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Support for sparse frames without background (XPCS among other) #558

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Apr 11, 2024
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Support for sparse frames without background (XPCS among other) #558

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66 changes: 35 additions & 31 deletions src/fabio/ext/dense.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
# Project: Fable Input/Output
# https://github.com/silx-kit/fabio
#
# Copyright (C) 2020-2023 European Synchrotron Radiation Facility, Grenoble, France
# Copyright (C) 2020-2024 European Synchrotron Radiation Facility, Grenoble, France
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
Expand All @@ -31,7 +31,7 @@
"""Densification of sparse frame format
"""
__author__ = "Jérôme Kieffer"
__date__ = "20/10/2023"
__date__ = "19/03/2024"
__contact__ = "Jerome.kieffer@esrf.fr"
__license__ = "MIT"

Expand Down Expand Up @@ -249,12 +249,15 @@ def densify(cython.floating[:,::1] mask,
cdef:
Py_ssize_t i, j, size, pos, size_over, width, height
double value, fres, fpos, idelta, start, std
bint integral, noisy, do_normalization=False
bint integral, noisy, do_normalization=False, do_background=True
any_t[:, ::1] dense
float[:,::1] c_normalization
MT mt
size = radius.shape[0]
assert background.shape[0] == size
if radius is None:
do_background = False
else:
size = radius.shape[0]
assert background.shape[0] == size
size_over = index.shape[0]
assert intensity.shape[0] == size_over
integral = numpy.issubdtype(dtype, numpy.integer)
Expand All @@ -277,36 +280,37 @@ def densify(cython.floating[:,::1] mask,
mt = MT(seed)

with nogil:
start = radius[0]
idelta = <double>(size - 1)/(radius[size-1] - start)

#Linear interpolation
for i in range(height):
for j in range(width):
fpos = (mask[i,j] - start)*idelta
if (fpos<0) or (fpos>=size) or (not isfinite(fpos)):
dense[i,j] = dummy
else:
pos = <uint32_t> fpos
if pos+1 == size:
value = background[pos]
fres = 0.0
if do_background:
start = radius[0]
idelta = <double>(size - 1)/(radius[size-1] - start)

#Linear interpolation
for i in range(height):
for j in range(width):
fpos = (mask[i,j] - start)*idelta
if (fpos<0) or (fpos>=size) or (not isfinite(fpos)):
dense[i,j] = dummy
else:
fres = fpos - pos
value = (1.0 - fres)*background[pos] + fres*background[pos+1]
if noisy:
pos = <uint32_t> fpos
if pos+1 == size:
std = background_std[pos]
value = background[pos]
fres = 0.0
else:
std = (1.0 - fres)*background_std[pos] + fres*background_std[pos+1]
value = max(0.0, mt._normal_m(value, std))
if do_normalization:
value *= c_normalization[i, j]
if integral:
dense[i,j] = <any_t>(value + 0.5) #this is rounding
else:
dense[i,j] = <any_t>(value)
fres = fpos - pos
value = (1.0 - fres)*background[pos] + fres*background[pos+1]
if noisy:
if pos+1 == size:
std = background_std[pos]
fres = 0.0
else:
std = (1.0 - fres)*background_std[pos] + fres*background_std[pos+1]
value = max(0.0, mt._normal_m(value, std))
if do_normalization:
value *= c_normalization[i, j]
if integral:
dense[i,j] = <any_t>(value + 0.5) #this is rounding
else:
dense[i,j] = <any_t>(value)
# Assignment of outliers
for i in range(size_over):
j = index[i]
Expand Down
67 changes: 48 additions & 19 deletions src/fabio/sparseimage.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@
__contact__ = "jerome.kieffer@esrf.fr"
__license__ = "MIT"
__copyright__ = "2020 ESRF"
__date__ = "15/03/2024"
__date__ = "19/03/2024"

import logging
logger = logging.getLogger(__name__)
Expand Down Expand Up @@ -82,7 +82,11 @@ def densify(mask,
:param seed: numerical seed for random number generator
:return dense array
"""
dense = numpy.interp(mask, radius, background)
dtype = intensity.dtype
if radius is None or background is None:
dense = numpy.zeros(radius.shape, dtype=dtype)
else:
dense = numpy.interp(mask, radius, background)
if background_std is not None:
if seed is not None:
numpy.random.seed(seed)
Expand All @@ -93,7 +97,7 @@ def densify(mask,

flat = dense.ravel()
flat[index] = intensity
dtype = intensity.dtype

if numpy.issubdtype(dtype, numpy.integer):
# Foolded by banker's rounding !!!!
dense +=0.5
Expand Down Expand Up @@ -173,9 +177,13 @@ def read(self, fname, frame=None):
raise NotGoodReader("HDF5 file does not contain any default NXdata.")
nx_data = entry[default_data]
self.mask = nx_data["mask"][()]
self.radius = nx_data["radius"][()]
self.background_avg = nx_data["background_avg"][()]
self.background_std = nx_data["background_std"][()]
try:
self.radius = nx_data["radius"][()]
self.background_avg = nx_data["background_avg"][()]
self.background_std = nx_data["background_std"][()]
except KeyError:
logger.info("No background information found")
self.radius = self.background_avg = self.background_std = None
self.frame_ptr = nx_data["frame_ptr"][()]
self.index = nx_data["index"][()]
self.intensity = nx_data["intensity"][()]
Expand Down Expand Up @@ -205,27 +213,48 @@ def _generate_data(self, index=0):
logger.warning("Not data have been read from disk")
return
start, stop = self.frame_ptr[index:index + 2]
if cython_densify is not None:
return cython_densify.densify(self.mask,
self.radius,
self.index[start:stop],
self.intensity[start:stop],
self.dummy,
self.intensity.dtype,
self.background_avg[index],
self.background_std[index] * self.noisy if self.noisy else None,
self.normalization)
if self.radius is None:
if cython_densify is None: # Numpy implementation
dense = densify(self.mask,
None,
self.index[start:stop],
self.intensity[start:stop],
self.dummy,
None,
None,
self.normalization)
else: # Cython
dense = cython_densify.densify(self.mask,
None,
self.index[start:stop],
self.intensity[start:stop],
self.dummy,
self.intensity.dtype,
None,
None,
self.normalization)
else:
# Fall-back on numpy code.
return densify(self.mask,
if cython_densify is None: # Numpy
dense = densify(self.mask,
self.radius,
self.index[start:stop],
self.intensity[start:stop],
self.dummy,
self.background_avg[index],
self.background_std[index] * self.noisy if self.noisy else None,
self.normalization)

else:
dense = cython_densify.densify(self.mask,
self.radius,
self.index[start:stop],
self.intensity[start:stop],
self.dummy,
self.intensity.dtype,
self.background_avg[index],
self.background_std[index] * self.noisy if self.noisy else None,
self.normalization)
return dense

def getframe(self, num):
""" returns the frame numbered 'num' in the stack if applicable"""
if self.nframes > 1:
Expand Down
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