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Direktori : /proc/self/root/opt/alt/python37/lib64/python3.7/site-packages/numpy/ma/tests/ |
Current File : //proc/self/root/opt/alt/python37/lib64/python3.7/site-packages/numpy/ma/tests/test_regression.py |
from __future__ import division, absolute_import, print_function import warnings import numpy as np from numpy.testing import (assert_, TestCase, assert_array_equal, assert_allclose, run_module_suite, suppress_warnings) 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(u"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]) # this test can be removed after deprecation. with suppress_warnings() as sup: sup.filter(DeprecationWarning, "bias and ddof have no effect") 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()