1 files changed, 0 insertions, 453 deletions
diff --git a/silx/utils/test/test_array_like.py b/silx/utils/test/test_array_like.py
deleted file mode 100644
index 7cd004c..0000000
--- a/silx/utils/test/test_array_like.py
+++ /dev/null
@@ -1,453 +0,0 @@
-# coding: utf-8
-# /*##########################################################################
-#
-# Copyright (c) 2016-2017 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 for array_like module"""
-
-__authors__ = ["P. Knobel"]
-__license__ = "MIT"
-__date__ = "09/01/2017"
-
-try:
-    import h5py
-except ImportError:
-    h5py = None
-
-import numpy
-import os
-import tempfile
-import unittest
-
-from ..array_like import DatasetView, ListOfImages
-from ..array_like import get_dtype, get_concatenated_dtype, get_shape,\
-    is_array, is_nested_sequence, is_list_of_arrays
-
-
-@unittest.skipIf(h5py is None,
-                 "h5py is needed to test DatasetView")
-class TestTransposedDatasetView(unittest.TestCase):
-
-    def setUp(self):
-        # dataset attributes
-        self.ndim = 3
-        self.original_shape = (5, 10, 20)
-        self.size = 1
-        for dim in self.original_shape:
-            self.size *= dim
-
-        self.volume = numpy.arange(self.size).reshape(self.original_shape)
-
-        self.tempdir = tempfile.mkdtemp()
-        self.h5_fname = os.path.join(self.tempdir, "tempfile.h5")
-        with h5py.File(self.h5_fname, "w") as f:
-            f["volume"] = self.volume
-
-        self.h5f = h5py.File(self.h5_fname, "r")
-
-        self.all_permutations = [(0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0),
-                                 (2, 0, 1), (2, 1, 0)]
-
-    def tearDown(self):
-        self.h5f.close()
-        os.unlink(self.h5_fname)
-        os.rmdir(self.tempdir)
-
-    def _testSize(self, obj):
-        """These assertions apply to all following test cases"""
-        self.assertEqual(obj.ndim, self.ndim)
-        self.assertEqual(obj.size, self.size)
-        size_from_shape = 1
-        for dim in obj.shape:
-            size_from_shape *= dim
-        self.assertEqual(size_from_shape, self.size)
-
-        for dim in self.original_shape:
-            self.assertIn(dim, obj.shape)
-
-    def testNoTransposition(self):
-        """no transposition (transposition = (0, 1, 2))"""
-        a = DatasetView(self.h5f["volume"])
-
-        self.assertEqual(a.shape, self.original_shape)
-        self._testSize(a)
-
-        # reversing the dimensions twice results in no change
-        rtrans = list(reversed(range(self.ndim)))
-        self.assertTrue(numpy.array_equal(
-                a,
-                a.transpose(rtrans).transpose(rtrans)))
-
-        for i in range(a.shape[0]):
-            for j in range(a.shape[1]):
-                for k in range(a.shape[2]):
-                    self.assertEqual(self.h5f["volume"][i, j, k],
-                                     a[i, j, k])
-
-    def _testTransposition(self, transposition):
-        """test transposed dataset
-
-        :param tuple transposition: List of dimensions (0... n-1) sorted
-            in the desired order
-        """
-        a = DatasetView(self.h5f["volume"],
-                        transposition=transposition)
-        self._testSize(a)
-
-        # sort shape of transposed object, to hopefully find the original shape
-        sorted_shape = tuple(dim_size for (_, dim_size) in
-                             sorted(zip(transposition, a.shape)))
-        self.assertEqual(sorted_shape, self.original_shape)
-
-        a_as_array = numpy.array(self.h5f["volume"]).transpose(transposition)
-
-        # test the __array__ method
-        self.assertTrue(numpy.array_equal(
-                numpy.array(a),
-                a_as_array))
-
-        # test slicing
-        for selection in [(2, slice(None), slice(None)),
-                          (slice(None), 1, slice(0, 8)),
-                          (slice(0, 3), slice(None), 3),
-                          (1, 3, slice(None)),
-                          (slice(None), 2, 1),
