text += "<tr>"
text += '<td align="left" bgcolor="%s">' % finalcolor
text += "<b><font size=3>%s </font></b>" % shell
text += "</td>"
text += '<td align="right" bgcolor="%s">' % finalcolor
text += "<b><font size=3>%.5f </font></b>" % Elements.Element[
ele]['binding'][shell]
text += "</td>"
text += "</tr>"
text += "</table>"
return text
if __name__ == "__main__":
import sys
from PyMca5 import PyMcaQt as qt
app = qt.QApplication(sys.argv)
if len(sys.argv) > 1:
ele = sys.argv[1]
else:
ele = "Fe"
w = qt.QWidget()
l = qt.QVBoxLayout(w)
html = ElementHtml()
text = qt.QTextEdit(w)
text.insertHtml(html.gethtml(ele))
text.setReadOnly(1)
l.addWidget(text)
w.show()
app.exec_()
def loadFileList(self, filelist, fileindex=0):
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 edf file
#get information
tempEdf = EdfFileDataSource.EdfFileDataSource(filelist[0])
keylist = tempEdf.getSourceInfo()['KeyList']
nImages = len(keylist)
dataObject = tempEdf.getDataObject(keylist[0])
self.info.update(dataObject.info)
if len(dataObject.data.shape) == 3:
#this is already a stack
self.data = dataObject.data
self.__nFiles = 1
self.__nImagesPerFile = nImages
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"] = filelist[0]
self.info["Size"] = 1
self.info["NumberOfFiles"] = 1
self.info["FileIndex"] = fileindex
return
arrRet = dataObject.data
if self.__dtype is None:
self.__dtype = arrRet.dtype
self.onBegin(self.nbFiles)
singleImageShape = arrRet.shape
actualImageStack = False
if (fileindex == 2) or (self.__imageStack):
self.__imageStack = True
if len(singleImageShape) == 1:
#single line
#be ready for specfile stack?
self.onEnd()
raise IOError("Not implemented yet")
self.data = numpy.zeros(
(arrRet.shape[0], nImages, self.nbFiles), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack = tempEdf.GetData(i)
self.data[:, i, self.incrProgressBar] = pieceOfStack[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
if nImages > 1:
#this is not the common case
#should I try to convert it to a standard one
#using a 3D matrix or keep as 4D matrix?
if self.nbFiles > 1:
raise IOError(\
"Multiple files with multiple images implemented yet")
self.data = numpy.zeros((arrRet.shape[0], arrRet.shape[1],
nImages * self.nbFiles),
self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack = tempEdf.GetData(i)
self.data[:,:,
nImages*self.incrProgressBar+i] = \
pieceOfStack[:,:]
self.incrProgressBar += 1
else:
#this is the common case
try:
# calculate needed megabytes
if self.__dtype == numpy.float:
bytefactor = 8
else:
bytefactor = 4
needed_ = self.nbFiles * \
arrRet.shape[0] *\
arrRet.shape[1] * bytefactor
physicalMemory = PhysicalMemory.getPhysicalMemoryOrNone(
)
if physicalMemory is not None:
# spare 5% or memory
if physicalMemory < (1.05 * needed_):
raise MemoryError(
"Not enough physical memory available")
if self.__imageStack:
self.data = numpy.zeros(
(self.nbFiles, arrRet.shape[0],
arrRet.shape[1]), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(
tempEdfFileName, 'rb')
pieceOfStack = tempEdf.GetData(0)
self.data[self.incrProgressBar] = pieceOfStack
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
actualImageStack = True
else:
self.data = numpy.zeros(
(arrRet.shape[0], arrRet.shape[1],
self.nbFiles), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(
tempEdfFileName, 'rb')
pieceOfStack = tempEdf.GetData(0)
self.data[:, :,
self.incrProgressBar] = pieceOfStack
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
except (MemoryError, ValueError):
hdf5done = False
if HDF5 and (('PyMcaQt' in sys.modules) or\
('PyMca.PyMcaQt' in sys.modules)):
from PyMca5 import PyMcaQt as qt
from PyMca5 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"
hdf, self.data = ArraySave.getHDF5FileInstanceAndBuffer(
hdf5file, (self.nbFiles, arrRet.shape[0],
arrRet.shape[1]))
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(
tempEdfFileName, 'rb')
pieceOfStack = tempEdf.GetData(0)
self.data[
self.
