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#/*##########################################################################
#
# The PyMca X-Ray Fluorescence Toolkit
#
# Copyright (c) 2004-2018 European Synchrotron Radiation Facility
#
# This file is part of the PyMca X-ray Fluorescence Toolkit developed at
# the ESRF by the Software group.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
#############################################################################*/
__author__ = "V.A. Sole - ESRF Data Analysis"
__contact__ = "sole@esrf.fr"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
import sys
import os
import numpy
import logging
from PyMca5.PyMcaCore import DataObject
from PyMca5.PyMcaIO import specfilewrapper as specfile
from PyMca5.PyMcaCore import SpecFileDataSource
HDF5 = False
try:
import h5py
HDF5 = True
except:
pass
SOURCE_TYPE = "SpecFileStack"
_logger = logging.getLogger(__name__)
X_AXIS = 0
Y_AXIS = 1
Z_AXIS = 2
class SpecFileStack(DataObject.DataObject):
def __init__(self, filelist=None):
DataObject.DataObject.__init__(self)
self.incrProgressBar = 0
self.__keyList = []
if filelist is not None:
if type(filelist) != type([]):
filelist = [filelist]
if len(filelist) == 1:
self.loadIndexedStack(filelist)
else:
self.loadFileList(filelist)
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
if "McaLiveTime" in info:
nTimes = self.nbFiles * (nmca // numberofdetectors)
self.info["McaLiveTime"] = numpy.zeros((nTimes,),
numpy.float32)
if "McaElapsedTime" in info:
nTimes = self.nbFiles * (nmca // numberofdetectors)
self.info["McaElapsedTime"] = numpy.zeros((nTimes,),
numpy.float32)
nTimes = -1
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
# only the last mca is read
key = "%s.1.%s" % (keyindex, numberofmca)
dataObject = tempInstance._getMcaData(key)
arrRet = dataObject.data
mca_number += 1
nTimes += 1
for i in iterlist:
# mcadata = scan_obj.mca(i)
self.data[filecounter,
mca_number,
:] = arrRet[:]
self.incrProgressBar += 1
for timeKey in ["McaElapsedTime", "McaLiveTime"]:
if timeKey in dataObject.info:
self.info[timeKey][nTimes] = \
dataObject.info[timeKey]
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)
# when reading fast we do not read the time information
# therefore we have to remove it from the info
self._cleanupTimeInfo()
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
# when reading fast we do not read the time information
# therefore we have to remove it from the info
self._cleanupTimeInfo()
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 \
('PySide' in sys.modules) or \
('PyMca5.PyMcaGui.PyMcaQt' in sys.modules):
qtflag = True
hdf5done = False
if HDF5 and qtflag:
from PyMca5.PyMcaGui import PyMcaQt as qt
from PyMca5.PyMcaIO 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 PyMca5.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:
# time information not read
self._cleanupTimeInfo()
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
_logger.warning("**************************************************")
_logger.warning(" Memory error!, attempting %dx%d sub-sampling ",
sampling_order, sampling_order)
_logger.warning("**************************************************")
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):
_logger.error("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
def _cleanupTimeInfo(self):
for timeKey in ["McaElapsedTime", "McaLiveTime"]:
if timeKey in self.info:
del self.info[timeKey]
def onBegin(self, n):
pass
def onProgress(self, n):
pass
def onEnd(self):
pass
def loadIndexedStack(self,filename, begin=None, end=None,
skip = None, fileindex=0):
#if begin is None: begin = 0
if type(filename) == type([]):
filename = filename[0]
if not os.path.exists(filename):
raise IOError("File %s does not exists" % filename)
name = os.path.basename(filename)
n = len(name)
i = 1
numbers = ['0', '1', '2', '3', '4', '5',
'6', '7', '8', '9']
while (i <= n):
c = name[n - i:n - i + 1]
if c in numbers:
break
i += 1
suffix = name[n - i + 1:]
if len(name) == len(suffix):
# just one file, one should use standard widget
# and not this one.
self.loadFileList(filename, fileindex=fileindex)
else:
nchain = []
while (i <= n):
c = name[n - i:n - i + 1]
if c not in numbers:
break
else:
nchain.append(c)
i += 1
number = ""
nchain.reverse()
for c in nchain:
number += c
fformat = "%" + "0%dd" % len(number)
if (len(number) + len(suffix)) == len(name):
prefix = ""
else:
prefix = name[0:n - i + 1]
prefix = os.path.join(os.path.dirname(filename), prefix)
if not os.path.exists(prefix + number + suffix):
_logger.warning("Internal error in EDFStack")
_logger.warning("file should exist: %s", prefix + number + suffix)
return
i = 0
if begin is None:
begin = 0
testname = prefix + fformat % begin + suffix
while not os.path.exists(prefix + fformat % begin + suffix):
begin += 1
testname = prefix + fformat % begin + suffix
if len(testname) > len(filename):
break
i = begin
else:
i = begin
if not os.path.exists(prefix + fformat % i + suffix):
raise ValueError("Invalid start index file = %s" % \
(prefix + fformat % i + suffix))
f = prefix + fformat % i + suffix
filelist = []
while os.path.exists(f):
filelist.append(f)
i += 1
if end is not None:
if i > end:
break
f = prefix + fformat % i + suffix
self.loadFileList(filelist, fileindex=fileindex)
def getSourceInfo(self):
sourceInfo = {}
sourceInfo["SourceType"] = SOURCE_TYPE
if self.__keyList == []:
for i in range(1, self.__nFiles + 1):
for j in range(1, self.__nImages + 1):
self.__keyList.append("%d.%d" % (i, j))
sourceInfo["KeyList"] = self.__keyList
def getKeyInfo(self, key):
_logger.info("Not implemented")
return {}
def isIndexedStack(self):
return self.__indexedStack
def getZSelectionArray(self, z=0):
return (self.data[:, :, z]).astype(numpy.float)
def getXYSelectionArray(self, coord=(0, 0)):
x, y = coord
return (self.data[y, x, :]).astype(numpy.float)
if __name__ == "__main__":
stack = SpecFileStack()
if len(sys.argv) > 1:
stack.loadIndexedStack(sys.argv[1])
else:
print("Usage: python SpecFileStack.py indexed_file")
|
