def push(array, n, axis):
from bottleneck import push
if is_duck_dask_array(array):
return dask_array_ops.push(array, n, axis)
else:
return push(array, n, axis)
def test_push():
"""Test push"""
ns = (0, 1, 2, 3, 4, 5, None)
a = np.array([np.nan, 1, 2, np.nan, np.nan, np.nan, np.nan, 3, np.nan])
for n in ns:
actual = bn.push(a.copy(), n=n)
desired = bn.slow.push(a.copy(), n=n)
assert_array_equal(actual, desired, "failed on n=%s" % str(n))
def test_push_2():
"Test push #2."
ns = (np.inf, -1, 0, 1, 2, 3, 4, 5, 1.1, 1.5, 1.9)
arr = np.array([np.nan, 1, 2, np.nan, np.nan, np.nan, np.nan, 3, np.nan])
for n in ns:
actual = bn.push(arr.copy(), n=n)
desired = bn.slow.push(arr.copy(), n=n)
assert_array_equal(actual, desired, "failed on n=%s" % str(n))
def test_push_2():
"Test push #2."
ns = (np.inf, -1, 0, 1, 2, 3, 4, 5, 1.1, 1.5, 1.9)
arr = np.array([np.nan, 1, 2, np.nan, np.nan, np.nan, np.nan, 3, np.nan])
for n in ns:
actual = bn.push(arr.copy(), n=n)
desired = bn.slow.push(arr.copy(), n=n)
assert_array_equal(actual, desired, "failed on n=%s" % str(n))
def test_push():
"Test push"
ns = (0, 1, 2, 3, 4, 5)
a = np.array([np.nan, 1, 2, np.nan, np.nan, np.nan, np.nan, 3, np.nan])
for n in ns:
actual = bn.push(a.copy(), n=n)
desired = bn.slow.push(a.copy(), n=n)
assert_array_equal(actual, desired, "failed on n=%s" % str(n))
def _bfill(arr, n=None, axis=-1):
'''inverse of ffill'''
import bottleneck as bn
arr = np.flip(arr, axis=axis)
# fill
arr = bn.push(arr, axis=axis, n=n)
# reverse back to original
return np.flip(arr, axis=axis)
def _bfill(arr, n=None, axis=-1):
'''inverse of ffill'''
import bottleneck as bn
arr = np.flip(arr, axis=axis)
# fill
arr = bn.push(arr, axis=axis, n=n)
# reverse back to original
return np.flip(arr, axis=axis)
def test_push_dask():
import bottleneck
import dask.array
array = np.array([np.nan, 1, 2, 3, np.nan, np.nan, np.nan, np.nan, 4, 5, np.nan, 6])
for n in [None, 1, 2, 3, 4, 5, 11]:
expected = bottleneck.push(array, axis=0, n=n)
for c in range(1, 11):
with raise_if_dask_computes():
actual = push(dask.array.from_array(array, chunks=c), axis=0, n=n)
np.testing.assert_equal(actual, expected)
# some chunks of size-1 with NaN
with raise_if_dask_computes():
actual = push(
dask.array.from_array(array, chunks=(1, 2, 3, 2, 2, 1, 1)), axis=0, n=n
)
np.testing.assert_equal(actual, expected)
def time_push(self, dtype, shape):
bn.push(self.arr)
import numpy as np import bottleneck as bn a = np.array([1, 2, np.nan, 4, 5]) print(bn.nansum(a)) print(bn.move_median(a, window=2, min_count=1)) bn.bench() bn.push()
