Chris@87: from __future__ import division, absolute_import, print_function Chris@87: Chris@87: import warnings Chris@87: Chris@87: import numpy as np Chris@87: from numpy.testing import ( Chris@87: run_module_suite, TestCase, assert_, assert_equal, assert_almost_equal, Chris@87: assert_raises, assert_array_equal Chris@87: ) Chris@87: Chris@87: Chris@87: # Test data Chris@87: _ndat = np.array([[0.6244, np.nan, 0.2692, 0.0116, np.nan, 0.1170], Chris@87: [0.5351, -0.9403, np.nan, 0.2100, 0.4759, 0.2833], Chris@87: [np.nan, np.nan, np.nan, 0.1042, np.nan, -0.5954], Chris@87: [0.1610, np.nan, np.nan, 0.1859, 0.3146, np.nan]]) Chris@87: Chris@87: Chris@87: # Rows of _ndat with nans removed Chris@87: _rdat = [np.array([0.6244, 0.2692, 0.0116, 0.1170]), Chris@87: np.array([0.5351, -0.9403, 0.2100, 0.4759, 0.2833]), Chris@87: np.array([0.1042, -0.5954]), Chris@87: np.array([0.1610, 0.1859, 0.3146])] Chris@87: Chris@87: Chris@87: class TestNanFunctions_MinMax(TestCase): Chris@87: Chris@87: nanfuncs = [np.nanmin, np.nanmax] Chris@87: stdfuncs = [np.min, np.max] Chris@87: Chris@87: def test_mutation(self): Chris@87: # Check that passed array is not modified. Chris@87: ndat = _ndat.copy() Chris@87: for f in self.nanfuncs: Chris@87: f(ndat) Chris@87: assert_equal(ndat, _ndat) Chris@87: Chris@87: def test_keepdims(self): Chris@87: mat = np.eye(3) Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: for axis in [None, 0, 1]: Chris@87: tgt = rf(mat, axis=axis, keepdims=True) Chris@87: res = nf(mat, axis=axis, keepdims=True) Chris@87: assert_(res.ndim == tgt.ndim) Chris@87: Chris@87: def test_out(self): Chris@87: mat = np.eye(3) Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: resout = np.zeros(3) Chris@87: tgt = rf(mat, axis=1) Chris@87: res = nf(mat, axis=1, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_dtype_from_input(self): Chris@87: codes = 'efdgFDG' Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: for c in codes: Chris@87: mat = np.eye(3, dtype=c) Chris@87: tgt = rf(mat, axis=1).dtype.type Chris@87: res = nf(mat, axis=1).dtype.type Chris@87: assert_(res is tgt) Chris@87: # scalar case Chris@87: tgt = rf(mat, axis=None).dtype.type Chris@87: res = nf(mat, axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_result_values(self): Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: tgt = [rf(d) for d in _rdat] Chris@87: res = nf(_ndat, axis=1) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_allnans(self): Chris@87: mat = np.array([np.nan]*9).reshape(3, 3) Chris@87: for f in self.nanfuncs: Chris@87: for axis in [None, 0, 1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(f(mat, axis=axis)).all()) Chris@87: assert_(len(w) == 1, 'no warning raised') Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: # Check scalars Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(f(np.nan))) Chris@87: assert_(len(w) == 1, 'no warning raised') Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: Chris@87: def test_masked(self): Chris@87: mat = np.ma.fix_invalid(_ndat) Chris@87: msk = mat._mask.copy() Chris@87: for f in [np.nanmin]: Chris@87: res = f(mat, axis=1) Chris@87: tgt = f(_ndat, axis=1) Chris@87: assert_equal(res, tgt) Chris@87: assert_equal(mat._mask, msk) Chris@87: assert_(not np.isinf(mat).any()) Chris@87: Chris@87: def test_scalar(self): Chris@87: for f in self.nanfuncs: Chris@87: assert_(f(0.) == 0.) Chris@87: Chris@87: def test_matrices(self): Chris@87: # Check that it works and that type and Chris@87: # shape are preserved Chris@87: mat = np.matrix(np.eye(3)) Chris@87: for f in self.nanfuncs: Chris@87: res = f(mat, axis=0) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (1, 3)) Chris@87: res = f(mat, axis=1) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (3, 1)) Chris@87: res = f(mat) Chris@87: assert_(np.isscalar(res)) Chris@87: # check that rows of nan are dealt with for subclasses (#4628) Chris@87: mat[1] = np.nan Chris@87: for f in self.nanfuncs: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: res = f(mat, axis=0) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(not np.any(np.isnan(res))) Chris@87: assert_(len(w) == 0) Chris@87: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: res = f(mat, axis=1) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(np.isnan(res[1, 0]) and not np.isnan(res[0, 0]) Chris@87: and not np.isnan(res[2, 0])) Chris@87: assert_(len(w) == 1, 'no warning raised') Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: res = f(mat) Chris@87: assert_(np.isscalar(res)) Chris@87: assert_(res != np.nan) Chris@87: assert_(len(w) == 0) Chris@87: Chris@87: Chris@87: class TestNanFunctions_ArgminArgmax(TestCase): Chris@87: Chris@87: nanfuncs = [np.nanargmin, np.nanargmax] Chris@87: Chris@87: def test_mutation(self): Chris@87: # Check that passed array is not modified. Chris@87: ndat = _ndat.copy() Chris@87: for f in self.nanfuncs: Chris@87: f(ndat) Chris@87: assert_equal(ndat, _ndat) Chris@87: Chris@87: def test_result_values(self): Chris@87: for f, fcmp in zip(self.nanfuncs, [np.greater, np.less]): Chris@87: for row in _ndat: Chris@87: with warnings.catch_warnings(record=True): Chris@87: warnings.simplefilter('always') Chris@87: ind = f(row) Chris@87: val = row[ind] Chris@87: # comparing with NaN is tricky as the result Chris@87: # is always false except for NaN != NaN Chris@87: assert_(not np.isnan(val)) Chris@87: assert_(not fcmp(val, row).any()) Chris@87: assert_(not np.equal(val, row[:ind]).any()) Chris@87: Chris@87: def test_allnans(self): Chris@87: mat = np.array([np.nan]*9).reshape(3, 3) Chris@87: for f in self.nanfuncs: Chris@87: for axis in [None, 0, 1]: Chris@87: assert_raises(ValueError, f, mat, axis=axis) Chris@87: assert_raises(ValueError, f, np.nan) Chris@87: Chris@87: def test_empty(self): Chris@87: mat = np.zeros((0, 3)) Chris@87: for f in self.nanfuncs: Chris@87: for axis in [0, None]: Chris@87: assert_raises(ValueError, f, mat, axis=axis) Chris@87: for axis in [1]: Chris@87: res = f(mat, axis=axis) Chris@87: assert_equal(res, np.zeros(0)) Chris@87: Chris@87: def test_scalar(self): Chris@87: for f in self.nanfuncs: Chris@87: assert_(f(0.) == 0.) Chris@87: Chris@87: def test_matrices(self): Chris@87: # Check that it works and that type and Chris@87: # shape are preserved Chris@87: mat = np.matrix(np.eye(3)) Chris@87: for f in self.nanfuncs: Chris@87: res = f(mat, axis=0) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (1, 3)) Chris@87: res = f(mat, axis=1) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (3, 1)) Chris@87: res = f(mat) Chris@87: assert_(np.isscalar(res)) Chris@87: Chris@87: Chris@87: class TestNanFunctions_IntTypes(TestCase): Chris@87: Chris@87: int_types = (np.int8, np.int16, np.int32, np.int64, np.uint8, Chris@87: np.uint16, np.uint32, np.uint64) Chris@87: Chris@87: mat = np.array([127, 39, 93, 87, 46]) Chris@87: Chris@87: def