コード例 #1
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    def test_from_file_with_file_path(self):
        """Should identify the filepath correctly and parse from it."""

        # should fail with the expected exception
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_fp)

        obs = DissimilarityMatrix.from_file(self.dm_2x2_asym_fp)
        self.assertEqual(self.dm_2x2_asym, obs)
        self.assertTrue(isinstance(obs, DissimilarityMatrix))

        obs = DissimilarityMatrix.from_file(self.dm_3x3_fp)
        self.assertEqual(self.dm_3x3, obs)
        self.assertTrue(isinstance(obs, DissimilarityMatrix))
コード例 #2
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    def test_round_trip_read_write(self):
        """Test reading, writing, and reading again works as expected."""
        for dm_f in self.dm_fs:
            # Read.
            dm1 = DissimilarityMatrix.from_file(dm_f)

            # Write.
            out_f = StringIO()
            dm1.to_file(out_f)
            out_f.seek(0)

            # Read.
            dm2 = DissimilarityMatrix.from_file(out_f)
            self.assertEqual(dm1, dm2)
コード例 #3
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ファイル: test_distance.py プロジェクト: BANSHEE-/scikit-bio
    def test_filter_asymmetric(self):
        # 2x2
        ids = ['b', 'a']
        exp = DissimilarityMatrix([[0, -2], [1, 0]], ids)
        obs = self.dm_2x2_asym.filter(ids)
        self.assertEqual(obs, exp)

        # 3x3
        dm = DissimilarityMatrix([[0, 10, 53], [42, 0, 22.5], [53, 1, 0]],
                                 ('bro', 'brah', 'breh'))
        ids = ['breh', 'brah']
        exp = DissimilarityMatrix([[0, 1], [22.5, 0]], ids)
        obs = dm.filter(ids)
        self.assertEqual(obs, exp)
コード例 #4
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ファイル: test_distance.py プロジェクト: Jorge-C/bipy
    def test_from_file_real_file(self):
        """Should correctly parse a real on-disk file."""
        self.tmp_f.write('\n'.join(DM_3x3_WHITESPACE_F))
        self.tmp_f.seek(0)

        obs = DissimilarityMatrix.from_file(self.tmp_f)
        self.assertEqual(obs, self.dm_3x3)
コード例 #5
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ファイル: test_distance.py プロジェクト: Jorge-C/bipy
    def test_from_file_invalid_input(self):
        """Raises error on ill-formatted dissimilarity matrix file."""
        # Empty dm.
        with self.assertRaises(DissimilarityMatrixFormatError):
            _ = DissimilarityMatrix.from_file([])

        # Number of values don't match number of IDs.
        with self.assertRaises(DissimilarityMatrixFormatError):
            _ = DissimilarityMatrix.from_file(self.bad_dm_f1)

        # Mismatched IDs.
        with self.assertRaises(DissimilarityMatrixFormatError):
            _ = DissimilarityMatrix.from_file(self.bad_dm_f2)

        # Extra data at end.
        with self.assertRaises(DissimilarityMatrixFormatError):
            _ = DissimilarityMatrix.from_file(self.bad_dm_f3)

        # Missing data.
        with self.assertRaises(DissimilarityMatrixFormatError):
            _ = DissimilarityMatrix.from_file(self.bad_dm_f4)

        # Header, but no data.
        with self.assertRaises(DissimilarityMatrixFormatError):
            _ = DissimilarityMatrix.from_file(self.bad_dm_f5)

        # Non-hollow.
        with self.assertRaises(DissimilarityMatrixError):
            _ = DissimilarityMatrix.from_file(self.bad_dm_f6)
コード例 #6
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ファイル: test_distance.py プロジェクト: BANSHEE-/scikit-bio
    def test_filter_subset(self):
        ids = ('c', 'a')
        exp = DissimilarityMatrix([[0, 4.2], [4.2, 0]], ids)
        obs = self.dm_3x3.filter(ids)
        self.assertEqual(obs, exp)

        ids = ('b', 'a')
        exp = DissimilarityMatrix([[0, 0.01], [0.01, 0]], ids)
        obs = self.dm_3x3.filter(ids)
        self.assertEqual(obs, exp)

