def HelperFunction(i, xpNum, digs, fLists, STYLE, PT_IMG): print(msg.format(str(i+1).zfill(digs), str(xpNum).zfill(digs)), end='\r') (sumDta, repDta) = [pkl.load(file) for file in (fLists[i])] name = fLists[i][0].split('/')[-1].split('.')[0][:-4][11:] # Export plots -------------------------------------------------------- fun.exportTracesPlot(repDta, name, STYLE, PT_IMG, append='TRA') cl = [i[:-2]+'cc' for i in CLR] if i == xpNum - 1: monet.exportGeneLegend( sumDta['genotypes'], cl, PT_IMG+'/plt_{}.png'.format(AOI), 500 ) tE = datetime.now() print('* Analyzed ({}/{}) '.format(xpNum, xpNum), end='\n') print(monet.PAD)
"alpha": .15, "dpi": 250, "legend": True, "aspect": .25, "colors": CLR, "xRange": [0, (365 * 6) / 3], "yRange": YRAN } STYLE['aspect'] = monet.scaleAspect(1, STYLE) tS = datetime.now() aux.printExperimentHead(PT_ROT, PT_IMG, PT_PRE, tS, 'SDY PreTraces') # ############################################################################# # Process files # ############################################################################# fLists = aux.getZeroFilteredFiles(PT_PRE, AOI, FZ=FZ, tyTag=('sum', 'srp')) (xpNum, digs) = monet.lenAndDigits(fLists) msg = '* Analyzing ({}/{})' # Iterate through experiments ------------------------------------------------- for i in range(0, xpNum): print(msg.format(str(i + 1).zfill(digs), str(xpNum).zfill(digs)), end='\r') (sumDta, repDta) = [pkl.load(file) for file in (fLists[i])] name = fLists[i][0].split('/')[-1].split('.')[0][:-4] plot.exportTracesPlot(repDta, name, STYLE, PT_IMG, append='TRA') cl = [i[:-2] + 'cc' for i in CLR] # Color palette --------------------------------------------------------------- cpltName = PT_IMG + '/plt_{}.png'.format(AOI) monet.exportGeneLegend(sumDta['genotypes'], cl, cpltName, 500) tE = datetime.now() print('* Analyzed ({}/{}) '.format(xpNum, xpNum), end='\n') print(monet.PAD)
fun.plotAndSaveStack( aggData, ssDay, ffString, ffStringH, pathRoot + "/images/" + drvStr + "S_" + expStr + FORMAT, xRange, yRange, styleS) if TRACES is True: pathsRoot = monet.listDirectoriesWithPathWithinAPath(pathRoot + pathExt + "GARBAGE/") expNum = len(pathsRoot) ssDay = xRange for i in range(0, expNum): # Print progress print('* Exporting ({}/{})'.format( str(i + 1).zfill(4), str(expNum).zfill(4)), end='\r') # Plot and export landscapeReps, ssDay, expStr = fun.getLandscapeReps( i, pathRoot, pathExt, aggregationDictionary) drvStr = str(DRIVE).zfill(2) fun.plotAndSaveLandscapeReps( landscapeReps, ssDay, pathRoot + "images/" + drvStr + "R_" + expStr + FORMAT, xRange, yRangeFixed, style) ############################################################################## # Export the legend ############################################################################## monet.exportGeneLegend(genes, colors, pathRoot + "/images/stacks/Palette" + FORMAT, 500)
fltrPattern = aux.patternForReleases(SET, '00', AOI, 'srp', ext='bz') repFiles = monet.getFilteredFiles(PT_PRE + fltrPattern, globPattern.format('srp')) ########################################################################### # Iterate through experiments ########################################################################### (fNum, digs) = monet.lenAndDigits(repFiles) Parallel(n_jobs=JOB)( delayed(monet.exportPstTracesPlotWrapper)(exIx, repFiles, xpidIx, dfTTI, dfTTO, dfWOP, dfMNX, dfPOE, dfCPT, aux.STABLE_T, THS, QNT, STYLE, PT_IMG, digs=digs, popScaler=1, border=True) for exIx in range(0, len(repFiles))) # Export gene legend ------------------------------------------------------ repDta = pkl.load(repFiles[-1]) monet.exportGeneLegend(repDta['genotypes'], [i[:-2] + 'cc' for i in CLR], PT_IMG + '/legend_{}.png'.format(AOI), 500)
