FM / tests

/usr/local/lib64/python3.6/site-packages/numpy/lib/tests/

/usr/local/lib64/python3.6/site-packages/numpy/lib/tests

Name	Size	Mode	Actions
data/	-	0755	rm
__pycache__/	-	0755	rm
test_arraypad.py	54283	0644	edit dl rm
test_arraysetops.py	24308	0644	edit dl rm
test_arrayterator.py	1291	0644	edit dl rm
test_financial.py	18316	0644	edit dl rm
test_format.py	38544	0644	edit dl rm
test_function_base.py	126152	0644	edit dl rm
test_histograms.py	33672	0644	edit dl rm
test_index_tricks.py	18324	0644	edit dl rm
test_io.py	100888	0644	edit dl rm
test_mixins.py	7030	0644	edit dl rm
test_nanfunctions.py	38085	0644	edit dl rm
test_packbits.py	17546	0644	edit dl rm
test_polynomial.py	10013	0644	edit dl rm
test_recfunctions.py	41155	0644	edit dl rm
test_regression.py	8257	0644	edit dl rm
test_shape_base.py	24303	0644	edit dl rm
test_stride_tricks.py	16954	0644	edit dl rm
test_twodim_base.py	18358	0644	edit dl rm
test_type_check.py	15119	0644	edit dl rm
test_ufunclike.py	3278	0644	edit dl rm
test_utils.py	3769	0644	edit dl rm
test__datasource.py	10487	0644	edit dl rm
test__iotools.py	13743	0644	edit dl rm
test__version.py	1989	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/numpy/lib/tests/test_arrayterator.py (1291B)

from operator import mul
from functools import reduce

import numpy as np
from numpy.random import randint
from numpy.lib import Arrayterator
from numpy.testing import assert_

def test():
    np.random.seed(np.arange(10))

# Create a random array
    ndims = randint(5)+1
    shape = tuple(randint(10)+1 for dim in range(ndims))
    els = reduce(mul, shape)
    a = np.arange(els)
    a.shape = shape

buf_size = randint(2*els)
    b = Arrayterator(a, buf_size)

# Check that each block has at most ``buf_size`` elements
    for block in b:
        assert_(len(block.flat) <= (buf_size or els))

# Check that all elements are iterated correctly
    assert_(list(b.flat) == list(a.flat))

# Slice arrayterator
    start = [randint(dim) for dim in shape]
    stop = [randint(dim)+1 for dim in shape]
    step = [randint(dim)+1 for dim in shape]
    slice_ = tuple(slice(*t) for t in zip(start, stop, step))
    c = b[slice_]
    d = a[slice_]

# Check that each block has at most ``buf_size`` elements
    for block in c:
        assert_(len(block.flat) <= (buf_size or els))

# Check that the arrayterator is sliced correctly
    assert_(np.all(c.__array__() == d))

# Check that all elements are iterated correctly
    assert_(list(c.flat) == list(d.flat))

from operator import mul from functools import reduce import numpy as np from numpy.random import randint from numpy.lib import Arrayterator from numpy.testing import assert_ def test(): np.random.seed(np.arange(10)) # Create a random array ndims = randint(5)+1 shape = tuple(randint(10)+1 for dim in range(ndims)) els = reduce(mul, shape) a = np.arange(els) a.shape = shape buf_size = randint(2*els) b = Arrayterator(a, buf_size) # Check that each block has at most ``buf_size`` elements for block in b: assert_(len(block.flat) <= (buf_size or els)) # Check that all elements are iterated correctly assert_(list(b.flat) == list(a.flat)) # Slice arrayterator start = [randint(dim) for dim in shape] stop = [randint(dim)+1 for dim in shape] step = [randint(dim)+1 for dim in shape] slice_ = tuple(slice(*t) for t in zip(start, stop, step)) c = b[slice_] d = a[slice_] # Check that each block has at most ``buf_size`` elements for block in c: assert_(len(block.flat) <= (buf_size or els)) # Check that the arrayterator is sliced correctly assert_(np.all(c.__array__() == d)) # Check that all elements are iterated correctly assert_(list(c.flat) == list(d.flat))