.note("We got a problem here -- line #" + str(count) + ".\n" + recipestr)
    g.exit()
  count += 1
  g.show(str(count))

[Pavgran]

Here's a script compiling slow^2 salvos:

Code: Select all

import golly as g

from collections import defaultdict as dd, namedtuple

g.show("Reading move data...")
g.update()

gliderE = g.parse("3o$o$bo!")
gliderO = g.parse("b2o$2o$2bo!")
hf = g.parse("6bo$5bobo$5bobo$6bo2$b2o7b2o$o2bo5bo2bo$b2o7b2o2$6bo$5bobo$5bobo$6bo!")
gdict = {"E":gliderE, "O":gliderO}

Move = namedtuple("Move", "lane_diff offset_diff glider_num envelope_pos envelope_neg gliders")

class Glider(namedtuple("_Glider", "lane parity")):
    def __new__(cls, glider_str):
        parity = {'E': 0, 'O': 1}[glider_str[-1]]
        lane = int(glider_str[:-1])
        return super().__new__(cls, lane, parity)

# outer dict by lane, inner dict by glider_num
move_data = dd(lambda: dd(list))

with open("hf_move_table.txt") as f:
    for line in f:
        offset, recipe = line.strip().split(':')
        x, y = map(int, offset.split(','))
        gliders = list(map(Glider, recipe.strip().split()))
        
        lane_diff = -(x+y)
        offset_diff = (x-y)
        glider_num = len(gliders)
        envelope_pos = max(glider.lane for glider in gliders)
        envelope_neg = min(glider.lane for glider in gliders)
        
        move = Move(lane_diff = lane_diff,
                    offset_diff = offset_diff,
                    glider_num = glider_num,
                    envelope_pos = envelope_pos,
                    envelope_neg = envelope_neg,
                    gliders = gliders,
                    )
        move_data[lane_diff][glider_num].append(move)

Fire = namedtuple("Fire", "move lane")

fire_recipes = [
    (2, -4, "-15E 3O -7E 9E", 11, 0),
    (2, -4, "-15E 3E -7E 9E", 11, 1),
    (-4, 2, "-15E 3O 7E -9E", 11, 0),
    (-4, 2, "-15E 3E 7E -9E", 11, 1),
    ]

# parity is key
fire_data = {0: [], 1: []}

for x, y, recipe, fire_lane, parity in fire_recipes:
    gliders = list(map(Glider, recipe.strip().split()))
    lane_diff = -(x+y)
    offset_diff = (x-y)
    glider_num = len(gliders)
    envelope_pos = max(glider.lane for glider in gliders)
    envelope_neg = min(glider.lane for glider in gliders)
    
    move = Move(lane_diff = lane_diff,
                offset_diff = offset_diff,
                glider_num = glider_num,
                envelope_pos = envelope_pos,
                envelope_neg = envelope_neg,
                gliders = gliders,
                )
    fire = Fire(move = move,
                lane = fire_lane)
    fire_data[parity].append(fire)

# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------
# That part is snatched from Dave Greene's script

g.show("Analysing input recipe...")
g.update()

def glidermatch(clist):
  count = 0
  for glider in glist:
    match = 1
    # remember that glider[0] and glider[1] are always zero
    x, y = clist[0],clist[1]
    # we could just do all the calculations and compare the whole list --
    #   offsetclist = [0,0,clist[2]-x,clist[3]-y,clist[4]-x,clist[5]-y,clist[6]-x,clist[7]-y,clist[8]-x,clist[9]-y]
    # -- but it might be very slightly faster to stop comparing at the first mismatch, so let's do that.
    for i in range(1,5): # check to see if any of the other four cells fail to match the template glider from glist
      if glider[2*i] != clist[2*i]-x or glider[2*i+1] != clist[2*i+1]-y:
        match = 0
        break
    if match == 1: # all cells matched
      return count
    count +=1
  return -1   # this will happen only if none of the four gliders are a match for the five cells in clist

g.setalgo("HashLife")

# glist = [ g.parse("3o$o$bo!",0,0), g.parse("bo$2o$obo!",1,-2), \
#           g.parse("2o$obo$o!",2,-1), g.parse("b2o$2o$2bo!",3,-1) ]
glist = [ g.parse("3o$o$bo!",0,0), g.parse("bo$2o$obo!",-1,0), \
          g.parse("2o$obo$o!",0,0), g.parse("b2o$2o$2bo!",-1,0) ]
glistoffsets = [0, 4, 2, 2]  # how far to the right each glider in glist is, in quarter-diagonals, compared to reference lane

if g.numstates()>2: g.exit("Please use a two-state rule.")

r=g.getrect()
if len(r)==0: g.exit("No pattern found.")

everything = g.getcells(g.getrect())
lanes, parities = [], []

ptr = len(everything) - 10
target = []
while target == []:
  whichglider = glidermatch(everything[ptr:])
  if whichglider == -1:
    target = everything[:ptr+10]
  else:
    lanes.append((everything[ptr]-everything[ptr+1])*2 + 1 - glistoffsets[whichglider])
    parities.append(whichglider % 2)
    # Let's say it's okay to not have a target object at all,
    # in which case the cell list will process correctly all the way to ptr=0.
    # Otherwise, we need to check for the case where the target is something with less than 5 cells, like a block
    if ptr < 10:
      target = everything[:ptr]  # break out of the loop
    else:
      ptr -= 10
# for speed reasons we're reading the cell list from the end to the beginning,
#   so we'll have to report the final lists in reverse order
lanes.reverse()
parities.reverse()

# -----------------------------------------------------------------------------
# -----------------------------------------------------------------------------

g.show("Assembling output pattern...")
g.addlayer()
g.new("Recipe")



# -------------------------
# -------------------------
# Tunable parameters
target_offset = 512
glider_delta = 256
max_envelope_pos = 60
max_envelope_neg = -60
keep_best_n = 10
# -------------------------
# -------------------------



g.putcells(hf, -6, -6)
g.putcells(target, -target_offset, target_offset, 0, 1, -1, 0)

Recipe = namedtuple("Recipe", "cost lane offset recipe")
best_n = [Recipe(0, 0, 0, ())]

for lane, parity in zip(lanes, parities):
    new_best_n = []
    for fire in fire_data[parity]:
        target_hf_lane = (lane + fire.lane)//2
        for cur_recipe in best_n:
            lane_diff = target_hf_lane - cur_recipe.lane
            cur_hf_offset = cur_recipe.offset
            for move_cost, moves in move_data[lane_diff].items():
                for move in moves:
                    move_envelope_pos = cur_hf_offset + move.envelope_pos + fire.move.envelope_pos
                    move_envelope_neg = cur_hf_offset + move.envelope_neg + fire.move.envelope_neg
                    if move_envelope_pos > max_envelope_pos: continue
                    if move_envelope_neg < max_envelope_neg: continue
                    cur_cost = cur_recipe.cost + move_cost + fire.move.glider_num
                    cur_lane = cur_recipe.lane + move.lane_diff + fire.move.lane_diff
                    cur_offset = cur_hf_offset
                    recipe = cur_recipe.recipe
                    recipe = (move.gliders, cur_offset, recipe)
                    cur_offset += move.offset_diff
                    recipe = (fire.move.gliders, cur_offset, recipe)
                    cur_offset += fire.move.offset_diff
                    # I'm sorry for variable reusing. Naming is hard
                    recipe = Recipe(cost = cur_cost,
                                    lane = cur_lane,
                                    offset = cur_offset,
                                    recipe = recipe,
                                    )
                    new_best_n.append(recipe)
    # Sorting first by cost, then by distance from center
    best_n = sorted(new_best_n, key = lambda recipe: (recipe.cost, abs(recipe.offset)))[:keep_best_n]
    if not best_n:
        g.exit("Couldn't find solution: either provided envelope is too small or there was very big jump between gliders")

# Unfolding best recipe
recipe = []
cur = best_n[0].recipe
while cur:
    gliders, offset, prev = cur
    recipe.append((gliders, offset))
    cur = prev

cur_pos = glider_delta
for gliders, offset in recipe[::-1]:
    for glider in gliders:
        gl = gdict[{0: 'E', 1: 'O'}[glider.parity]]
        g.putcells(gl, cur_pos + (glider.lane-1)//2 + offset, cur_pos)
        cur_pos += glider_delta

g.show("Done")

It works by keeping (adjustable) N current-best recipes, and tries all possible combinations of glider-firing recipe (currently 2) and move recipe that places honeyfarm on necessary lane for each of these recipes. It also ensures that slow^1 glider lanes are keeped in certain range, and generally tries to keep the honeyfarm close to the initial slow^1 lane.

How to use:
First of all, hf_move_table.txt from the post above should be in the same folder as the script.
Adjust tunable parameters, if necessary (around line 150), make sure that current layers contains NW-directed gliders aimed at some target.
Run the script.
It reads the table for a few seconds, then analyzes slow salvo, then tries to compile slow^2 salvo. Results should appear in new "Recipe" layer.

For example, given this input:

Code: Select all

x = 8496, y = 8637, rule = B3/S23
92b2o$92b2o5$103bo$103bo$81b3o19bo12$84b3o7b3o2$82bo5bo$82bo5bo19b2o$
82bo5bo18bo2bo$108bobo$84b3o22bo3$109b2o$108bobo$109bo7$90bo$89bobo4b
2o17bo$89bo2bo3b2o17bo$90b2o23bo2$108bo$107bobo$107bobo$97b2o9bo$97b2o
$63bo$63bo23bo$63bo22bobo$86bobo21bo$87bo21bobo$76b2o30bo2bo$75bo2bo
30b2o$76b2o3$107b2o$107b2o$81bo20b2o$33bo47bo19bo2bo$33bo36b2o9bo20b2o
$33bo32bo2bo2bo13b2o$66bo3b2o14b2o7b2o$66bo28b2o2b2o$28b3o68b2o$75b3o
4b2o7b2o45b2o$82bobo6b2o45bobo$52b2o25bo3bo55b2o$51bo2bo24bo27bo$52b2o
12b2o6bo4bo27bo21b2o$49bo16b2o6bo32bo21b2o$48bobo23bo45b2o$27bo20bo2bo
51b3o3b3o8b2o$26bobo10bo9b2o$26bo2bo8bobo66bo$27b2o9bobo66bo$39bo67bo
3$44b2o$44b2o3$16b2o$16b2o21bo$38bobo$38bobo29bo$27b3o2b3o4bo29bobo58b
o$70b2o57bobo$36bo92bobo$36bo93bo$36bo$142b2o$142bobo$143b2o5$12bo$12b
o$12bo107b2o$119bo2bo16b2o$120b2o17b2o$34bo$34bo$34bo25b2o$40b2o9b2o6b
o2bo$8b2o29bo2bo7bo2bo6b2o$bo6b2o29bobo9bobo43b2o$obo37bo11bo44bobo$ob
o95b2o37b2o$bo135b2o3$79b2o$42b3o34b2o$170b3o$40bo5bo$40bo5bo40b2o$40b
o5bo40b2o$137bo20b2o$42b3o92bo19bo2bo$137bo19bobo6b2o$152b2o4bo6bo2bo$
133b3o3b3o10b2o12b2o22bo$189bobo$137bo52b2o$137bo12bo$137bo11bobo$149b
obo$150bo25bo$145b2o29bo$145b2o29bo$164b2o$164b2o5b2o$146b2o23b2o$146b
2o2$34b2o$25bo8b2o107b2o26bo$24bobo38b2o76b2o25bobo$24bobo3b3o32bobo
102bo2bo$25bo40b2o103b2o$28bo131b2o$28bo62b2o54b2o10bo2bo$28bo62b2o54b
2o11b2o$47b2o$47b2o94bo$142bobo$143b2o$55b2o92b3o$55b2o36b2o$93b2o$
157bo$144b2o10bobo$143bo2bo9bobo$144b2o11bo3$138b2o$121b2o15bobo$121bo
bo15bo$122bo8$121b2o11bo23b2o$94bo25bo2bo9bobo22b2o$93bobo8b2o15bobo9b
obo$93bobo8b2o16bo11bo$94bo$129b2o7b2o$128bo2bo5bo2bo$129b2o7b2o$148b
2o$134bo12bo2bo$133bobo12bobo$81b2o50bobo13bo$80bo2bo50bo$80bobo43b2o$
81bo44b2o$112b2o$111bo2bo$112b2o8$105bo$88b2o15bo$88b2o15bo2$115b2o$
115b2o2$41b2o24bo$40bo2bo23bo$41b2o24bo2$50b2o11b3o$25b2o7b2o14b2o$25b
2o7b2o24b2o$42bo17b2o28b2o$41bobo36b2o8b2o$33b2o6bo2bo35b2o17bo$33b2o
7b2o54bobo$98b2o$58b3o5$43bo$42bobo$42bobo$43bo7b3o$91b2o$49bo41b2o$
49bo9b2o$49bo8bo2bo$59b2o9$29b3o8$65b2o$64bo2bo$64bobo$65bo9$71b2o$70b
o2bo$71b2o24$75bo$74b2o$74bobo5$99bo$98b2o$98bobo5$116bo$115b2o$115bob
o5$145b3o$145bo$146bo20$163bo$162b2o$162bobo39$183b3o$183bo$184bo57$
230bo$229b2o$229bobo5$253bo$252b2o$252bobo5$298bo$297b2o$297bobo5$313b
o$312b2o$312bobo27$349bo$348b2o$348bobo5$345bo$344b2o$344bobo41$403bo$
402b2o$402bobo5$412bo$411b2o$411bobo5$422b3o$422bo$423bo19$445b3o$445b
o$446bo5$461bo$460b2o$460bobo5$473bo$472b2o$472bobo5$491bo$490b2o$490b
obo10$511bo$510b2o$510bobo5$521bo$520b2o$520bobo5$538bo$537b2o$537bobo
11$550bo$549b2o$549bobo5$586b3o$586bo$587bo23$605b3o$605bo$606bo44$
630bo$629b2o$629bobo16$657bo$656b2o$656bobo18$691bo$690b2o$690bobo5$
683bo$682b2o$682bobo5$705b3o$705bo$706bo5$721bo$720b2o$720bobo5$732bo$
731b2o$731bobo49$788b3o$788bo$789bo18$800b3o$800bo$801bo7$815b3o$815bo
$816bo5$838bo$837b2o$837bobo5$860bo$859b2o$859bobo44$889bo$888b2o$888b
obo5$905b3o$905bo$906bo34$921bo$920b2o$920bobo5$944b3o$944bo$945bo5$
972bo$971b2o$971bobo5$979bo$978b2o$978bobo63$1044bo$1043b2o$1043bobo5$
1055bo$1054b2o$1054bobo5$1061b3o$1061bo$1062bo5$1081bo$1080b2o$1080bob
o5$1110bo$1109b2o$1109bobo23$1120bo$1119b2o$1119bobo5$1140b3o$1140bo$
1141bo39$1172bo$1171b2o$1171bobo5$1182b3o$1182bo$1183bo30$1214b3o$
1214bo$1215bo52$1266bo$1265b2o$1265bobo23$1295bo$1294b2o$1294bobo5$
1314bo$1313b2o$1313bobo5$1342bo$1341b2o$1341bobo30$1370bo$1369b2o$
1369bobo31$1394bo$1393b2o$1393bobo5$1400b3o$1400bo$1401bo70$1477b3o$
1477bo$1478bo5$1498b3o$1498bo$1499bo5$1470bo$1469b2o$1469bobo5$1487bo$
1486b2o$1486bobo5$1485bo$1484b2o$1484bobo5$1496bo$1495b2o$1495bobo17$
1511b3o$1511bo$1512bo7$1525b3o$1525bo$1526bo20$1552bo$1551b2o$1551bobo
19$1544b3o$1544bo$1545bo8$1552bo$1551b2o$1551bobo5$1560bo$1559b2o$
1559bobo5$1577bo$1576b2o$1576bobo46$1597b3o$1597bo$1598bo8$1610b3o$
1610bo$1611bo9$1621b3o$1621bo$1622bo5$1640bo$1639b2o$1639bobo5$1650bo$
1649b2o$1649bobo5$1629b3o$1629bo$1630bo5$1646bo$1645b2o$1645bobo5$
1653b3o$1653bo$1654bo5$1665b3o$1665bo$1666bo5$1681bo$1680b2o$1680bobo
21$1708bo$1707b2o$1707bobo6$1721b3o$1721bo$1722bo33$1773b3o$1773bo$
1774bo34$1807b3o$1807bo$1808bo5$1835bo$1834b2o$1834bobo5$1835bo$1834b
2o$1834bobo11$1845bo$1844b2o$1844bobo10$1854bo$1853b2o$1853bobo5$1879b
o$1878b2o$1878bobo7$1872bo$1871b2o$1871bobo6$1893b3o$1893bo$1894bo5$
1910bo$1909b2o$1909bobo23$1951b3o$1951bo$1952bo5$1957bo$1956b2o$1956bo
bo5$1973bo$1972b2o$1972bobo6$1988bo$1987b2o$1987bobo8$1983bo$1982b2o$
1982bobo11$2019bo$2018b2o$2018bobo5$2021bo$2020b2o$2020bobo9$2032bo$
2031b2o$2031bobo10$2037b3o$2037bo$2038bo5$2052b3o$2052bo$2053bo6$2052b
3o$2052bo$2053bo44$2087bo$2086b2o$2086bobo21$2099b3o$2099bo$2100bo12$
2144bo$2143b2o$2143bobo10$2151bo$2150b2o$2150bobo5$2169bo$2168b2o$
2168bobo22$2181bo$2180b2o$2180bobo11$2191bo$2190b2o$2190bobo8$2203b3o$
2203bo$2204bo35$2244b3o$2244bo$2245bo11$2253b3o$2253bo$2254bo5$2268b3o
$2268bo$2269bo12$2279b3o$2279bo$2280bo5$2280bo$2279b2o$2279bobo5$2274b
o$2273b2o$2273bobo5$2285b3o$2285bo$2286bo5$2301bo$2300b2o$2300bobo5$
2316bo$2315b2o$2315bobo5$2347b3o$2347bo$2348bo8$2360b3o$2360bo$2361bo
5$2376bo$2375b2o$2375bobo36$2422bo$2421b2o$2421bobo5$2446b3o$2446bo$
2447bo8$2459b3o$2459bo$2460bo5$2475bo$2474b2o$2474bobo36$2521bo$2520b
2o$2520bobo5$2511bo$2510b2o$2510bobo5$2481bo$2480b2o$2480bobo5$2406b3o
$2406bo$2407bo5$2411bo$2410b2o$2410bobo5$2419bo$2418b2o$2418bobo13$
2426bo$2425b2o$2425bobo5$2441bo$2440b2o$2440bobo34$2485b3o$2485bo$
2486bo5$2501b3o$2501bo$2502bo5$2512b3o$2512bo$2513bo32$2529b3o$2529bo$
2530bo9$2540bo$2539b2o$2539bobo15$2561b3o$2561bo$2562bo11$2571b3o$
2571bo$2572bo5$2583b3o$2583bo$2584bo6$2586b3o$2586bo$2587bo5$2593b3o$
2593bo$2594bo5$2595bo$2594b2o$2594bobo5$2612bo$2611b2o$2611bobo5$2619b
o$2618b2o$2618bobo11$2629bo$2628b2o$2628bobo8$2631bo$2630b2o$2630bobo
5$2677bo$2676b2o$2676bobo5$2691bo$2690b2o$2690bobo5$2708bo$2707b2o$
2707bobo10$2719bo$2718b2o$2718bobo11$2747bo$2746b2o$2746bobo5$2753bo$
2752b2o$2752bobo10$2755bo$2754b2o$2754bobo5$2765bo$2764b2o$2764bobo5$
2779b3o$2779bo$2780bo8$2792b3o$2792bo$2793bo5$2807b3o$2807bo$2808bo6$
2799b3o$2799bo$2800bo10$2811b3o$2811bo$2812bo5$2823bo$2822b2o$2822bobo
5$2847bo$2846b2o$2846bobo22$2863bo$2862b2o$2862bobo5$2833b3o$2833bo$
2834bo9$2844b3o$2844bo$2845bo16$2868b3o$2868bo$2869bo5$2884bo$2883b2o$
2883bobo13$2897bo$2896b2o$2896bobo5$2895bo$2894b2o$2894bobo9$2923bo$
2922b2o$2922bobo5$2937b3o$2937bo$2938bo11$2946b3o$2946bo$2947bo5$2961b
3o$2961bo$2962bo12$2972b3o$2972bo$2973bo5$2973bo$2972b2o$2972bobo5$
2971b3o$2971bo$2972bo5$2987bo$2986b2o$2986bobo5$3002bo$3001b2o$3001bob
o5$2964bo$2963b2o$2963bobo9$2976bo$2975b2o$2975bobo7$2988b3o$2988bo$
2989bo8$3000bo$2999b2o$2999bobo10$3019b3o$3019bo$3020bo13$3027b3o$
3027bo$3028bo5$3041b3o$3041bo$3042bo22$3073b3o$3073bo$3074bo5$3053bo$
3052b2o$3052bobo10$3060bo$3059b2o$3059bobo9$3072bo$3071b2o$3071bobo7$
3084b3o$3084bo$3085bo7$3096b3o$3096bo$3097bo22$3134bo$3133b2o$3133bobo
18$3150bo$3149b2o$3149bobo5$3134bo$3133b2o$3133bobo5$3145bo$3144b2o$
3144bobo8$3158bo$3157b2o$3157bobo5$3171b3o$3171bo$3172bo5$3177b3o$
3177bo$3178bo5$3073b3o$3073bo$3074bo5$3080bo$3079b2o$3079bobo5$3098bo$
3097b2o$3097bobo22$3112bo$3111b2o$3111bobo5$3095bo$3094b2o$3094bobo8$
3108bo$3107b2o$3107bobo7$3110bo$3109b2o$3109bobo9$3122bo$3121b2o$3121b
obo22$3143bo$3142b2o$3142bobo53$3190bo$3189b2o$3189bobo5$3185bo$3184b
2o$3184bobo8$3198bo$3197b2o$3197bobo7$3200bo$3199b2o$3199bobo9$3212bo$
3211b2o$3211bobo22$3233bo$3232b2o$3232bobo53$3280bo$3279b2o$3279bobo5$
3275bo$3274b2o$3274bobo13$3281bo$3280b2o$3280bobo5$3293bo$3292b2o$
3292bobo9$3301bo$3300b2o$3300bobo10$3307bo$3306b2o$3306bobo5$3337bo$
3336b2o$3336bobo17$3340bo$3339b2o$3339bobo5$3356bo$3355b2o$3355bobo5$
3363bo$3362b2o$3362bobo5$3370bo$3369b2o$3369bobo5$3374bo$3373b2o$3373b
obo6$3380b3o$3380bo$3381bo10$3402bo$3401b2o$3401bobo5$3406b3o$3406bo$
3407bo7$3417b3o$3417bo$3418bo8$3430b3o$3430bo$3431bo8$3428b3o$3428bo$
3429bo5$3440bo$3439b2o$3439bobo5$3439bo$3438b2o$3438bobo5$3464b3o$
3464bo$3465bo10$3484b3o$3484bo$3485bo5$3499b3o$3499bo$3500bo5$3515b3o$
3515bo$3516bo8$3508b3o$3508bo$3509bo5$3528b3o$3528bo$3529bo12$3543b3o$
3543bo$3544bo5$3555bo$3554b2o$3554bobo10$3575bo$3574b2o$3574bobo5$
3588b3o$3588bo$3589bo11$3597b3o$3597bo$3598bo5$3612b3o$3612bo$3613bo
12$3620bo$3619b2o$3619bobo5$3628bo$3627b2o$3627bobo8$3633bo$3632b2o$
3632bobo50$3689bo$3688b2o$3688bobo7$3687b3o$3687bo$3688bo9$3699b3o$
3699bo$3700bo14$3719bo$3718b2o$3718bobo5$3725bo$3724b2o$3724bobo5$
3742b3o$3742bo$3743bo5$3768b3o$3768bo$3769bo7$3781b3o$3781bo$3782bo12$
3788b3o$3788bo$3789bo29$3819b3o$3819bo$3820bo5$3849bo$3848b2o$3848bobo
5$3856bo$3855b2o$3855bobo7$3871bo$3870b2o$3870bobo5$3876b3o$3876bo$
3877bo11$3886b3o$3886bo$3887bo12$3895bo$3894b2o$3894bobo37$3934bo$
3933b2o$3933bobo5$3933bo$3932b2o$3932bobo16$3942bo$3941b2o$3941bobo5$
3927bo$3926b2o$3926bobo5$3909bo$3908b2o$3908bobo29$3924b3o$3924bo$
3925bo5$3969bo$3968b2o$3968bobo5$3975bo$3974b2o$3974bobo5$3974bo$3973b
2o$3973bobo11$3984bo$3983b2o$3983bobo5$4017b3o$4017bo$4018bo9$4029b3o$
4029bo$4030bo14$4049bo$4048b2o$4048bobo5$4055bo$4054b2o$4054bobo5$
4072b3o$4072bo$4073bo5$4105bo$4104b2o$4104bobo19$4143bo$4142b2o$4142bo
bo11$4153bo$4152b2o$4152bobo10$4163b3o$4163bo$4164bo5$4187bo$4186b2o$
4186bobo5$4204bo$4203b2o$4203bobo46$4224bo$4223b2o$4223bobo35$4255b3o$
4255bo$4256bo13$4267b3o$4267bo$4268bo5$4302bo$4301b2o$4301bobo82$4350b
o$4349b2o$4349bobo8$4363bo$4362b2o$4362bobo7$4376bo$4375b2o$4375bobo
14$4381bo$4380b2o$4380bobo5$4414bo$4413b2o$4413bobo10$4422bo$4421b2o$
4421bobo5$4409bo$4408b2o$4408bobo36$4431bo$4430b2o$4430bobo5$4436b3o$
4436bo$4437bo11$4446b3o$4446bo$4447bo5$4458b3o$4458bo$4459bo6$4461b3o$
4461bo$4462bo5$4468b3o$4468bo$4469bo5$4449bo$4448b2o$4448bobo5$4437bo$
4436b2o$4436bobo5$4435bo$4434b2o$4434bobo11$4445bo$4444b2o$4444bobo8$
4447bo$4446b2o$4446bobo5$4477b3o$4477bo$4478bo5$4521bo$4520b2o$4520bob
o5$4538bo$4537b2o$4537bobo5$4545bo$4544b2o$4544bobo11$4555bo$4554b2o$
4554bobo8$4557bo$4556b2o$4556bobo5$4646bo$4645b2o$4645bobo11$4656bo$
4655b2o$4655bobo13$4663bo$4662b2o$4662bobo5$4667b3o$4667bo$4668bo5$
4678b3o$4678bo$4679bo5$4698bo$4697b2o$4697bobo7$4712b3o$4712bo$4713bo
52$4727bo$4726b2o$4726bobo5$4769b3o$4769bo$4770bo5$4771bo$4770b2o$
4770bobo5$4776b3o$4776bo$4777bo11$4786b3o$4786bo$4787bo12$4792bo$4791b
2o$4791bobo5$4805b3o$4805bo$4806bo5$4824bo$4823b2o$4823bobo22$4849bo$
4848b2o$4848bobo5$4868b3o$4868bo$4869bo11$4879b3o$4879bo$4880bo5$4887b
3o$4887bo$4888bo5$4905b3o$4905bo$4906bo5$4907bo$4906b2o$4906bobo5$
4878bo$4877b2o$4877bobo5$4883b3o$4883bo$4884bo13$4889b3o$4889bo$4890bo
5$4903b3o$4903bo$4904bo5$4907b3o$4907bo$4908bo17$4924b3o$4924bo$4925bo
5$4924b3o$4924bo$4925bo6$4930b3o$4930bo$4931bo6$4941bo$4940b2o$4940bob
o11$4950bo$4949b2o$4949bobo11$4959bo$4958b2o$4958bobo5$4977bo$4976b2o$
4976bobo21$5008bo$5007b2o$5007bobo5$5014bo$5013b2o$5013bobo10$5025bo$
5024b2o$5024bobo18$5046bo$5045b2o$5045bobo5$5063bo$5062b2o$5062bobo23$
5078bo$5077b2o$5077bobo5$5073b3o$5073bo$5074bo5$5086bo$5085b2o$5085bob
o5$5122bo$5121b2o$5121bobo5$5127b3o$5127bo$5128bo7$5140b3o$5140bo$
5141bo10$5150b3o$5150bo$5151bo5$5174bo$5173b2o$5173bobo5$5179b3o$5179b
o$5180bo5$5193b3o$5193bo$5194bo10$5203b3o$5203bo$5204bo5$5189bo$5188b
2o$5188bobo29$5194bo$5193b2o$5193bobo5$5209bo$5208b2o$5208bobo5$5210bo
$5209b2o$5209bobo5$5225bo$5224b2o$5224bobo5$5228bo$5227b2o$5227bobo13$
5238bo$5237b2o$5237bobo5$5259b3o$5259bo$5260bo13$5265b3o$5265bo$5266bo
5$5274bo$5273b2o$5273bobo13$5282bo$5281b2o$5281bobo91$5341bo$5340b2o$
5340bobo5$5342bo$5341b2o$5341bobo12$5351bo$5350b2o$5350bobo24$5376bo$
5375b2o$5375bobo7$5370b3o$5370bo$5371bo5$5389bo$5388b2o$5388bobo13$
5396bo$5395b2o$5395bobo5$5416bo$5415b2o$5415bobo35$5446bo$5445b2o$
5445bobo17$5452bo$5451b2o$5451bobo5$5510bo$5509b2o$5509bobo5$5504b3o$
5504bo$5505bo5$5519bo$5518b2o$5518bobo36$5541bo$5540b2o$5540bobo5$
5640bo$5639b2o$5639bobo5$5652b3o$5652bo$5653bo5$5668b3o$5668bo$5669bo
5$5670b3o$5670bo$5671bo14$5681b3o$5681bo$5682bo30$5728bo$5727b2o$5727b
obo5$5735b3o$5735bo$5736bo7$5748b3o$5748bo$5749bo22$5776bo$5775b2o$
5775bobo5$5784bo$5783b2o$5783bobo5$5790bo$5789b2o$5789bobo10$5801bo$
5800b2o$5800bobo18$5815b3o$5815bo$5816bo5$5838b3o$5838bo$5839bo16$
5856bo$5855b2o$5855bobo5$5904bo$5903b2o$5903bobo11$5914bo$5913b2o$
5913bobo5$5932bo$5931b2o$5931bobo53$5988b3o$5988bo$5989bo6$6004b3o$
6004bo$6005bo5$6010b3o$6010bo$6011bo6$6016bo$6015b2o$6015bobo5$6038b3o
$6038bo$6039bo5$6035b3o$6035bo$6036bo11$6065b3o$6065bo$6066bo8$6078b3o
$6078bo$6079bo9$6089b3o$6089bo$6090bo5$6104bo$6103b2o$6103bobo5$6111bo
$6110b2o$6110bobo18$6117bo$6116b2o$6116bobo19$6124b3o$6124bo$6125bo8$
6144bo$6143b2o$6143bobo7$6142b3o$6142bo$6143bo8$6155b3o$6155bo$6156bo
6$6158b3o$6158bo$6159bo5$6172b3o$6172bo$6173bo5$6168b3o$6168bo$6169bo
11$6187bo$6186b2o$6186bobo5$6184bo$6183b2o$6183bobo5$6190bo$6189b2o$
6189bobo8$6203bo$6202b2o$6202bobo13$6209b3o$6209bo$6210bo16$6220bo$
6219b2o$6219bobo12$6239bo$6238b2o$6238bobo39$6288bo$6287b2o$6287bobo9$
6311bo$6310b2o$6310bobo11$6321bo$6320b2o$6320bobo8$6323bo$6322b2o$
6322bobo5$6397b3o$6397bo$6398bo5$6403b3o$6403bo$6404bo5$6410bo$6409b2o
$6409bobo5$6427bo$6426b2o$6426bobo5$6425bo$6424b2o$6424bobo5$6430bo$
6429b2o$6429bobo5$6449bo$6448b2o$6448bobo5$6447b3o$6447bo$6448bo11$
6457b3o$6457bo$6458bo5$6475b3o$6475bo$6476bo57$6528bo$6527b2o$6527bobo
5$6575bo$6574b2o$6574bobo5$6554bo$6553b2o$6553bobo33$6592bo$6591b2o$
6591bobo5$6600b3o$6600bo$6601bo10$6607b3o$6607bo$6608bo11$6617b3o$
6617bo$6618bo5$6632b3o$6632bo$6633bo5$6643b3o$6643bo$6644bo50$6678bo$
6677b2o$6677bobo38$6713b3o$6713bo$6714bo5$6719b3o$6719bo$6720bo61$
6767b3o$6767bo$6768bo9$6764bo$6763b2o$6763bobo5$6773b3o$6773bo$6774bo
13$6779b3o$6779bo$6780bo5$6791b3o$6791bo$6792bo9$6807b3o$6807bo$6808bo
39$6843bo$6842b2o$6842bobo5$6850bo$6849b2o$6849bobo8$6850bo$6849b2o$
6849bobo5$6866bo$6865b2o$6865bobo13$6873bo$6872b2o$6872bobo5$6887bo$
6886b2o$6886bobo22$6919bo$6918b2o$6918bobo5$6941bo$6940b2o$6940bobo5$
6967bo$6966b2o$6966bobo5$6962bo$6961b2o$6961bobo5$6957bo$6956b2o$6956b
obo5$6972bo$6971b2o$6971bobo5$6963b3o$6963bo$6964bo5$6977bo$6976b2o$
6976bobo5$6984bo$6983b2o$6983bobo11$6994bo$6993b2o$6993bobo8$6996bo$
6995b2o$6995bobo5$6981b3o$6981bo$6982bo5$6989bo$6988b2o$6988bobo15$
7005bo$7004b2o$7004bobo7$7013b3o$7013bo$7014bo9$7024b3o$7024bo$7025bo
24$7040bo$7039b2o$7039bobo5$7057b3o$7057bo$7058bo5$7065bo$7064b2o$
7064bobo5$7063bo$7062b2o$7062bobo7$7063bo$7062b2o$7062bobo5$7080bo$
7079b2o$7079bobo5$7080bo$7079b2o$7079bobo11$7078b3o$7078bo$7079bo6$
7083bo$7082b2o$7082bobo5$7090bo$7089b2o$7089bobo5$7106bo$7105b2o$7105b
obo11$7116bo$7115b2o$7115bobo5$7135bo$7134b2o$7134bobo5$7131bo$7130b2o
$7130bobo5$7153bo$7152b2o$7152bobo5$7163bo$7162b2o$7162bobo7$7163bo$
7162b2o$7162bobo11$7173bo$7172b2o$7172bobo10$7182bo$7181b2o$7181bobo5$
7207bo$7206b2o$7206bobo6$7221bo$7220b2o$7220bobo29$7234b3o$7234bo$
7235bo12$7231bo$7230b2o$7230bobo7$7241bo$7240b2o$7240bobo5$7241bo$
7240b2o$7240bobo8$7254bo$7253b2o$7253bobo5$7269bo$7268b2o$7268bobo5$
7248b3o$7248bo$7249bo5$7252bo$7251b2o$7251bobo29$7264bo$7263b2o$7263bo
bo8$7277bo$7276b2o$7276bobo5$7292bo$7291b2o$7291bobo5$7322bo$7321b2o$
7321bobo11$7332bo$7331b2o$7331bobo8$7334bo$7333b2o$7333bobo5$7293b3o$
7293bo$7294bo6$7307bo$7306b2o$7306bobo5$7289bo$7288b2o$7288bobo11$
7299bo$7298b2o$7298bobo9$7310bo$7309b2o$7309bobo5$7330b3o$7330bo$7331b
o10$7341b3o$7341bo$7342bo14$7367bo$7366b2o$7366bobo5$7374bo$7373b2o$
7373bobo5$7382bo$7381b2o$7381bobo12$7389bo$7388b2o$7388bobo5$7401b3o$
7401bo$7402bo7$7422bo$7421b2o$7421bobo5$7438bo$7437b2o$7437bobo11$
7448bo$7447b2o$7447bobo8$7450bo$7449b2o$7449bobo5$7416bo$7415b2o$7415b
obo11$7428bo$7427b2o$7427bobo9$7431b3o$7431bo$7432bo6$7437b3o$7437bo$
7438bo6$7448bo$7447b2o$7447bobo13$7455bo$7454b2o$7454bobo5$7462bo$
7461b2o$7461bobo5$7486bo$7485b2o$7485bobo5$7494bo$7493b2o$7493bobo5$
7490b3o$7490bo$7491bo10$7501b3o$7501bo$7502bo8$7504bo$7503b2o$7503bobo
5$7536bo$7535b2o$7535bobo5$7544b3o$7544bo$7545bo21$7574bo$7573b2o$
7573bobo5$7585bo$7584b2o$7584bobo5$7553bo$7552b2o$7552bobo5$7563bo$
7562b2o$7562bobo5$7570bo$7569b2o$7569bobo8$7583bo$7582b2o$7582bobo5$
7600bo$7599b2o$7599bobo27$7627bo$7626b2o$7626bobo5$7618bo$7617b2o$
7617bobo7$7633bo$7632b2o$7632bobo22$7647bo$7646b2o$7646bobo5$7630bo$
7629b2o$7629bobo8$7643bo$7642b2o$7642bobo5$7658bo$7657b2o$7657bobo5$
7614bo$7613b2o$7613bobo11$7624bo$7623b2o$7623bobo8$7627bo$7626b2o$
7626bobo5$7633bo$7632b2o$7632bobo5$7660bo$7659b2o$7659bobo5$7666bo$
7665b2o$7665bobo5$7672bo$7671b2o$7671bobo5$7685bo$7684b2o$7684bobo7$
7711bo$7710b2o$7710bobo5$7718bo$7717b2o$7717bobo7$7732bo$7731b2o$7731b
obo19$7756bo$7755b2o$7755bobo12$7758bo$7757b2o$7757bobo5$7757b3o$7757b
o$7758bo5$7781bo$7780b2o$7780bobo11$7791bo$7790b2o$7790bobo23$7808bo$
7807b2o$7807bobo5$7769bo$7768b2o$7768bobo6$7767b3o$7767bo$7768bo9$
7779b3o$7779bo$7780bo16$7800bo$7799b2o$7799bobo5$7798bo$7797b2o$7797bo
bo5$7798bo$7797b2o$7797bobo5$7800b3o$7800bo$7801bo18$7847b3o$7847bo$
7848bo17$7871b3o$7871bo$7872bo5$7906bo$7905b2o$7905bobo11$7916bo$7915b
2o$7915bobo8$7918bo$7917b2o$7917bobo23$7907b3o$7907bo$7908bo8$7920b3o$
7920bo$7921bo5$7939bo$7938b2o$7938bobo6$7929bo$7928b2o$7928bobo11$
7938b3o$7938bo$7939bo5$7968b3o$7968bo$7969bo12$7970b3o$7970bo$7971bo
22$7982b3o$7982bo$7983bo11$7992b3o$7992bo$7993bo8$8004b3o$8004bo$8005b
o9$8018b3o$8018bo$8019bo5$8002bo$8001b2o$8001bobo39$8052bo$8051b2o$
8051bobo14$8058bo$8057b2o$8057bobo5$8070bo$8069b2o$8069bobo9$8078bo$
8077b2o$8077bobo10$8084bo$8083b2o$8083bobo5$8113bo$8112b2o$8112bobo9$
8116bo$8115b2o$8115bobo26$8135b3o$8135bo$8136bo10$8146b3o$8146bo$8147b
o12$8174b3o$8174bo$8175bo5$8179b3o$8179bo$8180bo5$8183bo$8182b2o$8182b
obo5$8224bo$8223b2o$8223bobo8$8237bo$8236b2o$8236bobo5$8252bo$8251b2o$
8251bobo5$8233b3o$8233bo$8234bo5$8240bo$8239b2o$8239bobo9$8252bo$8251b
2o$8251bobo15$8271bo$8270b2o$8270bobo5$8273b3o$8273bo$8274bo5$8278bo$
8277b2o$8277bobo5$8278b3o$8278bo$8279bo5$8297bo$8296b2o$8296bobo5$
8314bo$8313b2o$8313bobo5$8320bo$8319b2o$8319bobo13$8327bo$8326b2o$
8326bobo5$8332bo$8331b2o$8331bobo5$8350bo$8349b2o$8349bobo13$8355bo$
8354b2o$8354bobo5$8357bo$8356b2o$8356bobo5$8357bo$8356b2o$8356bobo9$
8369bo$8368b2o$8368bobo18$8388b3o$8388bo$8389bo6$8383b3o$8383bo$8384bo
5$8395b3o$8395bo$8396bo18$8406bo$8405b2o$8405bobo5$8422b3o$8422bo$
8423bo5$8418bo$8417b2o$8417bobo35$8445bo$8444b2o$8444bobo6$8460bo$
8459b2o$8459bobo5$8455bo$8454b2o$8454bobo5$8470bo$8469b2o$8469bobo5$
8461b3o$8461bo$8462bo5$8475bo$8474b2o$8474bobo5$8482bo$8481b2o$8481bob
o11$8492bo$8491b2o$8491bobo8$8494bo$8493b2o$8493bobo!
#C [[ MAXGRIDSIZE 14 ]]

