#/*##########################################################################
#
# The PyMca X-Ray Fluorescence Toolkit
#
# Copyright (c) 2004-2014 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__ = "Alexandre Gobbo, V.A. Sole - ESRF Data Analysis"
__contact__ = "sole@esrf.fr"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
"""
EdfFile.py
Generic class for Edf files manipulation.
Interface:
===========================
class EdfFile:
__init__(self,FileName)
GetNumImages(self)
def GetData(self,Index, DataType="",Pos=None,Size=None):
GetPixel(self,Index,Position)
GetHeader(self,Index)
GetStaticHeader(self,Index)
WriteImage (self,Header,Data,Append=1,DataType="",WriteAsUnsigened=0,ByteOrder="")
Edf format assumptions:
===========================
The following details were assumed for this implementation:
- Each Edf file contains a certain number of data blocks.
- Each data block represents data stored in an one, two or three-dimensional array.
- Each data block contains a header section, written in ASCII, and a data section of
binary information.
- The size of the header section in bytes is a multiple of 1024. The header is
padded with spaces (0x20). If the header is not padded to a multiple of 1024,
the file is recognized, but the output is always made in this format.
- The header section starts by '{' and finishes by '}'. It is composed by several
pairs 'keyword = value;'. The keywords are case insensitive, but the values are case
sensitive. Each pair is put in a new line (they are separeted by 0x0A). In the
end of each line, a semicolon (;) separes the pair of a comment, not interpreted.
Exemple:
{
; Exemple Header
HeaderID = EH:000001:000000:000000 ; automatically generated
ByteOrder = LowByteFirst ;
DataType = FloatValue ; 4 bytes per pixel
Size = 4000000 ; size of data section
Dim_1= 1000 ; x coordinates
Dim_2 = 1000 ; y coordinates
(padded with spaces to complete 1024 bytes)
}
- There are some fields in the header that are required for this implementation. If any of
these is missing, or inconsistent, it will be generated an error:
Size: Represents size of data block
Dim_1: size of x coordinates (Dim_2 for 2-dimentional images, and also Dim_3 for 3d)
DataType
ByteOrder
- For the written images, these fields are automatically genereted:
Size,Dim_1 (Dim_2 and Dim_3, if necessary), Byte Order, DataType, HeaderID and Image
These fields are called here "static header", and can be retrieved by the method
GetStaticHeader. Other header components are taken by GetHeader. Both methods returns
a dictionary in which the key is the keyword of the pair. When writting an image through
WriteImage method, the Header parameter should not contain the static header information,
which is automatically generated.
- The indexing of images through these functions is based just on the 0-based position in
the file, the header items HeaderID and Image are not considered for referencing the
images.
- The data section contais a number of bytes equal to the value of Size keyword. Data
section is going to be translated into an 1D, 2D or 3D Numpy Array, and accessed
through GetData method call.
"""
DEBUG = 0
################################################################################
import sys
import numpy
import os.path #, tempfile, shutil
try:
import gzip
GZIP = True
except:
GZIP = False
try:
import bz2
BZ2 = True
except:
BZ2 = False
try:
from PyMca5.PyMcaIO import MarCCD
MARCCD_SUPPORT = True
except ImportError:
#MarCCD
MARCCD_SUPPORT = False
try:
from PyMca5.PyMcaIO import TiffIO
TIFF_SUPPORT = True
except ImportError:
#MarCCD
TIFF_SUPPORT = False
try:
from PyMca5.PyMcaIO import PilatusCBF
PILATUS_CBF_SUPPORT = True
except ImportError:
PILATUS_CBF_SUPPORT = False
try:
from PyMca5.FastEdf import extended_fread
CAN_USE_FASTEDF = 1
except:
CAN_USE_FASTEDF = 0
################################################################################
# constants
HEADER_BLOCK_SIZE = 1024
STATIC_HEADER_ELEMENTS = ("HeaderID", "Image", "ByteOrder", "DataType",
"Dim_1", "Dim_2", "Dim_3",
"Offset_1", "Offset_2", "Offset_3",
"Size")
STATIC_HEADER_ELEMENTS_CAPS = ("HEADERID", "IMAGE", "BYTEORDER", "DATATYPE",
"DIM_1", "DIM_2", "DIM_3",
"OFFSET_1", "OFFSET_2", "OFFSET_3",
"SIZE")
LOWER_CASE = 0
UPPER_CASE = 1
KEYS = 1
VALUES = 2
###############################################################################
[docs]class Image(object):
"""
"""
def __init__(self):
""" Constructor
"""
self.Header = {}
self.StaticHeader = {}
self.HeaderPosition = 0
self.DataPosition = 0
self.Size = 0
self.NumDim = 1
self.Dim1 = 0
self.Dim2 = 0
self.Dim3 = 0
self.DataType = ""
#for i in STATIC_HEADER_ELEMENTS: self.StaticHeader[i]=""
################################################################################
[docs]class EdfFile(object):
"""
"""
############################################################################
#Interface
def __init__(self, FileName, access=None, fastedf=None):
""" Constructor
@param FileName: Name of the file (either existing or to be created)
@type FileName: string
@param access: access mode "r" for reading (the file should exist) or
"w" for writing (if the file does not exist, it does not matter).
