def test_searchsorted():
raw = np.sort(np.random.randint(100, size=(16,)))
arr = tensor(raw, chunk_size=3).cumsum()
t1 = searchsorted(arr, 10)
assert t1.shape == ()
assert t1.flags['C_CONTIGUOUS'] == np.searchsorted(raw.cumsum(), 10).flags['C_CONTIGUOUS']
assert t1.flags['F_CONTIGUOUS'] == np.searchsorted(raw.cumsum(), 10).flags['F_CONTIGUOUS']
t1 = tile(t1)
assert t1.nsplits == ()
assert len(t1.chunks) == 1
assert t1.chunks[0].op.stage == OperandStage.reduce
with pytest.raises(ValueError):
searchsorted(np.random.randint(10, size=(14, 14)), 1)
with pytest.raises(ValueError):
searchsorted(arr, 10, side='both')
with pytest.raises(ValueError):
searchsorted(arr.tosparse(), 10)
raw2 = np.asfortranarray(np.sort(np.random.randint(100, size=(16,))))
arr = tensor(raw2, chunk_size=3)
to_search = np.asfortranarray([[1, 2], [3, 4]])
t1 = searchsorted(arr, to_search)
expected = np.searchsorted(raw2, to_search)
assert t1.shape == to_search.shape
assert t1.flags['C_CONTIGUOUS'] == expected.flags['C_CONTIGUOUS']
assert t1.flags['F_CONTIGUOUS'] == expected.flags['F_CONTIGUOUS']
def testSearchsorted(self):
raw = np.sort(np.random.randint(100, size=(16, )))
arr = tensor(raw, chunk_size=3).cumsum()
t1 = searchsorted(arr, 10)
self.assertEqual(t1.shape, ())
self.assertEqual(
t1.flags['C_CONTIGUOUS'],
np.searchsorted(raw.cumsum(), 10).flags['C_CONTIGUOUS'])
self.assertEqual(
t1.flags['F_CONTIGUOUS'],
np.searchsorted(raw.cumsum(), 10).flags['F_CONTIGUOUS'])
t1 = t1.tiles()
self.assertEqual(t1.nsplits, ())
self.assertEqual(len(t1.chunks), 1)
self.assertEqual(t1.chunks[0].op.stage, OperandStage.reduce)
with self.assertRaises(ValueError):
searchsorted(np.random.randint(10, size=(14, 14)), 1)
with self.assertRaises(ValueError):
searchsorted(arr, 10, side='both')
with self.assertRaises(ValueError):
searchsorted(arr.tosparse(), 10)
raw2 = np.asfortranarray(np.sort(np.random.randint(100, size=(16, ))))
arr = tensor(raw2, chunk_size=3)
to_search = np.asfortranarray([[1, 2], [3, 4]])
t1 = searchsorted(arr, to_search)
expected = np.searchsorted(raw2, to_search)
self.assertEqual(t1.shape, to_search.shape)
self.assertEqual(t1.flags['C_CONTIGUOUS'],
expected.flags['C_CONTIGUOUS'])
self.assertEqual(t1.flags['F_CONTIGUOUS'],
expected.flags['F_CONTIGUOUS'])
def testSearchsortedExecution(self):
raw = np.sort(np.random.randint(100, size=(16, )))
# test different chunk_size, 3 will have combine, 6 will skip combine
for chunk_size in (3, 6):
arr = tensor(raw, chunk_size=chunk_size)
# test scalar, with value in the middle
t1 = searchsorted(arr, 20)
res = self.executor.execute_tensor(t1, concat=True)[0]
expected = np.searchsorted(raw, 20)
np.testing.assert_array_equal(res, expected)
# test scalar, with value larger than 100
t2 = searchsorted(arr, 200)
res = self.executor.execute_tensor(t2, concat=True)[0]
expected = np.searchsorted(raw, 200)
np.testing.assert_array_equal(res, expected)
# test scalar, side left, with value exact in the middle of the array
t3 = searchsorted(arr, raw[10], side='left')
res = self.executor.execute_tensor(t3, concat=True)[0]
expected = np.searchsorted(raw, raw[10], side='left')
np.testing.assert_array_equal(res, expected)
# test scalar, side right, with value exact in the middle of the array
t4 = searchsorted(arr, raw[10], side='right')
res = self.executor.execute_tensor(t4, concat=True)[0]
expected = np.searchsorted(raw, raw[10], side='right')
np.testing.assert_array_equal(res, expected)
# test scalar, side left, with value exact in the end of the array
t5 = searchsorted(arr, raw[15], side='left')
res = self.executor.execute_tensor(t5, concat=True)[0]
expected = np.searchsorted(raw, raw[15], side='left')
np.testing.assert_array_equal(res, expected)
# test scalar, side right, with value exact in the end of the array
t6 = searchsorted(arr, raw[15], side='right')
res = self.executor.execute_tensor(t6, concat=True)[0]
expected = np.searchsorted(raw, raw[15], side='right')
np.testing.assert_array_equal(res, expected)
# test scalar, side left, with value exact in the start of the array
t7 = searchsorted(arr, raw[0], side='left')
res = self.executor.execute_tensor(t7, concat=True)[0]
expected = np.searchsorted(raw, raw[0], side='left')
np.testing.assert_array_equal(res, expected)
# test scalar, side right, with value exact in the start of the array
t8 = searchsorted(arr, raw[0], side='right')
res = self.executor.execute_tensor(t8, concat=True)[0]
expected = np.searchsorted(raw, raw[0], side='right')
np.testing.assert_array_equal(res, expected)
raw2 = np.random.randint(100, size=(3, 4))
# test tensor, side left
t9 = searchsorted(arr, tensor(raw2, chunk_size=2), side='left')
res = self.executor.execute_tensor(t9, concat=True)[0]
expected = np.searchsorted(raw, raw2, side='left')
np.testing.assert_array_equal(res, expected)
# test tensor, side right
t10 = searchsorted(arr, tensor(raw2, chunk_size=2), side='right')
res = self.executor.execute_tensor(t10, concat=True)[0]
expected = np.searchsorted(raw, raw2, side='right')
np.testing.assert_array_equal(res, expected)
# test one chunk
arr = tensor(raw, chunk_size=16)
# test scalar, tensor to search has 1 chunk
t11 = searchsorted(arr, 20)
res = self.executor.execute_tensor(t11, concat=True)[0]
expected = np.searchsorted(raw, 20)
np.testing.assert_array_equal(res, expected)
# test tensor with 1 chunk, tensor to search has 1 chunk
t12 = searchsorted(arr, tensor(raw2, chunk_size=4))
res = self.executor.execute_tensor(t12, concat=True)[0]
expected = np.searchsorted(raw, raw2)
np.testing.assert_array_equal(res, expected)
# test tensor with more than 1 chunk, tensor to search has 1 chunk
t13 = searchsorted(arr, tensor(raw2, chunk_size=2))
res = self.executor.execute_tensor(t13, concat=True)[0]
expected = np.searchsorted(raw, raw2)
np.testing.assert_array_equal(res, expected)
# test sorter
raw3 = np.random.randint(100, size=(16, ))
arr = tensor(raw3, chunk_size=3)
order = np.argsort(raw3)
order_arr = tensor(order, chunk_size=4)
t14 = searchsorted(arr, 20, sorter=order_arr)
res = self.executor.execute_tensor(t14, concat=True)[0]
expected = np.searchsorted(raw3, 20, sorter=order)
np.testing.assert_array_equal(res, expected)