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#/*##########################################################################
#
# The PyMca X-Ray Fluorescence Toolkit
#
# Copyright (c) 2004-2015 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 os
import sys
import struct
import numpy
from PyMca5 import DataObject
DEBUG = 0
SOURCE_TYPE = "EdfFileStack"
class LispixMap(DataObject.DataObject):
'''
Class to read Lispix files (Raw file described by a header file)
It reads the spectra into a DataObject instance.
This class info member contains all the parsed information.
This class data member contains the map itself as a 3D array.
'''
def __init__(self, filename, native=False):
'''
Parameters:
-----------
filename : str
Name of the input file.
native : boolean (default False)
If set to False, it will always return a stack of spectra.
It set to True, it will return what it is specified in the original file.
'''
dataFile, headerFile = _getDataAndDescriptionFileName(filename)
description = _parseHeaderFile(headerFile)
columns = description.get("width", None)
rows = description.get("height", None)
if columns is None:
raise IOError("Missing width field")
if rows is None:
raise IOError("Missing height field")
offset = description["offset"]
channels = description["depth"]
if description["data-type"] in ["float", "double"]:
if description["data-length"] == 4:
dtype = numpy.float32
fmt = "f"
elif description["data-length"] == 8:
dtype = numpy.float64
fmt = "d"
else:
raise ValueError("Out of standard float length %d" % description["data-length"])
elif description["data-type"] == "signed":
if description["data-length"] == 1:
dtype = numpy.int8
fmt = "b"
elif description["data-length"] == 2:
dtype = numpy.int16
fmt = "h"
elif description["data-length"] == 4:
dtype = numpy.int32
fmt = "l"
elif description["data-length"] == 8:
dtype = numpy.int64
fmt = "q"
elif description["data-type"] == "unsigned":
if description["data-length"] == 1:
dtype = numpy.uint8
fmt = "B"
elif description["data-length"] == 2:
dtype = numpy.uint16
fmt = "H"
elif description["data-length"] == 4:
dtype = numpy.uint32
fmt = "L"
elif description["data-length"] == 8:
dtype = numpy.uint64
fmt = "Q"
else:
raise IOError("Unknown data-type: <%s>" % description["data-type"])
if (description["record-by"] == "image") and (not native):
# we have to convert to stack of spectra to make sure all PyMca
# functionalities (particularly fitting) are available
if dtype in [numpy.int8, numpy.uint8, numpy.int16, numpy.uint16]:
# force stack of spectra with floating point values
self.data = numpy.zeros((rows, columns, channels), dtype=numpy.float32)
else:
self.data = numpy.zeros((rows, columns, channels), dtype=dtype)
try:
f =open(dataFile, "rb")
dataBuffer = f.read(offset)
if description["byte-order"] in ["big-endian", "high-endian"]:
fmt = ">%d%s" % (rows * columns, fmt)
else:
fmt = "<%d%s" % (rows * columns, fmt)
nBytes = struct.calcsize(fmt)
for i in range(channels):
tmpData = numpy.array(struct.unpack(fmt, f.read(nBytes)), dtype=self.data.dtype)
tmpData.shape = rows, columns
self.data[:, :, i] = tmpData
finally:
f.close()
mcaIndex = 2
elif (offset == 0) and (dtype not in [numpy.int8, numpy.uint8, numpy.int16, numpy.uint16]):
# direct, native readout using numpy
self.data = numpy.fromfile(dataFile, dtype=dtype)
native = True
elif description["record-by"] == "image":
if dtype in [numpy.int8, numpy.uint8, numpy.int16, numpy.uint16]:
# force stack of spectra with floating point values
self.data = numpy.zeros((channels, rows, columns), dtype=numpy.float32)
else:
self.data = numpy.zeros((channels, rows, columns), dtype=dtype)
try:
f =open(dataFile, "rb")
dataBuffer = f.read(offset)
if description["byte-order"] in ["big-endian", "high-endian"]:
fmt = ">%d%s" % (rows * columns, fmt)
else:
fmt = "<%d%s" % (rows * columns, fmt)
nBytes = struct.calcsize(fmt)
for i in range(channels):
tmpData = numpy.array(struct.unpack(fmt, f.read(nBytes)), dtype=self.data.dtype)
tmpData.shape = rows, columns
self.data[i] = tmpData
finally:
f.close()
native = True
elif description["record-by"] != "image":
