Golly script coding practice

For scripts to aid with computation or simulation in cellular automata.
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dvgrn
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Golly script coding practice

Post by dvgrn » August 23rd, 2022, 11:09 am

I wasn't terribly surprised by the lack of response to my offer here --
dvgrn wrote:
August 17th, 2022, 6:08 pm
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.)

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dvgrn
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Re: Golly script coding practice

Post by dvgrn » August 25th, 2022, 11:02 am

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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394.2S$393.S2.S$394.2S$347.S$347.S$347.S$358.S$357.S.S$357.2S2$320.2S
$320.2S66.S$387.S.S$387.S2.S$388.2S4$316.2S$316.2S40.2S$357.S2.S$358.
2S2$354.3S2$358.S$358.S$358.S$326.2S$325.S.S32.2S$325.2S33.2S$370.3S$
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.

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otismo
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Re: Golly script coding practice

Post by otismo » August 25th, 2022, 12:02 pm

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 !
"One picture is worth 1000 words; but one thousand words, carefully crafted, can paint an infinite number of pictures."
- autonomic writing
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Re: Golly script coding practice

Post by dvgrn » August 25th, 2022, 1:22 pm

otismo wrote:
August 25th, 2022, 12:02 pm
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.

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Re: Golly script coding practice

Post by dvgrn » August 26th, 2022, 4:20 pm

dvgrn wrote:
August 25th, 2022, 1:22 pm
... 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 --

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dvgrn
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Re: Golly script coding practice

Post by dvgrn » August 28th, 2022, 9:57 pm

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/greedd/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.

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dvgrn
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Re: Golly script coding practice

Post by dvgrn » August 29th, 2022, 9:03 am

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$114135.M$
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3M679$98743.M$98741.2M$98742.2M1134$97616.M$97616.M.M$97616.2M1294$
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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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M$14312.3M596$13718.M$13717.M$13717.3M589$13135.M$13134.M$13134.3M
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100.2H13.2H10.3H$92.H.2H.H30.H$88.6H3.H22.H6.3H$87.H4.H.H25.4H4.5H$
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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$200.A.A$
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214.A35.3H$249.H.H.2H$237.H10.3H.3H$198.2A13.2A22.3H12.H2.H$198.2A13.
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227.2H13.2H4.H$227.2H13.2H9.H.2H$222.2H24.H6.H$218.3H.3H30.H2.H$214.
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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$298.S2.S$
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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 1 time
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

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dvgrn
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Re: Golly script coding practice

Post by dvgrn » September 1st, 2022, 10:24 pm

dvgrn wrote:
August 29th, 2022, 9:03 am
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) Not downloaded yet
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.

User avatar
dvgrn
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Posts: 9103
Joined: May 17th, 2009, 11:00 pm
Location: Madison, WI
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Re: Golly script coding practice

