def test_indexes_support_numpy_like_take_by(self):
""" Verifies numpy_like.take can handle SDC index types as indices """
from sdc.functions import numpy_like
def pyfunc(arr, index):
return np.take(arr, index)
@self.jit
def sdc_func(arr, index):
return numpy_like.take(arr, index)
n, k = 1000, 200
np.random.seed(0)
arr = np.arange(n) * 2
indexes_to_test = [
get_sample_index(k, PositionalIndexType),
get_sample_index(k, RangeIndexType),
get_sample_index(k, Int64IndexType),
]
for index in indexes_to_test:
with self.subTest(index=index):
result = sdc_func(arr, index)
result_ref = pyfunc(arr, index)
np.testing.assert_array_equal(result, result_ref)
def test_positional_index_append(self):
def test_impl(index, other):
return index.append(other)
sdc_func = self.jit(test_impl)
n = 11
other_indexes = [
get_sample_index(n, PositionalIndexType),
get_sample_index(n, RangeIndexType),
get_sample_index(n, Int64IndexType),
]
for index, other in product(
_generate_positional_indexes_fixed(n),
other_indexes):
with self.subTest(index=index, other=other):
result = sdc_func(index, other)
result_ref = test_impl(index, other)
pd.testing.assert_index_equal(result, result_ref)
def test_multi_index_nparray(self):
def test_impl(index):
return np.array(index)
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
result = sdc_func(index)
result_ref = test_impl(index)
np.testing.assert_array_equal(result, result_ref)
def test_multi_index_ravel(self):
def test_impl(index):
return index.ravel()
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
result = sdc_func(index)
result_ref = test_impl(index)
# SDC MultiIndex.values return list but not numpy array
np.testing.assert_array_equal(result, list(result_ref))
def test_positional_index_join(self):
def test_impl(index, other):
return index.join(other, 'outer', return_indexers=True)
sdc_func = self.jit(test_impl)
n = 11
other_indexes = [
get_sample_index(2 * n, PositionalIndexType),
get_sample_index(2 * n, RangeIndexType),
get_sample_index(2 * n, Int64IndexType),
]
for index, other in product(
_generate_positional_indexes_fixed(n),
other_indexes):
with self.subTest(index=index, other=other):
result = sdc_func(index, other)
result_ref = test_impl(index, other)
# check_names=False, since pandas behavior is not type-stable
pd.testing.assert_index_equal(result[0], result_ref[0], check_names=False)
np.testing.assert_array_equal(result[1], result_ref[1])
np.testing.assert_array_equal(result[2], result_ref[2])
def test_multi_index_iterator_1(self):
def test_impl(index):
res = []
for i, label in enumerate(index):
res.append((i, label))
return res
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
result = sdc_func(index)
result_ref = test_impl(index)
self.assertEqual(result, result_ref)
def test_multi_index_getitem_scalar(self):
def test_impl(index, idx):
return index[idx]
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
idxs_to_test = [0, n // 2, n - 1, -1]
for idx in idxs_to_test:
with self.subTest(idx=idx):
result = sdc_func(index, idx)
result_ref = test_impl(index, idx)
self.assertEqual(result, result_ref)
def test_multi_index_contains(self):
def test_impl(index, value):
return value in index
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
values_to_test = [('a', 1), ('a', 4), ('e', 1), ('x', 5)]
for value in values_to_test:
with self.subTest(value=value):
result = sdc_func(index, value)
result_ref = test_impl(index, value)
np.testing.assert_array_equal(result, result_ref)
def test_multi_index_attribute_name(self):
def test_impl(index):
return index.name
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
for name in test_global_index_names:
index.name = name
with self.subTest(name=name):
result = sdc_func(index)
result_ref = test_impl(index)
self.assertEqual(result, result_ref)
def test_multi_index_attribute_dtype(self):
from numba.typed import List
# index dtype cannot be returned (boxed), thus it only checks it can be used
def test_impl(index):
return List.empty_list(index.dtype)
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
result = sdc_func(index)
expected = types.Tuple.from_types([types.unicode_type, types.intp])
self.assertEqual(result._dtype, expected)
def test_multi_index_reindex_equal_indexes(self):
def test_func(index1, index2):
return index1.reindex(index2)
sdc_func = self.jit(test_func)
n = 10
index1 = get_sample_index(n, MultiIndexType)
index2 = index1.copy(deep=True)
result = sdc_func(index1, index2)
result_ref = test_func(index1, index2)
pd.testing.assert_index_equal(result[0], result_ref[0])
np.testing.assert_array_equal(result[1], result_ref[1])
def test_multi_index_iterator_2(self):
def test_impl(index):
res = []
for label in index:
str_part, _ = label
if str_part == 'a':
res.append(label)
return res
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
result = sdc_func(index)
result_ref = test_impl(index)
self.assertEqual(result, result_ref)
def test_multi_index_operator_eq_scalar(self):
def test_impl(A, B):
return A == B
sdc_func = self.jit(test_impl)
n = 11
A = get_sample_index(n, MultiIndexType)
scalars_to_test = [('a', 1), ('a', 4), ('e', 1), ('x', 5)]
for B in scalars_to_test:
for swap_operands in (False, True):
if swap_operands:
A, B = B, A
with self.subTest(left=A, right=B):
result = np.asarray(sdc_func(A, B)) # FIXME_Numba#5157: remove np.asarray
result_ref = test_impl(A, B)
np.testing.assert_array_equal(result, result_ref)
def test_multi_index_getitem_slice(self):
def test_impl(index, idx):
return index[idx]
sdc_func = self.jit(test_impl)
n = 17
index = get_sample_index(n, MultiIndexType)
slices_params = combinations_with_replacement(
[None, 0, -1, n // 2, n, n - 3, n + 3, -(n + 3)],
2
)
for slice_start, slice_stop in slices_params:
for slice_step in [1, -1, 2]:
idx = slice(slice_start, slice_stop, slice_step)
with self.subTest(idx=idx):
result = sdc_func(index, idx)
result_ref = test_impl(index, idx)
pd.testing.assert_index_equal(result, result_ref)
def test_multi_index_getitem_scalar_idx_bounds(self):
def test_impl(index, idx):
return index[idx]
sdc_func = self.jit(test_impl)
n = 11
index = get_sample_index(n, MultiIndexType)
idxs_to_test = [-(n + 1), n]
for idx in idxs_to_test:
with self.subTest(idx=idx):
with self.assertRaises(Exception) as context:
test_impl(index, idx)
pandas_exception = context.exception
with self.assertRaises(type(pandas_exception)) as context:
sdc_func(index, idx)
sdc_exception = context.exception
self.assertIsInstance(sdc_exception, type(pandas_exception))
self.assertIn("out of bounds", str(sdc_exception))
