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)
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_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_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_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_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)
def test_init_invalid_input(self): # Requires a DistanceMatrix. with self.assertRaises(TypeError): CategoricalStats(DissimilarityMatrix([[0, 2], [3, 0]], ['a', 'b']), [1, 2]) # Requires column if DataFrame. with self.assertRaises(ValueError): CategoricalStats(self.dm, self.df) # Cannot provide column if not data frame. with self.assertRaises(ValueError): CategoricalStats(self.dm, self.grouping, column='Group') # Column must exist in data frame. with self.assertRaises(ValueError): CategoricalStats(self.dm, self.df, column='foo') # All distance matrix IDs must be in data frame. with self.assertRaises(ValueError): CategoricalStats(self.dm, self.df_missing_id, column='Group') # Grouping vector length must match number of objects in dm. with self.assertRaises(ValueError): CategoricalStats(self.dm, [1, 2]) # Grouping vector cannot have only unique values. with self.assertRaises(ValueError): CategoricalStats(self.dm, [1, 2, 3]) # Grouping vector cannot have only a single group. with self.assertRaises(ValueError): CategoricalStats(self.dm, [1, 1, 1])
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)
def test_eq(self): """Test data equality between different matrix types.""" # Compare DistanceMatrix to DissimilarityMatrix, where both have the # same data and IDs. eq_dm = DissimilarityMatrix(self.dm_3x3_data, ['a', 'b', 'c']) self.assertTrue(self.dm_3x3 == eq_dm) self.assertTrue(eq_dm == 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 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_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_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_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)
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_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_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 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_init_invalid_input(self): # Requires a DistanceMatrix. with self.assertRaises(TypeError): _ = CategoricalStats( DissimilarityMatrix([[0, 2], [3, 0]], ['a', 'b']), [1, 2]) # Grouping vector length must match number of objects in dm. with self.assertRaises(ValueError): _ = CategoricalStats(self.dm, [1, 2]) # Grouping vector cannot have only unique values. with self.assertRaises(ValueError): _ = CategoricalStats(self.dm, [1, 2, 3]) # Grouping vector cannot have only a single group. with self.assertRaises(ValueError): _ = CategoricalStats(self.dm, [1, 1, 1])
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_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_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_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)
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 izip(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.""" 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) 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 izip(self.dm_f_lines, self.dms): obs_f = StringIO() dm.to_file(obs_f) obs = obs_f.getvalue() obs_f.close() 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_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 izip(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 izip(self.dms, self.dm_shapes): self.assertEqual(dm.shape, shape) def test_size(self): """Test retrieving size of data matrix.""" for dm, size in izip(self.dms, self.dm_sizes): self.assertEqual(dm.size, size) def test_transpose(self): """Test retrieving transpose of dissimilarity matrix.""" for dm, transpose in izip(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 izip(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)
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)
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_constructor(self): """Test generating random dist mats with a specific constructor.""" exp = DissimilarityMatrix(np.asarray([[0.0]]), ['1']) obs = randdm(1, constructor=DissimilarityMatrix) self.assertEqual(obs, exp) self.assertEqual(type(obs), DissimilarityMatrix)
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_from_file(self): """Should parse and return a valid DissimilarityMatrix given a file.""" for dm_f, dm in izip(self.dm_fs, self.dms): obs = DissimilarityMatrix.from_file(dm_f) self.assertEqual(obs, dm)
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)