incrProgressBar, :, :] = pieceOfStack[:, :]
hdf.flush()
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
hdf5done = True
if not hdf5done:
for i in range(3):
print("\7")
samplingStep = None
i = 2
while samplingStep is None:
print(
"**************************************************"
)
print(
" Memory error!, attempting %dx%d sampling reduction "
) % (i, i)
print(
"**************************************************"
)
s1, s2 = arrRet[::i, ::i].shape
try:
self.data = numpy.zeros(
(s1, s2, self.nbFiles), self.__dtype)
samplingStep = i
except:
i += 1
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(
tempEdfFileName, 'rb')
pieceOfStack = tempEdf.GetData(0)
self.data[:, :, self.
incrProgressBar] = pieceOfStack[::
samplingStep, ::
samplingStep]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
self.__imageStack = False
if len(singleImageShape) == 1:
#single line
#be ready for specfile stack?
raise IOError("Not implemented yet")
self.data = numpy.zeros(
(self.nbFiles, arrRet.shape[0], nImages), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack = tempEdf.GetData(i)
self.data[self.incrProgressBar, :, i] = pieceOfStack[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
if nImages > 1:
#this is not the common case
#should I try to convert it to a standard one
#using a 3D matrix or kepp as 4D matrix?
if self.nbFiles > 1:
if (arrRet.shape[0] > 1) and\
(arrRet.shape[1] > 1):
raise IOError(\
"Multiple files with multiple images not implemented yet")
elif arrRet.shape[0] == 1:
self.data = numpy.zeros(
(self.nbFiles, arrRet.shape[0] * nImages,
arrRet.shape[1]), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(
tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack = tempEdf.GetData(i)
self.data[self.incrProgressBar, i,:] = \
pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
elif arrRet.shape[1] == 1:
self.data = numpy.zeros(
(self.nbFiles, arrRet.shape[1] * nImages,
arrRet.shape[0]), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(
tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack = tempEdf.GetData(i)
self.data[self.incrProgressBar, i,:] = \
pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
else:
self.data = numpy.zeros(
(nImages * self.nbFiles, arrRet.shape[0],
arrRet.shape[1]), self.__dtype)
self.incrProgressBar = 0
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack = tempEdf.GetData(i)
self.data[nImages * self.incrProgressBar +
i, :, :] = pieceOfStack[:, :]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
if fileindex == 1:
try:
self.data = numpy.zeros(
(arrRet.shape[0], self.nbFiles,
arrRet.shape[1]), self.__dtype)
except:
try:
self.data = numpy.zeros(
(arrRet.shape[0], self.nbFiles,
arrRet.shape[1]), numpy.float32)
except:
self.data = numpy.zeros(
(arrRet.shape[0], self.nbFiles,
arrRet.shape[1]), numpy.int16)
else:
try:
# calculate needed megabytes
if self.__dtype == numpy.float:
bytefactor = 8
else:
bytefactor = 4
needed_ = self.nbFiles * \
arrRet.shape[0] *\
arrRet.shape[1] * 4
physicalMemory = PhysicalMemory.getPhysicalMemoryOrNone(
)
if physicalMemory is not None:
# spare 5% of memory
if physicalMemory < (1.05 * needed_):
raise MemoryError(
"Not enough physical memory available")
self.data = numpy.zeros(
(self.nbFiles, arrRet.shape[0],
arrRet.shape[1]), self.__dtype)
except:
try:
needed_ = self.nbFiles * \
arrRet.shape[0] *\
arrRet.shape[1] * 4
physicalMemory = PhysicalMemory.getPhysicalMemoryOrNone(
)
if physicalMemory is not None:
# spare 5 % of memory
if physicalMemory < (1.05 * needed_):
raise MemoryError(
"Not enough physical memory available"
)
self.data = numpy.zeros(
(self.nbFiles, arrRet.shape[0],
arrRet.shape[1]), numpy.float32)
except (MemoryError, ValueError):
text = "Memory Error: Attempt subsampling or convert to HDF5"
if HDF5 and (('PyMcaQt' in sys.modules) or\
('PyMca.PyMcaQt' in sys.modules)):
from PyMca5 import PyMcaQt as qt
from PyMca5 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:
raise MemoryError(text)
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"
hdf, self.data = ArraySave.getHDF5FileInstanceAndBuffer(
hdf5file,
(self.nbFiles, arrRet.shape[0],
arrRet.shape[1]))
else:
raise MemoryError("Memory Error")
self.incrProgressBar = 0
if fileindex == 1:
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(tempEdfFileName, 'rb')
pieceOfStack = tempEdf.GetData(0)
self.data[:, self.
