/usr/share/pyshared/PyMca/TextImageStack.py is in pymca 4.5.0-4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 | #/*##########################################################################
# Copyright (C) 2004-2011 European Synchrotron Radiation Facility
#
# This file is part of the PyMCA X-ray Fluorescence Toolkit developed at
# the ESRF by the Beamline Instrumentation Software Support (BLISS) group.
#
# This toolkit is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by the Free
# Software Foundation; either version 2 of the License, or (at your option)
# any later version.
#
# PyMCA is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the GNU General Public License along with
# PyMCA; if not, write to the Free Software Foundation, Inc., 59 Temple Place,
# Suite 330, Boston, MA 02111-1307, USA.
#
# PyMCA follows the dual licensing model of Trolltech's Qt and Riverbank's PyQt
# and cannot be used as a free plugin for a non-free program.
#
# Please contact the ESRF industrial unit (industry@esrf.fr) if this license
# is a problem for you.
#############################################################################*/
import numpy
import sys
import os
from PyMca import DataObject
HDF5 = False
try:
import h5py
HDF5 = True
except:
pass
SOURCE_TYPE = "EdfFileStack"
DEBUG = 0
class TextImageStack(DataObject.DataObject):
def __init__(self, filelist = None, imagestack=None, dtype=None):
DataObject.DataObject.__init__(self)
self.incrProgressBar=0
self.__keyList = []
if imagestack is None:
self.__imageStack = True
else:
self.__imageStack = imagestack
self.__dtype = dtype
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):
if type(filelist) == type(''):
filelist = [filelist]
self.__keyList = []
self.sourceName = filelist
self.__indexedStack = True
self.sourceType = SOURCE_TYPE
self.info = {}
self.__nFiles=len(filelist)
#read first file
arrRet = numpy.loadtxt(filelist[0])
if self.__dtype is None:
self.__dtype = arrRet.dtype
self.__nImagesPerFile = 1
#try to allocate the memory
shape = self.__nFiles, arrRet.shape[0], arrRet.shape[1]
samplingStep = 1
hdf5done = False
try:
self.data = numpy.zeros(shape, self.__dtype)
except (MemoryError, ValueError):
hdf5done = False
if HDF5 and ('PyMcaQt' in sys.modules):
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 = str(hdf5file)
if not hdf5file.endswith(".h5"):
hdf5file += ".h5"
hdf, self.data = ArraySave.getHDF5FileInstanceAndBuffer(hdf5file,
shape,
dtype=self.__dtype,
interpretation="image",
compression=None)
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((self.__nFiles, s1, s2),
self.__dtype)
samplingStep = i
except (MemoryError, ValueError):
i += 1
#fill the array
self.onBegin(self.__nFiles)
self.__imageStack = True
self.incrProgressBar=0
if samplingStep == 1:
for tempFileName in filelist:
self.data[self.incrProgressBar]=numpy.loadtxt(tempFileName,
dtype=self.__dtype)
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
else:
for tempFileName in filelist:
pieceOfStack=numpy.loadtxt(tempFileName, dtype=self.__dtype)
self.data[self.incrProgressBar] = pieceOfStack[::samplingStep,
::samplingStep]
self.incrProgressBar += 1
self.onProgress(self.incrProgressBar)
self.onEnd()
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
else:
if self.__imageStack:
self.info["McaIndex"] = 0
self.info["FileIndex"] = 1
else:
self.info["McaIndex"] = 2
self.info["FileIndex"] = 0
self.info["SourceType"] = SOURCE_TYPE
self.info["SourceName"] = self.sourceName
self.info["NumberOfFiles"] = self.__nFiles * 1
self.info["Size"] = self.__nFiles * self.__nImagesPerFile
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 ['0', '1', '2',
'3', '4', '5',
'6', '7', '8',
'9']:
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 ['0', '1', '2',
'3', '4', '5',
'6', '7', '8',
'9']:
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):
print("Internal error in EDFStack")
print("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):
print("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)
|