diff options
Diffstat (limited to 'biology/groopm/files/patch-2to3')
| -rw-r--r-- | biology/groopm/files/patch-2to3 | 3414 |
1 files changed, 3414 insertions, 0 deletions
diff --git a/biology/groopm/files/patch-2to3 b/biology/groopm/files/patch-2to3 new file mode 100644 index 000000000000..365000a5d096 --- /dev/null +++ b/biology/groopm/files/patch-2to3 @@ -0,0 +1,3414 @@ +--- groopm/PCA.py.orig 2014-11-26 01:01:33 UTC ++++ groopm/PCA.py +@@ -79,7 +79,7 @@ class PCA: + try: + self.sumvariance /= self.sumvariance[-1] + except: +- print len(A), len(self.sumvariance), len(self.eigen) ++ print(len(A), len(self.sumvariance), len(self.eigen)) + raise + + self.npc = np.searchsorted( self.sumvariance, fraction ) + 1 +@@ -127,13 +127,13 @@ class Center: + def __init__( self, A, axis=0, scale=True, verbose=1 ): + self.mean = A.mean(axis=axis) + if verbose: +- print "Center -= A.mean:", self.mean ++ print("Center -= A.mean:", self.mean) + A -= self.mean + if scale: + std = A.std(axis=axis) + self.std = np.where( std, std, 1. ) + if verbose: +- print "Center /= A.std:", self.std ++ print("Center /= A.std:", self.std) + A /= self.std + else: + self.std = np.ones( A.shape[-1] ) +--- groopm/bin.py.orig 2015-03-06 07:01:36 UTC ++++ groopm/bin.py +@@ -59,8 +59,8 @@ from numpy import (around as np_around, + median as np_median, + std as np_std) + +-from ellipsoid import EllipsoidTool +-from groopmExceptions import ModeNotAppropriateException ++from .ellipsoid import EllipsoidTool ++from .groopmExceptions import ModeNotAppropriateException + + np.seterr(all='raise') + +@@ -155,7 +155,7 @@ class Bin: + """Combine the contigs of another bin with this one""" + # consume all the other bins rowIndices + if(verbose): +- print " BIN:",deadBin.id,"will be consumed by BIN:",self.id ++ print(" BIN:",deadBin.id,"will be consumed by BIN:",self.id) + self.rowIndices = np.concatenate([self.rowIndices, deadBin.rowIndices]) + self.binSize = self.rowIndices.shape[0] + +@@ -326,7 +326,7 @@ class Bin: + try: + return ET.getMinVolEllipse(bin_points, retA=retA) + except: +- print bin_points ++ print(bin_points) + raise + else: # minimum bounding ellipse of a point is 0 + if retA: +@@ -474,13 +474,13 @@ class Bin: + fig.set_size_inches(10,4) + plt.savefig(fileName,dpi=300) + except: +- print "Error saving image:", fileName, sys.exc_info()[0] ++ print("Error saving image:", fileName, sys.exc_info()[0]) + raise + else: + try: + plt.show() + except: +- print "Error showing image:", sys.exc_info()[0] ++ print("Error showing image:", sys.exc_info()[0]) + raise + del fig + +@@ -504,13 +504,13 @@ class Bin: + fig.set_size_inches(6,6) + plt.savefig(fileName+".png",dpi=300) + except: +- print "Error saving image:", fileName, sys.exc_info()[0] ++ print("Error saving image:", fileName, sys.exc_info()[0]) + raise + elif(show): + try: + plt.show() + except: +- print "Error showing image:", sys.exc_info()[0] ++ print("Error showing image:", sys.exc_info()[0]) + raise + plt.close(fig) + del fig +@@ -636,8 +636,8 @@ class Bin: + + If you pass through an EllipsoidTool then it will plot the minimum bounding ellipse as well! + """ +- disp_vals = np.array(zip([kPCA1[i] for i in self.rowIndices], +- [kPCA2[i] for i in self.rowIndices])) ++ disp_vals = np.array(list(zip([kPCA1[i] for i in self.rowIndices], ++ [kPCA2[i] for i in self.rowIndices]))) + disp_lens = np.array([np.sqrt(contigLengths[i]) for i in self.rowIndices]) + + # reshape +@@ -695,7 +695,7 @@ class Bin: + data = [str(self.id), str(isLikelyChimeric[self.id]), str(self.totalBP), str(self.binSize), gcm_str, gcs_str] + cov_mean = np.mean(covProfiles[self.rowIndices], axis=0) + cov_std = np.std(covProfiles[self.rowIndices], axis=0) +- for i in xrange(0, len(cov_mean)): ++ for i in range(0, len(cov_mean)): + data.append('%.4f' % cov_mean[i]) + data.append('%.4f' % cov_std[i]) + stream.write(separator.join(data)+"\n") +--- groopm/binManager.py.orig 2015-03-06 07:02:49 UTC ++++ groopm/binManager.py +@@ -85,11 +85,11 @@ from scipy.stats import f_oneway, distributions + from scipy.cluster.vq import kmeans,vq + + # GroopM imports +-from profileManager import ProfileManager +-from bin import Bin, mungeCbar +-import groopmExceptions as ge +-from groopmUtils import makeSurePathExists +-from ellipsoid import EllipsoidTool ++from .profileManager import ProfileManager ++from .bin import Bin, mungeCbar ++from . import groopmExceptions as ge ++from .groopmUtils import makeSurePathExists ++from .ellipsoid import EllipsoidTool + + np_seterr(all='raise') + +@@ -182,15 +182,15 @@ class BinManager: + if self.PM.numStoits == 3: + self.PM.transformedCP = self.PM.covProfiles + else: +- print "Number of stoits != 3. You need to transform" ++ print("Number of stoits != 3. You need to transform") + self.PM.transformCP(timer, silent=silent) + if not silent: +- print " Making bin objects" ++ print(" Making bin objects") + self.makeBins(self.getBinMembers()) + if not silent: +- print " Loaded %d bins from database" % len(self.bins) ++ print(" Loaded %d bins from database" % len(self.bins)) + if not silent: +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + + def getBinMembers(self): +@@ -210,7 +210,7 @@ class BinManager: + + # we need to get the largest BinId in use + if len(bin_members) > 0: +- self.nextFreeBinId = np_max(bin_members.keys()) ++ self.nextFreeBinId = np_max(list(bin_members.keys())) + return bin_members + + def makeBins(self, binMembers, zeroIsBin=False): +@@ -224,8 +224,8 @@ class BinManager: + self.bins[bid] = Bin(np_array(binMembers[bid]), bid, self.PM.scaleFactor-1) + self.bins[bid].makeBinDist(self.PM.transformedCP, self.PM.averageCoverages, self.PM.kmerNormPC1, self.PM.kmerPCs, self.PM.contigGCs, self.PM.contigLengths) + if len(invalid_bids) != 0: +- print "MT bins!" +- print invalid_bids ++ print("MT bins!") ++ print(invalid_bids) + exit(-1) + + def saveBins(self, binAssignments={}, nuke=False): +@@ -384,7 +384,7 @@ class BinManager: + all_links[key] = links[link] + + # sort and return +- return sorted(all_links.iteritems(), key=itemgetter(1), reverse=True) ++ return sorted(iter(all_links.items()), key=itemgetter(1), reverse=True) + + def getWithinLinkProfiles(self): + """Determine the average number of links between contigs for all bins""" +@@ -468,7 +468,7 @@ class BinManager: + (bin_assignment_update, bids) = self.getSplitties(bid, n, mode) + + if(auto and saveBins): +- print 'here!!!!' ++ print('here!!!!') + # charge on through + self.deleteBins([bids[0]], force=True) # delete the combined bin + # save new bins +@@ -536,12 +536,12 @@ class BinManager: + parts = 0 + while(not_got_parts): + try: +- parts = int(raw_input("Enter new number of parts:")) ++ parts = int(input("Enter new number of parts:")) + except ValueError: +- print "You need to enter an integer value!" ++ print("You need to enter an integer value!") + parts = 0 + if(1 == parts): +- print "Don't be a silly sausage!" ++ print("Don't be a silly sausage!") + elif(0 != parts): + not_got_parts = False + self.split(bid, +@@ -664,7 +664,7 @@ class BinManager: + F_cutoff = distributions.f.ppf(confidence, 2, len(dist1)+len(dist2)-2) + F_value = f_oneway(dist1,dist2)[0] + if tag != "": +- print "%s [V: %f, C: %f]" % (tag, F_value, F_cutoff) ++ print("%s [V: %f, C: %f]" % (tag, F_value, F_cutoff)) + return F_value < F_cutoff + + def merge(self, bids, auto=False, manual=False, newBid=False, saveBins=False, verbose=False, printInstructions=True, use_elipses=True): +@@ -715,11 +715,11 @@ class BinManager: + self.deleteBins([tmp_bin.id], force=True) + user_option = self.promptOnMerge(bids=[parent_bin.id,dead_bin.id]) + if(user_option == "N"): +- print "Merge skipped" ++ print("Merge skipped") + ret_val = 1 + continue_merge=False + elif(user_option == "Q"): +- print "All mergers skipped" ++ print("All mergers skipped") + return 0 + else: + ret_val = 2 +@@ -799,7 +799,7 @@ class BinManager: + try: + del self.PM.binnedRowIndices[row_index] + except KeyError: +- print bid, row_index, "FUNG" ++ print(bid, row_index, "FUNG") + self.PM.binIds[row_index] = 0 + + bin_assignment_update[row_index] = 0 +@@ -826,7 +826,7 @@ class BinManager: + # UI + + def printMergeInstructions(self): +- raw_input( "****************************************************************\n" ++ input( "****************************************************************\n" + " MERGING INSTRUCTIONS - PLEASE READ CAREFULLY\n" + "****************************************************************\n" + " The computer cannot always be trusted to perform bin mergers\n" +@@ -836,10 +836,10 @@ class BinManager: + " to continue with the merging operation.\n" + " The image on the far right shows the bins after merging\n" + " Press any key to produce plots...") +- print "****************************************************************" ++ print("****************************************************************") + + def printSplitInstructions(self): +- raw_input( "****************************************************************\n" ++ input( "****************************************************************\n" + " SPLITTING INSTRUCTIONS - PLEASE READ CAREFULLY\n" + "****************************************************************\n" + " The computer cannot always be trusted to perform bin splits\n" +@@ -848,7 +848,7 @@ class BinManager: + " be split. Look carefully at each plot and then close the plot\n" + " to continue with the splitting operation.\n\n" + " Press any key to produce plots...") +- print "****************************************************************" ++ print("****************************************************************") + + def getPlotterMergeIds(self): + """Prompt the user for ids to be merged and check that it's all good""" +@@ -856,7 +856,7 @@ class BinManager: + ret_bids = [] + while(input_not_ok): + ret_bids = [] +- option = raw_input("Please enter 'space' separated bin Ids or 'q' to quit: ") ++ option = input("Please enter 'space' separated bin Ids or 'q' to quit: ") + if(option.upper() == 'Q'): + return [] + bids = option.split(" ") +@@ -866,13 +866,13 @@ class BinManager: + i_bid = int(bid) + # check that it's in the bins list + if(i_bid not in self.bins): +- print "**Error: bin",bid,"not found" ++ print("**Error: bin",bid,"not found") + input_not_ok = True + break + input_not_ok = False + ret_bids.append(i_bid) + except ValueError: +- print "**Error: invalid value:", bid ++ print("**Error: invalid value:", bid) + input_not_ok = True + break + return ret_bids +@@ -889,19 +889,19 @@ class BinManager: + bin_str += " and "+str(bids[i]) + while(input_not_ok): + if(minimal): +- option = raw_input(" Merge? ("+vrs+") : ") ++ option = input(" Merge? ("+vrs+") : ") + else: +- option = raw_input(" ****WARNING**** About to merge bins"+bin_str+"\n" \ ++ option = input(" ****WARNING**** About to merge bins"+bin_str+"\n" \ + " If you continue you *WILL* overwrite existing bins!\n" \ + " You have been shown a 3d plot of the bins to be merged.\n" \ + " Continue only if you're sure this is what you want to do!\n" \ + " y = yes, n = no, q = no and quit merging\n" \ + " Merge? ("+vrs+") : ") + if(option.upper() in valid_responses): +- print "****************************************************************" ++ print("****************************************************************") + return option.upper() + else: +- print "Error, unrecognised choice '"+option.upper()+"'" ++ print("Error, unrecognised choice '"+option.upper()+"'") + minimal = True + + def promptOnSplit(self, parts, mode, minimal=False): +@@ -911,9 +911,9 @@ class BinManager: + vrs = ",".join([str.lower(str(x)) for x in valid_responses]) + while(input_not_ok): + if(minimal): +- option = raw_input(" Split? ("+vrs+") : ") ++ option = input(" Split? ("+vrs+") : ") + else: +- option = raw_input(" ****WARNING**** About to split bin into "+str(parts)+" parts\n" \ ++ option = input(" ****WARNING**** About to split bin into "+str(parts)+" parts\n" \ + " If you continue you *WILL* overwrite existing bins!\n" \ + " You have been shown a 3d plot of the bin after splitting.\n" \ + " Continue only if you're sure this is what you want to do!\n" \ +@@ -923,13 +923,13 @@ class BinManager: + " Split? ("+vrs+") : ") + if(option.upper() in valid_responses): + if(option.upper() == 'K' and mode.upper() == 'KMER' or option.upper() == 'C' and mode.upper() == 'COV' or option.upper() == 'L' and mode.upper() == 'LEN'): +- print "Error, you are already using that profile to split!" ++ print("Error, you are already using that profile to split!") + minimal=True + else: +- print "****************************************************************" ++ print("****************************************************************") + return option.upper() + else: +- print "Error, unrecognised choice '"+option.upper()+"'" ++ print("Error, unrecognised choice '"+option.upper()+"'") + minimal = True + + def promptOnDelete(self, bids, minimal=False): +@@ -940,19 +940,19 @@ class BinManager: + bids_str = ",".join([str.lower(str(x)) for x in bids]) + while(input_not_ok): + if(minimal): +- option = raw_input(" Delete? ("+vrs+") : ") ++ option = input(" Delete? ("+vrs+") : ") + else: +- option = raw_input(" ****WARNING**** About to delete bin(s):\n" \ ++ option = input(" ****WARNING**** About to delete bin(s):\n" \ + " "+bids_str+"\n" \ + " If you continue you *WILL* overwrite existing bins!\n" \ + " Continue only if you're sure this is what you want to do!