... it produces the following output:

Code: Select all

x = 1508353, y = 1507849, rule = B3/S23
512bo$511bobo$511bobo$512bo2$507b2o7b2o$506bo2bo5bo2bo$507b2o7b2o2$
512bo$511bobo$511bobo$512bo250$764b3o$764bo$765bo63$128b2o$127bobo$
128bo13$133b3o3$144bo$119bo17b2o4bobo$119bo17b2o3bo2bo$119bo23b2o2$
126bo$125bobo$125bobo$126bo9b2o$136b2o2$147bo$146bobo$124bo21bobo$123b
obo21bo25b2o$123bo2bo30b2o14b2o$124b2o30bo2bo$157b2o3$126b2o$126b2o$
131b2o20bo$130bo2bo19bo28b2o$131b2o20bo27bo2bo$147b2o32bobo$138b2o7b2o
33bo$134b2o2b2o18bo$134b2o21bobo$95b2o45b2o7b2o4bobo$94bobo45b2o6bobo
5bo$94b2o55bo$127bo$68b2o34b2o21bo35bo15bo$67bobo34b2o21bo34bobo13bobo
$67b2o44b2o47b2o14bobo$113b2o8b3o3b3o47bo2$127bo46b2o7b2o$127bo45bo2bo
5bo2bo$127bo46b2o7b2o2$90b2o87bo$71b2o16bo2bo85bobo$71b2o17b2o86bobo$
179bo$186b2o$186b2o3$164bo9b2o$104bo58bobo7bo2bo$73b2o28bobo57b2o8bobo
$73b2o28bobo68bo$104bo3$202b2o$39b3o160b2o$189bo$188bobo$188bobo$52b2o
20bo114bo$24b2o3b2o20bo2bo19bo$23bo2bo2bobo12b2o6bobo19bo$23bobo4bo12b
o2bo6bo4b2o$24bo19b2o12b2o10b3o3b3o2$74bo100b2o21b3o$61bo12bo100b2o$6b
3o51bobo11bo$60bobo$61bo$65b2o148bo$65b2o45b2o100bobo$46b2o63bobo101b
2o$39b2o5b2o63b2o$20bo18b2o23b2o$20bo43b2o109b2o$20bo133b2o18bo2bo$2o
152b2o19b2o$2o38bo26b2o78b2o77b2o$39bobo25b2o78b2o63b2o12b2o$38bo2bo
170b2o$39b2o158b2o$22b3o25b2o69b2o76b2o$49bo2bo10b2o56b2o$20bo5bo23b2o
11b2o$20bo5bo$20bo5bo41bo$8bo58bobo115bo$8bo13b3o42b2o115bobo$8bo51b3o
121bo2bo25b2o$117b2o66b2o26b2o$69b3o45b2o$54bo$53bobo11bo$53bobo11bo$
54bo12bo$71b3o$260bo$63bo195bobo$62bobo24b2o168bobo$62bobo23bobo169bo$
63bo25bo2$71b2o71b2o59b3o40bo$63b3o5b2o70bobo101bobo$143b2o64bo37bo2bo
$209bo38b2o$48b3o158bo$109bo$108bobo100b2o16bo$108bobo100b2o4bo10bobo$
109bo107bo10bobo$217bo11bo2$153b2o$153b2o$70bo$69bobo38b2o113bo$69bobo
37bo2bo112bo$70bo3bo34bobo97b2o14bo$73bobo34bo98b2o$72bo2bo151b3o$73b
2o74b2o$149b2o$120b3o$81b2o$81b2o35bo5bo89bo8b2o$118bo5bo81bo6bobo6bo
2bo$110bo7bo5bo80bobo4bo2bo7b2o$109bobo93bobo5b2o$76b2o9b2o20bo2bo7b3o
83bo$75bo2bo7bo2bo20b2o$76b2o9b2o2$91b3o$141b2o67b2o$89bo16b3o32b2o67b
2o2b2o$61b3o25bo124b2o$89bo54bo$144bo94bo$66bo77bo94bo$66bo9bo12bo149b
o$66bo8bobo11bo56b3o$74bo2bo11bo$75b2o66b2o65b2o$142bo2bo64b2o$143b2o
7$85b2o$85b2o4$101b3o3$110b2o$110b2o6$112b2o$111bo2bo$112b2o899b2o$
1012b2o$1014bo254$1262b3o$1262bo$1263bo254$1533b3o$1533bo$1534bo254$
1781b3o$1781bo$1782bo254$2048b3o$2048bo$2049bo254$2307b3o$2307bo$2308b
o254$2558b2o$2557b2o$2559bo254$2807b3o$2807bo$2808bo254$3067b3o$3067bo
$3068bo254$3328b2o$3327b2o$3329bo254$3567b3o$3567bo$3568bo254$3823b3o$
3823bo$3824bo254$4073b3o$4073bo$4074bo254$4352b2o$4351b2o$4353bo254$
4599b2o$4598b2o$4600bo254$4872b3o$4872bo$4873bo254$5120b3o$5120bo$
5121bo254$5379b3o$5379bo$5380bo254$5623b3o$5623bo$5624bo254$5872b3o$
5872bo$5873bo254$6137b3o$6137bo$6138bo254$6388b3o$6388bo$6389bo254$
6652b3o$6652bo$6653bo254$6912b3o$6912bo$6913bo254$7163b3o$7163bo$7164b
o254$7411b3o$7411bo$7412bo254$7679b2o$7678b2o$7680bo254$7932b3o$7932bo
$7933bo254$8186b3o$8186bo$8187bo254$8435b3o$8435bo$8436bo254$8700b3o$
8700bo$8701bo254$8951b3o$8951bo$8952bo254$9215b3o$9215bo$9216bo254$
9475b3o$9475bo$9476bo254$9731b3o$9731bo$9732bo254$9999b2o$9998b2o$
10000bo254$10233b3o$10233bo$10234bo254$10488b3o$10488bo$10489bo254$
10737b3o$10737bo$10738bo254$11002b3o$11002bo$11003bo254$11253b3o$
11253bo$11254bo254$11517b3o$11517bo$11518bo254$11777b3o$11777bo$11778b
o254$12033b3o$12033bo$12034bo254$12295b2o$12294b2o$12296bo254$12553b3o
$12553bo$12554bo254$12808b3o$12808bo$12809bo254$13049b2o$13048b2o$
13050bo254$13305b3o$13305bo$13306bo254$13553b3o$13553bo$13554bo254$
13819b2o$13818b2o$13820bo254$14069b3o$14069bo$14070bo254$14333b3o$
14333bo$14334bo254$14600b3o$14600bo$14601bo254$14852b3o$14852bo$14853b
o254$15095b3o$15095bo$15096bo254$15352b3o$15352bo$15353bo254$15601b3o$
15601bo$15602bo254$15866b3o$15866bo$15867bo254$16117b3o$16117bo$16118b
o254$16381b3o$16381bo$16382bo254$16639b3o$16639bo$16640bo254$16900b2o$
16899b2o$16901bo254$17164b2o$17163b2o$17165bo254$17398b2o$17397b2o$
17399bo254$17650b2o$17649b2o$17651bo254$17914b3o$17914bo$17915bo254$
18162b3o$18162bo$18163bo254$18428b2o$18427b2o$18429bo254$18678b3o$
18678bo$18679bo254$18942b3o$18942bo$18943bo254$19203b3o$19203bo$19204b
o254$19444b2o$19443b2o$19445bo254$19713b2o$19712b2o$19714bo254$19964b
3o$19964bo$19965bo254$20212b3o$20212bo$20213bo254$20477b3o$20477bo$
20478bo254$20728b3o$20728bo$20729bo254$20992b3o$20992bo$20993bo254$
21252b3o$21252bo$21253bo254$21508b3o$21508bo$21509bo254$21761b3o$
21761bo$21762bo254$22014b2o$22013b2o$22015bo254$22275b2o$22274b2o$
22276bo254$22522b3o$22522bo$22523bo254$22770b3o$22770bo$22771bo254$
23035b3o$23035bo$23036bo254$23286b3o$23286bo$23287bo254$23550b3o$
23550bo$23551bo254$23810b3o$23810bo$23811bo254$24059b3o$24059bo$24060b
o254$24316b3o$24316bo$24317bo254$24569b3o$24569bo$24570bo254$24817b3o$
24817bo$24818bo254$25070b3o$25070bo$25071bo254$25318b3o$25318bo$25319b
o254$25583b3o$25583bo$25584bo254$25834b3o$25834bo$25835bo254$26098b3o$
26098bo$26099bo254$26358b3o$26358bo$26359bo254$26611b3o$26611bo$26612b
o254$26872b3o$26872bo$26873bo254$27130b3o$27130bo$27131bo254$27385b3o$
27385bo$27386bo254$27634b3o$27634bo$27635bo254$27899b3o$27899bo$27900b
o254$28150b3o$28150bo$28151bo254$28414b3o$28414bo$28415bo254$28674b3o$
28674bo$28675bo254$28930b3o$28930bo$28931bo254$29187b2o$29186b2o$
29188bo254$29453b2o$29452b2o$29454bo254$29688b3o$29688bo$29689bo254$
29937b3o$29937bo$29938bo254$30202b3o$30202bo$30203bo254$30453b3o$
30453bo$30454bo254$30717b3o$30717bo$30718bo254$30978b3o$30978bo$30979b
o254$31232b2o$31231b2o$31233bo254$31484b3o$31484bo$31485bo254$31732b3o
$31732bo$31733bo254$31997b3o$31997bo$31998bo254$32248b3o$32248bo$
32249bo254$32512b3o$32512bo$32513bo254$32779b3o$32779bo$32780bo254$
33028b3o$33028bo$33029bo254$33271b3o$33271bo$33272bo254$33526b3o$
33526bo$33527bo254$33778b3o$33778bo$33779bo254$34043b3o$34043bo$34044b
o254$34291b3o$34291bo$34292bo254$34556b3o$34556bo$34557bo254$34807b3o$
34807bo$34808bo254$35071b3o$35071bo$35072bo254$35331b3o$35331bo$35332b
o254$35585b3o$35585bo$35586bo254$35839b2o$35838b2o$35840bo254$36092b3o
$36092bo$36093bo254$36346b3o$36346bo$36347bo254$36595b3o$36595bo$
36596bo254$36860b3o$36860bo$36861bo254$37111b3o$37111bo$37112bo254$
37375b3o$37375bo$37376bo254$37623b3o$37623bo$37624bo254$37886b3o$
37886bo$37887bo254$38140b2o$38139b2o$38141bo254$38412b3o$38412bo$
38413bo254$38649b3o$38649bo$38650bo254$38898b3o$38898bo$38899bo254$
39164b2o$39163b2o$39165bo254$39414b3o$39414bo$39415bo254$39678b3o$
39678bo$39679bo254$39938b3o$39938bo$39939bo254$40192b3o$40192bo$40193b
o254$40446b2o$40445b2o$40447bo254$40699b3o$40699bo$40700bo254$40953b3o
$40953bo$40954bo254$41202b3o$41202bo$41203bo254$41468b2o$41467b2o$
41469bo254$41718b3o$41718bo$41719bo254$41982b3o$41982bo$41983bo254$
42242b3o$42242bo$42243bo254$42498b3o$42498bo$42499bo254$42755b2o$
42754b2o$42756bo254$43021b2o$43020b2o$43022bo254$43256b3o$43256bo$
43257bo254$43505b3o$43505bo$43506bo254$43770b3o$43770bo$43771bo254$
44021b3o$44021bo$44022bo254$44285b3o$44285bo$44286bo254$44552b3o$
44552bo$44553bo254$44801b3o$44801bo$44802bo254$45061b2o$45060b2o$
45062bo254$45299b3o$45299bo$45300bo254$45574b3o$45574bo$45575bo254$
45822b3o$45822bo$45823bo254$46087b3o$46087bo$46088bo254$46345b3o$
46345bo$46346bo254$46593b3o$46593bo$46594bo254$46843b3o$46843bo$46844b
o254$47123b3o$47123bo$47124bo254$47374b2o$47373b2o$47375bo254$47609b2o
$47608b2o$47610bo254$47866b3o$47866bo$47867bo254$48115b3o$48115bo$
48116bo254$48380b3o$48380bo$48381bo254$48631b3o$48631bo$48632bo254$
48895b3o$48895bo$48896bo254$49155b3o$49155bo$49156bo254$49409b3o$
49409bo$49410bo254$49660b3o$49660bo$49661bo254$49914b3o$49914bo$49915b
o254$50171b3o$50171bo$50172bo254$50419b3o$50419bo$50420bo254$50684b3o$
50684bo$50685bo254$50935b3o$50935bo$50936bo254$51199b3o$51199bo$51200b
o254$51467b3o$51467bo$51468bo254$51713b3o$51713bo$51714bo254$51954b3o$
51954bo$51955bo254$52202b3o$52202bo$52203bo254$52467b3o$52467bo$52468b
o254$52718b3o$52718bo$52719bo254$52982b3o$52982bo$52983bo254$53242b3o$
53242bo$53243bo254$53498b3o$53498bo$53499bo254$53764b3o$53764bo$53765b
o254$54008b3o$54008bo$54009bo254$54263b3o$54263bo$54264bo254$54512b3o$
54512bo$54513bo254$54777b3o$54777bo$54778bo254$55028b3o$55028bo$55029b
o254$55292b3o$55292bo$55293bo254$55552b3o$55552bo$55553bo254$55805b3o$
55805bo$55806bo254$56065b3o$56065bo$56066bo254$56315b2o$56314b2o$
56316bo254$56570b3o$56570bo$56571bo254$56819b3o$56819bo$56820bo254$
57084b3o$57084bo$57085bo254$57335b3o$57335bo$57336bo254$57599b3o$
57599bo$57600bo254$57853b3o$57853bo$57854bo254$58125b2o$58124b2o$
58126bo254$58388b2o$58387b2o$58389bo254$58645b3o$58645bo$58646bo254$
58887b3o$58887bo$58888bo254$59161b3o$59161bo$59162bo254$59398b3o$
59398bo$59399bo254$59646b3o$59646bo$59647bo254$59912b2o$59911b2o$
59913bo254$60169b3o$60169bo$60170bo254$60417b3o$60417bo$60418bo254$
60681b3o$60681bo$60682bo254$60933b3o$60933bo$60934bo254$61176b3o$
61176bo$61177bo254$61433b3o$61433bo$61434bo254$61682b3o$61682bo$61683b
o254$61948b2o$61947b2o$61949bo254$62198b3o$62198bo$62199bo254$62462b3o
$62462bo$62463bo254$62720b3o$62720bo$62721bo254$62982b2o$62981b2o$
62983bo254$63225b3o$63225bo$63226bo254$63485b3o$63485bo$63486bo254$
63733b3o$63733bo$63734bo254$63998b3o$63998bo$63999bo254$64249b3o$
64249bo$64250bo254$64513b3o$64513bo$64514bo254$64773b3o$64773bo$64774b
o254$65024b3o$65024bo$65025bo254$65293b3o$65293bo$65294bo254$65526b2o$
65525b2o$65527bo254$65798b3o$65798bo$65799bo254$66046b3o$66046bo$
66047bo254$66311b3o$66311bo$66312bo254$66569b3o$66569bo$66570bo254$
66817b3o$66817bo$66818bo254$67079b3o$67079bo$67080bo254$67327b3o$
67327bo$67328bo254$67570b3o$67570bo$67571bo254$67831b3o$67831bo$67832b
o254$68080b3o$68080bo$68081bo254$68328b3o$68328bo$68329bo254$68593b3o$
68593bo$68594bo254$68844b3o$68844bo$68845bo254$69108b3o$69108bo$69109b
o254$69355b3o$69355bo$69356bo254$69643b3o$69643bo$69644bo254$69879b3o$
69879bo$69880bo254$70127b3o$70127bo$70128bo254$70392b3o$70392bo$70393b
o254$70643b3o$70643bo$70644bo254$70907b3o$70907bo$70908bo254$71167b3o$
71167bo$71168bo254$71418b3o$71418bo$71419bo254$71666b3o$71666bo$71667b
o254$71934b2o$71933b2o$71935bo254$72187b3o$72187bo$72188bo254$72441b3o
$72441bo$72442bo254$72690b3o$72690bo$72691bo254$72956b2o$72955b2o$
72957bo254$73206b3o$73206bo$73207bo254$73470b3o$73470bo$73471bo254$
73730b3o$73730bo$73731bo254$73986b3o$73986bo$73987bo254$74243b2o$
74242b2o$74244bo254$74509b2o$74508b2o$74510bo254$74744b3o$74744bo$
74745bo254$74993b3o$74993bo$74994bo254$75258b3o$75258bo$75259bo254$
75509b3o$75509bo$75510bo254$75773b3o$75773bo$75774bo254$76033b3o$
76033bo$76034bo254$76286b3o$76286bo$76287bo254$76540b3o$76540bo$76541b
o254$76794b3o$76794bo$76795bo254$77043b3o$77043bo$77044bo254$77308b3o$
77308bo$77309bo254$77559b3o$77559bo$77560bo254$77823b3o$77823bo$77824b
o254$78083b3o$78083bo$78084bo254$78339b3o$78339bo$78340bo254$78596b2o$
78595b2o$78597bo254$78862b2o$78861b2o$78863bo254$79097b3o$79097bo$
79098bo254$79346b3o$79346bo$79347bo254$79612b2o$79611b2o$79613bo254$
79862b3o$79862bo$79863bo254$80126b3o$80126bo$80127bo254$80393b3o$
80393bo$80394bo254$80642b3o$80642bo$80643bo254$80888b3o$80888bo$80889b
o254$81159b3o$81159bo$81160bo254$81401b3o$81401bo$81402bo254$81650b3o$
81650bo$81651bo254$81916b2o$81915b2o$81917bo254$82166b3o$82166bo$
82167bo254$82430b3o$82430bo$82431bo254$82691b3o$82691bo$82692bo254$
82951b3o$82951bo$82952bo254$83209b3o$83209bo$83210bo254$83449b2o$
83448b2o$83450bo254$83706b3o$83706bo$83707bo254$83954b3o$83954bo$
83955bo254$84220b2o$84219b2o$84221bo254$84470b3o$84470bo$84471bo254$
84734b3o$84734bo$84735bo254$84999b3o$84999bo$85000bo254$85247b3o$
85247bo$85248bo254$85490b3o$85490bo$85491bo254$85751b3o$85751bo$85752b
o254$86000b3o$86000bo$86001bo254$86248b3o$86248bo$86249bo254$86513b3o$
86513bo$86514bo254$86764b3o$86764bo$86765bo254$87028b3o$87028bo$87029b
o254$87276b3o$87276bo$87277bo254$87539b3o$87539bo$87540bo254$87805b3o$
87805bo$87806bo254$88053b3o$88053bo$88054bo254$88306b3o$88306bo$88307b
o254$88569b3o$88569bo$88570bo254$88817b3o$88817bo$88818bo254$89082b3o$
89082bo$89083bo254$89333b3o$89333bo$89334bo254$89597b3o$89597bo$89598b
o254$89858b3o$89858bo$89859bo254$90099b2o$90098b2o$90100bo254$90353b3o
$90353bo$90354bo254$90624b2o$90623b2o$90625bo254$90874b3o$90874bo$
90875bo254$91122b3o$91122bo$91123bo254$91387b3o$91387bo$91388bo254$
91638b3o$91638bo$91639bo254$91902b3o$91902bo$91903bo254$92155b3o$
92155bo$92156bo254$92435b3o$92435bo$92436bo254$92686b2o$92685b2o$
92687bo254$92921b2o$92920b2o$92922bo254$93178b3o$93178bo$93179bo254$
93427b3o$93427bo$93428bo254$93693b2o$93692b2o$93694bo254$93943b3o$
93943bo$93944bo254$94207b3o$94207bo$94208bo254$94461b3o$94461bo$94462b
o254$94722b2o$94721b2o$94723bo254$94981b3o$94981bo$94982bo254$95229b3o
$95229bo$95230bo254$95494b3o$95494bo$95495bo254$95752b3o$95752bo$
95753bo254$96000b3o$96000bo$96001bo254$96258b3o$96258bo$96259bo254$
96525b2o$96524b2o$96526bo254$96773b2o$96772b2o$96774bo254$97034b2o$
97033b2o$97035bo254$97267b3o$97267bo$97268bo254$97531b3o$97531bo$
97532bo254$97779b3o$97779bo$97780bo254$98045b2o$98044b2o$98046bo254$
98295b3o$98295bo$98296bo254$98559b3o$98559bo$98560bo254$98820b3o$
98820bo$98821bo254$99084b3o$99084bo$99085bo254$99330b2o$99329b2o$
99331bo254$99581b2o$99580b2o$99582bo254$99820b3o$99820bo$99821bo254$
100089b3o$100089bo$100090bo254$100338b3o$100338bo$100339bo254$100603b
3o$100603bo$100604bo254$100854b3o$100854bo$100855bo254$101118b3o$
101118bo$101119bo254$101386b3o$101386bo$101387bo254$101618b3o$101618bo
$101619bo254$101888b3o$101888bo$101889bo254$102130b3o$102130bo$102131b
o254$102378b3o$102378bo$102379bo254$102643b3o$102643bo$102644bo254$
102894b3o$102894bo$102895bo254$103158b3o$103158bo$103159bo254$103405b
3o$103405bo$103406bo254$103685b3o$103685bo$103686bo254$103927b3o$
103927bo$103928bo254$104197b3o$104197bo$104198bo254$104446b3o$104446bo
$104447bo254$104711b3o$104711bo$104712bo254$104969b3o$104969bo$104970b
o254$105217b3o$105217bo$105218bo254$105474b3o$105474bo$105475bo254$
105727b3o$105727bo$105728bo254$105985b2o$105984b2o$105986bo254$106233b
3o$106233bo$106234bo254$106482b3o$106482bo$106483bo254$106747b3o$
106747bo$106748bo254$106998b3o$106998bo$106999bo254$107262b3o$107262bo
$107263bo254$107523b3o$107523bo$107524bo254$107771b3o$107771bo$107772b
o254$108022b3o$108022bo$108023bo254$108287b2o$108286b2o$108288bo254$
108536b3o$108536bo$108537bo254$108785b3o$108785bo$108786bo254$109051b
2o$109050b2o$109052bo254$109301b3o$109301bo$109302bo254$109565b3o$
109565bo$109566bo254$109818b3o$109818bo$109819bo254$110098b3o$110098bo
$110099bo254$110349b2o$110348b2o$110350bo254$110584b2o$110583b2o$
110585bo254$110841b3o$110841bo$110842bo254$111090b3o$111090bo$111091bo
254$111355b3o$111355bo$111356bo254$111606b3o$111606bo$111607bo254$
111870b3o$111870bo$111871bo254$112124b3o$112124bo$112125bo254$112379b
2o$112378b2o$112380bo254$112644b3o$112644bo$112645bo254$112906b3o$
112906bo$112907bo254$113155b3o$113155bo$113156bo254$113404b3o$113404bo
$113405bo254$113652b3o$113652bo$113653bo254$113917b3o$113917bo$113918b
o254$114168b3o$114168bo$114169bo254$114432b3o$114432bo$114433bo254$
114679b3o$114679bo$114680bo254$114967b3o$114967bo$114968bo254$115194b
3o$115194bo$115195bo254$115443b3o$115443bo$115444bo254$115708b3o$
115708bo$115709bo254$115959b3o$115959bo$115960bo254$116223b3o$116223bo
$116224bo254$116490b3o$116490bo$116491bo254$116739b3o$116739bo$116740b
o254$116982b3o$116982bo$116983bo254$117237b3o$117237bo$117238bo254$
117489b3o$117489bo$117490bo254$117754b3o$117754bo$117755bo254$118002b
3o$118002bo$118003bo254$118268b2o$118267b2o$118269bo254$118518b3o$
118518bo$118519bo254$118782b3o$118782bo$118783bo254$119043b3o$119043bo
$119044bo254$119297b2o$119296b2o$119298bo254$119549b3o$119549bo$
119550bo254$119797b3o$119797bo$119798bo254$120062b3o$120062bo$120063bo
254$120313b3o$120313bo$120314bo254$120577b3o$120577bo$120578bo254$
120825b3o$120825bo$120826bo254$121088b3o$121088bo$121089bo254$121342b
2o$121341b2o$121343bo254$121614b3o$121614bo$121615bo254$121851b3o$
121851bo$121852bo254$122100b3o$122100bo$122101bo254$122366b2o$122365b
2o$122367bo254$122616b3o$122616bo$122617bo254$122880b3o$122880bo$
122881bo254$123148b3o$123148bo$123149bo254$123380b3o$123380bo$123381bo
254$123650b3o$123650bo$123651bo254$123892b3o$123892bo$123893bo254$
124140b3o$124140bo$124141bo254$124406b2o$124405b2o$124407bo254$124656b
3o$124656bo$124657bo254$124920b3o$124920bo$124921bo254$125178b3o$
125178bo$125179bo254$125432b2o$125431b2o$125433bo254$125681b3o$125681b
o$125682bo254$125951b3o$125951bo$125952bo254$126197b3o$126197bo$
126198bo254$126446b3o$126446bo$126447bo254$126711b3o$126711bo$126712bo
254$126962b3o$126962bo$126963bo254$127226b3o$127226bo$127227bo254$
127486b3o$127486bo$127487bo254$127740b3o$127740bo$127741bo254$127996b
2o$127995b2o$127997bo254$128249b3o$128249bo$128250bo254$128498b3o$
128498bo$128499bo254$128763b3o$128763bo$128764bo254$129014b3o$129014bo
$129015bo254$129278b3o$129278bo$129279bo254$129543b3o$129543bo$129544b
o254$129784b3o$129784bo$129785bo254$130063b2o$130062b2o$130064bo254$
130304b2o$130303b2o$130305bo254$130557b2o$130556b2o$130558bo254$
130809b3o$130809bo$130810bo254$131058b3o$131058bo$131059bo254$131323b
3o$131323bo$131324bo254$131574b3o$131574bo$131575bo254$131838b3o$
131838bo$131839bo254$132096b3o$132096bo$132097bo254$132354b2o$132353b
2o$132355bo254$132613b2o$132612b2o$132614bo254$132870b2o$132869b2o$
132871bo254$133127b2o$133126b2o$133128bo254$133371b3o$133371bo$133372b
o254$133619b3o$133619bo$133620bo254$133884b3o$133884bo$133885bo254$
134135b3o$134135bo$134136bo254$134399b3o$134399bo$134400bo254$134660b
3o$134660bo$134661bo254$134908b3o$134908bo$134909bo254$135159b3o$
135159bo$135160bo254$135421b2o$135420b2o$135422bo254$135672b3o$135672b
o$135673bo254$135921b3o$135921bo$135922bo254$136186b3o$136186bo$
136187bo254$136437b3o$136437bo$136438bo254$136701b3o$136701bo$136702bo
254$136958b3o$136958bo$136959bo254$137210b2o$137209b2o$137211bo254$
137474b2o$137473b2o$137475bo254$137721b3o$137721bo$137722bo254$137970b
3o$137970bo$137971bo254$138235b3o$138235bo$138236bo254$138486b3o$
138486bo$138487bo254$138750b3o$138750bo$138751bo254$139010b3o$139010bo
$139011bo254$139266b3o$139266bo$139267bo254$139509b2o$139508b2o$
139510bo254$139784b2o$139783b2o$139785bo254$140027b3o$140027bo$140028b
o254$140275b3o$140275bo$140276bo254$140541b2o$140540b2o$140542bo254$
140791b3o$140791bo$140792bo254$141055b3o$141055bo$141056bo254$141303b
3o$141303bo$141304bo254$141566b3o$141566bo$141567bo254$141820b2o$
141819b2o$141821bo254$142092b3o$142092bo$142093bo254$142329b3o$142329b
o$142330bo254$142578b3o$142578bo$142579bo254$142844b2o$142843b2o$
142845bo254$143094b3o$143094bo$143095bo254$143358b3o$143358bo$143359bo
254$143623b3o$143623bo$143624bo254$143871b3o$143871bo$143872bo254$
144114b3o$144114bo$144115bo254$144375b3o$144375bo$144376bo254$144624b
3o$144624bo$144625bo254$144872b3o$144872bo$144873bo254$145138b2o$
145137b2o$145139bo254$145388b3o$145388bo$145389bo254$145652b3o$145652b
o$145653bo254$145900b3o$145900bo$145901bo254$146156b3o$146156bo$
146157bo254$146409b3o$146409bo$146410bo254$146671b2o$146670b2o$146672b
o254$146937b3o$146937bo$146938bo254$147207b3o$147207bo$147208bo254$
147455b3o$147455bo$147456bo254$147720b3o$147720bo$147721bo254$147978b
3o$147978bo$147979bo254$148226b3o$148226bo$148227bo254$148483b3o$
148483bo$148484bo254$148739b3o$148739bo$148740bo254$149007b2o$149006b
2o$149008bo254$149241b3o$149241bo$149242bo254$149496b3o$149496bo$
149497bo254$149745b3o$149745bo$149746bo254$150010b3o$150010bo$150011bo
254$150261b3o$150261bo$150262bo254$150525b3o$150525bo$150526bo254$
150782b3o$150782bo$150783bo254$151034b2o$151033b2o$151035bo254$151298b
2o$151297b2o$151299bo254$151545b3o$151545bo$151546bo254$151794b3o$
151794bo$151795bo254$152059b3o$152059bo$152060bo254$152310b3o$152310bo
$152311bo254$152574b3o$152574bo$152575bo254$152834b3o$152834bo$152835b
o254$153087b3o$153087bo$153088bo254$153345b2o$153344b2o$153346bo254$
153593b3o$153593bo$153594bo254$153842b3o$153842bo$153843bo254$154107b
3o$154107bo$154108bo254$154358b3o$154358bo$154359bo254$154622b3o$
154622bo$154623bo254$154876b3o$154876bo$154877bo254$155140b3o$155140bo
$155141bo254$155397b2o$155396b2o$155398bo254$155655b3o$155655bo$
155656bo254$155897b3o$155897bo$155898bo254$156146b3o$156146bo$156147bo
254$156412b2o$156411b2o$156413bo254$156662b3o$156662bo$156663bo254$
156926b3o$156926bo$156927bo254$157174b3o$157174bo$157175bo254$157437b
3o$157437bo$157438bo254$157691b2o$157690b2o$157692bo254$157963b3o$
157963bo$157964bo254$158200b3o$158200bo$158201bo254$158449b3o$158449bo
$158450bo254$158715b2o$158714b2o$158716bo254$158965b3o$158965bo$
158966bo254$159229b3o$159229bo$159230bo254$159476b3o$159476bo$159477bo
254$159742b3o$159742bo$159743bo254$160013b3o$160013bo$160014bo254$
160262b3o$160262bo$160263bo254$160527b3o$160527bo$160528bo254$160785b
3o$160785bo$160786bo254$161033b3o$161033bo$161034bo254$161280b3o$
161280bo$161281bo254$161551b3o$161551bo$161552bo254$161792b3o$161792bo
$161793bo254$162042b3o$162042bo$162043bo254$162298b3o$162298bo$162299b
o254$162547b3o$162547bo$162548bo254$162813b2o$162812b2o$162814bo254$
163063b3o$163063bo$163064bo254$163327b3o$163327bo$163328bo254$163588b
3o$163588bo$163589bo254$163836b3o$163836bo$163837bo254$164087b3o$
164087bo$164088bo254$164349b2o$164348b2o$164350bo254$164600b3o$164600b
o$164601bo254$164849b3o$164849bo$164850bo254$165114b3o$165114bo$
165115bo254$165365b3o$165365bo$165366bo254$165629b3o$165629bo$165630bo
254$165889b3o$165889bo$165890bo254$166145b3o$166145bo$166146bo254$
166388b2o$166387b2o$166389bo254$166663b2o$166662b2o$166664bo254$
166906b3o$166906bo$166907bo254$167154b3o$167154bo$167155bo254$167419b
3o$167419bo$167420bo254$167670b3o$167670bo$167671bo254$167934b3o$
167934bo$167935bo254$168194b3o$168194bo$168195bo254$168450b3o$168450bo
$168451bo254$168718b2o$168717b2o$168719bo254$168952b3o$168952bo$
168953bo254$169207b3o$169207bo$169208bo254$169456b3o$169456bo$169457bo
254$169721b3o$169721bo$169722bo254$169972b3o$169972bo$169973bo254$
170236b3o$170236bo$170237bo254$170494b3o$170494bo$170495bo254$170743b
3o$170743bo$170744bo254$170993b3o$170993bo$170994bo254$171267b3o$
171267bo$171268bo254$171514b3o$171514bo$171515bo254$171762b3o$171762bo
$171763bo254$172028b2o$172027b2o$172029bo254$172278b3o$172278bo$
172279bo254$172542b3o$172542bo$172543bo254$172810b3o$172810bo$172811bo
254$173056b3o$173056bo$173057bo254$173297b3o$173297bo$173298bo254$
173545b3o$173545bo$173546bo254$173811b2o$173810b2o$173812bo254$174061b
3o$174061bo$174062bo254$174325b3o$174325bo$174326bo254$174572b3o$
174572bo$174573bo254$174852b3o$174852bo$174853bo254$175094b3o$175094bo
$175095bo254$175364b3o$175364bo$175365bo254$175613b3o$175613bo$175614b
o254$175879b2o$175878b2o$175880bo254$176136b3o$176136bo$176137bo254$
176384b3o$176384bo$176385bo254$176641b3o$176641bo$176642bo254$176897b
3o$176897bo$176898bo254$177163b3o$177163bo$177164bo254$177407b3o$
177407bo$177408bo254$177671b3o$177671bo$177672bo254$177919b3o$177919bo
$177920bo254$178184b3o$178184bo$178185bo254$178442b3o$178442bo$178443b
o254$178690b3o$178690bo$178691bo254$178955b3o$178955bo$178956bo254$
179201b3o$179201bo$179202bo254$179442b3o$179442bo$179443bo254$179690b
3o$179690bo$179691bo254$179955b3o$179955bo$179956bo254$180206b3o$
180206bo$180207bo254$180470b3o$180470bo$180471bo254$180727b3o$180727bo
$180728bo254$180990b3o$180990bo$180991bo254$181241b3o$181241bo$181242b
o254$181490b3o$181490bo$181491bo254$181753b3o$181753bo$181754bo254$
182002b3o$182002bo$182003bo254$182268b2o$182267b2o$182269bo254$182518b
3o$182518bo$182519bo254$182782b3o$182782bo$182783bo254$183042b3o$
183042bo$183043bo254$183296b3o$183296bo$183297bo254$183547b3o$183547bo
$183548bo254$183801b3o$183801bo$183802bo254$184058b3o$184058bo$184059b
o254$184306b3o$184306bo$184307bo254$184571b3o$184571bo$184572bo254$
184822b3o$184822bo$184823bo254$185086b3o$185086bo$185087bo254$185346b
3o$185346bo$185347bo254$185600b3o$185600bo$185601bo254$185854b2o$
185853b2o$185855bo254$186107b3o$186107bo$186108bo254$186361b3o$186361b
o$186362bo254$186610b3o$186610bo$186611bo254$186876b2o$186875b2o$
186877bo254$187126b3o$187126bo$187127bo254$187390b3o$187390bo$187391bo
254$187638b3o$187638bo$187639bo254$187901b3o$187901bo$187902bo254$
188155b2o$188154b2o$188156bo254$188427b3o$188427bo$188428bo254$188664b
3o$188664bo$188665bo254$188913b3o$188913bo$188914bo254$189179b2o$
189178b2o$189180bo254$189429b3o$189429bo$189430bo254$189693b3o$189693b
o$189694bo254$189953b3o$189953bo$189954bo254$190204b3o$190204bo$
190205bo254$190461b2o$190460b2o$190462bo254$190707b2o$190706b2o$
190708bo254$190982b3o$190982bo$190983bo254$191230b3o$191230bo$191231bo
254$191495b3o$191495bo$191496bo254$191753b3o$191753bo$191754bo254$
192001b3o$192001bo$192002bo254$192258b3o$192258bo$192259bo254$192511b
3o$192511bo$192512bo254$192769b2o$192768b2o$192770bo254$193017b3o$
193017bo$193018bo254$193266b3o$193266bo$193267bo254$193531b3o$193531bo
$193532bo254$193782b3o$193782bo$193783bo254$194046b3o$194046bo$194047b
o254$194306b3o$194306bo$194307bo254$194562b3o$194562bo$194563bo254$
194819b2o$194818b2o$194820bo254$195085b2o$195084b2o$195086bo254$
195320b3o$195320bo$195321bo254$195569b3o$195569bo$195570bo254$195835b
2o$195834b2o$195836bo254$196085b3o$196085bo$196086bo254$196349b3o$
196349bo$196350bo254$196609b3o$196609bo$196610bo254$196860b3o$196860bo
$196861bo254$197108b3o$197108bo$197109bo254$197376b2o$197375b2o$
197377bo254$197633b2o$197632b2o$197634bo254$197881b3o$197881bo$197882b
o254$198130b3o$198130bo$198131bo254$198396b2o$198395b2o$198397bo254$
198646b3o$198646bo$198647bo254$198910b3o$198910bo$198911bo254$199164b
3o$199164bo$199165bo254$199428b3o$199428bo$199429bo254$199685b2o$
199684b2o$199686bo254$199943b3o$199943bo$199944bo254$200185b3o$200185b
o$200186bo254$200434b3o$200434bo$200435bo254$200700b2o$200699b2o$
200701bo254$200950b3o$200950bo$200951bo254$201214b3o$201214bo$201215bo
254$201475b3o$201475bo$201476bo254$201739b3o$201739bo$201740bo254$
201985b2o$201984b2o$201986bo254$202236b2o$202235b2o$202237bo254$
202475b3o$202475bo$202476bo254$202744b3o$202744bo$202745bo254$202993b
3o$202993bo$202994bo254$203258b3o$203258bo$203259bo254$203509b3o$
203509bo$203510bo254$203773b3o$203773bo$203774bo254$204040b3o$204040bo
$204041bo254$204289b3o$204289bo$204290bo254$204530b3o$204530bo$204531b
o254$204807b2o$204806b2o$204808bo254$205050b3o$205050bo$205051bo254$
205298b3o$205298bo$205299bo254$205563b3o$205563bo$205564bo254$205814b
3o$205814bo$205815bo254$206078b3o$206078bo$206079bo254$206338b3o$
206338bo$206339bo254$206589b3o$206589bo$206590bo254$206846b2o$206845b
2o$206847bo254$207112b2o$207111b2o$207113bo254$207355b3o$207355bo$
207356bo254$207603b3o$207603bo$207604bo254$207868b3o$207868bo$207869bo
254$208119b3o$208119bo$208120bo254$208383b3o$208383bo$208384bo254$
208643b3o$208643bo$208644bo254$208899b3o$208899bo$208900bo254$209156b
2o$209155b2o$209157bo254$209402b2o$209401b2o$209403bo254$209669b3o$
209669bo$209670bo254$209918b3o$209918bo$209919bo254$210183b3o$210183bo
$210184bo254$210441b3o$210441bo$210442bo254$210689b3o$210689bo$210690b
o254$210953b3o$210953bo$210954bo254$211202b3o$211202bo$211203bo254$
211448b3o$211448bo$211449bo254$211718b3o$211718bo$211719bo254$211968b
3o$211968bo$211969bo254$212217b3o$212217bo$212218bo254$212466b3o$
212466bo$212467bo254$212731b3o$212731bo$212732bo254$212982b3o$212982bo
$212983bo254$213246b3o$213246bo$213247bo254$213496b3o$213496bo$213497b
o254$213767b3o$213767bo$213768bo254$214005b3o$214005bo$214006bo254$
214258b3o$214258bo$214259bo254$214524b3o$214524bo$214525bo254$214772b
3o$214772bo$214773bo254$215037b3o$215037bo$215038bo254$215288b3o$
215288bo$215289bo254$215552b3o$215552bo$215553bo254$215819b3o$215819bo
$215820bo254$216068b3o$216068bo$216069bo254$216311b3o$216311bo$216312b
o254$216566b3o$216566bo$216567bo254$216818b3o$216818bo$216819bo254$
217083b3o$217083bo$217084bo254$217331b3o$217331bo$217332bo254$217597b
2o$217596b2o$217598bo254$217847b3o$217847bo$217848bo254$218111b3o$
218111bo$218112bo254$218371b3o$218371bo$218372bo254$218622b3o$218622bo
$218623bo254$218879b2o$218878b2o$218880bo254$219132b3o$219132bo$
219133bo254$219384b3o$219384bo$219385bo254$219633b3o$219633bo$219634bo
254$219898b3o$219898bo$219899bo254$220149b3o$220149bo$220150bo254$
220413b3o$220413bo$220414bo254$220680b3o$220680bo$220681bo254$220929b
3o$220929bo$220930bo254$221175b3o$221175bo$221176bo254$221445b3o$
221445bo$221446bo254$221695b3o$221695bo$221696bo254$221944b3o$221944bo
$221945bo254$222193b3o$222193bo$222194bo254$222459b2o$222458b2o$
222460bo254$222709b3o$222709bo$222710bo254$222973b3o$222973bo$222974bo
254$223233b3o$223233bo$223234bo254$223484b3o$223484bo$223485bo254$
223741b2o$223740b2o$223742bo254$224007b2o$224006b2o$224008bo254$
224250b3o$224250bo$224251bo254$224498b3o$224498bo$224499bo254$224763b
3o$224763bo$224764bo254$225014b3o$225014bo$225015bo254$225278b3o$
225278bo$225279bo254$225538b3o$225538bo$225539bo254$225789b3o$225789bo
$225790bo254$226058b3o$226058bo$226059bo254$226291b2o$226290b2o$
226292bo254$226554b3o$226554bo$226555bo254$226803b3o$226803bo$226804bo
254$227068b3o$227068bo$227069bo254$227319b3o$227319bo$227320bo254$
227583b3o$227583bo$227584bo254$227843b3o$227843bo$227844bo254$228099b
3o$228099bo$228100bo254$228356b2o$228355b2o$228357bo254$228622b2o$
228621b2o$228623bo254$228857b3o$228857bo$228858bo254$229106b3o$229106b
o$229107bo254$229371b3o$229371bo$229372bo254$229622b3o$229622bo$
229623bo254$229886b3o$229886bo$229887bo254$230133b3o$230133bo$230134bo
254$230421b3o$230421bo$230422bo254$230648b3o$230648bo$230649bo254$
230897b3o$230897bo$230898bo254$231162b3o$231162bo$231163bo254$231413b
3o$231413bo$231414bo254$231677b3o$231677bo$231678bo254$231944b3o$
231944bo$231945bo254$232193b3o$232193bo$232194bo254$232439b3o$232439bo
$232440bo254$232703b3o$232703bo$232704bo254$232958b3o$232958bo$232959b
o254$233224b3o$233224bo$233225bo254$233472b3o$233472bo$233473bo254$
233737b3o$233737bo$233738bo254$233995b3o$233995bo$233996bo254$234243b
3o$234243bo$234244bo254$234494b3o$234494bo$234495bo254$234746b3o$
234746bo$234747bo254$235011b3o$235011bo$235012bo254$235256b3o$235256bo
$235257bo254$235512b3o$235512bo$235513bo254$235761b3o$235761bo$235762b
o254$236026b3o$236026bo$236027bo254$236277b3o$236277bo$236278bo254$
236541b3o$236541bo$236542bo254$236788b3o$236788bo$236789bo254$237068b
3o$237068bo$237069bo254$237310b3o$237310bo$237311bo254$237580b3o$
237580bo$237581bo254$237829b3o$237829bo$237830bo254$238094b3o$238094bo
$238095bo254$238352b3o$238352bo$238353bo254$238600b3o$238600bo$238601b
o254$238851b3o$238851bo$238852bo254$239103b3o$239103bo$239104bo254$
239368b3o$239368bo$239369bo254$239613b3o$239613bo$239614bo254$239878b
3o$239878bo$239879bo254$240126b3o$240126bo$240127bo254$240392b2o$
240391b2o$240393bo254$240649b3o$240649bo$240650bo254$240897b3o$240897b
o$240898bo254$241154b3o$241154bo$241155bo254$241408b3o$241408bo$
241409bo254$241659b3o$241659bo$241660bo254$241913b3o$241913bo$241914bo
254$242170b3o$242170bo$242171bo254$242418b3o$242418bo$242419bo254$
242684b2o$242683b2o$242685bo254$242934b3o$242934bo$242935bo254$243198b
3o$243198bo$243199bo254$243465b3o$243465bo$243466bo254$243714b3o$
243714bo$243715bo254$243960b3o$243960bo$243961bo254$244231b3o$244231bo
$244232bo254$244473b3o$244473bo$244474bo254$244722b3o$244722bo$244723b
o254$244988b2o$244987b2o$244989bo254$245238b3o$245238bo$245239bo254$
245502b3o$245502bo$245503bo254$245752b3o$245752bo$245753bo254$246023b
3o$246023bo$246024bo254$246269b2o$246268b2o$246270bo254$246522b3o$
246522bo$246523bo254$246778b3o$246778bo$246779bo254$247027b3o$247027bo
$247028bo254$247292b3o$247292bo$247293bo254$247543b3o$247543bo$247544b
o254$247807b3o$247807bo$247808bo254$248065b3o$248065bo$248066bo254$
248327b2o$248326b2o$248328bo254$248575b2o$248574b2o$248576bo254$
248838b3o$248838bo$248839bo254$249086b3o$249086bo$249087bo254$249352b
2o$249351b2o$249353bo254$249609b3o$249609bo$249610bo254$249857b3o$
249857bo$249858bo254$250114b3o$250114bo$250115bo254$250370b3o$250370bo
$250371bo254$250613b3o$250613bo$250614bo254$250864b3o$250864bo$250865b
o254$251140b2o$251139b2o$251141bo254$251382b3o$251382bo$251383bo254$
251631b3o$251631bo$251632bo254$251896b3o$251896bo$251897bo254$252147b
3o$252147bo$252148bo254$252411b3o$252411bo$252412bo254$252672b3o$
252672bo$252673bo254$252932b3o$252932bo$252933bo254$253179b3o$253179bo
$253180bo254$253446b3o$253446bo$253447bo254$253702b3o$253702bo$253703b
o254$253950b3o$253950bo$253951bo254$254215b3o$254215bo$254216bo254$
254473b3o$254473bo$254474bo254$254721b3o$254721bo$254722bo254$254971b
3o$254971bo$254972bo254$255251b3o$255251bo$255252bo254$255502b2o$
255501b2o$255503bo254$255737b2o$255736b2o$255738bo254$255994b3o$
255994bo$255995bo254$256243b3o$256243bo$256244bo254$256508b3o$256508bo
$256509bo254$256759b3o$256759bo$256760bo254$257023b3o$257023bo$257024b
o254$257280b3o$257280bo$257281bo254$257540b2o$257539b2o$257541bo254$
257786b3o$257786bo$257787bo254$258054b3o$258054bo$258055bo254$258298b
3o$258298bo$258299bo254$258547b3o$258547bo$258548bo254$258812b3o$
258812bo$258813bo254$259063b3o$259063bo$259064bo254$259327b3o$259327bo
$259328bo254$259587b3o$259587bo$259588bo254$259843b3o$259843bo$259844b
o254$260100b2o$260099b2o$260101bo254$260346b2o$260345b2o$260347bo254$
260613b3o$260613bo$260614bo254$260862b3o$260862bo$260863bo254$261127b
3o$261127bo$261128bo254$261385b3o$261385bo$261386bo254$261633b3o$
261633bo$261634bo254$261890b3o$261890bo$261891bo254$262143b3o$262143bo
$262144bo254$262401b2o$262400b2o$262402bo254$262649b3o$262649bo$
262650bo254$262898b3o$262898bo$262899bo254$263164b2o$263163b2o$263165b
o254$263414b3o$263414bo$263415bo254$263678b3o$263678bo$263679bo254$
263938b3o$263938bo$263939bo254$264191b3o$264191bo$264192bo254$264449b
2o$264448b2o$264450bo254$264697b3o$264697bo$264698bo254$264946b3o$
264946bo$264947bo254$265212b2o$265211b2o$265213bo254$265462b3o$265462b
o$265463bo254$265726b3o$265726bo$265727bo254$265984b3o$265984bo$
265985bo254$266238b2o$266237b2o$266239bo254$266487b3o$266487bo$266488b
o254$266757b3o$266757bo$266758bo254$267003b3o$267003bo$267004bo254$
267252b3o$267252bo$267253bo254$267518b2o$267517b2o$267519bo254$267768b
3o$267768bo$267769bo254$268032b3o$268032bo$268033bo254$268292b3o$
268292bo$268293bo254$268543b3o$268543bo$268544bo254$268800b2o$268799b
2o$268801bo254$269053b3o$269053bo$269054bo254$269305b3o$269305bo$
269306bo254$269554b3o$269554bo$269555bo254$269820b2o$269819b2o$269821b
o254$270070b3o$270070bo$270071bo254$270334b3o$270334bo$270335bo254$
270594b3o$270594bo$270595bo254$270845b3o$270845bo$270846bo254$271102b
