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Diffstat (limited to 'silx/math/test/test_combo.py')
| -rw-r--r-- | silx/math/test/test_combo.py | 168 |
1 files changed, 168 insertions, 0 deletions
diff --git a/silx/math/test/test_combo.py b/silx/math/test/test_combo.py new file mode 100644 index 0000000..92eb8b4 --- /dev/null +++ b/silx/math/test/test_combo.py @@ -0,0 +1,168 @@ +# coding: utf-8 +# /*########################################################################## +# Copyright (C) 2016 European Synchrotron Radiation Facility +# +# 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. +# +# ############################################################################*/ +"""Tests of the combo module""" + +from __future__ import division + +__authors__ = ["T. Vincent"] +__license__ = "MIT" +__date__ = "20/12/2016" + + +import unittest + +import numpy + +from silx.test.utils import ParametricTestCase + +from silx.math.combo import min_max + + +class TestMinMax(ParametricTestCase): + """Tests of min max combo""" + + FLOATING_DTYPES = 'float32', 'float64' + SIGNED_INT_DTYPES = 'uint8', 'uint16', 'uint32', 'uint64' + UNSIGNED_INT_DTYPES = 'uint8', 'uint16', 'uint32', 'uint64' + DTYPES = FLOATING_DTYPES + SIGNED_INT_DTYPES + UNSIGNED_INT_DTYPES + + def _test_min_max(self, data, min_positive): + """Compare min_max with numpy for the given dataset + + :param numpy.ndarray data: Data set to use for test + :param bool min_positive: True to test with positive min + """ + result = min_max(data, min_positive) + + minimum = numpy.nanmin(data) + if numpy.isnan(minimum): # All NaNs + self.assertTrue(numpy.isnan(result.minimum)) + self.assertEqual(result.argmin, 0) + + else: + self.assertEqual(result.minimum, minimum) + + argmin = numpy.where(data == minimum)[0][0] + self.assertEqual(result.argmin, argmin) + + maximum = numpy.nanmax(data) + if numpy.isnan(maximum): # All NaNs + self.assertTrue(numpy.isnan(result.maximum)) + self.assertEqual(result.argmax, 0) + + else: + self.assertEqual(result.maximum, maximum) + + argmax = numpy.where(data == maximum)[0][0] + self.assertEqual(result.argmax, argmax) + + if min_positive: + pos_data = data[data > 0] + if len(pos_data) > 0: + min_pos = numpy.min(pos_data) + argmin_pos = numpy.where(data == min_pos)[0][0] + else: + min_pos = None + argmin_pos = None + self.assertEqual(result.min_positive, min_pos) + self.assertEqual(result.argmin_positive, argmin_pos) + + def test_different_datasets(self): + """Test min_max with different numpy.arange datasets.""" + size = 1000 + + for dtype in self.DTYPES: + + tests = { + '0 to N': (0, 1), + 'N-1 to 0': (size - 1, -1)} + if dtype not in self.UNSIGNED_INT_DTYPES: + tests['N/2 to -N/2'] = size // 2, -1 + tests['0 to -N'] = 0, -1 + + for name, (start, step) in tests.items(): + for min_positive in (True, False): + with self.subTest(dtype=dtype, + min_positive=min_positive, + data=name): + data = numpy.arange( + start, start + step * size, step, dtype=dtype) + + self._test_min_max(data, min_positive) + + def test_nodata(self): + """Test min_max with None and empty array""" + for dtype in self.DTYPES: + with self.subTest(dtype=dtype): + with self.assertRaises(TypeError): + min_max(None) + + data = numpy.array((), dtype=dtype) + with self.assertRaises(ValueError): + min_max(data) + + def test_nandata(self): + """Test min_max with NaN in data""" + tests = [ + (float('nan'), float('nan')), # All NaNs + (float('nan'), 1.0), # NaN first and positive + (float('nan'), -1.0), # NaN first and negative + (1.0, 2.0, float('nan')), # NaN last and positive + (-1.0, -2.0, float('nan')), # NaN last and negative + (1.0, float('nan'), -1.0), # Some NaN + ] + + for dtype in self.FLOATING_DTYPES: + for data in tests: + with self.subTest(dtype=dtype, data=data): + data = numpy.array(data, dtype=dtype) + self._test_min_max(data, min_positive=True) + + def test_infdata(self): + """Test min_max with inf.""" + tests = [ + [float('inf')] * 3, # All +inf + [float('inf')] * 3, # All -inf + (float('inf'), float('-inf')), # + and - inf + (float('inf'), float('-inf'), float('nan')), # +/-inf, nan last + (float('nan'), float('-inf'), float('inf')), # +/-inf, nan first + (float('inf'), float('nan'), float('-inf')), # +/-inf, nan center + ] + + for dtype in self.FLOATING_DTYPES: + for data in tests: + with self.subTest(dtype=dtype, data=data): + data = numpy.array(data, dtype=dtype) + self._test_min_max(data, min_positive=True) + + +def suite(): + test_suite = unittest.TestSuite() + test_suite.addTests( + unittest.defaultTestLoader.loadTestsFromTestCase(TestMinMax)) + return test_suite + + +if __name__ == '__main__': + unittest.main(defaultTest="suite") |