if (AOI == 'HLT') or (AOI == 'CST'):
MF = (False, True)
else:
MF = (True, True)
###############################################################################
# Setting up paths and style
###############################################################################
exp = '100'
for exp in EXP:
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT,
PT_MTR) = aux.selectPath(USR, DRV, exp)
drive = drv.driveSelector(DRV, AOI)
DVP = drive.get('gDict')
# Time and head -----------------------------------------------------------
tS = datetime.now()
aux.printExperimentHead(PT_DTA, PT_IMG, PT_PRE, tS, 'PreTraces ' + AOI)
###########################################################################
# Load folders
###########################################################################
(expDirsMean, expDirsTrac) = fun.getExpPaths(PT_DTA)
(expNum, nodeDigits) = (len(expDirsMean), len(str(len(NOI))) + 1)
outNames = fun.splitExpNames(PT_OUT)
outExpNames = set(outNames)
###########################################################################
# Analyze data
###########################################################################
Parallel(n_jobs=JOB)(delayed(monet.preProcess)(exIx,
expNum,
expDirsMean,
expDirsTrac,
DVP,
(USR, DRV, AOI) = ('srv', 'tGD', 'HLT')
# (USR, DRV, AOI) = (sys.argv[1], sys.argv[2], sys.argv[3])
(OVW, gIx, hIx) = (True, 1, 0)
if (USR == 'srv2') or (USR == 'dsk2'):
EXPS = ('000', )
else:
EXPS = ('100', )
for EXP in EXPS:
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT,
PT_MTR) = aux.selectPath(USR, DRV, EXP)
uids = fun.getExperimentsIDSets(PT_PRE, skip=-1)
(hnf, cac, frc, hrt, ren, res, typ, grp) = uids[1:]
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG, PT_OUT, tS, 'PstFraction')
# #########################################################################
# Base experiments
# These are the experiments without any releases (for fractions)
# #########################################################################
basePat = aux.XP_NPAT.format('*', '*', '*', '*', '00', '*', AOI, '*',
'sum', 'bz')
baseFiles = sorted(glob(PT_PRE + basePat))
# #########################################################################
# Probe experiments
# sum: Analyzed data aggregated into one node
# srp: Garbage data aggregated into one node
# #########################################################################
msg = '* Analyzing ({}/{})'
(xpNum, digs) = monet.lenAndDigits(ren)
for (i, rnIt) in enumerate(ren):
# -------------------------------------------------------------------------
(scalers, HD_DEP, _, cmapR) = aux.selectDepVars(moi, THR, AOI)
cmap = cmapR # cmapR.reversed()
# if AOI == 'WLD':
# cmap = cmapR.reversed()
###########################################################################
# Loop through the experiments
###########################################################################
for exp in EXPS:
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT, PT_MTR) = aux.selectPath(USR, DRV, exp)
PT_IMG = PT_IMG + 'heat/'
monet.makeFolder(PT_IMG)
PT_IMG = PT_IMG+'-'.join(HD_IND)+'/'
monet.makeFolder(PT_IMG)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG, PT_MTR, tS, 'Heatmap '+AOI)
#######################################################################
# Analyzes
#######################################################################
# Load files into dataframe
fPtrn = '{}{}_{}_{}_qnt.csv'.format(PT_MTR, AOI, moi, QNT)
(df, header, headerInd) = aux.loadDFFromSummary(fPtrn)
# Filter the dataframe ------------------------------------------------
# Get the unique values for each indep-var column of the dataframe
uniqueValues = {i: list(df[i].unique()) for i in headerInd}
idTuplesAll = list(product(*uniqueValues.values()))
# Filtering all the experiments of the non-free columns
hdFree = [col for col in headerInd if col not in HD_IND]
# print(hdFree)
# Get the unique IDs of the experiments
uniqueIds = [uniqueValues.get(head) for head in hdFree]
if (USR == 'srv2') or (USR == 'dsk'):
EXPS = ('000', )
NOI = [[0]]
else:
EXPS = ('050', '100', '400', '800')
NOI = [[0], [1]]
for EXP in EXPS:
# #############################################################################
# Setup paths and drive
# #############################################################################
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT,
PT_MTR) = aux.selectPath(USR, DRV, EXP)
