def test_traverse_invalidating(self):
data = np.arange(5 * 3, dtype="f8").reshape(5, 3)
original_data = data.copy()
adjustments = {2: [Float64Multiply(0, 4, 0, 2, 2.0)]}
adjusted_array = AdjustedArray(data, adjustments, float("nan"))
for _ in adjusted_array.traverse(1, copy=False):
pass
assert_equal(data, original_data * 2)
err_msg = "cannot traverse invalidated AdjustedArray"
with pytest.raises(ValueError, match=err_msg):
adjusted_array.traverse(1)
def test_copy(self):
data = arange(5 * 3, dtype='f8').reshape(5, 3)
original_data = data.copy()
adjustments = {2: [Float64Multiply(0, 4, 0, 2, 2.0)]}
adjusted_array = AdjustedArray(data, adjustments, float('nan'))
traverse_copy = adjusted_array.copy()
clean_copy = adjusted_array.copy()
a_it = adjusted_array.traverse(2, copy=False)
b_it = traverse_copy.traverse(2, copy=False)
for a, b in zip(a_it, b_it):
assert_equal(a, b)
with self.assertRaises(ValueError) as e:
adjusted_array.copy()
assert_equal(
str(e.exception),
'cannot copy invalidated AdjustedArray',
)
# the clean copy should have the original data even though the
# original adjusted array has it's data mutated in place
assert_equal(clean_copy.data, original_data)
assert_equal(adjusted_array.data, original_data * 2)
def test_array_views_arent_writable(self):
data = arange(30, dtype=float).reshape(6, 5)
adj_array = AdjustedArray(data, {}, float('nan'))
for frame in adj_array.traverse(3):
with self.assertRaises(ValueError):
frame[0, 0] = 5.0
def test_array_views_arent_writable(self):
data = arange(30, dtype=float).reshape(6, 5)
adj_array = AdjustedArray(data, NOMASK, {}, float('nan'))
for frame in adj_array.traverse(3):
with self.assertRaises(ValueError):
frame[0, 0] = 5.0
def test_traverse_invalidating(self):
data = arange(5 * 3, dtype='f8').reshape(5, 3)
original_data = data.copy()
adjustments = {2: [Float64Multiply(0, 4, 0, 2, 2.0)]}
adjusted_array = AdjustedArray(data, adjustments, float('nan'))
for _ in adjusted_array.traverse(1, copy=False):
pass
assert_equal(data, original_data * 2)
with self.assertRaises(ValueError) as e:
adjusted_array.traverse(1)
assert_equal(
str(e.exception),
'cannot traverse invalidated AdjustedArray',
)
def test_no_adjustments(
self,
name,
data,
lookback,
adjustments,
missing_value,
perspective_offset,
expected_output,
):
array = AdjustedArray(data, adjustments, missing_value)
for _ in range(2): # Iterate 2x ensure adjusted_arrays are re-usable.
in_out = zip(array.traverse(lookback), expected_output)
for yielded, expected_yield in in_out:
check_arrays(yielded, expected_yield)
def test_invalid_lookback(self):
data = arange(30, dtype=float).reshape(6, 5)
adj_array = AdjustedArray(data, {}, float('nan'))
with self.assertRaises(WindowLengthTooLong):
adj_array.traverse(7)
with self.assertRaises(WindowLengthNotPositive):
adj_array.traverse(0)
with self.assertRaises(WindowLengthNotPositive):
adj_array.traverse(-1)
def test_invalid_lookback(self):
data = arange(30, dtype=float).reshape(6, 5)
adj_array = AdjustedArray(data, NOMASK, {}, float('nan'))
with self.assertRaises(WindowLengthTooLong):
adj_array.traverse(7)
with self.assertRaises(WindowLengthNotPositive):
adj_array.traverse(0)
with self.assertRaises(WindowLengthNotPositive):
adj_array.traverse(-1)
def test_overwrite_adjustment_cases(
self,
name,
baseline,
lookback,
adjustments,
missing_value,
perspective_offset,
expected,
):
array = AdjustedArray(baseline, adjustments, missing_value)
for _ in range(2): # Iterate 2x ensure adjusted_arrays are re-usable.
window_iter = array.traverse(
lookback,
perspective_offset=perspective_offset,
)
for yielded, expected_yield in zip_longest(window_iter, expected):
check_arrays(yielded, expected_yield)
def test_copy(self):
data = np.arange(5 * 3, dtype="f8").reshape(5, 3)
original_data = data.copy()
adjustments = {2: [Float64Multiply(0, 4, 0, 2, 2.0)]}
adjusted_array = AdjustedArray(data, adjustments, float("nan"))
traverse_copy = adjusted_array.copy()
clean_copy = adjusted_array.copy()
a_it = adjusted_array.traverse(2, copy=False)
b_it = traverse_copy.traverse(2, copy=False)
for a, b in zip(a_it, b_it):
assert_equal(a, b)
err_msg = "cannot copy invalidated AdjustedArray"
with pytest.raises(ValueError, match=err_msg):
adjusted_array.copy()
# the clean copy should have the original data even though the
# original adjusted array has it's data mutated in place
assert_equal(clean_copy.data, original_data)
assert_equal(adjusted_array.data, original_data * 2)