incrProgressBar, :] = pieceOfStack[:, :]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
else:
# test for ID24 map
ID24 = False
if "_sample_" in filelist[0]:
bckFile = filelist[0].replace(
"_sample_", "_samplebk_")
if os.path.exists(bckFile):
bckData = EdfFile.EdfFile(bckFile).GetData(0)
else:
bckData = 0
i0StartFile = filelist[0].replace(
"_sample_", "_I0start_")
if os.path.exists(i0StartFile):
ID24 = True
id24idx = 0
i0Start = EdfFile.EdfFile(
i0StartFile,
'rb').GetData(0).astype(numpy.float)
i0Start -= bckData
i0EndFile = filelist[0].replace(
"_sample_", "_I0end_")
i0Slope = 0.0
if os.path.exists(i0EndFile):
i0End = EdfFile.EdfFile(
i0EndFile, 'rb').GetData(0) - bckData
i0Slope = (i0End - i0Start) / len(filelist)
positionersFile = filelist[0].replace(
"_sample_", "_positioners_")
if os.path.exists(positionersFile):
positionersEdf = EdfFile.EdfFile(
positionersFile, 'rb')
self.info["positioners"] = {}
for i in range(positionersEdf.GetNumImages()):
motorName = positionersEdf.GetHeader(
i).get("Title", "Motor_%02d" % i)
motorValue = positionersEdf.GetData(i)
self.info["positioners"][
motorName] = motorValue
for tempEdfFileName in filelist:
tempEdf = EdfFile.EdfFile(tempEdfFileName, 'rb')
if ID24:
pieceOfStack = -numpy.log(
(tempEdf.GetData(0) - bckData) /
(i0Start[0, :] + id24idx * i0Slope))
pieceOfStack[numpy.isfinite(pieceOfStack) ==
False] = 1
id24idx += 1
else:
pieceOfStack = tempEdf.GetData(0)
try:
self.data[
self.
incrProgressBar, :, :] = pieceOfStack[:, :]
except:
if pieceOfStack.shape[1] != arrRet.shape[1]:
print(" ERROR on file %s" %
tempEdfFileName)
print(
" DIM 1 error Assuming missing data were at the end!!!"
)
if pieceOfStack.shape[0] != arrRet.shape[0]:
print(" ERROR on file %s" %
tempEdfFileName)
print(
" DIM 0 error Assuming missing data were at the end!!!"
