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# coding: utf-8
#
# Project: X-ray image reader
# https://github.com/silx-kit/fabio
#
#
# Copyright (C) European Synchrotron Radiation Facility, Grenoble, France
#
# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
#
# 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.
"""Authors: Henning O. Sorensen & Erik Knudsen
Center for Fundamental Research: Metal Structures in Four Dimensions
Risoe National Laboratory
Frederiksborgvej 399
DK-4000 Roskilde
email:erik.knudsen@risoe.dk
Jérôme Kieffer, ESRF, Grenoble, France
Sigmund Neher, GWDG, Göttingen, Germany
"""
__authors__ = ["Henning O. Sorensen", "Erik Knudsen", "Jon Wright",
"Jérôme Kieffer", "Sigmund Neher"]
__status__ = "production"
__copyright__ = "2007-2009 Risoe National Laboratory; 2015-2020 ESRF, 2016 GWDG"
__licence__ = "MIT"
import io
import os
from math import ceil
import logging
import time
import numpy
logger = logging.getLogger(__name__)
from .brukerimage import BrukerImage
from .fabioutils import pad, StringTypes
def mround(value, multiple=16):
"""Round a value up to the multiple of multiple
"""
return int(multiple * ceil(value / multiple))
def _split_data(data, baseline=None):
"Split an image, return the dict with various components"
data = data.astype("int32") # explicit copy
flat = data.ravel()
use_underflow = True
if baseline is None:
mini = data.min()
if mini >= 0:
mode = numpy.bincount(flat).argmax()
else:
mean = flat.mean()
std = flat.std()
inliers = abs(flat - mean) / std < 3
mode = int(flat[inliers].mean())
if (mode - mini) < 128:
baseline = mini + 1
else:
baseline = mode + 128 # Ensures the mode is in the middle of the uint8 range
elif baseline is False:
baseline = 0
use_underflow = False
# else:
# print("Forced baseline", baseline, data.min(), data.max())
umask = flat <= baseline
if use_underflow and numpy.any(umask):
underflow = flat[umask]
underflow_max = max(abs(underflow.min()), abs(underflow.max()))
underflow_dtype = numpy.dtype(f"int{mround(numpy.log2(underflow_max)+1,8)}")
underflow = underflow.astype(underflow_dtype)
flat -= baseline
flat[umask] = 0
else:
underflow = numpy.array([], dtype=numpy.int8)
flat -= baseline
o2_mask = numpy.logical_or(flat < 0, flat >= 65535)
if numpy.any(o2_mask):
overflow2 = flat[o2_mask]
flat[o2_mask] = 65535
else:
overflow2 = numpy.array([], dtype=numpy.int32)
o1_mask = flat >= 255
if numpy.any(o1_mask):
overflow1 = flat[o1_mask].astype(numpy.uint16)
flat[o1_mask] = 255
else:
overflow1 = numpy.array([], dtype=numpy.uint16)
data = flat.astype(numpy.uint8).reshape(data.shape)
res = {"data":data,
"baseline": baseline,
"underflow": underflow,
"overflow1": overflow1,
"overflow2": overflow2
}
return res
def _merge_data(data, baseline=0, underflow=None, overflow1=None, overflow2=None):
"""
Build an array from the various components
:param data: probably a uint8 array --> expanded to int32
:param baseline: value of the baseline
:param underflow: value of the data below the baseline (any value with 0 are replaced with those values)