\n" \ + " y = yes, n = no\n"\ + " Delete? ("+vrs+") : ") + if(option.upper() in valid_responses): +- print "****************************************************************" ++ print("****************************************************************") + return option.upper() + else: +- print "Error, unrecognised choice '"+option.upper()+"'" ++ print("Error, unrecognised choice '"+option.upper()+"'") + minimal = True + + #------------------------------------------------------------------------------ +@@ -1039,10 +1039,10 @@ class BinManager: + + # find the mean and stdev + if(not makeKillList): +- return (np_mean(np_array(Ms.values())), np_std(np_array(Ms.values())), np_median(np_array(Ss.values())), np_std(np_array(Ss.values()))) ++ return (np_mean(np_array(list(Ms.values()))), np_std(np_array(list(Ms.values()))), np_median(np_array(list(Ss.values()))), np_std(np_array(list(Ss.values())))) + + else: +- cutoff = np_mean(np_array(Ms.values())) + tolerance * np_std(np_array(Ms.values())) ++ cutoff = np_mean(np_array(list(Ms.values()))) + tolerance * np_std(np_array(list(Ms.values()))) + kill_list = [] + for bid in Ms: + if(Ms[bid] > cutoff): +@@ -1054,7 +1054,7 @@ class BinManager: + + return a list of potentially confounding kmer indices + """ +- print " Measuring kmer type variances" ++ print(" Measuring kmer type variances") + means = np_array([]) + stdevs = np_array([]) + bids = np_array([]) +@@ -1094,12 +1094,12 @@ class BinManager: + return_indices.append(sort_within_indices[i]) + + if(plot): +- print "BETWEEN" ++ print("BETWEEN") + for i in range(0,number_to_trim): +- print names[sort_between_indices[i]] +- print "WITHIN" ++ print(names[sort_between_indices[i]]) ++ print("WITHIN") + for i in range(0,number_to_trim): +- print names[sort_within_indices[i]] ++ print(names[sort_within_indices[i]]) + + plt.figure(1) + plt.subplot(211) +@@ -1126,7 +1126,7 @@ class BinManager: + stdout = open(fileName, 'w') + self.printInner(outFormat, stdout) + except: +- print "Error diverting stout to file:", fileName, exc_info()[0] ++ print("Error diverting stout to file:", fileName, exc_info()[0]) + raise + else: + self.printInner(outFormat) +@@ -1139,14 +1139,14 @@ class BinManager: + stream.write(separator.join(["#\"bid\"","\"cid\"","\"length\"","\"GC\""])+"\n") + elif(outFormat == 'bins'): + header = ["\"bin id\"","\"Likely chimeric\"","\"length (bp)\"","\"# seqs\"","\"GC mean\"","\"GC std\""] +- for i in xrange(0, len(self.PM.covProfiles[0])): ++ for i in range(0, len(self.PM.covProfiles[0])): + header.append("\"Coverage " + str(i+1) + " mean\"") + header.append("\"Coverage " + str(i+1) + " std\"") + stream.write(separator.join(header) + "\n") + elif(outFormat == 'full'): + pass + else: +- print "Error: Unrecognised format:", outFormat ++ print("Error: Unrecognised format:", outFormat) + return + + for bid in self.getBids(): +@@ -1224,13 +1224,13 @@ class BinManager: + try: + plt.savefig(fileName,dpi=300) + except: +- print "Error saving image:", fileName, exc_info()[0] ++ print("Error saving image:", fileName, exc_info()[0]) + raise + else: + try: + plt.show() + except: +- print "Error showing image:", exc_info()[0] ++ print("Error showing image:", exc_info()[0]) + raise + + plt.close(fig) +@@ -1344,7 +1344,7 @@ class BinManager: + try: + plt.show() + except: +- print "Error showing image:", exc_info()[0] ++ print("Error showing image:", exc_info()[0]) + raise + + plt.close(fig) +@@ -1369,10 +1369,10 @@ class BinManager: + self.bins[bid].makeBinDist(self.PM.transformedCP, self.PM.averageCoverages, self.PM.kmerNormPC1, self.PM.kmerPCs, self.PM.contigGCs, self.PM.contigLengths) + + if(sideBySide): +- print "Plotting side by side" +- self.plotSideBySide(self.bins.keys(), tag=FNPrefix, ignoreContigLengths=ignoreContigLengths) ++ print("Plotting side by side") ++ self.plotSideBySide(list(self.bins.keys()), tag=FNPrefix, ignoreContigLengths=ignoreContigLengths) + else: +- print "Plotting bins" ++ print("Plotting bins") + for bid in self.getBids(): + if folder != '': + self.bins[bid].plotBin(self.PM.transformedCP, self.PM.contigGCs, self.PM.kmerNormPC1, +@@ -1387,7 +1387,7 @@ class BinManager: + def plotBinCoverage(self, plotEllipses=False, plotContigLengs=False, printID=False): + """Make plots of all the bins""" + +- print "Plotting first 3 stoits in untransformed coverage space" ++ print("Plotting first 3 stoits in untransformed coverage space") + + # plot contigs in coverage space + fig = plt.figure() +@@ -1452,7 +1452,7 @@ class BinManager: + plt.show() + plt.close(fig) + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + + del fig +@@ -1504,13 +1504,13 @@ class BinManager: + fig.set_size_inches(12,6) + plt.savefig(fileName,dpi=300) + except: +- print "Error saving image:", fileName, exc_info()[0] ++ print("Error saving image:", fileName, exc_info()[0]) + raise + elif(show): + try: + plt.show() + except: +- print "Error showing image:", exc_info()[0] ++ print("Error showing image:", exc_info()[0]) + raise + plt.close(fig) + del fig +@@ -1554,7 +1554,7 @@ class BinManager: + plt.show() + plt.close(fig) + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + del fig + +@@ -1563,7 +1563,7 @@ class BinManager: + (bin_centroid_points, _bin_centroid_colors, bin_centroid_gc, _bids) = self.findCoreCentres(processChimeric=showChimeric) + fig = plt.figure() + ax = fig.add_subplot(111, projection='3d') +- print bin_centroid_gc ++ print(bin_centroid_gc) + sc = ax.scatter(bin_centroid_points[:,0], bin_centroid_points[:,1], bin_centroid_points[:,2], edgecolors='k', c=bin_centroid_gc, cmap=self.PM.colorMapGC, vmin=0.0, vmax=1.0) + sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect + +@@ -1588,7 +1588,7 @@ class BinManager: + plt.show() + plt.close(fig) + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + del fig + +--- groopm/cluster.py.orig 2015-03-06 04:42:51 UTC ++++ groopm/cluster.py +@@ -95,11 +95,11 @@ from scipy.spatial.distance import pdist, squareform, + from scipy.misc import imsave + + # GroopM imports +-from profileManager import ProfileManager +-from binManager import BinManager +-from refine import GrubbsTester, RefineEngine +-from PCA import PCA, Center +-from groopmExceptions import BinNotFoundException ++from .profileManager import ProfileManager ++from .binManager import BinManager ++from .refine import GrubbsTester, RefineEngine ++from .PCA import PCA, Center ++from .groopmExceptions import BinNotFoundException + + np_seterr(all='raise') + +@@ -160,22 +160,22 @@ class ClusterEngine: + vrs = ",".join([str.lower(str(x)) for x in valid_responses]) + while(input_not_ok): + if(minimal): +- option = raw_input(" Overwrite? ("+vrs+") : ") ++ option = input(" Overwrite? ("+vrs+") : ") + else: +- option = raw_input(" ****WARNING**** Database: '"+self.PM.dbFileName+"' has already been clustered.\n" \ ++ option = input(" ****WARNING**** Database: '"+self.PM.dbFileName+"' has already been clustered.\n" \ + " If you continue you *MAY* overwrite existing bins!\n" \ + " Overwrite? ("+vrs+") : ") + if(option.upper() in valid_responses): +- print "****************************************************************" ++ print("****************************************************************") + if(option.upper() == "N"): +- print "Operation cancelled" ++ print("Operation cancelled") + return False + else: + break + else: +- print "Error, unrecognised choice '"+option.upper()+"'" ++ print("Error, unrecognised choice '"+option.upper()+"'") + minimal = True +- print "Will Overwrite database",self.PM.dbFileName ++ print("Will Overwrite database",self.PM.dbFileName) + return True + + #------------------------------------------------------------------------------ +@@ -189,10 +189,10 @@ class ClusterEngine: + + # get some data + self.PM.loadData(self.timer, "length >= "+str(coreCut)) +- print " %s" % self.timer.getTimeStamp() ++ print(" %s" % self.timer.getTimeStamp()) + + # transform the data +- print " Loading transformed data" ++ print(" Loading transformed data") + self.PM.transformCP(self.timer) + # plot the transformed space (if we've been asked to...) + #if(self.debugPlots >= 3): +@@ -201,15 +201,15 @@ class ClusterEngine: + # now we can make this guy + self.TSpan = np_mean([np_norm(self.PM.corners[i] - self.PM.TCentre) for i in range(self.PM.numStoits)]) + +- print " %s" % self.timer.getTimeStamp() ++ print(" %s" % self.timer.getTimeStamp()) + + # cluster and bin! +- print "Create cores" ++ print("Create cores") + self.initialiseCores(kmerThreshold, coverageThreshold) +- print " %s" % self.timer.getTimeStamp() ++ print(" %s" % self.timer.getTimeStamp()) + + # condense cores +- print "Refine cores [begin: %d]" % len(self.BM.bins) ++ print("Refine cores [begin: %d]" % len(self.BM.bins)) + if self.finalPlot: + prfx = "CORE" + else: +@@ -217,9 +217,9 @@ class ClusterEngine: + self.RE.refineBins(self.timer, auto=True, saveBins=False, plotFinal=prfx, gf=gf) + + # Now save all the stuff to disk! +- print "Saving bins" ++ print("Saving bins") + self.BM.saveBins(nuke=True) +- print " %s" % self.timer.getTimeStamp() ++ print(" %s" % self.timer.getTimeStamp()) + + def initialiseCores(self, kmerThreshold, coverageThreshold): + """Process contigs and form CORE bins""" +@@ -230,8 +230,8 @@ class ClusterEngine: + # We can make a heat map and look for hot spots + self.populateImageMaps() + sub_counter = 0 +- print " .... .... .... .... .... .... .... .... .... ...." +- print "%4d" % sub_counter, ++ print(" .... .... .... .... .... .... .... .... .... ....") ++ print("%4d" % sub_counter, end=' ') + new_line_counter = 0 + num_bins = 0 + +@@ -303,13 +303,13 @@ class ClusterEngine: + self.updatePostBin(bin) + + new_line_counter += 1 +- print "% 4d" % bin.binSize, ++ print("% 4d" % bin.binSize, end=' ') + + # make the printing prettier + if(new_line_counter > 9): + new_line_counter = 0 + sub_counter += 10 +- print "\n%4d" % sub_counter, ++ print("\n%4d" % sub_counter, end=' ') + + if(self.debugPlots >= 1): + #***slow plot! +@@ -317,7 +317,7 @@ class ClusterEngine: + + except BinNotFoundException: pass + +- print "\n .... .... .... .... .... .... .... .... .... ...." ++ print("\n .... .... .... .... .... .... .... .... .... ....") + + def findNewClusterCenters(self, kmerThreshold, coverageThreshold): + """Find a putative cluster""" +@@ -498,32 +498,32 @@ class ClusterEngine: + k_dist_matrix = squareform(pdist(k_dat, 'cityblock')) + k_radius = np_median(np_sort(k_dist_matrix)[:,eps_neighbours]) + except MemoryError: +- print "\n" +- print '*******************************************************************************' +- print '********************************* ERROR *********************************' +- print '*******************************************************************************' +- print 'GroopM is attempting to do some maths on a putative bin which contains:' +- print +- print '\t\t%d contigs' % (len(rowIndices)) +- print +- print 'This has caused your machine to run out of memory.' +- print 'The most likely cause is that your samples are very different from each other.' +- print 'You can confirm this by running:' +- print +- print '\t\tgroopm explore -m allcontigs %s' % self.PM.dbFileName +- print +- print 'If you notice only vertical "spears" of contigs at the corners of the plot then' +- print 'this means that your samples are very different and you are not getting a good' +- print 'mapping from all samples to all contigs. You may get more mileage by assembling' +- print 'and binning your samples separately.' +- print +- print 'If you notice "clouds" of contigs then congratulations! You have found a bug.' +- print 'Please let me know at "%s or via github.com/minillinim/GroopM' % __email__ +- print +- print 'GroopM is aborting... sorry' +- print +- print '*******************************************************************************' +- print "\n" ++ print("\n") ++ print('*******************************************************************************') ++ print('********************************* ERROR *********************************') ++ print('*******************************************************************************') ++ print('GroopM is attempting to do some maths on a putative bin which contains:') ++ print() ++ print('\t\t%d contigs' % (len(rowIndices))) ++ print() ++ print('This has caused your machine to run out of memory.') ++ print('The most likely cause is that your samples are very different from each other.') ++ print('You can confirm this by running:') ++ print() ++ print('\t\tgroopm explore -m allcontigs %s' % self.PM.dbFileName) ++ print() ++ print('If you notice only vertical "spears" of contigs at the corners of the plot then') ++ print('this means that your samples are very different and you are not getting a good') ++ print('mapping from all samples to all contigs. You may get more mileage by assembling') ++ print('and binning your samples separately.') ++ print() ++ print('If you notice "clouds" of contigs then congratulations! You have found a bug.') ++ print('Please let me know at "%s or via github.com/minillinim/GroopM' % __email__) ++ print() ++ print('GroopM is aborting... sorry') ++ print() ++ print('*******************************************************************************') ++ print("\n") + exit(-1) + + # find nearest neighbours to each point in whitened coverage space, +@@ -1341,7 +1341,7 @@ class HoughPartitioner: + diffs *= (len(diffs)-1) + + # make it 2D +- t_data = np_array(zip(diffs, np_arange(d_len))) ++ t_data = np_array(list(zip(diffs, np_arange(d_len)))) + ###MMM FIX + #im_shape = (int(np_max(t_data, axis=0)[0]+1), d_len) + im_shape = (d_len, d_len) +@@ -1532,7 +1532,7 @@ class HoughPartitioner: + if imgTag is not None: + # make a pretty picture + fff = np_ones(imShape) * 255 +- for p in found_line.keys(): ++ for p in list(found_line.keys()): + fff[p[0],p[1]] = 220 + for p in tData: + fff[p[0],p[1]] = 0 +@@ -1573,7 +1573,7 @@ class HoughPartitioner: + if real_index not in assigned: + tmp[real_index] = None + assigned[real_index] = None +- centre = np_array(tmp.keys()) ++ centre = np_array(list(tmp.keys())) + if len(centre) > 0: + return np_array([centre]) + # nuffin +@@ -1593,7 +1593,7 @@ class HoughPartitioner: + if real_index not in assigned: + tmp[real_index] = None + assigned[real_index] = None +- centre = np_array(tmp.keys()) ++ centre = np_array(list(tmp.keys())) + + rets = [] + +@@ -1609,8 +1609,8 @@ class HoughPartitioner: + tmp[real_index] = None + assigned[real_index] = None + +- if len(tmp.keys()) > 0: +- rets.append(np_array(tmp.keys())) ++ if len(list(tmp.keys())) > 0: ++ rets.append(np_array(list(tmp.keys()))) + + else: + # otherwise we keep working with ranges +@@ -1643,8 +1643,8 @@ class HoughPartitioner: + tmp[real_index] = None + assigned[real_index] = None + +- if len(tmp.keys()) > 0: +- rets.append(np_array(tmp.keys())) ++ if len(list(tmp.keys())) > 0: ++ rets.append(np_array(list(tmp.keys()))) + else: + right_p = self.recursiveSelect(tData, + imShape, +@@ -1723,40 +1723,40 @@ class HoughPartitioner: + iry = half_rows + int(r/dr) + accumulator[iry, theta_index] -= 1 + """ +- cos_sin_array = np_array(zip([np_sin(dth * theta_index) for theta_index in range(cols)], +- [np_cos(dth * theta_index) for theta_index in range(cols)])) ++ cos_sin_array = np_array(list(zip([np_sin(dth * theta_index) for theta_index in range(cols)], ++ [np_cos(dth * theta_index) for theta_index in range(cols)]))) + Rs = np_array(np_sum(np_reshape([p * cos_sin_array for p in data], (d_len*cols,2)), + axis=1)/dr).astype('int') + half_rows +- Cs = np_array(range(cols)*d_len) ++ Cs = np_array(list(range(cols))*d_len) + + try: + flat_indices = Rs * cols + Cs + except ValueError: +- print "\n" +- print '*******************************************************************************' +- print '********************************* ERROR *********************************' +- print '*******************************************************************************' +- print 'GroopM is attempting to do some maths on a putative bin which contains' +- print 'too many contigs.' +- print +- print 'This has resulted in a buffer overflow in the numpy library... oops.' +- print 'The most likely cause is that your samples