integer_arrays(self): Chris@87: for dtype in self.int_types: Chris@87: yield self.mat.astype(dtype) Chris@87: Chris@87: def test_nanmin(self): Chris@87: tgt = np.min(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanmin(mat), tgt) Chris@87: Chris@87: def test_nanmax(self): Chris@87: tgt = np.max(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanmax(mat), tgt) Chris@87: Chris@87: def test_nanargmin(self): Chris@87: tgt = np.argmin(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanargmin(mat), tgt) Chris@87: Chris@87: def test_nanargmax(self): Chris@87: tgt = np.argmax(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanargmax(mat), tgt) Chris@87: Chris@87: def test_nansum(self): Chris@87: tgt = np.sum(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nansum(mat), tgt) Chris@87: Chris@87: def test_nanmean(self): Chris@87: tgt = np.mean(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanmean(mat), tgt) Chris@87: Chris@87: def test_nanvar(self): Chris@87: tgt = np.var(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanvar(mat), tgt) Chris@87: Chris@87: tgt = np.var(mat, ddof=1) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanvar(mat, ddof=1), tgt) Chris@87: Chris@87: def test_nanstd(self): Chris@87: tgt = np.std(self.mat) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanstd(mat), tgt) Chris@87: Chris@87: tgt = np.std(self.mat, ddof=1) Chris@87: for mat in self.integer_arrays(): Chris@87: assert_equal(np.nanstd(mat, ddof=1), tgt) Chris@87: Chris@87: Chris@87: class TestNanFunctions_Sum(TestCase): Chris@87: Chris@87: def test_mutation(self): Chris@87: # Check that passed array is not modified. Chris@87: ndat = _ndat.copy() Chris@87: np.nansum(ndat) Chris@87: assert_equal(ndat, _ndat) Chris@87: Chris@87: def test_keepdims(self): Chris@87: mat = np.eye(3) Chris@87: for axis in [None, 0, 1]: Chris@87: tgt = np.sum(mat, axis=axis, keepdims=True) Chris@87: res = np.nansum(mat, axis=axis, keepdims=True) Chris@87: assert_(res.ndim == tgt.ndim) Chris@87: Chris@87: def test_out(self): Chris@87: mat = np.eye(3) Chris@87: resout = np.zeros(3) Chris@87: tgt = np.sum(mat, axis=1) Chris@87: res = np.nansum(mat, axis=1, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_dtype_from_dtype(self): Chris@87: mat = np.eye(3) Chris@87: codes = 'efdgFDG' Chris@87: for c in codes: Chris@87: tgt = np.sum(mat, dtype=np.dtype(c), axis=1).dtype.type Chris@87: res = np.nansum(mat, dtype=np.dtype(c), axis=1).dtype.type Chris@87: assert_(res is tgt) Chris@87: # scalar case Chris@87: tgt = np.sum(mat, dtype=np.dtype(c), axis=None).dtype.type Chris@87: res = np.nansum(mat, dtype=np.dtype(c), axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_dtype_from_char(self): Chris@87: mat = np.eye(3) Chris@87: codes = 'efdgFDG' Chris@87: for c in codes: Chris@87: tgt = np.sum(mat, dtype=c, axis=1).dtype.type Chris@87: res = np.nansum(mat, dtype=c, axis=1).dtype.type Chris@87: assert_(res is tgt) Chris@87: # scalar case Chris@87: tgt = np.sum(mat, dtype=c, axis=None).dtype.type Chris@87: res = np.nansum(mat, dtype=c, axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_dtype_from_input(self): Chris@87: codes = 'efdgFDG' Chris@87: for c in codes: Chris@87: mat = np.eye(3, dtype=c) Chris@87: tgt = np.sum(mat, axis=1).dtype.type Chris@87: res = np.nansum(mat, axis=1).dtype.type Chris@87: assert_(res is tgt) Chris@87: # scalar case Chris@87: tgt = np.sum(mat, axis=None).dtype.type