PT_MTR) = aux.selectPath(USR, LND, REL) PT_IMG = PT_IMG + 'preTraces/' monet.makeFolder(PT_IMG) # Setup the run --------------------------------------------------------------- tS = datetime.now() monet.printExperimentHead(PT_ROT, PT_IMG, tS, 'UCIMI PreTraces ' + AOI) ############################################################################### # Load preprocessed files lists ############################################################################### tyTag = ('sum', 'srp') (fltrPattern, globPattern) = ('dummy', PT_PRE + '*' + AOI + '*' + '{}' + '*') if FZ: fltrPattern = PT_PRE + '*_00_*' + AOI + '*' + '{}' + '*' fLists = monet.getFilteredTupledFiles(fltrPattern, globPattern, tyTag) ############################################################################### # Process files ############################################################################### (xpNum, digs) = monet.lenAndDigits(fLists) for i in range(0, xpNum): monet.printProgress(i + 1, xpNum, digs) (sumDta, repDta) = [pkl.load(file) for file in (fLists[i])] name = fLists[i][0].split('/')[-1].split('.')[0][:-4] monet.exportTracesPlot(repDta, name, STYLE, PT_IMG, vLines=[0, 0]) ############################################################################### # Export plot legend ############################################################################### if len(fLists) > 0: cl = [i[:-2] + 'cc' for i in CLR] monet.exportGeneLegend(sumDta['genotypes'], cl, PT_IMG + '/plt_{}.png'.format(AOI), 500)
"legend": True, "aspect": .5, "colors": CLR, "xRange": [0, 1825], "yRange": [0, 20 * 100000] } STYLE['aspect'] = monet.scaleAspect(1, STYLE) ############################################################################### # Load preprocessed files lists ############################################################################### tyTag = ('sum', 'rep') fLists = list(zip(*[sorted(glob(PATH_OUT + '*' + tp + FMT)) for tp in tyTag])) fLists.reverse() ############################################################################### # Process files ############################################################################### (xpNum, digs) = fun.lenAndDigits(fLists) msg = '* Analyzing ({}/{})' for i in range(0, xpNum): print(msg.format(str(i + 1).zfill(digs), str(xpNum).zfill(digs)), end='\r') (sumDta, repDta) = [pkl.load(file) for file in (fLists[i])] name = fLists[i][0].split('/')[-1].split('.')[-2][:-4] # Export plots ------------------------------------------------------------ fun.exportTracesPlot(repDta, name, STYLE, PATH_IMG, append='TRA') cl = [i[:-2] + 'cc' for i in CLR] monet.exportGeneLegend(sumDta['genotypes'], cl, PATH_IMG + '/plt.png', 500) tE = datetime.now() print('* Analyzed ({}/{}) '.format(xpNum, xpNum), end='\n') # fun.printExpTerminal(tE-tS, PATH_ROOT, PATH_IMG, PATH_DATA) print(monet.PAD)
zip(*[ sorted(glob(PT_PRE + '*' + AOI + '*' + tp + '*')) for tp in tyTag ])) ########################################################################### # Process files ########################################################################### (xpNum, digs) = monet.lenAndDigits(fLists) msg = '* Analyzing ({}/{})' for i in range(0, xpNum): print(msg.format(str(i + 1).zfill(digs), str(xpNum).zfill(digs)), end='\r') (sumDta, repDta) = [pkl.load(file) for file in (fLists[i])] name = fLists[i][0].split('/')[-1].split('.')[0][:-4] # Export plots -------------------------------------------------------- monet.exportTracesPlot(repDta, name, STYLE, PT_IMG, append='TRA', wopPrint=False, transparent=True) cl = [i[:-2] + 'cc' for i in CLR] monet.exportGeneLegend( drive.get('gDict')['genotypes'], cl, PT_IMG + '/plt_{}.png'.format(AOI), 500) tE = datetime.now() print('* Analyzed ({}/{}) '.format(xpNum, xpNum), end='\n')