        # 4x4
        dm = DissimilarityMatrix([[0, 1, 55, 7], [1, 0, 16, 1],
                                  [55, 16, 0, 23], [7, 1, 23, 0]])
        ids = np.asarray(['3', '0', '1'])
        exp = DissimilarityMatrix([[0, 7, 1], [7, 0, 1], [1, 1, 0]], ids)
        obs = dm.filter(ids)
        self.assertEqual(obs, exp)
コード例 #7
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    def test_from_file_real_file(self):
        """Should correctly parse a real on-disk file."""
        with tempfile.TemporaryFile(mode='r+',
                                    prefix='skbio.core.tests.test_distance',
                                    suffix='.txt') as fh:
            fh.write('\n'.join(DM_3x3_WHITESPACE_F))
            fh.seek(0)

            obs = DissimilarityMatrix.from_file(fh)
        self.assertEqual(obs, self.dm_3x3)
コード例 #8
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    def test_init_from_dm(self):
        """Constructs a dm from a dm."""
        ids = ['foo', 'bar', 'baz']

        # DissimilarityMatrix -> DissimilarityMatrix
        exp = DissimilarityMatrix(self.dm_3x3_data, ids)
        obs = DissimilarityMatrix(self.dm_3x3, ids)
        self.assertEqual(obs, exp)
        # Test that copy of data is not made.
        self.assertTrue(obs.data is self.dm_3x3.data)
        obs.data[0, 1] = 424242
        self.assertTrue(np.array_equal(obs.data, self.dm_3x3.data))

        # DistanceMatrix -> DissimilarityMatrix
        exp = DissimilarityMatrix(self.dm_3x3_data, ids)
        obs = DissimilarityMatrix(
            DistanceMatrix(self.dm_3x3_data, ('a', 'b', 'c')), ids)
        self.assertEqual(obs, exp)

        # DissimilarityMatrix -> DistanceMatrix
        with self.assertRaises(DistanceMatrixError):
            DistanceMatrix(self.dm_2x2_asym, ['foo', 'bar'])
コード例 #9
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    def setUp(self):
        super(DissimilarityMatrixTests, self).setUp()

        self.dm_1x1 = DissimilarityMatrix(self.dm_1x1_data, ['a'])
        self.dm_2x2 = DissimilarityMatrix(self.dm_2x2_data, ['a', 'b'])
        self.dm_2x2_asym = DissimilarityMatrix(self.dm_2x2_asym_data,
                                               ['a', 'b'])
        self.dm_3x3 = DissimilarityMatrix(self.dm_3x3_data, ['a', 'b', 'c'])

        self.dms = [self.dm_1x1, self.dm_2x2, self.dm_2x2_asym, self.dm_3x3]
        self.dm_f_lines = [DM_1x1_F, DM_2x2_F, self.dm_2x2_asym_lines,
                           self.dm_3x3_lines]
        self.dm_fs = [self.dm_1x1_f, self.dm_2x2_f, self.dm_2x2_asym_f,
                      self.dm_3x3_f]
        self.dm_shapes = [(1, 1), (2, 2), (2, 2), (3, 3)]
        self.dm_sizes = [1, 4, 4, 9]
        self.dm_transposes = [
            self.dm_1x1, self.dm_2x2,
            DissimilarityMatrix([[0, -2], [1, 0]], ['a', 'b']), self.dm_3x3]
        self.dm_redundant_forms = [np.array(self.dm_1x1_data),
                                   np.array(self.dm_2x2_data),
                                   np.array(self.dm_2x2_asym_data),
                                   np.array(self.dm_3x3_data)]
コード例 #10
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class DissimilarityMatrixTests(DissimilarityMatrixTestData):
    def setUp(self):
        super(DissimilarityMatrixTests, self).setUp()