Chris@87: res = np.nansum(mat, axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_result_values(self): Chris@87: tgt = [np.sum(d) for d in _rdat] Chris@87: res = np.nansum(_ndat, axis=1) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_allnans(self): Chris@87: # Check for FutureWarning Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: res = np.nansum([np.nan]*3, axis=None) Chris@87: assert_(res == 0, 'result is not 0') Chris@87: assert_(len(w) == 0, 'warning raised') Chris@87: # Check scalar Chris@87: res = np.nansum(np.nan) Chris@87: assert_(res == 0, 'result is not 0') Chris@87: assert_(len(w) == 0, 'warning raised') Chris@87: # Check there is no warning for not all-nan Chris@87: np.nansum([0]*3, axis=None) Chris@87: assert_(len(w) == 0, 'unwanted warning raised') Chris@87: Chris@87: def test_empty(self): Chris@87: mat = np.zeros((0, 3)) Chris@87: tgt = [0]*3 Chris@87: res = np.nansum(mat, axis=0) Chris@87: assert_equal(res, tgt) Chris@87: tgt = [] Chris@87: res = np.nansum(mat, axis=1) Chris@87: assert_equal(res, tgt) Chris@87: tgt = 0 Chris@87: res = np.nansum(mat, axis=None) Chris@87: assert_equal(res, tgt) Chris@87: Chris@87: def test_scalar(self): Chris@87: assert_(np.nansum(0.) == 0.) Chris@87: Chris@87: def test_matrices(self): Chris@87: # Check that it works and that type and Chris@87: # shape are preserved Chris@87: mat = np.matrix(np.eye(3)) Chris@87: res = np.nansum(mat, axis=0) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (1, 3)) Chris@87: res = np.nansum(mat, axis=1) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (3, 1)) Chris@87: res = np.nansum(mat) Chris@87: assert_(np.isscalar(res)) Chris@87: Chris@87: Chris@87: class TestNanFunctions_MeanVarStd(TestCase): Chris@87: Chris@87: nanfuncs = [np.nanmean, np.nanvar, np.nanstd] Chris@87: stdfuncs = [np.mean, np.var, np.std] Chris@87: Chris@87: def test_mutation(self): Chris@87: # Check that passed array is not modified. Chris@87: ndat = _ndat.copy() Chris@87: for f in self.nanfuncs: Chris@87: f(ndat) Chris@87: assert_equal(ndat, _ndat) Chris@87: Chris@87: def test_dtype_error(self): Chris@87: for f in self.nanfuncs: Chris@87: for dtype in [np.bool_, np.int_, np.object]: Chris@87: assert_raises(TypeError, f, _ndat, axis=1, dtype=np.int) Chris@87: Chris@87: def test_out_dtype_error(self): Chris@87: for f in self.nanfuncs: Chris@87: for dtype in [np.bool_, np.int_, np.object]: Chris@87: out = np.empty(_ndat.shape[0], dtype=dtype) Chris@87: assert_raises(TypeError, f, _ndat, axis=1, out=out) Chris@87: Chris@87: def test_keepdims(self): Chris@87: mat = np.eye(3) Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: for axis in [None, 0, 1]: Chris@87: tgt = rf(mat, axis=axis, keepdims=True) Chris@87: res = nf(mat, axis=axis, keepdims=True) Chris@87: assert_(res.ndim == tgt.ndim) Chris@87: Chris@87: def test_out(self): Chris@87: mat = np.eye(3) Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: resout = np.zeros(3) Chris@87: tgt = rf(mat, axis=1) Chris@87: res = nf(mat, axis=1, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_dtype_from_dtype(self): Chris@87: mat = np.eye(3) Chris@87: codes = 'efdgFDG' Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: for c in codes: Chris@87: tgt = rf(mat, dtype=np.dtype(c), axis=1).dtype.type Chris@87: res = nf(mat, dtype=np.dtype(c), axis=1).dtype.type Chris@87: assert_(res is tgt) Chris@87: # scalar case Chris@87: tgt = rf(mat, dtype=np.dtype(c), axis=None).dtype.type Chris@87: res = nf(mat, dtype=np.dtype(c), axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_dtype_from_char(self): Chris@87: mat = np.eye(3) Chris@87: codes = 'efdgFDG' Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: for c in codes: Chris@87: tgt = rf(mat, dtype=c, axis=1).dtype.type Chris@87: res = nf(mat, dtype=c, axis=1).dtype.type Chris@87: assert_(res is tgt) Chris@87: # scalar case Chris@87: tgt = rf(mat, dtype=c, axis=None).dtype.type Chris@87: res = nf(mat, dtype=c, axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_dtype_from_input(self): Chris@87: codes = 'efdgFDG' Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: for c in codes: Chris@87: mat = np.eye(3, dtype=c) Chris@87: tgt = rf(mat, axis=1).dtype.type Chris@87: res = nf(mat, axis=1).dtype.type Chris@87: assert_(res is tgt, "res %s, tgt %s" % (res, tgt)) Chris@87: # scalar case Chris@87: tgt = rf(mat, axis=None).dtype.type Chris@87: res = nf(mat, axis=None).dtype.type Chris@87: assert_(res is tgt) Chris@87: Chris@87: def test_ddof(self): Chris@87: nanfuncs = [np.nanvar, np.nanstd] Chris@87: stdfuncs = [np.var, np.std] Chris@87: for nf, rf in zip(nanfuncs, stdfuncs): Chris@87: for ddof in [0, 1]: Chris@87: tgt = [rf(d, ddof=ddof) for d in _rdat] Chris@87: res = nf(_ndat, axis=1, ddof=ddof) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_ddof_too_big(self): Chris@87: nanfuncs = [np.nanvar, np.nanstd] Chris@87: stdfuncs = [np.var, np.std] Chris@87: dsize = [len(d) for d in _rdat] Chris@87: for nf, rf in zip(nanfuncs, stdfuncs): Chris@87: for ddof in range(5): Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: tgt = [ddof >= d for d in dsize] Chris@87: res = nf(_ndat, axis=1, ddof=ddof) Chris@87: assert_equal(np.isnan(res), tgt) Chris@87: if any(tgt): Chris@87: assert_(len(w) == 1) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: else: Chris@87: assert_(len(w) == 0) Chris@87: Chris@87: def test_result_values(self): Chris@87: for nf, rf in zip(self.nanfuncs, self.stdfuncs): Chris@87: tgt = [rf(d) for d in _rdat] Chris@87: res = nf(_ndat, axis=1) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_allnans(self): Chris@87: mat = np.array([np.nan]*9).reshape(3, 3) Chris@87: for f in self.nanfuncs: Chris@87: for axis in [None, 0, 1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(f(mat, axis=axis)).all()) Chris@87: assert_(len(w) == 1) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: # Check scalar Chris@87: assert_(np.isnan(f(np.nan))) Chris@87: assert_(len(w) == 2) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: Chris@87: def test_empty(self): Chris@87: mat = np.zeros((0, 3)) Chris@87: for f in self.nanfuncs: Chris@87: for axis in [0, None]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(f(mat, axis=axis)).all()) Chris@87: assert_(len(w) == 1) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: for axis in [1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_equal(f(mat, axis=axis), np.zeros([])) Chris@87: assert_(len(w) == 0) Chris@87: Chris@87: def test_scalar(self): Chris@87: for f in self.nanfuncs: Chris@87: assert_(f(0.) == 0.) Chris@87: Chris@87: def test_matrices(self): Chris@87: # Check that it works and that type and Chris@87: # shape are preserved Chris@87: mat = np.matrix(np.eye(3)) Chris@87: for f in self.nanfuncs: Chris@87: res = f(mat, axis=0) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (1, 