@type access: string
@type fastedf= True to use the fastedf module
@param fastedf= boolean
"""
self.Images = []
self.NumImages = 0
self.FileName = FileName
self.File = 0
if fastedf is None:
fastedf = 0
self.fastedf = fastedf
self.ADSC = False
self.MARCCD = False
self.TIFF = False
self.PILATUS_CBF = False
self.SPE = False
if sys.byteorder == "big":
self.SysByteOrder = "HighByteFirst"
else:
self.SysByteOrder = "LowByteFirst"
if hasattr(FileName, "seek") and\
hasattr(FileName, "read"):
# this looks like a file descriptor ...
self.__ownedOpen = False
self.File = FileName
try:
self.FileName = self.File.name
except AttributeError:
self.FileName = self.File.filename
elif FileName.lower().endswith('.gz'):
if GZIP:
self.__ownedOpen = False
self.File = gzip.GzipFile(FileName)
else:
raise IOError("No gzip module support in this system")
elif FileName.lower().endswith('.bz2'):
if BZ2:
self.__ownedOpen = False
self.File = bz2.BZ2File(FileName)
else:
raise IOError("No bz2 module support in this system")
else:
self.__ownedOpen = True
if self.File in [0, None]:
if access is not None:
if access[0].upper() == "R":
if not os.path.isfile(self.FileName):
raise IOError("File %s not found" % FileName)
if 'b' not in access:
access += 'b'
try:
if not os.path.isfile(self.FileName):
#write access
if access is None:
#allow writing and reading
access = "ab+"
self.File = open(self.FileName, access)
self.File.seek(0, 0)
return
if 'b' not in access:
access += 'b'
self.File = open(self.FileName, access)
return
else:
if access is None:
if (os.access(self.FileName, os.W_OK)):
access = "r+b"
else:
access = "rb"
self.File = open(self.FileName, access)
self.File.seek(0, 0)
twoChars = self.File.read(2)
tiff = False
if sys.version < '3.0':
if twoChars in ["II", "MM"]:
tiff = True
elif twoChars in [eval('b"II"'), eval('b"MM"')]:
tiff = True
if tiff:
fileExtension = os.path.splitext(self.FileName)[-1]
if fileExtension.lower() in [".tif", ".tiff"] or\
sys.version > '2.9':
if not TIFF_SUPPORT:
raise IOError("TIFF support not implemented")
else:
self.TIFF = True
elif not MARCCD_SUPPORT:
if not TIFF_SUPPORT:
raise IOError("MarCCD support not implemented")
else:
self.TIFF = True
else:
self.MARCCD = True
if os.path.basename(FileName).upper().endswith('.CBF'):
if not PILATUS_CBF_SUPPORT:
raise IOError("CBF support not implemented")
if twoChars[0] != "{":
self.PILATUS_CBF = True
elif os.path.basename(FileName).upper().endswith('.SPE'):
if twoChars[0] != "$":
self.SPE = True
elif os.path.basename(FileName).upper().endswith('EDF.GZ') or\
os.path.basename(FileName).upper().endswith('CCD.GZ'):
self.GZIP = True
except:
try:
self.File.close()
except:
pass
raise IOError("EdfFile: Error opening file")
self.File.seek(0, 0)
if self.TIFF:
self._wrapTIFF()
self.File.close()
return
if self.MARCCD:
self._wrapMarCCD()
self.File.close()
return
if self.PILATUS_CBF:
self._wrapPilatusCBF()
self.File.close()
return
if self.SPE:
self._wrapSPE()
self.File.close()
return
Index = 0
line = self.File.readline()
selectedLines = [""]
if sys.version > '2.6':
selectedLines.append(eval('b""'))
parsingHeader = False
while line not in selectedLines:
#decode to make sure I have character string
#str to make sure python 2.x sees it as string and not unicode
if sys.version < '3.0':
if type(line) != type(str("")):
line = "%s" % line
else:
try:
line = str(line.decode())
except UnicodeDecodeError:
try:
line = str(line.decode('utf-8'))
except UnicodeDecodeError:
try:
line = str(line.decode('latin-1'))
except UnicodeDecodeError:
line = "%s" % line
if (line.count("{\n") >= 1) or (line.count("{\r\n") >= 1):
parsingHeader = True
Index = self.NumImages
self.NumImages = self.NumImages + 1
self.Images.append(Image())
# Position = self.File.tell()
if line.count("=") >= 1:
listItems = line.split("=", 1)
typeItem = listItems[0].strip()
listItems = listItems[1].split(";", 1)
valueItem = listItems[0].strip()
if (typeItem == "HEADER_BYTES") and (Index == 0):
self.ADSC = True
break
#if typeItem in self.Images[Index].StaticHeader.keys():
if typeItem.upper() in STATIC_HEADER_ELEMENTS_CAPS:
self.Images[Index].StaticHeader[typeItem] = valueItem
else:
self.Images[Index].Header[typeItem] = valueItem
if ((line.count("}\n") >= 1) or (line.count("}\r") >= 1)) and (parsingHeader):
parsingHeader = False
#for i in STATIC_HEADER_ELEMENTS_CAPS:
# if self.Images[Index].StaticHeader[i]=="":
# raise "Bad File Format"
self.Images[Index].DataPosition = self.File.tell()
#self.File.seek(int(self.Images[Index].StaticHeader["Size"]), 1)
StaticPar = SetDictCase(self.Images[Index].StaticHeader, UPPER_CASE, KEYS)
if "SIZE" in StaticPar.keys():
self.Images[Index].Size = int(StaticPar["SIZE"])
if self.Images[Index].Size <= 0:
self.NumImages = Index
line = self.File.readline()
continue
else:
raise TypeError("EdfFile: Image doesn't have size information")
if "DIM_1" in StaticPar.keys():
self.Images[Index].Dim1 = int(StaticPar["DIM_1"])
self.Images[Index].Offset1 = int(\
StaticPar.get("Offset_1", "0"))
else:
raise TypeError("EdfFile: Image doesn't have dimension information")
if "DIM_2" in StaticPar.keys():
self.Images[Index].NumDim = 2
self.Images[Index].Dim2 = int(StaticPar["DIM_2"])
self.Images[Index].Offset2 = int(\
StaticPar.get("Offset_2", "0"))
if "DIM_3" in StaticPar.keys():
self.Images[Index].NumDim = 3
self.Images[Index].Dim3 = int(StaticPar["DIM_3"])
self.Images[Index].Offset3 = int(\
StaticPar.get("Offset_3", "0"))
if "DATATYPE" in StaticPar.keys():
self.Images[Index].DataType = StaticPar["DATATYPE"]
else:
raise TypeError("EdfFile: Image doesn't have datatype information")
if "BYTEORDER" in StaticPar.keys():
self.Images[Index].ByteOrder = StaticPar["BYTEORDER"]
else:
raise TypeError("EdfFile: Image doesn't have byteorder information")
self.File.seek(self.Images[Index].Size, 1)
line = self.File.readline()
if self.ADSC:
self.File.seek(0, 0)
self.NumImages = 1
#this is a bad implementation of fabio adscimage
#please take a look at the fabio module of fable at sourceforge
infile = self.File
header_keys = []
header = {}
try:
""" read an adsc header """
line = infile.readline()
bytesread = len(line)
while '}' not in line:
if '=' in line:
(key, val) = line.split('=')
header_keys.append(key.strip())
header[key.strip()] = val.strip(' ;\n')
line = infile.readline()
bytesread = bytesread + len(line)
except:
raise Exception("Error processing adsc header")
