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from __future__ import division, absolute_import, print_function
import warnings
import sys
import numpy as np
from numpy.testing import *
import unittest
class _GenericTest(object):
def _test_equal(self, a, b):
self._assert_func(a, b)
def _test_not_equal(self, a, b):
try:
self._assert_func(a, b)
passed = True
except AssertionError:
pass
else:
raise AssertionError("a and b are found equal but are not")
def test_array_rank1_eq(self):
"""Test two equal array of rank 1 are found equal."""
a = np.array([1, 2])
b = np.array([1, 2])
self._test_equal(a, b)
def test_array_rank1_noteq(self):
"""Test two different array of rank 1 are found not equal."""
a = np.array([1, 2])
b = np.array([2, 2])
self._test_not_equal(a, b)
def test_array_rank2_eq(self):
"""Test two equal array of rank 2 are found equal."""
a = np.array([[1, 2], [3, 4]])
b = np.array([[1, 2], [3, 4]])
self._test_equal(a, b)
def test_array_diffshape(self):
"""Test two arrays with different shapes are found not equal."""
a = np.array([1, 2])
b = np.array([[1, 2], [1, 2]])
self._test_not_equal(a, b)
def test_objarray(self):
"""Test object arrays."""
a = np.array([1, 1], dtype=np.object)
self._test_equal(a, 1)
def test_array_likes(self):
self._test_equal([1, 2, 3], (1, 2, 3))
class TestArrayEqual(_GenericTest, unittest.TestCase):
def setUp(self):
self._assert_func = assert_array_equal
def test_generic_rank1(self):
"""Test rank 1 array for all dtypes."""
def foo(t):
a = np.empty(2, t)
a.fill(1)
b = a.copy()
c = a.copy()
c.fill(0)
self._test_equal(a, b)
self._test_not_equal(c, b)
# Test numeric types and object
for t in '?bhilqpBHILQPfdgFDG':
foo(t)
# Test strings
for t in ['S1', 'U1']:
foo(t)
def test_generic_rank3(self):
"""Test rank 3 array for all dtypes."""
def foo(t):
a = np.empty((4, 2, 3), t)
a.fill(1)
b = a.copy()
c = a.copy()
c.fill(0)
self._test_equal(a, b)
self._test_not_equal(c, b)
# Test numeric types and object
for t in '?bhilqpBHILQPfdgFDG':
foo(t)
# Test strings
for t in ['S1', 'U1']:
foo(t)
def test_nan_array(self):
"""Test arrays with nan values in them."""
a = np.array([1, 2, np.nan])
b = np.array([1, 2, np.nan])
self._test_equal(a, b)
c = np.array([1, 2, 3])
self._test_not_equal(c, b)
def test_string_arrays(self):
"""Test two arrays with different shapes are found not equal."""
a = np.array(['floupi', 'floupa'])
b = np.array(['floupi', 'floupa'])
self._test_equal(a, b)
c = np.array(['floupipi', 'floupa'])
self._test_not_equal(c, b)
def test_recarrays(self):
"""Test record arrays."""
a = np.empty(2, [('floupi', np.float), ('floupa', np.float)])
a['floupi'] = [1, 2]
a['floupa'] = [1, 2]
b = a.copy()
self._test_equal(a, b)
c = np.empty(2, [('floupipi', np.float), ('floupa', np.float)])
c['floupipi'] = a['floupi'].copy()
c['floupa'] = a['floupa'].copy()
self._test_not_equal(c, b)
class TestBuildErrorMessage(unittest.TestCase):
def test_build_err_msg_defaults(self):
x = np.array([1.00001, 2.00002, 3.00003])
y = np.array([1.00002, 2.00003, 3.00004])
err_msg = 'There is a mismatch'
a = build_err_msg([x, y], err_msg)
b = ('\nItems are not equal: There is a mismatch\n ACTUAL: array([ '
