1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53
|
"Check that functions can handle list input"
import warnings
import numpy as np
from numpy.testing import assert_array_almost_equal
import bottleneck as bn
from .util import DTYPES
def test_list_input():
"Check that functions can handle list input"
for func in bn.get_functions('all'):
if func.__name__ != 'replace':
yield unit_maker, func
def lists(dtypes=DTYPES):
"Iterator that yields lists to use for unit testing."
ss = {}
ss[1] = {'size': 4, 'shapes': [(4,)]}
ss[2] = {'size': 6, 'shapes': [(1, 6), (2, 3)]}
ss[3] = {'size': 6, 'shapes': [(1, 2, 3)]}
ss[4] = {'size': 24, 'shapes': [(1, 2, 3, 4)]}
for ndim in ss:
size = ss[ndim]['size']
shapes = ss[ndim]['shapes']
a = np.arange(size)
for shape in shapes:
a = a.reshape(shape)
for dtype in dtypes:
yield a.astype(dtype).tolist()
def unit_maker(func):
"Test that bn.xxx gives the same output as bn.slow.xxx for list input."
msg = '\nfunc %s | input %s (%s) | shape %s\n'
msg += '\nInput array:\n%s\n'
name = func.__name__
func0 = eval('bn.slow.%s' % name)
for i, a in enumerate(lists()):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
try:
actual = func(a)
desired = func0(a)
except TypeError:
actual = func(a, 2)
desired = func0(a, 2)
a = np.array(a)
tup = (name, 'a'+str(i), str(a.dtype), str(a.shape), a)
err_msg = msg % tup
assert_array_almost_equal(actual, desired, err_msg=err_msg)
|