# banned by bzip/gzip???
try:
infile.seek(int(header['HEADER_BYTES']), 0)
except TypeError:
# Gzipped does not allow a seek and read header is not
# promising to stop in the right place
infile.close()
infile = self._open(fname, "rb")
infile.read(int(header['HEADER_BYTES']))
binary = infile.read()
infile.close()
#now read the data into the array
self.Images[Index].Dim1 = int(header['SIZE1'])
self.Images[Index].Dim2 = int(header['SIZE2'])
self.Images[Index].NumDim = 2
self.Images[Index].DataType = 'UnsignedShort'
try:
self.__data = numpy.reshape(
numpy.fromstring(binary, numpy.uint16),
(self.Images[Index].Dim2, self.Images[Index].Dim1))
except ValueError:
raise IOError('Size spec in ADSC-header does not match ' + \
'size of image data field')
if 'little' in header['BYTE_ORDER']:
self.Images[Index].ByteOrder = 'LowByteFirst'
else:
self.Images[Index].ByteOrder = 'HighByteFirst'
if self.SysByteOrder.upper() != self.Images[Index].ByteOrder.upper():
self.__data = self.__data.byteswap()
self.Images[Index].ByteOrder = self.SysByteOrder
self.Images[Index].StaticHeader['Dim_1'] = self.Images[Index].Dim1
self.Images[Index].StaticHeader['Dim_2'] = self.Images[Index].Dim2
self.Images[Index].StaticHeader['Offset_1'] = 0
self.Images[Index].StaticHeader['Offset_2'] = 0
self.Images[Index].StaticHeader['DataType'] = self.Images[Index].DataType
self.__makeSureFileIsClosed()
def _wrapTIFF(self):
self._wrappedInstance = TiffIO.TiffIO(self.File, cache_length = 0, mono_output=True)
self.NumImages = self._wrappedInstance.getNumberOfImages()
if self.NumImages < 1:
return
# wrapped image objects have to provide getInfo and getData
# info = self._wrappedInstance.getInfo( index)
# data = self._wrappedInstance.getData( index)
# for the time being I am going to assume all the images
# in the file have the same data type type
data = None
for Index in range(self.NumImages):
info = self._wrappedInstance.getInfo(Index)
self.Images.append(Image())
self.Images[Index].Dim1 = info['nRows']
self.Images[Index].Dim2 = info['nColumns']
self.Images[Index].NumDim = 2
if data is None:
data = self._wrappedInstance.getData(0)
self.Images[Index].DataType = self.__GetDefaultEdfType__(data.dtype)
self.Images[Index].StaticHeader['Dim_1'] = self.Images[Index].Dim1
self.Images[Index].StaticHeader['Dim_2'] = self.Images[Index].Dim2
self.Images[Index].StaticHeader['Offset_1'] = 0
self.Images[Index].StaticHeader['Offset_2'] = 0
self.Images[Index].StaticHeader['DataType'] = self.Images[Index].DataType
self.Images[Index].Header.update(info)
def _wrapMarCCD(self):
mccd = MarCCD.MarCCD(self.File)
self.NumImages = 1
self.__data = mccd.getData()
self.__info = mccd.getInfo()
self.Images.append(Image())
Index = 0
self.Images[Index].Dim1 = self.__data.shape[0]
self.Images[Index].Dim2 = self.__data.shape[1]
self.Images[Index].NumDim = 2
if self.__data.dtype == numpy.uint8:
self.Images[Index].DataType = 'UnsignedByte'
elif self.__data.dtype == numpy.uint16:
self.Images[Index].DataType = 'UnsignedShort'
else:
self.Images[Index].DataType = 'UnsignedInteger'
self.Images[Index].StaticHeader['Dim_1'] = self.Images[Index].Dim1
self.Images[Index].StaticHeader['Dim_2'] = self.Images[Index].Dim2
self.Images[Index].StaticHeader['Offset_1'] = 0
self.Images[Index].StaticHeader['Offset_2'] = 0
self.Images[Index].StaticHeader['DataType'] = self.Images[Index].DataType
self.Images[Index].Header.update(self.__info)
def _wrapPilatusCBF(self):
mccd = PilatusCBF.PilatusCBF(self.File)
self.NumImages = 1
self.__data = mccd.getData()
self.__info = mccd.getInfo()
self.Images.append(Image())
Index = 0
self.Images[Index].Dim1 = self.__data.shape[0]
self.Images[Index].Dim2 = self.__data.shape[1]
self.Images[Index].NumDim = 2
if self.__data.dtype == numpy.uint8:
self.Images[Index].DataType = 'UnsignedByte'
elif self.__data.dtype == numpy.uint16:
self.Images[Index].DataType = 'UnsignedShort'
else:
self.Images[Index].DataType = 'UnsignedInteger'
self.Images[Index].StaticHeader['Dim_1'] = self.Images[Index].Dim1
self.Images[Index].StaticHeader['Dim_2'] = self.Images[Index].Dim2
self.Images[Index].StaticHeader['Offset_1'] = 0
self.Images[Index].StaticHeader['Offset_2'] = 0
self.Images[Index].StaticHeader['DataType'] = self.Images[Index].DataType
self.Images[Index].Header.update(self.__info)
def _wrapSPE(self):
if 0 and sys.version < '3.0':
self.File.seek(42)
xdim = numpy.int64(numpy.fromfile(self.File, numpy.int16, 1)[0])
self.File.seek(656)
ydim = numpy.int64(numpy.fromfile(self.File, numpy.int16, 1))
self.File.seek(4100)
self.__data = numpy.fromfile(self.File, numpy.uint16, int(xdim * ydim))
else:
import struct
self.File.seek(0)
a = self.File.read()
xdim = numpy.int64(struct.unpack('<h', a[42:44])[0])
