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DS2-200p4cSol.py
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DS2-200p4cSol.py
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import matplotlib.pyplot as plt
plt.figure(figsize=(15,15))
plt.plot(0.255682,0.198925,'ro',color='#000000')
plt.plot(0.198864,0.172043,'ro',color='#000000')
plt.plot(0.181818,0.155914,'ro',color='#000000')
plt.plot(0.210227,0.150538,'ro',color='#000000')
plt.plot(0.193182,0.11828,'ro',color='#000000')
plt.plot(0.272727,0.155914,'ro',color='#000000')
plt.plot(0.323864,0.145161,'ro',color='#000000')
plt.plot(0.238636,0.155914,'ro',color='#000000')
plt.plot(0.193182,0.16129,'ro',color='#000000')
plt.plot(0.244318,0.129032,'ro',color='#000000')
plt.plot(0.267045,0.263441,'ro',color='#000000')
plt.plot(0.261364,0.284946,'ro',color='#000000')
plt.plot(0.210227,0.284946,'ro',color='#000000')
plt.plot(0.289773,0.204301,'ro',color='#000000')
plt.plot(0.244318,0.236559,'ro',color='#000000')
plt.plot(0.232955,0.252688,'ro',color='#000000')
plt.plot(0.198864,0.268817,'ro',color='#000000')
plt.plot(0.170455,0.204301,'ro',color='#000000')
plt.plot(0.244318,0.198925,'ro',color='#000000')
plt.plot(0.210227,0.236559,'ro',color='#000000')
plt.plot(0.181818,0.258065,'ro',color='#000000')
plt.plot(0.159091,0.193548,'ro',color='#000000')
plt.plot(0.153409,0.129032,'ro',color='#000000')
plt.plot(0.0113636,0.924731,'ro',color='#FF0000')
plt.plot(0.0170455,0.854839,'ro',color='#FF0000')
plt.plot(0.0568182,0.784946,'ro',color='#FF0000')
plt.plot(0.119318,0.677419,'ro',color='#FF0000')
plt.plot(0.170455,0.639785,'ro',color='#FF0000')
plt.plot(0.170455,0.682796,'ro',color='#FF0000')
plt.plot(0.1875,0.693548,'ro',color='#FF0000')
plt.plot(0.193182,0.72043,'ro',color='#FF0000')
plt.plot(0.147727,0.768817,'ro',color='#FF0000')
plt.plot(0.119318,0.822581,'ro',color='#FF0000')
plt.plot(0.125,0.876344,'ro',color='#FF0000')
plt.plot(0.0965909,0.956989,'ro',color='#FF0000')
plt.plot(0.0795455,0.973118,'ro',color='#FF0000')
plt.plot(0.0454545,0.94086,'ro',color='#FF0000')
plt.plot(0.0568182,0.860215,'ro',color='#FF0000')
plt.plot(0.0909091,0.817204,'ro',color='#FF0000')
plt.plot(0.119318,0.763441,'ro',color='#FF0000')
plt.plot(0.147727,0.725806,'ro',color='#FF0000')
plt.plot(0.198864,0.672043,'ro',color='#FF0000')
plt.plot(0.215909,0.666667,'ro',color='#FF0000')
plt.plot(0.244318,0.682796,'ro',color='#FF0000')
plt.plot(0.238636,0.698925,'ro',color='#FF0000')
plt.plot(0.227273,0.736559,'ro',color='#FF0000')
plt.plot(0.198864,0.77957,'ro',color='#FF0000')
plt.plot(0.159091,0.844086,'ro',color='#FF0000')
plt.plot(0.142045,0.892473,'ro',color='#FF0000')
plt.plot(0.0795455,0.94086,'ro',color='#FF0000')
plt.plot(0.0625,0.946237,'ro',color='#FF0000')
plt.plot(0.0738636,0.88172,'ro',color='#FF0000')
plt.plot(0.119318,0.806452,'ro',color='#FF0000')
plt.plot(0.147727,0.736559,'ro',color='#FF0000')
plt.plot(0.181818,0.682796,'ro',color='#FF0000')
plt.plot(0.227273,0.682796,'ro',color='#FF0000')
plt.plot(0.153409,0.650538,'ro',color='#FF0000')
plt.plot(0.130682,0.677419,'ro',color='#FF0000')
plt.plot(0.0909091,0.747312,'ro',color='#FF0000')
plt.plot(0.0681818,0.817204,'ro',color='#FF0000')
plt.plot(0.0340909,0.94086,'ro',color='#FF0000')
plt.plot(0.0227273,0.962366,'ro',color='#FF0000')
plt.plot(0.0852273,1,'ro',color='#FF0000')
