yeastlist = []
# Set seeds for random and sample the Yeast genes:
for j in range(1,101):
for i in range(1,21):
#y = YeastSample(i,j)
#y.makeSampledNexusFile()
# Add each yeast tree (gene and seed number) to the list of yeasts:
yeastlist.append("yeast_" + str(i) + "_genes_" + str(j) + "_seed")
for yeast in yeastlist:
tree = yeast
treedir = "c:/seqgen/" + yeast
if not os.path.exists(treedir):
os.chdir("c:/seqgen")
os.mkdir(treedir)
shutil.copy("c:/seqgen/" + yeast + ".nex", treedir + "/" + yeast + ".nex")
runRAxML(tree, treedir)
#makeRAxMLtreeout(tree, treedir)
tempBayes = MrBayesObj(tree)
tempBayes.runAllYeast()
tempPhyML = PhyMLObj(tree)
tempPhyML.runAll()
#treelist = ["leaf01sameedges","leaf02sameedges","leaf04sameedges","leaf06sameedges","leaf08sameedges","leaf10sameedges"]
for t in treelist:
for i in range (0,100):
tree = t + str(i)
treedir = "c:/seqgen/" + tree
runRAxML(tree, treedir)
makeRAxMLtreeout(tree, treedir)
copyjars(treedir + "/raxml/")
findSturmMean(tree, treedir + "/raxml/","raxml")
tempBayes = MrBayesObj(tree)
tempBayes.runAll()
tempPhyML = PhyMLObj(tree)
tempPhyML.runAll()
# # Find geodesic distances:
# model = "raxml"
# raxdir = "\\raxml\\"
# for i in range(0,100):
# tree = t + str(i)
# treedir = "c:/seqgen/" + tree
# print("Target path is: " + treedir + raxdir)
# copyGTP(treedir + raxdir)
# # Base + best + all bootstrap trees
# geoDistanceMatrix(tree, tree + "_" + model + "_" + "treeout.txt" , treedir + raxdir, model)
