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"""Tests for the array padding functions.
"""
from __future__ import division, absolute_import, print_function
import pytest
import numpy as np
from numpy.testing import (assert_array_equal, assert_raises, assert_allclose,
assert_equal)
from numpy.lib import pad
from numpy.lib.arraypad import _as_pairs
class TestAsPairs(object):
def test_single_value(self):
"""Test casting for a single value."""
expected = np.array([[3, 3]] * 10)
for x in (3, [3], [[3]]):
result = _as_pairs(x, 10)
assert_equal(result, expected)
# Test with dtype=object
obj = object()
assert_equal(
_as_pairs(obj, 10),
np.array([[obj, obj]] * 10)
)
def test_two_values(self):
"""Test proper casting for two different values."""
# Broadcasting in the first dimension with numbers
expected = np.array([[3, 4]] * 10)
for x in ([3, 4], [[3, 4]]):
result = _as_pairs(x, 10)
assert_equal(result, expected)
# and with dtype=object
obj = object()
assert_equal(
_as_pairs(["a", obj], 10),
np.array([["a", obj]] * 10)
)
# Broadcasting in the second / last dimension with numbers
assert_equal(
_as_pairs([[3], [4]], 2),
np.array([[3, 3], [4, 4]])
)
# and with dtype=object
assert_equal(
_as_pairs([["a"], [obj]], 2),
np.array([["a", "a"], [obj, obj]])
)
def test_with_none(self):
expected = ((None, None), (None, None), (None, None))
assert_equal(
_as_pairs(None, 3, as_index=False),
expected
)
assert_equal(
_as_pairs(None, 3, as_index=True),
expected
)
def test_pass_through(self):
"""Test if `x` already matching desired output are passed through."""
expected = np.arange(12).reshape((6, 2))
assert_equal(
_as_pairs(expected, 6),
expected
)
def test_as_index(self):
"""Test results if `as_index=True`."""
assert_equal(
_as_pairs([2.6, 3.3], 10, as_index=True),
np.array([[3, 3]] * 10, dtype=np.intp)
)
assert_equal(
_as_pairs([2.6, 4.49], 10, as_index=True),
np.array([[3, 4]] * 10, dtype=np.intp)
)
for x in (-3, [-3], [[-3]], [-3, 4], [3, -4], [[-3, 4]], [[4, -3]],
[[1, 2]] * 9 + [[1, -2]]):
with pytest.raises(ValueError, match="negative values"):
_as_pairs(x, 10, as_index=True)
def test_exceptions(self):
"""Ensure faulty usage is discovered."""
with pytest.raises(ValueError, match="more dimensions than allowed"):
_as_pairs([[[3]]], 10)
with pytest.raises(ValueError, match="could not be broadcast"):
_as_pairs([[1, 2], [3, 4]], 3)
with pytest.raises(ValueError, match="could not be broadcast"):
_as_pairs(np.ones((2, 3)), 3)
class TestConditionalShortcuts(object):
def test_zero_padding_shortcuts(self):
test = np.arange(120).reshape(4, 5, 6)
pad_amt = [(0, 0) for axis in test.shape]
modes = ['constant',
'edge',
'linear_ramp',
'maximum',
'mean',
'median',
'minimum',
'reflect',
'symmetric',
'wrap',
]
for mode in modes:
assert_array_equal(test, pad(test, pad_amt, mode=mode))
def test_shallow_statistic_range(self):
test = np.arange(120).reshape(4, 5, 6)
pad_amt = [(1, 1) for axis in test.shape]
modes = ['maximum',
'mean',
'median',
'minimum',
]
for mode in modes:
assert_array_equal(pad(test, pad_amt, mode='edge'),
pad(test, pad_amt, mode=mode, stat_length=1))
def test_clip_statistic_range(self):
test = np.arange(30).reshape(5, 6)
pad_amt = [(3, 3) for axis in test.shape]
modes = ['maximum',
'mean',
'median',
'minimum',
]
for mode in modes:
assert_array_equal(pad(test, pad_amt, mode=mode),
pad(test, pad_amt, mode=mode, stat_length=30))
class TestStatistic(object):
def test_check_mean_stat_length(self):
a = np.arange(100).astype('f')
a = pad(a, ((25, 20), ), 'mean', stat_length=((2, 3), ))
b = np.array(
[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,
0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5,
0.5, 0.5, 0.5, 0.5, 0.5,
0., 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., 54., 55., 56., 57., 58., 59.,
60., 61., 62., 63., 64., 65., 66., 67., 68., 69.,
70., 71., 72., 73., 74., 75., 76., 77., 78., 79.,
80., 81., 82., 83., 84., 85., 86., 87., 88., 89.,
90., 91., 92., 93., 94., 95., 96., 97., 98., 99.,
98., 98., 98., 98., 98., 98., 98., 98., 98., 98.,
98., 98., 98., 98., 98., 98., 98., 98., 98., 98.