if dtype in [numpy.int8, numpy.uint8, numpy.int16, numpy.uint16]:
# force stack of spectra with floating point values
self.data = numpy.zeros((rows, columns, channels), dtype=numpy.float32)
else:
self.data = numpy.zeros((rows, columns, channels), dtype=dtype)
try:
f =open(dataFile, "rb")
dataBuffer = f.read(offset)
if description["byte-order"] in ["big-endian", "high-endian"]:
fmt = ">%d%s" % (columns * channels, fmt)
else:
fmt = "<%d%s" % (columns * channels, fmt)
nBytes = struct.calcsize(fmt)
for i in range(rows):
tmpData = numpy.array(struct.unpack(fmt, f.read(nBytes)), dtype=self.data.dtype)
tmpData.shape = columns, channels
self.data[i] = tmpData
finally:
f.close()
native = True
else:
raise IOError("Unhandled reading case. I should not reach this point")
if native:
if description["record-by"] == "image":
self.data.shape = channels, rows, columns
mcaIndex = 0
elif description["record-by"] == "vector":
self.data.shape = rows, columns, channels
mcaIndex = 2
else:
print("Assuming spectra")
self.data.shape = rows, columns, channels
mcaIndex = 2
self.sourceName = filename
self.info = {}
self.info["SourceType"] = SOURCE_TYPE
self.info["SourceName"] = self.sourceName
shape = self.data.shape
for i in range(len(shape)):
key = 'Dim_%d' % (i + 1,)
self.info[key] = shape[i]
self.info["NumberOfFiles"] = 1
self.info["McaIndex"] = mcaIndex
self.info["McaCalib"] = [0.0, 1.0, 0.0]
self.info["Channel0"] = 0.0
def _getDataAndDescriptionFileName(filename):
"""
Given a file name, returns the name of the associated raw data file
and associated rpl description file.
If the associated file is not existing, it returns None.
"""
if filename.lower().endswith("raw"):
dataDile = filename
headerFile = filename[:-3] + "rpl"
else:
headerFile = filename
if not os.path.exists(headerFile):
headerFile = None
else:
headerFile = filename
dataFile = filename[:-3] + "raw"
return dataFile, headerFile
def _parseHeaderFile(headerFile):
"""
Given the input header file describing the data, returns a dictionnary
with the description of the binary data:
key value
width 187 # pixels per row
height 184 # rows
depth 4096 # images or spectrum points
offset 0 # bytes to skip
data-length 2 # bytes per pixel
data-type unsigned # possible values: signed, unsigned or float
byte-order little-endian # big-endian, little-endian, or dont-care
record-by vector # image, vector, or dont-care
"""
data = open(headerFile, "r").readlines()
numericKeyList = ["width", "Width",
"height", "Height",
"depth", "Depth",
"offset", "Offset",
"data-length", "Data-length"]
asciiKeyList = ["data-type", "Data-type",
"byte-order", "Byte-order",
"record-by", "Record-by"]
otherKeys = []
description = {}
description["depth"] = 1
description["offset"] = 0
description["data-length"] = 1
description["data-type"] = "unsigned"
description["byte-order"] = "little-endian"
for line in data:
treated = False
for key in numericKeyList:
if line.startswith(key):
cleanLine = line.replace("\t", " ")
cleanLine = cleanLine.replace("\n", "")
cleanLine = cleanLine.replace("\r", "")
content = cleanLine.split(key)[-1]
content = int(content.strip(" "))
description[key.lower()] = content
treated = True
break
if not treated:
for key in asciiKeyList:
if line.startswith(key):
cleanLine = line.replace("\t", " ")
cleanLine = cleanLine.replace("\n", "")
cleanLine = cleanLine.replace("\r", "")
content = cleanLine.split(key)[-1]
content = content.strip(" ")
description[key.lower()] = content.lower()
treated = True
break
if not treated:
content = line.replace("\t", " ")
if len(content.strip(" ")):
if DEBUG:
print("Ignored line:")
print(line)
return description
def isLispixMapFile(filename):
dataFile, descriptionFile = _getDataAndDescriptionFileName(filename)
if os.path.exists(descriptionFile) and os.path.exists(dataFile):
return True
return False
if __name__ == "__main__":
filename = None
if len(sys.argv) > 1:
filename = sys.argv[1]
print("is Lispix File?", isLispixMapFile(filename))
instance = LispixMap(filename)
print(instance.info)
print(instance.data.size)
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