def get_masks(labeled, minArea=None, maxArea=None, isSort=True, keyPrefix = None, labelLength=3):
'''
get mask dictionary from labeled maps (labeled by scipy.ndimage.label function)
area range of each mask was defined by minArea and maxArea
isSort: if True, sort masks by areas, big to small
keyPrefix: the prefix of key
labelLength: the number of characters of key
'''
maskNum = np.max(labeled.flatten())
masks = {}
for i in range(1,maskNum+1):
currMask = np.zeros(labeled.shape,dtype=np.uint8)
currMask[labeled==i]=1
if minArea is not None and np.sum(currMask.flatten()) < minArea: pass
elif maxArea is not None and np.sum(currMask.flatten()) > maxArea: pass
else:
if keyPrefix is not None: currKey = keyPrefix+'.'+ft.int2str(i,labelLength)
else: currKey = ft.int2str(i,labelLength)
masks.update({currKey:currMask})
if isSort:
masks = sort_masks(masks, keyPrefix = keyPrefix, labelLength=labelLength)
return masks
def get_masks(labeled, minArea=None, maxArea=None, isSort=True, keyPrefix=None, labelLength=3):
"""
get mask dictionary from labeled maps (labeled by scipy.ndimage.label function)
area range of each mask was defined by minArea and maxArea
isSort: if True, sort masks by areas, big to small
keyPrefix: the prefix of key
labelLength: the number of characters of key
"""
maskNum = np.max(labeled.flatten())
masks = {}
for i in range(1, maskNum + 1):
currMask = np.zeros(labeled.shape, dtype=np.uint8)
currMask[labeled == i] = 1
if minArea is not None and np.sum(currMask.flatten()) < minArea:
pass
elif maxArea is not None and np.sum(currMask.flatten()) > maxArea:
pass
else:
if keyPrefix is not None:
currKey = keyPrefix + '.' + ft.int2str(i, labelLength)
else:
currKey = ft.int2str(i, labelLength)
masks.update({currKey: currMask})
if isSort:
masks = sort_masks(masks, keyPrefix=keyPrefix, labelLength=labelLength)
return masks
def satDXToTimeSeries(filename):
file = open(filename)
data = ft.read(file)
(rows, cols) = data.shape
dict = pyLTR.TimeSeries()
mon = []
mday = []
dayFraction = []
doy = []
atime = []
for i in range(rows):
d = datetime.date(int(data[i, 0]), 1,
1) + datetime.timedelta(int(data[i, 1]) - 1)
mon.append(d.month)
mday.append(d.day)
dayFraction = (data[i, 2] + data[i, 3] / 60.0 +
data[i, 4] / 3600.0) / 24.0
doy.append(float(data[i, 1]) + dayFraction)
#atime.append(datetime.datetime(d.year,d.month,d.day,data[i,2],data[i,3],data[i,4]))
dict.append('time_doy', 'Day of Year', ' ', doy)
dict.append('density', 'Den', r'$\mathrm{1/cm^3}$', data[:, 5])
dict.append('vx', 'Vx', r'$\mathrm{km/s}$', data[:, 6])
dict.append('vy', 'Vy', r'$\mathrm{km/s}$', data[:, 7])
dict.append('vz', 'Vz', r'$\mathrm{km/s}$', data[:, 8])
dict.append('p', 'P', r'$\mathrm{keV/cm^3}$', data[:, 9])
dict.append('bx', 'Bx', r'$\mathrm{nT}$', data[:, 10])
dict.append('by', 'By', r'$\mathrm{nT}$', data[:, 11])
dict.append('bz', 'Bz', r'$\mathrm{nT}$', data[:, 12])
dict.append('ex', 'Ex', r'$\mathrm{V/m}$', data[:, 13])
dict.append('ey', 'Ey', r'$\mathrm{V/m}$', data[:, 14])
dict.append('ez', 'Ez', r'$\mathrm{V/m}$', data[:, 15])
return dict
def __init__(self, dossier_acquis, isdata):
"""
Definition of the data acquisition parameters
Parameters
----------
dossier_acquis : str
Path to the data.
isdata : bool
If isdata is True, data are processed, if isdata is False, white images are processed.
Returns
-------
None.