:param overflow1: value of the data where data=255 (in the range 255-65535)
:param overflow2: value of the data where overflow1=65535 (value >= 65535)
:return: array of int32
"""
in_dtype = data.dtype
data = data.astype(numpy.int32)
if (in_dtype.itemsize == 1) and (overflow1 is not None):
# Use Overflow1
mask = numpy.where(data == 255)
data[mask] = overflow1
if (in_dtype.itemsize < 4) and (overflow2 is not None):
# Use Overflow2
mask = numpy.where(data == 65535)
data[mask] = overflow2
if (underflow is None or underflow.size == 0):
data += baseline
else:
mask = data == 0
data[numpy.where(mask)] = underflow
data[numpy.logical_not(mask)] += baseline
return data
class Bruker100Image(BrukerImage):
DESCRIPTION = "SFRM File format used by Bruker detectors (version 100)"
DEFAULT_EXTENSIONS = ["sfrm"]
bpp_to_numpy = {1: numpy.uint8,
2: numpy.uint16,
4: numpy.int32}
version = 100
def __init__(self, data=None, header=None):
BrukerImage.__init__(self, data, header)
def _readheader(self, infile):
"""
The bruker format uses 80 char lines in key : value format
In the first 512*5 bytes of the header there should be a
HDRBLKS key, whose value denotes how many 512 byte blocks
are in the total header. The header is always n*5*512 bytes,
otherwise it wont contain whole key: value pairs
"""
line = 80
blocksize = 512
nhdrblks = 5 # by default we always read 5 blocks of 512
self.__headerstring = infile.read(blocksize * nhdrblks).decode("ASCII")
self.header = self.check_header()
for i in range(0, nhdrblks * blocksize, line):
if self.__headerstring[i: i + line].find(":") > 0:
key, val = self.__headerstring[i: i + line].split(":", 1)
key = key.strip() # remove the whitespace (why?)
val = val.strip()
if key in self.header:
# append lines if key already there
self.header[key] = self.header[key] + os.linesep + val
else:
self.header[key] = val
# we must have read this in the first 5*512 bytes.
nhdrblks = int(self.header['HDRBLKS'])
self.header['HDRBLKS'] = nhdrblks
# Now read in the rest of the header blocks, appending
self.__headerstring += infile.read(blocksize * (nhdrblks - 5)).decode("ASCII")
for i in range(5 * blocksize, nhdrblks * blocksize, line):
if self.__headerstring[i: i + line].find(":") > 0: # as for first 512 bytes of header
key, val = self.__headerstring[i: i + line].split(":", 1)
key = key.strip()
val = val.strip()
if key in self.header:
self.header[key] = self.header[key] + os.linesep + val
else:
self.header[key] = val
# set the image dimensions
shape = int(self.header['NROWS'].split()[0]), int(self.header['NCOLS'].split()[0])
self._shape = shape
self.version = int(self.header.get('FORMAT', "100"))
def read(self, fname, frame=None):
"""Read the data.
Data is stored in three blocks:
- data (uint8 mainly when bpp=1), possibly int32 if bpp=4
- overflow1 (2 bytes/value in uint16)
- overflow2 (4 bytes/value in int32)
- underflow (int8, int16 or int32).
The blocks are zero padded to a multiple of 16 bytes.
"""
with self._open(fname, "rb") as infile:
self._readheader(infile)
rows, cols = self.shape
npixelb = int(self.header['NPIXELB'].split()[0])