are very different from each other.' +- print 'You can confirm this by running:' +- print +- print '\t\tgroopm explore -c 0 -m allcontigs <dbfilename>' +- print +- print 'If you notice only vertical "spears" of contigs at the corners of the plot then' +- print 'this means that your samples are very different and you are not getting a good' +- print 'mapping from all samples to all contigs. You may get more mileage by assembling' +- print 'and binning your samples separately.' +- print +- print 'If you notice "clouds" of contigs then congratulations! You have found a bug.' +- print 'Please let me know at "%s or via github.com/minillinim/GroopM' % __email__ +- print +- print 'GroopM is aborting... sorry' +- print +- print '*******************************************************************************' +- print "\n" ++ print("\n") ++ print('*******************************************************************************') ++ print('********************************* ERROR *********************************') ++ print('*******************************************************************************') ++ print('GroopM is attempting to do some maths on a putative bin which contains') ++ print('too many contigs.') ++ print() ++ print('This has resulted in a buffer overflow in the numpy library... oops.') ++ print('The most likely cause is that your samples are very different from each other.') ++ print('You can confirm this by running:') ++ print() ++ print('\t\tgroopm explore -c 0 -m allcontigs <dbfilename>') ++ print() ++ print('If you notice only vertical "spears" of contigs at the corners of the plot then') ++ print('this means that your samples are very different and you are not getting a good') ++ print('mapping from all samples to all contigs. You may get more mileage by assembling') ++ print('and binning your samples separately.') ++ print() ++ print('If you notice "clouds" of contigs then congratulations! You have found a bug.') ++ print('Please let me know at "%s or via github.com/minillinim/GroopM' % __email__) ++ print() ++ print('GroopM is aborting... sorry') ++ print() ++ print('*******************************************************************************') ++ print("\n") + exit(-1) + + # update the accumulator with integer decrements +--- groopm/groopm.py.orig 2014-11-26 01:01:33 UTC ++++ groopm/groopm.py +@@ -52,14 +52,14 @@ __status__ = "Released" + import matplotlib as mpl + + # GroopM imports +-import mstore +-import cluster +-import refine +-import binManager +-import groopmUtils +-import groopmTimekeeper as gtime +-from groopmExceptions import ExtractModeNotAppropriateException +-from mstore import GMDataManager ++from . import mstore ++from . import cluster ++from . import refine ++from . import binManager ++from . import groopmUtils ++from . import groopmTimekeeper as gtime ++from .groopmExceptions import ExtractModeNotAppropriateException ++from .mstore import GMDataManager + + ############################################################################### + ############################################################################### +@@ -100,12 +100,12 @@ class GroopMOptionsParser(): + timer = gtime.TimeKeeper() + if(options.subparser_name == 'parse'): + # parse raw input +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in data parsing mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in data parsing mode..." % self.GMVersion) ++ print("*******************************************************************************") + # check this here: + if len(options.bamfiles) < 3: +- print "Sorry, You must supply at least 3 bamFiles to use GroopM. (You supplied %d)\n Exiting..." % len(options.bamfiles) ++ print("Sorry, You must supply at least 3 bamFiles to use GroopM. (You supplied %d)\n Exiting..." % len(options.bamfiles)) + return + GMdata = mstore.GMDataManager() + success = GMdata.createDB(options.bamfiles, +@@ -116,13 +116,13 @@ class GroopMOptionsParser(): + force=options.force, + threads=options.threads) + if not success: +- print options.dbname,"not updated" ++ print(options.dbname,"not updated") + + elif(options.subparser_name == 'core'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in core creation mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in core creation mode..." % self.GMVersion) ++ print("*******************************************************************************") + CE = cluster.ClusterEngine(options.dbname, + timer, + force=options.force, +@@ -139,9 +139,9 @@ class GroopMOptionsParser(): + + elif(options.subparser_name == 'refine'): + # refine bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in core refining mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in core refining mode..." % self.GMVersion) ++ print("*******************************************************************************") + bids = [] + #if options.bids is not None: + # bids = options.bids +@@ -158,7 +158,7 @@ class GroopMOptionsParser(): + pfx="REFINED" + else: + pfx="" +- print "Refine bins" ++ print("Refine bins") + + RE.refineBins(timer, + auto=auto, +@@ -167,9 +167,9 @@ class GroopMOptionsParser(): + + elif(options.subparser_name == 'recruit'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in bin expansion mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in bin expansion mode..." % self.GMVersion) ++ print("*******************************************************************************") + RE = refine.RefineEngine(timer, + dbFileName=options.dbname, + getUnbinned=True, +@@ -183,9 +183,9 @@ class GroopMOptionsParser(): + + elif(options.subparser_name == 'extract'): + # Extract data +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in '%s' extraction mode..." % (self.GMVersion, options.mode) +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in '%s' extraction mode..." % (self.GMVersion, options.mode)) ++ print("*******************************************************************************") + bids = [] + if options.bids is not None: + bids = options.bids +@@ -220,35 +220,35 @@ class GroopMOptionsParser(): + raise ExtractModeNotAppropriateException("mode: "+ options.mode + " is unknown") + elif(options.subparser_name == 'merge'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in bin merging mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in bin merging mode..." % self.GMVersion) ++ print("*******************************************************************************") + BM = binManager.BinManager(dbFileName=options.dbname) + BM.loadBins(timer, makeBins=True, silent=False) + BM.merge(options.bids, options.force, saveBins=True) + + elif(options.subparser_name == 'split'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in bin splitting mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in bin splitting mode..." % self.GMVersion) ++ print("*******************************************************************************") + BM = binManager.BinManager(dbFileName=options.dbname) + BM.loadBins(timer, makeBins=True, silent=False) + BM.split(options.bid, options.parts, mode=options.mode, saveBins=True, auto=options.force) + + elif(options.subparser_name == 'delete'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in bin deleting mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in bin deleting mode..." % self.GMVersion) ++ print("*******************************************************************************") + BM = binManager.BinManager(dbFileName=options.dbname) + BM.loadBins(timer, makeBins=True, silent=True)#, bids=options.bids) + BM.deleteBins(options.bids, force=options.force, saveBins=True, freeBinnedRowIndices=True) + + elif(options.subparser_name == 'plot'): +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in bin plotting mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in bin plotting mode..." % self.GMVersion) ++ print("*******************************************************************************") + BM = binManager.BinManager(dbFileName=options.dbname) + + if options.bids is None: +@@ -266,9 +266,9 @@ class GroopMOptionsParser(): + + elif(options.subparser_name == 'explore'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in bin '%s' explorer mode..." % (self.GMVersion, options.mode) +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in bin '%s' explorer mode..." % (self.GMVersion, options.mode)) ++ print("*******************************************************************************") + transform=True^options.no_transform + bids = [] + if options.bids is not None: +@@ -297,13 +297,13 @@ class GroopMOptionsParser(): + elif (options.mode == 'sidebyside'): + BE.plotSideBySide(timer, coreCut=options.cutoff) + else: +- print "**Error: unknown mode:",options.mode ++ print("**Error: unknown mode:",options.mode) + + elif(options.subparser_name == 'flyover'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Making a flyover..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Making a flyover..." % self.GMVersion) ++ print("*******************************************************************************") + bids = [] + if options.bids is not None: + bids = options.bids +@@ -323,9 +323,9 @@ class GroopMOptionsParser(): + + elif(options.subparser_name == 'highlight'): + # make bin cores +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in highlighter mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in highlighter mode..." % self.GMVersion) ++ print("*******************************************************************************") + bids = [] + if options.bids is not None: + bids = options.bids +@@ -355,9 +355,9 @@ class GroopMOptionsParser(): + BM.printBins(options.format, fileName=options.outfile) + + elif(options.subparser_name == 'dump'): +- print "*******************************************************************************" +- print " [[GroopM %s]] Running in data dumping mode..." % self.GMVersion +- print "*******************************************************************************" ++ print("*******************************************************************************") ++ print(" [[GroopM %s]] Running in data dumping mode..." % self.GMVersion) ++ print("*******************************************************************************") + + # prep fields. Do this first cause users are mot likely to + # mess this part up! +@@ -365,8 +365,8 @@ class GroopMOptionsParser(): + fields = options.fields.split(',') + for field in fields: + if field not in allowable_fields: +- print "ERROR: field '%s' not recognised. Allowable fields are:" % field +- print '\t',",".join(allowable_fields) ++ print("ERROR: field '%s' not recognised. Allowable fields are:" % field) ++ print('\t',",".join(allowable_fields)) + return + if options.separator == '\\t': + separator = '\t' +--- groopm/groopmUtils.py.orig 2014-11-26 01:01:33 UTC ++++ groopm/groopmUtils.py +@@ -62,8 +62,8 @@ np.seterr(all='raise') + from scipy.spatial.distance import cdist, squareform + + # GroopM imports +-import binManager +-import mstore ++from . import binManager ++from . import mstore + + # other local imports + from bamm.bamExtractor import BamExtractor as BMBE +@@ -126,16 +126,16 @@ class GMExtractor: + import gzip + GM_open = gzip.open + except: +- print "Error when guessing contig file mimetype" ++ print("Error when guessing contig file mimetype") + raise + with GM_open(file_name, "r") as f: + contigs = CP.getWantedSeqs(f, self.PM.contigNames, storage=contigs) + except: +- print "Could not parse contig file:",fasta[0],sys.exc_info()[0] ++ print("Could not parse contig file:",fasta[0],sys.exc_info()[0]) + raise + + # now print out the sequences +- print "Writing files" ++ print("Writing files") + for bid in self.BM.getBids(): + if self.BM.PM.isLikelyChimeric[bid]: + file_name = os.path.join(self.outDir, "%s_bin_%d.chimeric.fna" % (self.prefix, bid)) +@@ -148,9 +148,9 @@ class GMExtractor: + if(cid in contigs): + f.write(">%s\n%s\n" % (cid, contigs[cid])) + else: +- print "These are not the contigs you're looking for. ( %s )" % (cid) ++ print("These are not the contigs you're looking for. ( %s )" % (cid)) + except: +- print "Could not open file for writing:",file_name,sys.exc_info()[0] ++ print("Could not open file for writing:",file_name,sys.exc_info()[0]) + raise + + def extractReads(self, +@@ -177,7 +177,7 @@ class GMExtractor: + self.BM.loadBins(timer, makeBins=True,silent=False,bids=self.bids) + self.PM = self.BM.PM + +- print "Extracting reads" ++ print("Extracting reads") + + # work out a set of targets to pass to the parser + targets = [] +@@ -268,16 +268,16 @@ class BinExplorer: + transform = self.transform, + cutOff=coreCut) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting image" ++ print("Plotting image") + if self.bids == []: + self.bids = self.BM.getBids() + + if testing: + # ignore labelling files provided + self.binLabelsFile = "none" +- raw_input( "****************************************************************\n" ++ input( "****************************************************************\n" + " IMAGE MAKING INSTRUCTIONS - PLEASE READ CAREFULLY\n" + "****************************************************************\n" + " You are using GroopM in highlight mode. Congratulations!\n" +@@ -290,7 +290,7 @@ class BinExplorer: + " parameters to what you saw here, set bin labels, contig colours...\n\n" + " Good Luck!