)
self.data[self.incrProgressBar,\
:pieceOfStack.shape[0],\
:pieceOfStack.shape[1]] = pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
self.__nFiles = self.incrProgressBar
self.__nImagesPerFile = nImages
shape = self.data.shape
for i in range(len(shape)):
key = 'Dim_%d' % (i + 1, )
self.info[key] = shape[i]
if not isinstance(self.data, numpy.ndarray):
hdf.flush()
self.info["SourceType"] = "HDF5Stack1D"
if self.__imageStack:
self.info["McaIndex"] = 0
self.info["FileIndex"] = 1
else:
self.info["McaIndex"] = 2
self.info["FileIndex"] = 0
self.info["SourceName"] = [hdf5file]
self.info["NumberOfFiles"] = 1
self.info["Size"] = 1
elif actualImageStack:
self.info["SourceType"] = SOURCE_TYPE
self.info["McaIndex"] = 0
self.info["FileIndex"] = 1
self.info["SourceName"] = self.sourceName
self.info["NumberOfFiles"] = self.__nFiles * 1
self.info["Size"] = self.__nFiles * self.__nImagesPerFile
else:
self.info["SourceType"] = SOURCE_TYPE
self.info["FileIndex"] = fileindex
self.info["SourceName"] = self.sourceName
self.info["NumberOfFiles"] = self.__nFiles * 1
self.info["Size"] = self.__nFiles * self.__nImagesPerFile
# try to use positioners to compute the scales (ID24 specific)
xPositionerName = None
yPositionerName = None
if "positioners" in self.info and len(self.info["positioners"]) == 2:
for k, v in self.info["positioners"].items():
if isinstance(v, numpy.ndarray) and v.ndim == 2:
deltaDim1 = v[:, 1:] - v[:, :-1]
deltaDim0 = v[1:, :] - v[:-1, :]
if numpy.any(deltaDim1) and not numpy.any(deltaDim0):
# positioner varying only along dim1
xPositionerName = k
# should we check that all delta values are equal?
deltaX = numpy.mean(deltaDim1)
originX = v[0, 0]
elif numpy.any(deltaDim0) and not numpy.any(deltaDim1):
# positioner varying only along dim0
yPositionerName = k
deltaY = numpy.mean(deltaDim0)
originY = v[0, 0]
if xPositionerName is not None and yPositionerName is not None:
self.info["xScale"] = (originX, deltaX)
self.info["yScale"] = (originY, deltaY)
def loadFileList(self, filelist, fileindex=0):
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 edf file
#get information
tempEdf=EdfFileDataSource.EdfFileDataSource(filelist[0])
keylist = tempEdf.getSourceInfo()['KeyList']
nImages = len(keylist)
dataObject = tempEdf.getDataObject(keylist[0])
self.info.update(dataObject.info)
if len(dataObject.data.shape) == 3:
#this is already a stack
self.data = dataObject.data
self.__nFiles = 1
self.__nImagesPerFile = nImages
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"] = filelist[0]
self.info["Size"] = 1
self.info["NumberOfFiles"] = 1
self.info["FileIndex"] = fileindex
return
arrRet = dataObject.data
if self.__dtype is None:
self.__dtype = arrRet.dtype
self.onBegin(self.nbFiles)
singleImageShape = arrRet.shape
actualImageStack = False
if (fileindex == 2) or (self.__imageStack):
self.__imageStack = True
if len(singleImageShape) == 1:
#single line
#be ready for specfile stack?
self.onEnd()
raise IOError("Not implemented yet")
self.data = numpy.zeros((arrRet.shape[0],
nImages,
self.nbFiles),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack=tempEdf.GetData(i)
self.data[:,i, self.incrProgressBar] = pieceOfStack[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
if nImages > 1:
#this is not the common case
#should I try to convert it to a standard one
#using a 3D matrix or keep as 4D matrix?