-                          (4, slice(1, 9, 2), 2)]:
-            self.assertIsInstance(a[selection], numpy.ndarray)
-            self.assertTrue(numpy.array_equal(
-                    a[selection],
-                    a_as_array[selection]))
-
-        # test the DatasetView.__getitem__ for single values
-        # (step adjusted to test at least 3 indices in each dimension)
-        for i in range(0, a.shape[0], a.shape[0] // 3):
-            for j in range(0, a.shape[1], a.shape[1] // 3):
-                for k in range(0, a.shape[2], a.shape[2] // 3):
-                    sorted_indices = tuple(idx for (_, idx) in
-                                           sorted(zip(transposition, [i, j, k])))
-                    viewed_value = a[i, j, k]
-                    corresponding_original_value = self.h5f["volume"][sorted_indices]
-                    self.assertEqual(viewed_value,
-                                     corresponding_original_value)
-
-        # reversing the dimensions twice results in no change
-        rtrans = list(reversed(range(self.ndim)))
-        self.assertTrue(numpy.array_equal(
-                a,
-                a.transpose(rtrans).transpose(rtrans)))
-
-        # test .T property
-        self.assertTrue(numpy.array_equal(
-                a.T,
-                a.transpose(rtrans)))
-
-    def testTransposition012(self):
-        """transposition = (0, 1, 2)
-        (should be the same as testNoTransposition)"""
-        self._testTransposition((0, 1, 2))
-
-    def testTransposition021(self):
-        """transposition = (0, 2, 1)"""
-        self._testTransposition((0, 2, 1))
-
-    def testTransposition102(self):
-        """transposition = (1, 0, 2)"""
-        self._testTransposition((1, 0, 2))
-
-    def testTransposition120(self):
-        """transposition = (1, 2, 0)"""
-        self._testTransposition((1, 2, 0))
-
-    def testTransposition201(self):
-        """transposition = (2, 0, 1)"""
-        self._testTransposition((2, 0, 1))
-
-    def testTransposition210(self):
-        """transposition = (2, 1, 0)"""
-        self._testTransposition((2, 1, 0))
-
-    def testAllDoubleTranspositions(self):
-        for trans1 in self.all_permutations:
-            for trans2 in self.all_permutations:
-                self._testDoubleTransposition(trans1, trans2)
-
-    def _testDoubleTransposition(self, transposition1, transposition2):
-        a = DatasetView(self.h5f["volume"],
-                        transposition=transposition1).transpose(transposition2)
-
-        b = self.volume.transpose(transposition1).transpose(transposition2)
-
-        self.assertTrue(numpy.array_equal(a, b),
-                        "failed with double transposition %s %s" % (transposition1, transposition2))
-
-    def test1DIndex(self):
-        a = DatasetView(self.h5f["volume"])
-        self.assertTrue(numpy.array_equal(self.volume[1],
-                                          a[1]))
-
-        b = DatasetView(self.h5f["volume"], transposition=(1, 0, 2))
-        self.assertTrue(numpy.array_equal(self.volume[:, 1, :],
-                                          b[1]))
-
-
-class TestTransposedListOfImages(unittest.TestCase):
-    def setUp(self):
-        # images attributes
-        self.ndim = 3
-        self.original_shape = (5, 10, 20)
-        self.size = 1
-        for dim in self.original_shape:
-            self.size *= dim
-
-        volume = numpy.arange(self.size).reshape(self.original_shape)
-
-        self.images = []
-        for i in range(self.original_shape[0]):
-            self.images.append(
-                    volume[i])
-
-        self.images_as_3D_array = numpy.array(self.images)
-
-        self.all_permutations = [(0, 1, 2), (0, 2, 1), (1, 0, 2), (1, 2, 0),
-                                 (2, 0, 1), (2, 1, 0)]
-
-    def tearDown(self):
-        pass
-
-    def _testSize(self, obj):
-        """These assertions apply to all following test cases"""
-        self.assertEqual(obj.ndim, self.ndim)
-        self.assertEqual(obj.size, self.size)