\n\n" + " Press return to continue...") +- print "****************************************************************" ++ print("****************************************************************") + + # bids as labels and randomise colours + self.LP = LabelParser(self.BM.getBids()) +@@ -457,9 +457,9 @@ class BinExplorer: + cutOff=coreCut, + getUnbinned=True,) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting flyover" ++ print("Plotting flyover") + + import itertools + all_bids = self.BM.getBids() +@@ -475,7 +475,7 @@ class BinExplorer: + elev_increment = total_elev_shift / total_frames + self.BM.setColorMap(self.cmString) + +- print "Need",total_frames,"frames:" ++ print("Need",total_frames,"frames:") + + """ + Handle taking out bins as "fade packets", assign indices to a list +@@ -510,17 +510,17 @@ class BinExplorer: + # make the fade schedule for the remaining bins + remaining_frames = float(total_frames - fade_schedules[0]) + num_fade_gs = float(len(fade_groups) - 1) +- fade_schedules += [len(i) for i in self.splitCeil(range(int(remaining_frames)), int(num_fade_gs))] ++ fade_schedules += [len(i) for i in self.splitCeil(list(range(int(remaining_frames))), int(num_fade_gs))] + + if False: +- print len(self.BM.getBids()), num_fade_gs +- print fade_groups +- print fade_schedules ++ print(len(self.BM.getBids()), num_fade_gs) ++ print(fade_groups) ++ print(fade_schedules) + + # plot all contigs first and then fade out + fig = plt.figure() + while len(fade_groups) >= 1: +- print "Rendering frame: %d of: %d" % (int(current_frame),int(total_frames)) ++ print("Rendering frame: %d of: %d" % (int(current_frame),int(total_frames))) + # get the next fade group and fade schedule + faders = fade_groups.pop(0) + fade_schedule = fade_schedules.pop(0) +@@ -555,16 +555,16 @@ class BinExplorer: + bids=self.bids, + transform=self.transform) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting bin profiles" ++ print("Plotting bin profiles") + self.BM.setColorMap(self.cmString) + self.BM.plotProfileDistributions() + + def plotContigs(self, timer, coreCut, all=False): + """plot contigs""" + if all: +- print "Plotting all contigs" ++ print("Plotting all contigs") + self.PM.plotAll(timer, coreCut, transform=self.transform, ignoreContigLengths=self.ignoreContigLengths) + else: + self.BM.loadBins(timer, +@@ -574,9 +574,9 @@ class BinExplorer: + transform=self.transform, + cutOff=coreCut) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting binned contigs" ++ print("Plotting binned contigs") + self.BM.setColorMap(self.cmString) + if self.bids == []: + self.bids = self.BM.getBids() +@@ -592,9 +592,9 @@ class BinExplorer: + cutOff=coreCut, + transform=self.transform) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting bin assignments" ++ print("Plotting bin assignments") + if self.bids == []: + self.bids = self.BM.getBids() + +@@ -696,9 +696,9 @@ class BinExplorer: + transform=self.transform, + cutOff=coreCut) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting bin points" ++ print("Plotting bin points") + self.BM.setColorMap(self.cmString) + self.BM.plotBinPoints() + +@@ -726,9 +726,9 @@ class BinExplorer: + self.BM.setColorMap(self.cmString) + + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting side by side graphs" ++ print("Plotting side by side graphs") + (bin_centroid_points, bin_centroid_colors, bin_centroid_gc, bin_ids) = self.BM.findCoreCentres() + self.plotCoresVsContigs(bin_centroid_points, bin_centroid_colors) + +@@ -743,15 +743,15 @@ class BinExplorer: + bids=self.bids, + transform=self.transform) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting bin IDs" ++ print("Plotting bin IDs") + self.BM.setColorMap(self.cmString) + self.BM.plotBinIds() + + def plotUnbinned(self, timer, coreCut): + """Plot all contigs over a certain length which are unbinned""" +- print "Plotting unbinned contigs" ++ print("Plotting unbinned contigs") + self.PM.plotUnbinned(timer, coreCut, transform=self.transform, ignoreContigLengths=self.ignoreContigLengths) + + def plotSideBySide(self, timer, coreCut): +@@ -763,7 +763,7 @@ class BinExplorer: + transform=self.transform, + cutOff=coreCut) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: + self.BM.setColorMap(self.cmString) + self.BM.plotBins(sideBySide=True, +@@ -779,9 +779,9 @@ class BinExplorer: + transform=self.transform, + cutOff=coreCut) + if len(self.BM.bins) == 0: +- print "Sorry, no bins to plot" ++ print("Sorry, no bins to plot") + else: +- print "Plotting all bins together" ++ print("Plotting all bins together") + self.BM.setColorMap(self.cmString) + if self.bids == []: + p_bids = self.BM.getBids() +@@ -832,7 +832,7 @@ class BinExplorer: + plt.show() + plt.close(fig) + except: +- print "Error showing image", sys.exc_info()[0] ++ print("Error showing image", sys.exc_info()[0]) + raise + del fig + else: +@@ -859,7 +859,7 @@ class BinExplorer: + plt.savefig(f_name1,dpi=dpi,format=format) + plt.close(fig) + except: +- print "Error saving image",f_name1, sys.exc_info()[0] ++ print("Error saving image",f_name1, sys.exc_info()[0]) + raise + del fig + +@@ -893,7 +893,7 @@ class BinExplorer: + plt.savefig(f_name2,dpi=dpi,format=format) + plt.close(fig) + except: +- print "Error saving image",f_name1, sys.exc_info()[0] ++ print("Error saving image",f_name1, sys.exc_info()[0]) + raise + del fig + +@@ -1137,9 +1137,9 @@ class LabelParser: + try: + self.contig2Cols[name_2_row_index[cid]] = self.rgb(fields[1]) + except KeyError: +- print "ERROR: contig name %s not recognised" % cid ++ print("ERROR: contig name %s not recognised" % cid) + except: +- print "ERROR: parsing labels file: %s" % labelFileName ++ print("ERROR: parsing labels file: %s" % labelFileName) + raise + + # now we parse the rest of the contig names and colour the null colour +@@ -1178,7 +1178,7 @@ class LabelParser: + except IndexError: pass + self.loaded[bid] = True + except: +- print "ERROR parsing labels file: %s" % labelFileName ++ print("ERROR parsing labels file: %s" % labelFileName) + raise + + def setDefaultBinLabels(self, bids): +@@ -1192,7 +1192,7 @@ class LabelParser: + S = 1.0 + V = 1.0 + if setLoaded: +- for bid in self.bin2Str.keys(): ++ for bid in list(self.bin2Str.keys()): + self.loaded[bid] = True + num_bins = len(self.bin2Str) + offset = 0.5 +@@ -1201,7 +1201,7 @@ class LabelParser: + cols = [htr(H, S, V) for H in Hs] + np.random.shuffle(cols) + i = 0 +- for bid in self.bin2Str.keys(): ++ for bid in list(self.bin2Str.keys()): + if self.loaded[bid]: + # assign the color we picked + self.bin2Cols[bid] = cols[i] +--- groopm/mstore.py.orig 2015-03-06 04:42:41 UTC ++++ groopm/mstore.py +@@ -58,7 +58,7 @@ import numpy as np + from scipy.spatial.distance import cdist, squareform + + # GroopM imports +-from PCA import PCA, Center ++from .PCA import PCA, Center + + # BamM imports + try: +@@ -66,7 +66,7 @@ try: + from bamm.cWrapper import * + from bamm.bamFile import BM_coverageType as BMCT + except ImportError: +- print """ERROR: There was an error importing BamM. This probably means that ++ print("""ERROR: There was an error importing BamM. This probably means that + BamM is not installed properly or not in your PYTHONPATH. Installation + instructions for BamM are located at: + +@@ -79,7 +79,7 @@ you still encounter this error. Please lodge a bug rep + + Exiting... + -------------------------------------------------------------------------------- +-""" ++""") + import sys + sys.exit(-1) + +@@ -217,12 +217,12 @@ class GMDataManager: + if(not force): + user_option = self.promptOnOverwrite(dbFileName) + if(user_option != "Y"): +- print "Operation cancelled" ++ print("Operation cancelled") + return False + else: +- print "Overwriting database",dbFileName ++ print("Overwriting database",dbFileName) + except IOError as e: +- print "Creating new database", dbFileName ++ print("Creating new database", dbFileName) + + # create the db + try: +@@ -251,19 +251,19 @@ class GMDataManager: + import gzip + GM_open = gzip.open + except: +- print "Error when guessing contig file mimetype" ++ print("Error when guessing contig file mimetype") + raise + try: + with GM_open(contigsFile, "r") as f: + try: + (con_names, con_gcs, con_lengths, con_ksigs) = conParser.parse(f, cutoff, kse) + num_cons = len(con_names) +- cid_2_indices = dict(zip(con_names, range(num_cons))) ++ cid_2_indices = dict(list(zip(con_names, list(range(num_cons))))) + except: +- print "Error parsing contigs" ++ print("Error parsing contigs") + raise + except: +- print "Could not parse contig file:",contigsFile,exc_info()[0] ++ print("Could not parse contig file:",contigsFile,exc_info()[0]) + raise + + #------------------------ +@@ -280,15 +280,15 @@ class GMDataManager: + if len(bad_indices) > 0: + # report the bad contigs to the user + # and strip them before writing to the DB +- print "****************************************************************" +- print " IMPORTANT! - there are %d contigs with 0 coverage" % len(bad_indices) +- print " across all stoits. They will be ignored:" +- print "****************************************************************" +- for i in xrange(0, min(5, len(bad_indices))): +- print con_names[bad_indices[i]] ++ print("****************************************************************") ++ print(" IMPORTANT! - there are %d contigs with 0 coverage" % len(bad_indices)) ++ print(" across all stoits. They will be ignored:") ++ print("****************************************************************") ++ for i in range(0, min(5, len(bad_indices))): ++ print(con_names[bad_indices[i]]) + if len(bad_indices) > 5: +- print '(+ %d additional contigs)' % (len(bad_indices)-5) +- print "****************************************************************" ++ print('(+ %d additional contigs)' % (len(bad_indices)-5)) ++ print("****************************************************************") + + con_names = con_names[good_indices] + con_lengths = con_lengths[good_indices] +@@ -314,14 +314,14 @@ class GMDataManager: + expectedrows=num_cons + ) + except: +- print "Error creating KMERSIG table:", exc_info()[0] ++ print("Error creating KMERSIG table:", exc_info()[0]) + raise + + # compute the PCA of the ksigs and store these too + pc_ksigs, sumvariance = conParser.PCAKSigs(con_ksigs) + + db_desc = [] +- for i in xrange(0, len(pc_ksigs[0])): ++ for i in range(0, len(pc_ksigs[0])): + db_desc.append(('pc' + str(i+1), float)) + + try: +@@ -332,7 +332,7 @@ class GMDataManager: + expectedrows=num_cons + ) + except: +- print "Error creating KMERVALS table:", exc_info()[0] ++ print("Error creating KMERVALS table:", exc_info()[0]) + raise + + #------------------------ +@@ -378,7 +378,7 @@ class GMDataManager: + title="Bam based coverage", + expectedrows=num_cons) + except: +- print "Error creating coverage table:", exc_info()[0] ++ print("Error creating coverage table:", exc_info()[0]) + raise + + # transformed coverages +@@ -392,7 +392,7 @@ class GMDataManager: + title="Transformed coverage", + expectedrows=num_cons) + except: +- print "Error creating transformed coverage table:", exc_info()[0] ++ print("Error creating transformed coverage table:", exc_info()[0]) + raise + + # transformed coverage corners +@@ -406,7 +406,7 @@ class GMDataManager: + title="Transformed coverage corners", + expectedrows=len(stoitColNames)) + except: +- print "Error creating transformed coverage corner table:", exc_info()[0] ++ print("Error creating transformed coverage corner table:", exc_info()[0]) + raise + + # normalised coverages +@@ -418,16 +418,16 @@ class GMDataManager: + title="Normalised coverage", + expectedrows=num_cons) + except: +- print "Error creating normalised coverage table:", exc_info()[0] ++ print("Error creating normalised coverage table:", exc_info()[0]) + raise + + #------------------------ + # Add a table for the contigs + #------------------------ + self.setBinAssignments((h5file, meta_group), +- image=zip(con_names, ++ image=list(zip(con_names, + [0]*num_cons, +- con_lengths, con_gcs) ++ con_lengths, con_gcs)) + ) + + #------------------------ +@@ -435,7 +435,7 @@ class GMDataManager: + #------------------------ + self.initBinStats((h5file, meta_group)) + +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + + #------------------------ + # contig links +@@ -454,9 +454,9 @@ class GMDataManager: + title="ContigLinks", + expectedrows=len(rowwise_links)) + except: +- print "Error creating links table:", exc_info()[0] ++ print("Error creating links table:", exc_info()[0]) + raise +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + + #------------------------ + # Add metadata +@@ -475,12 +475,12 @@ class GMDataManager: + + # kmer signature variance table + pc_var = [sumvariance[0]] +- for i in xrange(1, len(sumvariance)): ++ for i in range(1, len(sumvariance)): + pc_var.append(sumvariance[i]-sumvariance[i-1]) + pc_var = tuple(pc_var) + + db_desc = [] +- for i in xrange(0, len(pc_var)): ++ for i in range(0, len(pc_var)): + db_desc.append(('pc' + str(i+1) + '_var', float)) + + try: +@@ -491,20 +491,20 @@ class GMDataManager: + expectedrows=1 + ) + except: +- print "Error creating tmp_kpca_variance table:", exc_info()[0] ++ print("Error creating tmp_kpca_variance table:", exc_info()[0]) + raise + + except: +- print "Error creating database:", dbFileName, exc_info()[0] ++ print("Error creating database:", dbFileName, exc_info()[0]) + raise + +- print "****************************************************************" +- print "Data loaded successfully!" +- print " ->",num_cons,"contigs" +- print " ->",len(stoitColNames),"BAM files" +- print "Written to: '"+dbFileName+"'" +- print "****************************************************************" +- print " %s" % timer.getTimeStamp() ++ print("****************************************************************") ++ print("Data loaded successfully!") ++ print(" ->",num_cons,"contigs") ++ print(" ->",len(stoitColNames),"BAM files") ++ print("Written to: '"+dbFileName+"'") ++ print("****************************************************************") ++ print(" %s" % timer.getTimeStamp()) + + # all good! + return True +@@ -516,17 +516,17 @@ class GMDataManager: + vrs = ",".join([str.lower(str(x)) for x in valid_responses]) + while(input_not_ok): + if(minimal): +- option = raw_input(" Overwrite? ("+vrs+") : ") ++ option = input(" Overwrite? ("+vrs+") : ") + else: + +- option = raw_input(" ****WARNING**** Database: '"+dbFileName+"' exists.\n" \ ++ option = input(" ****WARNING**** Database: '"+dbFileName+"' exists.\n" \ + " If you continue you *WILL* delete any previous analyses!