"""
self.dossier_acquis = dossier_acquis
self.dossier_data = f"{dossier_acquis}data/"
self.dossier_blanc = f"{dossier_acquis}blanc/"
self.isdata = isdata
self.fichier_config = f"{dossier_acquis}config/config_manip.txt"
procfolder = self.createresultfolder(dossier_acquis, "Pretraitement",
isdata)
self.dossier_pretraitement = procfolder
recfolder = self.createresultfolder(dossier_acquis, "Reconstruction",
isdata)
self.dossier_reconstruction = recfolder
gerchfolder = self.createresultfolder(dossier_acquis, "Gerchberg",
isdata)
self.dossier_gerchberg = gerchfolder
self.NA = float(ft.readvalue(self.fichier_config, 'NA'))
self.NIMM = float(ft.readvalue(self.fichier_config, 'N0'))
self.LAMBDA = float(ft.readvalue(self.fichier_config, 'LAMBDA'))
self.F_TUBE = float(ft.readvalue(self.fichier_config,
'F_TUBE')) # Tube lens focal length
self.F_OBJ = float(ft.readvalue(
self.fichier_config, 'F_OBJ')) # Microscope objective focal length
self.PIX = float(ft.readvalue(self.fichier_config,
'TPCAM')) # Physical pixel pitch
self.RAPFOC = float(ft.readvalue(
self.fichier_config,
'RF')) # focal length ratio of the resampling lens dublet
self.CHEMINMASQUE = f"{self.dossier_data}Image_mask.pgm"
self.CENTREX = int(ft.readvalue(
self.fichier_config, 'CIRCLE_CX')) # Pupil center in Fourier space
self.CENTREY = int(ft.readvalue(self.fichier_config, 'CIRCLE_CY'))
self.NB_HOLOTOT = int(ft.readvalue(self.fichier_config, 'NB_HOLO'))
def get_template():
pre = '/home/luke/Documents/computational_naval_architecture/projects/relational_hull_design'
directory = pre+'/relational_lsplines/relational_lsplines'
filename = 'TemplateTable.tex'
testlines = FileTools.GetLines(directory,filename)
for line in testlines:
print line
return testlines
def read_training_file(train_file):
global_features = {}
local_features = []
gold_vec = []
with FileTools.openReadFile(train_file) as ifile:
info = ifile.readline().rstrip()
e = info.split(" ")
n_global = int(e[0])
n_local = int(e[1])
# ignore next line
line = ifile.readline()
# print n_global,n_local
if (read_features(global_features, 1, ifile) == 0):
return [None, None]
global_features = dict([(x, int(global_features[x][0]) - 1)
for x in global_features])
line = ifile.readline()
if (len(line) == 0):
return None
n_sent = 0
while (len(line) > 0):
# print str(n_sent)+": "+line
if (line[0] != '#'):
print "Expecting comment in line " + line
return None
e = line.rstrip().split(" ")
gold = e[-1]
n_sent = n_sent + 1
if (n_sent % 10 == 0):
print(str(n_sent)) #, end='\r')
# sys.stdout.flush()
if (n_sent % 100 == 0):
break
local_sent_features = {}
if (read_features(local_sent_features, n_local, ifile) == 0):
return [None, None]
if (gold in global_features):
gold_vec.append(gold)
local_features.append(local_sent_features)
line = ifile.readline()
#print "\n"+str(n_sent)+" "+line
return [n_local, n_global, global_features, local_features, gold_vec]
def sort_masks(masks, keyPrefix='', labelLength=3):
'''
sort a dictionary of binary masks, big to small
'''
maskNum = len(masks.keys())
order = []
for key, mask in masks.iteritems():
order.append([key,np.sum(mask.flatten())])
order = sorted(order, key=lambda a:a[1], reverse=True)
newMasks = {}
for i in range(len(order)):
if keyPrefix is not None: currKey = keyPrefix+'.'+ft.int2str(i,labelLength)
else: currKey = ft.int2str(i,labelLength)
newMasks.update({currKey:masks[order[i][0]]})
return newMasks
def sort_masks(masks, keyPrefix='', labelLength=3):
"""
sort a dictionary of binary masks, big to small
"""
maskNum = len(masks.keys())
order = []
for key, mask in masks.iteritems():
order.append([key, np.sum(mask.flatten())])
order = sorted(order, key=lambda a: a[1], reverse=True)
newMasks = {}
for i in range(len(order)):
if keyPrefix is not None:
currKey = keyPrefix + '.' + ft.int2str(i, labelLength)
else:
currKey = ft.int2str(i, labelLength)
newMasks.update({currKey: masks[order[i][0]]})
return newMasks
def main(args):
if len(args) < 3:
print("Usage:", args[0], "<if> <of>")
return -1
with FileTools.openReadFile(args[1]) as ifh, FileTools.openWriteFile(