-        size_from_shape = 1
-        for dim in obj.shape:
-            size_from_shape *= dim
-        self.assertEqual(size_from_shape, self.size)
-
-        for dim in self.original_shape:
-            self.assertIn(dim, obj.shape)
-
-    def testNoTransposition(self):
-        """no transposition (transposition = (0, 1, 2))"""
-        a = ListOfImages(self.images)
-
-        self.assertEqual(a.shape, self.original_shape)
-        self._testSize(a)
-
-        for i in range(a.shape[0]):
-            for j in range(a.shape[1]):
-                for k in range(a.shape[2]):
-                    self.assertEqual(self.images[i][j, k],
-                                     a[i, j, k])
-
-        # reversing the dimensions twice results in no change
-        rtrans = list(reversed(range(self.ndim)))
-        self.assertTrue(numpy.array_equal(
-                a,
-                a.transpose(rtrans).transpose(rtrans)))
-
-        # test .T property
-        self.assertTrue(numpy.array_equal(
-                a.T,
-                a.transpose(rtrans)))
-
-    def _testTransposition(self, transposition):
-        """test transposed dataset
-
-        :param tuple transposition: List of dimensions (0... n-1) sorted
-            in the desired order
-        """
-        a = ListOfImages(self.images,
-                         transposition=transposition)
-        self._testSize(a)
-
-        # sort shape of transposed object, to hopefully find the original shape
-        sorted_shape = tuple(dim_size for (_, dim_size) in
-                             sorted(zip(transposition, a.shape)))
-        self.assertEqual(sorted_shape, self.original_shape)
-
-        a_as_array = numpy.array(self.images).transpose(transposition)
-
-        # test the DatasetView.__array__ method
-        self.assertTrue(numpy.array_equal(
-                numpy.array(a),
-                a_as_array))
-
-        # test slicing
-        for selection in [(2, slice(None), slice(None)),
-                          (slice(None), 1, slice(0, 8)),
-                          (slice(0, 3), slice(None), 3),
-                          (1, 3, slice(None)),
-                          (slice(None), 2, 1),
-                          (4, slice(1, 9, 2), 2)]:
-            self.assertIsInstance(a[selection], numpy.ndarray)
-            self.assertTrue(numpy.array_equal(
-                    a[selection],
-                    a_as_array[selection]))
-
-        # test the DatasetView.__getitem__ for single values
-        # (step adjusted to test at least 3 indices in each dimension)
-        for i in range(0, a.shape[0], a.shape[0] // 3):
-            for j in range(0, a.shape[1], a.shape[1] // 3):
-                for k in range(0, a.shape[2], a.shape[2] // 3):
-                    viewed_value = a[i, j, k]
-                    sorted_indices = tuple(idx for (_, idx) in
-                                           sorted(zip(transposition, [i, j, k])))
-                    corresponding_original_value = self.images[sorted_indices[0]][sorted_indices[1:]]
-                    self.assertEqual(viewed_value,
-                                     corresponding_original_value)
-
-        # reversing the dimensions twice results in no change
-        rtrans = list(reversed(range(self.ndim)))
-        self.assertTrue(numpy.array_equal(
-                a,
-                a.transpose(rtrans).transpose(rtrans)))
-
-        # test .T property
-        self.assertTrue(numpy.array_equal(
-                a.T,
-                a.transpose(rtrans)))
-
-    def _testDoubleTransposition(self, transposition1, transposition2):
-        a = ListOfImages(self.images,
-                         transposition=transposition1).transpose(transposition2)
-
-        b = self.images_as_3D_array.transpose(transposition1).transpose(transposition2)
-
-        self.assertTrue(numpy.array_equal(a, b),
-                        "failed with double transposition %s %s" % (transposition1, transposition2))
-
-    def testTransposition012(self):