2o$271101b2o$271103bo254$271368b2o$271367b2o$271369bo254$271611b3o$
271611bo$271612bo254$271859b3o$271859bo$271860bo254$272125b2o$272124b
2o$272126bo254$272375b3o$272375bo$272376bo254$272639b3o$272639bo$
272640bo254$272906b3o$272906bo$272907bo254$273155b3o$273155bo$273156bo
254$273401b3o$273401bo$273402bo254$273672b3o$273672bo$273673bo254$
273914b3o$273914bo$273915bo254$274163b3o$274163bo$274164bo254$274428b
3o$274428bo$274429bo254$274679b3o$274679bo$274680bo254$274943b3o$
274943bo$274944bo254$275193b3o$275193bo$275194bo254$275464b3o$275464bo
$275465bo254$275710b2o$275709b2o$275711bo254$275974b3o$275974bo$
275975bo254$276230b3o$276230bo$276231bo254$276478b3o$276478bo$276479bo
254$276743b3o$276743bo$276744bo254$277001b3o$277001bo$277002bo254$
277249b3o$277249bo$277250bo254$277507b3o$277507bo$277508bo254$277767b
3o$277767bo$277768bo254$278025b3o$278025bo$278026bo254$278265b2o$
278264b2o$278266bo254$278522b3o$278522bo$278523bo254$278770b3o$278770b
o$278771bo254$279036b2o$279035b2o$279037bo254$279286b3o$279286bo$
279287bo254$279550b3o$279550bo$279551bo254$279810b3o$279810bo$279811bo
254$280066b3o$280066bo$280067bo254$280323b2o$280322b2o$280324bo254$
280589b2o$280588b2o$280590bo254$280824b3o$280824bo$280825bo254$281073b
3o$281073bo$281074bo254$281338b3o$281338bo$281339bo254$281589b3o$
281589bo$281590bo254$281853b3o$281853bo$281854bo254$282113b3o$282113bo
$282114bo254$282367b3o$282367bo$282368bo254$282618b3o$282618bo$282619b
o254$282872b3o$282872bo$282873bo254$283129b3o$283129bo$283130bo254$
283377b3o$283377bo$283378bo254$283642b3o$283642bo$283643bo254$283893b
3o$283893bo$283894bo254$284157b3o$284157bo$284158bo254$284418b3o$
284418bo$284419bo254$284666b3o$284666bo$284667bo254$284931b2o$284930b
2o$284932bo254$285195b2o$285194b2o$285196bo254$285449b2o$285448b2o$
285450bo254$285695b3o$285695bo$285696bo254$285946b3o$285946bo$285947bo
254$286195b3o$286195bo$286196bo254$286461b2o$286460b2o$286462bo254$
286711b3o$286711bo$286712bo254$286975b3o$286975bo$286976bo254$287243b
3o$287243bo$287244bo254$287489b3o$287489bo$287490bo254$287730b3o$
287730bo$287731bo254$287978b3o$287978bo$287979bo254$288244b2o$288243b
2o$288245bo254$288494b3o$288494bo$288495bo254$288758b3o$288758bo$
288759bo254$289018b3o$289018bo$289019bo254$289274b3o$289274bo$289275bo
254$289531b2o$289530b2o$289532bo254$289797b2o$289796b2o$289798bo254$
290041b3o$290041bo$290042bo254$290289b3o$290289bo$290290bo254$290554b
3o$290554bo$290555bo254$290805b3o$290805bo$290806bo254$291069b3o$
291069bo$291070bo254$291329b3o$291329bo$291330bo254$291583b3o$291583bo
$291584bo254$291834b3o$291834bo$291835bo254$292088b3o$292088bo$292089b
o254$292345b3o$292345bo$292346bo254$292593b3o$292593bo$292594bo254$
292858b3o$292858bo$292859bo254$293109b3o$293109bo$293110bo254$293373b
3o$293373bo$293374bo254$293627b3o$293627bo$293628bo254$293875b3o$
293875bo$293876bo254$294143b2o$294142b2o$294144bo254$294404b2o$294403b
2o$294405bo254$294675b3o$294675bo$294676bo254$294918b3o$294918bo$
294919bo254$295166b3o$295166bo$295167bo254$295432b2o$295431b2o$295433b
o254$295689b3o$295689bo$295690bo254$295937b3o$295937bo$295938bo254$
296202b3o$296202bo$296203bo254$296448b3o$296448bo$296449bo254$296689b
3o$296689bo$296690bo254$296937b3o$296937bo$296938bo254$297203b2o$
297202b2o$297204bo254$297453b3o$297453bo$297454bo254$297717b3o$297717b
o$297718bo254$297977b3o$297977bo$297978bo254$298233b3o$298233bo$
298234bo254$298490b2o$298489b2o$298491bo254$298756b2o$298755b2o$
298757bo254$299000b3o$299000bo$299001bo254$299248b3o$299248bo$299249bo
254$299513b3o$299513bo$299514bo254$299764b3o$299764bo$299765bo254$
300028b3o$300028bo$300029bo254$300288b3o$300288bo$300289bo254$300544b
3o$300544bo$300545bo254$300801b2o$300800b2o$300802bo254$301058b3o$
301058bo$301059bo254$301318b3o$301318bo$301319bo254$301566b3o$301566bo
$301567bo254$301831b3o$301831bo$301832bo254$302089b3o$302089bo$302090b
o254$302337b3o$302337bo$302338bo254$302595b3o$302595bo$302596bo254$
302836b2o$302835b2o$302837bo254$303090b3o$303090bo$303091bo254$303361b
2o$303360b2o$303362bo254$303611b3o$303611bo$303612bo254$303859b3o$
303859bo$303860bo254$304124b3o$304124bo$304125bo254$304375b3o$304375bo
$304376bo254$304639b3o$304639bo$304640bo254$304906b3o$304906bo$304907b
o254$305162b3o$305162bo$305163bo254$305421b3o$305421bo$305422bo254$
305673b2o$305672b2o$305674bo254$305917b3o$305917bo$305918bo254$306168b
3o$306168bo$306169bo254$306416b3o$306416bo$306417bo254$306681b3o$
306681bo$306682bo254$306932b3o$306932bo$306933bo254$307196b3o$307196bo
$307197bo254$307461b3o$307461bo$307462bo254$307702b3o$307702bo$307703b
o254$307981b3o$307981bo$307982bo254$308236b2o$308235b2o$308237bo254$
308494b2o$308493b2o$308495bo254$308757b3o$308757bo$308758bo254$309005b
2o$309004b2o$309006bo254$309256b2o$309255b2o$309257bo254$309519b2o$
309518b2o$309520bo254$309765b3o$309765bo$309766bo254$310014b3o$310014b
o$310015bo254$310280b2o$310279b2o$310281bo254$310537b3o$310537bo$
310538bo254$310785b3o$310785bo$310786bo254$311043b3o$311043bo$311044bo
254$311291b3o$311291bo$311292bo254$311542b3o$311542bo$311543bo254$
311804b2o$311803b2o$311805bo254$312055b3o$312055bo$312056bo254$312304b
3o$312304bo$312305bo254$312569b3o$312569bo$312570bo254$312820b3o$
312820bo$312821bo254$313084b3o$313084bo$313085bo254$313344b3o$313344bo
$313345bo254$313600b3o$313600bo$313601bo254$313843b2o$313842b2o$
313844bo254$314118b2o$314117b2o$314119bo254$314361b3o$314361bo$314362b
o254$314609b3o$314609bo$314610bo254$314874b3o$314874bo$314875bo254$
315125b3o$315125bo$315126bo254$315389b3o$315389bo$315390bo254$315656b
3o$315656bo$315657bo254$315899b3o$315899bo$315900bo254$316154b3o$
316154bo$316155bo254$316420b3o$316420bo$316421bo254$316667b3o$316667bo
$316668bo254$316915b3o$316915bo$316916bo254$317180b3o$317180bo$317181b
o254$317431b3o$317431bo$317432bo254$317695b3o$317695bo$317696bo254$
317955b3o$317955bo$317956bo254$318209b3o$318209bo$318210bo254$318460b
3o$318460bo$318461bo254$318714b3o$318714bo$318715bo254$318971b3o$
318971bo$318972bo254$319219b3o$319219bo$319220bo254$319484b3o$319484bo
$319485bo254$319735b3o$319735bo$319736bo254$319999b3o$319999bo$320000b
o254$320259b3o$320259bo$320260bo254$320515b3o$320515bo$320516bo254$
320783b2o$320782b2o$320784bo254$321017b3o$321017bo$321018bo254$321272b
3o$321272bo$321273bo254$321521b3o$321521bo$321522bo254$321787b2o$
321786b2o$321788bo254$322037b3o$322037bo$322038bo254$322301b3o$322301b
o$322302bo254$322561b3o$322561bo$322562bo254$322812b3o$322812bo$
322813bo254$323081b3o$323081bo$323082bo254$323314b2o$323313b2o$323315b
o254$323577b3o$323577bo$323578bo254$323826b3o$323826bo$323827bo254$
324092b2o$324091b2o$324093bo254$324342b3o$324342bo$324343bo254$324606b
3o$324606bo$324607bo254$324866b3o$324866bo$324867bo254$325119b3o$
325119bo$325120bo254$325377b2o$325376b2o$325378bo254$325625b3o$325625b
o$325626bo254$325874b3o$325874bo$325875bo254$326140b2o$326139b2o$
326141bo254$326390b3o$326390bo$326391bo254$326654b3o$326654bo$326655bo
254$326915b3o$326915bo$326916bo254$327156b2o$327155b2o$327157bo254$
327410b3o$327410bo$327411bo254$327681b2o$327680b2o$327682bo254$327931b
3o$327931bo$327932bo254$328179b3o$328179bo$328180bo254$328445b2o$
328444b2o$328446bo254$328695b3o$328695bo$328696bo254$328959b3o$328959b
o$328960bo254$329224b3o$329224bo$329225bo254$329463b3o$329463bo$
329464bo254$329722b3o$329722bo$329723bo254$329981b2o$329980b2o$329982b
o254$330233b3o$330233bo$330234bo254$330481b3o$330481bo$330482bo254$
330746b3o$330746bo$330747bo254$330997b3o$330997bo$330998bo254$331261b
3o$331261bo$331262bo254$331522b3o$331522bo$331523bo254$331782b3o$
331782bo$331783bo254$332040b3o$332040bo$332041bo254$332280b2o$332279b
2o$332281bo254$332537b3o$332537bo$332538bo254$332785b3o$332785bo$
332786bo254$333051b2o$333050b2o$333052bo254$333301b3o$333301bo$333302b
o254$333565b3o$333565bo$333566bo254$333825b3o$333825bo$333826bo254$
334076b3o$334076bo$334077bo254$334333b2o$334332b2o$334334bo254$334599b
2o$334598b2o$334600bo254$334842b3o$334842bo$334843bo254$335090b3o$
335090bo$335091bo254$335356b2o$335355b2o$335357bo254$335606b3o$335606b
o$335607bo254$335870b3o$335870bo$335871bo254$336118b3o$336118bo$
336119bo254$336381b3o$336381bo$336382bo254$336635b2o$336634b2o$336636b
o254$336907b3o$336907bo$336908bo254$337144b3o$337144bo$337145bo254$
337393b3o$337393bo$337394bo254$337659b2o$337658b2o$337660bo254$337909b
3o$337909bo$337910bo254$338173b3o$338173bo$338174bo254$338434b3o$
338434bo$338435bo254$338694b3o$338694bo$338695bo254$338941b3o$338941bo
$338942bo254$339208b3o$339208bo$339209bo254$339464b3o$339464bo$339465b
o254$339712b3o$339712bo$339713bo254$339978b2o$339977b2o$339979bo254$
340235b3o$340235bo$340236bo254$340483b3o$340483bo$340484bo254$340748b
3o$340748bo$340749bo254$340980b3o$340980bo$340981bo254$341250b3o$
341250bo$341251bo254$341492b3o$341492bo$341493bo254$341740b3o$341740bo
$341741bo254$342006b2o$342005b2o$342007bo254$342256b3o$342256bo$
342257bo254$342520b3o$342520bo$342521bo254$342768b3o$342768bo$342769bo
254$343031b3o$343031bo$343032bo254$343302b3o$343302bo$343303bo254$
343539b2o$343538b2o$343540bo254$343815b3o$343815bo$343816bo254$344063b
3o$344063bo$344064bo254$344328b3o$344328bo$344329bo254$344586b3o$
344586bo$344587bo254$344834b3o$344834bo$344835bo254$345091b3o$345091bo
$345092bo254$345347b3o$345347bo$345348bo254$345615b2o$345614b2o$
345616bo254$345849b3o$345849bo$345850bo254$346104b3o$346104bo$346105bo
254$346353b3o$346353bo$346354bo254$346618b3o$346618bo$346619bo254$
346869b3o$346869bo$346870bo254$347133b3o$347133bo$347134bo254$347380b
3o$347380bo$347381bo254$347660b3o$347660bo$347661bo254$347902b3o$
347902bo$347903bo254$348172b3o$348172bo$348173bo254$348421b3o$348421bo
$348422bo254$348686b3o$348686bo$348687bo254$348944b3o$348944bo$348945b
o254$349192b3o$349192bo$349193bo254$349449b3o$349449bo$349450bo254$
349700b3o$349700bo$349701bo254$349957b2o$349956b2o$349958bo254$350223b
2o$350222b2o$350224bo254$350457b3o$350457bo$350458bo254$350706b3o$
350706bo$350707bo254$350971b3o$350971bo$350972bo254$351222b3o$351222bo
$351223bo254$351486b3o$351486bo$351487bo254$351753b3o$351753bo$351754b
o254$352002b3o$352002bo$352003bo254$352248b3o$352248bo$352249bo254$
352519b3o$352519bo$352520bo254$352761b3o$352761bo$352762bo254$353010b
3o$353010bo$353011bo254$353275b3o$353275bo$353276bo254$353526b3o$
353526bo$353527bo254$353790b3o$353790bo$353791bo254$354050b3o$354050bo
$354051bo254$354306b3o$354306bo$354307bo254$354557b3o$354557bo$354558b
o254$354809b3o$354809bo$354810bo254$355068b2o$355067b2o$355069bo254$
355337b2o$355336b2o$355338bo254$355583b3o$355583bo$355584bo254$355832b
3o$355832bo$355833bo254$356081b3o$356081bo$356082bo254$356346b3o$
356346bo$356347bo254$356597b3o$356597bo$356598bo254$356861b3o$356861bo
$356862bo254$357121b3o$357121bo$357122bo254$357372b3o$357372bo$357373b
o254$357629b2o$357628b2o$357630bo254$357875b2o$357874b2o$357876bo254$
358150b3o$358150bo$358151bo254$358398b3o$358398bo$358399bo254$358663b
3o$358663bo$358664bo254$358921b3o$358921bo$358922bo254$359169b3o$
359169bo$359170bo254$359426b3o$359426bo$359427bo254$359682b3o$359682bo
$359683bo254$359950b2o$359949b2o$359951bo254$360184b3o$360184bo$
360185bo254$360439b3o$360439bo$360440bo254$360688b3o$360688bo$360689bo
254$360953b3o$360953bo$360954bo254$361204b3o$361204bo$361205bo254$
361468b3o$361468bo$361469bo254$361728b3o$361728bo$361729bo254$361981b
3o$361981bo$361982bo254$362233b2o$362232b2o$362234bo254$362488b3o$
362488bo$362489bo254$362744b3o$362744bo$362745bo254$362993b3o$362993bo
$362994bo254$363258b3o$363258bo$363259bo254$363509b3o$363509bo$363510b
o254$363773b3o$363773bo$363774bo254$364021b3o$364021bo$364022bo254$
364284b3o$364284bo$364285bo254$364550b3o$364550bo$364551bo254$364798b
3o$364798bo$364799bo254$365051b3o$365051bo$365052bo254$365305b3o$
365305bo$365306bo254$365554b3o$365554bo$365555bo254$365819b3o$365819bo
$365820bo254$366070b3o$366070bo$366071bo254$366334b3o$366334bo$366335b
o254$366594b3o$366594bo$366595bo254$366847b3o$366847bo$366848bo254$
367099b2o$367098b2o$367100bo254$367361b3o$367361bo$367362bo254$367608b
3o$367608bo$367609bo254$367857b3o$367857bo$367858bo254$368122b3o$
368122bo$368123bo254$368373b3o$368373bo$368374bo254$368637b3o$368637bo
$368638bo254$368887b3o$368887bo$368888bo254$369158b3o$369158bo$369159b
o254$369404b2o$369403b2o$369405bo254$369658b3o$369658bo$369659bo254$
369907b3o$369907bo$369908bo254$370172b3o$370172bo$370173bo254$370423b
3o$370423bo$370424bo254$370687b3o$370687bo$370688bo254$370955b3o$
370955bo$370956bo254$371201b3o$371201bo$371202bo254$371442b3o$371442bo
$371443bo254$371690b3o$371690bo$371691bo254$371955b3o$371955bo$371956b
o254$372206b3o$372206bo$372207bo254$372470b3o$372470bo$372471bo254$
372730b3o$372730bo$372731bo254$372981b3o$372981bo$372982bo254$373250b
3o$373250bo$373251bo254$373483b2o$373482b2o$373484bo254$373755b3o$
373755bo$373756bo254$374003b3o$374003bo$374004bo254$374269b2o$374268b
2o$374270bo254$374519b3o$374519bo$374520bo254$374783b3o$374783bo$
374784bo254$375051b3o$375051bo$375052bo254$375297b3o$375297bo$375298bo
254$375538b3o$375538bo$375539bo254$375786b3o$375786bo$375787bo254$
376052b2o$376051b2o$376053bo254$376302b3o$376302bo$376303bo254$376566b
3o$376566bo$376567bo254$376826b3o$376826bo$376827bo254$377080b3o$
377080bo$377081bo254$377331b3o$377331bo$377332bo254$377594b3o$377594bo
$377595bo254$377849b3o$377849bo$377850bo254$378098b3o$378098bo$378099b
o254$378364b2o$378363b2o$378365bo254$378614b3o$378614bo$378615bo254$
378878b3o$378878bo$378879bo254$379128b3o$379128bo$379129bo254$379399b
3o$379399bo$379400bo254$379637b3o$379637bo$379638bo254$379890b3o$
379890bo$379891bo254$380156b3o$380156bo$380157bo254$380404b3o$380404bo
$380405bo254$380670b2o$380669b2o$380671bo254$380920b3o$380920bo$
380921bo254$381184b3o$381184bo$381185bo254$381452b3o$381452bo$381453bo
254$381684b3o$381684bo$381685bo254$381954b3o$381954bo$381955bo254$
382196b3o$382196bo$382197bo254$382444b3o$382444bo$382445bo254$382710b
2o$382709b2o$382711bo254$382960b3o$382960bo$382961bo254$383224b3o$
383224bo$383225bo254$383471b3o$383471bo$383472bo254$383737b3o$383737bo
$383738bo254$384008b3o$384008bo$384009bo254$384257b3o$384257bo$384258b
o254$384522b3o$384522bo$384523bo254$384780b3o$384780bo$384781bo254$
385028b3o$385028bo$385029bo254$385290b3o$385290bo$385291bo254$385534b
3o$385534bo$385535bo254$385794b2o$385793b2o$385795bo254$386047b3o$
386047bo$386048bo254$386297b2o$386296b2o$386298bo254$386554b3o$386554b
o$386555bo254$386802b3o$386802bo$386803bo254$387067b3o$387067bo$
387068bo254$387318b3o$387318bo$387319bo254$387582b3o$387582bo$387583bo
254$387849b3o$387849bo$387850bo254$388098b3o$388098bo$388099bo254$
388344b3o$388344bo$388345bo254$388615b3o$388615bo$388616bo254$388857b
3o$388857bo$388858bo254$389106b3o$389106bo$389107bo254$389371b3o$
389371bo$389372bo254$389622b3o$389622bo$389623bo254$389886b3o$389886bo
$389887bo254$390147b3o$390147bo$390148bo254$390389b2o$390388b2o$
390390bo254$390657b2o$390656b2o$390658bo254$390897b3o$390897bo$390898b
o254$391158b2o$391157b2o$391159bo254$391417b3o$391417bo$391418bo254$
391665b3o$391665bo$391666bo254$391931b2o$391930b2o$391932bo254$392181b
3o$392181bo$392182bo254$392445b3o$392445bo$392446bo254$392692b3o$
392692bo$392693bo254$392972b3o$392972bo$392973bo254$393214b3o$393214bo
$393215bo254$393484b3o$393484bo$393485bo254$393733b3o$393733bo$393734b
o254$393999b2o$393998b2o$394000bo254$394256b3o$394256bo$394257bo254$
394504b3o$394504bo$394505bo254$394762b3o$394762bo$394763bo254$395022b
3o$395022bo$395023bo254$395280b3o$395280bo$395281bo254$395516b3o$
395516bo$395517bo254$395770b3o$395770bo$395771bo254$396019b3o$396019bo
$396020bo254$396285b2o$396284b2o$396286bo254$396535b3o$396535bo$
396536bo254$396799b3o$396799bo$396800bo254$397059b3o$397059bo$397060bo
254$397315b3o$397315bo$397316bo254$397572b2o$397571b2o$397573bo254$
397838b2o$397837b2o$397839bo254$398073b3o$398073bo$398074bo254$398322b
3o$398322bo$398323bo254$398587b3o$398587bo$398588bo254$398838b3o$
398838bo$398839bo254$399102b3o$399102bo$399103bo254$399356b3o$399356bo
$399357bo254$399620b3o$399620bo$399621bo254$399877b2o$399876b2o$
399878bo254$400135b3o$400135bo$400136bo254$400377b3o$400377bo$400378bo
254$400626b3o$400626bo$400627bo254$400891b3o$400891bo$400892bo254$
401142b3o$401142bo$401143bo254$401406b3o$401406bo$401407bo254$401663b
3o$401663bo$401664bo254$401915b2o$401914b2o$401916bo254$402179b2o$
402178b2o$402180bo254$402426b3o$402426bo$402427bo254$402675b3o$402675b
o$402676bo254$402940b3o$402940bo$402941bo254$403191b3o$403191bo$
403192bo254$403455b3o$403455bo$403456bo254$403720b3o$403720bo$403721bo
254$403964b3o$403964bo$403965bo254$404224b2o$404223b2o$404225bo254$
404477b3o$404477bo$404478bo254$404723b3o$404723bo$404724bo254$404986b
3o$404986bo$404987bo254$405234b3o$405234bo$405235bo254$405499b3o$
405499bo$405500bo254$405750b3o$405750bo$405751bo254$406014b3o$406014bo
$406015bo254$406279b3o$406279bo$406280bo254$406527b3o$406527bo$406528b
o254$406770b3o$406770bo$406771bo254$407021b3o$407021bo$407022bo254$
407289b3o$407289bo$407290bo254$407537b3o$407537bo$407538bo254$407803b
2o$407802b2o$407804bo254$408053b3o$408053bo$408054bo254$408317b3o$
408317bo$408318bo254$408575b3o$408575bo$408576bo254$408829b2o$408828b
2o$408830bo254$409078b3o$409078bo$409079bo254$409348b3o$409348bo$
409349bo254$409594b3o$409594bo$409595bo254$409843b3o$409843bo$409844bo
254$410109b2o$410108b2o$410110bo254$410359b3o$410359bo$410360bo254$
410623b3o$410623bo$410624bo254$410883b3o$410883bo$410884bo254$411134b
3o$411134bo$411135bo254$411391b2o$411390b2o$411392bo254$411644b3o$
411644bo$411645bo254$411896b3o$411896bo$411897bo254$412145b3o$412145bo
$412146bo254$412411b2o$412410b2o$412412bo254$412661b3o$412661bo$
412662bo254$412925b3o$412925bo$412926bo254$413185b3o$413185bo$413186bo
254$413436b3o$413436bo$413437bo254$413693b2o$413692b2o$413694bo254$
413959b2o$413958b2o$413960bo254$414202b3o$414202bo$414203bo254$414450b
3o$414450bo$414451bo254$414716b2o$414715b2o$414717bo254$414966b3o$
414966bo$414967bo254$415230b3o$415230bo$415231bo254$415497b3o$415497bo
$415498bo254$415746b3o$415746bo$415747bo254$415992b3o$415992bo$415993b
o254$416263b3o$416263bo$416264bo254$416505b3o$416505bo$416506bo254$
416754b3o$416754bo$416755bo254$417019b3o$417019bo$417020bo254$417270b
3o$417270bo$417271bo254$417534b3o$417534bo$417535bo254$417801b3o$
417801bo$417802bo254$418050b3o$418050bo$418051bo254$418291b3o$418291bo
$418292bo254$418568b2o$418567b2o$418569bo254$418811b3o$418811bo$
418812bo254$419059b3o$419059bo$419060bo254$419325b2o$419324b2o$419326b
o254$419575b3o$419575bo$419576bo254$419839b3o$419839bo$419840bo254$
420099b3o$420099bo$420100bo254$420355b3o$420355bo$420356bo254$420612b
2o$420611b2o$420613bo254$420878b2o$420877b2o$420879bo254$421113b3o$
421113bo$421114bo254$421362b3o$421362bo$421363bo254$421627b3o$421627bo
$421628bo254$421878b3o$421878bo$421879bo254$422142b3o$422142bo$422143b
o254$422402b3o$422402bo$422403bo254$422656b3o$422656bo$422657bo254$
422907b3o$422907bo$422908bo254$423161b3o$423161bo$423162bo254$423418b
3o$423418bo$423419bo254$423666b3o$423666bo$423667bo254$423931b3o$
423931bo$423932bo254$424182b3o$424182bo$424183bo254$424446b3o$424446bo
$424447bo254$424703b3o$424703bo$424704bo254$424957b3o$424957bo$424958b
o254$425207b2o$425206b2o$425208bo254$425481b3o$425481bo$425482bo254$
425732b3o$425732bo$425733bo254$425987b3o$425987bo$425988bo254$426235b
3o$426235bo$426236bo254$426483b3o$426483bo$426484bo254$426748b3o$
426748bo$426749bo254$426999b3o$426999bo$427000bo254$427263b3o$427263bo
$427264bo254$427524b3o$427524bo$427525bo254$427772b3o$427772bo$427773b
o254$428023b3o$428023bo$428024bo254$428288b2o$428287b2o$428289bo254$
428537b3o$428537bo$428538bo254$428786b3o$428786bo$428787bo254$429051b
3o$429051bo$429052bo254$429302b3o$429302bo$429303bo254$429566b3o$
429566bo$429567bo254$429814b3o$429814bo$429815bo254$430077b3o$430077bo
$430078bo254$430331b2o$430330b2o$430332bo254$430603b3o$430603bo$
430604bo254$430840b3o$430840bo$430841bo254$431089b3o$431089bo$431090bo
254$431355b2o$431354b2o$431356bo254$431605b3o$431605bo$431606bo254$
431869b3o$431869bo$431870bo254$432116b3o$432116bo$432117bo254$432396b
3o$432396bo$432397bo254$432638b3o$432638bo$432639bo254$432908b3o$
432908bo$432909bo254$433157b3o$433157bo$433158bo254$433422b3o$433422bo
$433423bo254$433680b3o$433680bo$433681bo254$433928b3o$433928bo$433929b
o254$434192b3o$434192bo$434193bo254$434441b3o$434441bo$434442bo254$
434684b3o$434684bo$434685bo254$434949b3o$434949bo$434950bo254$435193b
3o$435193bo$435194bo254$435442b3o$435442bo$435443bo254$435708b2o$
435707b2o$435709bo254$435958b3o$435958bo$435959bo254$436222b3o$436222b
o$436223bo254$436489b3o$436489bo$436490bo254$436738b3o$436738bo$
436739bo254$436979b3o$436979bo$436980bo254$437256b2o$437255b2o$437257b
o254$437499b3o$437499bo$437500bo254$437747b3o$437747bo$437748bo254$
438013b2o$438012b2o$438014bo254$438263b3o$438263bo$438264bo254$438527b
3o$438527bo$438528bo254$438787b3o$438787bo$438788bo254$439043b3o$
439043bo$439044bo254$439300b2o$439299b2o$439301bo254$439566b2o$439565b
2o$439567bo254$439801b3o$439801bo$439802bo254$440050b3o$440050bo$
440051bo254$440316b2o$440315b2o$440317bo254$440566b3o$440566bo$440567b
o254$440830b3o$440830bo$440831bo254$441090b3o$441090bo$441091bo254$
441344b3o$441344bo$441345bo254$441595b3o$441595bo$441596bo254$441849b
3o$441849bo$441850bo254$442106b3o$442106bo$442107bo254$442354b3o$
442354bo$442355bo254$442620b2o$442619b2o$442621bo254$442870b3o$442870b
o$442871bo254$443134b3o$443134bo$443135bo254$443392b3o$443392bo$
443393bo254$443641b3o$443641bo$443642bo254$443891b3o$443891bo$443892bo
254$444146b3o$444146bo$444147bo254$444421b3o$444421bo$444422bo254$
444667b3o$444667bo$444668bo254$444915b3o$444915bo$444916bo254$445180b
3o$445180bo$445181bo254$445431b3o$445431bo$445432bo254$445695b3o$
445695bo$445696bo254$445949b3o$445949bo$445950bo254$446201b3o$446201bo
$446202bo254$446466b3o$446466bo$446467bo254$446711b3o$446711bo$446712b
o254$446967b3o$446967bo$446968bo254$447216b3o$447216bo$447217bo254$
447481b3o$447481bo$447482bo254$447732b3o$447732bo$447733bo254$447996b
3o$447996bo$447997bo254$448257b3o$448257bo$448258bo254$448524b2o$
448523b2o$448525bo254$448768b3o$448768bo$448769bo254$449022b2o$449021b
2o$449023bo254$449275b3o$449275bo$449276bo254$449523b3o$449523bo$
449524bo254$449788b3o$449788bo$449789bo254$450039b3o$450039bo$450040bo
254$450303b3o$450303bo$450304bo254$450551b3o$450551bo$450552bo254$
450814b3o$450814bo$450815bo254$451068b2o$451067b2o$451069bo254$451340b
3o$451340bo$451341bo254$451577b3o$451577bo$451578bo254$451826b3o$
451826bo$451827bo254$452092b2o$452091b2o$452093bo254$452342b3o$452342b
o$452343bo254$452606b3o$452606bo$452607bo254$452874b3o$452874bo$
452875bo254$453120b3o$453120bo$453121bo254$453361b3o$453361bo$453362bo
254$453609b3o$453609bo$453610bo254$453875b2o$453874b2o$453876bo254$
454125b3o$454125bo$454126bo254$454389b3o$454389bo$454390bo254$454654b
3o$454654bo$454655bo254$454895b3o$454895bo$454896bo254$455174b2o$
455173b2o$455175bo254$455415b2o$455414b2o$455416bo254$455668b2o$
455667b2o$455669bo254$455929b3o$455929bo$455930bo254$456177b3o$456177b
o$456178bo254$456442b3o$456442bo$456443bo254$456693b3o$456693bo$
456694bo254$456957b3o$456957bo$456958bo254$457215b3o$457215bo$457216bo
254$457469b2o$457468b2o$457470bo254$457718b3o$457718bo$457719bo254$
457988b3o$457988bo$457989bo254$458234b3o$458234bo$458235bo254$458483b
3o$458483bo$458484bo254$458748b3o$458748bo$458749bo254$458999b3o$
458999bo$459000bo254$459263b3o$459263bo$459264bo254$459520b3o$459520bo
$459521bo254$459772b2o$459771b2o$459773bo254$460040b3o$460040bo$
460041bo254$460291b3o$460291bo$460292bo254$460540b3o$460540bo$460541bo
254$460805b3o$460805bo$460806bo254$461063b3o$461063bo$461064bo254$
461311b3o$461311bo$461312bo254$461568b3o$461568bo$461569bo254$461821b
3o$461821bo$461822bo254$462075b3o$462075bo$462076bo254$462329b3o$
462329bo$462330bo254$462578b3o$462578bo$462579bo254$462843b3o$462843bo
$462844bo254$463094b3o$463094bo$463095bo254$463358b3o$463358bo$463359b
o254$463626b3o$463626bo$463627bo254$463872b3o$463872bo$463873bo254$
464113b3o$464113bo$464114bo254$464361b3o$464361bo$464362bo254$464626b
3o$464626bo$464627bo254$464877b3o$464877bo$464878bo254$465141b3o$
465141bo$465142bo254$465401b3o$465401bo$465402bo254$465655b3o$465655bo
$465656bo254$465906b3o$465906bo$465907bo254$466169b3o$466169bo$466170b
o254$466424b3o$466424bo$466425bo254$466673b3o$466673bo$466674bo254$
466939b2o$466938b2o$466940bo254$467189b3o$467189bo$467190bo254$467453b
3o$467453bo$467454bo254$467713b3o$467713bo$467714bo254$467966b3o$
467966bo$467967bo254$468218b2o$468217b2o$468219bo254$468473b3o$468473b
o$468474bo254$468729b3o$468729bo$468730bo254$468978b3o$468978bo$
468979bo254$469244b2o$469243b2o$469245bo254$469494b3o$469494bo$469495b
o254$469758b3o$469758bo$469759bo254$470019b3o$470019bo$470020bo254$
470283b3o$470283bo$470284bo254$470525b3o$470525bo$470526bo254$470779b
3o$470779bo$470780bo254$471033b3o$471033bo$471034bo254$471302b2o$
471301b2o$471303bo254$471560b2o$471559b2o$471561bo254$471824b2o$
471823b2o$471825bo254$472068b2o$472067b2o$472069bo254$472318b2o$
472317b2o$472319bo254$472588b2o$472587b2o$472589bo254$472823b3o$
472823bo$472824bo254$473071b3o$473071bo$473072bo254$473337b2o$473336b
2o$473338bo254$473587b3o$473587bo$473588bo254$473851b3o$473851bo$
473852bo254$474111b3o$474111bo$474112bo254$474355b3o$474355bo$474356bo
254$474621b3o$474621bo$474622bo254$474869b3o$474869bo$474870bo254$
475129b3o$475129bo$475130bo254$475377b3o$475377bo$475378bo254$475642b
3o$475642bo$475643bo254$475893b3o$475893bo$475894bo254$476157b3o$
476157bo$476158bo254$476410b3o$476410bo$476411bo254$476690b3o$476690bo
$476691bo254$476941b2o$476940b2o$476942bo254$477176b2o$477175b2o$
477177bo254$477433b3o$477433bo$477434bo254$477682b3o$477682bo$477683bo
254$477947b3o$477947bo$477948bo254$478198b3o$478198bo$478199bo254$
478462b3o$478462bo$478463bo254$478712b3o$478712bo$478713bo254$478983b
3o$478983bo$478984bo254$479229b2o$479228b2o$479230bo254$479483b3o$
479483bo$479484bo254$479732b3o$479732bo$479733bo254$479997b3o$479997bo
$479998bo254$480248b3o$480248bo$480249bo254$480512b3o$480512bo$480513b
o254$480777b3o$480777bo$480778bo254$481018b3o$481018bo$481019bo254$
481290b3o$481290bo$481291bo254$481541b3o$481541bo$481542bo254$481790b
3o$481790bo$481791bo254$482055b3o$482055bo$482056bo254$482313b3o$
482313bo$482314bo254$482561b3o$482561bo$482562bo254$482826b3o$482826bo
$482827bo254$483072b3o$483072bo$483073bo254$483313b3o$483313bo$483314b
o254$483561b3o$483561bo$483562bo254$483826b3o$483826bo$483827bo254$
484077b3o$484077bo$484078bo254$484341b3o$484341bo$484342bo254$484589b
3o$484589bo$484590bo254$484852b3o$484852bo$484853bo254$485123b3o$
485123bo$485124bo254$485360b2o$485359b2o$485361bo254$485627b3o$485627b
o$485628bo254$485876b3o$485876bo$485877bo254$486141b3o$486141bo$
486142bo254$486392b3o$486392bo$486393bo254$486656b3o$486656bo$486657bo
254$486910b3o$486910bo$486911bo254$487180b2o$487179b2o$487181bo254$
487436b2o$487435b2o$487437bo254$487673b2o$487672b2o$487674bo254$
487929b3o$487929bo$487930bo254$488177b3o$488177bo$488178bo254$488442b
3o$488442bo$488443bo254$488693b3o$488693bo$488694bo254$488957b3o$
488957bo$488958bo254$489217b3o$489217bo$489218bo254$489468b3o$489468bo
$489469bo254$489725b2o$489724b2o$489726bo254$489991b2o$489990b2o$
489992bo254$490234b3o$490234bo$490235bo254$490482b3o$490482bo$490483bo
254$490747b3o$490747bo$490748bo254$490998b3o$490998bo$490999bo254$
491262b3o$491262bo$491263bo254$491529b3o$491529bo$491530bo254$491778b
3o$491778bo$491779bo254$492024b3o$492024bo$492025bo254$492295b3o$
492295bo$492296bo254$492537b3o$492537bo$492538bo254$492786b3o$492786bo
$492787bo254$493051b3o$493051bo$493052bo254$493302b3o$493302bo$493303b
o254$493566b3o$493566bo$493567bo254$493823b3o$493823bo$493824bo254$
494083b2o$494082b2o$494084bo254$494329b3o$494329bo$494330bo254$494597b
3o$494597bo$494598bo254$494841b3o$494841bo$494842bo254$495090b3o$
495090bo$495091bo254$495355b3o$495355bo$495356bo254$495606b3o$495606bo
$495607bo254$495870b3o$495870bo$495871bo254$496138b3o$496138bo$496139b
o254$496384b3o$496384bo$496385bo254$496625b3o$496625bo$496626bo254$
496873b3o$496873bo$496874bo254$497138b3o$497138bo$497139bo254$497389b
3o$497389bo$497390bo254$497653b3o$497653bo$497654bo254$497901b3o$
497901bo$497902bo254$498164b3o$498164bo$498165bo254$498435b3o$498435bo
$498436bo254$498672b2o$498671b2o$498673bo254$498939b3o$498939bo$
498940bo254$499188b3o$499188bo$499189bo254$499453b3o$499453bo$499454bo
254$499704b3o$499704bo$499705bo254$499968b3o$499968bo$499969bo254$
500222b3o$500222bo$500223bo254$500492b2o$500491b2o$500493bo254$500748b
2o$500747b2o$500749bo254$500985b2o$500984b2o$500986bo254$501241b3o$
501241bo$501242bo254$501489b3o$501489bo$501490bo254$501754b3o$501754bo
$501755bo254$502005b3o$502005bo$502006bo254$502269b3o$502269bo$502270b
o254$502529b3o$502529bo$502530bo254$502780b3o$502780bo$502781bo254$
503037b2o$503036b2o$503038bo254$503303b2o$503302b2o$503304bo254$
503546b3o$503546bo$503547bo254$503794b3o$503794bo$503795bo254$504059b
3o$504059bo$504060bo254$504310b3o$504310bo$504311bo254$504574b3o$
504574bo$504575bo254$504841b3o$504841bo$504842bo254$505090b3o$505090bo
$505091bo254$505336b3o$505336bo$505337bo254$505607b3o$505607bo$505608b
o254$505849b3o$505849bo$505850bo254$506098b3o$506098bo$506099bo254$
506363b3o$506363bo$506364bo254$506614b3o$506614bo$506615bo254$506878b
3o$506878bo$506879bo254$507135b3o$507135bo$507136bo254$507395b2o$
507394b2o$507396bo254$507641b3o$507641bo$507642bo254$507909b3o$507909b
o$507910bo254$508153b3o$508153bo$508154bo254$508402b3o$508402bo$
508403bo254$508667b3o$508667bo$508668bo254$508918b3o$508918bo$508919bo
254$509182b3o$509182bo$509183bo254$509439b3o$509439bo$509440bo254$
509691b2o$509690b2o$509692bo254$509955b2o$509954b2o$509956bo254$
510202b3o$510202bo$510203bo254$510451b3o$510451bo$510452bo254$510716b
3o$510716bo$510717bo254$510967b3o$510967bo$510968bo254$511231b3o$
511231bo$511232bo254$511479b3o$511479bo$511480bo254$511742b3o$511742bo
$511743bo254$511996b2o$511995b2o$511997bo254$512268b3o$512268bo$
512269bo254$512505b3o$512505bo$512506bo254$512754b3o$512754bo$512755bo
254$513019b3o$513019bo$513020bo254$513270b3o$513270bo$513271bo254$
513534b3o$513534bo$513535bo254$513794b3o$513794bo$513795bo254$514045b
3o$514045bo$514046bo254$514302b2o$514301b2o$514303bo254$514568b2o$
514567b2o$514569bo254$514811b3o$514811bo$514812bo254$515059b3o$515059b
o$515060bo254$515324b3o$515324bo$515325bo254$515575b3o$515575bo$
515576bo254$515839b3o$515839bo$515840bo254$516106b3o$516106bo$516107bo
254$516358b3o$516358bo$516359bo254$516601b3o$516601bo$516602bo254$
516858b3o$516858bo$516859bo254$517107b3o$517107bo$517108bo254$517372b
3o$517372bo$517373bo254$517623b3o$517623bo$517624bo254$517887b3o$
517887bo$517888bo254$518135b3o$518135bo$518136bo254$518398b3o$518398bo
$518399bo254$518664b3o$518664bo$518665bo254$518912b3o$518912bo$518913b
o254$519169b3o$519169bo$519170bo254$519415b3o$519415bo$519416bo254$
519664b3o$519664bo$519665bo254$519929b3o$519929bo$519930bo254$520180b
3o$520180bo$520181bo254$520444b3o$520444bo$520445bo254$520694b3o$
520694bo$520695bo254$520965b3o$520965bo$520966bo254$521203b3o$521203bo
$521204bo254$521456b3o$521456bo$521457bo254$521722b3o$521722bo$521723b
o254$521970b3o$521970bo$521971bo254$522235b3o$522235bo$522236bo254$
522486b3o$522486bo$522487bo254$522750b3o$522750bo$522751bo254$523015b
3o$523015bo$523016bo254$523263b3o$523263bo$523264bo254$523506b3o$
523506bo$523507bo254$523757b3o$523757bo$523758bo254$524025b3o$524025bo
$524026bo254$524273b3o$524273bo$524274bo254$524538b3o$524538bo$524539b
o254$524789b3o$524789bo$524790bo254$525053b3o$525053bo$525054bo254$
525300b3o$525300bo$525301bo254$525580b3o$525580bo$525581bo254$525822b
3o$525822bo$525823bo254$526092b3o$526092bo$526093bo254$526341b3o$
526341bo$526342bo254$526606b3o$526606bo$526607bo254$526864b3o$526864bo
$526865bo254$527112b3o$527112bo$527113bo254$527377b3o$527377bo$527378b
o254$527609b3o$527609bo$527610bo254$527879b3o$527879bo$527880bo254$
528121b3o$528121bo$528122bo254$528369b3o$528369bo$528370bo254$528634b
3o$528634bo$528635bo254$528885b3o$528885bo$528886bo254$529149b3o$
529149bo$529150bo254$529409b3o$529409bo$529410bo254$529660b3o$529660bo
$529661bo254$529917b2o$529916b2o$529918bo254$530183b2o$530182b2o$
530184bo254$530426b3o$530426bo$530427bo254$530674b3o$530674bo$530675bo
254$530939b3o$530939bo$530940bo254$531190b3o$531190bo$531191bo254$
531454b3o$531454bo$531455bo254$531722b3o$531722bo$531723bo254$531954b
3o$531954bo$531955bo254$532224b3o$532224bo$532225bo254$532466b3o$
532466bo$532467bo254$532714b3o$532714bo$532715bo254$532980b2o$532979b
2o$532981bo254$533230b3o$533230bo$533231bo254$533494b3o$533494bo$
533495bo254$533754b3o$533754bo$533755bo254$534008b3o$534008bo$534009bo
254$534259b3o$534259bo$534260bo254$534522b3o$534522bo$534523bo254$
534777b3o$534777bo$534778bo254$535026b3o$535026bo$535027bo254$535291b
3o$535291bo$535292bo254$535542b3o$535542bo$535543bo254$535806b3o$
535806bo$535807bo254$536066b3o$536066bo$536067bo254$536319b3o$536319bo
$536320bo254$536571b2o$536570b2o$536572bo254$536826b3o$536826bo$
536827bo254$537082b3o$537082bo$537083bo254$537331b3o$537331bo$537332bo
254$537597b2o$537596b2o$537598bo254$537847b3o$537847bo$537848bo254$
538111b3o$538111bo$538112bo254$538371b3o$538371bo$538372bo254$538625b
3o$538625bo$538626bo254$538879b2o$538878b2o$538880bo254$539132b3o$
539132bo$539133bo254$539386b3o$539386bo$539387bo254$539635b3o$539635bo
$539636bo254$539901b2o$539900b2o$539902bo254$540151b3o$540151bo$
540152bo254$540415b3o$540415bo$540416bo254$540683b3o$540683bo$540684bo
254$540929b3o$540929bo$540930bo254$541170b3o$541170bo$541171bo254$
541418b3o$541418bo$541419bo254$541684b2o$541683b2o$541685bo254$541934b
3o$541934bo$541935bo254$542198b3o$542198bo$542199bo254$542455b3o$
542455bo$542456bo254$542715b2o$542714b2o$542716bo254$542961b3o$542961b
o$542962bo254$543229b3o$543229bo$543230bo254$543482b3o$543482bo$
543483bo254$543730b3o$543730bo$543731bo254$543996b2o$543995b2o$543997b
o254$544246b3o$544246bo$544247bo254$544510b3o$544510bo$544511bo254$
544778b3o$544778bo$544779bo254$545024b3o$545024bo$545025bo254$545265b
3o$545265bo$545266bo254$545513b3o$545513bo$545514bo254$545778b3o$
545778bo$545779bo254$546029b3o$546029bo$546030bo254$546293b3o$546293bo
$546294bo254$546560b3o$546560bo$546561bo254$546809b3o$546809bo$546810b
o254$547055b3o$547055bo$547056bo254$547326b3o$547326bo$547327bo254$
547577b3o$547577bo$547578bo254$547825b3o$547825bo$547826bo254$548090b
3o$548090bo$548091bo254$548341b3o$548341bo$548342bo254$548605b3o$
548605bo$548606bo254$548865b3o$548865bo$548866bo254$549116b3o$549116bo
$549117bo254$549373b2o$549372b2o$549374bo254$549624b3o$549624bo$