args[2]) as ofh:
words = []
tags = []
v = None
for l in ifh:
e = l.rstrip().split("\t")
if len(e) < 3:
ofh.write(v + " " + " ".join(words) + " ||| " +
" ".join(tags) + "\n")
words = []
tags = []
else:
t = e[2]
if t == 'B-V':
v = str(len(words))
elif t != 'O':
if t.find("ARG") != -1:
t = t.replace("ARG", "A")
else:
t = t.replace("-", "-AM-")
words.append(e[1])
tags.append(t)
if len(words):
ofh.write(" ".join(words) + " ||| " + " ".join(tags) + "\n")
return 0
def main():
argc = len(sys.argv)
n_iter = 100
reg = 0.1
if (argc < 3):
print("Usage: " + sys.argv[0] +
" <training file> <out file> <n_iter = " + str(n_iter) +
"> <reg = " + str(reg) + ">")
return -1
elif (argc > 3):
n_iter = int(sys.argv[3])
if (argc > 4):
reg = float(sys.argv[4])
ifile = sys.argv[1]
ofile = sys.argv[2]
[n_local, n_global, global_features, local_features,
gold_vec] = read_training_file(ifile)
if (local_features == None):
return -2
n_features = n_local + n_global
print(
str(n_local) + ", " + str(n_global) + ", " +
str(len(global_features)) + ", " + str(len(local_features)) + ", " +
str(len(local_features[0])))
weights = [random.uniform(-1, 1) for i in range(n_features)]
#weights = [1 for i in range(n_features)]
print len(global_features.values())
for i in range(n_iter):
[loss,
weights] = run_iteration(n_features, local_features, global_features,
n_global, n_local, weights, gold_vec, reg)
print str(i) + ": " + str(loss)
with FileTools.openWriteFile(ofile) as ofh:
for i in range(n_features):
ofh.write(str(weights[i]) + "\n")
return 0
def __init__(self, args, savepath, filei, centers):
self.args = args
self.energy = self.args.e
self.file = filei[0]
self.savepath = savepath
self.ft = FileTools.FileTools(args)
rit = RunInfoTools.RunInfoTools(args, savepath, filei)
self.ampbias = rit.ampbias
self.xtal = rit.xtal
self.x_center, self.y_center = centers[0], centers[1]
self.Aeff = rit.Aeff
# These lines annoyingly needed to make fitResult work :(
gSystem.Load("/afs/cern.ch/user/m/mplesser/H4Analysis/CfgManager/lib/libCFGMan.so")
gSystem.Load("/afs/cern.ch/user/m/mplesser/H4Analysis/lib/libH4Analysis.so")
gSystem.Load("/afs/cern.ch/user/m/mplesser/H4Analysis/DynamicTTree/lib/libDTT.so")
def read_training_file(self, train_file, n_training_samples=-1):
pos_map = {}
gold_vec = []
with FileTools.openReadFile(train_file) as ifile:
info = ifile.readline().rstrip()
e = info.split(" ")
n_pos_tags = int(e[0])
n_features = int(e[1])
features = []
sums = []
# ignore next line
line = ifile.readline()
s = {}
# print n_pos_tags,n_features
if (self.read_features(s, 1, ifile) == 0):
return [None,None]
pos_map = dict([(w,int(s[w][0])-1) for w in s])
line = ifile.readline()
if (len(line) == 0):
return None
n_sent = 0
while (len(line) > 0):
# print str(n_sent)+": "+line
if (line[0] != '#'):
print "Expecting comment in line "+line
return None
e = line.rstrip().split(" ")
gold = e[-1]
n_sent = n_sent + 1
local_sent_features = {}
if (self.read_features(local_sent_features, n_features, ifile) == 0):
return [None,None]
if (gold in pos_map):
gold_vec.append(gold)
arr = self.gen_local_pos_features(local_sent_features, pos_map, n_pos_tags, gold)
features.append(arr[0])
sums.append(arr[1])
line = ifile.readline()
# break
# if n_sent == 3:
# break
if (n_training_samples > 0 and n_sent == n_training_samples):
break
if (n_sent %10 == 0):
print str(n_sent)+" \r",
sys.stdout.flush()
#print "\n"+str(n_sent)+" "+line
self.n_features = n_features
self.n_pos_tags = n_pos_tags
self.pos_map = pos_map
self.gold_vec = gold_vec
self.features = features
self.sums = sums
return
DOSSIERACQUIS = "/home/nicolas/Acquisitions/Topi_pollen_600U/"
DATA = True # True for data preprocessing, False for white image processing
M = manip.Manip(DOSSIERACQUIS, DATA)
if DATA is True:
DOSSIERDATA = M.dossier_data
else:
DOSSIERDATA = M.dossier_blanc
# Creating results Folders
PROCESSINGFOLDER = f"{DOSSIERDATA}Reconstruction"
if not os.path.exists(PROCESSINGFOLDER):
os.makedirs(PROCESSINGFOLDER)
# Path to the parameter file, and parameters reading
CHEMINPARAM = f"{DOSSIERDATA}Pretraitement/Param.txt"