-        """transposition = (0, 1, 2)
-        (should be the same as testNoTransposition)"""
-        self._testTransposition((0, 1, 2))
-
-    def testTransposition021(self):
-        """transposition = (0, 2, 1)"""
-        self._testTransposition((0, 2, 1))
-
-    def testTransposition102(self):
-        """transposition = (1, 0, 2)"""
-        self._testTransposition((1, 0, 2))
-
-    def testTransposition120(self):
-        """transposition = (1, 2, 0)"""
-        self._testTransposition((1, 2, 0))
-
-    def testTransposition201(self):
-        """transposition = (2, 0, 1)"""
-        self._testTransposition((2, 0, 1))
-
-    def testTransposition210(self):
-        """transposition = (2, 1, 0)"""
-        self._testTransposition((2, 1, 0))
-
-    def testAllDoubleTranspositions(self):
-        for trans1 in self.all_permutations:
-            for trans2 in self.all_permutations:
-                self._testDoubleTransposition(trans1, trans2)
-
-    def test1DIndex(self):
-        a = ListOfImages(self.images)
-        self.assertTrue(numpy.array_equal(self.images[1],
-                                          a[1]))
-
-        b = ListOfImages(self.images, transposition=(1, 0, 2))
-        self.assertTrue(numpy.array_equal(self.images_as_3D_array[:, 1, :],
-                                          b[1]))
-
-
-class TestFunctions(unittest.TestCase):
-    """Test functions to guess the dtype and shape of an array_like
-    object"""
-    def testListOfLists(self):
-        l = [[0, 1, 2], [2, 3, 4]]
-        self.assertEqual(get_dtype(l),
-                         numpy.dtype(int))
-        self.assertEqual(get_shape(l),
-                         (2, 3))
-        self.assertTrue(is_nested_sequence(l))
-        self.assertFalse(is_array(l))
-        self.assertFalse(is_list_of_arrays(l))
-
-        l = [[0., 1.], [2., 3.]]
-        self.assertEqual(get_dtype(l),
-                         numpy.dtype(float))
-        self.assertEqual(get_shape(l),
-                         (2, 2))
-        self.assertTrue(is_nested_sequence(l))
-        self.assertFalse(is_array(l))
-        self.assertFalse(is_list_of_arrays(l))
-
-        # concatenated dtype of int and float
-        l = [numpy.array([[0, 1, 2], [2, 3, 4]]),
-             numpy.array([[0., 1., 2.], [2., 3., 4.]])]
-
-        self.assertEqual(get_concatenated_dtype(l),
-                         numpy.array(l).dtype)
-        self.assertEqual(get_shape(l),
-                         (2, 2, 3))
-        self.assertFalse(is_nested_sequence(l))
-        self.assertFalse(is_array(l))
-        self.assertTrue(is_list_of_arrays(l))
-
-    def testNumpyArray(self):
-        a = numpy.array([[0, 1], [2, 3]])
-        self.assertEqual(get_dtype(a),
-                         a.dtype)
-        self.assertFalse(is_nested_sequence(a))
-        self.assertTrue(is_array(a))
-        self.assertFalse(is_list_of_arrays(a))
-
-    @unittest.skipIf(h5py is None,
-                     "h5py is needed for this test")
-    def testH5pyDataset(self):
-        a = numpy.array([[0, 1], [2, 3]])
-
-        tempdir = tempfile.mkdtemp()
-        h5_fname = os.path.join(tempdir, "tempfile.h5")
-        with h5py.File(h5_fname, "w") as h5f:
-            h5f["dataset"] = a
-            d = h5f["dataset"]
-
-            self.assertEqual(get_dtype(d),
-                             numpy.dtype(int))
-            self.assertFalse(is_nested_sequence(d))
-            self.assertTrue(is_array(d))
-            self.assertFalse(is_list_of_arrays(d))
-
-        os.unlink(h5_fname)
-        os.rmdir(tempdir)
-
-
-def suite():
-    test_suite = unittest.TestSuite()
-    test_suite.addTest(
-        unittest.defaultTestLoader.loadTestsFromTestCase(TestTransposedDatasetView))
-    test_suite.addTest(
-        unittest.defaultTestLoader.loadTestsFromTestCase(TestTransposedListOfImages))
-    test_suite.addTest(
-        unittest.defaultTestLoader.loadTestsFromTestCase(TestFunctions))
-    return test_suite
-
-
-if __name__ == '__main__':
-    unittest.main(defaultTest='suite')