def test_is_label_indicator_matrix(): for group, group_examples in iteritems(EXAMPLES): if group == "multilabel-indicator": assert_, exp = assert_true, "True" else: assert_, exp = assert_false, "False" for example in group_examples: assert_( is_label_indicator_matrix(example), msg="is_label_indicator_matrix(%r) should be %s" % (example, exp) )
def test_is_label_indicator_matrix(): for group, group_examples in iteritems(EXAMPLES): if group == 'multilabel-indicator': assert_, exp = assert_true, 'True' else: assert_, exp = assert_false, 'False' for example in group_examples: assert_(is_label_indicator_matrix(example), msg='is_label_indicator_matrix(%r) should be %s' % (example, exp))
def test_is_label_indicator_matrix(): for group, group_examples in iteritems(EXAMPLES): if group in ['multilabel-indicator']: dense_assert_, dense_exp = assert_true, 'True' else: dense_assert_, dense_exp = assert_false, 'False' for example in group_examples: # Only mark explicitly defined sparse examples as valid sparse # multilabel-indicators if group == 'multilabel-indicator' and issparse(example): sparse_assert_, sparse_exp = assert_true, 'True' else: sparse_assert_, sparse_exp = assert_false, 'False' if (issparse(example) or (hasattr(example, '__array__') and np.asarray(example).ndim == 2 and np.asarray(example).dtype.kind in 'biuf' and np.asarray(example).shape[1] > 0)): examples_sparse = [ sparse_matrix(example) for sparse_matrix in [ coo_matrix, csc_matrix, csr_matrix, dok_matrix, lil_matrix ] ] for exmpl_sparse in examples_sparse: sparse_assert_(is_label_indicator_matrix(exmpl_sparse), msg=('is_label_indicator_matrix(%r)' ' should be %s') % (exmpl_sparse, sparse_exp)) # Densify sparse examples before testing if issparse(example): example = example.toarray() dense_assert_(is_label_indicator_matrix(example), msg='is_label_indicator_matrix(%r) should be %s' % (example, dense_exp))
def test_is_label_indicator_matrix(): for group, group_examples in iteritems(EXAMPLES): if group in ['multilabel-indicator']: dense_assert_, dense_exp = assert_true, 'True' else: dense_assert_, dense_exp = assert_false, 'False' for example in group_examples: # Only mark explicitly defined sparse examples as valid sparse # multilabel-indicators if group == 'multilabel-indicator' and issparse(example): sparse_assert_, sparse_exp = assert_true, 'True' else: sparse_assert_, sparse_exp = assert_false, 'False' if (issparse(example) or (hasattr(example, '__array__') and np.asarray(example).ndim == 2 and np.asarray(example).dtype.kind in 'biuf' and np.asarray(example).shape[1] > 0)): examples_sparse = [sparse_matrix(example) for sparse_matrix in [coo_matrix, csc_matrix, csr_matrix, dok_matrix, lil_matrix]] for exmpl_sparse in examples_sparse: sparse_assert_(is_label_indicator_matrix(exmpl_sparse), msg=('is_label_indicator_matrix(%r)' ' should be %s') % (exmpl_sparse, sparse_exp)) # Densify sparse examples before testing if issparse(example): example = example.toarray() dense_assert_(is_label_indicator_matrix(example), msg='is_label_indicator_matrix(%r) should be %s' % (example, dense_exp))
def test_is_label_indicator_matrix(): assert_true(is_label_indicator_matrix(np.random.randint(2, size=(10, 10)))) assert_false(is_label_indicator_matrix([[1], [2], [0, 1]])) assert_false(is_label_indicator_matrix([[1], [2]])) assert_false(is_label_indicator_matrix([[1], [2], []])) assert_false(is_label_indicator_matrix([[1], [0, 2], []])) assert_false(is_label_indicator_matrix(range(10))) assert_false(is_label_indicator_matrix(np.arange(10))) assert_false(is_label_indicator_matrix(np.reshape(np.arange(9), (3, 3)))) assert_false(is_label_indicator_matrix(np.reshape(np.arange(10), (-1, 1)))) assert_false(is_label_indicator_matrix(np.reshape(np.arange(10), (1, -1)))) assert_false(is_label_indicator_matrix(np.random.randint(2, size=(10, )))) assert_false(is_label_indicator_matrix(np.random.randint(2, size=(10, 1))))