'1.00001, 2.00002, 3.00003])\n DESIRED: array([ 1.00002, '
'2.00003, 3.00004])')
self.assertEqual(a, b)
def test_build_err_msg_no_verbose(self):
x = np.array([1.00001, 2.00002, 3.00003])
y = np.array([1.00002, 2.00003, 3.00004])
err_msg = 'There is a mismatch'
a = build_err_msg([x, y], err_msg, verbose=False)
b = '\nItems are not equal: There is a mismatch'
self.assertEqual(a, b)
def test_build_err_msg_custom_names(self):
x = np.array([1.00001, 2.00002, 3.00003])
y = np.array([1.00002, 2.00003, 3.00004])
err_msg = 'There is a mismatch'
a = build_err_msg([x, y], err_msg, names=('FOO', 'BAR'))
b = ('\nItems are not equal: There is a mismatch\n FOO: array([ '
'1.00001, 2.00002, 3.00003])\n BAR: array([ 1.00002, 2.00003, '
'3.00004])')
self.assertEqual(a, b)
def test_build_err_msg_custom_precision(self):
x = np.array([1.000000001, 2.00002, 3.00003])
y = np.array([1.000000002, 2.00003, 3.00004])
err_msg = 'There is a mismatch'
a = build_err_msg([x, y], err_msg, precision=10)
b = ('\nItems are not equal: There is a mismatch\n ACTUAL: array([ '
'1.000000001, 2.00002 , 3.00003 ])\n DESIRED: array([ '
'1.000000002, 2.00003 , 3.00004 ])')
self.assertEqual(a, b)
class TestEqual(TestArrayEqual):
def setUp(self):
self._assert_func = assert_equal
def test_nan_items(self):
self._assert_func(np.nan, np.nan)
self._assert_func([np.nan], [np.nan])
self._test_not_equal(np.nan, [np.nan])
self._test_not_equal(np.nan, 1)
def test_inf_items(self):
self._assert_func(np.inf, np.inf)
self._assert_func([np.inf], [np.inf])
self._test_not_equal(np.inf, [np.inf])
def test_non_numeric(self):
self._assert_func('ab', 'ab')
self._test_not_equal('ab', 'abb')
def test_complex_item(self):
self._assert_func(complex(1, 2), complex(1, 2))
self._assert_func(complex(1, np.nan), complex(1, np.nan))
self._test_not_equal(complex(1, np.nan), complex(1, 2))
self._test_not_equal(complex(np.nan, 1), complex(1, np.nan))
self._test_not_equal(complex(np.nan, np.inf), complex(np.nan, 2))
def test_negative_zero(self):
self._test_not_equal(np.PZERO, np.NZERO)
def test_complex(self):
x = np.array([complex(1, 2), complex(1, np.nan)])
y = np.array([complex(1, 2), complex(1, 2)])
self._assert_func(x, x)
self._test_not_equal(x, y)
class TestArrayAlmostEqual(_GenericTest, unittest.TestCase):
def setUp(self):
self._assert_func = assert_array_almost_equal
def test_simple(self):
x = np.array([1234.2222])
y = np.array([1234.2223])
self._assert_func(x, y, decimal=3)
self._assert_func(x, y, decimal=4)
self.assertRaises(AssertionError,
lambda: self._assert_func(x, y, decimal=5))
def test_nan(self):
anan = np.array([np.nan])
aone = np.array([1])
ainf = np.array([np.inf])
self._assert_func(anan, anan)
self.assertRaises(AssertionError,
lambda : self._assert_func(anan, aone))
self.assertRaises(AssertionError,
lambda : self._assert_func(anan, ainf))
self.assertRaises(AssertionError,
lambda : self._assert_func(ainf, anan))
def test_inf(self):
a = np.array([[1., 2.], [3., 4.]])
b = a.copy()
a[0, 0] = np.inf
self.assertRaises(AssertionError,
lambda : self._assert_func(a, b))
def test_subclass(self):
a = np.array([[1., 2.], [3., 4.]])