REWALD = float(ft.readvalue(CHEMINPARAM, 'REwald'))
NB_ANGLE = int(ft.readvalue(CHEMINPARAM, 'nb_angle'))
FMAXHOLO = int(ft.readvalue(CHEMINPARAM, 'fmaxHolo'))
DIMHOLO = int(ft.readvalue(CHEMINPARAM, 'dimHolo'))
PIXTHEO = float(ft.readvalue(CHEMINPARAM, 'pixTheo'))
UBornPitch = 1 / (2 * FMAXHOLO * PIXTHEO)
NB_HOLO = NB_ANGLE
# Filter Radii
GreenRadius = 60
RedRadius = 80
# Rounding tomographic volume dimensions to the next power of 2
pow2 = ft.NextPow2(2 * DIMHOLO)
DIMTOMO = 2**pow2
DOSSIERACQUIS = "/home/nicolas/Acquisitions/Topi_pollen_600S/"
DATA = True # True for data preprocessing, False for white image processing
M = manip.Manip(DOSSIERACQUIS, DATA)
if DATA is True:
DOSSIERDATA = M.dossier_data
else:
DOSSIERDATA = M.dossier_blanc
# Creating results Folders
PROCESSINGFOLDER = f"{DOSSIERDATA}Reconstruction"
if not os.path.exists(PROCESSINGFOLDER):
os.makedirs(PROCESSINGFOLDER)
# Path to the parameter file, and parameters reading
CHEMINPARAM = f"{DOSSIERDATA}Pretraitement/Param.txt"
REWALD = float(ft.readvalue(CHEMINPARAM, 'REwald'))
NB_ANGLE = int(ft.readvalue(CHEMINPARAM, 'nb_angle'))
FMAXHOLO = int(ft.readvalue(CHEMINPARAM, 'fmaxHolo'))
DIMHOLO = int(ft.readvalue(CHEMINPARAM, 'dimHolo'))
PIXTHEO = float(ft.readvalue(CHEMINPARAM, 'pixTheo'))
UBornPitch = 1 / (2 * FMAXHOLO * PIXTHEO)
NB_HOLO = NB_ANGLE
# Paths to the real, and imaginary parts of the field
CHEMIN_RE_UBORN = f"{DOSSIERDATA}Pretraitement/ReBorn_{DIMHOLO}.tiff"
CHEMIN_IM_UBORN = f"{DOSSIERDATA}Pretraitement/ImBorn_{DIMHOLO}.tiff"
# Paths to the saved cuts
CHEMINSAV_XY = f"{PROCESSINGFOLDER}/XY_CUT.tiff"
CHEMINSAV_YZ = f"{PROCESSINGFOLDER}/YZ_CUT.tiff"
CHEMINSAVOTF_XY = f"{PROCESSINGFOLDER}/XY_CUT_OTF.tiff"
DOSSIERACQUIS = "/home/nicolas/Acquisitions/Topi_pollen_600U/"
DATA = True # True for data preprocessing, False for white image processing
M = manip.Manip(DOSSIERACQUIS, DATA)
if DATA is True:
DOSSIERDATA = M.dossier_data
else:
DOSSIERDATA = M.dossier_blanc
# Creating results Folders
PROCESSINGFOLDER = f"{DOSSIERDATA}Reconstruction"
if not os.path.exists(PROCESSINGFOLDER):
os.makedirs(PROCESSINGFOLDER)
# Path to the parameter file, and parameters reading
CHEMINPARAM = f"{DOSSIERDATA}Pretraitement/Param.txt"
REWALD = float(ft.readvalue(CHEMINPARAM, 'REwald'))
NB_ANGLE = int(ft.readvalue(CHEMINPARAM, 'nb_angle'))
FMAXHOLO = int(ft.readvalue(CHEMINPARAM, 'fmaxHolo'))
DIMHOLO = int(ft.readvalue(CHEMINPARAM, 'dimHolo'))
PIXTHEO = float(ft.readvalue(CHEMINPARAM, 'pixTheo'))
UBornPitch = 1 / (2 * FMAXHOLO * PIXTHEO)
NB_HOLO = NB_ANGLE
# Paths to the real, and imaginary parts of the field
CHEMIN_RE_UBORN = f"{DOSSIERDATA}Pretraitement/ReBorn_{DIMHOLO}.tiff"
CHEMIN_IM_UBORN = f"{DOSSIERDATA}Pretraitement/ImBorn_{DIMHOLO}.tiff"
# Path to the specular coordinates
SpecCoordPath = f"{DOSSIERDATA}Pretraitement/Centres_{DIMHOLO}.txt"
fi = rp.Calc_fi(SpecCoordPath, NB_ANGLE, DIMHOLO)
maxRa = np.max(ra)
minDec = np.min(dec)
maxDec = np.max(dec)
if (crval[0] < minRa) | (crval[0] > maxRa) | (
crval[1] < minDec) | (crval[1] > maxDec):
print(
'WARNING: MAP CENTRE DOES NOT MATCH TELESCOPE POINTING CENTRE. CHECK COORDINATES'
)
print('MEAN RA: {:.2f}, MEAN DEC: {:.2f}'.format(
np.mean(ra), np.mean(dec)))
wcs = Mapping.DefineWCS(naxis, cdelt, crval)
maps, hits = Mapping.MakeMaps(tod, ra, dec, wcs)
dataout['hits'] = hits
dataout['maps'] = maps
dataout['naxis'] = np.array(naxis)
dataout['cdelt'] = np.array(cdelt)
dataout['crval'] = np.array(crval)
sbStr = ''.join(str(e) for e in sidebands)
hoStr = ''.join(str(e) for e in pixels)
FileTools.WriteH5Py(
'{}/{}_{}_Horns{}_Sidebands{}.h5'.format(
Parameters.get('Inputs', 'outputDir'),
Parameters.get('Inputs', 'outputname'), prefix, hoStr, sbStr),
dataout)
dataout = {} # clear data
dfile.close()
DistSrc = DistName + "_src"
DistDir = "../../DistTemp/"
#====================================================================
# script assumes to run in src/Tools
DistTools.EnsureDir(DistDir)
if (DistTools.EnsureDir(DistDir + DistSrc) == 1):
raise "Dist path already there!!"
