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)