Post by dvgrn » September 11th, 2022, 9:34 am

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, 1], [-29, 0], [-37, 0], [-33, 0], [-33, 0], [-43, 1], [-35, 0], [-27, 0], [-7, 1], [-37, 0], [-7, 1], [-1, 1], [-1, 0], [-3, 0], [11, 1], [3, 1], [3, 1], [1, 0], [-15, 1], [-29, 0], [-29, 0], [-11, 1], [37, 1], [27, 1], [27, 1], [31, 0], [49, 0], [31, 0], [27, 1], [53, 0], [61, 0], [-19, 1], [-25, 1], [-9, 1], [-41, 0], [-29, 1], [-7, 1], [-23, 0], [-17, 0], [-13, 0], [-15, 0], [-9, 0], [7, 0], [13, 0], [33, 0], [19, 0], [-7, 1], [25, 0], [-23, 0], [-31, 0], [-31, 1], [-25, 1], [-11, 1], [-41, 1], [-57, 1], [-3, 0], [1, 1], [15, 1], [3, 1], [-21, 1], [-1, 1], [-7, 1], [5, 0], [45, 0], [65, 0], [65, 0], [49, 0], [77, 0], [77, 0], [85, 0], [-73, 0], [-79, 0], [-75, 0], [-87, 0], [-69, 1], [-101, 0], [-105, 1], [-103, 1], [-99, 0], [-105, 0], [-105, 0], [-127, 1], [-89, 0], [-93, 1], [-77, 1], [-97, 1], [-81, 0], [-87, 0], [-71, 0], [-95, 1], [-93, 1], [-71, 1], [-33, 0], [-29, 1], [-37, 1], [-43, 1], [-33, 1], [-29, 0], [-53, 0], [-57, 0], [-41, 0], [-69, 0], [-69, 0], [-77, 0], [-9, 0], [-3, 0], [9, 1], [-9, 0], [27, 0], [27, 0], [13, 0], [27, 0], [-15, 0], [-9, 0], [7, 1], [17, 1], [-5, 1], [-5, 0], [13, 0], [13, 1], [29, 1], [-5, 1], [1, 0], [-3, 0], [9, 0], [29, 0], [-15, 1], [-13, 1], [-39, 0], [-103, 0], [-63, 1], [-11, 0], [-43, 1], [-43, 1], [-13, 1], [-37, 0], [-45, 0], [-41, 0], [-41, 0], [-51, 1], [-43, 0], [-35, 0], [-15, 1], [-45, 0], [-15, 1], [-9, 1], [-9, 0], [-11, 0], [3, 1], [-5, 1], [-5, 1], [-7, 0], [-23, 1], [-37, 0], [-37, 0], [-19, 1], [29, 1], [19, 1], [19, 1], [23, 0], [41, 0], [23, 0], [19, 1], [45, 0], [53, 0], [-9, 0], [-29, 0], [-11, 0], [-19, 0], [-15, 1], [-23, 1], [-39, 0], [-33, 1], [-33, 1], [-25, 0], [-55, 1], [-37, 0], [-31, 0], [-27, 0], [-29, 0], [-23, 0], [-7, 0], [-1, 0], [19, 0], [5, 0], [-21, 1], [11, 0], [-37, 0], [-45, 0], [-45, 1], [-39, 1], [-25, 1], [-55, 1], [-71, 1], [-17, 0], [-13, 1], [1, 1], [-11, 1], [-35, 1], [-15, 1], [-21, 1], [-9, 0], [31, 0], [51, 0], [51, 0], [35, 0], [63, 0], [63, 0], [71, 0], [-87, 0], [-93, 0], [-89, 0], [-101, 0], [-83, 1], [-115, 0], [-119, 1], [-117, 1], [-113, 0], [-119, 0], [-119, 0], [-141, 1], [-103, 0], [-107, 1], [-91, 1], [-111, 1], [-95, 0], [-101, 0], [-85, 0], [-109, 1], [-107, 1], [-85, 1], [-47, 0], [-43, 1], [-51, 1], [-57, 1], [-47, 1], [-43, 0], [-67, 0], [-71, 0], [-55, 0], [-83, 0], [-83, 0], [-91, 0], [-23, 0], [-17, 0], [-5, 1], [-23, 0], [13, 0], [13, 0], [-1, 0], [13, 0], [-29, 0], [-23, 0], [-7, 1], [3, 1], [-19, 1], [-19, 0], [-1, 0], [-1, 1], [15, 1], [-19, 1], [-13, 0], [-17, 0], [-5, 0], [15, 0], [-29, 1], [-27, 1], [-53, 0], [-117, 0], [-77, 1], [-25, 0], [-57, 1], [-57, 1], [-27, 1], [-51, 0], [-59, 0], [-55, 0], [-55, 0], [-65, 1], [-57, 0], [-49, 0], [-29, 1], [-59, 0], [-29, 1], [-23, 1], [-23, 0], [-25, 0], [-11, 1], [-19, 1], [-19, 1], [-21, 0], [-37, 1], [-51, 0], [-51, 0], [-33, 1], [15, 1], [5, 1], [5, 1], [9, 0], [27, 0], [9, 0], [5, 1], [31, 0], [39, 0], [-23, 1], [-5, 1], [-5, 1], [3, 1], [-17, 1], [-17, 0], [-3, 0], [-21, 0], [-15, 0], [-11, 0], [-13, 0], [-7, 0], [9, 0], [15, 0], [35, 0], [21, 0], [-5, 1], [27, 0], [-21, 0], [-29, 0], [-29, 1], [-23, 1], [-9, 1], [-39, 1], [-55, 1], [-1, 0], [3, 1], [17, 1], [5, 1], [-19, 1], [1, 1], [-5, 1], [7, 0], [47, 0], [67, 0], [67, 0], [51, 0], [79, 0], [79, 0], [87, 0], [-71, 0], [-77, 0], [-73, 0], [-85, 0], [-67, 1], [-99, 0], [-103, 1], [-101, 1], [-97, 0], [-103, 0], [-103, 0], [-125, 1], [-87, 0], [-91, 1], [-75, 1], [-95, 1], [-79, 0], [-85, 0], [-69, 0], [-93, 1], [-91, 1], [-69, 1], [-31, 0], [-27, 1], [-35, 1], [-41, 1], [-31, 1], [-27, 0], [-51, 0], [-55, 0], [-39, 0], [-67, 0], [-67, 0], [-75, 0], [-7, 0], [-1, 0], [11, 1], [-7, 0], [29, 0], [29, 0], [15, 0], [29, 0], [-13, 0], [-7, 0], [9, 1], [19, 1], [-3, 1], [-3, 0], [15, 0], [15, 1], [31, 1], [-3, 1], [3, 0], [-1, 0], [11, 0], [31, 0], [-13, 1], [-11, 1], [-37, 0], [-101, 0], [-61, 1], [-9, 0], [-41, 1], [-41, 1], [-11, 