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📄 test__datasource.py(10.16 KB)
📄 test__iotools.py(13.15 KB)
📄 test__version.py(2.08 KB)
📄 test_arraypad.py(42.68 KB)
📄 test_arraysetops.py(15.49 KB)
📄 test_arrayterator.py(1.42 KB)
📄 test_financial.py(6.62 KB)
📄 test_format.py(33.49 KB)
📄 test_function_base.py(126.81 KB)
📄 test_index_tricks.py(13.1 KB)
📄 test_io.py(75.59 KB)
📄 test_mixins.py(6.7 KB)
📄 test_nanfunctions.py(34.07 KB)
📄 test_packbits.py(12.63 KB)
📄 test_polynomial.py(7.03 KB)
📄 test_recfunctions.py(30.54 KB)
📄 test_regression.py(8.62 KB)
📄 test_shape_base.py(19.02 KB)
📄 test_stride_tricks.py(14.69 KB)
📄 test_twodim_base.py(16.72 KB)
📄 test_type_check.py(12.62 KB)
📄 test_ufunclike.py(2.96 KB)
📄 test_utils.py(1.62 KB)

Editing: test_ufunclike.py

from __future__ import division, absolute_import, print_function

import numpy as np
import numpy.core as nx
import numpy.lib.ufunclike as ufl
from numpy.testing import (
    run_module_suite, TestCase, assert_, assert_equal, assert_array_equal,
    assert_warns
    )

class TestUfunclike(TestCase):

def test_isposinf(self):
        a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0])
        out = nx.zeros(a.shape, bool)
        tgt = nx.array([True, False, False, False, False, False])

res = ufl.isposinf(a)
        assert_equal(res, tgt)
        res = ufl.isposinf(a, out)
        assert_equal(res, tgt)
        assert_equal(out, tgt)

def test_isneginf(self):
        a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0])
        out = nx.zeros(a.shape, bool)
        tgt = nx.array([False, True, False, False, False, False])

res = ufl.isneginf(a)
        assert_equal(res, tgt)
        res = ufl.isneginf(a, out)
        assert_equal(res, tgt)
        assert_equal(out, tgt)

def test_fix(self):
        a = nx.array([[1.0, 1.1, 1.5, 1.8], [-1.0, -1.1, -1.5, -1.8]])
        out = nx.zeros(a.shape, float)
        tgt = nx.array([[1., 1., 1., 1.], [-1., -1., -1., -1.]])

res = ufl.fix(a)
        assert_equal(res, tgt)
        res = ufl.fix(a, out)
        assert_equal(res, tgt)
        assert_equal(out, tgt)
        assert_equal(ufl.fix(3.14), 3)

def test_fix_with_subclass(self):
        class MyArray(nx.ndarray):
            def __new__(cls, data, metadata=None):
                res = nx.array(data, copy=True).view(cls)
                res.metadata = metadata
                return res

def __array_wrap__(self, obj, context=None):
                obj.metadata = self.metadata
                return obj

a = nx.array([1.1, -1.1])
        m = MyArray(a, metadata='foo')
        f = ufl.fix(m)
        assert_array_equal(f, nx.array([1, -1]))
        assert_(isinstance(f, MyArray))
        assert_equal(f.metadata, 'foo')

# check 0d arrays don't decay to scalars
        m0d = m[0,...]
        m0d.metadata = 'bar'
        f0d = ufl.fix(m0d)
        assert_(isinstance(f0d, MyArray))
        assert_equal(f0d.metadata, 'bar')

def test_deprecated(self):
        # NumPy 1.13.0, 2017-04-26
        assert_warns(DeprecationWarning, ufl.fix, [1, 2], y=nx.empty(2))
        assert_warns(DeprecationWarning, ufl.isposinf, [1, 2], y=nx.empty(2))
        assert_warns(DeprecationWarning, ufl.isneginf, [1, 2], y=nx.empty(2))

def test_scalar(self):
        x = np.inf
        actual = np.isposinf(x)
        expected = np.True_
        assert_equal(actual, expected)
        assert_equal(type(actual), type(expected))

x = -3.4
        actual = np.fix(x)
        expected = np.float64(-3.0)
        assert_equal(actual, expected)
        assert_equal(type(actual), type(expected))

out = np.array(0.0)
        actual = np.fix(x, out=out)
        assert_(actual is out)

if __name__ == "__main__":
    run_module_suite()

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