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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
#
# Project: Fast Azimuthal integration
# https://github.com/silx-kit/pyFAI
#
# Copyright (C) 2012-2021 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.
"""Module with makes a discrete 2D-array appear like a continuous function thanks
to bilinear interpolations.
"""
__author__ = "Jerome Kieffer"
__license__ = "MIT"
__date__ = "14/01/2021"
__copyright__ = "2011-2021, ESRF"
__contact__ = "jerome.kieffer@esrf.fr"
import cython
import numpy
from cython cimport floating
from cython.parallel import prange
import logging
logger = logging.getLogger("pyFAI.ext.bilinear")
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 calc_cartesian_positions(floating[::1] d1, floating[::1] d2,
float[:, :, :, ::1] pos,
bint is_flat=True):
"""Calculate the Cartesian position for array of position (d1, d2)
with pixel coordinated stored in array pos.
This is bilinear interpolation.
:param d1: position in dim1
:param d2: position in dim2
:param pos: array with position of pixels corners
:return: 3-tuple of position.
"""
cdef:
int64_t i, p1, p2, dim1, dim2, size = d1.size
float32_t delta1, delta2, f1, f2, A0, A1, A2, B0, B1, B2, C1, C0, C2, D0, D1, D2
float32_t[::1] out1 = numpy.zeros(size, dtype=numpy.float32)
float32_t[::1] out2 = numpy.zeros(size, dtype=numpy.float32)
float32_t[::1] out3
if not is_flat:
out3 = numpy.zeros(size, dtype=numpy.float32)
dim1 = pos.shape[0]
dim2 = pos.shape[1]
assert size == d2.size, "d2.size == size"
for i in prange(size, nogil=True, schedule="static"):
f1 = floor(d1[i])
f2 = floor(d2[i])
p1 = <int> f1
p2 = <int> f2
delta1 = d1[i] - f1
delta2 = d2[i] - f2
if p1 < 0:
with gil:
logger.warning("Negative index along dim1: f1= %s", f1)
p1 = 0
f1 = 0.0
delta1 = d1[i]
if p2 < 0:
with gil:
logger.warning("Negative index along dim2: f2= %s", f2)
p2 = 0
f2 = 0.0
delta2 = d2[i]
if p1 >= dim1:
if p1 > dim1:
with gil:
logger.warning("Overflow on dim1: d1= %s, f1=%s, p1=%s, delta1=%s", d1[i], f1, p1, delta1)
p1 = dim1 - 1
delta1 = d1[i] - p1
if p2 >= dim2:
if p2 > dim2:
with gil:
logger.warning("Overflow on dim2: d2= %s, f2=%s, p2=%s, delta2=%s", d2[i], f2, p2, delta2)
p2 = dim2 - 1
delta2 = d2[i] - p2
A1 = pos[p1, p2, 0, 1]
A2 = pos[p1, p2, 0, 2]
B1 = pos[p1, p2, 1, 1]
B2 = pos[p1, p2, 1, 2]
C1 = pos[p1, p2, 2, 1]
C2 = pos[p1, p2, 2, 2]
D1 = pos[p1, p2, 3, 1]
D2 = pos[p1, p2, 3, 2]
if not is_flat:
A0 = pos[p1, p2, 0, 0]
B0 = pos[p1, p2, 1, 0]
C0 = pos[p1, p2, 2, 0]
D0 = pos[p1, p2, 3, 0]
out3[i] += A0 * (1.0 - delta1) * (1.0 - delta2) \
+ B0 * delta1 * (1.0 - delta2) \
+ C0 * delta1 * delta2 \
+ D0 * (1.0 - delta1) * delta2
# A and D are on the same: dim1 (Y)
# A and B are on the same: dim2 (X)
# nota: += is needed as well as numpy.zero because of prange: avoid reduction
out1[i] += A1 * (1.0 - delta1) * (1.0 - delta2) \
+ B1 * delta1 * (1.0 - delta2) \
+ C1 * delta1 * delta2 \
+ D1 * (1.0 - delta1) * delta2
out2[i] += A2 * (1.0 - delta1) * (1.0 - delta2) \
+ B2 * delta1 * (1.0 - delta2) \
+ C2 * delta1 * delta2 \
+ D2 * (1.0 - delta1) * delta2
if is_flat:
return numpy.asarray(out1), numpy.asarray(out2), None
else:
return numpy.asarray(out1), numpy.asarray(out2), numpy.asarray(out3)
def convert_corner_2D_to_4D(int ndim,
floating[:, ::1] d1 not None,
floating[:, ::1] d2 not None,
floating[:, ::1] d3=None):
"""
Convert 2 (or 3) arrays of corner position into a 4D array of pixel corner coordinates
:param ndim: 2d or 3D output
:param d1: 2D position in dim1 (shape +1)
:param d2: 2D position in dim2 (shape +1)
:param d3: 2D position in dim3 (z) (shape +1)
:return: pos 4D array with position of pixels corners
"""
cdef int64_t shape0, shape1, i, j
# edges position are n+1 compared to number of pixels
shape0 = d1.shape[0] - 1
shape1 = d2.shape[1] - 1
assert d1.shape[0] == d2.shape[0], "d1.shape[0] == d2.shape[0]"
assert d1.shape[1] == d2.shape[1], "d1.shape[1] == d2.shape[1]"
cdef float32_t[:, :, :, ::1] pos = numpy.zeros((shape0, shape1, 4, ndim),
dtype=numpy.float32)
for i in prange(shape0, nogil=True, schedule="static"):
for j in range(shape1):
pos[i, j, 0, ndim - 2] += d1[i, j]
pos[i, j, 0, ndim - 1] += d2[i, j]
pos[i, j, 1, ndim - 2] += d1[i + 1, j]
pos[i, j, 1, ndim - 1] += d2[i + 1, j]
pos[i, j, 2, ndim - 2] += d1[i + 1, j + 1]
pos[i, j, 2, ndim - 1] += d2[i + 1, j + 1]
pos[i, j, 3, ndim - 2] += d1[i, j + 1]
pos[i, j, 3, ndim - 1] += d2[i, j + 1]
if (d3 is not None) and (ndim == 3):
assert d1.shape[0] == d3.shape[0], "d1.shape[0] == d3.shape[0]"
assert d1.shape[1] == d3.shape[1], "d1.shape[1] == d3.shape[1]"
for i in prange(shape0, nogil=True, schedule="static"):
for j in range(shape1):
pos[i, j, 0, 0] += d3[i, j]
pos[i, j, 1, 0] += d3[i + 1, j]
pos[i, j, 2, 0] += d3[i + 1, j + 1]
pos[i, j, 3, 0] += d3[i, j + 1]
return numpy.asarray(pos)
include "bilinear.pxi"
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