axTemp.set_xticks(range(0, style["xRange"][1], 150)) axTemp.tick_params(color=(0, 0, 0, 0.5)) for spine in axTemp.spines.values(): spine.set_edgecolor((0, 0, 0, 0.5)) figsArray[0].savefig(expOutStr + "/Pop_FULL.pdf", dpi=style['dpi'], facecolor=None, edgecolor='w', orientation='portrait', papertype=None, format='pdf', transparent=True, bbox_inches='tight', pad_inches=.01) plt.close('all') ############################################################################### # Goodbye Message ############################################################################### print('* Finished!') print(aux.PADL) print(aux.CWHT + 'UCI Experiments Analysis [{}]'.format(str(datetime.datetime.now())) + aux.CEND) print(aux.PAD) monet.exportGeneLegend( ['W', 'H'], [(0, .22, .66, .5), (1, 0, .6, .5)], #aux.STYLE_HLT['colors'], expOutStr + '/plt.pdf', 500)
fLists = list(zip(*[sorted(glob(pathPre + '*' + tp + EXT)) for tp in typTag])) ############################################################################### # Load preprocessed files lists ############################################################################### (xpNum, digs) = fun.lenAndDigits(fLists) msg = '* Analyzing ({}/{})' for i in range(0, xpNum): print(msg.format(str(i + 1).zfill(digs), str(xpNum).zfill(digs)), end='\r') (sumDta, spaDta, repDta, srpDta) = [pkl.load(file) for file in (fLists[i])] # (sumDta, repDta) = [pkl.load(file) for file in (fLists[i])] name = fLists[i][0].split('/')[-1].split('.')[-2][:-4] # Process data ------------------------------------------------------------ spaDtaNorm = monet.rescaleGeneSpatiotemporals(spaDta) overlay = monet.plotGenotypeOverlayFromLandscape( spaDtaNorm, vmax=1, style={ "aspect": 50 * STYLE['aspect'], "cmap": CMAPS }, ) # Export plots ------------------------------------------------------------ fun.exportTracesPlot(repDta, name, STYLE, pathImg, append='TRA') monet.quickSaveFigure(overlay, '{}/{}-{}.pdf'.format(pathImg, name, 'OVR'), format='pdf') monet.exportGeneLegend(sumDta['genotypes'], CLR, pathImg + '/plt.pdf', 500) tEnd = datetime.now() print('* Analyzed ({}/{}) '.format(xpNum, xpNum), end='\n') aux.printExperimentTail(str(tEnd - tSrt), 'Plotting')
overlay = monet.plotGenotypeOverlayFromLandscape( geneSpatiotemporalsNorm, style={ "aspect": 50 * STYLE['aspect'], "cmap": CMAPS }, vmax=1 # 50 ) figsArray = (monet.plotLandscapeDataRepetitions(ykLand, STYLE), monet.plotLandscapeDataRepetitions(tpLand, STYLE)) fun.exportTracesPlot(ykLand, name, STYLE, PATH_IMG, append='D' + '_YK_' + pp) fun.exportTracesPlot(tpLand, name, STYLE, PATH_IMG, append='D' + '_TP_' + pp) monet.quickSaveFigure(overlay, '{}/{}-{}.pdf'.format(PATH_IMG, name, 'O_' + pp), format='pdf') plt.close('all') monet.exportGeneLegend(ykLand['genotypes'], COLORS, PATH_IMG + '/plt.pdf', 500) ############################################################################### # Print terminal message ############################################################################### tEnd = datetime.datetime.now() aux.printExperimentTail(str(tEnd - tSrt), 'GeoValidation Finished! ')