ydim = numpy.int64(struct.unpack('<h', a[656:658])[0])
fmt = '<%dH' % int(xdim * ydim)
self.__data = numpy.array(struct.unpack(fmt, a[4100:int(4100+ int(2 * xdim * ydim))])).astype(numpy.uint16)
self.__data.shape = ydim, xdim
Index = 0
self.Images.append(Image())
self.NumImages = 1
self.Images[Index].Dim1 = ydim
self.Images[Index].Dim2 = xdim
self.Images[Index].NumDim = 2
self.Images[Index].DataType = 'UnsignedShort'
self.Images[Index].ByteOrder = 'LowByteFirst'
if self.SysByteOrder.upper() != self.Images[Index].ByteOrder.upper():
self.__data = self.__data.byteswap()
self.Images[Index].StaticHeader['Dim_1'] = self.Images[Index].Dim1
self.Images[Index].StaticHeader['Dim_2'] = self.Images[Index].Dim2
self.Images[Index].StaticHeader['Offset_1'] = 0
self.Images[Index].StaticHeader['Offset_2'] = 0
self.Images[Index].StaticHeader['DataType'] = self.Images[Index].DataType
[docs] def GetNumImages(self):
""" Returns number of images of the object (and associated file)
"""
return self.NumImages
[docs] def GetData(self, *var, **kw):
try:
self.__makeSureFileIsOpen()
return self._GetData(*var, **kw)
finally:
self.__makeSureFileIsClosed()
def _GetData(self, Index, DataType="", Pos=None, Size=None):
""" Returns numpy array with image data
Index: The zero-based index of the image in the file
DataType: The edf type of the array to be returnd
If ommited, it is used the default one for the type
indicated in the image header
Attention to the absence of UnsignedShort,
UnsignedInteger and UnsignedLong types in
Numpy Python
Default relation between Edf types and NumPy's typecodes:
SignedByte int8 b
UnsignedByte uint8 B
SignedShort int16 h
UnsignedShort uint16 H
SignedInteger int32 i
UnsignedInteger uint32 I
SignedLong int32 i
UnsignedLong uint32 I
Signed64 int64 (l in 64bit, q in 32 bit)
Unsigned64 uint64 (L in 64bit, Q in 32 bit)
FloatValue float32 f
DoubleValue float64 d
Pos: Tuple (x) or (x,y) or (x,y,z) that indicates the begining
of data to be read. If ommited, set to the origin (0),
(0,0) or (0,0,0)
Size: Tuple, size of the data to be returned as x) or (x,y) or
(x,y,z) if ommited, is the distance from Pos to the end.
If Pos and Size not mentioned, returns the whole data.
"""
fastedf = self.fastedf
if Index < 0 or Index >= self.NumImages:
raise ValueError("EdfFile: Index out of limit")
if fastedf is None:fastedf = 0
if Pos is None and Size is None:
if self.ADSC or self.MARCCD or self.PILATUS_CBF or self.SPE:
return self.__data
elif self.TIFF:
data = self._wrappedInstance.getData(Index)
return data
else:
self.File.seek(self.Images[Index].DataPosition, 0)
datatype = self.__GetDefaultNumpyType__(self.Images[Index].DataType, index=Index)
try:
datasize = self.__GetSizeNumpyType__(datatype)
except TypeError:
print("What is the meaning of this error?")
datasize = 8
if self.Images[Index].NumDim == 3:
sizeToRead = self.Images[Index].Dim1 * \
self.Images[Index].Dim2 * \
self.Images[Index].Dim3 * datasize
Data = numpy.fromstring(self.File.read(sizeToRead),
datatype)
Data = numpy.reshape(Data, (self.Images[Index].Dim3, self.Images[Index].Dim2, self.Images[Index].Dim1))
elif self.Images[Index].NumDim == 2:
sizeToRead = self.Images[Index].Dim1 * \
self.Images[Index].Dim2 * datasize
Data = numpy.fromstring(self.File.read(sizeToRead),
datatype)
#print "datatype = ",datatype
#print "Data.type = ", Data.dtype.char
#print "self.Images[Index].DataType ", self.Images[Index].DataType
#print "Data.shape",Data.shape
#print "datasize = ",datasize
#print "sizeToRead ",sizeToRead
#print "lenData = ", len(Data)
Data = numpy.reshape(Data, (self.Images[Index].Dim2, self.Images[Index].Dim1))
elif self.Images[Index].NumDim == 1:
sizeToRead = self.Images[Index].Dim1 * datasize
Data = numpy.fromstring(self.File.read(sizeToRead),
datatype)
elif self.ADSC or self.MARCCD or self.PILATUS_CBF or self.SPE:
return self.__data[Pos[1]:(Pos[1] + Size[1]),
Pos[0]:(Pos[0] + Size[0])]
elif self.TIFF:
data = self._wrappedInstance.getData(Index)
return data[Pos[1]:(Pos[1] + Size[1]),
Pos[0]:(Pos[0] + Size[0])]
elif fastedf and CAN_USE_FASTEDF:
type = self.__GetDefaultNumpyType__(self.Images[Index].DataType, index=Index)
size_pixel = self.__GetSizeNumpyType__(type)
Data = numpy.array([], type)
if self.Images[Index].NumDim == 1:
if Pos == None: Pos = (0,)
if Size == None: Size = (0,)
sizex = self.Images[Index].Dim1
Size = list(Size)
if Size[0] == 0:Size[0] = sizex - Pos[0]
self.File.seek((Pos[0] * size_pixel) + self.Images[Index].DataPosition, 0)
Data = numpy.fromstring(self.File.read(Size[0] * size_pixel), type)
elif self.Images[Index].NumDim == 2:
if Pos == None: Pos = (0, 0)
if Size == None: Size = (0, 0)
Size = list(Size)
sizex, sizey = self.Images[Index].Dim1, self.Images[Index].Dim2