549625bo254$549885b3o$549885bo$549886bo254$550133b3o$550133bo$550134bo
254$550399b2o$550398b2o$550400bo254$550649b3o$550649bo$550650bo254$
550913b3o$550913bo$550914bo254$551173b3o$551173bo$551174bo254$551426b
3o$551426bo$551427bo254$551687b3o$551687bo$551688bo254$551936b3o$
551936bo$551937bo254$552184b3o$552184bo$552185bo254$552433b3o$552433bo
$552434bo254$552699b2o$552698b2o$552700bo254$552949b3o$552949bo$
552950bo254$553213b3o$553213bo$553214bo254$553473b3o$553473bo$553474bo
254$553727b3o$553727bo$553728bo254$553978b3o$553978bo$553979bo254$
554232b3o$554232bo$554233bo254$554489b3o$554489bo$554490bo254$554737b
3o$554737bo$554738bo254$555003b2o$555002b2o$555004bo254$555253b3o$
555253bo$555254bo254$555517b3o$555517bo$555518bo254$555777b3o$555777bo
$555778bo254$556028b3o$556028bo$556029bo254$556297b3o$556297bo$556298b
o254$556530b2o$556529b2o$556531bo254$556793b3o$556793bo$556794bo254$
557042b3o$557042bo$557043bo254$557308b2o$557307b2o$557309bo254$557558b
3o$557558bo$557559bo254$557822b3o$557822bo$557823bo254$558083b3o$
558083bo$558084bo254$558324b2o$558323b2o$558325bo254$558578b3o$558578b
o$558579bo254$558849b2o$558848b2o$558850bo254$559099b3o$559099bo$
559100bo254$559347b3o$559347bo$559348bo254$559613b2o$559612b2o$559614b
o254$559863b3o$559863bo$559864bo254$560127b3o$560127bo$560128bo254$
560388b3o$560388bo$560389bo254$560642b3o$560642bo$560643bo254$560895b
3o$560895bo$560896bo254$561134b3o$561134bo$561135bo254$561382b3o$
561382bo$561383bo254$561648b2o$561647b2o$561649bo254$561898b3o$561898b
o$561899bo254$562162b3o$562162bo$562163bo254$562416b3o$562416bo$
562417bo254$562680b3o$562680bo$562681bo254$562941b3o$562941bo$562942bo
254$563190b2o$563189b2o$563191bo254$563451b3o$563451bo$563452bo254$
563699b3o$563699bo$563700bo254$563965b2o$563964b2o$563966bo254$564215b
3o$564215bo$564216bo254$564479b3o$564479bo$564480bo254$564747b3o$
564747bo$564748bo254$564993b3o$564993bo$564994bo254$565234b3o$565234bo
$565235bo254$565482b3o$565482bo$565483bo254$565747b3o$565747bo$565748b
o254$565998b3o$565998bo$565999bo254$566262b3o$566262bo$566263bo254$
566522b3o$566522bo$566523bo254$566776b3o$566776bo$566777bo254$567027b
3o$567027bo$567028bo254$567290b3o$567290bo$567291bo254$567545b3o$
567545bo$567546bo254$567794b3o$567794bo$567795bo254$568059b3o$568059bo
$568060bo254$568310b3o$568310bo$568311bo254$568574b3o$568574bo$568575b
o254$568834b3o$568834bo$568835bo254$569088b3o$569088bo$569089bo254$
569339b3o$569339bo$569340bo254$569593b3o$569593bo$569594bo254$569850b
3o$569850bo$569851bo254$570098b3o$570098bo$570099bo254$570364b2o$
570363b2o$570365bo254$570614b3o$570614bo$570615bo254$570878b3o$570878b
o$570879bo254$571136b3o$571136bo$571137bo254$571390b2o$571389b2o$
571391bo254$571639b3o$571639bo$571640bo254$571909b3o$571909bo$571910bo
254$572155b3o$572155bo$572156bo254$572404b3o$572404bo$572405bo254$
572670b2o$572669b2o$572671bo254$572920b3o$572920bo$572921bo254$573184b
3o$573184bo$573185bo254$573444b3o$573444bo$573445bo254$573695b3o$
573695bo$573696bo254$573952b2o$573951b2o$573953bo254$574205b3o$574205b
o$574206bo254$574457b3o$574457bo$574458bo254$574706b3o$574706bo$
574707bo254$574972b2o$574971b2o$574973bo254$575222b3o$575222bo$575223b
o254$575486b3o$575486bo$575487bo254$575753b3o$575753bo$575754bo254$
576002b3o$576002bo$576003bo254$576248b3o$576248bo$576249bo254$576519b
3o$576519bo$576520bo254$576761b3o$576761bo$576762bo254$577010b3o$
577010bo$577011bo254$577275b3o$577275bo$577276bo254$577526b3o$577526bo
$577527bo254$577790b3o$577790bo$577791bo254$578050b3o$578050bo$578051b
o254$578306b3o$578306bo$578307bo254$578549b2o$578548b2o$578550bo254$
578824b2o$578823b2o$578825bo254$579067b3o$579067bo$579068bo254$579315b
3o$579315bo$579316bo254$579580b3o$579580bo$579581bo254$579831b3o$
579831bo$579832bo254$580095b3o$580095bo$580096bo254$580349b3o$580349bo
$580350bo254$580601b3o$580601bo$580602bo254$580866b3o$580866bo$580867b
o254$581111b3o$581111bo$581112bo254$581367b3o$581367bo$581368bo254$
581616b3o$581616bo$581617bo254$581881b3o$581881bo$581882bo254$582132b
3o$582132bo$582133bo254$582396b3o$582396bo$582397bo254$582656b3o$
582656bo$582657bo254$582909b3o$582909bo$582910bo254$583163b3o$583163bo
$583164bo254$583417b3o$583417bo$583418bo254$583666b3o$583666bo$583667b
o254$583931b3o$583931bo$583932bo254$584182b3o$584182bo$584183bo254$
584446b3o$584446bo$584447bo254$584703b3o$584703bo$584704bo254$584955b
2o$584954b2o$584956bo254$585219b2o$585218b2o$585220bo254$585466b3o$
585466bo$585467bo254$585715b3o$585715bo$585716bo254$585981b2o$585980b
2o$585982bo254$586231b3o$586231bo$586232bo254$586495b3o$586495bo$
586496bo254$586756b3o$586756bo$586757bo254$587004b3o$587004bo$587005bo
254$587255b3o$587255bo$587256bo254$587520b2o$587519b2o$587521bo254$
587769b3o$587769bo$587770bo254$588018b3o$588018bo$588019bo254$588284b
2o$588283b2o$588285bo254$588534b3o$588534bo$588535bo254$588798b3o$
588798bo$588799bo254$589058b3o$589058bo$589059bo254$589312b3o$589312bo
$589313bo254$589566b2o$589565b2o$589567bo254$589819b3o$589819bo$
589820bo254$590073b3o$590073bo$590074bo254$590322b3o$590322bo$590323bo
254$590587b3o$590587bo$590588bo254$590838b3o$590838bo$590839bo254$
591102b3o$591102bo$591103bo254$591362b3o$591362bo$591363bo254$591615b
3o$591615bo$591616bo254$591867b2o$591866b2o$591868bo254$592122b3o$
592122bo$592123bo254$592378b3o$592378bo$592379bo254$592627b3o$592627bo
$592628bo254$592892b3o$592892bo$592893bo254$593143b3o$593143bo$593144b
o254$593407b3o$593407bo$593408bo254$593672b3o$593672bo$593673bo254$
593913b3o$593913bo$593914bo254$594192b2o$594191b2o$594193bo254$594433b
2o$594432b2o$594434bo254$594686b2o$594685b2o$594687bo254$594938b3o$
594938bo$594939bo254$595187b3o$595187bo$595188bo254$595453b2o$595452b
2o$595454bo254$595703b3o$595703bo$595704bo254$595967b3o$595967bo$
595968bo254$596228b3o$596228bo$596229bo254$596492b3o$596492bo$596493bo
254$596738b2o$596737b2o$596739bo254$596989b2o$596988b2o$596990bo254$
597228b3o$597228bo$597229bo254$597497b3o$597497bo$597498bo254$597746b
3o$597746bo$597747bo254$598012b2o$598011b2o$598013bo254$598262b3o$
598262bo$598263bo254$598526b3o$598526bo$598527bo254$598786b3o$598786bo
$598787bo254$599039b3o$599039bo$599040bo254$599297b2o$599296b2o$
599298bo254$599545b3o$599545bo$599546bo254$599794b3o$599794bo$599795bo
254$600060b2o$600059b2o$600061bo254$600310b3o$600310bo$600311bo254$
600574b3o$600574bo$600575bo254$600841b3o$600841bo$600842bo254$601090b
3o$601090bo$601091bo254$601331b3o$601331bo$601332bo254$601608b2o$
601607b2o$601609bo254$601851b3o$601851bo$601852bo254$602099b3o$602099b
o$602100bo254$602365b2o$602364b2o$602366bo254$602615b3o$602615bo$
602616bo254$602879b3o$602879bo$602880bo254$603147b3o$603147bo$603148bo
254$603379b3o$603379bo$603380bo254$603649b3o$603649bo$603650bo254$
603891b3o$603891bo$603892bo254$604139b3o$604139bo$604140bo254$604405b
2o$604404b2o$604406bo254$604655b3o$604655bo$604656bo254$604919b3o$
604919bo$604920bo254$605176b3o$605176bo$605177bo254$605432b2o$605431b
2o$605433bo254$605685b2o$605684b2o$605686bo254$605940b2o$605939b2o$
605941bo254$606195b2o$606194b2o$606196bo254$606470b3o$606470bo$606471b
o254$606718b3o$606718bo$606719bo254$606983b3o$606983bo$606984bo254$
607241b3o$607241bo$607242bo254$607489b3o$607489bo$607490bo254$607754b
3o$607754bo$607755bo254$607986b3o$607986bo$607987bo254$608256b3o$
608256bo$608257bo254$608498b3o$608498bo$608499bo254$608746b3o$608746bo
$608747bo254$609011b3o$609011bo$609012bo254$609262b3o$609262bo$609263b
o254$609526b3o$609526bo$609527bo254$609780b3o$609780bo$609781bo254$
610032b3o$610032bo$610033bo254$610286b3o$610286bo$610287bo254$610560b
2o$610559b2o$610561bo254$610822b3o$610822bo$610823bo254$611070b3o$
611070bo$611071bo254$611335b3o$611335bo$611336bo254$611593b3o$611593bo
$611594bo254$611841b3o$611841bo$611842bo254$612106b3o$612106bo$612107b
o254$612338b3o$612338bo$612339bo254$612608b3o$612608bo$612609bo254$
612850b3o$612850bo$612851bo254$613098b3o$613098bo$613099bo254$613364b
2o$613363b2o$613365bo254$613614b3o$613614bo$613615bo254$613878b3o$
613878bo$613879bo254$614132b3o$614132bo$614133bo254$614388b3o$614388bo
$614389bo254$614643b3o$614643bo$614644bo254$614914b2o$614913b2o$
614915bo254$615163b3o$615163bo$615164bo254$615411b3o$615411bo$615412bo
254$615677b2o$615676b2o$615678bo254$615927b3o$615927bo$615928bo254$
616191b3o$616191bo$616192bo254$616439b3o$616439bo$616440bo254$616702b
3o$616702bo$616703bo254$616973b3o$616973bo$616974bo254$617210b2o$
617209b2o$617211bo254$617477b3o$617477bo$617478bo254$617726b3o$617726b
o$617727bo254$617991b3o$617991bo$617992bo254$618249b3o$618249bo$
618250bo254$618497b3o$618497bo$618498bo254$618762b3o$618762bo$618763bo
254$618994b3o$618994bo$618995bo254$619264b3o$619264bo$619265bo254$
619506b3o$619506bo$619507bo254$619754b3o$619754bo$619755bo254$620019b
3o$620019bo$620020bo254$620270b3o$620270bo$620271bo254$620534b3o$
620534bo$620535bo254$620801b3o$620801bo$620802bo254$621050b3o$621050bo
$621051bo254$621296b3o$621296bo$621297bo254$621567b3o$621567bo$621568b
o254$621818b3o$621818bo$621819bo254$622066b3o$622066bo$622067bo254$
622331b3o$622331bo$622332bo254$622582b3o$622582bo$622583bo254$622846b
3o$622846bo$622847bo254$623103b3o$623103bo$623104bo254$623355b2o$
623354b2o$623356bo254$623619b2o$623618b2o$623620bo254$623866b3o$
623866bo$623867bo254$624115b3o$624115bo$624116bo254$624380b3o$624380bo
$624381bo254$624631b3o$624631bo$624632bo254$624895b3o$624895bo$624896b
o254$625149b3o$625149bo$625150bo254$625410b2o$625409b2o$625411bo254$
625669b3o$625669bo$625670bo254$625917b3o$625917bo$625918bo254$626182b
3o$626182bo$626183bo254$626440b3o$626440bo$626441bo254$626688b3o$
626688bo$626689bo254$626939b3o$626939bo$626940bo254$627200b2o$627199b
2o$627201bo254$627449b3o$627449bo$627450bo254$627705b3o$627705bo$
627706bo254$627954b3o$627954bo$627955bo254$628219b3o$628219bo$628220bo
254$628470b3o$628470bo$628471bo254$628734b3o$628734bo$628735bo254$
628995b3o$628995bo$628996bo254$629236b2o$629235b2o$629237bo254$629505b
2o$629504b2o$629506bo254$629756b3o$629756bo$629757bo254$630004b3o$
630004bo$630005bo254$630270b2o$630269b2o$630271bo254$630520b3o$630520b
o$630521bo254$630784b3o$630784bo$630785bo254$631038b3o$631038bo$
631039bo254$631308b2o$631307b2o$631309bo254$631558b3o$631558bo$631559b
o254$631818b3o$631818bo$631819bo254$632072b3o$632072bo$632073bo254$
632323b3o$632323bo$632324bo254$632567b3o$632567bo$632568bo254$632822b
3o$632822bo$632823bo254$633070b3o$633070bo$633071bo254$633335b3o$
633335bo$633336bo254$633586b3o$633586bo$633587bo254$633850b3o$633850bo
$633851bo254$634110b3o$634110bo$634111bo254$634363b3o$634363bo$634364b
o254$634623b3o$634623bo$634624bo254$634873b2o$634872b2o$634874bo254$
635128b3o$635128bo$635129bo254$635377b3o$635377bo$635378bo254$635642b
3o$635642bo$635643bo254$635893b3o$635893bo$635894bo254$636157b3o$
636157bo$636158bo254$636424b3o$636424bo$636425bo254$636673b3o$636673bo
$636674bo254$636919b3o$636919bo$636920bo254$637190b3o$637190bo$637191b
o254$637432b3o$637432bo$637433bo254$637681b3o$637681bo$637682bo254$
637946b3o$637946bo$637947bo254$638197b3o$638197bo$638198bo254$638461b
3o$638461bo$638462bo254$638721b3o$638721bo$638722bo254$638972b3o$
638972bo$638973bo254$639229b2o$639228b2o$639230bo254$639495b2o$639494b
2o$639496bo254$639738b3o$639738bo$639739bo254$639986b3o$639986bo$
639987bo254$640251b3o$640251bo$640252bo254$640502b3o$640502bo$640503bo
254$640766b3o$640766bo$640767bo254$641026b3o$641026bo$641027bo254$
641277b3o$641277bo$641278bo254$641529b2o$641528b2o$641530bo254$641803b
3o$641803bo$641804bo254$642061b2o$642060b2o$642062bo254$642311b3o$
642311bo$642312bo254$642551b3o$642551bo$642552bo254$642800b3o$642800bo
$642801bo254$643066b2o$643065b2o$643067bo254$643316b3o$643316bo$
643317bo254$643580b3o$643580bo$643581bo254$643840b3o$643840bo$643841bo
254$644096b3o$644096bo$644097bo254$644339b2o$644338b2o$644340bo254$
644614b2o$644613b2o$644615bo254$644857b3o$644857bo$644858bo254$645105b
3o$645105bo$645106bo254$645371b2o$645370b2o$645372bo254$645621b3o$
645621bo$645622bo254$645885b3o$645885bo$645886bo254$646145b3o$646145bo
$646146bo254$646399b3o$646399bo$646400bo254$646653b2o$646652b2o$
646654bo254$646906b3o$646906bo$646907bo254$647160b3o$647160bo$647161bo
254$647409b3o$647409bo$647410bo254$647674b3o$647674bo$647675bo254$
647925b3o$647925bo$647926bo254$648189b3o$648189bo$648190bo254$648449b
3o$648449bo$648450bo254$648702b3o$648702bo$648703bo254$648954b2o$
648953b2o$648955bo254$649209b3o$649209bo$649210bo254$649465b3o$649465b
o$649466bo254$649714b3o$649714bo$649715bo254$649979b3o$649979bo$
649980bo254$650230b3o$650230bo$650231bo254$650494b3o$650494bo$650495bo
254$650759b3o$650759bo$650760bo254$651000b3o$651000bo$651001bo254$
651279b2o$651278b2o$651280bo254$651520b2o$651519b2o$651521bo254$
651773b2o$651772b2o$651774bo254$652025b3o$652025bo$652026bo254$652274b
3o$652274bo$652275bo254$652540b2o$652539b2o$652541bo254$652790b3o$
652790bo$652791bo254$653054b3o$653054bo$653055bo254$653314b3o$653314bo
$653315bo254$653570b3o$653570bo$653571bo254$653832b2o$653831b2o$
653833bo254$654090b3o$654090bo$654091bo254$654345b3o$654345bo$654346bo
254$654586b2o$654585b2o$654587bo254$654842b3o$654842bo$654843bo254$
655090b3o$655090bo$655091bo254$655355b3o$655355bo$655356bo254$655606b
3o$655606bo$655607bo254$655870b3o$655870bo$655871bo254$656135b3o$
656135bo$656136bo254$656379b3o$656379bo$656380bo254$656639b2o$656638b
2o$656640bo254$656892b3o$656892bo$656893bo254$657138b3o$657138bo$
657139bo254$657401b3o$657401bo$657402bo254$657649b3o$657649bo$657650bo
254$657914b3o$657914bo$657915bo254$658165b3o$658165bo$658166bo254$
658429b3o$658429bo$658430bo254$658689b3o$658689bo$658690bo254$658940b
3o$658940bo$658941bo254$659197b2o$659196b2o$659198bo254$659463b2o$
659462b2o$659464bo254$659706b3o$659706bo$659707bo254$659954b3o$659954b
o$659955bo254$660219b3o$660219bo$660220bo254$660470b3o$660470bo$
660471bo254$660734b3o$660734bo$660735bo254$661002b3o$661002bo$661003bo
254$661234b3o$661234bo$661235bo254$661504b3o$661504bo$661505bo254$
661746b3o$661746bo$661747bo254$661994b3o$661994bo$661995bo254$662260b
2o$662259b2o$662261bo254$662510b3o$662510bo$662511bo254$662774b3o$
662774bo$662775bo254$663022b3o$663022bo$663023bo254$663285b3o$663285bo
$663286bo254$663551b3o$663551bo$663552bo254$663799b3o$663799bo$663800b
o254$664052b3o$664052bo$664053bo254$664315b3o$664315bo$664316bo254$
664563b3o$664563bo$664564bo254$664828b3o$664828bo$664829bo254$665079b
3o$665079bo$665080bo254$665343b3o$665343bo$665344bo254$665603b3o$
665603bo$665604bo254$665859b3o$665859bo$665860bo254$666127b2o$666126b
2o$666128bo254$666361b3o$666361bo$666362bo254$666616b3o$666616bo$
666617bo254$666865b3o$666865bo$666866bo254$667130b3o$667130bo$667131bo
254$667381b3o$667381bo$667382bo254$667645b3o$667645bo$667646bo254$
667899b3o$667899bo$667900bo254$668160b2o$668159b2o$668161bo254$668420b
3o$668420bo$668421bo254$668666b3o$668666bo$668667bo254$668922b3o$
668922bo$668923bo254$669171b3o$669171bo$669172bo254$669436b3o$669436bo
$669437bo254$669687b3o$669687bo$669688bo254$669951b3o$669951bo$669952b
o254$670212b3o$670212bo$670213bo254$670460b3o$670460bo$670461bo254$
670711b3o$670711bo$670712bo254$670973b2o$670972b2o$670974bo254$671224b
3o$671224bo$671225bo254$671473b3o$671473bo$671474bo254$671739b2o$
671738b2o$671740bo254$671989b3o$671989bo$671990bo254$672253b3o$672253b
o$672254bo254$672513b3o$672513bo$672514bo254$672764b3o$672764bo$
672765bo254$673021b2o$673020b2o$673022bo254$673287b2o$673286b2o$
673288bo254$673530b3o$673530bo$673531bo254$673778b3o$673778bo$673779bo
254$674044b2o$674043b2o$674045bo254$674294b3o$674294bo$674295bo254$
674558b3o$674558bo$674559bo254$674819b3o$674819bo$674820bo254$675084b
2o$675083b2o$675085bo254$675339b2o$675338b2o$675340bo254$675589b3o$
675589bo$675590bo254$675841b2o$675840b2o$675842bo254$676101b3o$676101b
o$676102bo254$676344b3o$676344bo$676345bo254$676592b3o$676592bo$
676593bo254$676857b3o$676857bo$676858bo254$677108b3o$677108bo$677109bo
254$677372b3o$677372bo$677373bo254$677626b3o$677626bo$677627bo254$
677881b2o$677880b2o$677882bo254$678136b3o$678136bo$678137bo254$678387b
2o$678386b2o$678388bo254$678647b3o$678647bo$678648bo254$678904b3o$
678904bo$678905bo254$679152b3o$679152bo$679153bo254$679417b3o$679417bo
$679418bo254$679668b3o$679668bo$679669bo254$679932b3o$679932bo$679933b
o254$680179b3o$680179bo$680180bo254$680445b3o$680445bo$680446bo254$
680716b3o$680716bo$680717bo254$680965b3o$680965bo$680966bo254$681230b
3o$681230bo$681231bo254$681488b3o$681488bo$681489bo254$681736b3o$
681736bo$681737bo254$681993b3o$681993bo$681994bo254$682247b3o$682247bo
$682248bo254$682503b2o$682502b2o$682504bo254$682756b3o$682756bo$
682757bo254$683005b3o$683005bo$683006bo254$683270b3o$683270bo$683271bo
254$683528b3o$683528bo$683529bo254$683776b3o$683776bo$683777bo254$
684034b3o$684034bo$684035bo254$684288b2o$684287b2o$684289bo254$684540b
3o$684540bo$684541bo254$684788b3o$684788bo$684789bo254$685053b3o$
685053bo$685054bo254$685304b3o$685304bo$685305bo254$685568b3o$685568bo
$685569bo254$685829b3o$685829bo$685830bo254$686094b2o$686093b2o$
686095bo254$686349b2o$686348b2o$686350bo254$686599b3o$686599bo$686600b
o254$686851b2o$686850b2o$686852bo254$687111b3o$687111bo$687112bo254$
687354b3o$687354bo$687355bo254$687602b3o$687602bo$687603bo254$687867b
3o$687867bo$687868bo254$688118b3o$688118bo$688119bo254$688382b3o$
688382bo$688383bo254$688643b3o$688643bo$688644bo254$688891b3o$688891bo
$688892bo254$689142b3o$689142bo$689143bo254$689404b2o$689403b2o$
689405bo254$689655b3o$689655bo$689656bo254$689904b3o$689904bo$689905bo
254$690169b3o$690169bo$690170bo254$690420b3o$690420bo$690421bo254$
690684b3o$690684bo$690685bo254$690942b3o$690942bo$690943bo254$691193b
3o$691193bo$691194bo254$691444b3o$691444bo$691445bo254$691715b3o$
691715bo$691716bo254$691958b3o$691958bo$691959bo254$692218b3o$692218bo
$692219bo254$692466b3o$692466bo$692467bo254$692731b3o$692731bo$692732b
o254$692982b3o$692982bo$692983bo254$693246b3o$693246bo$693247bo254$
693496b3o$693496bo$693497bo254$693767b3o$693767bo$693768bo254$694005b
3o$694005bo$694006bo254$694258b3o$694258bo$694259bo254$694524b3o$
694524bo$694525bo254$694772b3o$694772bo$694773bo254$695037b3o$695037bo
$695038bo254$695288b3o$695288bo$695289bo254$695552b3o$695552bo$695553b
o254$695820b3o$695820bo$695821bo254$696052b3o$696052bo$696053bo254$
696322b3o$696322bo$696323bo254$696564b3o$696564bo$696565bo254$696812b
3o$696812bo$696813bo254$697078b2o$697077b2o$697079bo254$697328b3o$
697328bo$697329bo254$697592b3o$697592bo$697593bo254$697852b3o$697852bo
$697853bo254$698108b3o$698108bo$698109bo254$698365b2o$698364b2o$
698366bo254$698611b2o$698610b2o$698612bo254$698887b3o$698887bo$698888b
o254$699135b3o$699135bo$699136bo254$699401b2o$699400b2o$699402bo254$
699658b3o$699658bo$699659bo254$699906b3o$699906bo$699907bo254$700151b
3o$700151bo$700152bo254$700414b3o$700414bo$700415bo254$700668b2o$
700667b2o$700669bo254$700940b3o$700940bo$700941bo254$701177b3o$701177b
o$701178bo254$701426b3o$701426bo$701427bo254$701692b2o$701691b2o$
701693bo254$701942b3o$701942bo$701943bo254$702206b3o$702206bo$702207bo
254$702460b3o$702460bo$702461bo254$702712b3o$702712bo$702713bo254$
702977b3o$702977bo$702978bo254$703222b3o$703222bo$703223bo254$703478b
3o$703478bo$703479bo254$703727b3o$703727bo$703728bo254$703993b2o$
703992b2o$703994bo254$704243b3o$704243bo$704244bo254$704507b3o$704507b
o$704508bo254$704754b3o$704754bo$704755bo254$705034b3o$705034bo$
705035bo254$705276b3o$705276bo$705277bo254$705546b3o$705546bo$705547bo
254$705795b3o$705795bo$705796bo254$706061b2o$706060b2o$706062bo254$
706318b3o$706318bo$706319bo254$706566b3o$706566bo$706567bo254$706817b
3o$706817bo$706818bo254$707078b2o$707077b2o$707079bo254$707327b3o$
707327bo$707328bo254$707582b3o$707582bo$707583bo254$707847b3o$707847bo
$707848bo254$708095b3o$708095bo$708096bo254$708360b3o$708360bo$708361b
o254$708618b3o$708618bo$708619bo254$708866b3o$708866bo$708867bo254$
709121b3o$709121bo$709122bo254$709382b2o$709381b2o$709383bo254$709646b
2o$709645b2o$709647bo254$709880b2o$709879b2o$709881bo254$710139b2o$
710138b2o$710140bo254$710394b3o$710394bo$710395bo254$710642b3o$710642b
o$710643bo254$710907b3o$710907bo$710908bo254$711158b3o$711158bo$
711159bo254$711422b3o$711422bo$711423bo254$711679b3o$711679bo$711680bo
254$711931b2o$711930b2o$711932bo254$712195b2o$712194b2o$712196bo254$
712442b3o$712442bo$712443bo254$712691b3o$712691bo$712692bo254$712956b
3o$712956bo$712957bo254$713207b3o$713207bo$713208bo254$713471b3o$
713471bo$713472bo254$713731b3o$713731bo$713732bo254$713987b3o$713987bo
$713988bo254$714244b2o$714243b2o$714245bo254$714490b2o$714489b2o$
714491bo254$714757b3o$714757bo$714758bo254$715006b3o$715006bo$715007bo
254$715271b3o$715271bo$715272bo254$715529b3o$715529bo$715530bo254$
715777b3o$715777bo$715778bo254$716041b3o$716041bo$716042bo254$716290b
3o$716290bo$716291bo254$716536b3o$716536bo$716537bo254$716807b3o$
716807bo$716808bo254$717049b3o$717049bo$717050bo254$717298b3o$717298bo
$717299bo254$717563b3o$717563bo$717564bo254$717814b3o$717814bo$717815b
o254$718078b3o$718078bo$718079bo254$718338b3o$718338bo$718339bo254$
718592b3o$718592bo$718593bo254$718855b2o$718854b2o$718856bo254$719107b
2o$719106b2o$719108bo254$719358b2o$719357b2o$719359bo254$719609b3o$
719609bo$719610bo254$719864b3o$719864bo$719865bo254$720113b3o$720113bo
$720114bo254$720379b2o$720378b2o$720380bo254$720629b3o$720629bo$
720630bo254$720893b3o$720893bo$720894bo254$721153b3o$721153bo$721154bo
254$721411b3o$721411bo$721412bo254$721666b3o$721666bo$721667bo254$
721925b3o$721925bo$721926bo254$722189b3o$722189bo$722190bo254$722447b
3o$722447bo$722448bo254$722703b3o$722703bo$722704bo254$722952b3o$
722952bo$722953bo254$723217b3o$723217bo$723218bo254$723475b3o$723475bo
$723476bo254$723723b3o$723723bo$723724bo254$723980b3o$723980bo$723981b
o254$724236b3o$724236bo$724237bo254$724502b3o$724502bo$724503bo254$
724737b3o$724737bo$724738bo254$724985b3o$724985bo$724986bo254$725234b
3o$725234bo$725235bo254$725499b3o$725499bo$725500bo254$725750b3o$
725750bo$725751bo254$726014b3o$726014bo$726015bo254$726282b3o$726282bo
$726283bo254$726514b3o$726514bo$726515bo254$726784b3o$726784bo$726785b
o254$727026b3o$727026bo$727027bo254$727274b3o$727274bo$727275bo254$
727539b3o$727539bo$727540bo254$727790b3o$727790bo$727791bo254$728054b
3o$728054bo$728055bo254$728308b3o$728308bo$728309bo254$728564b3o$
728564bo$728565bo254$728819b3o$728819bo$728820bo254$729090b2o$729089b
2o$729091bo254$729339b3o$729339bo$729340bo254$729587b3o$729587bo$
729588bo254$729852b3o$729852bo$729853bo254$730103b3o$730103bo$730104bo
254$730367b3o$730367bo$730368bo254$730634b3o$730634bo$730635bo254$
730883b3o$730883bo$730884bo254$731129b3o$731129bo$731130bo254$731400b
3o$731400bo$731401bo254$731642b3o$731642bo$731643bo254$731891b3o$
731891bo$731892bo254$732156b3o$732156bo$732157bo254$732407b3o$732407bo
$732408bo254$732671b3o$732671bo$732672bo254$732924b3o$732924bo$732925b
o254$733168b3o$733168bo$733169bo254$733460b2o$733459b2o$733461bo254$
733692b3o$733692bo$733693bo254$733959b2o$733958b2o$733960bo254$734220b
2o$734219b2o$734221bo254$734465b3o$734465bo$734466bo254$734732b3o$
734732bo$734733bo254$735003b2o$735002b2o$735004bo254$735258b2o$735257b
2o$735259bo254$735513b2o$735512b2o$735514bo254$735747b2o$735746b2o$
735748bo254$736018b2o$736017b2o$736019bo254$736256b2o$736255b2o$
736257bo254$736517b3o$736517bo$736518bo254$736765b3o$736765bo$736766bo
254$737030b3o$737030bo$737031bo254$737288b3o$737288bo$737289bo254$
737536b3o$737536bo$737537bo254$737793b3o$737793bo$737794bo254$738044b
3o$738044bo$738045bo254$738301b2o$738300b2o$738302bo254$738567b2o$
738566b2o$738568bo254$738810b3o$738810bo$738811bo254$739058b3o$739058b
o$739059bo254$739323b3o$739323bo$739324bo254$739574b3o$739574bo$
739575bo254$739838b3o$739838bo$739839bo254$740105b3o$740105bo$740106bo
254$740354b3o$740354bo$740355bo254$740600b3o$740600bo$740601bo254$
740871b3o$740871bo$740872bo254$741113b3o$741113bo$741114bo254$741362b
3o$741362bo$741363bo254$741627b3o$741627bo$741628bo254$741878b3o$
741878bo$741879bo254$742142b3o$742142bo$742143bo254$742402b3o$742402bo
$742403bo254$742655b3o$742655bo$742656bo254$742907b2o$742906b2o$
742908bo254$743169b3o$743169bo$743170bo254$743416b3o$743416bo$743417bo
254$743665b3o$743665bo$743666bo254$743931b2o$743930b2o$743932bo254$
744181b3o$744181bo$744182bo254$744445b3o$744445bo$744446bo254$744705b
3o$744705bo$744706bo254$744958b3o$744958bo$744959bo254$745216b2o$
745215b2o$745217bo254$745464b3o$745464bo$745465bo254$745713b3o$745713b
o$745714bo254$745979b2o$745978b2o$745980bo254$746229b3o$746229bo$
746230bo254$746493b3o$746493bo$746494bo254$746746b3o$746746bo$746747bo
254$747026b3o$747026bo$747027bo254$747277b2o$747276b2o$747278bo254$
747512b2o$747511b2o$747513bo254$747769b3o$747769bo$747770bo254$748018b
3o$748018bo$748019bo254$748283b3o$748283bo$748284bo254$748534b3o$
748534bo$748535bo254$748798b3o$748798bo$748799bo254$749058b3o$749058bo
$749059bo254$749314b3o$749314bo$749315bo254$749571b2o$749570b2o$
749572bo254$749837b2o$749836b2o$749838bo254$750072b3o$750072bo$750073b
o254$750321b3o$750321bo$750322bo254$750587b2o$750586b2o$750588bo254$
750837b3o$750837bo$750838bo254$751101b3o$751101bo$751102bo254$751369b
3o$751369bo$751370bo254$751613b3o$751613bo$751614bo254$751862b3o$
751862bo$751863bo254$752110b3o$752110bo$752111bo254$752389b3o$752389bo
$752390bo254$752630b3o$752630bo$752631bo254$752890b3o$752890bo$752891b
o254$753138b3o$753138bo$753139bo254$753403b3o$753403bo$753404bo254$
753654b3o$753654bo$753655bo254$753918b3o$753918bo$753919bo254$754172b
3o$754172bo$754173bo254$754442b2o$754441b2o$754443bo254$754690b3o$
754690bo$754691bo254$754935b2o$754934b2o$754936bo254$755186b3o$755186b
o$755187bo254$755449b2o$755448b2o$755450bo254$755699b3o$755699bo$
755700bo254$755960b3o$755960bo$755961bo254$756209b3o$756209bo$756210bo
254$756475b2o$756474b2o$756476bo254$756725b3o$756725bo$756726bo254$
756989b3o$756989bo$756990bo254$757256b3o$757256bo$757257bo254$757505b
3o$757505bo$757506bo254$757746b3o$757746bo$757747bo254$758023b2o$
758022b2o$758024bo254$758266b3o$758266bo$758267bo254$758514b3o$758514b
o$758515bo254$758779b3o$758779bo$758780bo254$759030b3o$759030bo$
759031bo254$759294b3o$759294bo$759295bo254$759562b3o$759562bo$759563bo
254$759794b3o$759794bo$759795bo254$760064b3o$760064bo$760065bo254$
760306b3o$760306bo$760307bo254$760554b3o$760554bo$760555bo254$760820b
2o$760819b2o$760821bo254$761070b3o$761070bo$761071bo254$761334b3o$
761334bo$761335bo254$761588b3o$761588bo$761589bo254$761844b3o$761844bo
$761845bo254$762099b3o$762099bo$762100bo254$762370b2o$762369b2o$
762371bo254$762619b3o$762619bo$762620bo254$762867b3o$762867bo$762868bo
254$763133b2o$763132b2o$763134bo254$763383b3o$763383bo$763384bo254$
763647b3o$763647bo$763648bo254$763897b3o$763897bo$763898bo254$764168b
3o$764168bo$764169bo254$764414b2o$764413b2o$764415bo254$764677b3o$
764677bo$764678bo254$764925b3o$764925bo$764926bo254$765190b3o$765190bo
$765191bo254$765448b3o$765448bo$765449bo254$765696b3o$765696bo$765697b
o254$765953b3o$765953bo$765954bo254$766207b3o$766207bo$766208bo254$
766458b3o$766458bo$766459bo254$766712b3o$766712bo$766713bo254$766969b
3o$766969bo$766970bo254$767217b3o$767217bo$767218bo254$767483b2o$
767482b2o$767484bo254$767733b3o$767733bo$767734bo254$767997b3o$767997b
o$767998bo254$768257b3o$768257bo$768258bo254$768513b3o$768513bo$
768514bo254$768779b3o$768779bo$768780bo254$769023b3o$769023bo$769024bo
254$769287b3o$769287bo$769288bo254$769535b3o$769535bo$769536bo254$
769800b3o$769800bo$769801bo254$770058b3o$770058bo$770059bo254$770306b
3o$770306bo$770307bo254$770564b3o$770564bo$770565bo254$770812b3o$
770812bo$770813bo254$771063b3o$771063bo$771064bo254$771328b2o$771327b
2o$771329bo254$771577b3o$771577bo$771578bo254$771826b3o$771826bo$
771827bo254$772091b3o$772091bo$772092bo254$772342b3o$772342bo$772343bo
254$772606b3o$772606bo$772607bo254$772871b3o$772871bo$772872bo254$
773119b3o$773119bo$773120bo254$773362b3o$773362bo$773363bo254$773623b
3o$773623bo$773624bo254$773872b3o$773872bo$773873bo254$774120b3o$
774120bo$774121bo254$774386b2o$774385b2o$774387bo254$774636b3o$774636b
o$774637bo254$774900b3o$774900bo$774901bo254$775160b3o$775160bo$
775161bo254$775423b3o$775423bo$775424bo254$775669b3o$775669bo$775670bo
254$775933b3o$775933bo$775934bo254$776185b3o$776185bo$776186bo254$
776434b3o$776434bo$776435bo254$776700b2o$776699b2o$776701bo254$776950b
3o$776950bo$776951bo254$777214b3o$777214bo$777215bo254$777475b3o$
777475bo$777476bo254$777723b3o$777723bo$777724bo254$777974b3o$777974bo
$777975bo254$778239b2o$778238b2o$778240bo254$778488b3o$778488bo$
778489bo254$778737b3o$778737bo$778738bo254$779003b2o$779002b2o$779004b
o254$779253b3o$779253bo$779254bo254$779517b3o$779517bo$779518bo254$
779770b3o$779770bo$779771bo254$780050b3o$780050bo$780051bo254$780301b
2o$780300b2o$780302bo254$780536b2o$780535b2o$780537bo254$780793b3o$
780793bo$780794bo254$781042b3o$781042bo$781043bo254$781308b2o$781307b
2o$781309bo254$781558b3o$781558bo$781559bo254$781822b3o$781822bo$
781823bo254$782089b3o$782089bo$782090bo254$782338b3o$782338bo$782339bo
254$782579b3o$782579bo$782580bo254$782856b2o$782855b2o$782857bo254$
783099b3o$783099bo$783100bo254$783347b3o$783347bo$783348bo254$783612b
3o$783612bo$783613bo254$783863b3o$783863bo$783864bo254$784127b3o$
784127bo$784128bo254$784381b3o$784381bo$784382bo254$784636b2o$784635b
2o$784637bo254$784891b3o$784891bo$784892bo254$785142b2o$785141b2o$
785143bo254$785402b3o$785402bo$785403bo254$785659b3o$785659bo$785660bo
254$785907b3o$785907bo$785908bo254$786172b3o$786172bo$786173bo254$
786423b3o$786423bo$786424bo254$786687b3o$786687bo$786688bo254$786955b
3o$786955bo$786956bo254$787187b3o$787187bo$787188bo254$787457b3o$
787457bo$787458bo254$787699b3o$787699bo$787700bo254$787947b3o$787947bo
$787948bo254$788213b2o$788212b2o$788214bo254$788463b3o$788463bo$
788464bo254$788727b3o$788727bo$788728bo254$788984b3o$788984bo$788985bo
254$789236b2o$789235b2o$789237bo254$789500b2o$789499b2o$789501bo254$
789756b3o$789756bo$789757bo254$790004b3o$790004bo$790005bo254$790270b
2o$790269b2o$790271bo254$790520b3o$790520bo$790521bo254$790784b3o$
790784bo$790785bo254$791044b3o$791044bo$791045bo254$791300b3o$791300bo
$791301bo254$791557b2o$791556b2o$791558bo254$791823b2o$791822b2o$
791824bo254$792058b3o$792058bo$792059bo254$792307b3o$792307bo$792308bo
254$792573b2o$792572b2o$792574bo254$792823b3o$792823bo$792824bo254$
793087b3o$793087bo$793088bo254$793347b3o$793347bo$793348bo254$793603b
3o$793603bo$793604bo254$793860b2o$793859b2o$793861bo254$794106b2o$
794105b2o$794107bo254$794373b3o$794373bo$794374bo254$794622b3o$794622b
o$794623bo254$794888b2o$794887b2o$794889bo254$795145b3o$795145bo$
795146bo254$795393b3o$795393bo$795394bo254$795644b3o$795644bo$795645bo
254$795908b3o$795908bo$795909bo254$796165b2o$796164b2o$796166bo254$
796423b3o$796423bo$796424bo254$796665b3o$796665bo$796666bo254$796914b
3o$796914bo$796915bo254$797180b2o$797179b2o$797181bo254$797430b3o$
797430bo$797431bo254$797694b3o$797694bo$797695bo254$797961b3o$797961bo
$797962bo254$798210b3o$798210bo$798211bo254$798451b3o$798451bo$798452b
o254$798728b2o$798727b2o$798729bo254$798971b3o$798971bo$798972bo254$
799219b3o$799219bo$799220bo254$799485b2o$799484b2o$799486bo254$799735b
3o$799735bo$799736bo254$799999b3o$799999bo$800000bo254$800264b3o$
800264bo$800265bo254$800503b3o$800503bo$800504bo254$800762b3o$800762bo
$800763bo254$801021b2o$801020b2o$801022bo254$801273b3o$801273bo$
801274bo254$801521b3o$801521bo$801522bo254$801787b2o$801786b2o$801788b
o254$802037b3o$802037bo$802038bo254$802301b3o$802301bo$802302bo254$
802561b3o$802561bo$802562bo254$802817b3o$802817bo$802818bo254$803060b
2o$803059b2o$803061bo254$803335b2o$803334b2o$803336bo254$803578b3o$
803578bo$803579bo254$803826b3o$803826bo$803827bo254$804091b3o$804091bo
$804092bo254$804342b3o$804342bo$804343bo254$804606b3o$804606bo$804607b
o254$804867b3o$804867bo$804868bo254$805115b3o$805115bo$805116bo254$
805366b3o$805366bo$805367bo254$805628b2o$805627b2o$805629bo254$805879b
3o$805879bo$805880bo254$806128b3o$806128bo$806129bo254$806393b3o$
806393bo$806394bo254$806644b3o$806644bo$806645bo254$806908b3o$806908bo
$806909bo254$807166b3o$807166bo$807167bo254$807420b2o$807419b2o$
807421bo254$807669b3o$807669bo$807670bo254$807939b3o$807939bo$807940bo
254$808185b3o$808185bo$808186bo254$808434b3o$808434bo$808435bo254$
808699b3o$808699bo$808700bo254$808950b3o$808950bo$808951bo254$809214b
3o$809214bo$809215bo254$809467b3o$809467bo$809468bo254$809747b3o$
809747bo$809748bo254$809998b2o$809997b2o$809999bo254$810233b2o$810232b
2o$810234bo254$810490b3o$810490bo$810491bo254$810739b3o$810739bo$
810740bo254$811004b3o$811004bo$811005bo254$811255b3o$811255bo$811256bo
254$811519b3o$811519bo$811520bo254$811779b3o$811779bo$811780bo254$
812030b3o$812030bo$812031bo254$812287b2o$812286b2o$812288bo254$812540b
3o$812540bo$812541bo254$812792b3o$812792bo$812793bo254$813041b3o$
813041bo$813042bo254$813306b3o$813306bo$813307bo254$813557b3o$813557bo
$813558bo254$813821b3o$813821bo$813822bo254$814081b3o$814081bo$814082b
o254$814334b3o$814334bo$814335bo254$814586b2o$814585b2o$814587bo254$
814841b3o$814841bo$814842bo254$815097b3o$815097bo$815098bo254$815346b
3o$815346bo$815347bo254$815611b3o$815611bo$815612bo254$815862b3o$
815862bo$815863bo254$816126b3o$816126bo$816127bo254$816386b3o$816386bo
$816387bo254$816639b3o$816639bo$816640bo254$816891b2o$816890b2o$
816892bo254$817153b3o$817153bo$817154bo254$817400b3o$817400bo$817401bo
254$817649b3o$817649bo$817650bo254$817914b3o$817914bo$817915bo254$
818165b3o$818165bo$818166bo254$818429b3o$818429bo$818430bo254$818689b
3o$818689bo$818690bo254$818945b3o$818945bo$818946bo254$819188b2o$
819187b2o$819189bo254$819463b2o$819462b2o$819464bo254$819706b3o$
819706bo$819707bo254$819954b3o$819954bo$819955bo254$820219b3o$820219bo
$820220bo254$820470b3o$820470bo$820471bo254$820734b3o$820734bo$820735b
o254$820994b3o$820994bo$820995bo254$821250b3o$821250bo$821251bo254$
821518b2o$821517b2o$821519bo254$821752b3o$821752bo$821753bo254$822007b
3o$822007bo$822008bo254$822256b3o$822256bo$822257bo254$822521b3o$
822521bo$822522bo254$822772b3o$822772bo$822773bo254$823036b3o$823036bo
$823037bo254$823286b3o$823286bo$823287bo254$823557b3o$823557bo$823558b
o254$823803b2o$823802b2o$823804bo254$824057b3o$824057bo$824058bo254$
824306b3o$824306bo$824307bo254$824571b3o$824571bo$824572bo254$824822b
3o$824822bo$824823bo254$825086b3o$825086bo$825087bo254$825336b3o$
825336bo$825337bo254$825607b3o$825607bo$825608bo254$825853b2o$825852b
2o$825854bo254$826107b3o$826107bo$826108bo254$826356b3o$826356bo$
826357bo254$826622b2o$826621b2o$826623bo254$826872b3o$826872bo$826873b
o254$827136b3o$827136bo$827137bo254$827396b3o$827396bo$827397bo254$