b = np.ma.masked_array([[1., 2.], [0., 4.]],
[[False, False], [True, False]])
assert_array_almost_equal(a, b)
assert_array_almost_equal(b, a)
assert_array_almost_equal(b, b)
class TestAlmostEqual(_GenericTest, unittest.TestCase):
def setUp(self):
self._assert_func = assert_almost_equal
def test_nan_item(self):
self._assert_func(np.nan, np.nan)
self.assertRaises(AssertionError,
lambda : self._assert_func(np.nan, 1))
self.assertRaises(AssertionError,
lambda : self._assert_func(np.nan, np.inf))
self.assertRaises(AssertionError,
lambda : self._assert_func(np.inf, np.nan))
def test_inf_item(self):
self._assert_func(np.inf, np.inf)
self._assert_func(-np.inf, -np.inf)
self.assertRaises(AssertionError,
lambda : self._assert_func(np.inf, 1))
def test_simple_item(self):
self._test_not_equal(1, 2)
def test_complex_item(self):
self._assert_func(complex(1, 2), complex(1, 2))
self._assert_func(complex(1, np.nan), complex(1, np.nan))
self._assert_func(complex(np.inf, np.nan), complex(np.inf, np.nan))
self._test_not_equal(complex(1, np.nan), complex(1, 2))
self._test_not_equal(complex(np.nan, 1), complex(1, np.nan))
self._test_not_equal(complex(np.nan, np.inf), complex(np.nan, 2))
def test_complex(self):
x = np.array([complex(1, 2), complex(1, np.nan)])
z = np.array([complex(1, 2), complex(np.nan, 1)])
y = np.array([complex(1, 2), complex(1, 2)])
self._assert_func(x, x)
self._test_not_equal(x, y)
self._test_not_equal(x, z)
def test_error_message(self):
"""Check the message is formatted correctly for the decimal value"""
x = np.array([1.00000000001, 2.00000000002, 3.00003])
y = np.array([1.00000000002, 2.00000000003, 3.00004])
# test with a different amount of decimal digits
# note that we only check for the formatting of the arrays themselves
b = ('x: array([ 1.00000000001, 2.00000000002, 3.00003 '
' ])\n y: array([ 1.00000000002, 2.00000000003, 3.00004 ])')
try:
self._assert_func(x, y, decimal=12)
except AssertionError as e:
# remove anything that's not the array string
self.assertEqual(str(e).split('%)\n ')[1], b)
# with the default value of decimal digits, only the 3rd element differs
# note that we only check for the formatting of the arrays themselves
b = ('x: array([ 1. , 2. , 3.00003])\n y: array([ 1. , '
'2. , 3.00004])')
try:
self._assert_func(x, y)
except AssertionError as e:
# remove anything that's not the array string
self.assertEqual(str(e).split('%)\n ')[1], b)
class TestApproxEqual(unittest.TestCase):
def setUp(self):
self._assert_func = assert_approx_equal
def test_simple_arrays(self):
x = np.array([1234.22])
y = np.array([1234.23])
self._assert_func(x, y, significant=5)
self._assert_func(x, y, significant=6)
self.assertRaises(AssertionError,
lambda: self._assert_func(x, y, significant=7))
def test_simple_items(self):
x = 1234.22
y = 1234.23
self._assert_func(x, y, significant=4)
self._assert_func(x, y, significant=5)
self._assert_func(x, y, significant=6)
self.assertRaises(AssertionError,
lambda: self._assert_func(x, y, significant=7))
def test_nan_array(self):
anan = np.array(np.nan)
aone = np.array(1)
ainf = np.array(np.inf)
self._assert_func(anan, anan)
self.assertRaises(AssertionError,
lambda : self._assert_func(anan, aone))
self.assertRaises(AssertionError,
lambda : self._assert_func(anan, ainf))
self.assertRaises(AssertionError,
lambda : self._assert_func(ainf, anan))
def test_nan_items(self):
anan = np.array(np.nan)
aone = np.array(1)
ainf = np.array(np.inf)
self._assert_func(anan, anan)
self.assertRaises(AssertionError,
lambda : self._assert_func(anan, aone))
self.assertRaises(AssertionError,
lambda : self._assert_func(anan, ainf))
self.assertRaises(AssertionError,
lambda : self._assert_func(ainf, anan))
class TestRaises(unittest.TestCase):
def setUp(self):
class MyException(Exception):
pass
self.e = MyException
def raises_exception(self, e):
raise e
def does_not_raise_exception(self):
pass
def test_correct_catch(self):
f = raises(self.e)(self.raises_exception)(self.e)
def test_wrong_exception(self):
try:
f = raises(self.e)(self.raises_exception)(RuntimeError)
except RuntimeError:
return
else:
raise AssertionError("should have caught RuntimeError")
def test_catch_no_raise(self):
try:
f = raises(self.e)(self.does_not_raise_exception)()
except AssertionError:
return
else:
raise AssertionError("should have raised an AssertionError")
class TestWarns(unittest.TestCase):