if Size[0] == 0:Size[0] = sizex - Pos[0]
if Size[1] == 0:Size[1] = sizey - Pos[1]
Data = numpy.zeros([Size[1], Size[0]], type)
self.File.seek((((Pos[1] * sizex) + Pos[0]) * size_pixel) + self.Images[Index].DataPosition, 0)
extended_fread(Data, Size[0] * size_pixel , numpy.array([Size[1]]),
numpy.array([sizex * size_pixel]) , self.File)
elif self.Images[Index].NumDim == 3:
if Pos == None: Pos = (0, 0, 0)
if Size == None: Size = (0, 0, 0)
Size = list(Size)
sizex, sizey, sizez = self.Images[Index].Dim1, self.Images[Index].Dim2, self.Images[Index].Dim3
if Size[0] == 0:Size[0] = sizex - Pos[0]
if Size[1] == 0:Size[1] = sizey - Pos[1]
if Size[2] == 0:Size[2] = sizez - Pos[2]
Data = numpy.zeros([Size[2], Size[1], Size[0]], type)
self.File.seek(((((Pos[2] * sizey + Pos[1]) * sizex) + Pos[0]) * size_pixel) + self.Images[Index].DataPosition, 0)
extended_fread(Data, Size[0] * size_pixel , numpy.array([Size[2], Size[1]]),
numpy.array([ sizey * sizex * size_pixel , sizex * size_pixel]) , self.File)
else:
if fastedf:
print("I could not use fast routines")
type = self.__GetDefaultNumpyType__(self.Images[Index].DataType, index=Index)
size_pixel = self.__GetSizeNumpyType__(type)
Data = numpy.array([], type)
if self.Images[Index].NumDim == 1:
if Pos == None: Pos = (0,)
if Size == None: Size = (0,)
sizex = self.Images[Index].Dim1
Size = list(Size)
if Size[0] == 0:Size[0] = sizex - Pos[0]
self.File.seek((Pos[0] * size_pixel) + self.Images[Index].DataPosition, 0)
Data = numpy.fromstring(self.File.read(Size[0] * size_pixel), type)
elif self.Images[Index].NumDim == 2:
if Pos == None: Pos = (0, 0)
if Size == None: Size = (0, 0)
Size = list(Size)
sizex, sizey = self.Images[Index].Dim1, self.Images[Index].Dim2
if Size[0] == 0:Size[0] = sizex - Pos[0]
if Size[1] == 0:Size[1] = sizey - Pos[1]
#print len(range(Pos[1],Pos[1]+Size[1])), "LECTURES OF ", Size[0], "POINTS"
#print "sizex = ", sizex, "sizey = ", sizey
Data = numpy.zeros((Size[1], Size[0]), type)
dataindex = 0
for y in range(Pos[1], Pos[1] + Size[1]):
self.File.seek((((y * sizex) + Pos[0]) * size_pixel) + self.Images[Index].DataPosition, 0)
line = numpy.fromstring(self.File.read(Size[0] * size_pixel), type)
Data[dataindex, :] = line[:]
#Data=numpy.concatenate((Data,line))
dataindex += 1
#print "DataSize = ",Data.shape
#print "Requested reshape = ",Size[1],'x',Size[0]
#Data = numpy.reshape(Data, (Size[1],Size[0]))
elif self.Images[Index].NumDim == 3:
if Pos == None: Pos = (0, 0, 0)
if Size == None: Size = (0, 0, 0)
Size = list(Size)
sizex, sizey, sizez = self.Images[Index].Dim1, self.Images[Index].Dim2, self.Images[Index].Dim3
if Size[0] == 0:Size[0] = sizex - Pos[0]
if Size[1] == 0:Size[1] = sizey - Pos[1]
if Size[2] == 0:Size[2] = sizez - Pos[2]
for z in range(Pos[2], Pos[2] + Size[2]):
for y in range(Pos[1], Pos[1] + Size[1]):
self.File.seek(((((z * sizey + y) * sizex) + Pos[0]) * size_pixel) + self.Images[Index].DataPosition, 0)
line = numpy.fromstring(self.File.read(Size[0] * size_pixel), type)
Data = numpy.concatenate((Data, line))
Data = numpy.reshape(Data, (Size[2], Size[1], Size[0]))
if self.SysByteOrder.upper() != self.Images[Index].ByteOrder.upper():
Data = Data.byteswap()
if DataType != "":
Data = self.__SetDataType__ (Data, DataType)
return Data
[docs] def GetPixel(self, Index, Position):
""" Returns double value of the pixel, regardless the format of the array
Index: The zero-based index of the image in the file
Position: Tuple with the coordinete (x), (x,y) or (x,y,z)
"""
if Index < 0 or Index >= self.NumImages:
raise ValueError("EdfFile: Index out of limit")
if len(Position) != self.Images[Index].NumDim:
raise ValueError("EdfFile: coordinate with wrong dimension ")
size_pixel = self.__GetSizeNumpyType__(self.__GetDefaultNumpyType__(self.Images[Index].DataType), index=Index)
offset = Position[0] * size_pixel
if self.Images[Index].NumDim > 1:
size_row = size_pixel * self.Images[Index].Dim1
offset = offset + (Position[1] * size_row)
if self.Images[Index].NumDim == 3:
size_img = size_row * self.Images[Index].Dim2
offset = offset + (Position[2] * size_img)
self.File.seek(self.Images[Index].DataPosition + offset, 0)
Data = numpy.fromstring(self.File.read(size_pixel), self.__GetDefaultNumpyType__(self.Images[Index].DataType, index=Index))
if self.SysByteOrder.upper() != self.Images[Index].ByteOrder.upper():
Data = Data.byteswap()
Data = self.__SetDataType__ (Data, "DoubleValue")
return Data[0]
[docs] def WriteImage(self, *var, **kw):
try:
self.__makeSureFileIsOpen()
return self._WriteImage(*var, **kw)
finally:
self.__makeSureFileIsClosed()
def _WriteImage (self, Header, Data, Append=1, DataType="", ByteOrder=""):
""" Writes image to the file.