827649b3o$827649bo$827650bo254$827903b3o$827903bo$827904bo254$828166b
3o$828166bo$828167bo254$828414b3o$828414bo$828415bo254$828679b3o$
828679bo$828680bo254$828937b3o$828937bo$828938bo254$829185b3o$829185bo
$829186bo254$829442b3o$829442bo$829443bo254$829698b3o$829698bo$829699b
o254$829941b3o$829941bo$829942bo254$830192b3o$830192bo$830193bo254$
830468b2o$830467b2o$830469bo254$830710b3o$830710bo$830711bo254$830959b
3o$830959bo$830960bo254$831224b3o$831224bo$831225bo254$831475b3o$
831475bo$831476bo254$831739b3o$831739bo$831740bo254$831986b3o$831986bo
$831987bo254$832266b3o$832266bo$832267bo254$832508b3o$832508bo$832509b
o254$832778b3o$832778bo$832779bo254$833027b3o$833027bo$833028bo254$
833293b2o$833292b2o$833294bo254$833550b3o$833550bo$833551bo254$833798b
3o$833798bo$833799bo254$834055b3o$834055bo$834056bo254$834308b3o$
834308bo$834309bo254$834566b2o$834565b2o$834567bo254$834823b3o$834823b
o$834824bo254$835071b3o$835071bo$835072bo254$835337b2o$835336b2o$
835338bo254$835594b3o$835594bo$835595bo254$835842b3o$835842bo$835843bo
254$836104b3o$836104bo$836105bo254$836343b3o$836343bo$836344bo254$
836602b3o$836602bo$836603bo254$836861b2o$836860b2o$836862bo254$837113b
3o$837113bo$837114bo254$837361b3o$837361bo$837362bo254$837627b2o$
837626b2o$837628bo254$837877b3o$837877bo$837878bo254$838141b3o$838141b
o$838142bo254$838389b3o$838389bo$838390bo254$838652b3o$838652bo$
838653bo254$838918b3o$838918bo$838919bo254$839166b3o$839166bo$839167bo
254$839419b3o$839419bo$839420bo254$839673b3o$839673bo$839674bo254$
839922b3o$839922bo$839923bo254$840187b3o$840187bo$840188bo254$840438b
3o$840438bo$840439bo254$840702b3o$840702bo$840703bo254$840970b3o$
840970bo$840971bo254$841202b3o$841202bo$841203bo254$841472b3o$841472bo
$841473bo254$841714b3o$841714bo$841715bo254$841962b3o$841962bo$841963b
o254$842228b2o$842227b2o$842229bo254$842478b3o$842478bo$842479bo254$
842742b3o$842742bo$842743bo254$843002b3o$843002bo$843003bo254$843258b
3o$843258bo$843259bo254$843515b2o$843514b2o$843516bo254$843781b2o$
843780b2o$843782bo254$844025b3o$844025bo$844026bo254$844273b3o$844273b
o$844274bo254$844539b2o$844538b2o$844540bo254$844789b3o$844789bo$
844790bo254$845053b3o$845053bo$845054bo254$845313b3o$845313bo$845314bo
254$845557b3o$845557bo$845558bo254$845823b3o$845823bo$845824bo254$
846071b3o$846071bo$846072bo254$846331b3o$846331bo$846332bo254$846579b
3o$846579bo$846580bo254$846845b2o$846844b2o$846846bo254$847095b3o$
847095bo$847096bo254$847359b3o$847359bo$847360bo254$847616b3o$847616bo
$847617bo254$847868b2o$847867b2o$847869bo254$848136b3o$848136bo$
848137bo254$848387b3o$848387bo$848388bo254$848636b3o$848636bo$848637bo
254$848901b3o$848901bo$848902bo254$849159b3o$849159bo$849160bo254$
849407b3o$849407bo$849408bo254$849662b3o$849662bo$849663bo254$849911b
3o$849911bo$849912bo254$850161b3o$850161bo$850162bo254$850435b3o$
850435bo$850436bo254$850682b3o$850682bo$850683bo254$850930b3o$850930bo
$850931bo254$851195b3o$851195bo$851196bo254$851446b3o$851446bo$851447b
o254$851710b3o$851710bo$851711bo254$851970b3o$851970bo$851971bo254$
852224b3o$852224bo$852225bo254$852475b3o$852475bo$852476bo254$852729b
3o$852729bo$852730bo254$852986b3o$852986bo$852987bo254$853234b3o$
853234bo$853235bo254$853499b3o$853499bo$853500bo254$853750b3o$853750bo
$853751bo254$854014b3o$854014bo$854015bo254$854281b3o$854281bo$854282b
o254$854533b3o$854533bo$854534bo254$854776b3o$854776bo$854777bo254$
855033b3o$855033bo$855034bo254$855282b3o$855282bo$855283bo254$855547b
3o$855547bo$855548bo254$855798b3o$855798bo$855799bo254$856062b3o$
856062bo$856063bo254$856322b3o$856322bo$856323bo254$856576b3o$856576bo
$856577bo254$856827b3o$856827bo$856828bo254$857081b3o$857081bo$857082b
o254$857338b3o$857338bo$857339bo254$857586b3o$857586bo$857587bo254$
857851b3o$857851bo$857852bo254$858102b3o$858102bo$858103bo254$858366b
3o$858366bo$858367bo254$858624b3o$858624bo$858625bo254$858878b2o$
858877b2o$858879bo254$859127b3o$859127bo$859128bo254$859397b3o$859397b
o$859398bo254$859643b3o$859643bo$859644bo254$859892b3o$859892bo$
859893bo254$860157b3o$860157bo$860158bo254$860408b3o$860408bo$860409bo
254$860672b3o$860672bo$860673bo254$860926b3o$860926bo$860927bo254$
861178b3o$861178bo$861179bo254$861443b3o$861443bo$861444bo254$861688b
3o$861688bo$861689bo254$861944b3o$861944bo$861945bo254$862193b3o$
862193bo$862194bo254$862458b3o$862458bo$862459bo254$862709b3o$862709bo
$862710bo254$862973b3o$862973bo$862974bo254$863234b3o$863234bo$863235b
o254$863482b3o$863482bo$863483bo254$863755b2o$863754b2o$863756bo254$
864004b3o$864004bo$864005bo254$864249b3o$864249bo$864250bo254$864504b
3o$864504bo$864505bo254$864753b3o$864753bo$864754bo254$865019b2o$
865018b2o$865020bo254$865269b3o$865269bo$865270bo254$865533b3o$865533b
o$865534bo254$865790b3o$865790bo$865791bo254$866042b2o$866041b2o$
866043bo254$866306b2o$866305b2o$866307bo254$866553b3o$866553bo$866554b
o254$866802b3o$866802bo$866803bo254$867068b2o$867067b2o$867069bo254$
867318b3o$867318bo$867319bo254$867582b3o$867582bo$867583bo254$867850b
3o$867850bo$867851bo254$868082b3o$868082bo$868083bo254$868352b3o$
868352bo$868353bo254$868594b3o$868594bo$868595bo254$868842b3o$868842bo
$868843bo254$869107b3o$869107bo$869108bo254$869358b3o$869358bo$869359b
o254$869622b3o$869622bo$869623bo254$869870b3o$869870bo$869871bo254$
870133b3o$870133bo$870134bo254$870404b3o$870404bo$870405bo254$870641b
2o$870640b2o$870642bo254$870917b3o$870917bo$870918bo254$871165b3o$
871165bo$871166bo254$871430b3o$871430bo$871431bo254$871688b3o$871688bo
$871689bo254$871936b3o$871936bo$871937bo254$872194b3o$872194bo$872195b
o254$872444b2o$872443b2o$872445bo254$872693b2o$872692b2o$872694bo254$
872950b2o$872949b2o$872951bo254$873218b2o$873217b2o$873219bo254$
873471b3o$873471bo$873472bo254$873722b3o$873722bo$873723bo254$873971b
3o$873971bo$873972bo254$874236b3o$874236bo$874237bo254$874487b3o$
874487bo$874488bo254$874751b3o$874751bo$874752bo254$875018b3o$875018bo
$875019bo254$875270b3o$875270bo$875271bo254$875513b3o$875513bo$875514b
o254$875770b3o$875770bo$875771bo254$876019b3o$876019bo$876020bo254$
876284b3o$876284bo$876285bo254$876535b3o$876535bo$876536bo254$876799b
3o$876799bo$876800bo254$877053b3o$877053bo$877054bo254$877305b3o$
877305bo$877306bo254$877570b3o$877570bo$877571bo254$877815b3o$877815bo
$877816bo254$878071b3o$878071bo$878072bo254$878320b3o$878320bo$878321b
o254$878585b3o$878585bo$878586bo254$878836b3o$878836bo$878837bo254$
879100b3o$879100bo$879101bo254$879360b3o$879360bo$879361bo254$879613b
3o$879613bo$879614bo254$879865b2o$879864b2o$879866bo254$880120b3o$
880120bo$880121bo254$880376b3o$880376bo$880377bo254$880625b3o$880625bo
$880626bo254$880890b3o$880890bo$880891bo254$881141b3o$881141bo$881142b
o254$881405b3o$881405bo$881406bo254$881655b3o$881655bo$881656bo254$
881926b3o$881926bo$881927bo254$882172b2o$882171b2o$882173bo254$882425b
3o$882425bo$882426bo254$882681b3o$882681bo$882682bo254$882930b3o$
882930bo$882931bo254$883196b2o$883195b2o$883197bo254$883446b3o$883446b
o$883447bo254$883710b3o$883710bo$883711bo254$883970b3o$883970bo$
883971bo254$884226b3o$884226bo$884227bo254$884494b2o$884493b2o$884495b
o254$884728b3o$884728bo$884729bo254$884983b3o$884983bo$884984bo254$
885232b3o$885232bo$885233bo254$885497b3o$885497bo$885498bo254$885748b
3o$885748bo$885749bo254$886012b3o$886012bo$886013bo254$886279b3o$
886279bo$886280bo254$886522b3o$886522bo$886523bo254$886777b3o$886777bo
$886778bo254$887043b3o$887043bo$887044bo254$887290b3o$887290bo$887291b
o254$887538b3o$887538bo$887539bo254$887803b3o$887803bo$887804bo254$
888054b3o$888054bo$888055bo254$888318b3o$888318bo$888319bo254$888579b
3o$888579bo$888580bo254$888833b3o$888833bo$888834bo254$889086b3o$
889086bo$889087bo254$889325b3o$889325bo$889326bo254$889573b3o$889573bo
$889574bo254$889838b3o$889838bo$889839bo254$890089b3o$890089bo$890090b
o254$890353b3o$890353bo$890354bo254$890601b3o$890601bo$890602bo254$
890864b3o$890864bo$890865bo254$891135b3o$891135bo$891136bo254$891372b
2o$891371b2o$891373bo254$891639b3o$891639bo$891640bo254$891888b3o$
891888bo$891889bo254$892153b3o$892153bo$892154bo254$892404b3o$892404bo
$892405bo254$892668b3o$892668bo$892669bo254$892918b3o$892918bo$892919b
o254$893189b3o$893189bo$893190bo254$893435b2o$893434b2o$893436bo254$
893699b3o$893699bo$893700bo254$893946b3o$893946bo$893947bo254$894195b
3o$894195bo$894196bo254$894460b3o$894460bo$894461bo254$894711b3o$
894711bo$894712bo254$894975b3o$894975bo$894976bo254$895229b3o$895229bo
$895230bo254$895475b3o$895475bo$895476bo254$895749b3o$895749bo$895750b
o254$896007b3o$896007bo$896008bo254$896259b3o$896259bo$896260bo254$
896515b3o$896515bo$896516bo254$896765b3o$896765bo$896766bo254$897031b
3o$897031bo$897032bo254$897271b3o$897271bo$897272bo254$897520b3o$
897520bo$897521bo254$897785b3o$897785bo$897786bo254$898036b3o$898036bo
$898037bo254$898300b3o$898300bo$898301bo254$898561b3o$898561bo$898562b
o254$898815b2o$898814b2o$898816bo254$899067b3o$899067bo$899068bo254$
899315b3o$899315bo$899316bo254$899581b2o$899580b2o$899582bo254$899831b
3o$899831bo$899832bo254$900095b3o$900095bo$900096bo254$900360b3o$
900360bo$900361bo254$900599b3o$900599bo$900600bo254$900870b2o$900869b
2o$900871bo254$901125b2o$901124b2o$901126bo254$901368b3o$901368bo$
901369bo254$901617b3o$901617bo$901618bo254$901882b3o$901882bo$901883bo
254$902133b3o$902133bo$902134bo254$902397b3o$902397bo$902398bo254$
902647b3o$902647bo$902648bo254$902918b3o$902918bo$902919bo254$903156b
3o$903156bo$903157bo254$903409b3o$903409bo$903410bo254$903675b3o$
903675bo$903676bo254$903923b3o$903923bo$903924bo254$904188b3o$904188bo
$904189bo254$904439b3o$904439bo$904440bo254$904703b3o$904703bo$904704b
o254$904956b3o$904956bo$904957bo254$905200b3o$905200bo$905201bo254$
905492b2o$905491b2o$905493bo254$905724b3o$905724bo$905725bo254$905991b
2o$905990b2o$905992bo254$906252b2o$906251b2o$906253bo254$906497b3o$
906497bo$906498bo254$906764b3o$906764bo$906765bo254$907030b2o$907029b
2o$907031bo254$907285b2o$907284b2o$907286bo254$907539b2o$907538b2o$
907540bo254$907796b2o$907795b2o$907797bo254$908049b2o$908048b2o$
908050bo254$908297b2o$908296b2o$908298bo254$908549b3o$908549bo$908550b
o254$908797b3o$908797bo$908798bo254$909062b3o$909062bo$909063bo254$
909320b3o$909320bo$909321bo254$909568b3o$909568bo$909569bo254$909825b
3o$909825bo$909826bo254$910076b3o$910076bo$910077bo254$910333b2o$
910332b2o$910334bo254$910579b2o$910578b2o$910580bo254$910854b3o$
910854bo$910855bo254$911102b3o$911102bo$911103bo254$911368b2o$911367b
2o$911369bo254$911625b3o$911625bo$911626bo254$911873b3o$911873bo$
911874bo254$912130b3o$912130bo$912131bo254$912381b3o$912381bo$912382bo
254$912650b3o$912650bo$912651bo254$912883b2o$912882b2o$912884bo254$
913146b3o$913146bo$913147bo254$913395b3o$913395bo$913396bo254$913661b
2o$913660b2o$913662bo254$913911b3o$913911bo$913912bo254$914175b3o$
914175bo$914176bo254$914429b3o$914429bo$914430bo254$914681b3o$914681bo
$914682bo254$914946b3o$914946bo$914947bo254$915191b3o$915191bo$915192b
o254$915447b3o$915447bo$915448bo254$915696b3o$915696bo$915697bo254$
915962b2o$915961b2o$915963bo254$916212b3o$916212bo$916213bo254$916476b
3o$916476bo$916477bo254$916737b3o$916737bo$916738bo254$916997b3o$
916997bo$916998bo254$917244b3o$917244bo$917245bo254$917511b3o$917511bo
$917512bo254$917767b3o$917767bo$917768bo254$918015b3o$918015bo$918016b
o254$918281b2o$918280b2o$918282bo254$918538b3o$918538bo$918539bo254$
918786b3o$918786bo$918787bo254$919044b3o$919044bo$919045bo254$919298b
3o$919298bo$919299bo254$919551b3o$919551bo$919552bo254$919790b3o$
919790bo$919791bo254$920038b3o$920038bo$920039bo254$920303b3o$920303bo
$920304bo254$920554b3o$920554bo$920555bo254$920818b3o$920818bo$920819b
o254$921078b3o$921078bo$921079bo254$921331b3o$921331bo$921332bo254$
921591b2o$921590b2o$921592bo254$921848b3o$921848bo$921849bo254$922106b
3o$922106bo$922107bo254$922354b3o$922354bo$922355bo254$922620b2o$
922619b2o$922621bo254$922870b3o$922870bo$922871bo254$923134b3o$923134b
o$923135bo254$923394b3o$923394bo$923395bo254$923647b3o$923647bo$
923648bo254$923905b2o$923904b2o$923906bo254$924153b3o$924153bo$924154b
o254$924402b3o$924402bo$924403bo254$924668b2o$924667b2o$924669bo254$
924918b3o$924918bo$924919bo254$925182b3o$925182bo$925183bo254$925442b
3o$925442bo$925443bo254$925696b3o$925696bo$925697bo254$925950b2o$
925949b2o$925951bo254$926203b3o$926203bo$926204bo254$926457b3o$926457b
o$926458bo254$926706b3o$926706bo$926707bo254$926971b3o$926971bo$
926972bo254$927222b3o$927222bo$927223bo254$927486b3o$927486bo$927487bo
254$927747b3o$927747bo$927748bo254$927995b3o$927995bo$927996bo254$
928246b3o$928246bo$928247bo254$928511b2o$928510b2o$928512bo254$928760b
3o$928760bo$928761bo254$929009b3o$929009bo$929010bo254$929274b3o$
929274bo$929275bo254$929525b3o$929525bo$929526bo254$929789b3o$929789bo
$929790bo254$930049b3o$930049bo$930050bo254$930302b3o$930302bo$930303b
o254$930554b2o$930553b2o$930555bo254$930809b3o$930809bo$930810bo254$
931065b3o$931065bo$931066bo254$931314b3o$931314bo$931315bo254$931579b
3o$931579bo$931580bo254$931830b3o$931830bo$931831bo254$932094b3o$
932094bo$932095bo254$932354b3o$932354bo$932355bo254$932607b3o$932607bo
$932608bo254$932859b2o$932858b2o$932860bo254$933121b3o$933121bo$
933122bo254$933368b3o$933368bo$933369bo254$933617b3o$933617bo$933618bo
254$933882b3o$933882bo$933883bo254$934133b3o$934133bo$934134bo254$
934397b3o$934397bo$934398bo254$934655b3o$934655bo$934656bo254$934909b
2o$934908b2o$934910bo254$935158b3o$935158bo$935159bo254$935428b3o$
935428bo$935429bo254$935674b3o$935674bo$935675bo254$935923b3o$935923bo
$935924bo254$936189b2o$936188b2o$936190bo254$936439b3o$936439bo$
936440bo254$936703b3o$936703bo$936704bo254$936963b3o$936963bo$936964bo
254$937219b3o$937219bo$937220bo254$937472b3o$937472bo$937473bo254$
937725b2o$937724b2o$937726bo254$937986b2o$937985b2o$937987bo254$
938233b3o$938233bo$938234bo254$938481b3o$938481bo$938482bo254$938747b
2o$938746b2o$938748bo254$938997b3o$938997bo$938998bo254$939261b3o$
939261bo$939262bo254$939521b3o$939521bo$939522bo254$939765b3o$939765bo
$939766bo254$940031b3o$940031bo$940032bo254$940279b3o$940279bo$940280b
o254$940539b3o$940539bo$940540bo254$940787b3o$940787bo$940788bo254$
941052b3o$941052bo$941053bo254$941303b3o$941303bo$941304bo254$941567b
3o$941567bo$941568bo254$941821b3o$941821bo$941822bo254$942091b2o$
942090b2o$942092bo254$942341b3o$942341bo$942342bo254$942601b3o$942601b
o$942602bo254$942855b3o$942855bo$942856bo254$943106b3o$943106bo$
943107bo254$943339b2o$943338b2o$943340bo254$943607b3o$943607bo$943608b
o254$943856b3o$943856bo$943857bo254$944121b3o$944121bo$944122bo254$
944372b3o$944372bo$944373bo254$944636b3o$944636bo$944637bo254$944896b
3o$944896bo$944897bo254$945147b3o$945147bo$945148bo254$945404b2o$
945403b2o$945405bo254$945670b2o$945669b2o$945671bo254$945913b3o$
945913bo$945914bo254$946161b3o$946161bo$946162bo254$946426b3o$946426bo
$946427bo254$946677b3o$946677bo$946678bo254$946941b3o$946941bo$946942b
o254$947194b3o$947194bo$947195bo254$947474b3o$947474bo$947475bo254$
947725b2o$947724b2o$947726bo254$947960b2o$947959b2o$947961bo254$
948217b3o$948217bo$948218bo254$948466b3o$948466bo$948467bo254$948731b
3o$948731bo$948732bo254$948982b3o$948982bo$948983bo254$949246b3o$
949246bo$949247bo254$949514b3o$949514bo$949515bo254$949760b3o$949760bo
$949761bo254$950001b3o$950001bo$950002bo254$950249b3o$950249bo$950250b
o254$950515b2o$950514b2o$950516bo254$950765b3o$950765bo$950766bo254$
951029b3o$951029bo$951030bo254$951289b3o$951289bo$951290bo254$951543b
3o$951543bo$951544bo254$951794b3o$951794bo$951795bo254$952057b3o$
952057bo$952058bo254$952312b3o$952312bo$952313bo254$952561b3o$952561bo
$952562bo254$952827b2o$952826b2o$952828bo254$953077b3o$953077bo$
953078bo254$953341b3o$953341bo$953342bo254$953601b3o$953601bo$953602bo
254$953854b3o$953854bo$953855bo254$954106b2o$954105b2o$954107bo254$
954361b3o$954361bo$954362bo254$954617b3o$954617bo$954618bo254$954866b
3o$954866bo$954867bo254$955132b2o$955131b2o$955133bo254$955382b3o$
955382bo$955383bo254$955646b3o$955646bo$955647bo254$955907b3o$955907bo
$955908bo254$956155b3o$956155bo$956156bo254$956406b3o$956406bo$956407b
o254$956668b2o$956667b2o$956669bo254$956919b3o$956919bo$956920bo254$
957168b3o$957168bo$957169bo254$957433b3o$957433bo$957434bo254$957684b
3o$957684bo$957685bo254$957948b3o$957948bo$957949bo254$958208b3o$
958208bo$958209bo254$958459b3o$958459bo$958460bo254$958707b3o$958707bo
$958708bo254$958975b2o$958974b2o$958976bo254$959232b2o$959231b2o$
959233bo254$959480b3o$959480bo$959481bo254$959729b3o$959729bo$959730bo
254$959995b2o$959994b2o$959996bo254$960245b3o$960245bo$960246bo254$
960509b3o$960509bo$960510bo254$960759b3o$960759bo$960760bo254$961030b
3o$961030bo$961031bo254$961276b2o$961275b2o$961277bo254$961530b3o$
961530bo$961531bo254$961779b3o$961779bo$961780bo254$962045b2o$962044b
2o$962046bo254$962295b3o$962295bo$962296bo254$962559b3o$962559bo$
962560bo254$962824b3o$962824bo$962825bo254$963068b3o$963068bo$963069bo
254$963328b2o$963327b2o$963329bo254$963581b3o$963581bo$963582bo254$
963827b3o$963827bo$963828bo254$964090b3o$964090bo$964091bo254$964338b
3o$964338bo$964339bo254$964604b2o$964603b2o$964605bo254$964854b3o$
964854bo$964855bo254$965118b3o$965118bo$965119bo254$965386b3o$965386bo
$965387bo254$965632b3o$965632bo$965633bo254$965873b3o$965873bo$965874b
o254$966121b3o$966121bo$966122bo254$966387b2o$966386b2o$966388bo254$
966637b3o$966637bo$966638bo254$966901b3o$966901bo$966902bo254$967148b
3o$967148bo$967149bo254$967428b3o$967428bo$967429bo254$967670b3o$
967670bo$967671bo254$967940b3o$967940bo$967941bo254$968189b3o$968189bo
$968190bo254$968455b2o$968454b2o$968456bo254$968712b3o$968712bo$
968713bo254$968960b3o$968960bo$968961bo254$969218b3o$969218bo$969219bo
254$969478b3o$969478bo$969479bo254$969736b3o$969736bo$969737bo254$
969972b3o$969972bo$969973bo254$970235b3o$970235bo$970236bo254$970483b
3o$970483bo$970484bo254$970748b3o$970748bo$970749bo254$970999b3o$
970999bo$971000bo254$971263b3o$971263bo$971264bo254$971531b3o$971531bo
$971532bo254$971763b3o$971763bo$971764bo254$972033b3o$972033bo$972034b
o254$972275b3o$972275bo$972276bo254$972523b3o$972523bo$972524bo254$
972788b3o$972788bo$972789bo254$973039b3o$973039bo$973040bo254$973303b
3o$973303bo$973304bo254$973557b3o$973557bo$973558bo254$973817b2o$
973816b2o$973818bo254$974074b3o$974074bo$974075bo254$974330b3o$974330b
o$974331bo254$974579b3o$974579bo$974580bo254$974844b3o$974844bo$
974845bo254$975095b3o$975095bo$975096bo254$975359b3o$975359bo$975360bo
254$975616b3o$975616bo$975617bo254$975876b2o$975875b2o$975877bo254$
976122b3o$976122bo$976123bo254$976390b3o$976390bo$976391bo254$976634b
3o$976634bo$976635bo254$976883b3o$976883bo$976884bo254$977149b2o$
977148b2o$977150bo254$977399b3o$977399bo$977400bo254$977663b3o$977663b
o$977664bo254$977923b3o$977923bo$977924bo254$978174b3o$978174bo$
978175bo254$978431b2o$978430b2o$978432bo254$978684b3o$978684bo$978685b
o254$978936b3o$978936bo$978937bo254$979185b3o$979185bo$979186bo254$
979450b3o$979450bo$979451bo254$979701b3o$979701bo$979702bo254$979965b
3o$979965bo$979966bo254$980222b3o$980222bo$980223bo254$980474b2o$
980473b2o$980475bo254$980738b2o$980737b2o$980739bo254$980985b3o$
980985bo$980986bo254$981234b3o$981234bo$981235bo254$981500b2o$981499b
2o$981501bo254$981750b3o$981750bo$981751bo254$982014b3o$982014bo$
982015bo254$982282b3o$982282bo$982283bo254$982528b3o$982528bo$982529bo
254$982769b3o$982769bo$982770bo254$983017b3o$983017bo$983018bo254$
983283b2o$983282b2o$983284bo254$983533b3o$983533bo$983534bo254$983797b
3o$983797bo$983798bo254$984058b3o$984058bo$984059bo254$984318b3o$
984318bo$984319bo254$984565b3o$984565bo$984566bo254$984832b3o$984832bo
$984833bo254$985079b3o$985079bo$985080bo254$985328b3o$985328bo$985329b
o254$985594b2o$985593b2o$985595bo254$985844b3o$985844bo$985845bo254$
986108b3o$986108bo$986109bo254$986368b3o$986368bo$986369bo254$986619b
3o$986619bo$986620bo254$986876b2o$986875b2o$986877bo254$987122b2o$
987121b2o$987123bo254$987397b3o$987397bo$987398bo254$987645b3o$987645b
o$987646bo254$987911b2o$987910b2o$987912bo254$988168b3o$988168bo$
988169bo254$988416b3o$988416bo$988417bo254$988674b3o$988674bo$988675bo
254$988928b2o$988927b2o$988929bo254$989180b3o$989180bo$989181bo254$
989428b3o$989428bo$989429bo254$989694b2o$989693b2o$989695bo254$989944b
3o$989944bo$989945bo254$990208b3o$990208bo$990209bo254$990468b3o$
990468bo$990469bo254$990721b3o$990721bo$990722bo254$990975b3o$990975bo
$990976bo254$991238b3o$991238bo$991239bo254$991486b3o$991486bo$991487b
o254$991751b3o$991751bo$991752bo254$992009b3o$992009bo$992010bo254$
992257b3o$992257bo$992258bo254$992504b3o$992504bo$992505bo254$992775b
3o$992775bo$992776bo254$993021b2o$993020b2o$993022bo254$993275b3o$
993275bo$993276bo254$993524b3o$993524bo$993525bo254$993789b3o$993789bo
$993790bo254$994040b3o$994040bo$994041bo254$994304b3o$994304bo$994305b
o254$994564b3o$994564bo$994565bo254$994817b3o$994817bo$994818bo254$
995069b2o$995068b2o$995070bo254$995331b3o$995331bo$995332bo254$995578b
3o$995578bo$995579bo254$995827b3o$995827bo$995828bo254$996092b3o$
996092bo$996093bo254$996343b3o$996343bo$996344bo254$996607b3o$996607bo
$996608bo254$996875b3o$996875bo$996876bo254$997121b3o$997121bo$997122b
o254$997362b3o$997362bo$997363bo254$997610b3o$997610bo$997611bo254$
997875b3o$997875bo$997876bo254$998126b3o$998126bo$998127bo254$998390b
3o$998390bo$998391bo254$998638b3o$998638bo$998639bo254$998901b3o$
998901bo$998902bo254$999172b3o$999172bo$999173bo254$999409b2o$999408b
2o$999410bo254$999685b3o$999685bo$999686bo254$999933b3o$999933bo$
999934bo254$1000199b2o$1000198b2o$1000200bo254$1000456b3o$1000456bo$
1000457bo254$1000704b3o$1000704bo$1000705bo254$1000958b3o$1000958bo$
1000959bo254$1001210b2o$1001209b2o$1001211bo254$1001474b2o$1001473b2o$
1001475bo254$1001721b3o$1001721bo$1001722bo254$1001970b3o$1001970bo$
1001971bo254$1002235b3o$1002235bo$1002236bo254$1002486b3o$1002486bo$
1002487bo254$1002750b3o$1002750bo$1002751bo254$1002998b3o$1002998bo$
1002999bo254$1003261b3o$1003261bo$1003262bo254$1003515b2o$1003514b2o$
1003516bo254$1003787b3o$1003787bo$1003788bo254$1004024b3o$1004024bo$
1004025bo254$1004273b3o$1004273bo$1004274bo254$1004538b3o$1004538bo$
1004539bo254$1004789b3o$1004789bo$1004790bo254$1005053b3o$1005053bo$
1005054bo254$1005313b3o$1005313bo$1005314bo254$1005567b3o$1005567bo$
1005568bo254$1005818b3o$1005818bo$1005819bo254$1006072b3o$1006072bo$
1006073bo254$1006329b3o$1006329bo$1006330bo254$1006577b3o$1006577bo$
1006578bo254$1006842b3o$1006842bo$1006843bo254$1007093b3o$1007093bo$
1007094bo254$1007357b3o$1007357bo$1007358bo254$1007622b3o$1007622bo$
1007623bo254$1007863b3o$1007863bo$1007864bo254$1008142b2o$1008141b2o$
1008143bo254$1008383b2o$1008382b2o$1008384bo254$1008636b2o$1008635b2o$
1008637bo254$1008888b3o$1008888bo$1008889bo254$1009137b3o$1009137bo$
1009138bo254$1009402b3o$1009402bo$1009403bo254$1009653b3o$1009653bo$
1009654bo254$1009917b3o$1009917bo$1009918bo254$1010177b3o$1010177bo$
1010178bo254$1010428b3o$1010428bo$1010429bo254$1010685b2o$1010684b2o$
1010686bo254$1010951b2o$1010950b2o$1010952bo254$1011194b3o$1011194bo$
1011195bo254$1011442b3o$1011442bo$1011443bo254$1011707b3o$1011707bo$
1011708bo254$1011958b3o$1011958bo$1011959bo254$1012222b3o$1012222bo$
1012223bo254$1012489b3o$1012489bo$1012490bo254$1012738b3o$1012738bo$
1012739bo254$1012984b3o$1012984bo$1012985bo254$1013255b3o$1013255bo$
1013256bo254$1013497b3o$1013497bo$1013498bo254$1013746b3o$1013746bo$
1013747bo254$1014011b3o$1014011bo$1014012bo254$1014262b3o$1014262bo$
1014263bo254$1014526b3o$1014526bo$1014527bo254$1014786b3o$1014786bo$
1014787bo254$1015035b3o$1015035bo$1015036bo254$1015292b3o$1015292bo$
1015293bo254$1015545b3o$1015545bo$1015546bo254$1015793b3o$1015793bo$
1015794bo254$1016046b3o$1016046bo$1016047bo254$1016309b3o$1016309bo$
1016310bo254$1016553b3o$1016553bo$1016554bo254$1016819b2o$1016818b2o$
1016820bo254$1017081b2o$1017080b2o$1017082bo254$1017348b3o$1017348bo$
1017349bo254$1017581b3o$1017581bo$1017582bo254$1017851b3o$1017851bo$
1017852bo254$1018099b3o$1018099bo$1018100bo254$1018365b2o$1018364b2o$
1018366bo254$1018615b3o$1018615bo$1018616bo254$1018879b3o$1018879bo$
1018880bo254$1019139b3o$1019139bo$1019140bo254$1019392b3o$1019392bo$
1019393bo254$1019644b2o$1019643b2o$1019645bo254$1019906b3o$1019906bo$
1019907bo254$1020153b3o$1020153bo$1020154bo254$1020402b3o$1020402bo$
1020403bo254$1020668b2o$1020667b2o$1020669bo254$1020918b3o$1020918bo$
1020919bo254$1021182b3o$1021182bo$1021183bo254$1021436b3o$1021436bo$
1021437bo254$1021700b3o$1021700bo$1021701bo254$1021957b2o$1021956b2o$
1021958bo254$1022215b3o$1022215bo$1022216bo254$1022457b3o$1022457bo$
1022458bo254$1022706b3o$1022706bo$1022707bo254$1022971b3o$1022971bo$
1022972bo254$1023222b3o$1023222bo$1023223bo254$1023486b3o$1023486bo$
1023487bo254$1023746b3o$1023746bo$1023747bo254$1024002b3o$1024002bo$
1024003bo254$1024270b2o$1024269b2o$1024271bo254$1024504b3o$1024504bo$
1024505bo254$1024759b3o$1024759bo$1024760bo254$1025008b3o$1025008bo$
1025009bo254$1025273b3o$1025273bo$1025274bo254$1025524b3o$1025524bo$
1025525bo254$1025788b3o$1025788bo$1025789bo254$1026045b3o$1026045bo$
1026046bo254$1026297b2o$1026296b2o$1026298bo254$1026561b2o$1026560b2o$
1026562bo254$1026808b3o$1026808bo$1026809bo254$1027057b3o$1027057bo$
1027058bo254$1027322b3o$1027322bo$1027323bo254$1027573b3o$1027573bo$
1027574bo254$1027837b3o$1027837bo$1027838bo254$1028091b3o$1028091bo$
1028092bo254$1028355b3o$1028355bo$1028356bo254$1028612b2o$1028611b2o$
1028613bo254$1028870b3o$1028870bo$1028871bo254$1029112b3o$1029112bo$
1029113bo254$1029361b3o$1029361bo$1029362bo254$1029626b3o$1029626bo$
1029627bo254$1029877b3o$1029877bo$1029878bo254$1030141b3o$1030141bo$
1030142bo254$1030406b3o$1030406bo$1030407bo254$1030647b3o$1030647bo$
1030648bo254$1030926b2o$1030925b2o$1030927bo254$1031167b2o$1031166b2o$
1031168bo254$1031420b2o$1031419b2o$1031421bo254$1031672b3o$1031672bo$
1031673bo254$1031921b3o$1031921bo$1031922bo254$1032186b3o$1032186bo$
1032187bo254$1032437b3o$1032437bo$1032438bo254$1032701b3o$1032701bo$
1032702bo254$1032968b3o$1032968bo$1032969bo254$1033217b3o$1033217bo$
1033218bo254$1033458b3o$1033458bo$1033459bo254$1033735b2o$1033734b2o$
1033736bo254$1033978b3o$1033978bo$1033979bo254$1034226b3o$1034226bo$
1034227bo254$1034492b2o$1034491b2o$1034493bo254$1034742b3o$1034742bo$
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1084925bo254$1085172b3o$1085172bo$1085173bo254$1085437b3o$1085437bo$
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1128940bo254$1129205b2o$1129204b2o$1129206bo254$1129455b3o$1129455bo$
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1129977bo254$1130236b2o$1130235b2o$1130237bo254$1130482b3o$1130482bo$
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1131517bo254$1131767b3o$1131767bo$1131768bo254$1132031b3o$1132031bo$
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1132543bo254$1132796b2o$1132795b2o$1132797bo254$1133053b3o$1133053bo$
1133054bo254$1133307b3o$1133307bo$1133308bo254$1133560b3o$1133560bo$
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1134076bo254$1134325b3o$1134325bo$1134326bo254$1134589b3o$1134589bo$
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1137152bo254$1137403b2o$1137402b2o$1137404bo254$1137667b2o$1137666b2o$
1137668bo254$1137914b3o$1137914bo$1137915bo254$1138163b3o$1138163bo$
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1139202bo254$1139463b2o$1139462b2o$1139464bo254$1139711b2o$1139710b2o$
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1140223bo254$1140487b3o$1140487bo$1140488bo254$1140745b3o$1140745bo$
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1141251bo254$1141506b3o$1141506bo$1141507bo254$1141774b2o$1141773b2o$
1141775bo254$1142008b3o$1142008bo$1142009bo254$1142263b3o$1142263bo$
1142264bo254$1142512b3o$1142512bo$1142513bo254$1142777b3o$1142777bo$
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1143293bo254$1143559b3o$1143559bo$1143560bo254$1143808b3o$1143808bo$
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1180175bo254$1180408b2o$1180407b2o$1180409bo254$1180667b2o$1180666b2o$
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1249778bo254$1250042b3o$1250042bo$1250043bo254$1250293b3o$1250293bo$
1250294bo254$1250557b3o$1250557bo$1250558bo254$1250824b3o$1250824bo$
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1352712bo254$1352954b3o$1352954bo$1352955bo254$1353202b3o$1353202bo$
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1353719bo254$1353982b3o$1353982bo$1353983bo254$1354243b3o$1354243bo$
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1354743bo254$1355007b2o$1355006b2o$1355008bo254$1355256b3o$1355256bo$
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1356795bo254$1357058b2o$1357057b2o$1357059bo254$1357305b3o$1357305bo$
1357306bo254$1357554b3o$1357554bo$1357555bo254$1357819b3o$1357819bo$
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1465331bo254$1465595b3o$1465595bo$1465596bo254$1465846b3o$1465846bo$
1465847bo254$1466110b3o$1466110bo$1466111bo254$1466360b3o$1466360bo$
1466361bo254$1466631b3o$1466631bo$1466632bo254$1466877b2o$1466876b2o$
1466878bo254$1467131b3o$1467131bo$1467132bo254$1467380b3o$1467380bo$
1467381bo254$1467645b3o$1467645bo$1467646bo254$1467896b3o$1467896bo$
1467897bo254$1468160b3o$1468160bo$1468161bo254$1468414b3o$1468414bo$
1468415bo254$1468666b3o$1468666bo$1468667bo254$1468931b3o$1468931bo$
1468932bo254$1469176b3o$1469176bo$1469177bo254$1469432b3o$1469432bo$
1469433bo254$1469681b3o$1469681bo$1469682bo254$1469946b3o$1469946bo$
1469947bo254$1470197b3o$1470197bo$1470198bo254$1470461b3o$1470461bo$
1470462bo254$1470728b3o$1470728bo$1470729bo254$1470977b3o$1470977bo$
1470978bo254$1471218b3o$1471218bo$1471219bo254$1471495b2o$1471494b2o$
1471496bo254$1471738b3o$1471738bo$1471739bo254$1471986b3o$1471986bo$
1471987bo254$1472251b3o$1472251bo$1472252bo254$1472502b3o$1472502bo$
1472503bo254$1472766b3o$1472766bo$1472767bo254$1473027b3o$1473027bo$
1473028bo254$1473275b3o$1473275bo$1473276bo254$1473526b3o$1473526bo$
1473527bo254$1473791b2o$1473790b2o$1473792bo254$1474040b3o$1474040bo$
1474041bo254$1474289b3o$1474289bo$1474290bo254$1474554b3o$1474554bo$
1474555bo254$1474805b3o$1474805bo$1474806bo254$1475069b3o$1475069bo$
1475070bo254$1475329b3o$1475329bo$1475330bo254$1475585b3o$1475585bo$
1475586bo254$1475828b2o$1475827b2o$1475829bo254$1476103b2o$1476102b2o$
1476104bo254$1476346b3o$1476346bo$1476347bo254$1476594b3o$1476594bo$
1476595bo254$1476860b2o$1476859b2o$1476861bo254$1477110b3o$1477110bo$
1477111bo254$1477374b3o$1477374bo$1477375bo254$1477624b3o$1477624bo$
1477625bo254$1477895b3o$1477895bo$1477896bo254$1478141b2o$1478140b2o$
1478142bo254$1478394b3o$1478394bo$1478395bo254$1478650b3o$1478650bo$
1478651bo254$1478899b3o$1478899bo$1478900bo254$1479165b2o$1479164b2o$
1479166bo254$1479415b3o$1479415bo$1479416bo254$1479679b3o$1479679bo$
1479680bo254$1479927b3o$1479927bo$1479928bo254$1480190b3o$1480190bo$
1480191bo254$1480444b2o$1480443b2o$1480445bo254$1480716b3o$1480716bo$
1480717bo254$1480953b3o$1480953bo$1480954bo254$1481202b3o$1481202bo$
1481203bo254$1481468b2o$1481467b2o$1481469bo254$1481718b3o$1481718bo$
1481719bo254$1481982b3o$1481982bo$1481983bo254$1482243b3o$1482243bo$
1482244bo254$1482497b2o$1482496b2o$1482498bo254$1482749b3o$1482749bo$
1482750bo254$1482997b3o$1482997bo$1482998bo254$1483262b3o$1483262bo$
1483263bo254$1483513b3o$1483513bo$1483514bo254$1483777b3o$1483777bo$
1483778bo254$1484030b3o$1484030bo$1484031bo254$1484310b3o$1484310bo$
1484311bo254$1484561b2o$1484560b2o$1484562bo254$1484796b2o$1484795b2o$
1484797bo254$1485062b3o$1485062bo$1485063bo254$1485310b3o$1485310bo$
1485311bo254$1485576b2o$1485575b2o$1485577bo254$1485833b3o$1485833bo$
1485834bo254$1486081b3o$1486081bo$1486082bo254$1486328b3o$1486328bo$
1486329bo254$1486599b3o$1486599bo$1486600bo254$1486845b2o$1486844b2o$
1486846bo254$1487098b3o$1487098bo$1487099bo254$1487354b3o$1487354bo$
1487355bo254$1487603b3o$1487603bo$1487604bo254$1487868b3o$1487868bo$
1487869bo254$1488119b3o$1488119bo$1488120bo254$1488383b3o$1488383bo$
1488384bo254$1488633b3o$1488633bo$1488634bo254$1488904b3o$1488904bo$
1488905bo254$1489150b2o$1489149b2o$1489151bo254$1489413b3o$1489413bo$
1489414bo254$1489661b3o$1489661bo$1489662bo254$1489926b3o$1489926bo$
1489927bo254$1490184b3o$1490184bo$1490185bo254$1490432b3o$1490432bo$
1490433bo254$1490689b3o$1490689bo$1490690bo254$1490940b3o$1490940bo$
1490941bo254$1491197b2o$1491196b2o$1491198bo254$1491443b2o$1491442b2o$
1491444bo254$1491718b3o$1491718bo$1491719bo254$1491966b3o$1491966bo$
1491967bo254$1492231b3o$1492231bo$1492232bo254$1492489b3o$1492489bo$
1492490bo254$1492737b3o$1492737bo$1492738bo254$1492991b3o$1492991bo$
1492992bo254$1493251b2o$1493250b2o$1493252bo254$1493497b3o$1493497bo$
1493498bo254$1493765b3o$1493765bo$1493766bo254$1494009b3o$1494009bo$
1494010bo254$1494258b3o$1494258bo$1494259bo254$1494523b3o$1494523bo$
1494524bo254$1494774b3o$1494774bo$1494775bo254$1495038b3o$1495038bo$
1495039bo254$1495298b3o$1495298bo$1495299bo254$1495552b3o$1495552bo$
1495553bo254$1495803b3o$1495803bo$1495804bo254$1496057b3o$1496057bo$
1496058bo254$1496314b3o$1496314bo$1496315bo254$1496562b3o$1496562bo$
1496563bo254$1496827b3o$1496827bo$1496828bo254$1497078b3o$1497078bo$
1497079bo254$1497342b3o$1497342bo$1497343bo254$1497603b3o$1497603bo$
1497604bo254$1497844b2o$1497843b2o$1497845bo254$1498113b2o$1498112b2o$
1498114bo254$1498364b3o$1498364bo$1498365bo254$1498612b3o$1498612bo$
1498613bo254$1498878b2o$1498877b2o$1498879bo254$1499128b3o$1499128bo$
1499129bo254$1499392b3o$1499392bo$1499393bo254$1499640b3o$1499640bo$
1499641bo254$1499903b3o$1499903bo$1499904bo254$1500157b2o$1500156b2o$
1500158bo254$1500429b3o$1500429bo$1500430bo254$1500666b3o$1500666bo$
1500667bo254$1500915b3o$1500915bo$1500916bo254$1501180b3o$1501180bo$
1501181bo254$1501431b3o$1501431bo$1501432bo254$1501695b3o$1501695bo$
1501696bo254$1501963b3o$1501963bo$1501964bo254$1502195b3o$1502195bo$
1502196bo254$1502465b3o$1502465bo$1502466bo254$1502707b3o$1502707bo$
1502708bo254$1502955b3o$1502955bo$1502956bo254$1503220b3o$1503220bo$
1503221bo254$1503471b3o$1503471bo$1503472bo254$1503735b3o$1503735bo$
1503736bo254$1503995b3o$1503995bo$1503996bo254$1504251b3o$1504251bo$
1504252bo254$1504508b2o$1504507b2o$1504509bo254$1504754b2o$1504753b2o$
1504755bo254$1505030b3o$1505030bo$1505031bo254$1505278b3o$1505278bo$
1505279bo254$1505543b3o$1505543bo$1505544bo254$1505801b3o$1505801bo$
1505802bo254$1506049b3o$1506049bo$1506050bo254$1506313b3o$1506313bo$
1506314bo254$1506562b3o$1506562bo$1506563bo254$1506808b3o$1506808bo$
1506809bo254$1507079b3o$1507079bo$1507080bo254$1507321b3o$1507321bo$
1507322bo254$1507570b3o$1507570bo$1507571bo254$1507835b3o$1507835bo$
1507836bo254$1508086b3o$1508086bo$1508087bo254$1508350b3o$1508350bo$
1508351bo!