\n" \ + " Overwrite? ("+vrs+") : ") + if(option.upper() in valid_responses): +- print "****************************************************************" ++ print("****************************************************************") + return option.upper() + else: +- print "Error, unrecognised choice '"+option.upper()+"'" ++ print("Error, unrecognised choice '"+option.upper()+"'") + minimal = True + + #------------------------------------------------------------------------------ +@@ -538,7 +538,7 @@ class GMDataManager: + this_DB_version = self.getGMDBFormat(dbFileName) + if __current_GMDB_version__ == this_DB_version: + if not silent: +- print " GroopM DB version (%s) up to date" % this_DB_version ++ print(" GroopM DB version (%s) up to date" % this_DB_version) + return + + # now, if we get here then we need to do some work +@@ -558,14 +558,14 @@ class GMDataManager: + + def upgradeDB_0_to_1(self, dbFileName): + """Upgrade a GM db from version 0 to version 1""" +- print "*******************************************************************************\n" +- print " *** Upgrading GM DB from version 0 to version 1 ***" +- print "" +- print " please be patient..." +- print "" ++ print("*******************************************************************************\n") ++ print(" *** Upgrading GM DB from version 0 to version 1 ***") ++ print("") ++ print(" please be patient...") ++ print("") + # the change in this version is that we'll be saving the first + # two kmerSig PCA's in a separate table +- print " Calculating and storing the kmerSig PCAs" ++ print(" Calculating and storing the kmerSig PCAs") + + # compute the PCA of the ksigs + ksigs = self.getKmerSigs(dbFileName) +@@ -585,26 +585,26 @@ class GMDataManager: + expectedrows=num_cons + ) + except: +- print "Error creating KMERVALS table:", exc_info()[0] ++ print("Error creating KMERVALS table:", exc_info()[0]) + raise + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + # update the formatVersion field and we're done + self.setGMDBFormat(dbFileName, 1) +- print "*******************************************************************************" ++ print("*******************************************************************************") + + def upgradeDB_1_to_2(self, dbFileName): + """Upgrade a GM db from version 1 to version 2""" +- print "*******************************************************************************\n" +- print " *** Upgrading GM DB from version 1 to version 2 ***" +- print "" +- print " please be patient..." +- print "" ++ print("*******************************************************************************\n") ++ print(" *** Upgrading GM DB from version 1 to version 2 ***") ++ print("") ++ print(" please be patient...") ++ print("") + # the change in this version is that we'll be saving a variable number of kmerSig PCA's + # and GC information for each contig +- print " Calculating and storing the kmer signature PCAs" ++ print(" Calculating and storing the kmer signature PCAs") + + # grab any data needed from database before opening if for modification + bin_ids = self.getBins(dbFileName) +@@ -617,7 +617,7 @@ class GMDataManager: + num_cons = len(pc_ksigs) + + db_desc = [] +- for i in xrange(0, len(pc_ksigs[0])): ++ for i in range(0, len(pc_ksigs[0])): + db_desc.append(('pc' + str(i+1), float)) + + try: +@@ -639,11 +639,11 @@ class GMDataManager: + h5file.renameNode(pg, 'kpca', 'tmp_kpca', overwrite=True) + + except: +- print "Error creating kpca table:", exc_info()[0] ++ print("Error creating kpca table:", exc_info()[0]) + raise + + # Add GC +- contigFile = raw_input('\nPlease specify fasta file containing the bam reference sequences: ') ++ contigFile = input('\nPlease specify fasta file containing the bam reference sequences: ') + with open(contigFile, "r") as f: + try: + contigInfo = {} +@@ -657,7 +657,7 @@ class GMDataManager: + con_gcs = np.array([contigInfo[cid][1] for cid in con_names]) + con_lengths = np.array([contigInfo[cid][0] for cid in con_names]) + except: +- print "Error parsing contigs" ++ print("Error parsing contigs") + raise + + # remove any contigs not in the current DB (these were removed due to having zero coverage) +@@ -670,27 +670,27 @@ class GMDataManager: + + mg = h5file.getNode('/', name='meta') + self.setBinAssignments((h5file, mg), +- image=zip(con_names, ++ image=list(zip(con_names, + bin_ids, +- con_lengths, con_gcs) ++ con_lengths, con_gcs)) + ) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + # update the formatVersion field and we're done + self.setGMDBFormat(dbFileName, 2) +- print "*******************************************************************************" ++ print("*******************************************************************************") + + def upgradeDB_2_to_3(self, dbFileName): + """Upgrade a GM db from version 2 to version 3""" +- print "*******************************************************************************\n" +- print " *** Upgrading GM DB from version 2 to version 3 ***" +- print "" +- print " please be patient..." +- print "" ++ print("*******************************************************************************\n") ++ print(" *** Upgrading GM DB from version 2 to version 3 ***") ++ print("") ++ print(" please be patient...") ++ print("") + # the change in this version is that we'll be saving the variance for each kmerSig PCA +- print " Calculating and storing variance of kmer signature PCAs" ++ print(" Calculating and storing variance of kmer signature PCAs") + + # compute the PCA of the ksigs + conParser = ContigParser() +@@ -699,12 +699,12 @@ class GMDataManager: + + # calcualte variance of each PC + pc_var = [sumvariance[0]] +- for i in xrange(1, len(sumvariance)): ++ for i in range(1, len(sumvariance)): + pc_var.append(sumvariance[i]-sumvariance[i-1]) + pc_var = tuple(pc_var) + + db_desc = [] +- for i in xrange(0, len(pc_var)): ++ for i in range(0, len(pc_var)): + db_desc.append(('pc' + str(i+1) + '_var', float)) + + try: +@@ -726,26 +726,26 @@ class GMDataManager: + h5file.renameNode(meta, 'kpca_variance', 'tmp_kpca_variance', overwrite=True) + + except: +- print "Error creating kpca_variance table:", exc_info()[0] ++ print("Error creating kpca_variance table:", exc_info()[0]) + raise + except: +- print "Error opening DB:", dbFileName, exc_info()[0] ++ print("Error opening DB:", dbFileName, exc_info()[0]) + raise + + # update the formatVersion field and we're done + self.setGMDBFormat(dbFileName, 3) +- print "*******************************************************************************" ++ print("*******************************************************************************") + + def upgradeDB_3_to_4(self, dbFileName): + """Upgrade a GM db from version 3 to version 4""" +- print "*******************************************************************************\n" +- print " *** Upgrading GM DB from version 3 to version 4 ***" +- print "" +- print " please be patient..." +- print "" ++ print("*******************************************************************************\n") ++ print(" *** Upgrading GM DB from version 3 to version 4 ***") ++ print("") ++ print(" please be patient...") ++ print("") + # the change in this version is that we'll be saving the variance for each kmerSig PCA +- print " Adding chimeric flag for each bin." +- print " !!! Groopm core must be run again for this flag to be properly set. !!!" ++ print(" Adding chimeric flag for each bin.") ++ print(" !!! Groopm core must be run again for this flag to be properly set. !!!") + + # read existing data in 'bins' table + try: +@@ -755,7 +755,7 @@ class GMDataManager: + for row in all_rows: + ret_dict[row[0]] = row[1] + except: +- print "Error opening DB:", dbFileName, exc_info()[0] ++ print("Error opening DB:", dbFileName, exc_info()[0]) + raise + + # write new table with chimeric flag set to False by default +@@ -785,28 +785,28 @@ class GMDataManager: + title="Bin information", + expectedrows=1) + except: +- print "Error creating META table:", exc_info()[0] ++ print("Error creating META table:", exc_info()[0]) + raise + + h5file.renameNode(mg, 'bins', 'tmp_bins', overwrite=True) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + # update the formatVersion field and we're done + self.setGMDBFormat(dbFileName, 4) +- print "*******************************************************************************" ++ print("*******************************************************************************") + + def upgradeDB_4_to_5(self, dbFileName): + """Upgrade a GM db from version 4 to version 5""" +- print "*******************************************************************************\n" +- print " *** Upgrading GM DB from version 4 to version 5 ***" +- print "" +- print " please be patient..." +- print "" ++ print("*******************************************************************************\n") ++ print(" *** Upgrading GM DB from version 4 to version 5 ***") ++ print("") ++ print(" please be patient...") ++ print("") + # the change in this version is that we'll be saving the transformed coverage coords +- print " Saving transformed coverage profiles" +- print " You will not need to re-run parse or core due to this change" ++ print(" Saving transformed coverage profiles") ++ print(" You will not need to re-run parse or core due to this change") + + # we need to get the raw coverage profiles and the kmerPCA1 data + indices = self.getConditionalIndices(dbFileName, silent=False, checkUpgrade=False) +@@ -849,7 +849,7 @@ class GMDataManager: + title="Bam based coverage", + expectedrows=CT.numContigs) + except: +- print "Error creating coverage table:", exc_info()[0] ++ print("Error creating coverage table:", exc_info()[0]) + raise + + h5file.renameNode(profile_group, 'coverage', 'tmp_coverages', overwrite=True) +@@ -865,7 +865,7 @@ class GMDataManager: + title="Transformed coverage", + expectedrows=CT.numContigs) + except: +- print "Error creating transformed coverage table:", exc_info()[0] ++ print("Error creating transformed coverage table:", exc_info()[0]) + raise + + # transformed coverage corners +@@ -879,7 +879,7 @@ class GMDataManager: + title="Transformed coverage corners", + expectedrows=CT.numStoits) + except: +- print "Error creating transformed coverage corner table:", exc_info()[0] ++ print("Error creating transformed coverage corner table:", exc_info()[0]) + raise + + +@@ -892,7 +892,7 @@ class GMDataManager: + title="Normalised coverage", + expectedrows=CT.numContigs) + except: +- print "Error creating normalised coverage table:", exc_info()[0] ++ print("Error creating normalised coverage table:", exc_info()[0]) + raise + + # stoit col names may have been shuffled +@@ -912,7 +912,7 @@ class GMDataManager: + + # update the formatVersion field and we're done + self.setGMDBFormat(dbFileName, 5) +- print "*******************************************************************************" ++ print("*******************************************************************************") + + + #------------------------------------------------------------------------------ +@@ -925,7 +925,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='r') as h5file: + full_record = [list(x) for x in h5file.root.links.links.readWhere("contig1 >= 0")] + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + if indices == []: +@@ -958,7 +958,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='r') as h5file: + return np.array([x.nrow for x in h5file.root.meta.contigs.where(condition)]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getCoverageProfiles(self, dbFileName, condition='', indices=np.array([])): +@@ -972,7 +972,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(h5file.root.profile.coverage[x.nrow]) for x in h5file.root.meta.contigs.where(condition)]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getTransformedCoverageProfiles(self, dbFileName, condition='', indices=np.array([])): +@@ -986,7 +986,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(h5file.root.profile.transCoverage[x.nrow]) for x in h5file.root.meta.contigs.where(condition)]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getNormalisedCoverageProfiles(self, dbFileName, condition='', indices=np.array([])): +@@ -1000,12 +1000,12 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(h5file.root.profile.normCoverage[x.nrow]) for x in h5file.root.meta.contigs.where(condition)]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def nukeBins(self, dbFileName): + """Reset all bin information, completely""" +- print " Clearing all old bin information from",dbFileName ++ print(" Clearing all old bin information from",dbFileName) + self.setBinStats(dbFileName, []) + self.setNumBins(dbFileName, 0) + self.setBinAssignments(dbFileName, updates={}, nuke=True) +@@ -1061,13 +1061,13 @@ class GMDataManager: + title="Bin information", + expectedrows=1) + except: +- print "Error creating META table:", exc_info()[0] ++ print("Error creating META table:", exc_info()[0]) + raise + + # rename the tmp table to overwrite + h5file.renameNode(mg, 'bins', 'tmp_bins', overwrite=True) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getBinStats(self, dbFileName): +@@ -1085,7 +1085,7 @@ class GMDataManager: + + return ret_dict + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + return {} + +@@ -1100,7 +1100,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(x)[1] for x in h5file.root.meta.contigs.readWhere(condition)]).ravel() + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def setBinAssignments(self, storage, updates=None, image=None, nuke=False): +@@ -1135,17 +1135,17 @@ class GMDataManager: + bins = self.getBins(dbFileName) + + # now apply the updates +- for tr in updates.keys(): ++ for tr in list(updates.keys()): + bins[tr] = updates[tr] + + # and build the image +- image = np.array(zip(contig_names, bins, contig_lengths, contig_gcs), ++ image = np.array(list(zip(contig_names, bins, contig_lengths, contig_gcs)), + dtype=db_desc) + + try: + h5file = tables.openFile(dbFileName, mode='a') + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + meta_group = h5file.getNode('/', name='meta') + closeh5 = True +@@ -1157,7 +1157,7 @@ class GMDataManager: + image = np.array(image, + dtype=db_desc) + else: +- print "get with the program dude" ++ print("get with the program dude") + return + + # now we write the data +@@ -1174,7 +1174,7 @@ class GMDataManager: + title="Contig information", + expectedrows=num_cons) + except: +- print "Error creating CONTIG table:", exc_info()[0] ++ print("Error creating CONTIG table:", exc_info()[0]) + raise + + # rename the tmp table to overwrite +@@ -1193,7 +1193,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(x)[0] for x in h5file.root.meta.contigs.readWhere(condition)]).ravel() + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getContigLengths(self, dbFileName, condition='', indices=np.array([])): +@@ -1207,7 +1207,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(x)[2] for x in h5file.root.meta.contigs.readWhere(condition)]).ravel() + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getContigGCs(self, dbFileName, condition='', indices=np.array([])): +@@ -1221,7 +1221,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(x)[3] for x in h5file.root.meta.contigs.readWhere(condition)]).ravel() + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getKmerSigs(self, dbFileName, condition='', indices=np.array([])): +@@ -1235,7 +1235,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(h5file.root.profile.kms[x.nrow]) for x in h5file.root.meta.contigs.where(condition)]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getKmerPCAs(self, dbFileName, condition='', indices=np.array([])): +@@ -1249,7 +1249,7 @@ class GMDataManager: + condition = "cid != ''" # no condition breaks everything! + return np.array([list(h5file.root.profile.kpca[x.nrow]) for x in h5file.root.meta.contigs.where(condition)]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + #------------------------------------------------------------------------------ +@@ -1261,7 +1261,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='r') as h5file: + return np.array(list(h5file.root.meta.kpca_variance[0])) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getTransformedCoverageCorners(self, dbFileName): +@@ -1270,7 +1270,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='r') as h5file: + return np.array([list(x) for x in h5file.root.meta.transCoverageCorners.read()]) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def setMeta(self, h5file, metaData, overwrite=False): +@@ -1310,7 +1310,7 @@ class GMDataManager: + "Descriptive data", + expectedrows=1) + except: +- print "Error creating META table:", exc_info()[0] ++ print("Error creating META table:", exc_info()[0]) + raise + + if overwrite: +@@ -1324,7 +1324,7 @@ class GMDataManager: + # theres only one value + return h5file.root.meta.meta.read()[fieldName][0] + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def setGMDBFormat(self, dbFileName, version): +@@ -1344,7 +1344,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='a', rootUEP="/") as h5file: + self.setMeta(h5file, meta_data, overwrite=True) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getGMDBFormat(self, dbFileName): +@@ -1397,7 +1397,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='a', rootUEP="/") as h5file: + self.setMeta(h5file, meta_data, overwrite=True) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def getNumBins(self, dbFileName): +@@ -1417,7 +1417,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='r') as h5file: + return h5file.root.meta.meta.read()['clustered'] + except: +- print "Error opening database:", dbFileName, exc_info()[0] ++ print("Error opening database:", dbFileName, exc_info()[0]) + raise + + def setClustered(self, dbFileName, state): +@@ -1437,7 +1437,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='a', rootUEP="/") as h5file: + self.setMeta(h5file, meta_data, overwrite=True) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + def isComplete(self, dbFileName): +@@ -1446,7 +1446,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='r') as h5file: + return h5file.root.meta.meta.read()['complete'] + except: +- print "Error opening database:", dbFileName, exc_info()[0] ++ print("Error opening database:", dbFileName, exc_info()[0]) + raise + + def setComplete(self, dbFileName, state): +@@ -1466,7 +1466,7 @@ class GMDataManager: + with tables.openFile(dbFileName, mode='a', rootUEP="/") as h5file: + self.setMeta(h5file, meta_data, overwrite=True) + except: +- print "Error opening DB:",dbFileName, exc_info()[0] ++ print("Error opening DB:",dbFileName, exc_info()[0]) + raise + + #------------------------------------------------------------------------------ +@@ -1543,7 +1543,7 @@ class GMDataManager: + fh.write(separator+data_converters[j](data_arrays[j][i])) + fh.write('\n') + except: +- print "Error opening output file %s for writing" % outFile ++ print("Error opening output file %s for writing" % outFile) + raise + + ############################################################################### +@@ -1574,7 +1574,7 @@ class ContigParser: + + def parse(self, contigFile, cutoff, kse): + """Do the heavy lifting of parsing""" +- print "Parsing contigs" ++ print("Parsing contigs") + contigInfo = {} # save everything here first so we can sort accordingly + for cid,seq in self.readFasta(contigFile): + if len(seq) >= cutoff: +@@ -1619,7 +1619,7 @@ class ContigParser: + + def getWantedSeqs(self, contigFile, wanted, storage={}): + """Do the heavy lifting of parsing""" +- print "Parsing contigs" ++ print("Parsing contigs") + for cid,seq in self.readFasta(contigFile): + if(cid in wanted): + storage[cid] = seq +@@ -1696,7 +1696,7 @@ class KmerSigEngine: + returns a tuple of floats which is the kmer sig + """ + # tmp storage +- sig = dict(zip(self.kmerCols, [0.0] * self.numMers)) ++ sig = dict(list(zip(self.kmerCols, [0.0] * self.numMers))) + # the number fo kmers in this sequence + num_mers = len(seq)-self.kLen+1 + for i in range(0,num_mers): +@@ -1710,7 +1710,7 @@ class KmerSigEngine: + try: + return tuple([sig[x] / num_mers for x in self.kmerCols]) + except ZeroDivisionError: +- print "***WARNING*** Sequence '%s' is not playing well with the kmer signature engine " % seq ++ print("***WARNING*** Sequence '%s' is not playing well with the kmer signature engine " % seq) + return tuple([0.0] * self.numMers) + + ############################################################################### +@@ -1724,7 +1724,7 @@ class BamParser: + + def parse(self, bamFiles, contigNames, cid2Indices, threads): + """Parse multiple bam files and store the results in the main DB""" +- print "Parsing BAM files using %d threads" % threads ++ print("Parsing BAM files using %d threads" % threads) + + BP = BMBP(BMCT(CT.P_MEAN_TRIMMED, 5, 5)) + BP.parseBams(bamFiles, +@@ -1736,8 +1736,8 @@ class BamParser: + # we need to make sure that the ordering of contig names is consistent + # first we get a dict that connects a contig name to the index in + # the coverages array +- con_name_lookup = dict(zip(BP.BFI.contigNames, +- range(len(BP.BFI.contigNames)))) ++ con_name_lookup = dict(list(zip(BP.BFI.contigNames, ++ list(range(len(BP.BFI.contigNames)))))) + + # Next we build the cov_sigs array by appending the coverage + # profiles in the same order. We need to handle the case where +@@ -1799,7 +1799,7 @@ class CoverageTransformer: + self.kmerNormPC1 = kmerNormPC1 + self.covProfiles = coverageProfiles + self.stoitColNames = stoitColNames +- self.indices = range(self.numContigs) ++ self.indices = list(range(self.numContigs)) + self.scaleFactor = scaleFactor + + # things we care about! +@@ -1814,8 +1814,8 @@ class CoverageTransformer: + shrinkFn = lambda x:x + + if(not silent): +- print " Reticulating splines" +- print " Dimensionality reduction" ++ print(" Reticulating splines") ++ print(" Dimensionality reduction") + + unit_vectors = [(np.cos(i*2*np.pi/self.numStoits),np.sin(i*2*np.pi/self.numStoits)) for i in range(self.numStoits)] + +@@ -1954,13 +1954,13 @@ class CoverageTransformer: + # so we need to make sure that we get all the nodes in the ordering list + trier = 0 # start of a new disjoint ring + ordering = [trier] +- while len(ordering) < len(lr_dict.keys()): ++ while len(ordering) < len(list(lr_dict.keys())): + try: + adding_index = lr_dict[trier][0] # ok IF this guy has a registered neighbour + if adding_index in ordering: # NOT ok if the neighbour is already in the list + raise IndexError() + ordering.append(adding_index) +- while len(ordering) < len(lr_dict.keys()): # try consume the entire ring ++ while len(ordering) < len(list(lr_dict.keys())): # try consume the entire ring + # len(ordering) >= 2 + last = ordering[-1] + if lr_dict[last][0] == ordering[-2]: # bi-directionality means this will always work +@@ -1973,7 +1973,7 @@ class CoverageTransformer: + # stick (2 city system) + while(trier in ordering): # find the next index NOT in the ordering + trier += 1 +- if trier < len(lr_dict.keys()): # make sure it makes sense ++ if trier < len(list(lr_dict.keys())): # make sure it makes sense + ordering.append(trier) + break + else: +@@ -1985,14 +1985,14 @@ class CoverageTransformer: + # single point + while(trier in ordering): + trier += 1 +- if trier < len(lr_dict.keys()): # make sure it makes sense ++ if trier < len(list(lr_dict.keys())): # make sure it makes sense + ordering.append(trier) + + # sanity check + if len(ordering) != self.numStoits: +- print "WATTUP, ordering is looking wrong!" +- print ordering +- print lr_dict ++ print("WATTUP, ordering is looking wrong!") ++ print(ordering) ++ print(lr_dict) + + # reshuffle the contig order! + # yay for bubble sort! +--- groopm/profileManager.py.orig 2015-03-06 07:00:49 UTC ++++ groopm/profileManager.py +@@ -96,10 +96,10 @@ from scipy.spatial import KDTree as kdt + from scipy.stats import f_oneway, distributions + + # GroopM imports +-from PCA import PCA, Center +-from mstore import GMDataManager +-from bin import Bin, mungeCbar +-import groopmExceptions as ge ++from .PCA import PCA, Center ++from .mstore import GMDataManager ++from .bin import Bin, mungeCbar ++from . import groopmExceptions as ge + + np_seterr(all='raise') + +@@ -179,7 +179,7 @@ class ProfileManager: + if(silent): + verbose=False + if verbose: +- print "Loading data from:", self.dbFileName ++ print("Loading data from:", self.dbFileName) + + try: + self.numStoits = self.getNumStoits() +@@ -188,19 +188,19 @@ class ProfileManager: + condition=condition, + silent=silent) + if(verbose): +- print " Loaded indices with condition:", condition ++ print(" Loaded indices with condition:", condition) + self.numContigs = len(self.indices) + + if self.numContigs == 0: +- print " ERROR: No contigs loaded using condition:", condition ++ print(" ERROR: No contigs loaded using condition:", condition) + return + + if(not silent): +- print " Working with: %d contigs" % self.numContigs ++ print(" Working with: %d contigs" % self.numContigs) + + if(loadCovProfiles): + if(verbose): +- print " Loading coverage profiles" ++ print(" Loading coverage profiles") + self.covProfiles = self.dataManager.getCoverageProfiles(self.dbFileName, indices=self.indices) + self.normCoverages = self.dataManager.getNormalisedCoverageProfiles(self.dbFileName, indices=self.indices) + +@@ -209,14 +209,14 @@ class ProfileManager: + + if loadRawKmers: + if(verbose): +- print " Loading RAW kmer sigs" ++ print(" Loading RAW kmer sigs") + self.kmerSigs = self.dataManager.getKmerSigs(self.dbFileName, indices=self.indices) + + if(loadKmerPCs): + self.kmerPCs = self.dataManager.getKmerPCAs(self.dbFileName, indices=self.indices) + + if(verbose): +- print " Loading PCA kmer sigs (" + str(len(self.kmerPCs[0])) + " dimensional space)" ++ print(" Loading PCA kmer sigs (" + str(len(self.kmerPCs[0])) + " dimensional space)") + + self.kmerNormPC1 = np_copy(self.kmerPCs[:,0]) + self.kmerNormPC1 -= np_min(self.kmerNormPC1) +@@ -226,26 +226,26 @@ class ProfileManager: + self.kmerVarPC = self.dataManager.getKmerVarPC(self.dbFileName, indices=self.indices) + + if(verbose): +- print " Loading PCA kmer variance (total variance: %.2f" % np_sum(self.kmerVarPC) + ")" ++ print(" Loading PCA kmer variance (total variance: %.2f" % np_sum(self.kmerVarPC) + ")") + + if(loadContigNames): + if(verbose): +- print " Loading contig names" ++ print(" Loading contig names") + self.contigNames = self.dataManager.getContigNames(self.dbFileName, indices=self.indices) + + if(loadContigLengths): + self.contigLengths = self.dataManager.getContigLengths(self.dbFileName, indices=self.indices) + if(verbose): +- print " Loading contig lengths (Total: %d BP)" % ( sum(self.contigLengths) ) ++ print(" Loading contig lengths (Total: %d BP)" % ( sum(self.contigLengths) )) + + if(loadContigGCs): + self.contigGCs = self.dataManager.getContigGCs(self.dbFileName, indices=self.indices) + if(verbose): +- print " Loading contig GC ratios (Average GC: %0.3f)" % ( np_mean(self.contigGCs) ) ++ print(" Loading contig GC ratios (Average GC: %0.3f)" % ( np_mean(self.contigGCs) )) + + if(makeColors): + if(verbose): +- print " Creating color map" ++ print(" Creating color map") + + # use HSV to RGB to generate colors + S = 1 # SAT and VAL remain fixed at 1. Reduce to make +@@ -254,7 +254,7 @@ class ProfileManager: + + if(loadBins): + if(verbose): +- print " Loading bin assignments" ++ print(" Loading bin assignments") + + self.binIds = self.dataManager.getBins(self.dbFileName, indices=self.indices) + +@@ -289,7 +289,7 @@ class ProfileManager: + self.stoitColNames = self.getStoitColNames() + + except: +- print "Error loading DB:", self.dbFileName, exc_info()[0] ++ print("Error loading DB:", self.dbFileName, exc_info()[0]) + raise + + def reduceIndices(self, deadRowIndices): +@@ -419,7 +419,7 @@ class ProfileManager: + # we'd like to take it down to about 1500 or so RI's + # but we'd like to do this in a repeatable way + ideal_contig_num = 1500 +- sub_cons = range(len(self.indices)) ++ sub_cons = list(range(len(self.indices))) + while len(sub_cons) > ideal_contig_num: + # select every second contig when sorted by norm cov + cov_sorted = np_argsort(self.normCoverages[sub_cons]) +@@ -497,7 +497,7 @@ class ProfileManager: + def transformCP(self, timer, silent=False, nolog=False): + """Do the main transformation on the coverage profile data""" + if(not silent): +- print " Reticulating splines" ++ print(" Reticulating splines") + self.transformedCP = self.dataManager.getTransformedCoverageProfiles(self.dbFileName, indices=self.indices) + self.corners = self.dataManager.getTransformedCoverageCorners(self.dbFileName) + self.TCentre = np_mean(self.corners, axis=0) +@@ -530,7 +530,7 @@ class ProfileManager: + def createColorMapHSV(self): + S = 1.0 + V = 1.0 +- return LinearSegmentedColormap.from_list('GC', [htr((1.0 + np_sin(np_pi * (val/1000.0) - np_pi/2))/2., S, V) for val in xrange(0, 1000)], N=1000) ++ return LinearSegmentedColormap.from_list('GC', [htr((1.0 + np_sin(np_pi * (val/1000.0) - np_pi/2))/2., S, V) for val in range(0, 1000)], N=1000) + + def setColorMap(self, colorMapStr): + if colorMapStr == 'HSV': +@@ -617,7 +617,7 @@ class ProfileManager: + if self.numStoits == 3: + self.transformedCP = self.covProfiles + else: +- print "Number of stoits != 3. You need to transform" ++ print("Number of stoits != 3. You need to transform") + self.transformCP(timer) + + fig = plt.figure() +@@ -633,7 +633,7 @@ class ProfileManager: + plt.show() + plt.close(fig) + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + del fig + +@@ -646,7 +646,7 @@ class ProfileManager: + if self.numStoits == 3: + self.transformedCP = self.covProfiles + else: +- print "Number of stoits != 3. You need to transform" ++ print("Number of stoits != 3. You need to transform") + self.transformCP(timer) + + fig = plt.figure() +@@ -691,7 +691,7 @@ class ProfileManager: + plt.show() + plt.close(fig) + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + del fig + +@@ -801,7 +801,7 @@ class ProfileManager: + ax = fig.add_subplot(111, projection='3d') + if len(restrictedBids) == 0: + if highlight is None: +- print "BF:", np_shape(self.transformedCP) ++ print("BF:", np_shape(self.transformedCP)) + if ignoreContigLengths: + sc = ax.scatter(self.transformedCP[:,0], + self.transformedCP[:,1], +@@ -895,7 +895,7 @@ class ProfileManager: + marker='.') + sc.set_edgecolors = sc.set_facecolors = lambda *args:None # disable depth transparency effect + +- print np_shape(disp_vals), np_shape(hide_vals), np_shape(self.transformedCP) ++ print(np_shape(disp_vals), np_shape(hide_vals), np_shape(self.transformedCP)) + + # render color bar + cbar = plt.colorbar(sc, shrink=0.5) +@@ -914,7 +914,7 @@ class ProfileManager: + r_cols = np_append(r_cols, self.contigGCs[i]) + num_added += 1 + r_trans = np_reshape(r_trans, (num_added,3)) +- print np_shape(r_trans) ++ print(np_shape(r_trans)) + #r_cols = np_reshape(r_cols, (num_added,3)) + sc = ax.scatter(r_trans[:,0], + r_trans[:,1], +@@ -958,13 +958,13 @@ class ProfileManager: + fig.set_size_inches(primaryWidth,primaryWidth) + plt.savefig(fileName,dpi=dpi,format=format) + except: +- print "Error saving image",fileName, exc_info()[0] ++ print("Error saving image",fileName, exc_info()[0]) + raise + elif(show): + try: + plt.show() + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + if del_fig: + plt.close(fig) +@@ -1075,13 +1075,13 @@ class ProfileManager: + fig.set_size_inches(primaryWidth,primaryWidth) + plt.savefig(fileName,dpi=dpi,format=format) + except: +- print "Error saving image",fileName, exc_info()[0] ++ print("Error saving image",fileName, exc_info()[0]) + raise + else: + try: + plt.show() + except: +- print "Error showing image", exc_info()[0] ++ print("Error showing image", exc_info()[0]) + raise + + ############################################################################### +--- groopm/refine.py.orig 2014-11-26 01:01:33 UTC ++++ groopm/refine.py +@@ -87,11 +87,11 @@ from scipy.spatial import KDTree as kdt + from scipy.spatial.distance import cdist, squareform, pdist + + # GroopM imports +-from binManager import BinManager +-from ellipsoid import EllipsoidTool +-from PCA import PCA, Center +-import groopmExceptions as ge +-from som import SOM ++from .binManager import BinManager ++from .ellipsoid import EllipsoidTool ++from .PCA import PCA, Center ++from . import groopmExceptions as ge ++from .som import SOM + np_seterr(all='raise') + + ############################################################################### +@@ -150,23 +150,23 @@ class RefineEngine: + ignoreRanges=True + + if auto: +- print " Start automatic bin refinement" +- num_binned = len(self.PM.binnedRowIndices.keys()) ++ print(" Start automatic bin refinement") ++ num_binned = len(list(self.PM.binnedRowIndices.keys())) + perc = "%.2f" % round((float(num_binned)/float(self.PM.numContigs))*100,2) +- print " ",num_binned,"contigs across",len(self.BM.bins.keys()),"cores (",perc,"% )" ++ print(" ",num_binned,"contigs across",len(list(self.BM.bins.keys())),"cores (",perc,"% )") + + graph = self.autoRefineBins(timer, makeGraph=gf!