Header: Dictionary containing the non-static header
information (static information is generated
according to position of image and data format
Append: If equals to 0, overwrites the file. Otherwise, appends
to the end of the file
DataType: The data type to be saved to the file:
SignedByte
UnsignedByte
SignedShort
UnsignedShort
SignedInteger
UnsignedInteger
SignedLong
UnsignedLong
FloatValue
DoubleValue
Default: according to Data array typecode:
1: SignedByte
b: UnsignedByte
s: SignedShort
w: UnsignedShort
i: SignedInteger
l: SignedLong
u: UnsignedLong
f: FloatValue
d: DoubleValue
ByteOrder: Byte order of the data in file:
HighByteFirst
LowByteFirst
Default: system's byte order
"""
if Append == 0:
self.File.truncate(0)
self.Images = []
self.NumImages = 0
Index = self.NumImages
self.NumImages = self.NumImages + 1
self.Images.append(Image())
#self.Images[Index].StaticHeader["Dim_1"] = "%d" % Data.shape[1]
#self.Images[Index].StaticHeader["Dim_2"] = "%d" % Data.shape[0]
if len(Data.shape) == 1:
self.Images[Index].Dim1 = Data.shape[0]
self.Images[Index].StaticHeader["Dim_1"] = "%d" % self.Images[Index].Dim1
self.Images[Index].Size = (Data.shape[0] * \
self.__GetSizeNumpyType__(Data.dtype))
elif len(Data.shape) == 2:
self.Images[Index].Dim1 = Data.shape[1]
self.Images[Index].Dim2 = Data.shape[0]
self.Images[Index].StaticHeader["Dim_1"] = "%d" % self.Images[Index].Dim1
self.Images[Index].StaticHeader["Dim_2"] = "%d" % self.Images[Index].Dim2
self.Images[Index].Size = (Data.shape[0] * Data.shape[1] * \
self.__GetSizeNumpyType__(Data.dtype))
self.Images[Index].NumDim = 2
elif len(Data.shape) == 3:
self.Images[Index].Dim1 = Data.shape[2]
self.Images[Index].Dim2 = Data.shape[1]
self.Images[Index].Dim3 = Data.shape[0]
self.Images[Index].StaticHeader["Dim_1"] = "%d" % self.Images[Index].Dim1
self.Images[Index].StaticHeader["Dim_2"] = "%d" % self.Images[Index].Dim2
self.Images[Index].StaticHeader["Dim_3"] = "%d" % self.Images[Index].Dim3
self.Images[Index].Size = (Data.shape[0] * Data.shape[1] * Data.shape[2] * \
self.__GetSizeNumpyType__(Data.dtype))
self.Images[Index].NumDim = 3
elif len(Data.shape) > 3:
raise TypeError("EdfFile: Data dimension not suported")
if DataType == "":
self.Images[Index].DataType = self.__GetDefaultEdfType__(Data.dtype)
else:
self.Images[Index].DataType = DataType
Data = self.__SetDataType__ (Data, DataType)
if ByteOrder == "":
self.Images[Index].ByteOrder = self.SysByteOrder
else:
self.Images[Index].ByteOrder = ByteOrder
self.Images[Index].StaticHeader["Size"] = "%d" % self.Images[Index].Size
self.Images[Index].StaticHeader["Image"] = Index + 1
self.Images[Index].StaticHeader["HeaderID"] = "EH:%06d:000000:000000" % self.Images[Index].StaticHeader["Image"]
self.Images[Index].StaticHeader["ByteOrder"] = self.Images[Index].ByteOrder
self.Images[Index].StaticHeader["DataType"] = self.Images[Index].DataType
self.Images[Index].Header = {}
self.File.seek(0, 2)
StrHeader = "{\n"
for i in STATIC_HEADER_ELEMENTS:
if i in self.Images[Index].StaticHeader.keys():
StrHeader = StrHeader + ("%s = %s ;\n" % (i , self.Images[Index].StaticHeader[i]))
for i in Header.keys():
StrHeader = StrHeader + ("%s = %s ;\n" % (i, Header[i]))
self.Images[Index].Header[i] = Header[i]
newsize = (((len(StrHeader) + 1) / HEADER_BLOCK_SIZE) + 1) * HEADER_BLOCK_SIZE - 2
newsize = int(newsize)
StrHeader = StrHeader.ljust(newsize)
StrHeader = StrHeader + "}\n"
self.Images[Index].HeaderPosition = self.File.tell()
self.File.write(StrHeader.encode())
self.Images[Index].DataPosition = self.File.tell()
#if self.Images[Index].StaticHeader["ByteOrder"] != self.SysByteOrder:
if self.Images[Index].ByteOrder.upper() != self.SysByteOrder.upper():
self.File.write((Data.byteswap()).tostring())
else:
self.File.write(Data.tostring())
############################################################################
#Internal Methods
def __makeSureFileIsOpen(self):
if DEBUG:
print("Making sure file is open")
if not self.__ownedOpen:
return
if self.ADSC or self.MARCCD or self.PILATUS_CBF or self.SPE:
if DEBUG:
print("Special case. Image is buffered")
return
if self.File in [0, None]:
if DEBUG:
print("File is None")
elif self.File.closed:
if DEBUG:
print("Reopening closed file")
accessMode = self.File.mode
fileName = self.File.name
newFile = open(fileName, accessMode)
self.File = newFile
return
def __makeSureFileIsClosed(self):
if DEBUG:
print("Making sure file is closed")
if not self.__ownedOpen:
return
if self.ADSC or self.MARCCD or self.PILATUS_CBF or self.SPE:
if DEBUG:
print("Special case. Image is buffered")
return
if self.File in [0, None]:
if DEBUG:
print("File is None")
elif not self.File.closed:
if DEBUG:
print("Closing file")
self.File.close()
return
def __GetDefaultNumpyType__(self, EdfType, index=None):
""" Internal method: returns NumPy type according to Edf type