# you had to read the Bruker docs to know this!
# We are now at the start of the image - assuming bruker._readheader worked
# Get image block size from NPIXELB.
# The total size is nbytes * nrows * ncolumns.
data_size = rows * cols * npixelb
# data_size_padded = mround(data_size, 512)
data_size_padded = data_size
raw_data = infile.read(data_size_padded)
data = numpy.frombuffer(raw_data[:data_size], dtype=self.bpp_to_numpy[npixelb]).reshape((rows, cols))
# self.data = readbytestream(infile, infile.tell(), rows, cols, npixelb,
# datatype="int", signed='n', swap='n')
if npixelb > 1 and not numpy.little_endian:
self.data = data.byteswap()
else:
self.data = data
# now process the overflows
noverfl_values = [int(f) for f in self.header['NOVERFL'].split()]
to_merge = {"data":data,
"underflow": None,
"overflow1": None,
"overflow2": None,
"baseline": None}
for k, nov in enumerate(noverfl_values):
if nov <= 0:
continue
if k == 0:
bpp = int(self.header['NPIXELB'].split()[1])
datatype = numpy.dtype(f"int{bpp*8}")
elif k > 2:
break
else:
bpp = 2 * k
datatype = self.bpp_to_numpy[bpp]
to_read = nov * bpp
# pad nov*bpp to a multiple of 16 bytes
nbytes = mround(to_read, 16)
# Multiple of 16 just above
data_str = infile.read(nbytes)
# ar without zeros
ar = numpy.frombuffer(data_str[:to_read], dtype=datatype)
if k == 0:
# read the set of "underflow pixels" - these will be completely disregarded for now
to_merge["underflow"] = ar
elif k == 1:
to_merge["overflow1"] = ar
elif k == 2:
to_merge["overflow2"] = ar
else:
break
logger.debug("%s bytes read + %d bytes padding" % (nov * bpp, nbytes - nov * bpp))
# Read baseline
if noverfl_values[0] == -1:
# If number of underflows is -1, there is neither baseline, nor underflow correction
to_merge["baseline"] = 0
else:
to_merge["baseline"] = int(self.header["NEXP"].split()[2])
self.data = _merge_data(**to_merge)
self.resetvals()
return self
def gen_header(self):
"""
Generate headers (with some magic and guesses)
format is Bruker100
"""
headers = []
for key in self.HEADERS_KEYS:
if key in self.header:
value = self.header[key]
if key == "CFR":
line = key.ljust(4) + ":"
else:
line = key.ljust(7) + ":"
if type(value) in StringTypes:
if key == 'NOVERFL':
line += "".join(str(v).ljust(24, ' ') for k, v in enumerate(value.split()) if k < 3)
elif key == "NPIXELB":
line += "".join(str(v).ljust(36, ' ') for k, v in enumerate(value.split()) if k < 2)
elif key in ("NROWS", "NCOLS"):
line += "".join(str(v).ljust(36, ' ') for k, v in enumerate(value.split()) if k < 2)
elif key == "NEXP":
line += "".join(str(v).ljust(72 // 5, ' ') for k, v in enumerate(value.split()) if k < 5)
elif key == "DETTYPE":
line += str(value)
elif key == "CFR":
line += str(value)
elif os.linesep in value:
lines = value.split(os.linesep)
for i in lines[:-1]:
headers.append((line + str(i)).ljust(80, " "))
line = key.ljust(7) + ":"
line += str(lines[-1])
elif len(value) < 72:
line += str(value)
else:
for i in range(len(value) // 72):
headers.append((line + str(value[72 * i:72 * (i + 1)])))
line = key.ljust(7) + ":"
line += value[72 * (i + 1):]
elif "__len__" in dir(value):
f = "%%.%is" % (72 // len(value) - 1)
line += " ".join([f % i for i in value])
else:
line += str(value)
headers.append(line.ljust(80, " "))
header_size = sum(len(i) for i in headers)
if header_size > 512 * int(self.header["HDRBLKS"]):
tmp = ceil(header_size / 512)
self.header["HDRBLKS"] = mround(tmp, 5)
for i in range(len(headers)):
if headers[i].startswith("HDRBLKS"):
headers[i] = ("HDRBLKS:%s" % self.header["HDRBLKS"]).ljust(80, " ")