#====================================================================
# copy src
sys.stdout.write('Copy src Tree ...\n')
DistTools.EnsureDir(DistDir + DistSrc + '/src')
FileTools.cpallWithFilter('../../src', DistDir + DistSrc + '/src',
FileTools.SetUpFilter(DistTools.SrcFilter))
#====================================================================
# copy top level files
#FileTools.cpfile("../Doc/README.html",DistDir+DistBin+"/README.html")
#FileTools.cpfile("../Doc/INSTALL.html",DistDir+DistBin+"/INSTALL.html")
#FileTools.cpfile("../Doc/LICENSE.GPL.html",DistDir+DistBin+"/LICENSE.GPL.html")
#FileTools.cpfile("../Doc/LICENSE.LGPL.html",DistDir+DistBin+"/LICENSE.LGPL.html")
#DistTools.cpfile("../Tools/BuildTool.py",DistDir+DistBin+"/BuildTool.py")
#====================================================================
# zipping an archive
os.popen("7z a -tzip " + DistDir + DistSrc + ".zip " + DistDir + DistSrc +
" -mx9")
# shell and operating system
import os,sys
#sys.path.append( "E:\\Develop\\Projekte\\FreeCADWin\\src\\Tools" )
import DistTools,FileTools
# line seperator
ls = os.linesep
# path seperator
ps = os.pathsep
# dir seperator
ds = os.sep
DistName = DistTools.BuildDistName()
DistInst = DistName + "_installer.msi"
DistDir = "../../DistTemp/"
#====================================================================
# copy intaller file
FileTools.cpfile("../../Install/FreeCAD.msi",DistDir+DistInst)
DistSrc = DistName + "_src"
DistDir = "../../DistTemp/"
#====================================================================
# script assumes to run in src/Tools
DistTools.EnsureDir(DistDir)
if (DistTools.EnsureDir(DistDir+DistSrc) == 1):
raise "Dist path already there!!"
#====================================================================
# copy src
sys.stdout.write( 'Copy src Tree ...\n')
DistTools.EnsureDir(DistDir+DistSrc+'/src')
FileTools.cpallWithFilter('../../src',DistDir+DistSrc+'/src',FileTools.SetUpFilter(DistTools.SrcFilter))
#====================================================================
# copy top level files
#FileTools.cpfile("../Doc/README.html",DistDir+DistBin+"/README.html")
#FileTools.cpfile("../Doc/INSTALL.html",DistDir+DistBin+"/INSTALL.html")
#FileTools.cpfile("../Doc/LICENSE.GPL.html",DistDir+DistBin+"/LICENSE.GPL.html")
#FileTools.cpfile("../Doc/LICENSE.LGPL.html",DistDir+DistBin+"/LICENSE.LGPL.html")
#DistTools.cpfile("../Tools/BuildTool.py",DistDir+DistBin+"/BuildTool.py")
#====================================================================
# zipping an archive
os.popen("7z a -tzip "+ DistDir+DistSrc+".zip "+ DistDir+DistSrc + " -mx9")
FileTools.rmall(DistDir+DistSrc)
if not os.path.exists(PROCESSINGFOLDER):
os.makedirs(PROCESSINGFOLDER)
# Choosing method
Method = {
0: "BASE",
1: "DARKFIELD",
2: "PHASECONTRAST",
3: "RHEINBERG",
4: "DIC"
}
MethodUsed = Method[2]
# Path to the parameter file, and parameters reading
CHEMINPARAM = f"{DOSSIERDATA}Pretraitement/Param.txt"
REWALD = float(ft.readvalue(CHEMINPARAM, 'REwald'))
NB_ANGLE = int(ft.readvalue(CHEMINPARAM, 'nb_angle'))
FMAXHOLO = int(ft.readvalue(CHEMINPARAM, 'fmaxHolo'))
DIMHOLO = int(ft.readvalue(CHEMINPARAM, 'dimHolo'))
PIXTHEO = float(ft.readvalue(CHEMINPARAM, 'pixTheo'))
UBornPitch = 1 / (2 * FMAXHOLO * PIXTHEO)
NB_HOLO = NB_ANGLE
# Path to the specular coordinates
SpecCoordPath = f"{DOSSIERDATA}Pretraitement/Centres_{DIMHOLO}.txt"
fi = rp.Calc_fi(SpecCoordPath, NB_ANGLE, DIMHOLO)