"""
return self.GetDefaultNumpyType(EdfType, index)
def __GetDefaultEdfType__(self, NumpyType):
""" Internal method: returns Edf type according Numpy type
"""
if NumpyType in ["b", numpy.int8]: return "SignedByte"
elif NumpyType in ["B", numpy.uint8]: return "UnsignedByte"
elif NumpyType in ["h", numpy.int16]: return "SignedShort"
elif NumpyType in ["H", numpy.uint16]: return "UnsignedShort"
elif NumpyType in ["i", numpy.int32]: return "SignedInteger"
elif NumpyType in ["I", numpy.uint32]: return "UnsignedInteger"
elif NumpyType == "l":
if sys.platform == 'linux2':
return "Signed64"
else:
return "SignedLong"
elif NumpyType == "L":
if sys.platform == 'linux2':
return "Unsigned64"
else:
return "UnsignedLong"
elif NumpyType == numpy.int64:
return "Signed64"
elif NumpyType == numpy.uint64:
return "Unsigned64"
elif NumpyType in ["f", numpy.float32]:
return "FloatValue"
elif NumpyType in ["d", numpy.float64]:
return "DoubleValue"
else:
raise TypeError("unknown NumpyType %s" % NumpyType)
def __GetSizeNumpyType__(self, NumpyType):
""" Internal method: returns size of NumPy's Array Types
"""
if NumpyType in ["b", numpy.int8]: return 1
elif NumpyType in ["B", numpy.uint8]: return 1
elif NumpyType in ["h", numpy.int16]: return 2
elif NumpyType in ["H", numpy.uint16]: return 2
elif NumpyType in ["i", numpy.int32]: return 4
elif NumpyType in ["I", numpy.uint32]: return 4
elif NumpyType == "l":
if sys.platform == 'linux2':
return 8 #64 bit
else:
return 4 #32 bit
elif NumpyType == "L":
if sys.platform == 'linux2':
return 8 #64 bit
else:
return 4 #32 bit
elif NumpyType in ["f", numpy.float32]: return 4
elif NumpyType in ["d", numpy.float64]: return 8
elif NumpyType == "Q": return 8 #unsigned 64 in 32 bit
elif NumpyType == "q": return 8 #signed 64 in 32 bit
elif NumpyType == numpy.uint64: return 8
elif NumpyType == numpy.int64: return 8
else:
raise TypeError("unknown NumpyType %s" % NumpyType)
def __SetDataType__ (self, Array, DataType):
""" Internal method: array type convertion
"""
# AVOID problems not using FromEdfType= Array.dtype.char
FromEdfType = Array.dtype
ToEdfType = self.__GetDefaultNumpyType__(DataType)
if ToEdfType != FromEdfType:
aux = Array.astype(self.__GetDefaultNumpyType__(DataType))
return aux
return Array
def __del__(self):
try:
self.__makeSureFileIsClosed()
except:
pass
[docs] def GetDefaultNumpyType(self, EdfType, index=None):
""" Returns NumPy type according Edf type
"""
if index is None:return GetDefaultNumpyType(EdfType)
EdfType = EdfType.upper()
if EdfType in ['SIGNED64'] :return numpy.int64
if EdfType in ['UNSIGNED64']:return numpy.uint64
if EdfType in ["SIGNEDLONG", "UNSIGNEDLONG"]:
dim1 = 1
dim2 = 1
dim3 = 1
if hasattr(self.Images[index], "Dim1"):
dim1 = self.Images[index].Dim1
if hasattr(self.Images[index], "Dim2"):
dim2 = self.Images[index].Dim2
if dim2 <= 0: dim2 = 1
if hasattr(self.Images[index], "Dim3"):
dim3 = self.Images[index].Dim3
if dim3 <= 0: dim3 = 1
if hasattr(self.Images[index], "Size"):
size = self.Images[index].Size
if size / (dim1 * dim2 * dim3) == 8:
if EdfType == "UNSIGNEDLONG":
return numpy.uint64
else:
return numpy.int64
if EdfType == "UNSIGNEDLONG":
return numpy.uint32
else:
return numpy.int32
return GetDefaultNumpyType(EdfType)
[docs]def GetDefaultNumpyType(EdfType):
""" Returns NumPy type according Edf type
"""
EdfType = EdfType.upper()
if EdfType == "SIGNEDBYTE": return numpy.int8 # "b"
elif EdfType == "UNSIGNEDBYTE": return numpy.uint8 # "B"
elif EdfType == "SIGNEDSHORT": return numpy.int16 # "h"
elif EdfType == "UNSIGNEDSHORT": return numpy.uint16 # "H"
elif EdfType == "SIGNEDINTEGER": return numpy.int32 # "i"
elif EdfType == "UNSIGNEDINTEGER": return numpy.uint32 # "I"
elif EdfType == "SIGNEDLONG": return numpy.int32 # "i" #ESRF acquisition is made in 32bit
elif EdfType == "UNSIGNEDLONG": return numpy.uint32 # "I" #ESRF acquisition is made in 32bit
elif EdfType == "SIGNED64": return numpy.int64 # "l"
elif EdfType == "UNSIGNED64": return numpy.uint64 # "L"
elif EdfType == "FLOATVALUE": return numpy.float32 # "f"
elif EdfType == "FLOAT": return numpy.float32 # "f"
elif EdfType == "DOUBLEVALUE": return numpy.float64 # "d"
else: raise TypeError("unknown EdfType %s" % EdfType)
[docs]def SetDictCase(Dict, Case, Flag):
""" Returns dictionary with keys and/or values converted into upper or lowercase
Dict: input dictionary
Case: LOWER_CASE, UPPER_CASE
Flag: KEYS, VALUES or KEYS | VALUES
"""
newdict = {}
for i in Dict.keys():
newkey = i
newvalue = Dict[i]
if Flag & KEYS:
if Case == LOWER_CASE: newkey = newkey.lower()
else: newkey = newkey.upper()
if Flag & VALUES:
if Case == LOWER_CASE: newvalue = newvalue.lower()
else: newvalue = newvalue.upper()
newdict[newkey] = newvalue
return newdict
[docs]def GetRegion(Arr, Pos, Size):
"""Returns array with refion of Arr.