[dvgrn]

Here's a script compiling slow^2 salvos...

Great! That will do just fine, until/unless someone wants to attempt the tricky optimization option -- simsim314 would call it the "grey goo option", I think. I.e., just keep a moderate-sized patch of ash at the elbow and hit it with whatever series of gliders happens to produce the correct sideways glider and/or move the patch of ash in the correct direction.

No doubt it would take many thousands of times longer to finish a slow^2 compilation, since basically every compile process would be a separate search. But I'm _fairly_ sure that it would save a little bit of cost. If nothing else, there's a little bit of effort wasted bringing the target slow^2 elbow back to a honeyfarm after each glider is emitted.

[dvgrn]

Running through many of the above steps again, but this time building NW-traveling Corderships. Here's the initial slow-salvo recipe for this orientation of Cordership seed:

Code: Select all

x = 3904, y = 3914, rule = B3/S23
3901bobo$3901b2o$3902bo54$3845bo$3843b2o$3844b2o27$3812bo$3810b2o$
3811b2o31$3779bo$3777b2o$3778b2o17$3746bo$3744b2o$3745b2o39$3713bo$
3711b2o$3712b2o24$3680bo$3678b2o$3679b2o45$3646bo$3644b2o$3645b2o39$
3613bo$3611b2o$3612b2o23$3580bo$3578b2o$3579b2o29$3535bo$3533b2o$3534b
2o49$3502bo$3500b2o$3501b2o31$3469bo$3468bo$3468b3o35$3436bo$3435bo$
3435b3o18$3403bo$3401b2o$3402b2o25$3370bo$3368b2o$3369b2o33$3337bo$
3335b2o$3336b2o28$3304bo$3302b2o$3303b2o21$3238bo$3236b2o$3237b2o8$
3271bo$3269b2o$3270b2o33$3205bo$3204bo$3204b3o17$3169bo$3168bo$3168b3o
65$3136bo$3135bo$3135b3o30$3103bo$3101b2o$3102b2o27$3070bo$3068b2o$
3069b2o25$3029bo$3028bo$3028b3o36$2996bo$2995bo$2995b3o23$2963bo$2961b
2o$2962b2o32$2930bo$2928b2o$2929b2o34$2897bo$2895b2o$2896b2o32$2864bo$
2862b2o$2863b2o24$2831bo$2829b2o$2830b2o18$2798bo$2796b2o$2797b2o38$
2765bo$2764bo$2764b3o35$2732bo$2731bo$2731b3o30$2699bo$2697b2o$2698b2o
27$2666bo$2665bo$2665b3o44$2633bo$2631b2o$2632b2o19$2600bo$2599bo$
2599b3o32$2567bo$2565b2o$2566b2o36$2534bo$2532b2o$2533b2o28$2501bo$
2499b2o$2500b2o31$2468bo$2466b2o$2467b2o42$2435bo$2433b2o$2434b2o42$
2402bo$2400b2o$2401b2o18$2369bo$2368bo$2368b3o45$2336bo$2334b2o$2335b
2o28$2303bo$2301b2o$2302b2o22$2270bo$2268b2o$2269b2o38$2237bo$2236bo$
2236b3o37$2204bo$2203bo$2203b3o13$2171bo$2169b2o$2170b2o55$2133bo$
2131b2o$2132b2o30$2100bo$2098b2o$2099b2o48$2067bo$2065b2o$2066b2o23$
2034bo$2032b2o$2033b2o31$2001bo$1999b2o$2000b2o43$1968bo$1966b2o$1967b
2o28$1935bo$1933b2o$1934b2o39$1902bo$1900b2o$1901b2o16$1869bo$1867b2o$
1868b2o37$1836bo$1834b2o$1835b2o41$1803bo$1801b2o$1802b2o21$1770bo$
1768b2o$1769b2o31$1737bo$1735b2o$1736b2o36$1704bo$1703bo$1703b3o51$
1671bo$1670bo$1670b3o24$1638bo$1637bo$1637b3o27$1605bo$1604bo$1604b3o
33$1572bo$1570b2o$1571b2o31$1539bo$1537b2o$1538b2o10$1506bo$1504b2o$
1505b2o28$1473bo$1472bo$1472b3o53$1440bo$1438b2o$1439b2o24$1407bo$
1405b2o$1406b2o39$1374bo$1372b2o$1373b2o26$1341bo$1339b2o$1340b2o13$
1308bo$1306b2o$1307b2o29$1275bo$1273b2o$1274b2o25$1242bo$1241bo$1241b
3o66$1209bo$1207b2o$1208b2o20$1176bo$1175bo$1175b3o17$1143bo$1142bo$
1142b3o35$1110bo$1109bo$1109b3o34$1077bo$1076bo$1076b3o23$1044bo$1043b
o$1043b3o33$1011bo$1010bo$978bo31b3o$976b2o$977b2o34$945bo$944bo$944b
3o36$912bo$911bo$911b3o52$868bo$867bo$867b3o25$835bo$834bo$834b3o16$
802bo$801bo$801b3o38$769bo$768bo$768b3o34$736bo$735bo$735b3o37$703bo$
701b2o$702b2o30$670bo$668b2o$669b2o28$637bo$636bo$636b3o30$604bo$602b
2o$603b2o30$571bo$569b2o$570b2o39$538bo$536b2o$537b2o27$505bo$503b2o$
504b2o40$472bo$470b2o$471b2o17$439bo$437b2o$438b2o34$406bo$404b2o$405b
2o46$373bo$371b2o$372b2o33$340bo$338b2o$339b2o29$307bo$305b2o$306b2o
24$274bo$272b2o$273b2o63$241bo$239b2o$240b2o21$208bo$207bo$207b3o12$
175bo$174bo$174b3o41$142bo$141bo$141b3o67$109bo$107b2o$108b2o22$76bo$
74b2o$75b2o37$43bo$42bo$42b3o35$10bo$9bo$9b3o4$2o$2o!