# Paths to the real, and imaginary parts of the field
CHEMIN_RE_UBORN = f"{DOSSIERDATA}Pretraitement/ReBorn_{DIMHOLO}.tiff"
CHEMIN_IM_UBORN = f"{DOSSIERDATA}Pretraitement/ImBorn_{DIMHOLO}.tiff"
import settings
import sys
import DBTools
arg = sys.argv
if len(arg) < 2:
print("Please use : ", arg[0], " [directory]")
exit()
elif not os.path.isdir(arg[1]):
print(arg[1], " is not a directory")
exit()
startDir = arg[1]
result = FileTools.searchFile(startDir)
dbTools = DBTools.DBTools()
if settings.display != "none" and settings.display != "error":
print(str(len(result)) + " music file find")
i = 0
for track in result:
i += 1
if settings.display != "none" and settings.display != "error":
print("file ", end='')
print(i, end='/')
PlotDir = Config.get('Inputs','PlotDir')
DataFile = Config.get('Inputs','DataFile')
if 'none'.lower() in PlotDir.lower():
PlotDir = None
todjd0 = TimeString2JD(Config.get('Observation','todstart')) + float(Config.get('TimeCorrections', 'additiveFactor') )
nside = Config.getint('Inputs', 'nside')
bl = Config.getint('Inputs', 'baseline')
blong = Config.getint('Inputs', 'blong')
npix = 12*nside**2
# Read in the TOD, integrate over all SB0
if os.path.isfile('{}/{}'.format(Config.get('Inputs', 'datadir'),Config.get('Inputs', 'compressedtod'))):
tod = FileTools.ReadH5Py('{}/{}'.format(Config.get('Inputs', 'datadir'),Config.get('Inputs', 'compressedtod')))['auto_py']
todjd = np.arange(tod.size)/Config.getfloat('Observation', 'todsr') / 3600./ 24. * (1. - float(Config.get('TimeCorrections', 'multiFactor')) ) + todjd0
else:
todfile = h5py.File('{}/{}'.format(Config.get('Inputs', 'datadir'), Config.get('Inputs', 'todfile')))
tod = np.mean(todfile['auto_py'][:,0,:],axis=1)
todfile.close()
FileTools.WriteH5Py('{}/{}'.format(Config.get('Inputs', 'datadir'),Config.get('Inputs', 'compressedtod')),
{'auto_py': tod})
# Check for nans in TOD and normalise
tod[np.isnan(tod)] = 0.
tod = (tod - np.mean(tod))/np.std(tod)
# Read in encoder data
# shell and operating system
import os,sys
#sys.path.append( "E:\\Develop\\Projekte\\FreeCADWin\\src\\Tools" )
import DistTools,FileTools
# line seperator
ls = os.linesep
# path seperator
ps = os.pathsep
# dir seperator
ds = os.sep
DistName = DistTools.BuildDistName()
DistInst = DistName + "_installer.msi"
DistDir = "../../DistTemp/"
#====================================================================
# copy intaller file
FileTools.cpfile("../../Install/FreeCAD.msi",DistDir+DistInst)
tagg.sub_aggs.append(tagg1)
qsearch = pyes.query.Search(q)
qsearch.agg.add(tagg)
rs = conn.search(query=qsearch, indices='example_index', type="example_type")
print json.dumps(rs.aggs, indent=2)
formatTranslator = FormatTranslator.FormatTranslator()
result = formatTranslator.ES_Aggs_2_Layer_to_Matrix_and_indice(
rs.aggs, "user_id", "name")
print result['rowIndexList']
print result['colIndexList']
print result['matrix']
fileTools = FileTools.FileTools()
fileTools.List_to_CSV(result['colIndexList'], "col_index.csv")
fileTools.Matrix_to_CSV(result['matrix'], "matrix.csv")
'''------------------------------------------- Agg to csv -------------------------------------------'''
conn = pyes.es.ES('localhost:9200')
q = pyes.MatchAllQuery()
tagg = pyes.aggs.TermsAgg('name', field='name', sub_aggs=[])
qsearch = pyes.query.Search(q)
qsearch.agg.add(tagg)
rs = conn.search(query=qsearch, indices='example_index', type="example_type")
print json.dumps(rs.aggs, indent=2)
fileTools = FileTools.FileTools()