Arr must be 1d, 2d or 3d
Pos and Size are tuples in the format (x) or (x,y) or (x,y,z)
Both parameters must have the same size as the dimention of Arr
"""
Dim = len(Arr.shape)
if len(Pos) != Dim: return None
if len(Size) != Dim: return None
if (Dim == 1):
SizeX = Size[0]
if SizeX == 0: SizeX = Arr.shape[0] - Pos[0]
ArrRet = numpy.take(Arr, range(Pos[0], Pos[0] + SizeX))
elif (Dim == 2):
SizeX = Size[0]
SizeY = Size[1]
if SizeX == 0: SizeX = Arr.shape[1] - Pos[0]
if SizeY == 0: SizeY = Arr.shape[0] - Pos[1]
ArrRet = numpy.take(Arr, range(Pos[1], Pos[1] + SizeY))
ArrRet = numpy.take(ArrRet, range(Pos[0], Pos[0] + SizeX), 1)
elif (Dim == 3):
SizeX = Size[0]
SizeY = Size[1]
SizeZ = Size[2]
if SizeX == 0: SizeX = Arr.shape[2] - Pos[0]
if SizeY == 0: SizeX = Arr.shape[1] - Pos[1]
if SizeZ == 0: SizeZ = Arr.shape[0] - Pos[2]
ArrRet = numpy.take(Arr, range(Pos[2], Pos[2] + SizeZ))
ArrRet = numpy.take(ArrRet, range(Pos[1], Pos[1] + SizeY), 1)
ArrRet = numpy.take(ArrRet, range(Pos[0], Pos[0] + SizeX), 2)
else:
ArrRet = None
return ArrRet
#EXAMPLE CODE:
if __name__ == "__main__":
if 1:
# import os
a = numpy.zeros((5, 10))
for i in range(5):
for j in range(10):
a[i, j] = 10 * i + j
edf = EdfFile("armando.edf", access="ab+")
edf.WriteImage({}, a)
del edf #force to close the file
inp = EdfFile("armando.edf")
b = inp.GetData(0)
out = EdfFile("armando2.edf")
out.WriteImage({}, b)
del out #force to close the file
inp2 = EdfFile("armando2.edf")
c = inp2.GetData(0)
print("A SHAPE = ", a.shape)
print("B SHAPE = ", b.shape)
print("C SHAPE = ", c.shape)
for i in range(5):
print("A", a[i, :])
print("B", b[i, :])
print("C", c[i, :])
x = numpy.arange(100)
x.shape = 5, 20
for item in ["SignedByte", "UnsignedByte",
"SignedShort", "UnsignedShort",
"SignedLong", "UnsignedLong",
"Signed64", "Unsigned64",
"FloatValue", "DoubleValue"]:
fname = item + ".edf"
if os.path.exists(fname):
os.remove(fname)
towrite = EdfFile(fname)
towrite.WriteImage({}, x, DataType=item, Append=0)
sys.exit(0)
#Creates object based on file exe.edf
exe = EdfFile("images/test_image.edf")
x = EdfFile("images/test_getdata.edf")
#Gets unsigned short data, storing in an signed long
arr = exe.GetData(0, Pos=(100, 200), Size=(200, 400))
x.WriteImage({}, arr, 0)
arr = exe.GetData(0, Pos=(100, 200))
x.WriteImage({}, arr)
arr = exe.GetData(0, Size=(200, 400))
x.WriteImage({}, arr)
arr = exe.GetData(0)
x.WriteImage({}, arr)
sys.exit()
#Creates object based on file exe.edf
exe = EdfFile("images/.edf")
#Creates long array , filled with 0xFFFFFFFF(-1)
la = numpy.zeros((100, 100))
la = la - 1
#Creates a short array, filled with 0xFFFF
sa = numpy.zeros((100, 100))
sa = sa + 0xFFFF
sa = sa.astype("s")
#Writes long array, initializing file (append=0)
exe.WriteImage({}, la, 0, "")
#Appends short array with new header items
exe.WriteImage({'Name': 'Alexandre', 'Date': '16/07/2001'}, sa)
#Appends short array, in Edf type unsigned
exe.WriteImage({}, sa, DataType="UnsignedShort")
#Appends short array, in Edf type unsigned
exe.WriteImage({}, sa, DataType="UnsignedLong")
#Appends long array as a double, considering unsigned
exe.WriteImage({}, la, DataType="DoubleValue", WriteAsUnsigened=1)
#Gets unsigned short data, storing in an signed long
ushort = exe.GetData(2, "SignedLong")
#Makes an operation
ushort = ushort - 0x10
#Saves Result as signed long
exe.WriteImage({}, ushort)
#Saves in the original format (unsigned short)
OldHeader = exe.GetStaticHeader(2)
exe.WriteImage({}, ushort, 1, OldHeader["DataType"])