(PT_IMG_I, PT_IMG_O) = (PT_IMG + 'pstTraces/', PT_IMG + 'stacksAOI/')
monet.makeFolder(PT_IMG_O)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG_I, PT_IMG_O, tS,
'AOI VConcat ' + QNT)
# Get files -------------------------------------------------------------------
imgLists = [glob('{}*{}*{}*'.format(PT_IMG_I, i, QNT)) for i in AOI]
imgTuples = list(zip(*[sorted(i) for i in imgLists]))
# #############################################################################
# Iterate through images
# #############################################################################
fmt = 'Processing {}/' + str(len(imgTuples))
for (i, tp) in enumerate(imgTuples):
print(fmt.format(str(i + 1).zfill(3)), end='\r')
fName = tp[0].split('/')[-1][:-4].replace('-HLT_', '-')
imgArray = [cv2.imread(i) for i in tp]
vertical = cv2.hconcat(imgArray)
# show the output image
cv2.imwrite(PT_IMG_O + fName + '.png', vertical)
monet.makeFolder(PT_IMG)
drive = drv.driveSelector(DRV, AOI)
(CLR, YRAN) = (drive.get('colors'), (0, drive.get('yRange')))
STYLE = {
"width": .25,
"alpha": .15,
"dpi": 500,
"legend": True,
"aspect": .25,
"colors": CLR,
"xRange": [0, (365 * 5) / 3],
"yRange": YRAN
}
STYLE['aspect'] = monet.scaleAspect(1, STYLE)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG, PT_PRE, tS, 'PstTraces')
###########################################################################
# Load postprocessed files
###########################################################################
pstPat = PT_MTR + AOI + '_{}_' + QNT + '_qnt.csv'
pstFiles = [pstPat.format(i) for i in ('TTI', 'TTO', 'WOP', 'MNX', 'RAP')]
(dfTTI, dfTTO, dfWOP, dfMNX, _) = [pd.read_csv(i) for i in pstFiles]
###########################################################################
# Load preprocessed files lists
###########################################################################
repFiles = glob(PT_PRE + '*' + AOI + '*' + 'srp' + '*')
if FZ:
fLists = fun.getFilteredFiles(PT_PRE + '*_00_*' + AOI + '*srp.bz',
PT_PRE + '*' + AOI + '*' + '*srp.bz')
else:
fLists = glob(PT_PRE + '*' + AOI + '*' + '*srp.bz')
from datetime import datetime
import MoNeT_MGDrivE as monet
# (USR, DRV, AOI) = ('dsk', 'tGD', 'HLT')
(USR, DRV, AOI) = (sys.argv[1], sys.argv[2], sys.argv[3])
QNT = ['50', '75', '90']
EXP = '000'
# #############################################################################
# Setup paths and drive
# #############################################################################
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT,
PT_MTR) = aux.selectPath(USR, DRV, EXP)
(PT_IMG_I, PT_IMG_O) = (PT_IMG + 'pstTraces/', PT_IMG + 'stacksQNT/')
monet.makeFolder(PT_IMG_O)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG_I, PT_IMG_O, tS, 'QNT VConcat ' + AOI)
# Get files -------------------------------------------------------------------
imgLists = [glob('{}*{}*{}*'.format(PT_IMG_I, AOI, i)) for i in QNT]
imgTuples = list(zip(*[sorted(i) for i in imgLists]))
# #############################################################################
# Iterate through images
# #############################################################################
fmt = 'Processing {}/' + str(len(imgTuples))
for (i, tp) in enumerate(imgTuples):
print(fmt.format(str(i + 1).zfill(3)), end='\r')
fName = tp[0].split('/')[-1][:-7]
imgArray = [cv2.imread(i) for i in tp]
vertical = cv2.vconcat(imgArray)
# show the output image
cv2.imwrite(PT_IMG_O + fName + '.png', vertical)
[-.05, 0, .1, .2, .3, .4, .5, .6, .7, .8, .9, 1.05],
'linear', 'linear', 'linear'
)
(exp, moi, mtr) = ('000', 'WOP', '0.1')
(scalers, HD_DEP, _, cmapR) = aux.selectDepVars(moi, float(mtr), AOI)
cmap = cmapR.reversed()
###########################################################################
# Loop through the experiments
###########################################################################
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT, PT_MTR) = aux.selectPath(USR, DRV, exp)
PT_IMG = PT_IMG + 'violin/'
monet.makeFolder(PT_IMG)
PT_IMG = PT_IMG+'-'.join(HD_IND)+'/'
monet.makeFolder(PT_IMG)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG, PT_MTR, tS, 'Violin '+AOI)
#######################################################################
# Analyzes
#######################################################################
# Load files into dataframe
fPtrn = '{}{}_{}_{}_qnt.csv'.format(PT_MTR, AOI, moi, QNT)
