99 lines
2.9 KiB
Python
99 lines
2.9 KiB
Python
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import numpy as np
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import numpy.core as nx
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import numpy.lib.ufunclike as ufl
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from numpy.testing import (
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assert_, assert_equal, assert_array_equal, assert_warns, assert_raises
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)
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class TestUfunclike:
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def test_isposinf(self):
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a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0])
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out = nx.zeros(a.shape, bool)
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tgt = nx.array([True, False, False, False, False, False])
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res = ufl.isposinf(a)
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assert_equal(res, tgt)
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res = ufl.isposinf(a, out)
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assert_equal(res, tgt)
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assert_equal(out, tgt)
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a = a.astype(np.complex_)
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with assert_raises(TypeError):
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ufl.isposinf(a)
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def test_isneginf(self):
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a = nx.array([nx.inf, -nx.inf, nx.nan, 0.0, 3.0, -3.0])
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out = nx.zeros(a.shape, bool)
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tgt = nx.array([False, True, False, False, False, False])
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res = ufl.isneginf(a)
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assert_equal(res, tgt)
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res = ufl.isneginf(a, out)
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assert_equal(res, tgt)
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assert_equal(out, tgt)
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a = a.astype(np.complex_)
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with assert_raises(TypeError):
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ufl.isneginf(a)
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def test_fix(self):
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a = nx.array([[1.0, 1.1, 1.5, 1.8], [-1.0, -1.1, -1.5, -1.8]])
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out = nx.zeros(a.shape, float)
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tgt = nx.array([[1., 1., 1., 1.], [-1., -1., -1., -1.]])
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res = ufl.fix(a)
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assert_equal(res, tgt)
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res = ufl.fix(a, out)
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assert_equal(res, tgt)
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assert_equal(out, tgt)
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assert_equal(ufl.fix(3.14), 3)
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def test_fix_with_subclass(self):
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class MyArray(nx.ndarray):
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def __new__(cls, data, metadata=None):
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res = nx.array(data, copy=True).view(cls)
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res.metadata = metadata
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return res
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def __array_wrap__(self, obj, context=None):
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if isinstance(obj, MyArray):
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obj.metadata = self.metadata
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return obj
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def __array_finalize__(self, obj):
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self.metadata = getattr(obj, 'metadata', None)
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return self
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a = nx.array([1.1, -1.1])
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m = MyArray(a, metadata='foo')
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f = ufl.fix(m)
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assert_array_equal(f, nx.array([1, -1]))
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assert_(isinstance(f, MyArray))
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assert_equal(f.metadata, 'foo')
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# check 0d arrays don't decay to scalars
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m0d = m[0,...]
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m0d.metadata = 'bar'
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f0d = ufl.fix(m0d)
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assert_(isinstance(f0d, MyArray))
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assert_equal(f0d.metadata, 'bar')
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def test_scalar(self):
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x = np.inf
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actual = np.isposinf(x)
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expected = np.True_
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assert_equal(actual, expected)
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assert_equal(type(actual), type(expected))
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x = -3.4
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actual = np.fix(x)
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expected = np.float64(-3.0)
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assert_equal(actual, expected)
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assert_equal(type(actual), type(expected))
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out = np.array(0.0)
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actual = np.fix(x, out=out)
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assert_(actual is out)
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