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# -*- coding: utf-8 -*-
#cython: embedsignature=True, language_level=3
#cython: boundscheck=False, wraparound=False, cdivision=True, initializedcheck=False,
## This is for developping
## cython: profile=True, warn.undeclared=True, warn.unused=True, warn.unused_result=False, warn.unused_arg=True
# -*- coding: utf-8 -*-
#
# Project: Fast Azimuthal integration
# https://github.com/silx-kit/pyFAI
#
# Copyright (C) 2012-2020 European Synchrotron Radiation Facility, 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.
"""Module providing features to relabel regions.
It is used to flag from largest regions to the smallest.
"""
__author__ = "Jerome Kieffer"
__contact__ = "Jerome.kieffer@esrf.fr"
__date__ = "14/01/2021"
__status__ = "stable"
__license__ = "MIT"
import numpy
from libc.stdint cimport int8_t, uint8_t, int16_t, uint16_t, \
int32_t, uint32_t, int64_t, uint64_t
ctypedef double float64_t
ctypedef float float32_t
def countThem(label,
data,
blured):
"""Count
:param label: 2D array containing labeled zones
:param data: 2D array containing the raw data
:param blured: 2D array containing the blured data
:return: 2D arrays containing:
* count pixels in labeled zone: label == index).sum()
* max of data in that zone: data[label == index].max()
* max of blurred in that zone: blured[label == index].max()
* data-blurred where data is max.
"""
cdef:
uint32_t[::1] clabel = numpy.ascontiguousarray(label.ravel(), dtype=numpy.uint32)
float[::1] cdata = numpy.ascontiguousarray(data.ravel(), dtype=numpy.float32)
float[::1] cblured = numpy.ascontiguousarray(blured.ravel(), dtype=numpy.float32)
size_t maxLabel = label.max()
uint64_t[::1] count = numpy.zeros(maxLabel + 1, dtype=numpy.uint64)
float32_t[::1] maxData = numpy.zeros(maxLabel + 1, dtype=numpy.float32)
float32_t[::1] maxBlured = numpy.zeros(maxLabel + 1, dtype=numpy.float32)
float32_t[::1] maxDelta = numpy.zeros(maxLabel + 1, dtype=numpy.float32)
int s, i, idx
float d, b
s = label.size
assert s == cdata.size, "cdata.size"
assert s == cblured.size, "cblured.size"
with nogil:
for i in range(s):
idx = clabel[i]
d = cdata[i]
b = cblured[i]
count[idx] += 1
if d > maxData[idx]:
maxData[idx] = d
maxDelta[idx] = d - b
if b > maxBlured[idx]:
maxBlured[idx] = b
return numpy.asarray(count), numpy.asarray(maxData), numpy.asarray(maxBlured), numpy.asarray(maxDelta)
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