101 lines
3.0 KiB
Python
101 lines
3.0 KiB
Python
|
import numpy as np
|
||
|
|
||
|
from numpy import fix, isposinf, isneginf
|
||
|
from numpy.testing import (
|
||
|
assert_, assert_equal, assert_array_equal, assert_raises
|
||
|
)
|
||
|
|
||
|
|
||
|
class TestUfunclike:
|
||
|
|
||
|
def test_isposinf(self):
|
||
|
a = np.array([np.inf, -np.inf, np.nan, 0.0, 3.0, -3.0])
|
||
|
out = np.zeros(a.shape, bool)
|
||
|
tgt = np.array([True, False, False, False, False, False])
|
||
|
|
||
|
res = isposinf(a)
|
||
|
assert_equal(res, tgt)
|
||
|
res = isposinf(a, out)
|
||
|
assert_equal(res, tgt)
|
||
|
assert_equal(out, tgt)
|
||
|
|
||
|
a = a.astype(np.complex128)
|
||
|
with assert_raises(TypeError):
|
||
|
isposinf(a)
|
||
|
|
||
|
def test_isneginf(self):
|
||
|
a = np.array([np.inf, -np.inf, np.nan, 0.0, 3.0, -3.0])
|
||
|
out = np.zeros(a.shape, bool)
|
||
|
tgt = np.array([False, True, False, False, False, False])
|
||
|
|
||
|
res = isneginf(a)
|
||
|
assert_equal(res, tgt)
|
||
|
res = isneginf(a, out)
|
||
|
assert_equal(res, tgt)
|
||
|
assert_equal(out, tgt)
|
||
|
|
||
|
a = a.astype(np.complex128)
|
||
|
with assert_raises(TypeError):
|
||
|
isneginf(a)
|
||
|
|
||
|
def test_fix(self):
|
||
|
a = np.array([[1.0, 1.1, 1.5, 1.8], [-1.0, -1.1, -1.5, -1.8]])
|
||
|
out = np.zeros(a.shape, float)
|
||
|
tgt = np.array([[1., 1., 1., 1.], [-1., -1., -1., -1.]])
|
||
|
|
||
|
res = fix(a)
|
||
|
assert_equal(res, tgt)
|
||
|
res = fix(a, out)
|
||
|
assert_equal(res, tgt)
|
||
|
assert_equal(out, tgt)
|
||
|
assert_equal(fix(3.14), 3)
|
||
|
|
||
|
def test_fix_with_subclass(self):
|
||
|
class MyArray(np.ndarray):
|
||
|
def __new__(cls, data, metadata=None):
|
||
|
res = np.array(data, copy=True).view(cls)
|
||
|
res.metadata = metadata
|
||
|
return res
|
||
|
|
||
|
def __array_wrap__(self, obj, context=None, return_scalar=False):
|
||
|
if not isinstance(obj, MyArray):
|
||
|
obj = obj.view(MyArray)
|
||
|
if obj.metadata is None:
|
||
|
obj.metadata = self.metadata
|
||
|
return obj
|
||
|
|
||
|
def __array_finalize__(self, obj):
|
||
|
self.metadata = getattr(obj, 'metadata', None)
|
||
|
return self
|
||
|
|
||
|
a = np.array([1.1, -1.1])
|
||
|
m = MyArray(a, metadata='foo')
|
||
|
f = fix(m)
|
||
|
assert_array_equal(f, np.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 = fix(m0d)
|
||
|
assert_(isinstance(f0d, MyArray))
|
||
|
assert_equal(f0d.metadata, 'bar')
|
||
|
|
||
|
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)
|