def SetSource (self,source_name=None,source_obj=None):
"""
Sets a new source for data retrieving, an specfile.
If the file exists, self.Source will be the Specfile
object associated to this file.
Parameters:
source_name: name of the specfile
"""
if source_name==self.SourceName: return 1
if source_name is not None:
if source_obj is not None:
self.Source= source_obj
else:
try:
self.Source= specfile.Specfile(source_name)
except:
self.Source= None
else:
self.Source= None
self.SourceInfo= None
if self.Source is None:
self.SourceName= None
return 0
else:
self.SourceName= source_name
return 1
def refresh(self):
self._sourceObjectList=[]
self.__fileHeaderList = []
for name in self.__sourceNameList:
if not os.path.exists(name):
raise ValueError("File %s does not exists" % name)
for name in self.__sourceNameList:
self._sourceObjectList.append(specfile.Specfile(name))
self.__fileHeaderList.append(False)
self.__lastKeyInfo = {}
def __init__(self, filename):
DataObject.DataObject.__init__(self)
sf = specfile.Specfile(filename)
scan = sf[1]
data = scan.data()
nMca, nchannels = data.shape
nMca = nMca - 1
xValues = data[0, :] * 1
xValues.shape = -1
if 0:
self.data = numpy.zeros((nMca, nchannels), numpy.float32)
self.data[:, :] = data[1:, :]
self.data.shape = 1, nMca, nchannels
else:
self.data = data[1:, :]
self.data.shape = 1, nMca, nchannels
data = None
#perform a least squares adjustment to a line
x = numpy.arange(nchannels).astype(numpy.float32)
Sxy = numpy.dot(x, xValues.T)
Sxx = numpy.dot(x, x.T)
Sx = x.sum()
Sy = xValues.sum()
d = nchannels * Sxx - Sx * Sx
zero = (Sxx * Sy - Sx * Sxy) / d
gain = (nchannels * Sxy - Sx * Sy) / d
#and fill the requested information to be identified as a stack
self.info['SourceName'] = [filename]
self.info["SourceType"] = "SpecFileStack"
self.info["Size"] = 1, nMca, nchannels
self.info["NumberOfFiles"] = 1
self.info["FileIndex"] = 0
self.info["McaCalib"] = [zero, gain, 0.0]
self.info["Channel0"] = 0.0
def get_scan(self, scannumber):
spec = specfilewrapper.Specfile(self.config.specfile)
return spec.select('{0}.1'.format(scannumber))
print("VICTOREEN")
plot(energy, spectrum, 'o')
plot(xPre, pre_edge_function(prePol, xPre), 'r')
plot(xPost,
post_edge_function(postPol, xPost)+pre_edge_function(prePol, xPost), 'y')
show()
return energy, normalizedSpectrum, edge
SUPPORTED_ALGORITHMS = {"polynomial":XASPolynomialNormalization,
"victoreen": XASVictoreenNormalization}
if __name__ == "__main__":
import sys
from PyMca import specfilewrapper as specfile
import time
sf = specfile.Specfile(sys.argv[1])
scan = sf[0]
data = scan.data()
energy = data[0, :]
spectrum = data[1, :]
n = 100
t0 = time.time()
for i in range(n):
edge = estimateXANESEdge(spectrum+i, energy=energy)
print("EDGE ELAPSED = ", (time.time() - t0)/float(n))
print("EDGE = %f" % edge)
if DEBUG:
n = 1
else:
n = 100
t0 = time.time()
def loadFileList(self, filelist, fileindex=0, shape=None):
if type(filelist) == type(''):
filelist = [filelist]
self.__keyList = []
self.sourceName = filelist
self.__indexedStack = True
self.sourceType = SOURCE_TYPE
self.info = {}
self.nbFiles = len(filelist)
#read first file
#get information
tempInstance = SpecFileDataSource.SpecFileDataSource(filelist[0])
keylist = tempInstance.getSourceInfo()['KeyList']
nscans = len(keylist) #that is the number of scans
nmca = 0
numberofdetectors = 0
for key in keylist:
info = tempInstance.getKeyInfo(key)
numberofmca = info['NbMca']
if numberofmca > 0:
numberofdetectors = info['NbMcaDet']
scantype = info["ScanType"]
if numberofmca:
nmca += numberofmca
if numberofdetectors == 0:
raise ValueError("No MCA found in file %s" % filelist[0])
if (nscans > 1) and ((nmca / numberofdetectors) == nscans):
SLOW_METHOD = True
else:
SLOW_METHOD = False
#get last mca of first point
key = "%s.1.%s" % (keylist[-1], numberofmca)
dataObject = tempInstance._getMcaData(key)
self.info.update(dataObject.info)
arrRet = dataObject.data
self.onBegin(self.nbFiles * nmca / numberofdetectors)
self.incrProgressBar = 0
if info['NbMcaDet'] > 1:
#Should I generate a map for each mca and not just for the last one as I am doing?
