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#!/usr/bin/env python
# coding: utf-8
#
# Project: Azimuthal integration
# https://github.com/silx-kit/pyFAI
#
# Copyright (C) 2015-2018 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.
"test suite for dark_current / flat_field correction"
__author__ = "Jérôme Kieffer"
__contact__ = "Jerome.Kieffer@ESRF.eu"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__date__ = "21/01/2021"
import unittest
import numpy
import sys
import logging
logger = logging.getLogger(__name__)
pyFAI = sys.modules["pyFAI"]
from ..opencl import ocl
from .utilstest import UtilsTest
from ..azimuthalIntegrator import AzimuthalIntegrator
from ..method_registry import IntegrationMethod
class TestFlat1D(unittest.TestCase):
def setUp(self):
unittest.TestCase.setUp(self)
self.shape = 640, 480
self.flat = 1.0 + numpy.random.random(self.shape)
self.dark = numpy.random.random(self.shape)
self.raw = self.flat + self.dark
self.eps = 1e-6
self.ai = AzimuthalIntegrator()
self.ai.setFit2D(directDist=1, centerX=self.shape[1] // 2, centerY=self.shape[0] // 2, pixelX=1, pixelY=1)
self.bins = 500
def tearDown(self):
unittest.TestCase.tearDown(self)
self.shape = None
self.flat = None
self.dark = None
self.raw = None
self.eps = None
self.ai = None
self.bins = None
def test_no_correct(self):
result = self.ai.integrate1d_ng(self.raw, self.bins, unit="r_mm", correctSolidAngle=False)
I = result.intensity
logger.info("1D Without correction Imin=%s Imax=%s <I>=%s std=%s", I.min(), I.max(), I.mean(), I.std())
self.assertNotAlmostEqual(I.mean(), 1, 2, "Mean should not be 1")
self.assertFalse(I.max() - I.min() < self.eps, "deviation should be large")
def test_correct(self):
for meth in IntegrationMethod._registry.values():
if meth.dimension != 1: continue
res = self.ai.integrate1d_ng(self.raw, self.bins, unit="r_mm", method=meth, correctSolidAngle=False, dark=self.dark, flat=self.flat)
if meth.target_name and meth.algo_lower == "histogram":
"OpenCL atomic are not that good !"
eps = 3 * self.eps
else:
eps = self.eps
_, I = res
logger.info("1D method:%s Imin=%s Imax=%s <I>=%s std=%s", str(meth), I.min(), I.max(), I.mean(), I.std())
self.assertAlmostEqual(I.mean(), 1, 2, "Mean should be 1 in %s" % meth)
self.assertLess(I.max() - I.min(), eps, "deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()))
class TestFlat2D(unittest.TestCase):
def setUp(self):
self.shape = 640, 480
self.flat = 1 + numpy.random.random(self.shape)
self.dark = numpy.random.random(self.shape)
self.raw = self.flat + self.dark
self.eps = 1e-6
self.ai = AzimuthalIntegrator()
self.ai.setFit2D(directDist=1, centerX=self.shape[1] // 2, centerY=self.shape[0] // 2, pixelX=1, pixelY=1)
self.bins = 500
self.azim = 360
def tearDown(self):
self.shape = None
self.flat = None
self.dark = None
self.raw = None
self.eps = None
self.ai = None
self.bins = None
self.azim = None
def test_no_correct(self):
I, _, _ = self.ai.integrate2d(self.raw, self.bins, self.azim, unit="r_mm", correctSolidAngle=False)
I = I[numpy.where(I > 0)]
logger.info("2D Without correction Imin=%s Imax=%s <I>=%s std=%s", I.min(), I.max(), I.mean(), I.std())
self.assertNotAlmostEqual(I.mean(), 1, 2, "Mean should not be 1")
self.assertFalse(I.max() - I.min() < self.eps, "deviation should be large")
def test_correct(self):
test2d = {"numpy": self.eps,
"cython": self.eps,
"splitbbox": self.eps,
"splitpix": self.eps,
"lut": self.eps,
}
if ocl and UtilsTest.opencl:
for device in ["cpu", "gpu", "acc"]:
if ocl.select_device(dtype=device):
test2d["lut_ocl_%s" % device] = self.eps
test2d["csr_ocl_%s" % device] = self.eps
for meth in test2d:
logger.info("About to test2d %s", meth)
try:
I, _, _ = self.ai.integrate2d(self.raw, self.bins, self.azim, unit="r_mm", method=meth, correctSolidAngle=False, dark=self.dark, flat=self.flat)
except (MemoryError, pyFAI.opencl.pyopencl.MemoryError):
logger.warning("Got MemoryError from OpenCL device")
continue
I = I[numpy.where(I > 0)]
logger.info("2D method:%s Imin=%s Imax=%s <I>=%s std=%s", meth, I.min(), I.max(), I.mean(), I.std())
self.assertAlmostEqual(I.mean(), 1, 2, "Mean should be 1 in %s" % meth)
self.assertTrue(I.max() - I.min() < test2d[meth], "deviation should be small with meth %s, got %s" % (meth, I.max() - I.min()))
def suite():
testsuite = unittest.TestSuite()
loader = unittest.defaultTestLoader.loadTestsFromTestCase
testsuite.addTest(loader(TestFlat1D))
testsuite.addTest(loader(TestFlat2D))
return testsuite
if __name__ == '__main__':
runner = unittest.TextTestRunner()
runner.run(suite())
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