fileTools.ES_Aggs_1_Layer_to_CSV(rs.aggs, "agg.csv", agg_name="name")
from scipy.fftpack import fftn, ifftn, fftshift
import Retropropagation as rp
NA_ill = 1.4
nimm = 1.518
nbead = 1.55
nbangle = 50
kappa = 0.01
Radius = 20
DOSSIERDATA = "/home/nicolas/Simulations/"
CHEMINPARAM = f"{DOSSIERDATA}Param.txt"
# Path to the parameter file, and parameters reading
DARKFIELD = False
PHASECONTRAST = False
REWALD = float(ft.readvalue(CHEMINPARAM, 'REwald'))
NB_ANGLE = int(ft.readvalue(CHEMINPARAM, 'nb_angle'))
FMAXHOLO = int(ft.readvalue(CHEMINPARAM, 'fmaxHolo'))
DIMHOLO = int(ft.readvalue(CHEMINPARAM, 'dimHolo'))
PIXTHEO = float(ft.readvalue(CHEMINPARAM, 'pixTheo'))
UBornPitch = 1 / (2 * FMAXHOLO * PIXTHEO)
NB_HOLO = NB_ANGLE
# Paths to the real, and imaginary parts of the field
CHEMIN_RE_UBORN = f"{DOSSIERDATA}ReBorn_{DIMHOLO}.tiff"
CHEMIN_IM_UBORN = f"{DOSSIERDATA}ImBorn_{DIMHOLO}.tiff"
# Path to the specular coordinates
SpecCoordPath = f"{DOSSIERDATA}/Centres_{DIMHOLO}.txt"
fi = rp.Calc_fi(SpecCoordPath, NB_ANGLE, DIMHOLO)
import Retropropagation as rp
import manip
import napari
# Path to the parameter file, and parameters reading
# Data folders and config files
if os.name == 'nt': # Windows
DOSSIERACQUIS = "C:/Users/p1600109/Documents/Recherche/Acquisitions/Topi_pollen_600S/"
else: # Linux
DOSSIERACQUIS = "/home/nicolas/Acquisitions/Topi_pollen_600S/"
DATA = True # True for data preprocessing, False for white image processing
M = manip.Manip(DOSSIERACQUIS, DATA)
DOSSIERDATA = M.dossier_data
PROCESSINGFOLDER = f"{DOSSIERDATA}Reconstruction"
CHEMINPARAM = f"{DOSSIERDATA}Pretraitement/Param.txt"
DIMHOLO = int(ft.readvalue(CHEMINPARAM, 'dimHolo'))
PIXTHEO = float(ft.readvalue(CHEMINPARAM, 'pixTheo'))
# Creation of results folder
GERCHBERGFOLDER = M.dossier_gerchberg
if not os.path.exists(GERCHBERGFOLDER):
os.makedirs(GERCHBERGFOLDER)
# Rounding tomographic volume dimensions to the next power of 2
pow2 = ft.NextPow2(2 * DIMHOLO)
DIMTOMO = 2**pow2
# Paths to the refraction, and absorption of the object
CHEMINABSORP = f"{PROCESSINGFOLDER}/Absorption_{DIMTOMO}x{DIMTOMO}x{DIMTOMO}.tiff"
CHEMINREFRAC = f"{PROCESSINGFOLDER}/Refraction_{DIMTOMO}x{DIMTOMO}x{DIMTOMO}.tiff"
CHEMINOTF = f"{PROCESSINGFOLDER}/OTF_{DIMTOMO}x{DIMTOMO}x{DIMTOMO}.tiff"
#FileTools.cpfile("FreeCAD.css","../../doc/res/FreeCAD.css")
#====================================================================
sys.stdout.write('Running source documentation ...')
# running doxygen with the parameters from the config file
param = "doxygen fcbt" + ds + "BuildDocDoxy.cfg"
LogFile.write(param)
print param
text = os.popen(param).read()
LogFile.write(text)
if not os.path.isdir("../../doc/SourceDocumentation"):
os.mkdir("../../doc/SourceDocumentation")
#====================================================================
sys.stdout.write(' done\n Generate HTML ...')
FileTools.cpall("html", "../../doc/SourceDocumentation")
"""
#====================================================================
sys.stdout.write(' done\n Generate DVI ...')
os.chdir("latex")
text = os.popen("latex refman.tex").read()
LogFile.write(text)
text = os.popen("makeindex refman.idx").read()
LogFile.write(text)
text = os.popen("latex refman.tex").read()
text = os.popen("latex refman.tex").read()
text = os.popen("latex refman.tex").read()
FileTools.cpfile("refman.dvi","../../../doc/FrameWork/FrameWork.dvi")
#====================================================================
sys.stdout.write (' done\n Generate PS ...')