(df, header, headerInd) = aux.loadDFFromSummary(fPtrn)
# (fig, ax) = plt.subplots()
# ax = sns.violinplot(
# x=mtr, y='i_ren', data=df, palette="muted", cut=0, split=False, orient='h',
# ax=ax
# )
(fig, ax) = plt.subplots()
HNF = list(set(df['i_hnf']))
colors = plt.cm.RdPu(np.linspace(0, 1, 100))
for (i, hnf) in enumerate(HNF):
exp = EXP[0]
for exp in EXP:
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT, PT_MTR) = aux.selectPath(USR, DRV, exp)
PT_IMG_I = PT_IMG + 'preTraces/'
PT_IMG_O = PT_IMG + 'preOverlay/'
monet.makeFolder(PT_IMG_O)
drive = drv.driveSelector(DRV, AOI)
(CLR, YRAN) = (drive.get('colors'), (0, drive.get('yRange')))
STYLE = {
"width": .25, "alpha": .75, "dpi": 200, "legend": True,
"aspect": .25, "colors": CLR, "xRange": [0, (365*5)/3],
"yRange": (0, YRAN[1]*1.5)
}
STYLE['aspect'] = monet.scaleAspect(1, STYLE)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG, PT_PRE, tS, 'PreOverlays '+AOI)
###########################################################################
# Load preprocessed files lists
###########################################################################
fLists = list(zip(
*[sorted(glob(PT_IMG_I+'*'+'*'+tp+'*')) for tp in typs]
))
###########################################################################
# Iterate file lists
###########################################################################
for fs in fLists:
imgs = [Image.open(i).convert('RGBA') for i in fs]
(w, h) = imgs[0].size
bkg = Image.new('RGBA', (w, h), (255, 255, 255, 255))
for i in imgs:
bkg.paste(i, (0, 0), i)
ax.imshow(repsRatios, cmap=cmap)
# add TTI-------------------------------------------------------------
[plt.axvline(i, color='black', alpha=.65, lw=0.175, ls='-.') for i in tti]
# add TTO-------------------------------------------------------------
[plt.axvline(j, color='black', alpha=.75, lw=0.2, ls='dotted') for j in tto]
# Save the figure------------------------------------------------------
outName = fName.split('/')[-1].split('.')[0][:-4]
plt.xlim(X_RAN)
ax.axes.xaxis.set_ticklabels([])
ax.axes.yaxis.set_ticklabels([])
ax.axes.xaxis.set_visible(False)
ax.axes.yaxis.set_visible(False)
ax.xaxis.set_tick_params(size=0)
ax.yaxis.set_tick_params(size=0)
plt.savefig(PT_IMG+outName + '.png', bbox_inches='tight', pad_inches=0.01, dpi=500)
plt.close("all")
for exp in EXPS:
# Select path ------------------------------------------------------------
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT, PT_MTR) = aux.selectPath(USR, DRV, exp)
PT_IMG = PT_IMG+'xRay/'
monet.makeFolder(PT_IMG)
tS = datetime.now()
aux.printExperimentHead(PT_ROT, PT_IMG, PT_MTR, tS, 'X-Ray '+AOI)
# Load file --------------------------------------------------------------
fNames = glob(PT_OUT+'*{}*.npy'.format(AOI))
xpNumS = str(len(fNames)).zfill(4)
(xpNum, digs) = monet.lenAndDigits(fNames)
Parallel(n_jobs=1)(delayed(parallelPlotter)(i, xpNum, digs, fName, PT_IMG) for (i, fName) in enumerate(fNames))
else:
EXPS = ('050', '100', '400', '800')
NOI = [[0], [1]]
header = ['i_hnf', 'i_cac', 'i_frc', 'i_hrt', 'i_ren', 'i_res', 'i_grp']
outLabels = ('TTI', 'TTO', 'WOP', 'RAP', 'MNX')
###############################################################################
# Iterate through experiments
###############################################################################
xpDict = {}
smryDicts = ({}, {}, {}, {}, {})
expNum = len(EXPS)
for (j, EXP) in enumerate(EXPS):
tS = datetime.now()
(PT_ROT, PT_IMG, PT_DTA, PT_PRE, PT_OUT,
PT_MTR) = aux.selectPath(USR, DRV, EXP)
aux.printExperimentHead(PT_ROT, PT_IMG, PT_OUT, tS, 'PostProcess ' + AOI)
print('{}* [{}/{}] {}{}'.format(monet.CWHT,
str(j + 1).zfill(3),
str(expNum).zfill(3), EXP, monet.CEND))
# Output dataframes paths -------------------------------------------------
pth = PT_MTR + AOI + '_{}_' + QNT + '_qnt.csv'
DFOPths = [pth.format(z) for z in outLabels]
# Get experiment IDs ------------------------------------------------------
# print(PT_OUT)
uids = fun.getExperimentsIDSets(PT_OUT, skip=-1)
(hnf, cac, frc, hrt, ren, res, typ, grp) = uids[1:]
# Parse filepaths ---------------------------------------------------------
ptrn = aux.XP_NPAT.format('*', '*', '*', '*', '*', '*', AOI, '*', 'rto',
'npy')
fPaths = sorted(glob(PT_OUT + ptrn))
# Create empty dataframes to store the data -------------------------------
