Mercurial > hg > vamp-build-and-test
diff DEPENDENCIES/mingw32/Python27/Lib/site-packages/numpy/ma/tests/test_regression.py @ 87:2a2c65a20a8b
Add Python libs and headers
author | Chris Cannam |
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date | Wed, 25 Feb 2015 14:05:22 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/DEPENDENCIES/mingw32/Python27/Lib/site-packages/numpy/ma/tests/test_regression.py Wed Feb 25 14:05:22 2015 +0000 @@ -0,0 +1,75 @@ +from __future__ import division, absolute_import, print_function + +import numpy as np +from numpy.testing import * +from numpy.compat import sixu + +rlevel = 1 + + +class TestRegression(TestCase): + def test_masked_array_create(self,level=rlevel): + # Ticket #17 + x = np.ma.masked_array([0, 1, 2, 3, 0, 4, 5, 6], + mask=[0, 0, 0, 1, 1, 1, 0, 0]) + assert_array_equal(np.ma.nonzero(x), [[1, 2, 6, 7]]) + + def test_masked_array(self,level=rlevel): + # Ticket #61 + np.ma.array(1, mask=[1]) + + def test_mem_masked_where(self,level=rlevel): + # Ticket #62 + from numpy.ma import masked_where, MaskType + a = np.zeros((1, 1)) + b = np.zeros(a.shape, MaskType) + c = masked_where(b, a) + a-c + + def test_masked_array_multiply(self,level=rlevel): + # Ticket #254 + a = np.ma.zeros((4, 1)) + a[2, 0] = np.ma.masked + b = np.zeros((4, 2)) + a*b + b*a + + def test_masked_array_repeat(self, level=rlevel): + # Ticket #271 + np.ma.array([1], mask=False).repeat(10) + + def test_masked_array_repr_unicode(self): + # Ticket #1256 + repr(np.ma.array(sixu("Unicode"))) + + def test_atleast_2d(self): + # Ticket #1559 + a = np.ma.masked_array([0.0, 1.2, 3.5], mask=[False, True, False]) + b = np.atleast_2d(a) + assert_(a.mask.ndim == 1) + assert_(b.mask.ndim == 2) + + def test_set_fill_value_unicode_py3(self): + # Ticket #2733 + a = np.ma.masked_array(['a', 'b', 'c'], mask=[1, 0, 0]) + a.fill_value = 'X' + assert_(a.fill_value == 'X') + + def test_var_sets_maskedarray_scalar(self): + # Issue gh-2757 + a = np.ma.array(np.arange(5), mask=True) + mout = np.ma.array(-1, dtype=float) + a.var(out=mout) + assert_(mout._data == 0) + + def test_ddof_corrcoef(self): + # See gh-3336 + x = np.ma.masked_equal([1, 2, 3, 4, 5], 4) + y = np.array([2, 2.5, 3.1, 3, 5]) + r0 = np.ma.corrcoef(x, y, ddof=0) + r1 = np.ma.corrcoef(x, y, ddof=1) + # ddof should not have an effect (it gets cancelled out) + assert_allclose(r0.data, r1.data) + +if __name__ == "__main__": + run_module_suite()