        self.dm_1x1 = DissimilarityMatrix(self.dm_1x1_data, ['a'])
        self.dm_2x2 = DissimilarityMatrix(self.dm_2x2_data, ['a', 'b'])
        self.dm_2x2_asym = DissimilarityMatrix(self.dm_2x2_asym_data,
                                               ['a', 'b'])
        self.dm_3x3 = DissimilarityMatrix(self.dm_3x3_data, ['a', 'b', 'c'])

        self.dms = [self.dm_1x1, self.dm_2x2, self.dm_2x2_asym, self.dm_3x3]
        self.dm_f_lines = [DM_1x1_F, DM_2x2_F, self.dm_2x2_asym_lines,
                           self.dm_3x3_lines]
        self.dm_fs = [self.dm_1x1_f, self.dm_2x2_f, self.dm_2x2_asym_f,
                      self.dm_3x3_f]
        self.dm_shapes = [(1, 1), (2, 2), (2, 2), (3, 3)]
        self.dm_sizes = [1, 4, 4, 9]
        self.dm_transposes = [
            self.dm_1x1, self.dm_2x2,
            DissimilarityMatrix([[0, -2], [1, 0]], ['a', 'b']), self.dm_3x3]
        self.dm_redundant_forms = [np.array(self.dm_1x1_data),
                                   np.array(self.dm_2x2_data),
                                   np.array(self.dm_2x2_asym_data),
                                   np.array(self.dm_3x3_data)]

    def test_round_trip_read_write(self):
        """Test reading, writing, and reading again works as expected."""
        for dm_f in self.dm_fs:
            # Read.
            dm1 = DissimilarityMatrix.from_file(dm_f)

            # Write.
            out_f = StringIO()
            dm1.to_file(out_f)
            out_f.seek(0)

            # Read.
            dm2 = DissimilarityMatrix.from_file(out_f)
            self.assertEqual(dm1, dm2)

    def test_from_file(self):
        """Should parse and return a valid DissimilarityMatrix given a file."""
        for dm_f, dm in zip(self.dm_fs, self.dms):
            obs = DissimilarityMatrix.from_file(dm_f)
            self.assertEqual(obs, dm)

    def test_from_file_with_file_path(self):
        """Should identify the filepath correctly and parse from it."""

        # should fail with the expected exception
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_fp)

        obs = DissimilarityMatrix.from_file(self.dm_2x2_asym_fp)
        self.assertEqual(self.dm_2x2_asym, obs)
        self.assertTrue(isinstance(obs, DissimilarityMatrix))

        obs = DissimilarityMatrix.from_file(self.dm_3x3_fp)
        self.assertEqual(self.dm_3x3, obs)
        self.assertTrue(isinstance(obs, DissimilarityMatrix))

    def test_from_file_extra_junk(self):
        """Should correctly parse a file with extra whitespace and comments."""
        obs = DissimilarityMatrix.from_file(self.dm_3x3_whitespace_f)
        self.assertEqual(obs, self.dm_3x3)

    def test_from_file_list_of_strings(self):
        """Should correctly parse a list of strings."""
        obs = DissimilarityMatrix.from_file(DM_3x3_WHITESPACE_F)
        self.assertEqual(obs, self.dm_3x3)

    def test_from_file_real_file(self):
        """Should correctly parse a real on-disk file."""
        with tempfile.TemporaryFile(mode='r+',
                                    prefix='skbio.core.tests.test_distance',
                                    suffix='.txt') as fh:
            fh.write('\n'.join(DM_3x3_WHITESPACE_F))
            fh.seek(0)

            obs = DissimilarityMatrix.from_file(fh)
        self.assertEqual(obs, self.dm_3x3)

    def test_from_file_invalid_input(self):
        """Raises error on ill-formatted dissimilarity matrix file."""
        # Empty dm.
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file([])