plt.plot(0.119318,0.88172,'ro',color='#FF0000')
plt.plot(0.153409,0.833333,'ro',color='#FF0000')
plt.plot(0.164773,0.77957,'ro',color='#FF0000')
plt.plot(0.181818,0.72043,'ro',color='#FF0000')
plt.plot(0.210227,0.698925,'ro',color='#FF0000')
plt.plot(0.232955,0.672043,'ro',color='#FF0000')
plt.plot(0.227273,0.666667,'ro',color='#FF0000')
plt.plot(0.193182,0.639785,'ro',color='#FF0000')
plt.plot(0.0965909,0.731183,'ro',color='#FF0000')
plt.plot(0.0795455,0.784946,'ro',color='#FF0000')
plt.plot(0.0170455,0.887097,'ro',color='#FF0000')
plt.plot(0,0.919355,'ro',color='#FF0000')
plt.plot(0.0113636,0.956989,'ro',color='#FF0000')
plt.plot(0.0681818,0.978495,'ro',color='#FF0000')
plt.plot(0.107955,0.94086,'ro',color='#FF0000')
plt.plot(0.0965909,0.908602,'ro',color='#FF0000')
plt.plot(0.130682,0.865591,'ro',color='#FF0000')
plt.plot(0.153409,0.83871,'ro',color='#FF0000')
plt.plot(0.164773,0.72043,'ro',color='#FF0000')
plt.plot(0.153409,0.752688,'ro',color='#FF0000')
plt.plot(0.0795455,0.903226,'ro',color='#FF0000')
plt.plot(0.0795455,0.913978,'ro',color='#FF0000')
plt.plot(0.170455,0.645161,'ro',color='#FF0000')
plt.plot(0.1875,0.72043,'ro',color='#FF0000')
plt.plot(0.176136,0.752688,'ro',color='#FF0000')
plt.plot(0.647727,0.645161,'ro',color='#00FF00')
plt.plot(0.642045,0.591398,'ro',color='#00FF00')
plt.plot(0.647727,0.569892,'ro',color='#00FF00')
plt.plot(0.732955,0.553763,'ro',color='#00FF00')
plt.plot(0.727273,0.586022,'ro',color='#00FF00')
plt.plot(0.732955,0.623656,'ro',color='#00FF00')
plt.plot(0.795455,0.623656,'ro',color='#00FF00')
plt.plot(0.806818,0.612903,'ro',color='#00FF00')
plt.plot(0.704545,0.586022,'ro',color='#00FF00')
plt.plot(0.698864,0.634409,'ro',color='#00FF00')
plt.plot(0.659091,0.61828,'ro',color='#00FF00')
plt.plot(0.715909,0.586022,'ro',color='#00FF00')
plt.plot(0.784091,0.596774,'ro',color='#00FF00')
plt.plot(0.784091,0.623656,'ro',color='#00FF00')
plt.plot(0.738636,0.650538,'ro',color='#00FF00')
plt.plot(0.681818,0.666667,'ro',color='#00FF00')
plt.plot(0.659091,0.623656,'ro',color='#00FF00')
plt.plot(0.693182,0.596774,'ro',color='#00FF00')
plt.plot(0.767045,0.580645,'ro',color='#00FF00')
plt.plot(0.778409,0.575269,'ro',color='#00FF00')
plt.plot(0.857955,0.526882,'ro',color='#00FF00')
plt.plot(0.880682,0.580645,'ro',color='#00FF00')
plt.plot(0.857955,0.602151,'ro',color='#00FF00')
plt.plot(0.823864,0.564516,'ro',color='#00FF00')
plt.plot(0.8125,0.564516,'ro',color='#00FF00')
plt.plot(0.823864,0.548387,'ro',color='#00FF00')
plt.plot(0.869318,0.580645,'ro',color='#00FF00')
plt.plot(0.835227,0.575269,'ro',color='#00FF00')
plt.plot(0.744318,0.575269,'ro',color='#00FF00')
plt.plot(0.693182,0.575269,'ro',color='#00FF00')
plt.plot(0.698864,0.548387,'ro',color='#00FF00')
plt.plot(0.761364,0.543011,'ro',color='#00FF00')
plt.plot(0.835227,0.537634,'ro',color='#00FF00')
plt.plot(0.886364,0.844086,'ro',color='#00FF00')
plt.plot(0.721591,0.827957,'ro',color='#00FF00')
plt.plot(0.931818,0.758065,'ro',color='#00FF00')
plt.plot(1,0.66129,'ro',color='#00FF00')
plt.plot(0.801136,0.736559,'ro',color='#00FF00')
plt.plot(0.715909,0.188172,'ro',color='#00FF00')
plt.plot(0.6875,0.123656,'ro',color='#00FF00')
plt.plot(0.6875,0.0752688,'ro',color='#00FF00')
plt.plot(0.704545,0.0322581,'ro',color='#00FF00')
plt.plot(0.732955,0.0645161,'ro',color='#00FF00')
plt.plot(0.767045,0.11828,'ro',color='#00FF00')
