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"""Test moving window functions."""
import numpy as np
from numpy.testing import assert_equal, assert_array_almost_equal, assert_raises
import bottleneck as bn
from .util import arrays, array_order
import pytest
@pytest.mark.parametrize("func", bn.get_functions("move"), ids=lambda x: x.__name__)
def test_move(func):
"""Test that bn.xxx gives the same output as a reference function."""
fmt = (
"\nfunc %s | window %d | min_count %s | input %s (%s) | shape %s | "
"axis %s | order %s\n"
)
fmt += "\nInput array:\n%s\n"
aaae = assert_array_almost_equal
func_name = func.__name__
func0 = eval("bn.slow.%s" % func_name)
if func_name == "move_var":
decimal = 3
else:
decimal = 5
for i, a in enumerate(arrays(func_name)):
axes = range(-1, a.ndim)
for axis in axes:
windows = range(1, a.shape[axis])
for window in windows:
min_counts = list(range(1, window + 1)) + [None]
for min_count in min_counts:
actual = func(a, window, min_count, axis=axis)
desired = func0(a, window, min_count, axis=axis)
tup = (
func_name,
window,
str(min_count),
"a" + str(i),
str(a.dtype),
str(a.shape),
str(axis),
array_order(a),
a,
)
err_msg = fmt % tup
aaae(actual, desired, decimal, err_msg)
err_msg += "\n dtype mismatch %s %s"
da = actual.dtype
dd = desired.dtype
assert_equal(da, dd, err_msg % (da, dd))
# ---------------------------------------------------------------------------
# Test argument parsing
@pytest.mark.parametrize("func", bn.get_functions("move"), ids=lambda x: x.__name__)
def test_arg_parsing(func, decimal=5):
"""test argument parsing."""
name = func.__name__
func0 = eval("bn.slow.%s" % name)
a = np.array([1.0, 2, 3])
fmt = "\n%s" % func
fmt += "%s\n"
fmt += "\nInput array:\n%s\n" % a
actual = func(a, 2)
desired = func0(a, 2)
err_msg = fmt % "(a, 2)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a, 2, 1)
desired = func0(a, 2, 1)
err_msg = fmt % "(a, 2, 1)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a, window=2)
desired = func0(a, window=2)
err_msg = fmt % "(a, window=2)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a, window=2, min_count=1)
desired = func0(a, window=2, min_count=1)
err_msg = fmt % "(a, window=2, min_count=1)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a, window=2, min_count=1, axis=0)
desired = func0(a, window=2, min_count=1, axis=0)
err_msg = fmt % "(a, window=2, min_count=1, axis=0)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a, min_count=1, window=2, axis=0)
desired = func0(a, min_count=1, window=2, axis=0)
err_msg = fmt % "(a, min_count=1, window=2, axis=0)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a, axis=-1, min_count=None, window=2)
desired = func0(a, axis=-1, min_count=None, window=2)
err_msg = fmt % "(a, axis=-1, min_count=None, window=2)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
actual = func(a=a, axis=-1, min_count=None, window=2)
desired = func0(a=a, axis=-1, min_count=None, window=2)
err_msg = fmt % "(a=a, axis=-1, min_count=None, window=2)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
if name in ("move_std", "move_var"):
actual = func(a, 2, 1, -1, ddof=1)
desired = func0(a, 2, 1, -1, ddof=1)
err_msg = fmt % "(a, 2, 1, -1, ddof=1)"
assert_array_almost_equal(actual, desired, decimal, err_msg)
# regression test: make sure len(kwargs) == 0 doesn't raise
args = (a, 1, 1, -1)
kwargs = {}
func(*args, **kwargs)
@pytest.mark.parametrize("func", bn.get_functions("move"), ids=lambda x: x.__name__)
def test_arg_parse_raises(func):
"""test argument parsing raises in move"""
a = np.array([1.0, 2, 3])
assert_raises(TypeError, func)
assert_raises(TypeError, func, axis=a)
assert_raises(TypeError, func, a, 2, axis=0, extra=0)
assert_raises(TypeError, func, a, 2, axis=0, a=a)
assert_raises(TypeError, func, a, 2, 2, 0, 0, 0)
assert_raises(TypeError, func, a, 2, axis="0")
assert_raises(TypeError, func, a, 1, min_count="1")
if func.__name__ not in ("move_std", "move_var"):
assert_raises(TypeError, func, a, 2, ddof=0)
# ---------------------------------------------------------------------------
# move_median.c is complicated. Let's do some more testing.
#
# If you make changes to move_median.c then do lots of tests by increasing
# range(100) in the two functions below to range(10000). And for extra credit
# increase size to 30. With those two changes the unit tests will take a
# LONG time to run.
def test_move_median_with_nans():
"""test move_median.c with nans"""
fmt = "\nfunc %s | window %d | min_count %s\n\nInput array:\n%s\n"
aaae = assert_array_almost_equal
min_count = 1
size = 10
func = bn.move_median
func0 = bn.slow.move_median
rs = np.random.RandomState([1, 2, 3])
for i in range(100):
a = np.arange(size, dtype=np.float64)
idx = rs.rand(*a.shape) < 0.1
a[idx] = np.inf
idx = rs.rand(*a.shape) < 0.2
a[idx] = np.nan
rs.shuffle(a)
for window in range(2, size + 1):
actual = func(a, window=window, min_count=min_count)
desired = func0(a, window=window, min_count=min_count)
err_msg = fmt % (func.__name__, window, min_count, a)
aaae(actual, desired, decimal=5, err_msg=err_msg)
def test_move_median_without_nans():
"""test move_median.c without nans"""
fmt = "\nfunc %s | window %d | min_count %s\n\nInput array:\n%s\n"
aaae = assert_array_almost_equal
min_count = 1
size = 10
func = bn.move_median
func0 = bn.slow.move_median
rs = np.random.RandomState([1, 2, 3])
for i in range(100):
a = np.arange(size, dtype=np.int64)
rs.shuffle(a)
for window in range(2, size + 1):
actual = func(a, window=window, min_count=min_count)
desired = func0(a, window=window, min_count=min_count)
err_msg = fmt % (func.__name__, window, min_count, a)
aaae(actual, desired, decimal=5, err_msg=err_msg)
# ----------------------------------------------------------------------------
# Regression test for square roots of negative numbers
def test_move_std_sqrt():
"""Test move_std for neg sqrt."""
a = [
0.0011448196318903589,
0.00028718669878572767,
0.00028718669878572767,
0.00028718669878572767,
0.00028718669878572767,
]
err_msg = "Square root of negative number. ndim = %d"
b = bn.move_std(a, window=3)
assert np.isfinite(b[2:]).all(), err_msg % 1
a2 = np.array([a, a])
b = bn.move_std(a2, window=3, axis=1)
assert np.isfinite(b[:, 2:]).all(), err_msg % 2
a3 = np.array([[a, a], [a, a]])
b = bn.move_std(a3, window=3, axis=2)
assert np.isfinite(b[:, :, 2:]).all(), err_msg % 3
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