="") + if graph is not None: +- print " Writing graph to:", gf ++ print(" Writing graph to:", gf) + try: + with open(gf, "w") as gv_fh: + gv_fh.write(graph) + except: +- print "Error writing graph to:", gf ++ print("Error writing graph to:", gf) + +- num_binned = len(self.PM.binnedRowIndices.keys()) ++ num_binned = len(list(self.PM.binnedRowIndices.keys())) + perc = "%.2f" % round((float(num_binned)/float(self.PM.numContigs))*100,2) +- print " ",num_binned,"contigs across",len(self.BM.bins.keys()),"cores (",perc,"% )" ++ print(" ",num_binned,"contigs across",len(list(self.BM.bins.keys())),"cores (",perc,"% )") + + if plotFinal != "": + bids = self.BM.getBids() +@@ -196,28 +196,28 @@ class RefineEngine: + user_option = self.promptOnPlotterRefine() + + if(user_option == 'Q'): +- print '\nBye!' ++ print('\nBye!') + return + + elif(user_option == 'C'): +- print "Select colormap:" +- print " 1. HSV" +- print " 2. Accent" +- print " 3. Blues" +- print " 4. Spectral" +- print " 5. Grayscale" +- print " 6. Discrete (14 colors)" +- print " 7. Discrete paired (14 colors)" ++ print("Select colormap:") ++ print(" 1. HSV") ++ print(" 2. Accent") ++ print(" 3. Blues") ++ print(" 4. Spectral") ++ print(" 5. Grayscale") ++ print(" 6. Discrete (14 colors)") ++ print(" 7. Discrete paired (14 colors)") + + bValid = False + while(not bValid): + try: +- colormap_id = int(raw_input(" Enter colormap number (e.g., 1): ")) ++ colormap_id = int(input(" Enter colormap number (e.g., 1): ")) + if colormap_id < 1 or colormap_id > 7: + raise ValueError('Invalid colormap id.') + bValid = True + except ValueError: +- print "Colormap must be specified as a number between 1 and 7." ++ print("Colormap must be specified as a number between 1 and 7.") + + if colormap_id == 1: + self.PM.setColorMap('HSV') +@@ -238,19 +238,19 @@ class RefineEngine: + if use_elipses: + ET = None + use_elipses = False +- print "\nEllipses off" ++ print("\nEllipses off") + else: + ET = self.ET + use_elipses = True +- print "\nEllipses on" ++ print("\nEllipses on") + + elif(user_option == 'X'): + if show_chimeric_bins: + show_chimeric_bins = False +- print "\nHiding likely chimeric bins." ++ print("\nHiding likely chimeric bins.") + else: + show_chimeric_bins = True +- print "\nShowing likely chimeric bins." ++ print("\nShowing likely chimeric bins.") + + elif(user_option == 'R'): + self.BM.plotBinIds(ignoreRanges=ignoreRanges, showChimeric=show_chimeric_bins) +@@ -277,7 +277,7 @@ class RefineEngine: + have_range = False + while(not have_range): + try: +- gc_range_str = raw_input(" Enter GC range to examine (e.g., 0.5-0.6): ") ++ gc_range_str = input(" Enter GC range to examine (e.g., 0.5-0.6): ") + + if '-' not in gc_range_str: + raise ValueError('Incorrectly formatted GC range.') +@@ -289,7 +289,7 @@ class RefineEngine: + + have_range = True + except ValueError: +- print "GC ranges must be entered as 'a-b' (e.g., 0.5-0.6)." ++ print("GC ranges must be entered as 'a-b' (e.g., 0.5-0.6).") + self.BM.plotBinIds(gc_range=gc_range, ignoreRanges=ignoreRanges) + + elif(user_option == 'B'): +@@ -299,17 +299,17 @@ class RefineEngine: + while(not have_bid): + have_bid = True + try: +- usr_bids = raw_input(" Enter 'space' seperated bin id(s) to plot: ") ++ usr_bids = input(" Enter 'space' seperated bin id(s) to plot: ") + bids = [int(i) for i in usr_bids.split(" ")] + if bids == [-1]: + bids = self.BM.getBids() + else: + for bid in bids: + if bid not in self.BM.bins: +- print "ERROR: Bin %d not found!" % bid ++ print("ERROR: Bin %d not found!" % bid) + have_bid &= False + except ValueError: +- print "You need to enter an integer value!" ++ print("You need to enter an integer value!") + + if len(bids) > 0: + self.BM.plotSelectBins(bids, plotMers=True, ET=ET) +@@ -320,22 +320,22 @@ class RefineEngine: + have_parts = False + while(not have_bid): + try: +- bid = int(raw_input(" Enter bid to split: ")) ++ bid = int(input(" Enter bid to split: ")) + if bid not in self.BM.bins: +- print "ERROR: Bin %d not found!" % bid ++ print("ERROR: Bin %d not found!" % bid) + else: + have_bid = True + except ValueError: +- print "You need to enter an integer value!" ++ print("You need to enter an integer value!") + while(not have_parts): + try: +- parts = int(raw_input(" Enter number of parts to split into: ")) ++ parts = int(input(" Enter number of parts to split into: ")) + if(parts < 2): +- print "ERROR: Need to choose 2 or more parts" ++ print("ERROR: Need to choose 2 or more parts") + else: + have_parts = True + except ValueError: +- print "You need to enter an integer value!" ++ print("You need to enter an integer value!") + self.BM.split(bid, + parts, + mode='kmer', +@@ -350,23 +350,23 @@ class RefineEngine: + have_radius = False + while(not have_bid): + try: +- bid = int(raw_input(" Enter bid of interest: ")) ++ bid = int(input(" Enter bid of interest: ")) + if bid not in self.BM.bins: +- print "ERROR: Bin %d not found!" % bid ++ print("ERROR: Bin %d not found!" % bid) + else: + have_bid = True + except ValueError: +- print "You need to enter an integer value!" ++ print("You need to enter an integer value!") + while(not have_radius): + try: +- usr_radius = raw_input(" Enter radius to select from [default 100]: ") ++ usr_radius = input(" Enter radius to select from [default 100]: ") + if usr_radius == "": + radius = 100 + else: + radius = int(usr_radius) + have_radius = True + except ValueError: +- print "You need to enter an integer value!" ++ print("You need to enter an integer value!") + + # we need to find all points in an area about the centroid of + # this bin +@@ -397,9 +397,9 @@ class RefineEngine: + # reshape + disp_vals = np_reshape(disp_vals, (num_points, 3)) + +- print " Points are located in bins:" ++ print(" Points are located in bins:") + for seen_bid in seen_bids: +- print " %d - %d occurances" % (seen_bid, len(seen_bids[seen_bid])) ++ print(" %d - %d occurances" % (seen_bid, len(seen_bids[seen_bid]))) + + fig = plt.figure() + ax = fig.add_subplot(1,1,1, projection='3d') +@@ -423,7 +423,7 @@ class RefineEngine: + try: + plt.show() + except: +- print "Error showing image:", sys.exc_info()[0] ++ print("Error showing image:", sys.exc_info()[0]) + raise + plt.close(fig) + del fig +@@ -459,7 +459,7 @@ class RefineEngine: + # identify and remove outlier bins + if markLikelyChimeric: + nuked = self.markLikelyChimericBins() +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + + if makeGraph: +@@ -472,7 +472,7 @@ class RefineEngine: + # merge bins together + if mergeSimilarBins: + self.mergeSimilarBins(graph=graph, verbose=False) +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + + if plotAfterOB: +@@ -485,12 +485,12 @@ class RefineEngine: + self.PM.contigGCs, + self.PM.contigLengths) + self.BM.plotBins(FNPrefix="AFTER_OB", ET=self.ET) +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + + if shuffleRefine: + nuked = self.shuffleRefineContigs(timer) +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + if makeGraph: + # Make sure we know these guys were deleted +@@ -501,7 +501,7 @@ class RefineEngine: + + if removeDuds: + nuked = self.removeDuds() +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + if makeGraph: + # Make sure we know these guys were deleted +@@ -516,7 +516,7 @@ class RefineEngine: + def markLikelyChimericBins(self, verbose=False): + """ Identify bins which contain mixed genomes based on GC. + Small bins are nuked, large bins are flagged as chimeric. """ +- print " Identifying possible chimeric bins" ++ print(" Identifying possible chimeric bins") + sys_stdout.flush() + + # first we need to build a distribution! +@@ -553,8 +553,8 @@ class RefineEngine: + freeBinnedRowIndices=True, + saveBins=False) + +- print " Identified %d likely chimeric bin(s), removed %d small chimeric bin(s)" % (num_chimeric_bins, len(dead_bins)) +- print " %s" % ",".join(str(u) for u in dead_bins) ++ print(" Identified %d likely chimeric bin(s), removed %d small chimeric bin(s)" % (num_chimeric_bins, len(dead_bins))) ++ print(" %s" % ",".join(str(u) for u in dead_bins)) + return dead_bins + + def mergeSimilarBins(self, verbose=False, graph=None, silent=False): +@@ -565,7 +565,7 @@ class RefineEngine: + orig_num_bins = len(self.BM.getNonChimericBinIds()) + + if not silent: +- print " Merging similar bins (%d) with kCut %0.2f (+/-%0.3f) cCut %0.2f (+/-%0.3f)" % (orig_num_bins, kCutMedian, kCutStd, cCutMedian, cCutStd) ++ print(" Merging similar bins (%d) with kCut %0.2f (+/-%0.3f) cCut %0.2f (+/-%0.3f)" % (orig_num_bins, kCutMedian, kCutStd, cCutMedian, cCutStd)) + + # identify merging groups and then merge them + mergers = self.findMergeGroups(kCutMedian, kCutStd, cCutMedian, cCutStd, verbose=verbose) +@@ -575,7 +575,7 @@ class RefineEngine: + bins_removed = self.combineMergers(merge, kCutMedian, kCutStd, cCutMedian, cCutStd, graph=graph) + num_bins_removed += len(bins_removed) + if not silent: +- print " Merged %d of %d cores leaving %d cores total" % (num_bins_removed, orig_num_bins, len(self.BM.getNonChimericBinIds())) ++ print(" Merged %d of %d cores leaving %d cores total" % (num_bins_removed, orig_num_bins, len(self.BM.getNonChimericBinIds()))) + + return num_bins_removed + +@@ -666,10 +666,10 @@ class RefineEngine: + common_neighbors = set(cov_neighbor_list).intersection(set(kmer_neighbor_list)) + + if verbose: +- print "++++++++++" +- print bid, cov_neighbor_list +- print bid, kmer_neighbor_list +- print bid, common_neighbors ++ print("++++++++++") ++ print(bid, cov_neighbor_list) ++ print(bid, kmer_neighbor_list) ++ print(bid, common_neighbors) + + # test each neighbor in turn + for i, neighbor_index in enumerate(common_neighbors): +@@ -680,8 +680,8 @@ class RefineEngine: + merged_query_bid = merged_bins[merged_query_bid] + + if verbose: +- print "++++++++++" +- print base_bid, query_bid, merged_base_bid, merged_query_bid ++ print("++++++++++") ++ print(base_bid, query_bid, merged_base_bid, merged_query_bid) + #----- + # TIME WASTERS + +@@ -689,7 +689,7 @@ class RefineEngine: + seen_key = self.BM.makeBidKey(base_bid, query_bid) + if(seen_key in processed_pairs or merged_base_bid == merged_query_bid): + if verbose: +- print "TW" ++ print("TW") + continue + processed_pairs[seen_key] = True + +@@ -708,7 +708,7 @@ class RefineEngine: + ) + if lengths_wrong: + if verbose: +- print "LW" ++ print("LW") + continue + + #----- +@@ -719,15 +719,15 @@ class RefineEngine: + c_dist_bw = self.cDistBetweenBins(base_bin, query_bin) + + if verbose: +- print 'k_dist_bw, c_dist_bw' +- print k_dist_bw, c_dist_bw +- print '---------------------' ++ print('k_dist_bw, c_dist_bw') ++ print(k_dist_bw, c_dist_bw) ++ print('---------------------') + + + if k_dist_bw < kCutMedian and c_dist_bw < cCutMedian: + if verbose: +- print 'MERGED' +- print '---------------------' ++ print('MERGED') ++ print('---------------------') + + if merged_query_bid < merged_base_bid: + merged_bins[merged_base_bid] = merged_query_bid +@@ -773,7 +773,7 @@ class RefineEngine: + + if not INTT: + if verbose: +- print "KINTT" ++ print("KINTT") + continue + #----- + # MINIMUM BOUNDING COVERAGE ELLIPSOID +@@ -802,7 +802,7 @@ class RefineEngine: + + if not intersects: + if verbose: +- print "CINTT" ++ print("CINTT") + continue + + # We only get here if we're going to merge the bins +@@ -869,7 +869,7 @@ class RefineEngine: + cur_bin = self.BM.getBin(cur_bid) + + dists = [] +- for i in xrange(1, len(sorted_bid)): ++ for i in range(1, len(sorted_bid)): + frag_bid = sorted_bid[i] + frag_bin = self.BM.getBin(frag_bid) + +@@ -1069,14 +1069,14 @@ class RefineEngine: + iterations=800, + silent=silent, + weightImgFileNamePrefix=animateFilePrefix) +- print " --" +- print " %s" % timer.getTimeStamp() ++ print(" --") ++ print(" %s" % timer.getTimeStamp()) + if render: + SS.renderWeights("S1") + + if maskBoundaries: + if not silent: +- print " Creating boundary mask" ++ print(" Creating boundary mask") + # make a boundary mask + if render: + SS.makeBoundaryMask(plotMaskFile="S2.png") +@@ -1086,23 +1086,23 @@ class RefineEngine: + if defineBins: + # assign regions on som surface to specific bins + if not silent: +- print " Defining bin regions" ++ print(" Defining bin regions") + SS.defineBinRegions(bids, training_data, render=render) + if render: + SS.renderBoundaryMask("S5.png") + if maskBoundaries: + # mask out regions where we don't like it + if not silent: +- print " Masking SOM classifier" ++ print(" Masking SOM classifier") + SS.maskBoundaries(addNoise=False, doFlat=True) + if render: + SS.renderWeights("S6") + +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + if retrain: + # retrain bin regions using contigs from the bin + if not silent: +- print " Retraining SOM classifier" ++ print(" Retraining SOM classifier") + for i in range(len(bids)): + bid = bids[i] + sys_stdout.write("\r Retraining on bin: %d (%d of %d)" % (bid, i+1, len(bids))) +@@ -1117,7 +1117,7 @@ class RefineEngine: + render=render) + if render: + SS.renderWeights("gg") +- print " --" ++ print(" --") + + if render: + SS.renderWeights("S7") +@@ -1148,8 +1148,8 @@ class RefineEngine: + + # now we'd like