if self.nbFiles > 1:
raise IOError(\
"Multiple files with multiple images implemented yet")
self.data = numpy.zeros((arrRet.shape[0],
arrRet.shape[1],
nImages * self.nbFiles),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack=tempEdf.GetData(i)
self.data[:,:,
nImages*self.incrProgressBar+i] = \
pieceOfStack[:,:]
self.incrProgressBar += 1
else:
#this is the common case
try:
# calculate needed megabytes
if self.__dtype == numpy.float:
bytefactor = 8
else:
bytefactor = 4
needed_ = self.nbFiles * \
arrRet.shape[0] *\
arrRet.shape[1] * bytefactor
physicalMemory = PhysicalMemory.getPhysicalMemoryOrNone()
if physicalMemory is not None:
# spare 5% or memory
if physicalMemory < (1.05 * needed_):
raise MemoryError("Not enough physical memory available")
if self.__imageStack:
self.data = numpy.zeros((self.nbFiles,
arrRet.shape[0],
arrRet.shape[1]),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
pieceOfStack=tempEdf.GetData(0)
self.data[self.incrProgressBar] = pieceOfStack
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
actualImageStack = True
else:
self.data = numpy.zeros((arrRet.shape[0],
arrRet.shape[1],
self.nbFiles),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
pieceOfStack=tempEdf.GetData(0)
self.data[:,:, self.incrProgressBar] = pieceOfStack
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
except (MemoryError, ValueError):
hdf5done = False
if HDF5 and (('PyMcaQt' in sys.modules) or\
('PyMca.PyMcaQt' in sys.modules)):
from PyMca5 import PyMcaQt as qt
from PyMca5 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"
hdf, self.data = ArraySave.getHDF5FileInstanceAndBuffer(hdf5file,
(self.nbFiles,
arrRet.shape[0],
arrRet.shape[1]))
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
pieceOfStack=tempEdf.GetData(0)
self.data[self.incrProgressBar,:,:] = pieceOfStack[:,:]
hdf.flush()
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
hdf5done = True
if not hdf5done:
for i in range(3):
print("\7")
samplingStep = None
i = 2
while samplingStep is None:
print("**************************************************")
print(" Memory error!, attempting %dx%d sampling reduction ") % (i,i)
print("**************************************************")
s1, s2 = arrRet[::i, ::i].shape
try:
self.data = numpy.zeros((s1, s2,
self.nbFiles),
self.__dtype)
samplingStep = i
except:
i += 1
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
pieceOfStack=tempEdf.GetData(0)
self.data[:,:, self.incrProgressBar] = pieceOfStack[
::samplingStep,::samplingStep]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
self.__imageStack = False
if len(singleImageShape) == 1:
#single line
#be ready for specfile stack?
raise IOError("Not implemented yet")
self.data = numpy.zeros((self.nbFiles,
arrRet.shape[0],
nImages),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack=tempEdf.GetData(i)
self.data[self.incrProgressBar, :,i] = pieceOfStack[:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
if nImages > 1:
#this is not the common case
#should I try to convert it to a standard one
#using a 3D matrix or kepp as 4D matrix?
if self.nbFiles > 1:
if (arrRet.shape[0] > 1) and\
(arrRet.shape[1] > 1):
raise IOError(\
"Multiple files with multiple images not implemented yet")
elif arrRet.shape[0] == 1:
self.data = numpy.zeros((self.nbFiles,
arrRet.shape[0] * nImages,
arrRet.shape[1]),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack=tempEdf.GetData(i)
self.data[self.incrProgressBar, i,:] = \
pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
elif arrRet.shape[1] == 1:
self.data = numpy.zeros((self.nbFiles,
arrRet.shape[1] * nImages,
arrRet.shape[0]),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack=tempEdf.GetData(i)
self.data[self.incrProgressBar, i,:] = \
pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
else:
self.data = numpy.zeros((nImages * self.nbFiles,
arrRet.shape[0],
arrRet.shape[1]),
self.__dtype)
self.incrProgressBar=0
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
for i in range(nImages):
pieceOfStack=tempEdf.GetData(i)
self.data[nImages*self.incrProgressBar+i,
:,:] = pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
