def test_copy_values_with_start_index(self):
# Given
l1 = LongArray(8)
l1.set_data(numpy.arange(8))
l2 = LongArray(8)
l2.set_data(numpy.zeros(8, dtype=int))
# When
indices = LongArray(3)
indices.set_data(numpy.array([2, 4, 6]))
l1.copy_values(indices, l2, start=5)
# Then
numpy.testing.assert_array_equal(l2.get_npy_array(),
[0] * 5 + [2, 4, 6])
# When
l2.set_data(numpy.zeros(8, dtype=int))
indices.set_data(numpy.array([1, 2, 3]))
l1.copy_values(indices, l2, stride=2, start=2)
# Then
numpy.testing.assert_array_equal(l2.get_npy_array(),
[0, 0, 2, 3, 4, 5, 6, 7])
def test_copy_subset_works_with_strides(self):
# Given
l1 = LongArray(8)
l1.set_data(numpy.arange(8))
l2 = LongArray(4)
l2.set_data(numpy.arange(10, 14))
# When
l1.copy_subset(l2, 2, 3, stride=2)
# Then
numpy.testing.assert_array_equal(
l1.get_npy_array(),
[0, 1, 2, 3, 10, 11, 6, 7]
)
# When
l1.copy_subset(l2, 2, 4, stride=2)
# Then
numpy.testing.assert_array_equal(
l1.get_npy_array(),
[0, 1, 2, 3, 10, 11, 12, 13]
)
def test_remove_with_strides(self):
# Given
l1 = LongArray(12)
l1.set_data(numpy.arange(12))
# When
rem = [3, 1]
l1.remove(numpy.array(rem, dtype=numpy.int), stride=3)
# Then
self.assertEqual(l1.length, 6)
self.assertEqual(
numpy.allclose([0, 1, 2, 6, 7, 8], l1.get_npy_array()), True)
# Given
l1 = LongArray(12)
l1.set_data(numpy.arange(12))
# When
rem = [0, 2]
l1.remove(numpy.array(rem, dtype=numpy.int), stride=3)
# Then
self.assertEqual(l1.length, 6)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
self.assertEqual(
numpy.allclose([9, 10, 11, 3, 4, 5], l1.get_npy_array()), True)
def test_set_data(self):
"""
Tests the set_data function.
"""
la = LongArray(5)
np = numpy.arange(5)
la.set_data(np)
for i in range(5):
self.assertEqual(la[i], np[i])
self.assertRaises(ValueError, la.set_data, numpy.arange(10))
def test_pickling(self):
"""
Tests the __reduce__ and __setstate__ functions.
"""
l1 = LongArray(10)
l1.set_data(numpy.arange(10))
import pickle
l1_dump = pickle.dumps(l1)
l1_load = pickle.loads(l1_dump)
self.assertEqual((l1_load.get_npy_array() == l1.get_npy_array()).all(),
True)
def test_copy_subset(self):
l1 = LongArray(10)
l1.set_data(numpy.arange(10))
l2 = LongArray(4)
l2[0] = 4
l2[1] = 3
l2[2] = 2
l2[3] = 1
# a valid copy.
l1.copy_subset(l2, 5, 9)
self.assertEqual(numpy.allclose([0, 1, 2, 3, 4, 4, 3, 2, 1, 9],
l1.get_npy_array()), True)
# try to copy different sized arrays without any index specification.
l1.set_data(numpy.arange(10))
# copy to the last k values of source array.
l1.copy_subset(l2, start_index=6)
self.assertEqual(numpy.allclose([0, 1, 2, 3, 4, 5, 4, 3, 2, 1],
l1.get_npy_array()), True)
l1.set_data(numpy.arange(10))
l1.copy_subset(l2, start_index=7)
self.assertEqual(numpy.allclose([0, 1, 2, 3, 4, 5, 6, 4, 3, 2],
l1.get_npy_array()), True)
# some invalid operations.
l1.set_data(numpy.arange(10))
self.assertRaises(ValueError, l1.copy_subset, l2, -1, 1)
self.assertRaises(ValueError, l1.copy_subset, l2, 3, 2)
self.assertRaises(ValueError, l1.copy_subset, l2, 0, 11)
self.assertRaises(ValueError, l1.copy_subset, l2, 10, 20)
self.assertRaises(ValueError, l1.copy_subset, l2, -1, -1)
def test_squeeze_large_array_should_not_segfault(self):
# Given
la = LongArray(10)
la.set_data(numpy.zeros(10, dtype=int))
la.reserve(100000)
# When
la.squeeze()
la.reserve(1000)
# Then
self.assertEqual(la.length, 10)
numpy.testing.assert_array_almost_equal(la.get_npy_array(), 0)
self.assertEqual(la.alloc >= la.length, True)
def test_update_min_max(self):
"""
Tests the update_min_max function.
"""
l1 = LongArray(10)
l1.set_data(numpy.arange(10))
l1.update_min_max()
self.assertEqual(l1.minimum, 0)
self.assertEqual(l1.maximum, 9)
l1[9] = -1
l1[0] = -20
l1[4] = 200
l1.update_min_max()
self.assertEqual(l1.minimum, -20)
self.assertEqual(l1.maximum, 200)
def test_remove(self):
l1 = LongArray(10)
l1.set_data(numpy.arange(10))
rem = [0, 4, 3]
l1.remove(numpy.array(rem, dtype=numpy.int))
self.assertEqual(l1.length, 7)
self.assertEqual(
numpy.allclose([7, 1, 2, 8, 9, 5, 6], l1.get_npy_array()), True)
l1.remove(numpy.array(rem, dtype=numpy.int))
self.assertEqual(l1.length, 4)
self.assertEqual(numpy.allclose([6, 1, 2, 5], l1.get_npy_array()),
True)
rem = [0, 1, 3]
l1.remove(numpy.array(rem, dtype=numpy.int))
self.assertEqual(l1.length, 1)
self.assertEqual(numpy.allclose([2], l1.get_npy_array()), True)
l1.remove(numpy.array([0], dtype=numpy.int))
self.assertEqual(l1.length, 0)
self.assertEqual(len(l1.get_npy_array()), 0)
def test_align_array(self):
l1 = LongArray(10)
l1.set_data(numpy.arange(10))
new_indices = LongArray(10)
new_indices.set_data(numpy.asarray([1, 5, 3, 2, 4, 7, 8, 6, 9, 0]))
l1.align_array(new_indices)
self.assertEqual(numpy.allclose([1, 5, 3, 2, 4, 7, 8, 6, 9, 0],
l1.get_npy_array()), True)
# Test case with strides.
l1 = LongArray(6)
l1.set_data(numpy.arange(6))
new_indices = LongArray(3)
new_indices.set_data(numpy.asarray([2, 1, 0]))
l1.align_array(new_indices, 2)
self.assertEqual(numpy.allclose([4, 5, 2, 3, 0, 1],
l1.get_npy_array()), True)