res = pad("".join(headers), self.SPACER + "." * 78, 512 * int(self.header["HDRBLKS"]))
return res
def write(self, fname):
"""
Write a bruker100 format image
"""
if numpy.issubdtype(self.data.dtype, float):
if "LINEAR" in self.header:
try:
slope, offset = self.header["LINEAR"].split(None, 1)
slope = float(slope)
offset = float(offset)
except Exception:
logger.warning("Error in converting to float data with linear parameter: %s" % self.header["LINEAR"])
slope, offset = 1.0, 0.0
else:
offset = self.data.min()
max_data = self.data.max()
max_range = 2 ** 24 - 1 # similar to the mantissa of a float32
if max_data > offset:
slope = (max_data - offset) / float(max_range)
else:
slope = 1.0
tmp_data = numpy.round(((self.data - offset) / slope)).astype(numpy.uint32)
self.header["LINEAR"] = "%s %s" % (slope, offset)
else:
tmp_data = self.data
if (int(self.header.get("NOVERFL", "-1").split()[0]) == -1):
baseline = False
elif (len(self.header.get("NEXP", "").split()) > 2):
baseline = int(self.header.get("NEXP", "").split()[2])
else:
baseline = None
split = _split_data(tmp_data, baseline)
data = split["data"]
underflow = split['underflow']
overflow1 = split['overflow1']
overflow2 = split['overflow2']
if baseline is False:
self.header["NOVERFL"] = f"-1 {overflow1.size} {overflow2.size}"
self.header["NPIXELB"] = f"{data.dtype.itemsize} 1"
if "NEXP" in self.header:
lst = self.header["NEXP"].split()
lst[2] = "32"
else:
lst = ["1", "1", "32", "0", "0"]
else:
self.header["NOVERFL"] = f"{underflow.size} {overflow1.size} {overflow2.size}"
self.header["NPIXELB"] = f"{data.dtype.itemsize} {underflow.dtype.itemsize}"
if "NEXP" in self.header:
lst = self.header["NEXP"].split()
lst[2] = str(split['baseline'])
else:
lst = ["1", "1", "0", "0", "0"]
self.header["NEXP"] = " ".join(lst)
self.header["HDRBLKS"] = "5"
if "NROWS" in self.header:
self.header['NROWS'] = self.header['NROWS'].split()
else:
self.header['NROWS'] = [None]
if "NCOLS" in self.header:
self.header['NCOLS'] = self.header['NCOLS'].split()
else:
self.header['NCOLS'] = [None]
self.header['NROWS'][0] = str(tmp_data.shape[0])
self.header['NCOLS'][0] = str(tmp_data.shape[1])
self.header['NROWS'] = " ".join(self.header['NROWS'])
self.header['NCOLS'] = " ".join(self.header['NCOLS'])
self.header["FORMAT"] = str(self.version)
if "VERSION" not in self.header:
self.header["VERSION"] = "16"
if "FILENAM" not in self.header:
self.header["FILENAM"] = fname
if "CREATED" not in self.header:
self.header["CREATED"] = time.strftime('%Y-%m-%d %H:%M:%S')
if "TITLE" not in self.header:
self.header["TITLE"] = "\n"*8
if "DISTANC" not in self.header:
self.header["DISTANC"] = 10
if "CENTER" not in self.header:
self.header["CENTER"] = f"{self.shape[1]/2} {self.shape[0]/2}"
if "WAVELEN" not in self.header:
self.header["WAVELEN"] = "1.0 1.0 1.0"
if 'MAXXY' not in self.header:
argmax = self.data.argmax()
width = data.shape[1]
self.header['MAXXY'] = f"{argmax%width} {argmax//width}"
if "DETTYPE" not in self.header:
self.header["DETTYPE"] = "UNKNOWN"
bytes_header = self.gen_header().encode("ASCII")
with self._open(fname, "wb") as bruker:
fast = isinstance(bruker, io.BufferedWriter)
bruker.write(bytes_header)
if fast:
data.tofile(bruker)
else:
bruker.write(data.tobytes())
# # 512-Padding
# padded = mround(data.nbytes, 512)
# bruker.write(b"\x00"*(padded - data.nbytes))
for extra in (underflow, overflow1, overflow2):
if extra.nbytes:
if fast:
extra.tofile(bruker)
else:
bruker.write(extra.tobytes())
padded = mround(extra.nbytes, 16)
bruker.write(b"\x00"*(padded - extra.nbytes))
bruker100image = Bruker100Image
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