to centre the weights and mask within an + # appropriately sized square +- min_p = np_min(maskPoints.keys(), axis=0) +- max_p = np_max(maskPoints.keys(), axis=0) ++ min_p = np_min(list(maskPoints.keys()), axis=0) ++ max_p = np_max(list(maskPoints.keys()), axis=0) + diffs = max_p - min_p + small_side = np_min(diffs) + sweights = np_copy(SS.weights.nodes[min_p[0]:min_p[0]+diffs[0]+1,min_p[1]:min_p[1]+diffs[1]+1]) +@@ -1158,7 +1158,7 @@ class RefineEngine: + # shift and mask out all other bins + shifted_mask_points = {} + shifted_bin_mask = np_ones((diffs[0]+1,diffs[1]+1)) +- for (r,c) in maskPoints.keys(): ++ for (r,c) in list(maskPoints.keys()): + shift = maskPoints[(r,c)] - min_p + shifted_bin_mask[shift[0],shift[1]] = 0 + shifted_mask_points[(shift[0], shift[1])] = shift +@@ -1174,7 +1174,7 @@ class RefineEngine: + + #SS.weights.renderSurface("D_%d.png"%bid, nodes=sweights) + # update the torusMesh values appropriately +- for (r,c) in maskPoints.keys(): ++ for (r,c) in list(maskPoints.keys()): + shift = maskPoints[(r,c)] - min_p + SS.weights.nodes[r,c] = sweights[shift[0], shift[1]] + SS.weights.fixFlatNodes() +@@ -1185,7 +1185,7 @@ class RefineEngine: + + def shuffleRefineContigs(self, timer, inclusivity=2): + """refine bins by shuffling contigs around""" +- print " Start shuffle refinement" ++ print(" Start shuffle refinement") + + # first, build a SOM + bids = self.BM.getBids() +@@ -1198,7 +1198,7 @@ class RefineEngine: + defineBins=True, + retrain=True) + +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + + # now do the shuffle refinement, keep an eye out for + new_assignments = {} +@@ -1280,30 +1280,30 @@ class RefineEngine: + nones[old_bid] = 1 + + +- if False: +- print " ------------------------------------------------------" +- print " BID ORIG CHGE SAME NEWS NONE TOTAL" +- print " ------------------------------------------------------" ++ if False: ++ print(" ------------------------------------------------------") ++ print(" BID ORIG CHGE SAME NEWS NONE TOTAL") ++ print(" ------------------------------------------------------") + for bid in bids: +- print " %4d %5d " % (bid, self.BM.bins[bid].binSize), ++ print(" %4d %5d " % (bid, self.BM.bins[bid].binSize), end=' ') + if bid in wrongs: +- print "%04d " % wrongs[bid], ++ print("%04d " % wrongs[bid], end=' ') + else: +- print "0000 ", ++ print("0000 ", end=' ') + if bid in rights: +- print "%04d " % rights[bid], ++ print("%04d " % rights[bid], end=' ') + else: +- print "0000 ", ++ print("0000 ", end=' ') + if bid in news: +- print "%04d " % news[bid], ++ print("%04d " % news[bid], end=' ') + else: +- print "0000 ", ++ print("0000 ", end=' ') + if bid in nones: +- print "%04d " % nones[bid], ++ print("%04d " % nones[bid], end=' ') + else: +- print "0000 ", +- print "%04d " % len(new_assignments[bid]) +- print "\n ---------------------------------------------" ++ print("0000 ", end=' ') ++ print("%04d " % len(new_assignments[bid])) ++ print("\n ---------------------------------------------") + + # now get ready for saving. + # first, we nuke all non-chimeric bins +@@ -1335,7 +1335,7 @@ class RefineEngine: + + def removeDuds(self, ms=20, mv=1000000, verbose=False): + """Run this after refining to remove scrappy leftovers""" +- print " Removing dud cores (min %d contigs or %d bp)" % (ms, mv) ++ print(" Removing dud cores (min %d contigs or %d bp)" % (ms, mv)) + deleters = [] + for bid in self.BM.getBids(): + self.BM.bins[bid] +@@ -1343,13 +1343,13 @@ class RefineEngine: + # delete this chap! + deleters.append(bid) + if verbose: +- print "duds", deleters ++ print("duds", deleters) + if len(deleters) > 0: + self.BM.deleteBins(deleters, + force=True, + freeBinnedRowIndices=True, + saveBins=False) +- print " Removed %d cores leaving %d cores" % (len(deleters), len(self.BM.bins)) ++ print(" Removed %d cores leaving %d cores" % (len(deleters), len(self.BM.bins))) + return deleters + + #------------------------------------------------------------------------------ +@@ -1509,7 +1509,7 @@ class RefineEngine: + step_size = float(len(row_indices)) / sample_size + si = [] + index = 0.0 +- for _i in xrange(0, sample_size): ++ for _i in range(0, sample_size): + si.append(row_indices[sorted_indices[int(index)]]) + index += step_size + +@@ -1568,10 +1568,10 @@ class RefineEngine: + indices2 = bin2.rowIndices + + angles = [] +- for i in xrange(0, min(len(bin1.rowIndices), max_in_bin)): ++ for i in range(0, min(len(bin1.rowIndices), max_in_bin)): + r1 = indices1[i] + +- for j in xrange(0, min(len(bin2.rowIndices), max_in_bin)): ++ for j in range(0, min(len(bin2.rowIndices), max_in_bin)): + r2 = indices2[j] + try: + ang = np_arccos(np_dot(self.PM.covProfiles[r1], self.PM.covProfiles[r2]) / +@@ -2051,7 +2051,7 @@ class RefineEngine: + + def recruitWrapper(self, timer, inclusivity=2, step=200, nukeAll=False, saveBins=False): + """Recuit more contigs to the bins""" +- print "Recruiting unbinned contigs" ++ print("Recruiting unbinned contigs") + + # make a list of all the cov and kmer vals + total_expanded = 0 +@@ -2090,9 +2090,9 @@ class RefineEngine: + + # talk to the user + perc_binned = float(total_binned)/float(total_contigs) +- print " Planned steps = ", steps +- print " BEGIN: %0.4f" % perc_binned +"%"+" of %d requested contigs in bins" % total_contigs +- print " %d contigs unbinned" % total_unbinned ++ print(" Planned steps = ", steps) ++ print(" BEGIN: %0.4f" % perc_binned +"%"+" of %d requested contigs in bins" % total_contigs) ++ print(" %d contigs unbinned" % total_unbinned) + + # build the classifier on all the existing bins + (SS, minz, maxz, side) = self.buildSOM(timer, +@@ -2100,7 +2100,7 @@ class RefineEngine: + defineBins=True, + retrain=True) + +- print " %s" % timer.getTimeStamp() ++ print(" %s" % timer.getTimeStamp()) + + # go through the steps we decided on + affected_bids = list(np_copy(self.BM.getBids())) +@@ -2132,7 +2132,7 @@ class RefineEngine: + block -= minz + block /= maxz + +- print " Recruiting contigs above: %d (%d contigs)" % (cutoff, len(unbinned_rows)) ++ print(" Recruiting contigs above: %d (%d contigs)" % (cutoff, len(unbinned_rows))) + + for i in range(len(unbinned_rows)): + putative_bid = SS.classifyContig(block[i]) +@@ -2159,21 +2159,21 @@ class RefineEngine: + for row_index in new_binned: + del unbinned[row_index] + +- print " Recruited: %d contigs" % this_step_binned +- print " %s" % timer.getTimeStamp() ++ print(" Recruited: %d contigs" % this_step_binned) ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + + # talk to the user + perc_recruited = float(total_expanded)/float(total_unbinned) + perc_binned = float(total_binned)/float(total_contigs) +- print " Recruited %0.4f" % perc_recruited +"%"+" of %d unbinned contigs" % total_unbinned +- print " END: %0.4f" % perc_binned +"%"+" of %d requested contigs in bins" % total_contigs +- print " %s" % timer.getTimeStamp() ++ print(" Recruited %0.4f" % perc_recruited +"%"+" of %d unbinned contigs" % total_unbinned) ++ print(" END: %0.4f" % perc_binned +"%"+" of %d requested contigs in bins" % total_contigs) ++ print(" %s" % timer.getTimeStamp()) + sys_stdout.flush() + + # now save + if(saveBins): +- print "Saving bins" ++ print("Saving bins") + self.BM.saveBins() + + #------------------------------------------------------------------------------ +@@ -2183,7 +2183,7 @@ class RefineEngine: + """Output a valid graphviz dot file""" + op = "digraph refine {\n" + # render nodes +- for bid in graph[0].keys(): ++ for bid in list(graph[0].keys()): + op += graph[0][bid] + # render edges + op += "\n".join(graph[1]) +@@ -2191,7 +2191,7 @@ class RefineEngine: + return op + + def printRefinePlotterInstructions(self): +- raw_input( "****************************************************************\n" ++ input( "****************************************************************\n" + " REFINING INSTRUCTIONS - PLEASE READ CAREFULLY\n"+ + "****************************************************************\n" + " You have chosen to refine in plotter mode. Congratulations!\n" +@@ -2201,7 +2201,7 @@ class RefineEngine: + " Follow the instructions to merge or split these bins\n\n" + " Good Luck!\n\n" + " Press return to continue...") +- print "****************************************************************" ++ print("****************************************************************") + + def promptOnPlotterRefine(self, minimal=False): + """Find out what the user wishes to do next when refining bins""" +@@ -2210,9 +2210,9 @@ class RefineEngine: + vrs = ",".join([str.lower(str(x)) for x in valid_responses]) + while(input_not_ok): + if(minimal): +- option = raw_input(" What next? ("+vrs+") : ") ++ option = input(" What next? ("+vrs+") : ") + else: +- option = raw_input("\n Please choose from the following options:\n" \ ++ option = input("\n Please choose from the following options:\n" \ + "------------------------------------------------------------\n" \ + " r = plot entire space using bin ids\n" \ + " p = plot entire space with bins as points\n" \ +@@ -2231,7 +2231,7 @@ class RefineEngine: + if(option.upper() in valid_responses): + return option.upper() + else: +- print "Error, unrecognised choice '"+option+"'" ++ print("Error, unrecognised choice '"+option+"'") + minimal=True + + def PCA2Col(self, PCAs): +@@ -2409,7 +2409,7 @@ class GrubbsTester: + idx = 999 + + if verbose: +- print np_mean(compVals+[maxVal]), np_std(compVals+[maxVal], ddof=1), maxVal, v, idx, self.critVs[idx], v > self.critVs[idx] ++ print(np_mean(compVals+[maxVal]), np_std(compVals+[maxVal], ddof=1), maxVal, v, idx, self.critVs[idx], v > self.critVs[idx]) + + return v > self.critVs[idx] + +--- groopm/som.py.orig 2014-11-26 01:01:33 UTC ++++ groopm/som.py +@@ -1,5 +1,5 @@ + #!/usr/bin/env python +-from __future__ import division ++ + ############################################################################### + # # + # som.py # +@@ -77,12 +77,13 @@ from math import log, exp + import numpy as np + from scipy.spatial.distance import cdist + from PIL import Image, ImageDraw ++from functools import reduce + np.seterr(all='raise') + + # GroopM imports +-from torusMesh import TorusMesh as TM +-from rainbow import Rainbow +-import groopmExceptions as ge ++from .torusMesh import TorusMesh as TM ++from .rainbow import Rainbow ++from . import groopmExceptions as ge + + ############################################################################### + ############################################################################### +@@ -193,7 +194,7 @@ class SOM: + # we only need to return a tuple + nt = self.makeNTuple(s_bid,q_bid) + neighbours[nt] = True +- return neighbours.keys() ++ return list(neighbours.keys()) + + def makeNTuple(self, bid1, bid2): + """A way for making standard tuples from bids""" +@@ -228,7 +229,7 @@ class SOM: + """ + + if not silent: +- print " Start SOM training. Side: %d Max: %d iterations" % (self.side, iterations) ++ print(" Start SOM training. Side: %d Max: %d iterations" % (self.side, iterations)) + + if radius == 0.0: + radius = self.radius +@@ -376,7 +377,7 @@ class SOM: + weights = np.clip(weights + deltasheet[rows:2*rows,cols:2*cols], 0, 1) + else: + delta_fold = deltasheet[rows:2*rows,cols:2*cols] +- for (r,c) in mask.keys(): ++ for (r,c) in list(mask.keys()): + weights[r,c] = np.clip(weights[r,c] + delta_fold[r,c], 0, 1) + flat_nodes = weights.reshape((rows*cols, self.dimension)) + +@@ -386,7 +387,7 @@ class SOM: + # make a tmp image, perhaps + if(weightImgFileNamePrefix != ""): + filename = "%s_%04d.jpg" % (weightImgFileNamePrefix, i) +- print " writing: %s" % filename ++ print(" writing: %s" % filename) + self.weights.renderSurface(filename) + + return weights +@@ -467,7 +468,7 @@ class SOM: + # get all the points within this region + points = self.floodFill(startR, startC, self.boundaryMask) + collision_bid = 0 +- for (r,c) in points.keys(): ++ for (r,c) in list(points.keys()): + if self.binAssignments[r,c] != 0: + if self.binAssignments[r,c] != bid: + # we have already assigned this point to a bin +@@ -487,7 +488,7 @@ class SOM: + # rebuild the mask with a new cutoff + mc = mc/2 + mask = np.copy(self.boundaryMask) +- for (r,c) in points.keys(): ++ for (r,c) in list(points.keys()): + if self.VS_flat[r,c] > mc: + mask[r,c] = 1. + else: +@@ -497,15 +498,15 @@ class SOM: + new_points = self.floodFill(startR, startC, mask) + #print len(collision_points.keys()), len(new_points.keys()) + #print collision_points.keys()[0] in new_points +- if len(collision_points.keys()) == 0 or len(new_points.keys()) == 0: ++ if len(list(collision_points.keys())) == 0 or len(list(new_points.keys())) == 0: + continue + # there should be no overlap +- if collision_points.keys()[0] not in new_points: ++ if list(collision_points.keys())[0] not in new_points: + # we have resolved the issue + resolved = True + # now we need to fix the binAssignments and boundary mask + self.boundaryMask = mask +- for (r,c) in points.keys(): ++ for (r,c) in list(points.keys()): + if (r,c) in new_points: + # assign this point to the new bid + self.binAssignments[r,c] = bid +@@ -517,7 +518,7 @@ class SOM: + break + + if not resolved: +- print "Cannot repair map, bin %d may be incorrectly merged with bin %d" % (bid, collision_bid) ++ print("Cannot repair map, bin %d may be incorrectly merged with bin %d" % (bid, collision_bid)) + return + + def makeBinMask(self, profile, fileName="", dim=False): +@@ -526,7 +527,7 @@ class SOM: + points = self.floodFill(r, c, self.boundaryMask) + if fileName != "": + ret_mask = np.ones_like(self.boundaryMask) +- for (r,c) in points.keys(): ++ for (r,c) in list(points.keys()): + ret_mask[r,c] = 0 + self.renderBoundaryMask(fileName, mask=ret_mask) + +@@ -600,7 +601,7 @@ class SOM: + img = img.resize((self.weights.columns*10, self.weights.rows*10),Image.NEAREST) + img.save(filename) + except: +- print sys.exc_info()[0] ++ print(sys.exc_info()[0]) + raise + + def renderBoundaryMask(self, fileName, mask=None, colMap=None): +@@ -625,7 +626,7 @@ class SOM: + img = img.resize((self.side*10, self.side*10),Image.NEAREST) + img.save(fileName) + except: +- print sys.exc_info()[0] ++ print(sys.exc_info()[0]) + raise + + def transColour(self, val): +@@ -659,7 +660,7 @@ class SOM: + img = img.resize((self.weights.columns*10, self.weights.rows*10),Image.NEAREST) + img.save(fileName) + except: +- print sys.exc_info()[0] ++ print(sys.exc_info()[0]) + raise + + ############################################################################### +--- groopm/torusMesh.py.orig 2014-11-26 01:01:33 UTC ++++ groopm/torusMesh.py +@@ -250,7 +250,7 @@ class TorusMesh: + img = img.resize((columns*10, rows*10),Image.NEAREST) + img.save(fileName) + except: +- print sys.exc_info()[0] ++ print(sys.exc_info()[0]) + raise + + ############################################################################### |