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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Project: Fast Azimuthal Integration
# https://github.com/pyFAI/pyFAI
#
# Copyright (C) European Synchrotron Radiation Facility, Grenoble, France
#
# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
"""
Test suites for sparse matrix multiplication modules
"""
import unittest, numpy, os, sys, time
from utilstest import UtilsTest, getLogger
logger = getLogger(__file__)
pyFAI = sys.modules["pyFAI"]
from pyFAI import splitBBox
from pyFAI import splitBBoxCSR
from pyFAI import splitBBoxLUT
import fabio
class TestSparseBBox(unittest.TestCase):
"""Test Azimuthal integration based sparse matrix mutiplication methods
Bounding box pixel splitting
"""
N = 1000
unit = "2th_deg"
ai = pyFAI.load(UtilsTest.getimage("1893/Pilatus1M.poni"))
data = fabio.open(UtilsTest.getimage("1883/Pilatus1M.edf")).data
ref = ai.integrate1d(data, N, correctSolidAngle=False, unit=unit, method="splitBBox")[1]
cython = splitBBox.histoBBox1d(data, ai._ttha, ai._dttha, bins=N)
def test_LUT(self):
obt = self.ai.integrate1d(self.data, self.N, correctSolidAngle=False, unit=self.unit, method="LUT")[1]
logger.debug("delta on global result: %s" % (abs(obt - self.ref) / self.ref).max())
self.assert_(numpy.allclose(obt, self.ref))
cython = self.ai._lut_integrator.integrate(self.data)
for ref, obt in zip(self.cython, cython):
logger.debug("delta on cython result: %s" % (abs(obt - ref) / ref).max())
self.assert_(numpy.allclose(obt, ref))
def test_CSR(self):
obt = self.ai.integrate1d(self.data, self.N, correctSolidAngle=False, unit=self.unit, method="CSR")[1]
logger.debug("delta on global result: %s" % (abs(obt - self.ref) / self.ref).max())
self.assert_(numpy.allclose(obt, self.ref))
cython = self.ai._csr_integrator.integrate(self.data)
for ref, obt in zip(self.cython, cython):
logger.debug("delta on cython result: %s" % (abs(obt - ref) / ref).max())
self.assert_(numpy.allclose(obt, ref))
def test_suite_all_sparse():
testSuite = unittest.TestSuite()
testSuite.addTest(TestSparseBBox("test_LUT"))
testSuite.addTest(TestSparseBBox("test_CSR"))
return testSuite
if __name__ == '__main__':
mysuite = test_suite_all_sparse()
runner = unittest.TextTestRunner()
runner.run(mysuite)
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