iterlist = range(info['NbMcaDet'], info['NbMca'] + 1,
info['NbMcaDet'])
else:
iterlist = [1]
if SLOW_METHOD and shape is None:
self.data = numpy.zeros(
(self.nbFiles, nmca / numberofdetectors, arrRet.shape[0]),
arrRet.dtype.char)
filecounter = 0
for tempFileName in filelist:
tempInstance = SpecFileDataSource.SpecFileDataSource(
tempFileName)
mca_number = -1
for keyindex in keylist:
info = tempInstance.getKeyInfo(keyindex)
numberofmca = info['NbMca']
if numberofmca <= 0:
continue
key = "%s.1.%s" % (keyindex, numberofmca)
dataObject = tempInstance._getMcaData(key)
arrRet = dataObject.data
mca_number += 1
for i in iterlist:
#mcadata = scan_obj.mca(i)
self.data[filecounter, mca_number, :] = arrRet[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
filecounter += 1
elif shape is None and (self.nbFiles == 1) and (iterlist == [1]):
#it can only be here if there is one file
#it can only be here if there is only one scan
#it can only be here if there is only one detector
self.data = numpy.zeros((1, numberofmca, arrRet.shape[0]),
arrRet.dtype.char)
for tempFileName in filelist:
tempInstance = specfile.Specfile(tempFileName)
#it can only be here if there is one scan per file
#prevent problems if the scan number is different
#scan = tempInstance.select(keylist[-1])
scan = tempInstance[-1]
iterationList = range(scan.nbmca())
for i in iterationList:
#mcadata = scan_obj.mca(i)
self.data[0, i, :] = scan.mca(i + 1)[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
filecounter = 1
elif shape is None:
#it can only be here if there is one scan per file
try:
self.data = numpy.zeros(
(self.nbFiles, numberofmca / numberofdetectors,
arrRet.shape[0]), arrRet.dtype.char)
filecounter = 0
for tempFileName in filelist:
tempInstance = specfile.Specfile(tempFileName)
#it can only be here if there is one scan per file
#prevent problems if the scan number is different
#scan = tempInstance.select(keylist[-1])
scan = tempInstance[-1]
for i in iterlist:
#mcadata = scan_obj.mca(i)
self.data[filecounter, 0, :] = scan.mca(i)[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
filecounter += 1
except MemoryError:
qtflag = False
if ('PyQt4.QtCore' in sys.modules) or\
('PyMcaQt' in sys.modules) or\
('PyMca.PyMcaQt' in sys.modules):
qtflag = True
hdf5done = False
if HDF5 and qtflag:
import PyMcaQt as qt
import ArraySave
msg = qt.QMessageBox.information(
None, "Memory error\n",
"Do you want to convert your data to HDF5?\n",
qt.QMessageBox.Yes, qt.QMessageBox.No)
if msg != qt.QMessageBox.No:
hdf5file = qt.QFileDialog.getSaveFileName(
None, "Please select output file name",
os.path.dirname(filelist[0]), "HDF5 files *.h5")
if not len(hdf5file):
raise IOError("Invalid output file")
hdf5file = qt.safe_str(hdf5file)
if not hdf5file.endswith(".h5"):
hdf5file += ".h5"
#get the final shape
from PyMca.RGBCorrelatorWidget import ImageShapeDialog
stackImageShape = self.nbFiles,\
int(numberofmca/numberofdetectors)
dialog = ImageShapeDialog(None, shape=stackImageShape)
dialog.setModal(True)
ret = dialog.exec_()
if ret:
stackImageShape = dialog.getImageShape()
dialog.close()
del dialog
hdf, self.data = ArraySave.getHDF5FileInstanceAndBuffer(
hdf5file, (stackImageShape[0], stackImageShape[1],
arrRet.shape[0]),
compression=None,
interpretation="spectrum")
nRow = 0
nCol = 0
for tempFileName in filelist:
tempInstance = specfile.Specfile(tempFileName)
#it can only be here if there is one scan per file
#prevent problems if the scan number is different
#scan = tempInstance.select(keylist[-1])
scan = tempInstance[-1]
nRow = int(self.incrProgressBar /