def test_warn(self):
def f():
warnings.warn("yo")
return 3
before_filters = sys.modules['warnings'].filters[:]
assert_equal(assert_warns(UserWarning, f), 3)
after_filters = sys.modules['warnings'].filters
assert_raises(AssertionError, assert_no_warnings, f)
assert_equal(assert_no_warnings(lambda x: x, 1), 1)
# Check that the warnings state is unchanged
assert_equal(before_filters, after_filters,
"assert_warns does not preserver warnings state")
def test_warn_wrong_warning(self):
def f():
warnings.warn("yo", DeprecationWarning)
failed = False
filters = sys.modules['warnings'].filters[:]
try:
try:
# Should raise an AssertionError
assert_warns(UserWarning, f)
failed = True
except AssertionError:
pass
finally:
sys.modules['warnings'].filters = filters
if failed:
raise AssertionError("wrong warning caught by assert_warn")
class TestAssertAllclose(unittest.TestCase):
def test_simple(self):
x = 1e-3
y = 1e-9
assert_allclose(x, y, atol=1)
self.assertRaises(AssertionError, assert_allclose, x, y)
a = np.array([x, y, x, y])
b = np.array([x, y, x, x])
assert_allclose(a, b, atol=1)
self.assertRaises(AssertionError, assert_allclose, a, b)
b[-1] = y * (1 + 1e-8)
assert_allclose(a, b)
self.assertRaises(AssertionError, assert_allclose, a, b,
rtol=1e-9)
assert_allclose(6, 10, rtol=0.5)
self.assertRaises(AssertionError, assert_allclose, 10, 6, rtol=0.5)
def test_min_int(self):
a = np.array([np.iinfo(np.int_).min], dtype=np.int_)
# Should not raise:
assert_allclose(a, a)
class TestArrayAlmostEqualNulp(unittest.TestCase):
@dec.knownfailureif(True, "Github issue #347")
def test_simple(self):
np.random.seed(12345)
for i in range(100):
dev = np.random.randn(10)
x = np.ones(10)
y = x + dev * np.finfo(np.float64).eps
assert_array_almost_equal_nulp(x, y, nulp=2 * np.max(dev))
def test_simple2(self):
x = np.random.randn(10)
y = 2 * x
def failure():
return assert_array_almost_equal_nulp(x, y,
nulp=1000)
self.assertRaises(AssertionError, failure)
def test_big_float32(self):
x = (1e10 * np.random.randn(10)).astype(np.float32)
y = x + 1
assert_array_almost_equal_nulp(x, y, nulp=1000)
def test_big_float64(self):
x = 1e10 * np.random.randn(10)
y = x + 1
def failure():
assert_array_almost_equal_nulp(x, y, nulp=1000)
self.assertRaises(AssertionError, failure)
def test_complex(self):
x = np.random.randn(10) + 1j * np.random.randn(10)
y = x + 1
def failure():
assert_array_almost_equal_nulp(x, y, nulp=1000)
self.assertRaises(AssertionError, failure)
def test_complex2(self):
x = np.random.randn(10)
y = np.array(x, np.complex) + 1e-16 * np.random.randn(10)
assert_array_almost_equal_nulp(x, y, nulp=1000)
class TestULP(unittest.TestCase):
def test_equal(self):
x = np.random.randn(10)
assert_array_max_ulp(x, x, maxulp=0)
def test_single(self):
# Generate 1 + small deviation, check that adding eps gives a few UNL
x = np.ones(10).astype(np.float32)
x += 0.01 * np.random.randn(10).astype(np.float32)
eps = np.finfo(np.float32).eps
assert_array_max_ulp(x, x+eps, maxulp=20)
def test_double(self):
# Generate 1 + small deviation, check that adding eps gives a few UNL
x = np.ones(10).astype(np.float64)
x += 0.01 * np.random.randn(10).astype(np.float64)
eps = np.finfo(np.float64).eps
assert_array_max_ulp(x, x+eps, maxulp=200)
def test_inf(self):
for dt in [np.float32, np.float64]:
inf = np.array([np.inf]).astype(dt)
big = np.array([np.finfo(dt).max])
assert_array_max_ulp(inf, big, maxulp=200)
def test_nan(self):
# Test that nan is 'far' from small, tiny, inf, max and min
for dt in [np.float32, np.float64]:
if dt == np.float32:
maxulp = 1e6
else:
maxulp = 1e12
inf = np.array([np.inf]).astype(dt)
nan = np.array([np.nan]).astype(dt)
big = np.array([np.finfo(dt).max])
tiny = np.array([np.finfo(dt).tiny])
zero = np.array([np.PZERO]).astype(dt)
nzero = np.array([np.NZERO]).astype(dt)
self.assertRaises(AssertionError,
lambda: assert_array_max_ulp(nan, inf,
maxulp=maxulp))
self.assertRaises(AssertionError,
lambda: assert_array_max_ulp(nan, big,
maxulp=maxulp))
self.assertRaises(AssertionError,
lambda: assert_array_max_ulp(nan, tiny,
maxulp=maxulp))
self.assertRaises(AssertionError,
lambda: assert_array_max_ulp(nan, zero,
maxulp=maxulp))
self.assertRaises(AssertionError,
lambda: assert_array_max_ulp(nan, nzero,
maxulp=maxulp))
if __name__ == '__main__':
run_module_suite()
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