])
assert_array_equal(a, b)
def test_check_maximum_1(self):
a = np.arange(100)
a = pad(a, (25, 20), 'maximum')
b = np.array(
[99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
99, 99, 99, 99, 99,
0, 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, 54, 55, 56, 57, 58, 59,
60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 96, 97, 98, 99,
99, 99, 99, 99, 99, 99, 99, 99, 99, 99,
99, 99, 99, 99, 99, 99, 99, 99, 99, 99]
)
assert_array_equal(a, b)
def test_check_maximum_2(self):
a = np.arange(100) + 1
a = pad(a, (25, 20), 'maximum')
b = np.array(
[100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100,
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, 54, 55, 56, 57, 58, 59, 60,
61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100]
)
assert_array_equal(a, b)
def test_check_maximum_stat_length(self):
a = np.arange(100) + 1
a = pad(a, (25, 20), 'maximum', stat_length=10)
b = np.array(
[10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
10, 10, 10, 10, 10,
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, 54, 55, 56, 57, 58, 59, 60,
61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100,
100, 100, 100, 100, 100, 100, 100, 100, 100, 100]
)
assert_array_equal(a, b)
def test_check_minimum_1(self):
a = np.arange(100)
a = pad(a, (25, 20), 'minimum')
b = np.array(
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0,
0, 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, 54, 55, 56, 57, 58, 59,
60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
90, 91, 92, 93, 94, 95, 96, 97, 98, 99,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
)
assert_array_equal(a, b)
def test_check_minimum_2(self):
a = np.arange(100) + 2
a = pad(a, (25, 20), 'minimum')
b = np.array(
[2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2,
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, 54, 55, 56, 57, 58, 59, 60, 61,
62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
72, 73, 74, 75, 76, 77, 78, 79, 80, 81,
82, 83, 84, 85, 86, 87, 88, 89, 90, 91,
92, 93, 94, 95, 96, 97, 98, 99, 100, 101,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2, 2]
)
assert_array_equal(a, b)
def test_check_minimum_stat_length(self):
a = np.arange(100) + 1
a = pad(a, (25, 20), 'minimum', stat_length=10)
b = np.array(
[ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1,
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, 54, 55, 56, 57, 58, 59, 60,
61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
91, 92, 93, 94, 95, 96, 97, 98, 99, 100,
91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
91, 91, 91, 91, 91, 91, 91, 91, 91, 91]
)
assert_array_equal(a, b)
def test_check_median(self):
a = np.arange(100).astype('f')
a = pad(a, (25, 20), 'median')
b = np.array(
[49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5,
49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5,
49.5, 49.5, 49.5, 49.5, 49.5,
0., 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., 54., 55., 56., 57., 58., 59.,
60., 61., 62., 63., 64., 65., 66., 67., 68., 69.,
70., 71., 72., 73., 74., 75., 76., 77., 78., 79.,
80., 81., 82., 83., 84., 85., 86., 87., 88., 89.,
90., 91., 92., 93., 94., 95., 96., 97., 98., 99.,
49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5,
49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5, 49.5]
)
assert_array_equal(a, b)
def test_check_median_01(self):
a = np.array([[3, 1, 4], [4, 5, 9], [9, 8, 2]])
a = pad(a, 1, 'median')
b = np.array(
[[4, 4, 5, 4, 4],
[3, 3, 1, 4, 3],
[5, 4, 5, 9, 5],
[8, 9, 8, 2, 8],
[4, 4, 5, 4, 4]]