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! ')