        # Number of values don't match number of IDs.
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_f1)

        # Mismatched IDs.
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_f2)

        # Extra data at end.
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_f3)

        # Missing data.
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_f4)

        # Header, but no data.
        with self.assertRaises(DissimilarityMatrixFormatError):
            DissimilarityMatrix.from_file(self.bad_dm_f5)

        # Non-hollow.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix.from_file(self.bad_dm_f6)

    def test_to_file(self):
        """Should serialize a DissimilarityMatrix to file."""
        for dm_f_line, dm in zip(self.dm_f_lines, self.dms):
            for file_type in ('file like', 'file name'):
                if file_type == 'file like':
                    obs_f = StringIO()
                    dm.to_file(obs_f)
                    obs = obs_f.getvalue()
                    obs_f.close()
                elif file_type == 'file name':
                    with tempfile.NamedTemporaryFile('r+') as temp_file:
                        dm.to_file(temp_file.name)
                        temp_file.flush()
                        temp_file.seek(0)
                        obs = temp_file.read()
                self.assertEqual(obs, dm_f_line)

    def test_init_from_dm(self):
        """Constructs a dm from a dm."""
        ids = ['foo', 'bar', 'baz']

        # DissimilarityMatrix -> DissimilarityMatrix
        exp = DissimilarityMatrix(self.dm_3x3_data, ids)
        obs = DissimilarityMatrix(self.dm_3x3, ids)
        self.assertEqual(obs, exp)
        # Test that copy of data is not made.
        self.assertTrue(obs.data is self.dm_3x3.data)
        obs.data[0, 1] = 424242
        self.assertTrue(np.array_equal(obs.data, self.dm_3x3.data))

        # DistanceMatrix -> DissimilarityMatrix
        exp = DissimilarityMatrix(self.dm_3x3_data, ids)
        obs = DissimilarityMatrix(
            DistanceMatrix(self.dm_3x3_data, ('a', 'b', 'c')), ids)
        self.assertEqual(obs, exp)

        # DissimilarityMatrix -> DistanceMatrix
        with self.assertRaises(DistanceMatrixError):
            DistanceMatrix(self.dm_2x2_asym, ['foo', 'bar'])

    def test_init_no_ids(self):
        exp = DissimilarityMatrix(self.dm_3x3_data, ('0', '1', '2'))
        obs = DissimilarityMatrix(self.dm_3x3_data)
        self.assertEqual(obs, exp)
        self.assertEqual(obs['1', '2'], 12.0)

    def test_init_invalid_input(self):
        """Raises error on invalid dissimilarity matrix data / IDs."""
        # Empty data.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix([], [])

        # Another type of empty data.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix(np.empty((0, 0)), [])

        # Invalid number of dimensions.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix([1, 2, 3], ['a'])

        # Dimensions don't match.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix([[1, 2, 3]], ['a'])

        data = [[0, 1], [1, 0]]

        # Duplicate IDs.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix(data, ['a', 'a'])

        # Number of IDs don't match dimensions.
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix(data, ['a', 'b', 'c'])

        # Non-hollow.
        data = [[0.0, 1.0], [1.0, 0.01]]
        with self.assertRaises(DissimilarityMatrixError):
            DissimilarityMatrix(data, ['a', 'b'])

    def test_data(self):
        """Test retrieving/setting data matrix."""
        for dm, exp in zip(self.dms, self.dm_redundant_forms):
            obs = dm.data
            self.assertTrue(np.array_equal(obs, exp))

        with self.assertRaises(AttributeError):
            self.dm_3x3.data = 'foo'

    def test_ids(self):
        """Test retrieving/setting IDs."""
        obs = self.dm_3x3.ids
        self.assertEqual(obs, ('a', 'b', 'c'))