stackImageShape[1])
nCol = self.incrProgressBar % stackImageShape[1]
for i in iterlist:
#mcadata = scan_obj.mca(i)
self.data[nRow, nCol, :] = scan.mca(i)[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
hdf5done = True
hdf.flush()
self.onEnd()
self.info["SourceType"] = "HDF5Stack1D"
self.info["McaIndex"] = 2
self.info["FileIndex"] = 0
self.info["SourceName"] = [hdf5file]
self.info["NumberOfFiles"] = 1
self.info["Size"] = 1
return
else:
raise
else:
sampling_order = 1
s0 = shape[0]
s1 = shape[1]
MEMORY_ERROR = False
try:
self.data = numpy.zeros((shape[0], shape[1], arrRet.shape[0]),
arrRet.dtype.char)
except MemoryError:
try:
self.data = numpy.zeros(
(shape[0], shape[1], arrRet.shape[0]), numpy.float32)
except MemoryError:
MEMORY_ERROR = True
while MEMORY_ERROR:
try:
for i in range(5):
print("\7")
sampling_order += 1
print("**************************************************")
print(" Memory error!, attempting %dx%d sub-sampling " %\
(sampling_order, sampling_order))
print("**************************************************")
s0 = int(shape[0] / sampling_order)
s1 = int(shape[1] / sampling_order)
#if shape[0] % sampling_order:
# s0 = s0 + 1
#if shape[1] % sampling_order:
# s1 = s1 + 1
self.data = numpy.zeros((s0, s1, arrRet.shape[0]),
numpy.float32)
MEMORY_ERROR = False
except MemoryError:
pass
filecounter = 0
for j in range(s0):
filecounter = (j * sampling_order) * shape[1]
for k in range(s1):
tempFileName = filelist[filecounter]
tempInstance = specfile.Specfile(tempFileName)
if tempInstance is None:
if not os.path.exists(tempFileName):
print("File %s does not exists" % tempFileName)
raise IOError(\
"File %s does not exists" % tempFileName)
scan = tempInstance.select(keylist[-1])
for i in iterlist:
#sum the present mcas
self.data[j, k, :] += scan.mca(i)[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
filecounter += sampling_order
self.nbFiles = s0 * s1
self.onEnd()
"""
# Scan types
# ----------
#SF_EMPTY = 0 # empty scan
#SF_SCAN = 1 # non-empty scan
#SF_MESH = 2 # mesh scan
#SF_MCA = 4 # single mca
#SF_NMCA = 8 # multi mca (more than 1 mca per acq)
case = None
if scantype == (SpecFileDataSource.SF_MESH + \
SpecFileDataSource.SF_MCA):
# SINGLE MESH + SINGLE MCA
# nfiles = 1
# nscans = 1
# nmca = 1
# there is a danger if it can be considered an indexed file ...
pass
elif scantype == (SpecFileDataSource.SF_MESH + \
SpecFileDataSource.SF_NMCA):
# SINGLE MESH + MULTIPLE MCA
# nfiles = 1
# nscans = 1
# nmca > 1
# there is a danger if it can be considered an indexed file ...
#for the time being I take last mca
pass
elif scantype == (SpecFileDataSource.SF_SCAN+ \
SpecFileDataSource.SF_MCA):
#Assumed scans containing always 1 detector
pass
elif scantype == (SpecFileDataSource.SF_MCA):
#Assumed scans containing always 1 detector
pass
elif scantype == (SpecFileDataSource.SF_SCAN+ \
SpecFileDataSource.SF_NMCA):
#Assumed scans containing the same number of detectors
#for the time being I take last mca
pass
elif scantype == (SpecFileDataSource.SF_NMCA):
#Assumed scans containing the same number of detectors
#for the time being I take last mca
pass
else:
raise ValueError, "Unhandled scan type = %s" % scantype
"""
self.__nFiles = self.nbFiles
self.__nImagesPerFile = 1
shape = self.data.shape
for i in range(len(shape)):
key = 'Dim_%d' % (i + 1, )
self.info[key] = shape[i]
self.info["SourceType"] = SOURCE_TYPE
self.info["SourceName"] = self.sourceName
self.info["Size"] = self.__nFiles * self.__nImagesPerFile
self.info["NumberOfFiles"] = self.__nFiles * 1
self.info["FileIndex"] = fileindex