relStr=REL_STR) axTemp = monet.printVLines(axTemp, list(range(20, 26 * 7, 7)), alpha=.1, lStyle='--', width=.1) # Export to disk expOutStr = path + drivePars.get('folder') + '/' + experimentString figsArray[j].savefig(expOutStr + "_N" + str(j) + ".pdf", dpi=style['dpi'], bbox_inches='tight', pad_inches=0.025, transparent=True) plt.close('all') monet.exportGeneLegend(drv['genotypes'], style['colors'], path + drivePars.get('folder') + '/Swatch.png', 300) # Terminal ############################################################ print('Exported {0}/{1}: {2}'.format( str(i + 1).rjust(4, '0'), num, expOutStr)) ########################################################################## # Export color palette ########################################################################## # drvNum = len(drv['genotypes']) # (labels, colors) = (drv['genotypes'], style['colors'][0:drvNum]) # filename = path + drivePars.get('folder') + '/legend.pdf' # monet.exportGeneLegend(labels, colors, filename, dpi=750) ############################################################################## time = str(datetime.datetime.now()) print(aux.PAD + '* Finished [{0}]'.format(time) + aux.PAD) ##############################################################################
'genotypes': GDICT['genotypes'], 'population': np.loadtxt(file, skiprows=1, delimiter=',') } plot = monet.plotMeanGenotypeTrace(pop, STYLE) axTemp = plot.get_axes()[0] axTemp.set_xlim(STYLE['xRange'][0], STYLE['xRange'][1]) axTemp.set_ylim(STYLE['yRange'][0], STYLE['yRange'][1]) axTemp.axhlines(range(0, 1, .1), colors=(0, 0, 0, .25), linewidth=.2, ls='dashed') plot.savefig("{}/{}-{}.pdf".format(PATH_IMG, name, 'E'), dpi=STYLE['dpi'], facecolor=None, edgecolor='w', orientation='portrait', papertype=None, format='pdf', transparent=True, bbox_inches='tight', pad_inches=.01) plt.close('all') print('Finished exporting all the plots!') print(aux.CEND, end='\r') ############################################################################### # Print terminal message ############################################################################### tEnd = datetime.datetime.now() aux.printExperimentTail(str(tEnd - tSrt), 'GeoValidation Finished! ') monet.exportGeneLegend(GDICT['genotypes'], COLORS, PATH_IMG + 'plt.pdf', 500)
############################################################################### tSrt = datetime.datetime.now() aux.printExperimentHead(PATH, PATH_IMG, PATH_ERR, str(tSrt), 'GeoValidation ') if xpTest is False: print(aux.CRED + 'ERROR: Missmatch in number of experiments!' + aux.CEND) sys.exit() ############################################################################### # Main analyses ############################################################################### for i in range(xpNumb): # Load data --------------------------------------------------------------- aux.printProggress(i, xpNumb, sig) (nS, mS, tS) = fun.loadAndCalcResponse(sig[i], GDICT, MALE, FEMALE) (nP, mP, tP) = fun.loadAndCalcResponse(prb[i], GDICT, MALE, FEMALE) # Calculate and save error ----------------------------------------------- err = fun.rpd(mS['landscape'], mP['landscape']) np.savetxt('{}/{}.csv'.format(PATH_ERR, nS), err, fmt='%.4e', delimiter=',', header=','.join(mS['genotypes'])) # Plots ------------------------------------------------------------------ fun.exportTracesPlot(tS, nS, STYLE, PATH_IMG, append='S') fun.exportTracesPlot(tP, nP, STYLE, PATH_IMG, append='P') monet.exportGeneLegend(mS['genotypes'], COLORS, PATH_IMG + "/plt.pdf", 500) ############################################################################### # Print terminal message ############################################################################### tEnd = datetime.datetime.now() aux.printExperimentTail(str(tEnd - tSrt), 'GeoValidation Finished! ')