        # Test that we overwrite the existing IDs and that the ID index is
        # correctly rebuilt.
        new_ids = ['foo', 'bar', 'baz']
        self.dm_3x3.ids = new_ids
        obs = self.dm_3x3.ids
        self.assertEqual(obs, tuple(new_ids))
        self.assertTrue(np.array_equal(self.dm_3x3['bar'],
                                       np.array([0.01, 0.0, 12.0])))
        with self.assertRaises(MissingIDError):
            self.dm_3x3['b']

    def test_ids_invalid_input(self):
        """Test setting invalid IDs raises an error."""
        with self.assertRaises(DissimilarityMatrixError):
            self.dm_3x3.ids = ['foo', 'bar']
        # Make sure that we can still use the dissimilarity matrix after trying
        # to be evil.
        obs = self.dm_3x3.ids
        self.assertEqual(obs, ('a', 'b', 'c'))

    def test_dtype(self):
        """Test retrieving dtype of data matrix."""
        for dm in self.dms:
            self.assertEqual(dm.dtype, np.float64)

    def test_shape(self):
        """Test retrieving shape of data matrix."""
        for dm, shape in zip(self.dms, self.dm_shapes):
            self.assertEqual(dm.shape, shape)

    def test_size(self):
        """Test retrieving size of data matrix."""
        for dm, size in zip(self.dms, self.dm_sizes):
            self.assertEqual(dm.size, size)

    def test_transpose(self):
        """Test retrieving transpose of dissimilarity matrix."""
        for dm, transpose in zip(self.dms, self.dm_transposes):
            self.assertEqual(dm.T, transpose)
            self.assertEqual(dm.transpose(), transpose)
            # We should get a reference to a different object back, even if the
            # transpose is the same as the original.
            self.assertTrue(dm.transpose() is not dm)

    def test_redundant_form(self):
        """Test retrieving the data matrix in redundant form."""
        for dm, redundant in zip(self.dms, self.dm_redundant_forms):
            obs = dm.redundant_form()
            self.assertTrue(np.array_equal(obs, redundant))

    def test_copy(self):
        """Test correct copying of a DissimilarityMatrix."""
        copy = self.dm_2x2.copy()
        self.assertEqual(copy, self.dm_2x2)
        self.assertFalse(copy.data is self.dm_2x2.data)
        # deepcopy doesn't actually create a copy of the IDs because it is a
        # tuple of strings, which is fully immutable.
        self.assertTrue(copy.ids is self.dm_2x2.ids)

        new_ids = ['hello', 'world']
        copy.ids = new_ids
        self.assertNotEqual(copy.ids, self.dm_2x2.ids)

        copy = self.dm_2x2.copy()
        copy.data[0, 1] = 0.0001
        self.assertFalse(np.array_equal(copy.data, self.dm_2x2.data))

    def test_str(self):
        """Test retrieving string representation of a DissimilarityMatrix."""
        for dm in self.dms:
            obs = str(dm)
            # Do some very light testing here to make sure we're getting a
            # non-empty string back. We don't want to test the exact
            # formatting.
            self.assertTrue(obs)

    def test_eq(self):
        """DissimilarityMatrix equality test functions correctly."""
        for dm in self.dms:
            copy = dm.copy()
            self.assertTrue(dm == dm)
            self.assertTrue(copy == copy)
            self.assertTrue(dm == copy)
            self.assertTrue(copy == dm)

        self.assertFalse(self.dm_1x1 == self.dm_3x3)

    def test_ne(self):
        """Test unequal dms are identified as such."""
        # Wrong class.
        self.assertTrue(self.dm_3x3 != 'foo')

        # Wrong shape.
        self.assertTrue(self.dm_3x3 != self.dm_1x1)

        # Wrong IDs.
        other = self.dm_3x3.copy()
        other.ids = ['foo', 'bar', 'baz']
        self.assertTrue(self.dm_3x3 != other)