Here is the Corderfleet and Corderabsorbers we'll be trying to build -- both tightened up a bit from the version shown here for comparison with the larger SEward Corderfleet:

Code: Select all

x = 2211, y = 2196, rule = LifeHistory
22.2A$22.2A12$21.2A$20.A2.A$16.A4.2A$15.A.A$15.A.A$16.A4$34.2A$34.2A
10$12.2A$11.A2.A$12.2A19.2A$32.A2.A$.2A25.A4.2A$A2.A23.A.A$A.A24.A.A$
.A26.A2$3.2A$4.A$4.A.A$5.2A$49.2A$49.2A12$48.2A$47.A2.A$43.A4.2A$42.A
.A$42.A.A$43.A4$62.2A$62.2A12$61.2A$60.A2.A$56.A4.2A$55.A.A19.2A$55.A
.A19.2A$56.A11$76.2A11.2A$75.A2.A10.2A$71.A4.2A$70.A.A$70.A.A$71.A8$
88.2A$87.A2.A$83.A4.2A$82.A.A$82.A.A$83.A4$106.2A$106.2A12$105.2A$
104.A2.A$100.A4.2A$99.A.A$99.A.A$100.A22.2A$123.2A11$132.2A$122.2A8.
2A$121.A2.A$117.A4.2A$116.A.A$116.A.A$117.A7$131.2A$130.A2.A9.2A$126.
A4.2A10.2A$125.A.A$125.A.A$126.A9$142.2A$141.A2.A$137.A4.2A$136.A.A$
136.A.A19.2A$137.A20.2A12$157.2A$156.A2.A$152.A4.2A$151.A.A$151.A.A$
152.A22.2A$175.2A12$174.2A$173.A2.A10.2A$169.A4.2A11.2A$168.A.A$168.A
.A$169.A9$186.2A$185.A2.A$181.A4.2A$180.A.A16.2A$180.A.A16.2A$181.A
11$198.2A7.2A$197.A2.A6.2A$193.A4.2A$192.A.A$192.A.A$193.A6$218.2A$
218.2A$206.2A$205.A2.A$201.A4.2A$200.A.A$200.A.A$201.A6$217.2A$216.A
2.A$212.A4.2A$211.A.A$211.A.A$212.A6$236.2A$236.2A12$235.2A$234.A2.A$
230.A4.2A$229.A.A19.2A$229.A.A19.2A$230.A11$250.2A$249.A2.A$245.A4.2A
13.2A$244.A.A18.2A$244.A.A$245.A10$264.2A10.2A$263.A2.A9.2A$259.A4.2A
$258.A.A$258.A.A$259.A8$275.2A10.2A$274.A2.A9.2A$270.A4.2A$269.A.A$
269.A.A$270.A8$286.2A$285.A2.A$281.A4.2A$280.A.A$280.A.A$281.A4$298.
2A$298.2A12$297.2A$296.A2.A$292.A4.2A$291.A.A$291.A.A18.2A$292.A19.2A
10$322.2A$322.2A$311.2A$310.A2.A$306.A4.2A$305.A.A$305.A.A$306.A6$
321.2A$320.A2.A$316.A4.2A$315.A.A$315.A.A$316.A5$339.2A$339.2A10$349.
2A$349.2A$338.2A$337.A2.A$333.A4.2A$332.A.A$332.A.A$333.A6$348.2A$
347.A2.A$343.A4.2A$342.A.A$342.A.A$343.A5$365.2A$365.2A12$364.2A$363.
A2.A$359.A4.2A$358.A.A$358.A.A20.2A$359.A21.2A12$380.2A$379.A2.A$375.
A4.2A$374.A.A$374.A.A$375.A20.2A$396.2A12$395.2A$394.A2.A$390.A4.2A$
389.A.A$389.A.A$390.A6$412.2A$412.2A11$424.2A77.2A$411.2A11.2A76.A.A$
410.A2.A88.2A$406.A4.2A$405.A.A$405.A.A$406.A5$512.2A$512.2A$423.2A$
422.A2.A$418.A4.2A$417.A.A$417.A.A$418.A$508.2A$508.2A12$431.2A67.2A
33.2A$431.2A67.2A32.A.A$534.2A$503.A$503.A$503.A$586.2A$505.3A77.A2.A
$586.2A$502.2A$441.2A58.A2.A$441.2A59.2A40.2A$544.2A$430.2A$429.A2.A
171.A$425.A4.2A172.A$424.A.A177.A$424.A.A$425.A$540.2A$540.2A2$503.2A
$440.2A60.A.A$439.A2.A60.A73.2A$435.A4.2A72.A62.2A$434.A.A77.A58.2A$
434.A.A77.A58.2A$435.A3$521.3A64.3A$532.2A$532.2A2$535.A60.2A$535.A
43.3A3.3A8.2A$450.2A83.A71.2A$450.2A112.2A17.A23.2A$537.3A24.2A17.A$
583.A10.2A$534.2A58.2A$533.A2.A32.A$534.2A33.A$569.A$605.2A$605.2A2$
504.2A73.3A$503.A2.A$449.2A53.A.A$448.A2.A53.A$444.A4.2A143.2A10.A$
443.A.A148.2A9.A.A$443.A.A89.2A68.2A$444.A89.A.A$535.A$546.A$546.A$
546.A37.2A$498.2A84.2A$497.A2.A$498.2A$553.3A$564.2A21.2A$564.2A21.2A
2.2A$591.2A$567.A$567.A$567.A2$569.3A2$566.2A$565.A2.A$566.2A40.2A$
608.2A4$536.2A$535.A2.A$536.A.A$537.A66.2A$591.2A11.2A$591.2A2.2A$
567.2A26.2A$566.A.A$567.A$578.A$578.A$578.A$530.2A$529.A2.A$530.2A$
585.3A$596.2A33.2A$596.2A32.A.A$630.2A$599.A$599.A$599.A2$601.3A2$
598.2A$597.A2.A$598.2A40.2A$640.2A4$568.2A$567.A2.A$568.A.A$569.A66.
2A$636.2A2$599.2A$598.A.A$599.A$610.A$610.A$610.A$562.2A$561.A2.A$
562.2A$617.3A$628.2A33.2A$628.2A32.A.A$662.2A$631.A$631.A$631.A2$633.
3A2$630.2A$629.A2.A$630.2A40.2A$672.2A4$600.2A$599.A2.A$600.A.A$601.A
66.2A$668.2A2$631.2A$630.A.A$631.A$642.A$642.A$642.A$594.2A$593.A2.A$
594.2A$649.3A$660.2A33.2A$660.2A32.A.A$694.2A$663.A$663.A$663.A$704.
2A$665.3A36.2A2$662.2A$661.A2.A$662.2A5$632.2A$631.A2.A$632.A.A$633.A
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$917.3A15.A$916.2A.2A14.A$915.2A3.A7.4A3.A$882.2A32.A.A.A.A5.A3.A$
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2A$1111.3A6.2A$1112.A3$1120.2A$1087.2A31.A.A$1088.A2.A4.A23.A3.3A$
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$1088.A6.A24.2A$1087.2A.A9.2A13.2A$1095.A4.2A13.2A$1093.2A$1114.A$
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1126.A2.A4.A23.A3.3A$1123.A2.3A.A2.A.A22.A.A3.4A$1123.A2.A4.4A23.A.A
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1179.3A15.A$1178.2A.2A14.A$1177.2A3.A7.4A3.A$1178.A.A.A.A5.A3.A$1179.
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1189.A.A$1173.A2.A12.3A$1174.3A.3A10.A$1174.2A.A.A$1176.3A$1177.2A$
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A.A.A5.A3.A$1217.2A.A2.A4.2A3.A$1220.2A.A7.3A$1221.2A10.2A.A6.2A$
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1298.A2.A4.A23.A3.3A$1295.A2.3A.A2.A.A22.A.A3.4A$1295.A2.A4.4A23.A.A
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$1525.A6.A24.2A$1524.2A.A9.2A13.2A$1532.A4.2A13.2A$1530.2A$1551.A$
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$1577.A4.2A13.2A$1575.2A$1596.A$1595.A.A$1595.A.A6$1586.A$1586.A.A$
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2A4.A$1614.4A4.2A13.2A3$1635.3A$1636.2A5$1613.A$1616.A6.A.A$1611.A11.
A.A.A$1610.A3.A2.A10.2A$1611.3A2.A10.A$1612.A3.A$1614.2A$1614.A4$
1617.2A42.A$1617.2A41.3A15.A$1659.2A.2A14.A$1658.2A3.A7.4A3.A$1659.A.
A.A.A5.A3.A$1660.2A.A2.A4.2A3.A$1663.2A.A7.3A$1664.2A10.2A.A6.2A$
1677.3A6.2A$1678.A3$1686.2A$1653.2A31.A.A$1654.A2.A4.A23.A3.3A$1651.A
2.3A.A2.A.A22.A.A3.4A$1651.A2.A4.4A23.A.A3.4A$1651.A2.A30.3A.3A$1654.
A6.A24.2A$1653.2A.A9.2A13.2A$1661.A4.2A13.2A$1659.2A$1680.A$1679.A.A$
1679.A.A6$1670.A$1670.A.A$1654.A2.A12.3A$1655.3A.3A10.A$1655.2A.A.A$
1657.3A$1658.2A4$1661.2A$1661.2A$1705.A$1704.3A15.A$1703.2A.2A14.A$
1702.2A3.A7.4A3.A$1703.A.A.A.A5.A3.A$1704.2A.A2.A4.2A3.A$1707.2A.A7.
3A$1708.2A10.2A.A6.2A$1721.3A6.2A$1722.A3$1730.2A$1697.2A31.A.A$1698.
A2.A4.A23.A3.3A$1695.A2.3A.A2.A.A22.A.A3.4A$1695.A2.A4.4A23.A.A3.4A$
1695.A2.A30.3A.3A$1698.A6.A24.2A$1697.2A.A9.2A13.2A$1705.A4.2A13.2A$
1703.2A$1724.A$1723.A.A$1723.A.A6$1714.A$1714.A.A$1698.A2.A12.3A$
1699.3A.3A10.A$1699.2A.A.A$1701.3A$1702.2A2$1744.A$1743.3A15.A$1705.
2A35.2A.2A14.A$1705.2A34.2A3.A7.4A3.A$1742.A.A.A.A5.A3.A$1743.2A.A2.A
4.2A3.A$1746.2A.A7.3A$1747.2A10.2A.A6.2A$1760.3A6.2A$1761.A3$1769.2A$
1736.2A31.A.A$1737.A2.A4.A23.A3.3A$1734.A2.3A.A2.A.A22.A.A3.4A$1734.A
2.A4.4A23.A.A3.4A$1734.A2.A30.3A.3A$1737.A6.A24.2A$1736.2A.A9.2A13.2A
$1744.A4.2A13.2A$1742.2A$1763.A$1762.A.A$1762.A.A6$1753.A$1753.A.A$
1737.A2.A12.3A$1738.3A.3A10.A$1738.2A.A.A$1740.3A$1741.2A3$1785.A$
1744.2A38.3A15.A$1744.2A37.2A.2A14.A$1782.2A3.A7.4A3.A$1783.A.A.A.A5.
A3.A$1784.2A.A2.A4.2A3.A$1787.2A.A7.3A$1788.2A10.2A.A6.2A$1801.3A6.2A
$1802.A3$1810.2A$1777.2A31.A.A$1778.A2.A4.A23.A3.3A$1775.A2.3A.A2.A.A
22.A.A3.4A$1775.A2.A4.4A23.A.A3.4A$1775.A2.A30.3A.3A$1778.A6.A24.2A$
1777.2A.A9.2A13.2A$1785.A4.2A13.2A$1783.2A$1804.A$1803.A.A$1803.A.A6$
1794.A$1794.A.A$1778.A2.A12.3A$1779.3A.3A10.A$1779.2A.A.A$1781.3A$
1782.2A4$1785.2A$1785.2A$1830.A$1829.3A15.A$1828.2A.2A14.A$1827.2A3.A
7.4A3.A$1828.A.A.A.A5.A3.A$1829.2A.A2.A4.2A3.A$1832.2A.A7.3A$1833.2A
10.2A.A6.2A$1846.3A6.2A$1847.A3$1855.2A$1822.2A31.A.A$1823.A2.A4.A23.
A3.3A$1820.A2.3A.A2.A.A22.A.A3.4A$1820.A2.A4.4A23.A.A3.4A$1820.A2.A
30.3A.3A$1823.A6.A24.2A$1822.2A.A9.2A13.2A$1830.A4.2A13.2A$1828.2A$
1849.A$1848.A.A$1848.A.A6$1839.A$1839.A.A$1823.A2.A12.3A$1824.3A.3A
10.A$1824.2A.A.A$1826.3A$1827.2A40.A$1868.3A15.A$1867.2A.2A14.A$1866.
2A3.A7.4A3.A$1830.2A35.A.A.A.A5.A3.A$1830.2A36.2A.A2.A4.2A3.A$1871.2A
.A7.3A$1872.2A10.2A.A6.2A$1885.3A6.2A$1886.A3$1894.2A$1861.2A31.A.A$
1862.A2.A4.A23.A3.3A$1859.A2.3A.A2.A.A22.A.A3.4A$1859.A2.A4.4A23.A.A
3.4A$1859.A2.A30.3A.3A$1862.A6.A24.2A$1861.2A.A9.2A13.2A$1869.A4.2A
13.2A$1867.2A$1888.A$1887.A.A$1887.A.A6$1878.A$1878.A.A$1862.A2.A12.
3A$1863.3A.3A10.A$1863.2A.A.A$1865.3A$1866.2A2$1908.A$1907.3A15.A$
1869.2A35.2A.2A14.A$1869.2A34.2A3.A7.4A3.A$1906.A.A.A.A5.A3.A$1907.2A
.A2.A4.2A3.A$1910.2A.A7.3A$1911.2A10.2A.A6.2A$1924.3A6.2A$1925.A3$
1933.2A$1900.2A31.A.A$1901.A2.A4.A23.A3.3A$1898.A2.3A.A2.A.A22.A.A3.
4A$1898.A2.A4.4A23.A.A3.4A$1898.A2.A30.3A.3A$1901.A6.A24.2A$1900.2A.A
9.2A13.2A$1908.A4.2A13.2A$1906.2A$1927.A$1926.A.A$1926.A.A6$1917.A$
1917.A.A$1901.A2.A12.3A$1902.3A.3A10.A$1902.2A.A.A$1904.3A$1905.2A4$
1908.2A$1908.2A$1955.A$1954.3A15.A$1953.2A.2A14.A$1952.2A3.A7.4A3.A$
1953.A.A.A.A5.A3.A$1954.2A.A2.A4.2A3.A$1957.2A.A7.3A$1958.2A10.2A.A6.
2A$1971.3A6.2A$1972.A3$1980.2A$1947.2A31.A.A$1948.A2.A4.A23.A3.3A$
1945.A2.3A.A2.A.A22.A.A3.4A$1945.A2.A4.4A23.A.A3.4A$1945.A2.A30.3A.3A
$1948.A6.A24.2A$1947.2A.A9.2A13.2A$1955.A4.2A13.2A$1953.2A$1974.A$
1973.A.A$1973.A.A6$1964.A$1964.A.A$1948.A2.A12.3A$1949.3A.3A10.A$
1949.2A.A.A$1951.3A$1952.2A4$1955.2A$1955.2A2$1999.A$1998.3A15.A$
1997.2A.2A14.A$1996.2A3.A7.4A3.A$1997.A.A.A.A5.A3.A$1998.2A.A2.A4.2A
3.A$2001.2A.A7.3A$2002.2A10.2A.A6.2A$2015.3A6.2A$2016.A3$2024.2A$
1991.2A31.A.A$1992.A2.A4.A23.A3.3A$1989.A2.3A.A2.A.A22.A.A3.4A$1989.A
2.A4.4A23.A.A3.4A$1989.A2.A30.3A.3A$1992.A6.A24.2A$1991.2A.A9.2A13.2A
$1999.A4.2A13.2A$1997.2A$2018.A$2017.A.A$2017.A.A6$2008.A$2008.A.A$
1992.A2.A12.3A$1993.3A.3A10.A$1993.2A.A.A$1995.3A$1996.2A4$1999.2A39.
A$1999.2A38.3A15.A$2038.2A.2A14.A$2037.2A3.A7.4A3.A$2038.A.A.A.A5.A3.
A$2039.2A.A2.A4.2A3.A$2042.2A.A7.3A$2043.2A10.2A.A6.2A$2056.3A6.2A$
2057.A3$2065.2A$2032.2A31.A.A$2033.A2.A4.A23.A3.3A$2030.A2.3A.A2.A.A
22.A.A3.4A$2030.A2.A4.4A23.A.A3.4A$2030.A2.A30.3A.3A$2033.A6.A24.2A$
2032.2A.A9.2A13.2A$2040.A4.2A13.2A$2038.2A$2059.A$2058.A.A$2058.A.A6$
2049.A$2049.A.A$2033.A2.A12.3A$2034.3A.3A10.A$2034.2A.A.A43.A$2036.3A
43.3A15.A$2037.2A42.2A.2A14.A$2080.2A3.A7.4A3.A$2081.A.A.A.A5.A3.A$
2082.2A.A2.A4.2A3.A$2040.2A43.2A.A7.3A$2040.2A44.2A10.2A.A6.2A$2099.
3A6.2A$2100.A3$2108.2A$2075.2A31.A.A$2076.A2.A4.A23.A3.3A$2073.A2.3A.
A2.A.A22.A.A3.4A$2073.A2.A4.4A23.A.A3.4A$2073.A2.A30.3A.3A$2076.A6.A
24.2A$2075.2A.A9.2A13.2A$2083.A4.2A13.2A$2081.2A$2102.A$2101.A.A$
2101.A.A6$2092.A$2092.A.A$2076.A2.A12.3A$2077.3A.3A10.A$2077.2A.A.A$
2079.3A$2080.2A4$2083.2A47.A$2083.2A46.3A15.A$2130.2A.2A14.A$2129.2A
3.A7.4A3.A$2130.A.A.A.A5.A3.A$2131.2A.A2.A4.2A3.A$2134.2A.A7.3A$2135.
2A10.2A.A6.2A$2148.3A6.2A$2149.A3$2157.2A$2124.2A31.A.A$2125.A2.A4.A
23.A3.3A$2122.A2.3A.A2.A.A22.A.A3.4A$2122.A2.A4.4A23.A.A3.4A$2122.A2.
A30.3A.3A$2125.A6.A24.2A$2124.2A.A9.2A13.2A$2132.A4.2A13.2A$2130.2A$
2151.A$2150.A.A$2150.A.A6$2141.A$2141.A.A$2125.A2.A12.3A$2126.3A.3A
10.A$2126.2A.A.A44.A$2128.3A44.A.A$2129.2A43.A3.A13.3A$2174.A3.A8.A$
2174.A.A.3A4.2A.3A$2175.2A.A2.A5.A.2A$2132.2A45.A.A8.A$2132.2A45.2A
11.A2.A5.2A$2192.3A6.2A4$2202.A$2169.A31.2A$2168.2A7.A23.A.A.2A$2167.
A.A.3A2.A.A23.3A.2A.2A$2166.3A3.2A3.A23.A3.2A2.2A$2167.A.A.2A.A.A24.A
3.A$2168.2A.2A28.A2.A$2169.A.5A.A3.2A13.2A4.A$2173.4A4.2A13.2A3$2194.
3A$2195.2A5$2172.A$2175.A6.A.A$2170.A11.A.A.A$2169.A3.A2.A10.2A$2170.
3A2.A10.A$2171.A3.A$2173.2A$2173.A4$2176.2A$2176.2A!

I've included AlbertArmstain's 180-degree turner for reference, but there's some more destruction and construction to be done along with the Corderabsorbers, that I'm not showing here.

This blueprint means building Corderships in the following relative positions:

Code: Select all

x = 1429, y = 1277, rule = LifeSuper
M29$47.M38$85.M24$134.M36$170.M40$218.pA38$259.W39$299.M41$347.W37$
385.M41$432.M37$470.M39$512.M34$557.W43$602.W43$647.M41$689.pA40$730.
M48$784.W45$829.M35$869.pA40$913.M42$957.W38$996.W39$1037.M42$1082.W
36$1121.M38$1160.M42$1207.M43$1251.W40$1292.M34$1335.M40$1384.M34$
1428.pA!

I will be following along my earlier work in this thread, starting here, substituting this new data. But if anyone sees a problem with what I'm building based on the above, please let me know here before I get too far along!

EDIT: Now I'm supposed to run this script, revised for NW Cordership positions (and rotated to match the orientation from last time):

Code: Select all

import golly as g

# g.parse() produces a cell list, with no rule information attached to it --
# so the header line isn't needed.  In fact, g.parse() does very weird things
# if you include the header line -- quite possibly we should fix that.
offsetspat = g.parse("""1276.M47$1247.M38$1209.M49$1185.M36$1149.M48$1109.pA41$1071.W40$1032.
M48$991.W38$954.M47$913.M38$876.M42$837.M45$803.W45$760.W45$717.M42$
676.pA41$636.M54$588.W45$543.M40$508.pA44$468.M44$426.W39$388.W41$
349.M45$307.W39$271.M39$233.M47$191.M44$148.W41$108.M43$74.M49$34.M
44$pA!""")

s, parities="",""
# this is a multistate cell list, so coordinates are in (x, y, state) triplets
for i in range(0,len(offsetspat)-1,3):
  s += str( [ offsetspat[i],offsetspat[i+1] ] )+"\n"
  if offsetspat[i+2]== 25:
    parities += "O"
  else:
    parities += "E"
g.setclipstr(s + "\n" + parities)

... which produces

Code: Select all

[1276, 0]
[1247, 47]
[1209, 85]
[1185, 134]
[1149, 170]
[1109, 218]
[1071, 259]
[1032, 299]
[991, 347]
[954, 385]
[913, 432]
[876, 470]
[837, 512]
[803, 557]
[760, 602]
[717, 647]
[676, 689]
[636, 730]
[588, 784]
[543, 829]
[508, 869]
[468, 913]
[426, 957]
[388, 996]
[349, 1037]
[307, 1082]
[271, 1121]
[233, 1160]
[191, 1207]
[148, 1251]
[108, 1292]
[74, 1335]
[34, 1384]
[0, 1428]

EEEEEOEEEEEEEEEEOEEEOEEEEEEEEEEEEO

-- red Cordership (meaning has to be constructed with odd parity) is last, as it should be, and corresponds with an "O" in the parity string. So far so good.

The test code is telling me there are 34 cells to process, and I want to build 34 Corderships, so that's good too. Running the script to get actual Cordership build locations (at this weird standard orientation):

Code: Select all

import golly as g

# g.parse() produces a cell list, with no rule information attached to it --
# so the header line isn't needed.  In fact, g.parse() does very weird things
# if you include the header line -- quite possibly we should fix that.
offsetspat = g.parse("""1276.pA44$1242.M49$1202.M43$1168.M41$1128.W44$1085.M47$1043.M39$1005.
M39$969.W45$927.M41$888.W39$850.W44$808.M44$768.pA40$733.M45$688.W54$
640.M41$600.pA42$559.M45$516.W45$473.W45$439.M42$400.M38$363.M47$322.
M38$285.W48$244.M40$205.W41$167.pA48$127.M36$91.M49$67.M38$29.M47$M!""")

coordlist = []
# this is a multistate cell list, so coordinates are in (x, y, state) triplets
# and there will be a trailing '0' at the end if there's an even number of cells in the list
if len(offsetspat)%3 != 0:
  if offsetspat[-1] == 0:
    offsetspat = offsetspat[:-1]  # remove trailing zero
if len(offsetspat)%3 != 0:
  # this shouldn't ever happen, so send this problem back to the coder
  g.exit("Input multistate list seems to be in an invalid format.")

# Now the list is no longer necessarily a valid Golly multistate list,
#   but we don't care -- we know how many cells are in it, because we
#   got rid of any marker '0's at the end.
numcells = len(offsetspat)//3
g.show( "Number of cells to process: " + str(numcells) )

locations = []
# Reading top to bottom, the last cell's coordinates will be the one corresponding to the first Cordership.
# The next Cordership's location, given by the second-to-last cell in the list,
# has to be calculated relative to the previous location, all the way through the list.
prevlocx, prevlocy = offsetspat[numcells*3 - 3], offsetspat[numcells*3 - 2]
for i in range(numcells-2, -1, -1):
  # g.note(str([offsetspat[i*3],offsetspat[i*3+1]]))
  newlocx,newlocy = offsetspat[i*3],offsetspat[i*3+1]
  dx, dy = newlocx - prevlocx, newlocy - prevlocy
  # g.note(str(["dx",dx,"dy",dy, "prevlocx", prevlocx, "prevlocy", prevlocy, "newlocx", newlocx, "newlocy", newlocy]))
  while 1:
    dxadj, dyadj = dx - 8, dy + 8
    # is the adjusted location closer to the previous Cordership's location? (i.e., closer to (0,0) )
    if dxadj**2 + dyadj**2 < dx**2 + dy**2:
      # if so, use that location instead
      # g.note(str(["Cordership #",i,"was",[dx,dy],"next trial",[dxadj,dyadj]]))
      dx, dy = dxadj, dyadj
    else:
      # g.note(str([dx,dy]) + " is as close as we're going to get.")
      break  # can't keep getting closer to zero forever, so eventually we'll escape this loop
  locations.append([dx,dy])
  
  # Now -- very important -- we have to update (prevlocx, prevlocy) to do the next calculation relative to
  #   the (newlocx, newlocy) Cordership.  Otherwise we end up with absolute coordinates, not relative ones.
  prevlocx, prevlocy = newlocx, newlocy
g.setclipstr(str(locations))

Result:

Code: Select all

[[-6, -4], [-8, -1], [-6, -3], [0, -1], [3, -4], [-6, 1], [-2, 1], [-4, 1], [2, -5], [-1, -1], [-2, 1], [2, -4], [0, -4], [-5, 0], [-3, 3], [0, -6], [0, -1], [1, -2], [3, -5], [3, -5], [-6, -5], [-1, -2], [-3, 2], [1, -7], [-3, 2], [-7, 0], [-1, 0], [-2, -1], [0, -8], [4, -4], [-16, -9], [-2, 2], [-11, -7]]

... That was the first trial run, but it was in reverse order, because I'd forgotten which order my code was reading the cells in. The first several offsets should have been recognizable as the same offsets as we needed for the SE Corderfleet. Which they weren't. But now they are:

Code: Select all

[[-11, -7], [-2, 2], [-16, -9], [4, -4], [0, -8], [-2, -1], [-1, 0], [-7, 0], [-3, 2], [1, -7], [-3, 2], [-1, -2], [-6, -5], [3, -5], [3, -5], [1, -2], [0, -1], [0, -6], [-3, 3], [-5, 0], [0, -4], [2, -4], [-2, 1], [-1, -1], [2, -5], [-4, 1], [-2, 1], [-6, 1], [3, -4], [0, -1], [-6, -3], [-8, -1], [-6, -4]]

[dvgrn]

(-31,16).

For the NW Cordership recipe posted in the last message, if I want to end up building a new Cordership exactly on top of the last one, I'm going to have to move the target block 31 cells left and 16 cells down.

The [-11, -7] numbers generated at the end of the last post will modify that default target-block movement distance. So... time to build some slsparse infile.mc's!

-- Oops, no, I take that back. (-31,16) is specific to the sample Cordership seed build that I quoted in the last post -- but future recipes will each start with the block in a different position.

Probably the easiest thing is to place the seed in the Golly universe so that the output block shows up at (0, 0). Then if I put the input block at (0,0), too, the next Cordership will show up exactly on top of the last one... but if I move the input block to, say, [-11,-7], then the new Cordership will show up [11, 7] closer to the glider source than the previous one.

(I got that backwards the first time around, of course. Or really the second time around -- the first time I was 90 degrees off, because of the confusing rotation that I've gone and done to the coordinate system. The reason that you put the input block farther away is that that has the effect of telling slsparse to build things closer to the glider source, relative to that input block.)

Code: Select all

import golly as g

# avoid needing a subroutine or complicated logic by making a lookup table
#  that gives the right output state value to mark a target block cell, no matter if
#  the cell is already ON or not
# If a cell is already state 3, 4, 5, or 6, the attempted lookup will cause errors --
#   which is what we want, because the template pattern should definitely not
#    contain any such thing.
lookup = [4,3]

offsetslist = [[-11, -7], [-2, 2], [-16, -9], [4, -4], [0, -8], [-2, -1], [-1, 0], [-7, 0], [-3, 2], [1, -7], [-3, 2], [-1, -2], [-6, -5], [3, -5], [3, -5], [1, -2], [0, -1], [0, -6], [-3, 3], [-5, 0], [0, -4], [2, -4], [-2, 1], [-1, -1], [2, -5], [-4, 1], [-2, 1], [-6, 1], [3, -4], [0, -1], [-6, -3], [-8, -1], [-6, -4]]

baserle = g.parse("""25.A$24.A.A$25.2A4$12.2A15.A$12.2A14.A.A$28.2A3$29.A$28.A.A$28.2A3$
42.A4.A$.2A38.A.A2.A.A$A.A38.2A3.2A$.A18.2A$20.2A30.2A$52.A.A$32.2A
19.A$32.2A6$15.A$14.A.A$15.A$46.2A$46.2A3$9.2A9.A$8.A.A8.A.A$9.A9.2A
2$38.2A$38.2A4$35.2A$34.A.A$35.A86$135.A$134.A.A.2A$133.A2.A.2A$133.A
.A$134.A!""",-17,-7)  # adjust so that the leftover block after the seed is triggered is at 0,0
count = 0
for item in offsetslist:
  dx, dy = item
  g.new("infile"+str(count))
  g.putcells(baserle)
  
  # mark the four cells in the target block
  for y in range(dy,2+dy):
    for x in range(dx, 2+dx):
      g.setcell(x, y, lookup[g.getcell(x,y)])
  g.save("C:/Users/greedd/Desktop/RCT/infiles/infile" + str(count) + ".mc","mc")
  count += 1

... The next several steps are straightforward, using previously written code and only changing filename locations.

Final result coming soon (here's hoping everything is right and it can clean the NW ash trail...)

EDIT: Nope, my code was able to string together 34 Cordership-seed recipes and fire them off just fine. The first one was in the right place because, well, I put it in the right place. The second one was in the right place, because I had used the second one as a manual test of the placement calculation, so I wouldn't have continued if that one hadn't showed up in the right place.

The third one ... is quite a distance too close to the glider source. So my basic math was wrong somewhere early on. I should have tested two Cordership placements manually instead of just the one... Will fix and re-run and get the correct salvo, but possibly not until tomorrow -- by noon or so November 6 Central Standard Time, with any luck.

EDIT: Well, color me clueless -- I didn't look close enough at the output of my batch file, which contained rather obvious little signs of problems like

Code: Select all

C:\repos\slmake>cp C:/users/greedd/Desktop/RCT/infile32.mc C:/repos/slmake/infile.mc
cp: cannot stat 'C:/users/greedd/Desktop/RCT/infile32.mc': No such file or directory

... With the result that slsparse happily recalculated the exact same recipe for me 33 times, and I dutifully ran the code that strung them all together. Hang on while I re-run everything from that point...

EDIT2 6 November: Yup, well, just half a dozen gliders in that whole list have the wrong parity. Probably I'm off by one in applying parities to Corderships -- thought I had done that right, but any which way it's an easy fix. More shortly.

[Hippo.69]

Code: Select all

lanes = [9, -9, 9, -9, 9, -9, 9, -9, 11, -11]
parities = [1, 0, 0, 1, 1, 0, 1, 0, 1, 0]

I would prefere recepie encodding

Code: Select all

lanes = [9, -9, 9, -9, 9, -9, 9, -9, 11, -11]
parities = [1, 0, 0, 1, 1, nil, 1, nil, 1, 0]

(or rather 2 replacing nil)
where 0, 1 means forced parity the recepie require, while nil/2 the arbitrary parity.
This option (2) in many cases improves the recepie "packing".

Conversion from 01 to 012 format could definitely be automated ... was it already done?

[dvgrn]

Conversion from 01 to 012 format could definitely be automated ... was it already done?

I haven't coded up anything like that yet.

However, the fact that calcyman was able to quote a savings of 28211 bits for the RCT's DBCA construction, would seem to indicate that there's some code floating around somewhere that tests slow-salvo recipes and makes that distinction.

[Hippo.69]

Code: Select all

lanes = [9, -9, 9, -9, 9, -9, 9, -9, 11, -11]
parities = [1, 0, 0, 1, 1, 0, 1, 0, 1, 0]

I would prefere recepie encodding

Code: Select all

lanes = [9, -9, 9, -9, 9, -9, 9, -9, 11, -11]
parities = [1, 0, 0, 1, 1, nil, 1, nil, 1, 0]

(or rather 2 replacing nil)
where 0, 1 means forced parity the recepie require, while nil/2 the arbitrary parity.
This option (2) in many cases improves the recepie "packing".

Conversion from 01 to 012 format could definitely be automated ... was it already done?

Grr, I have written disputation of complications in phase dependencies possible to describe by different letters where case denotes phase dependency, with difficult openning/closing patterns, possible NP-hardness of converting such a recepie to good enough DBCA recepies ... and I was logged of meanwhile and the post vanished , so I will try to implement the codding convertor and I will try some recepies and we will see how effective heuristics could be in implementing the DBCA convertors ... and I will post the "language description" afterwards.

I have made "simple" script doing just "2" classification (not trying bigger dependencies), it is actually incorrect when ^2 ships are fired ... their phase fixation is not detectable and the classification becomes (could become) 2 so these have to me manually fixed. I am still debugging ... from first 46 gliders sample it seems about half is phase indepenent.

Classifying more complicated dependencies (part of the muster pattern is in the same phase as alternative one, but another part is in another phase ... but these parts would not touch till one of them becomes stable ... that would be nice to do that clasification when creating the recepie, (knowing the dependencies), but tracking them later would probably be difficult. It wouls require to classify P2 desyncronized parts and stop the alternatives if there is any other difference. The only scenario I could imagine be maintainable is stoping the alternatives whenever older independent P region is hit ... if newer is not stabilised yet. ... so ther will be natural "nesting" of p2 independent parts of the pattern.
As "2" classification is already a big improvement and it takes a lot of time to compute, I am not starting experiments with "such nesting" (yet).

I was originally giving plenty of time to alternatives to stabilise what could find alternative solutions to destroying tasks, but to make detection faster (for such a huge recepie), I have decided only to detect "the same reactions" ... stabilising in the same time +/-1 tick rounded to 8 (to the same pattern) it is not as strict as "the reaction envelope contains only stable patterns), but it will not differ too often.

Seems this snippet works rather fine (there is conversion among two line formats, only starting portion of the parity test result is important, I am not including input/output and calling envelope ... I am running it on two copies of the pattern layers 0,1 started on layer 0 to see if something wents wrong:

Code: Select all

local g = golly()

g.setbase(2)
g.setstep(0)
g.autoupdate(true)

function comparerectfills(f1,f2) --we know the arrays have the same dimensions
  local i
  if #f1~=#f2 then return false end
  for i=1,#f1 do
    if f1[i]~=f2[i] then return false end
  end
  return true
end

function safeBorderRect(rect)
  local cells
  while true do
    cells=g.getcells({rect[1]-1,rect[2],2,rect[4]})
    if #cells>0 then
      rect[1]=rect[1]-1
      rect[3]=rect[3]+1
      goto continue
    end
    cells=g.getcells({rect[1],rect[2]-1,rect[3],2})
    if #cells>0 then
      rect[2]=rect[2]-1
      rect[4]=rect[4]+1
      goto continue
    end
    cells=g.getcells({rect[1]+rect[3]-2,rect[2],2,rect[4]})
    if #cells>0 then
      rect[3]=rect[3]+1
      goto continue
    end
    cells=g.getcells({rect[1],rect[2]+rect[4]-2,rect[3],2})
    if #cells>0 then
      rect[4]=rect[4]+1
      goto continue
    end
    break
    ::continue::
  end
  return rect
end

function parityTest(phase,line,maxxminusy)
  local orig,muster,prev,curr,rect,t,i,result,mustert
  rect = {(line-952+maxxminusy)/2-47,(line-952-maxxminusy)/2-33,85,85}
  if playCount<11 then
    rect = {(line-952+maxxminusy)/2-17,(line-952-maxxminusy)/2-5,25,25}
  end
  local xored = {}
  local res = "{"..(line-952).."_"..(line-949)..","
  rect = safeBorderRect(rect)
  g.select(rect)
  g.fitsel()
  g.setmag(1)
  orig = g.getcells(rect)
  g.putcells(glider[phase+1],(line-952+maxxminusy)/2+4,(line-952-maxxminusy)/2-4)
  prev = g.getcells(rect)
  t=0
  while true do
    g.advance(0,8) --p8 curcitry nearby
    t=t+8
    curr=g.getcells(rect)
    if comparerectfills(prev,curr) then
 --   g.note("orig stabilised at time "..t)
      muster=curr
      mustert=t
      break
    end
    prev=curr
    if t>1000 then
      sCache=sCache.."orig not stabilised!"
      aCache=aCache.."orig not stabilised!"
      writeACache()
      writeSCache()
      g.note("orig not stabilised!")
      g.putcells(orig,0,0,1,0,0,1,"copy")
      return res
    end
  end
  for i=1,#orig,2 do
    if g.getcell(orig[i],orig[i+1])~=1 then --change in the line
      lineVacancyExact[orig[i]+orig[i+1]]=nil
      if lineVacancy[orig[i]+orig[i+1]]~=nil then
        if lineVacancy[orig[i]+orig[i+1]]<orig[i]-orig[i+1] then
          lineVacancy[orig[i]+orig[i+1]]=orig[i]-orig[i+1]
        end
      end
      table.insert(xored,orig[i])
      table.insert(xored,orig[i+1])
    end
  end
  g.clear(0)
  g.putcells(orig,0,0,1,0,0,1,"copy")
 -- g.note("returned")
  for i=1,#muster,2 do
    if g.getcell(muster[i],muster[i+1])~=1 then --change in the line
      lineVacancyExact[muster[i]+muster[i+1]]=nil
      if lineVacancy[muster[i]+muster[i+1]]~=nil then
        if lineVacancy[muster[i]+muster[i+1]]<muster[i]-muster[i+1] then
          lineVacancy[muster[i]+muster[i+1]]=muster[i]-muster[i+1]
        end
      end
      table.insert(xored,muster[i])
      table.insert(xored,muster[i+1])
    end
  end
  g.putcells(glider[2-phase],(line-952+maxxminusy)/2+4,(line-952-maxxminusy)/2-4)
  prev = g.getcells(rect)
  t=0
  while true do
    g.advance(0,8) --p8 curcitry nearby
    t=t+8
    curr=g.getcells(rect)
    if comparerectfills(prev,curr) then
  --  g.note("other stabilised at time "..t)
      result = comparerectfills(curr,muster)
      break
    end
    prev=curr
    if t>8+mustert then
  --  g.note("other not stabilised")
      result=false
      break
    end
  end
  g.clear(0)
  g.putcells(orig,0,0,1,0,0,1,"copy")
  g.putcells(glider[1+phase],(line-952+maxxminusy)/2+4,(line-952-maxxminusy)/2-4)
  --g.note("returned 2nd")
  if result then
    res=res.."2,"..maxxminusy..","
    g.setlayer(1)
    g.select(rect)
    g.putcells(glider[2-phase],(line-952+maxxminusy)/2+3,(line-952-maxxminusy)/2-3)
    --g.sleep(1000)
    g.setlayer(0)
    if t<mustert then
      t=mustert
    end
  else
    res=res..phase..","..maxxminusy..","
    g.setlayer(1)
    g.putcells(glider[1+phase],(line-952+maxxminusy)/2+3,(line-952-maxxminusy)/2-3)
    g.setlayer(0)
    t=mustert
  end
  res=res..(t-4)..",{"
  for i=1,#xored-1 do
    res=res..xored[i]..","
  end
  res=res..xored[#xored].."},"..line.."}"
  g.run(t)
  g.setlayer(1)
  g.run(t)
  g.setlayer(0)
  return res
end

function process_commandPair(commandPair)
	local commaPos,line,phase,comment
      bBracePos = string.find(commandPair,"{")
      if bBracePos==nil then
        aCache=aCache.."command "..commandPair.."does not contain {"
        sCache=sCache.."command "..commandPair.."does not contain {"
        writeACache()
        writeSCache()
        g.note("command "..commandPair.."does not contain {")
      end
	commaPos = string.find(commandPair,",")
      comment = string.sub(commandPair,1,bBracePos-1)
      aCache = aCache..comment
      sCache = sCache..comment
      playCount=1+playCount
      g.show(sCache)
	line = tonumber(string.sub(commandPair,bBracePos+1,commaPos-1))
	phase = tonumber(string.sub(commandPair,commaPos+1))
      local xplusy,xminusy
      local maxxminusy = -20
      for xplusy = line-952-2,line-952+7 do
         if lineVacancyExact[xplusy]==nil then
            if lineVacancy[xplusy]==nil then lineVacancy[xplusy]=3056-(xplusy%2) end
            for xminusy=lineVacancy[xplusy],maxxminusy-2,-2 do
              if g.getcell((xplusy+xminusy)/2,(xplusy-xminusy)/2)~=0 then
                lineVacancy[xplusy]=xminusy
                lineVacancyExact[xplusy]=true -- anything except nil
                break
              end
            end
         end
         if lineVacancyExact[xplusy]==nil then
            lineVacancy[xplusy]=maxxminusy-2+((maxxminusy+xplusy)%2)
	 end
         if lineVacancy[xplusy]>maxxminusy then
         	maxxminusy=lineVacancy[xplusy]
         end
      end
      maxxminusy = maxxminusy+(maxxminusy+line)%2
      anotation = parityTest(phase,line,maxxminusy)
      aCache = aCache..anotation
      commaPos = string.find(anotation,",")
      sCache = sCache..string.sub(anotation,1,commaPos)
      g.show(sCache)
      anotation=string.sub(anotation,commaPos+1)
      commaPos = string.find(anotation,",")
      sCache = sCache..string.sub(anotation,1,commaPos-1).."}"
      if string.len(sCache)>80 then
        --g.sound("play", "beep.wav", 0.5)--ready to cancel ... when show is empty
        writeACache()
        writeSCache()
      end
      if string.len(aCache)>80 then
        writeACache()
      end
end

I have added layer 1 to debug a strange bug leading to "the DBCA onstruction did not work" ... I had bug in comparison of rectangle contents.
After the bug detected, I let it in the code, but it seems to me it's safe to remove the overhead. But it will reduce the multiplicative constant at most to one half of the current one ... (unles Golly runs out of resources). g.autoupdate() togling would help much more ... I expect.
Oh another not yet tested change ... added lineVacancyExact and LineVacancy contains either exact value or its upper bound ... it will save a lot of work with its updating. ... I will post change after testing ... done, seems it works. (Combining spaces with tabs is bad habbit )

Wow, I have debugged main issue around midday yesterday and interrupted the run few times to speedup the process a bit ... and today morning
the syntesis of ECCA is not finished yet ... the recepie is really long... I bet ECCA will be finished by noon today.
I didn't take too much care to incomming gliders of RCT15 and there was some collision near 0,0 and it already eaten SW portion of switching circuit.
So I hope the ECCA recepie will be finished before the collision could intervene.