plt.plot(0.727273,0.139785,'ro',color='#00FF00')
plt.plot(0.732955,0.16129,'ro',color='#00FF00')
plt.plot(0.795455,0.145161,'ro',color='#00FF00')
plt.plot(0.818182,0.0698925,'ro',color='#00FF00')
plt.plot(0.846591,0.155914,'ro',color='#00FF00')
plt.plot(0.772727,0.166667,'ro',color='#00FF00')
plt.plot(0.744318,0.112903,'ro',color='#00FF00')
plt.plot(0.8125,0.112903,'ro',color='#00FF00')
plt.plot(0.823864,0.112903,'ro',color='#00FF00')
plt.plot(0.8125,0.0483871,'ro',color='#00FF00')
plt.plot(0.795455,0.0698925,'ro',color='#00FF00')
plt.plot(0.772727,0.0698925,'ro',color='#00FF00')
plt.plot(0.761364,0.0483871,'ro',color='#00FF00')
plt.plot(0.744318,0.0268817,'ro',color='#00FF00')
plt.plot(0.698864,0.0322581,'ro',color='#00FF00')
plt.plot(0.755682,0.0322581,'ro',color='#00FF00')
plt.plot(0.801136,0.0376344,'ro',color='#00FF00')
plt.plot(0.840909,0.0537634,'ro',color='#00FF00')
plt.plot(0.863636,0.0967742,'ro',color='#00FF00')
plt.plot(0.875,0.145161,'ro',color='#00FF00')
plt.plot(0.795455,0.166667,'ro',color='#00FF00')
plt.plot(0.710227,0.16129,'ro',color='#00FF00')
plt.plot(0.710227,0.0967742,'ro',color='#00FF00')
plt.plot(0.710227,0.0215054,'ro',color='#00FF00')
plt.plot(0.8125,0.0107527,'ro',color='#00FF00')
plt.plot(0.857955,0.0376344,'ro',color='#00FF00')
plt.plot(0.852273,0.0752688,'ro',color='#00FF00')
plt.plot(0.869318,0.693548,'ro',color='#00FF00')
plt.plot(0.863636,0.72043,'ro',color='#00FF00')
plt.plot(0.852273,0.768817,'ro',color='#00FF00')
plt.plot(0.744318,0.741935,'ro',color='#00FF00')
plt.plot(0.784091,0.682796,'ro',color='#00FF00')
plt.plot(0.846591,0.682796,'ro',color='#00FF00')
plt.plot(0.909091,0.645161,'ro',color='#00FF00')
plt.plot(0.960227,0.693548,'ro',color='#00FF00')
plt.plot(0.801136,0.139785,'ro',color='#00FF00')
plt.plot(0.767045,0.129032,'ro',color='#00FF00')
plt.plot(0.801136,0.107527,'ro',color='#00FF00')
plt.plot(0.784091,0.0860215,'ro',color='#00FF00')
plt.plot(0.778409,0.0537634,'ro',color='#00FF00')
plt.plot(0.806818,0.0322581,'ro',color='#00FF00')
plt.plot(0.857955,0.112903,'ro',color='#00FF00')
plt.plot(0.823864,0.16129,'ro',color='#00FF00')
plt.plot(0.755682,0.182796,'ro',color='#00FF00')
plt.plot(0.755682,0.145161,'ro',color='#00FF00')
plt.plot(0.801136,0.0860215,'ro',color='#00FF00')
plt.plot(0.835227,0.11828,'ro',color='#00FF00')
plt.plot(0.738636,0.107527,'ro',color='#00FF00')
plt.plot(0.715909,0.102151,'ro',color='#00FF00')
plt.plot(0.261364,0.11828,'ro',color='#0000FF')
plt.plot(0.335227,0.145161,'ro',color='#0000FF')
plt.plot(0.227273,0.0806452,'ro',color='#0000FF')
plt.plot(0.25,0.0698925,'ro',color='#0000FF')
plt.plot(0.164773,0.0752688,'ro',color='#0000FF')
plt.plot(0.136364,0.0860215,'ro',color='#0000FF')
plt.plot(0.107955,0.0483871,'ro',color='#0000FF')
plt.plot(0.181818,0.0483871,'ro',color='#0000FF')
plt.plot(0.238636,0.0537634,'ro',color='#0000FF')
plt.plot(0.238636,0.0215054,'ro',color='#0000FF')
plt.plot(0.159091,0,'ro',color='#0000FF')
plt.plot(0.255682,0.016129,'ro',color='#0000FF')
plt.plot(0.295455,0.0591398,'ro',color='#0000FF')
plt.plot(0.289773,0.102151,'ro',color='#0000FF')
plt.plot(0.210227,0.0967742,'ro',color='#0000FF')
plt.plot(0.142045,0.0376344,'ro',color='#0000FF')
plt.plot(0.119318,0.0107527,'ro',color='#0000FF')
plt.plot(0.198864,0,'ro',color='#0000FF')
plt.plot(0.227273,0.00537634,'ro',color='#0000FF')
plt.show()