        # Wrong data.
        other = self.dm_3x3.copy()
        other.data[1, 0] = 42.42
        self.assertTrue(self.dm_3x3 != other)

        self.assertFalse(self.dm_2x2 != self.dm_2x2)

    def test_getslice(self):
        """Test that __getslice__ defers to __getitem__."""
        # Slice of first dimension only.
        obs = self.dm_2x2[1:]
        self.assertTrue(np.array_equal(obs, np.array([[0.123, 0.0]])))
        self.assertEqual(type(obs), np.ndarray)

    def test_getitem_by_id(self):
        """Test retrieving row vectors by ID."""
        obs = self.dm_1x1['a']
        self.assertTrue(np.array_equal(obs, np.array([0.0])))

        obs = self.dm_2x2_asym['b']
        self.assertTrue(np.array_equal(obs, np.array([-2.0, 0.0])))

        obs = self.dm_3x3['c']
        self.assertTrue(np.array_equal(obs, np.array([4.2, 12.0, 0.0])))

        with self.assertRaises(MissingIDError):
            self.dm_2x2['c']

    def test_getitem_by_id_pair(self):
        """Test retrieving elements by ID pair."""
        # Same object.
        self.assertEqual(self.dm_1x1['a', 'a'], 0.0)

        # Different objects (symmetric).
        self.assertEqual(self.dm_3x3['b', 'c'], 12.0)
        self.assertEqual(self.dm_3x3['c', 'b'], 12.0)

        # Different objects (asymmetric).
        self.assertEqual(self.dm_2x2_asym['a', 'b'], 1.0)
        self.assertEqual(self.dm_2x2_asym['b', 'a'], -2.0)

        with self.assertRaises(MissingIDError):
            self.dm_2x2['a', 'c']

    def test_getitem_ndarray_indexing(self):
        """Test __getitem__ delegates to underlying ndarray."""
        # Single element access.
        obs = self.dm_3x3[0, 1]
        self.assertEqual(obs, 0.01)

        # Single element access (via two __getitem__ calls).
        obs = self.dm_3x3[0][1]
        self.assertEqual(obs, 0.01)

        # Row access.
        obs = self.dm_3x3[1]
        self.assertTrue(np.array_equal(obs, np.array([0.01, 0.0, 12.0])))
        self.assertEqual(type(obs), np.ndarray)

        # Grab all data.
        obs = self.dm_3x3[:, :]
        self.assertTrue(np.array_equal(obs, self.dm_3x3.data))
        self.assertEqual(type(obs), np.ndarray)

        with self.assertRaises(IndexError):
            self.dm_3x3[:, 3]

    def test_parse_ids(self):
        """Empty stub: DissimilarityMatrix._parse_ids tested elsewhere."""
        pass

    def test_validate(self):
        """Empty stub: DissimilarityMatrix._validate tested elsewhere."""
        pass

    def test_index_list(self):
        """Empty stub: DissimilarityMatrix._index_list tested elsewhere."""
        pass

    def test_is_id_pair(self):
        """Empty stub: DissimilarityMatrix._is_id_pair tested elsewhere."""
        pass

    def test_format_ids(self):
        """Empty stub: DissimilarityMatrix._format_ids tested elsewhere."""
        pass

    def test_pprint_ids(self):
        """Test pretty-print formatting of IDs."""
        # No truncation.
        exp = 'a, b, c'
        obs = self.dm_3x3._pprint_ids()
        self.assertEqual(obs, exp)

        # Truncation.
        exp = 'a, b, ...'
        obs = self.dm_3x3._pprint_ids(max_chars=5)
        self.assertEqual(obs, exp)
コード例 #11
0
 def test_from_file_list_of_strings(self):
     """Should correctly parse a list of strings."""
     obs = DissimilarityMatrix.from_file(DM_3x3_WHITESPACE_F)
     self.assertEqual(obs, self.dm_3x3)
コード例 #12
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 def test_from_file_extra_junk(self):
     """Should correctly parse a file with extra whitespace and comments."""
     obs = DissimilarityMatrix.from_file(self.dm_3x3_whitespace_f)
     self.assertEqual(obs, self.dm_3x3)
コード例 #13
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 def test_from_file(self):
     """Should parse and return a valid DissimilarityMatrix given a file."""
     for dm_f, dm in zip(self.dm_fs, self.dms):
         obs = DissimilarityMatrix.from_file(dm_f)
         self.assertEqual(obs, dm)