Grrr, due to some bug in Golly, I was not able to save last pattern of the about 16 hours computation.
So I have the dependency file of the portion, but not the result of recepie:( ... so I have to run it again The ECCA was close to complete.
I could try to code playing the anotations ... it would run quickly through the recepie to reach the final pattern. ... run is so slow, setstep step is much faster. Hmm, I have lines wrongly in all anotations they should be all one higher .

I am planning to change cycle detecting glider xminusy placement to be usable for recepies which are not limited to minimal possible xminusy.

Start of current RCT15 DBCA "line program" (x+y) of extreme glider lines used as the SW glider line specification:

Code: Select all

{-109_-106,2}{-109_-106,2}{-129_-126,1}p256{-131_-128,1}p256{-133_-130,1}p256{-115_-112,2}
p256{-115_-112,2}p256{-105_-102,2}{-89_-86,1}remannts of collision removed>{-93_-90,1}
{-32_-29,2}{-31_-28,2}{-42_-39,2}{-45_-42,1}{-52_-49,0}{-69_-66,0}{-67_-64,0}{-79_-76,0}
ECCA arm block ready>{-79_-76,2}{41_44,2}{44_47,1}{46_49,0}{46_49,1}{52_55,0}{47_50,1}
{46_49,2}{54_57,2}gliderSE>{45_48,2}{43_46,2}{51_54,2}{60_63,2}{45_48,1}{65_68,0}
{64_67,2}{72_75,2}gliderSE>{63_66,2}{68_71,2}{60_63,2}{66_69,2}{49_52,1}{64_67,1}
{56_59,2}{47_50,2}{55_58,2}gliderSE>{46_49,2}{48_51,1}{47_50,0}{54_57,2}{57_60,1}
{49_52,1}{44_47,2}{52_55,0}{55_58,2}{57_60,2}{59_62,2}{54_57,1}{69_72,2}{70_73,1}
{80_83,2}{83_86,0}{90_93,1}{81_84,1}{98_101,2}{108_111,2}{112_115,0}{104_107,0}{112_115,1}
{111_114,2}{116_119,2}{112_115,2}{112_115,2}{120_123,2}{112_115,0}{107_110,2}{105_108,0}
{96_99,0}{91_94,1}{97_100,2}{88_91,2}{98_101,2}{91_94,0}{76_79,0}{96_99,0}{109_112,1}
{117_120,2}{120_123,1}{122_125,0}{122_125,0}{124_127,1}{117_120,1}{117_120,0}{127_130,1}
{133_136,1}{132_135,1}{132_135,2}{137_140,0}{126_129,1}{138_141,2}{145_148,0}{80_83,1}
{78_81,2}{75_78,0}{72_75,0}{91_94,2}{80_83,0}{74_77,1}{82_85,0}{87_90,2}{77_80,2}
{77_80,2}{87_90,2}{82_85,2}{77_80,0}{90_93,1}{82_85,2}{82_85,2}{82_85,1}{78_81,2}
{88_91,1}{83_86,1}{74_77,1}{84_87,2}{69_72,2}{66_69,1}SW prep for jump far SE ready>{58_61,1}
{4_7,1}{2_5,2}{6_9,1}{-7_-4,2}{-7_-4,2}{12_15,0}{20_23,2}{9_12,2}{19_22,2}{44_47,2}
{45_48,2}{45_48,2}{47_50,2}{49_52,2}{48_51,2}{51_54,2}{59_62,2}{71_74,2}{74_77,0}
{81_84,1}{72_75,1}{89_92,2}{108_111,2}{110_113,2}{112_115,2}{111_114,2}{114_117,2}
{122_125,2}{125_128,2}{122_125,1}{124_127,1}{109_112,1}{114_117,1}{127_130,2}{144_147,2}
{148_151,1}{155_158,0}{172_175,0}{170_173,0}{189_192,1}{191_194,2}{193_196,2}{195_198,2}
{194_197,2}{197_200,2}{205_208,2}{208_211,2}{213_216,1}{205_208,2}{212_215,1}{191_194,0}
{193_196,2}{192_195,2}{188_191,1}{188_191,1}{195_198,0}{190_193,1}{203_206,2}{104_107,2}
{104_107,2}{115_118,2}{105_108,2}{81_84,2}{72_75,2}{81_84,2}{75_78,2}{76_79,2}{89_92,2}
{69_72,2}{65_68,1}{63_66,0}{55_58,0}{70_73,1}{49_52,1}{70_73,0}{40_43,2}{40_43,2}
{51_54,2}{41_44,2}{96_99,2}{99_102,0}{106_109,1}{97_100,1}{114_117,2}{133_136,2}{136_139,1}
{134_137,1}{142_145,1}{139_142,2}{135_138,2}{131_134,2}{147_150,2}{136_139,2}{148_151,2}
{144_147,1}{148_151,0}{143_146,2}{163_166,2}{154_157,2}{142_145,2}{139_142,1}{127_130,2}
{114_117,2}{114_117,0}{108_111,1}{123_126,2}{114_117,0}{121_124,2}{116_119,2}{114_117,0}
{99_102,0}{143_146,0}{147_150,2}{156_159,2}{156_159,2}{159_162,1}{154_157,0}{143_146,2}
{150_153,2}{146_149,1}{148_151,1}{151_154,1}{138_141,2}{134_137,0}{147_150,2}{139_142,1}
{128_131,0}{129_132,1}{135_138,1}{148_151,2}{153_156,2}{161_164,2}{153_156,0}{140_143,1}
{131_134,2}{160_163,1}{155_158,2}{148_151,2}{156_159,0}{169_172,1}{178_181,2}{150_153,1}
{154_157,2}{157_160,1}{154_157,0}{160_163,2}{168_171,2}{176_179,2}{168_171,1}{162_165,0}
{160_163,2}{161_164,1}{162_165,0}{164_167,2}{167_170,0}{177_180,1}{172_175,0}{161_164,0}
{160_163,2}{176_179,1}{174_177,0}{173_176,2}{174_177,1}{167_170,1}{174_177,1}{180_183,1}
{180_183,2}{161_164,2}{142_145,2}{139_142,1}{143_146,0}{138_141,2}{142_145,1}{139_142,0}
{127_130,2}{124_127,1}{128_131,0}{132_135,2}{127_130,1}{147_150,1}{142_145,2}{121_124,0}
{115_118,0}{113_116,2}{124_127,2}{119_122,2}{89_92,2}{89_92,2}{86_89,0}{79_82,1}{88_91,1}
{71_74,2}{61_64,2}{64_67,1}{71_74,0}{66_69,1}{59_62,0}{33_36,2}{37_40,1}{35_38,1}
{32_35,1}{17_20,2}{25_28,2}{19_22,2}{23_26,0}{29_32,1}{21_24,2}{25_28,1}{25_28,0}
{39_42,2}{39_42,1}{37_40,1}{51_54,0}{46_49,0}{41_44,2}{33_36,2}{60_63,2}{51_54,2}
{51_54,1}{47_50,2}{45_48,2}{49_52,1}{64_67,0}{103_106,2}{102_105,2}{99_102,1}{107_110,1}
{103_106,1}{110_113,0}{102_105,2}{86_89,0}{72_75,0}{71_74,0}{69_72,2}{70_73,1}{56_59,1}
{65_68,1}{65_68,0}{69_72,1}{72_75,0}{74_77,2}{100_103,2}{103_106,1}{95_98,1}{96_99,0}
{104_107,1}{94_97,2}{107_110,2}{99_102,2}{116_119,1}{116_119,2}{114_117,0}{119_122,1}
{112_115,0}{109_112,0}{120_123,1}{133_136,2}{113_116,2}{104_107,2}{111_114,1}{103_106,2}
{109_112,1}{120_123,0}{115_118,1}{119_122,2}{131_134,2}{128_131,2}{128_131,0}{147_150,2}
{170_173,2}{169_172,1}{167_170,1}{181_184,0}{176_179,0}{171_174,2}{163_166,2}{179_182,2}{189_192,2}
{180_183,2}{184_187,1}{176_179,1}{177_180,1}{179_182,0}{183_186,2}{141_144,0}{145_148,0}
{125_128,0}{157_160,2}{157_160,0}{145_148,1}{156_159,0}{161_164,0}{154_157,0}{146_149,2}
{142_145,1}{158_161,2}{147_150,1}{148_151,1}{148_151,2}{156_159,2}{150_153,2}{154_157,0}
{145_148,0}{140_143,2}{52_55,2}{55_58,0}{57_60,1}{55_58,0}{60_63,0}{61_64,2}{41_44,2}
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{1360_1363,0}{1351_1354,0}{1335_1338,2}{1334_1337,0}{1336_1339,1}{1336_1339,0}{1327_1330,1}
{1334_1337,1}{1337_1340,2}{1330_1333,2}{1327_1330,0}{1329_1332,0}{1312_1315,1}{1321_1324,1}
{1315_1318,1}{1335_1338,1}{1361_1364,1}{1354_1357,0}{1352_1355,1}{1357_1360,2}{1357_1360,2}
{1356_1359,0}{1365_1368,0}{1352_1355,2}{1355_1358,1}{1364_1367,0}{1364_1367,0}{1332_1335,0}
{1333_1336,0}{1324_1327,2}{1328_1331,1}{1320_1323,1}{1320_1323,0}{1316_1319,2}{1318_1321,2}
{1321_1324,0}{1308_1311,2}{1312_1315,1}{1312_1315,1}{1321_1324,1}{1313_1316,0}{1301_1304,0}
{1308_1311,2}{1308_1311,2}{1305_1308,1}{1318_1321,2}{1310_1313,1}{1316_1319,0}{1316_1319,2}
{1323_1326,2}{1325_1328,2}{1314_1317,1}{1318_1321,2}{1335_1338,1}{1333_1336,2}{1332_1335,0}
{1310_1313,1}{1299_1302,2}{1292_1295,2}{1293_1296,1}{1290_1293,0}{1289_1292,2}{1292_1295,2}
{1287_1290,1}{1284_1287,1}{1295_1298,0}{1294_1297,0}{1252_1255,2}{1250_1253,2}{1247_1250,0}
{1237_1240,1}{1239_1242,1}{1249_1252,0}{1260_1263,0}{1261_1264,1}{1237_1240,1}{1199_1202,2}
{1202_1205,1}{1207_1210,0}{1198_1201,2}{1186_1189,2}{1195_1198,2}{1204_1207,2}{1199_1202,2}
{1194_1197,0}{1200_1203,1}{1203_1206,1}{1201_1204,1}{1208_1211,0}{1206_1209,2}{1196_1199,2}
{1203_1206,0}{1216_1219,0}{1214_1217,0}{1197_1200,1}{1209_1212,2}{1219_1222,2}{1218_1221,1}
{1232_1235,1}{1233_1236,0}{1230_1233,1}{1218_1221,0}{1216_1219,0}{1214_1217,2}{1214_1217,1}
{1215_1218,1}{1215_1218,1}{1187_1190,1}{1187_1190,0}{1229_1232,2}{1239_1242,2}{1232_1235,0}
{1217_1220,0}{1237_1240,0}{1250_1253,1}{1249_1252,2}{1246_1249,1}{1259_1262,2}{1247_1250,1}
{1254_1257,2}{1257_1260,2}{1221_1224,1}{1228_1231,2}{1231_1234,0}{1239_1242,0}{1243_1246,0}
{1247_1250,0}{1249_1252,1}{1249_1252,0}{1246_1249,0}{1254_1257,0}{1225_1228,2}{1228_1231,1}
{1238_1241,0}{1223_1226,1}{1223_1226,1}{1196_1199,2}{1168_1171,2}{1171_1174,2}{1166_1169,0}
{1163_1166,1}{1170_1173,1}{1168_1171,1}{1167_1170,2}{1165_1168,2}{1168_1171,2}{1161_1164,2}
{1159_1162,2}{1165_1168,2}{1154_1157,0}{1146_1149,0}{1160_1163,2}{1157_1160,0}{1149_1152,0}
{1152_1155,1}{1169_1172,1}{1170_1173,2}{1149_1152,2}{1160_1163,1}{1164_1167,2}{1162_1165,2}
{1165_1168,1}{1173_1176,1}{1162_1165,0}{1157_1160,0}{1156_1159,1}{1148_1151,2}{1148_1151,1}
{1133_1136,1}{1138_1141,0}{1146_1149,1}{1146_1149,1}{1149_1152,1}{1163_1166,0}{1140_1143,0}
{1147_1150,1}{1142_1145,2}{1141_1144,1}{1150_1153,1}{1144_1147,0}{1144_1147,1}{1142_1145,0}
{1139_1142,0}{1156_1159,2}{1146_1149,2}{1153_1156,0}{1168_1171,1}{1165_1168,0}{1160_1163,2}
{1160_1163,2}{1164_1167,1}{1156_1159,1}{1151_1154,2}{1160_1163,0}{1154_1157,2}{1161_1164,2}
{1164_1167,1}{1188_1191,2}{1194_1197,0}{1187_1190,1}{1171_1174,0}{1158_1161,2}{1167_1170,1}
{1157_1160,2}{1161_1164,2}{1153_1156,2}{1156_1159,0}{1148_1151,0}{1158_1161,0}{1163_1166,2}
{1155_1158,2}{1155_1158,2}{1158_1161,2}{1153_1156,0}{1168_1171,0}{1159_1162,0}{1148_1151,1}
{1147_1150,2}{1140_1143,2}{1134_1137,2}{1125_1128,2}{1130_1133,2}{1135_1138,0}{1127_1130,1}
{1125_1128,2}{1123_1126,2}{1124_1127,2}{1117_1120,2}{1125_1128,1}{1131_1134,1}{1150_1153,1}
{1143_1146,1}{1146_1149,1}{1144_1147,2}{1140_1143,0}{1137_1140,0}{1142_1145,0}{1138_1141,0}
{1155_1158,1}{1151_1154,2}{1156_1159,2}{1145_1148,2}{1145_1148,2}{1145_1148,2}{1141_1144,0}
{1138_1141,0}{1139_1142,0}{1142_1145,0}{1150_1153,2}{1151_1154,2}{1142_1145,2}{1153_1156,2}
{1151_1154,2}{1142_1145,2}{1142_1145,1}{1142_1145,1}{1158_1161,0}{1157_1160,0}{1167_1170,2}
{1158_1161,2}{1156_1159,2}{1156_1159,0}{1139_1142,2}{1148_1151,2}{1170_1173,1}{1203_1206,2}
{1187_1190,0}{1186_1189,1}{1193_1196,2}{1190_1193,2}{1195_1198,1}{1200_1203,0}{1196_1199,1}
{1210_1213,2}{1210_1213,2}{1199_1202,2}{1199_1202,2}{1196_1199,1}{1194_1197,0}{1190_1193,0}
{1195_1198,0}{1201_1204,1}{1188_1191,1}{1190_1193,2}{1193_1196,1}{1195_1198,0}{1199_1202,0}
{1194_1197,0}{1188_1191,1}{1201_1204,1}{1208_1211,2}{1215_1218,2}{1203_1206,0}{1195_1198,0}
{1205_1208,0}{1202_1205,0}{1207_1210,2}{1211_1214,1}{1213_1216,0}{1215_1218,0}{1212_1215,1}
{1203_1206,2}{1201_1204,2}{1192_1195,2}{1199_1202,0}{1196_1199,1}{1197_1200,1}{1209_1212,0}
{1202_1205,1}{1194_1197,1}{1195_1198,2}{1191_1194,0}{1187_1190,0}{1188_1191,0}{1196_1199,0}
{1206_1209,2}{1197_1200,2}{1187_1190,2}{1187_1190,2}{1191_1194,1}{1195_1198,1}{1196_1199,1}
{1173_1176,1}{1162_1165,2}{1153_1156,2}{1163_1166,2}{1156_1159,1}{1167_1170,1}{1158_1161,1}
{1147_1150,1}{1148_1151,1}{1162_1165,2}{1169_1172,2}{1163_1166,2}{1161_1164,0}{1169_1172,1}
{1166_1169,0}{1159_1162,2}{1163_1166,0}{1195_1198,0}{1197_1200,0}{1191_1194,0}{1202_1205,0}
{1210_1213,2}{1217_1220,2}{1205_1208,0}{1209_1212,0}{1208_1211,0}{1204_1207,1}{1214_1217,1}
{1215_1218,0}{1189_1192,2}{1196_1199,2}{1199_1202,2}{1194_1197,0}{1191_1194,1}{1202_1205,1}
{1199_1202,1}{1206_1209,0}{1199_1202,2}{1199_1202,1}{1196_1199,2}{1207_1210,0}{1213_1216,1}
{1218_1221,1}{1217_1220,0}{1209_1212,2}{1208_1211,2}{1207_1210,0}{1195_1198,0}{1201_1204,0}
{1186_1189,1}{1187_1190,0}{1197_1200,2}{1216_1219,2}{1240_1243,2}{1250_1253,2}{1253_1256,0}
{1240_1243,2}{1248_1251,0}{1261_1264,1}{1258_1261,1}{1242_1245,0}{1257_1260,2}{1252_1255,2}
{1249_1252,2}{1254_1257,0}{1249_1252,0}{1256_1259,0}{1256_1259,1}{1251_1254,0}{1256_1259,2}
{1266_1269,2}{1262_1265,0}{1254_1257,1}{1248_1251,1}{1260_1263,1}{1257_1260,0}{1254_1257,0}
{1253_1256,2}{1261_1264,2}{1244_1247,0}{1247_1250,1}{1243_1246,0}{1239_1242,0}{1255_1258,2}
{1255_1258,2}{1255_1258,2}{1263_1266,2}{1251_1254,0}{1253_1256,0}{1256_1259,2}{1239_1242,0}
{1252_1255,1}{1255_1258,2}{1264_1267,2}{1281_1284,2}{1281_1284,2}{1281_1284,0}{1282_1285,1}
{1286_1289,0}{1291_1294,1}{1283_1286,2}{1263_1266,2}{1266_1269,2}{1259_1262,2}{1265_1268,2}
{1247_1250,2}{1224_1227,2}{1226_1229,2}{1207_1210,0}{1206_1209,2}{1215_1218,0}{1207_1210,1}
{1199_1202,2}{1196_1199,0}{1186_1189,1}{1188_1191,1}{1198_1201,0}{1209_1212,0}{1210_1213,1}
{1238_1241,2}{1242_1245,1}{1248_1251,0}{1229_1232,2}{1237_1240,2}{1247_1250,2}{1247_1250,1}
{1259_1262,0}{1247_1250,1}{1243_1246,1}{1248_1251,1}{1251_1254,2}{1258_1261,2}{1268_1271,2}
{1268_1271,2}{1264_1267,1}{1260_1263,1}{1259_1262,1}{1247_1250,2}{1222_1225,2}{1221_1224,2}
{1221_1224,2}{1225_1228,0}{1233_1236,1}{1219_1222,0}{1186_1189,1}{1173_1176,1}{1155_1158,1}
{1164_1167,0}{1163_1166,2}{1158_1161,0}{1162_1165,1}{1167_1170,1}{1141_1144,2}{1128_1131,2}
{1124_1127,1}{1126_1129,1}{1129_1132,1}{1138_1141,1}{1129_1132,1}{1154_1157,2}{1141_1144,1}
{1139_1142,0}{1138_1141,2}{1141_1144,2}{1145_1148,2}{1148_1151,2}{1155_1158,2}{1144_1147,2}
{1159_1162,2}{1151_1154,2}{1160_1163,2}{1167_1170,2}{1150_1153,1}{1149_1152,2}{1155_1158,1}
{1165_1168,0}{1161_1164,1}{1161_1164,1}{1143_1146,2}{1146_1149,1}{1150_1153,0}{1157_1160,1}
{1148_1151,2}{1151_1154,2}{1148_1151,2}{1151_1154,0}{1154_1157,0}{1149_1152,0}{1161_1164,1}
{1163_1166,0}{1165_1168,2}{1165_1168,0}{1155_1158,0}{1162_1165,0}{1172_1175,0}{1152_1155,2}
{1153_1156,2}{1161_1164,2}{1158_1161,2}{1154_1157,0}{1151_1154,1}{1152_1155,2}{1167_1170,1}
{1168_1171,0}{1151_1154,2}{1148_1151,2}{1153_1156,0}{1161_1164,2}{1131_1134,2}{1139_1142,1}
{1136_1139,1}{1157_1160,2}{1149_1152,2}{1163_1166,2}{1163_1166,2}{1167_1170,2}{1208_1211,1}
{1215_1218,0}{1232_1235,0}{1236_1239,0}{1215_1218,2}{1205_1208,2}{1205_1208,2}{1202_1205,1}
{1194_1197,1}{1208_1211,1}{1198_1201,0}{1209_1212,0}{1191_1194,2}{1195_1198,1}{1200_1203,0}
{1199_1202,1}{1206_1209,2}{1213_1216,2}{1206_1209,0}{1211_1214,2}{1215_1218,2}{1198_1201,0}
{1192_1195,2}{1201_1204,2}{1194_1197,1}{1198_1201,0}{1193_1196,2}{1170_1173,2}{1195_1198,1}
{1190_1193,2}{1219_1222,0}{1227_1230,2}{1227_1230,2}{1231_1234,1}{1246_1249,2}{1237_1240,1}
{1232_1235,1}{1218_1221,2}{1209_1212,1}{1198_1201,2}{1230_1233,2}{1232_1235,2}{1232_1235,1}
{1238_1241,0}{1243_1246,1}{1244_1247,0}{1222_1225,0}{1235_1238,2}{1244_1247,2}{1243_1246,0}
{1249_1252,1}{1234_1237,2}{1243_1246,0}{1256_1259,1}{1321_1324,1}{1372_1375,2}{1423_1426,2}
{1426_1429,2}{1428_1431,2}{1427_1430,2}{1430_1433,2}{1446_1449,2}{1437_1440,2}{1438_1441,0}
{1424_1427,0}{1426_1429,2}{1431_1434,1}{1405_1408,1}{1400_1403,1}{1407_1410,2}{1397_1400,2}
{1397_1400,2}{1401_1404,1}{1405_1408,0}{1401_1404,0}{1396_1399,2}{1400_1403,1}{1381_1384,2}
{1374_1377,1}{1359_1362,1}{1379_1382,1}{1396_1399,0}{1395_1398,0}{1395_1398,2}{1396_1399,1}
{1395_1398,1}{1395_1398,1}{1440_1443,2}{1441_1444,1}{1433_1436,0}{1433_1436,1}{1428_1431,1}
{1441_1444,1}{1440_1443,0}{1438_1441,2}{1446_1449,2}{1458_1461,2}{1454_1457,0}{1462_1465,0}
{1461_1464,0}{1461_1464,0}{1467_1470,2}{1457_1460,0}{1455_1458,0}{1440_1443,2}{1443_1446,0}
{1427_1430,0}{1425_1428,0}{1432_1435,0}{1440_1443,1}{1453_1456,2}{1456_1459,2}{1454_1457,0}
{1451_1454,0}{1423_1426,1}{1423_1426,0}{1421_1424,2}{1421_1424,0}{1412_1415,0}{1412_1415,1}
{1423_1426,1}{1424_1427,0}{1422_1425,0}{1419_1422,1}{1426_1429,0}{1432_1435,2}{1435_1438,2}
{1430_1433,0}{1425_1428,1}{1442_1445,1}{1440_1443,0}{1447_1450,1}{1439_1442,1}{1438_1441,2}
{1448_1451,2}{1443_1446,2}{1444_1447,2}{1441_1444,1}{1435_1438,1}{1434_1437,2}{1425_1428,2}
{1436_1439,2}{1411_1414,2}{1418_1421,2}{1406_1409,0}{1409_1412,1}{1407_1410,0}{1402_1405,0}
{1398_1401,2}{1398_1401,2}{1424_1427,2}{1428_1431,1}{1432_1435,0}{1420_1423,2}{1416_1419,0}
{1419_1422,1}{1399_1402,2}{1396_1399,1}{1409_1412,2}{1401_1404,1}{1407_1410,0}{1405_1408,2}
{1455_1458,2}{1445_1448,0}{1442_1445,2}{1442_1445,2}{1435_1438,2}{1442_1445,0}{1437_1440,2}
{1427_1430,1}{1425_1428,2}{1428_1431,2}{1424_1427,1}{1450_1453,0}{1440_1443,2}{1456_1459,2}
{1456_1459,0}{1471_1474,0}{1466_1469,1}{1476_1479,1}{1463_1466,1}{1451_1454,1}{1461_1464,1}
{1471_1474,2}{1479_1482,2}{1462_1465,0}{1474_1477,0}{1470_1473,2}{1420_1423,0}{1437_1440,1}
{1405_1408,0}{1431_1434,1}{1420_1423,0}{1408_1411,2}{1407_1410,1}{1407_1410,1}{1422_1425,1}
{1425_1428,1}{1408_1411,1}{1412_1415,0}{1422_1425,2}{1426_1429,0}{1413_1416,2}{1411_1414,2}
{1421_1424,0}{1420_1423,0}{1419_1422,0}{1415_1418,2}{1437_1440,1}{1419_1422,2}{1422_1425,1}
{1424_1427,0}{1406_1409,2}{1429_1432,1}{1421_1424,1}{1419_1422,1}{1424_1427,0}{1430_1433,2}
{1440_1443,0}{1422_1425,2}{1418_1421,1}{1410_1413,0}{1431_1434,2}{1425_1428,1}{1420_1423,0}
{1436_1439,0}{1415_1418,1}{1415_1418,0}{1406_1409,0}{1404_1407,2}{1414_1417,2}{1405_1408,2}
{1403_1406,2}{1366_1369,1}{1359_1362,2}{1367_1370,2}{1369_1372,2}{1358_1361,1}{1372_1375,0}
{1364_1367,0}{1358_1361,0}{1350_1353,1}{1339_1342,2}{1343_1346,1}{1351_1354,0}{1357_1360,1}
{1337_1340,1}{1332_1335,0}{1348_1351,1}{1320_1323,2}{1323_1326,2}{1323_1326,0}{1308_1311,0}
{1310_1313,1}{1314_1317,1}{1324_1327,2}{1340_1343,2}{1340_1343,2}{1337_1340,2}{1342_1345,1}
{1337_1340,0}{1327_1330,1}{1329_1332,1}{1333_1336,1}{1325_1328,2}{1315_1318,2}{1322_1325,1}
{1317_1320,1}{1324_1327,1}{1317_1320,1}{1307_1310,2}{1284_1287,2}{1287_1290,2}{1295_1298,2}
{1300_1303,2}{1303_1306,2}{1298_1301,2}{1303_1306,2}{1299_1302,2}{1247_1250,1}{1234_1237,2}
{1244_1247,2}{1239_1242,2}{1234_1237,1}{1217_1220,2}{1220_1223,1}{1226_1229,0}{1216_1219,2}
{1220_1223,2}{1215_1218,2}{1216_1219,2}{1207_1210,2}{1204_1207,0}{1212_1215,0}{1211_1214,1}
{1205_1208,2}{1218_1221,1}{1215_1218,2}{1218_1221,2}{1218_1221,1}{1218_1221,0}{1205_1208,1}
{1221_1224,0}{1204_1207,2}{1192_1195,2}{1196_1199,1}{1168_1171,0}{1171_1174,2}{1171_1174,0}
{1159_1162,1}{1151_1154,2}{1144_1147,2}{1170_1173,0}{1166_1169,0}{1169_1172,1}{1165_1168,2}
{1161_1164,0}{1149_1152,0}{1153_1156,2}{1188_1191,1}{1189_1192,1}{1190_1193,0}{1190_1193,2}
{1199_1202,2}{1189_1192,2}{1196_1199,0}{1193_1196,1}{1196_1199,0}{1206_1209,1}{1207_1210,0}
{1195_1198,2}{1240_1243,0}{1247_1250,0}{1246_1249,2}{1246_1249,0}{1247_1250,1}{1253_1256,1}

Seems 2 "phase" is about half of the recepie. (may be a bit less during builds of narrow cuircuits)

I have finished ECCA portion, and portion to prepare to jumpFSE, but now I am confused after "JumpFSE{108_111,2}".
The plan was to copy far SE near the origin and anotate plan near the origin.
But seem I have to draw the pattern manualy as Golly refutes to work so far from the origin.
Maybe I have to draw initial few gliders near the origin ...

[Hippo.69]

Here is final version of the code snippet:

Code: Select all

function safeBorderRect(rect)
  local cells
  while true do
    cells=g.getcells({rect[1]-1,rect[2],2,rect[4]})
    if #cells>0 then
      rect[1]=rect[1]-1
      rect[3]=rect[3]+1
      goto continue
    end
    cells=g.getcells({rect[1],rect[2]-1,rect[3],2})
    if #cells>0 then
      rect[2]=rect[2]-1
      rect[4]=rect[4]+1
      goto continue
    end
    cells=g.getcells({rect[1]+rect[3]-2,rect[2],2,rect[4]})
    if #cells>0 then
      rect[3]=rect[3]+1
      goto continue
    end
    cells=g.getcells({rect[1],rect[2]+rect[4]-2,rect[3],2})
    if #cells>0 then
      rect[4]=rect[4]+1
      goto continue
    end
    break
    ::continue::
  end
  return rect
end

function parityTest(phase,line,maxxminusy)
  local orig,muster,prev,curr,rect,t,i,result,mustert
  rect = {(line-952+maxxminusy)/2-47,(line-952-maxxminusy)/2-33,85,85}
  if playCount<11 then
    rect = {(line-952+maxxminusy)/2-17,(line-952-maxxminusy)/2-5,25,25}
  end
  local xored = {}
--  local res = "{"..(line-952).."_"..(line-949).."," <= this is wrong
  local res = "{"..(line-951).."_"..(line-948).."," 
  rect = safeBorderRect(rect)
  g.select(rect)
  g.fitsel()
  g.setmag(1)
  orig = g.getcells(rect)
  g.putcells(glider[phase+1],(line-952+maxxminusy)/2+4,(line-952-maxxminusy)/2-4)
  prev = g.getcells(rect)
  t=0
  while true do
    g.advance(0,8) --p8 curcitry nearby
    t=t+8
    curr=g.getcells(rect)
    if comparerectfills(prev,curr) then
 --   g.note("orig stabilised at time "..t)
      muster=curr
      mustert=t
      break
    end
    prev=curr
    if t>1000 then
      sCache=sCache.."orig not stabilised!"
      aCache=aCache.."orig not stabilised!"
      writeACache()
      writeSCache()
      g.note("orig not stabilised!")
      g.putcells(orig,0,0,1,0,0,1,"copy")
      return res
    end
  end
  for i=1,#orig,2 do
    if g.getcell(orig[i],orig[i+1])~=1 then --change in the line
      lineVacancyExact[orig[i]+orig[i+1]]=nil
      if lineVacancy[orig[i]+orig[i+1]]~=nil then
        if lineVacancy[orig[i]+orig[i+1]]<orig[i]-orig[i+1] then
          lineVacancy[orig[i]+orig[i+1]]=orig[i]-orig[i+1]
        end
      end
      table.insert(xored,orig[i])
      table.insert(xored,orig[i+1])
    end
  end
  g.clear(0)
  g.putcells(orig,0,0,1,0,0,1,"copy")
 -- g.note("returned")
  for i=1,#muster,2 do
    if g.getcell(muster[i],muster[i+1])~=1 then --change in the line
      lineVacancyExact[muster[i]+muster[i+1]]=nil
      if lineVacancy[muster[i]+muster[i+1]]~=nil then
        if lineVacancy[muster[i]+muster[i+1]]<muster[i]-muster[i+1] then
          lineVacancy[muster[i]+muster[i+1]]=muster[i]-muster[i+1]
        end
      end
      table.insert(xored,muster[i])
      table.insert(xored,muster[i+1])
    end
  end
  g.putcells(glider[2-phase],(line-952+maxxminusy)/2+4,(line-952-maxxminusy)/2-4)
  prev = g.getcells(rect)
  t=0
  while true do
    g.advance(0,8) --p8 curcitry nearby
    t=t+8
    curr=g.getcells(rect)
    if comparerectfills(prev,curr) then
  --  g.note("other stabilised at time "..t)
      result = comparerectfills(curr,muster)
      break
    end
    prev=curr
    if t>8+mustert then
  --  g.note("other not stabilised")
      result=false
      break
    end
  end
  g.clear(0)
  g.putcells(orig,0,0,1,0,0,1,"copy")
  g.putcells(glider[1+phase],(line-952+maxxminusy)/2+4,(line-952-maxxminusy)/2-4)
  --g.note("returned 2nd")
  if result then
    res=res.."2,"..maxxminusy..","
    --g.setlayer(1)
    --g.select(rect)
    --g.putcells(glider[2-phase],(line-952+maxxminusy)/2+3,(line-952-maxxminusy)/2-3)
    --g.setlayer(0)
    if t<mustert then
      t=mustert
    end
  else
    res=res..phase..","..maxxminusy..","
    --g.setlayer(1)
    --g.putcells(glider[1+phase],(line-952+maxxminusy)/2+3,(line-952-maxxminusy)/2-3)
    --g.setlayer(0)
    t=mustert
  end
  res=res..(t-4)..",{"
  for i=1,#xored-1 do
    res=res..xored[i]..","
  end
  res=res..xored[#xored].."},"..line.."}"
  --g.note("cancel")
  local log=math.ceil(math.log(t)/math.log(2))
  g.setstep(log)
  g.step()
  --g.setlayer(1)
  --g.setstep(log)
  --g.step()
  --g.setlayer(0)
  --g.note("cancel")
  return res
end

function process_commandPair(commandPair)
	local commaPos,line,phase,comment
      bBracePos = string.find(commandPair,"{")
      if bBracePos==nil then
        aCache=aCache.."command "..commandPair.."does not contain {"
        sCache=sCache.."command "..commandPair.."does not contain {"
        writeACache()
        writeSCache()
        g.note("command "..commandPair.."does not contain {")
      end
	commaPos = string.find(commandPair,",")
      comment = string.sub(commandPair,1,bBracePos-1)
      aCache = aCache..comment
      sCache = sCache..comment
      playCount=1+playCount
      g.show(sCache)
	line = tonumber(string.sub(commandPair,bBracePos+1,commaPos-1))
	phase = tonumber(string.sub(commandPair,commaPos+1))
      -- gliderminxplusy = line-951, glidermaxxplusy = line-948
      local xplusy,xminusy,maxxminusy
      for xplusy = line-951-3,line-948+3 do
        if lineVacancy[xplusy]==nil then lineVacancy[xplusy]=3056-(xplusy%2) end
      end
      local notfound=true
      while notfound do
        maxxminusy = lineVacancy[line-951-3]
        for xplusy = line-951-2,line-948+3 do
          if lineVacancy[xplusy]>maxxminusy then
            maxxminusy=lineVacancy[xplusy]
          end
        end
        g.show(sCache.." "..maxxminusy)
        for xplusy = line-951-3,line-948+3 do
          if lineVacancyExact[xplusy]==nil then
            if lineVacancy[xplusy]>maxxminusy-19 then
              lineVacancy[xplusy]=lineVacancy[xplusy]-20 --unless corrected
              for xminusy=lineVacancy[xplusy]+20,lineVacancy[xplusy]+2,-2 do
                if g.getcell((xplusy+xminusy)/2,(xplusy-xminusy)/2)~=0 then
                  lineVacancy[xplusy]=xminusy
                  lineVacancyExact[xplusy]=true -- anything except nil
                  break
                end
              end
            end
          elseif lineVacancy[xplusy]==maxxminusy then
            notfound = false
          end
        end
      end
      maxxminusy = maxxminusy+(maxxminusy+line)%2
      anotation = parityTest(phase,line,maxxminusy)
      aCache = aCache..anotation
      commaPos = string.find(anotation,",")
      sCache = sCache..string.sub(anotation,1,commaPos)
      g.show(sCache)
      anotation=string.sub(anotation,commaPos+1)
      commaPos = string.find(anotation,",")
      sCache = sCache..string.sub(anotation,1,commaPos-1).."}"
      if string.len(sCache)>80 then
        --g.sound("play", "beep.wav", 0.5)--ready to cancel ... when show is empty
        writeACache()
        writeSCache()
      end
      if string.len(aCache)>80 then
        writeACache()
      end
end

The constants 951 resp. 3056 should be adjusted for another SW salvo analysis (translation of line to xplusy / xminusy too close to construction arm not to hit that close).

[Hippo.69]

The next task is to troubleshoot and find out why. If anyone is following along with this thread, let me know if any questions are coming up that I'm not answering. I'm including some comments in the code, but am not really sure if they're useful to my audience (because I'm not sure I have an audience.)

I have used another approach in viewtopic.php?p=154745#p154745 when finding phase (in)dependences.
It seems to me, it must be faster to maintain "clean paths" ... lineVacancy than to let golly simulate. What I saved to long salvo describtion are safe positions for gliders and time before the pattern stabilises (if it fits to the simulated region). It does not necessary give optimal glider placement as the next glider could collide while further parts of the region stabilise). I was interested in rounding to powers of 2 rather to finding smallest possible distances ... so consider it to be fast approximating metthod. I bet it would help to use it as starting estimate for delta ...