else:
if fileindex == 1:
try:
self.data = numpy.zeros((arrRet.shape[0],
self.nbFiles,
arrRet.shape[1]),
self.__dtype)
except:
try:
self.data = numpy.zeros((arrRet.shape[0],
self.nbFiles,
arrRet.shape[1]),
numpy.float32)
except:
self.data = numpy.zeros((arrRet.shape[0],
self.nbFiles,
arrRet.shape[1]),
numpy.int16)
else:
try:
# calculate needed megabytes
if self.__dtype == numpy.float:
bytefactor = 8
else:
bytefactor = 4
needed_ = self.nbFiles * \
arrRet.shape[0] *\
arrRet.shape[1] * 4
physicalMemory = PhysicalMemory.getPhysicalMemoryOrNone()
if physicalMemory is not None:
# spare 5% of memory
if physicalMemory < (1.05 * needed_):
raise MemoryError("Not enough physical memory available")
self.data = numpy.zeros((self.nbFiles,
arrRet.shape[0],
arrRet.shape[1]),
self.__dtype)
except:
try:
needed_ = self.nbFiles * \
arrRet.shape[0] *\
arrRet.shape[1] * 4
physicalMemory = PhysicalMemory.getPhysicalMemoryOrNone()
if physicalMemory is not None:
# spare 5 % of memory
if physicalMemory < (1.05 * needed_):
raise MemoryError("Not enough physical memory available")
self.data = numpy.zeros((self.nbFiles,
arrRet.shape[0],
arrRet.shape[1]),
numpy.float32)
except (MemoryError, ValueError):
text = "Memory Error: Attempt subsampling or convert to HDF5"
if HDF5 and (('PyMcaQt' in sys.modules) or\
('PyMca.PyMcaQt' in sys.modules)):
from PyMca5 import PyMcaQt as qt
from PyMca5 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:
raise MemoryError(text)
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"
hdf, self.data = ArraySave.getHDF5FileInstanceAndBuffer(hdf5file,
(self.nbFiles,
arrRet.shape[0],
arrRet.shape[1]))
else:
raise MemoryError("Memory Error")
self.incrProgressBar=0
if fileindex == 1:
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
pieceOfStack=tempEdf.GetData(0)
self.data[:,self.incrProgressBar,:] = pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
else:
# test for ID24 map
ID24 = False
if "_sample_" in filelist[0]:
i0StartFile = filelist[0].replace("_sample_", "_I0start_")
if os.path.exists(i0StartFile):
ID24 = True
id24idx = 0
i0Start = EdfFile.EdfFile(i0StartFile, 'rb').GetData(0).astype(numpy.float)
i0EndFile = filelist[0].replace("_sample_", "_I0end_")
i0Slope = 0.0
if os.path.exists(i0EndFile):
i0End = EdfFile.EdfFile(i0EndFile, 'rb').GetData(0)
i0Slope = (i0End-i0Start)/len(filelist)
for tempEdfFileName in filelist:
tempEdf=EdfFile.EdfFile(tempEdfFileName, 'rb')
if ID24:
pieceOfStack=-numpy.log(tempEdf.GetData(0)/(i0Start[0,:] + id24idx * i0Slope))
pieceOfStack[numpy.isfinite(pieceOfStack) == False] = 1
id24idx += 1
else:
pieceOfStack=tempEdf.GetData(0)
try:
self.data[self.incrProgressBar, :,:] = pieceOfStack[:,:]
except:
if pieceOfStack.shape[1] != arrRet.shape[1]:
print(" ERROR on file %s" % tempEdfFileName)
print(" DIM 1 error Assuming missing data were at the end!!!")
if pieceOfStack.shape[0] != arrRet.shape[0]:
print(" ERROR on file %s" % tempEdfFileName)
print(" DIM 0 error Assuming missing data were at the end!!!")
self.data[self.incrProgressBar,\
:pieceOfStack.shape[0],\
:pieceOfStack.shape[1]] = pieceOfStack[:,:]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
self.__nFiles = self.incrProgressBar
self.__nImagesPerFile = nImages
shape = self.data.shape
for i in range(len(shape)):
key = 'Dim_%d' % (i+1,)
self.info[key] = shape[i]
if not isinstance(self.data, numpy.ndarray):
hdf.flush()
self.info["SourceType"] = "HDF5Stack1D"
if self.__imageStack:
self.info["McaIndex"] = 0
self.info["FileIndex"] = 1
else:
self.info["McaIndex"] = 2
self.info["FileIndex"] = 0
self.info["SourceName"] = [hdf5file]
self.info["NumberOfFiles"] = 1
self.info["Size"] = 1
elif actualImageStack:
self.info["SourceType"] = SOURCE_TYPE
self.info["McaIndex"] = 0
self.info["FileIndex"] = 1
self.info["SourceName"] = self.sourceName
self.info["NumberOfFiles"] = self.__nFiles * 1
self.info["Size"] = self.__nFiles * self.__nImagesPerFile
else:
self.info["SourceType"] = SOURCE_TYPE
self.info["FileIndex"] = fileindex
self.info["SourceName"] = self.sourceName
self.info["NumberOfFiles"] = self.__nFiles * 1
self.info["Size"] = self.__nFiles * self.__nImagesPerFile