CPT += 1
if "RHEINBERG" == MethodUsed:
StackRGB[:,:,int((Z+1200)/80),0] = SumHoloR
StackRGB[:,:,int((Z+1200)/80),1] = SumHoloG
StackRGB[:,:,int((Z+1200)/80),2] = SumHoloB
else :
Stack[:,:,int((Z+1200)/80)] = SumHolo
CPTSUM += 1
print(f"Slice {CPTSUM} out of {Stack.shape[2]}")
print(f"Pre-Processing time for {CPTSUM} Slices: "
f"{np.round(time.time() - start_time,decimals=2)} seconds")
if "RHEINBERG" == MethodUsed:
ft.SAVtiffRGBCube(f"{PROCESSINGFOLDER}/{MethodUsed}_{2*dimHolo}x{2*dimHolo}x{StackRGB.shape[2]}.tiff",
StackRGB, 2*M.PIX*1e6)
else:
ft.SAVtiffCube(f"{PROCESSINGFOLDER}/{MethodUsed}_{2*dimHolo}x{2*dimHolo}x{Stack.shape[2]}.tiff",
Stack, 2*M.PIX*1e6)
# Center recording and file closing
fidParams.write(f"nb_angle {CPT_EXIST-1}\n")
fidParams.write(f"fmaxHolo {fmaxHolo}\n")
fidParams.write(f"dimHolo {dimHolo}\n")
fidParams.write(f"pixTheo {M.PIX/Gtot}\n")
tf.imwrite(CHEMINSAV_CENTRES, np.float32(np.int32(Centres)))
fidCentrestxt.close()
fidParams.close()
DistBin = DistName + "_binary_WinX86"
DistDir = "../../DistTemp/"
#====================================================================
# script assumes to run in src/Tools
DistTools.EnsureDir(DistDir)
if (DistTools.EnsureDir(DistDir+DistBin) == 1):
raise "Dist path already there!!"
#====================================================================
# copy src
sys.stdout.write( 'Copy src Tree ...\n')
DistTools.EnsureDir(DistDir+DistBin+'/src')
FileTools.cpallWithFilter('../../src',DistDir+DistBin+'/src',FileTools.SetUpFilter(DistTools.SrcFilter))
#====================================================================
# copy bin and lib
sys.stdout.write( 'Copy bin and lib Tree ...\n')
DistTools.EnsureDir(DistDir+DistBin+'/bin')
FileTools.cpallWithFilter('../../bin',DistDir+DistBin+'/bin',FileTools.SetUpFilter(DistTools.BinFilter))
DistTools.EnsureDir(DistDir+DistBin+'/lib')
FileTools.cpallWithFilter('../../lib',DistDir+DistBin+'/lib',FileTools.SetUpFilter(DistTools.LibFilter))
#====================================================================
# copy Modules
sys.stdout.write( 'Copy modul Tree ...\n')
DistTools.EnsureDir(DistDir+DistBin+'/Mod')
FileTools.cpallWithFilter('../../src/Mod',DistDir+DistBin+'/Mod',FileTools.SetUpFilter(DistTools.ModFilter))
popt,pcov = scipy.optimize.curve_fit(spt.generateEPSP,cirf_time,
cirf_raw,p)
cirf_fit = spt.generateEPSP(cirf_time,popt[0],popt[1],popt[2],popt[3])
leg3, = plt.plot(cirf_time,cirf_fit,'--',label = 'Least-squares fit')
plt.legend(handles = [leg1, leg2, leg3], fontsize = 18)
plt.xlabel('Time (s)', fontsize = 20)
plt.ylabel('Normalized amplitude', fontsize = 20)
plt.title('CIRF for regression', fontsize = 22)
plt.box('off')
plt.tick_params(labelsize = 14)
print('Parameters \n' + str(popt))
#%% Load ephys data
import FileTools as ft
pyDir = r'S:\Avinash\SPIM\Alx\8-9-2015_Alx RG x 939_4dpf\Ephys\Fish2'
pyFileName = ft.findAndSortFilesInDir(pyDir,ext = 'mat')[-1]
pyData_disk = h5py.File(os.path.join(pyDir,pyFileName))['data']
pyData = {}
pyData['stim'],pyData['swim'] = {},{}
pyData['stim']['amps'] = pyData_disk['stim']['amps'][:]
pyData['stim']['inds'] = pyData_disk['stim']['inds'][:].astype(int)
pyData['swim']['startInds'] = pyData_disk['swim']['startInds'][:].astype(int)
pyData['swim']['distFromLastStim'] = pyData_disk['swim']['distFromLastStim'][:]
pyData['time'] = pyData_disk['t'][:]
pyData['smooth'] = np.transpose(pyData_disk['smooth']['burst'][:])
pyData['samplingRate'] = np.int(1/(pyData['time'][1]-pyData['time'][0]))