1], [-35, 0], [-43, 0], [-39, 0], [-39, 0], [-49, 1], [-41, 0], [-33, 0], [-13, 1], [-43, 0], [-13, 1], [-7, 1], [-7, 0], [-9, 0], [5, 1], [-3, 1], [-3, 1], [-5, 0], [-21, 1], [-35, 0], [-35, 0], [-17, 1], [31, 1], [21, 1], [21, 1], [25, 0], [43, 0], [25, 0], [21, 1], [47, 0], [55, 0], [-25, 0], [-31, 0], [-1, 1], [17, 1], [3, 0], [-29, 1], [11, 1], [-5, 0], [1, 0], [5, 0], [3, 0], [9, 0], [25, 0], [31, 0], [51, 0], [37, 0], [11, 1], [43, 0], [-5, 0], [-13, 0], [-13, 1], [-7, 1], [7, 1], [-23, 1], [-39, 1], [15, 0], [19, 1], [33, 1], [21, 1], [-3, 1], [17, 1], [11, 1], [23, 0], [63, 0], [83, 0], [83, 0], [67, 0], [95, 0], [95, 0], [103, 0], [-55, 0], [-61, 0], [-57, 0], [-69, 0], [-51, 1], [-83, 0], [-87, 1], [-85, 1], [-81, 0], [-87, 0], [-87, 0], [-109, 1], [-71, 0], [-75, 1], [-59, 1], [-79, 1], [-63, 0], [-69, 0], [-53, 0], [-77, 1], [-75, 1], [-53, 1], [-15, 0], [-11, 1], [-19, 1], [-25, 1], [-15, 1], [-11, 0], [-35, 0], [-39, 0], [-23, 0], [-51, 0], [-51, 0], [-59, 0], [9, 0], [15, 0], [27, 1], [9, 0], [45, 0], [45, 0], [31, 0], [45, 0], [3, 0], [9, 0], [25, 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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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2 7861 0 7862 0
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3 7994 7995 0 0
4 0 8127 8128 8129
5 8126 0 8130 0
6 8114 0 8123 8131
3 0 0 0 8000
4 8133 0 8094 0
4 0 8081 8083 8084
4 0 7991 8093 0
5 8134 8135 0 8136
4 0 8002 0 0
5 0 8138 0 0
6 0 8137 0 8139
4 7996 0 0 0
5 0 0 8141 0
4 0 7864 0 0
3 0 0 0 8046
4 7870 0 0 8144
4 0 7877 0 0
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3 8043 8047 0 0
3 0 0 8057 0
4 8147 8148 7943 8149
5 8143 8145 8146 8150
3 0 7897 7953 7954
3 7924 0 7965 0
4 0 0 8152 8153
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7 8132 0 8140 8156
3 7957 0 7959 0
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2 7862 7860 7861 7868
3 7866 8161 7965 0
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3 0 0 0 8097
4 0 0 0 8167
5 8160 8163 8166 8168
3 0 7897 0 7910
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3 7897 7924 7954 7965
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5 8100 8109 8102 8199
2 7873 0 7875 0
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6 8195 8200 0 8204
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11 7765 0 7839 8223
12 413 2138 8224 0
3 7874 0 7876 0
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3 0 7910 0 0
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4 0 7885 7880 7887
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4 8226 0 0 8281
5 8279 8280 0 8282
6 8276 8278 0 8283
3 0 8120 0 0
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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
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6 0 0 8296 0
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4 8307 0 0 0
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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.

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dvgrn
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Re: Golly script coding practice

Post by dvgrn » September 13th, 2022, 2:30 pm

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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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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dvgrn
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Re: Golly script coding practice

Post by dvgrn » September 21st, 2022, 6:45 pm

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!

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dvgrn
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Re: Golly script coding practice

Post by dvgrn » September 21st, 2022, 9:59 pm

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, 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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.

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