3)) Chris@87: res = f(mat, axis=1) Chris@87: assert_(isinstance(res, np.matrix)) Chris@87: assert_(res.shape == (3, 1)) Chris@87: res = f(mat) Chris@87: assert_(np.isscalar(res)) Chris@87: Chris@87: Chris@87: class TestNanFunctions_Median(TestCase): Chris@87: Chris@87: def test_mutation(self): Chris@87: # Check that passed array is not modified. Chris@87: ndat = _ndat.copy() Chris@87: np.nanmedian(ndat) Chris@87: assert_equal(ndat, _ndat) Chris@87: Chris@87: def test_keepdims(self): Chris@87: mat = np.eye(3) Chris@87: for axis in [None, 0, 1]: Chris@87: tgt = np.median(mat, axis=axis, out=None, overwrite_input=False) Chris@87: res = np.nanmedian(mat, axis=axis, out=None, overwrite_input=False) Chris@87: assert_(res.ndim == tgt.ndim) Chris@87: Chris@87: d = np.ones((3, 5, 7, 11)) Chris@87: # Randomly set some elements to NaN: Chris@87: w = np.random.random((4, 200)) * np.array(d.shape)[:, None] Chris@87: w = w.astype(np.intp) Chris@87: d[tuple(w)] = np.nan Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always', RuntimeWarning) Chris@87: res = np.nanmedian(d, axis=None, keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 1, 1)) Chris@87: res = np.nanmedian(d, axis=(0, 1), keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 7, 11)) Chris@87: res = np.nanmedian(d, axis=(0, 3), keepdims=True) Chris@87: assert_equal(res.shape, (1, 5, 7, 1)) Chris@87: res = np.nanmedian(d, axis=(1,), keepdims=True) Chris@87: assert_equal(res.shape, (3, 1, 7, 11)) Chris@87: res = np.nanmedian(d, axis=(0, 1, 2, 3), keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 1, 1)) Chris@87: res = np.nanmedian(d, axis=(0, 1, 3), keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 7, 1)) Chris@87: Chris@87: def test_out(self): Chris@87: mat = np.random.rand(3, 3) Chris@87: nan_mat = np.insert(mat, [0, 2], np.nan, axis=1) Chris@87: resout = np.zeros(3) Chris@87: tgt = np.median(mat, axis=1) Chris@87: res = np.nanmedian(nan_mat, axis=1, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: # 0-d output: Chris@87: resout = np.zeros(()) Chris@87: tgt = np.median(mat, axis=None) Chris@87: res = np.nanmedian(nan_mat, axis=None, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: res = np.nanmedian(nan_mat, axis=(0, 1), out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_small_large(self): Chris@87: # test the small and large code paths, current cutoff 400 elements Chris@87: for s in [5, 20, 51, 200, 1000]: Chris@87: d = np.random.randn(4, s) Chris@87: # Randomly set some elements to NaN: Chris@87: w = np.random.randint(0, d.size, size=d.size // 5) Chris@87: d.ravel()[w] = np.nan Chris@87: d[:,0] = 1. # ensure at least one good value Chris@87: # use normal median without nans to compare Chris@87: tgt = [] Chris@87: for x in d: Chris@87: nonan = np.compress(~np.isnan(x), x) Chris@87: tgt.append(np.median(nonan, overwrite_input=True)) Chris@87: Chris@87: assert_array_equal(np.nanmedian(d, axis=-1), tgt) Chris@87: Chris@87: def test_result_values(self): Chris@87: tgt = [np.median(d) for d in _rdat] Chris@87: res = np.nanmedian(_ndat, axis=1) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_allnans(self): Chris@87: mat = np.array([np.nan]*9).reshape(3, 3) Chris@87: for axis in [None, 0, 1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(np.nanmedian(mat, axis=axis)).all()) Chris@87: if axis is None: Chris@87: assert_(len(w) == 1) Chris@87: else: Chris@87: assert_(len(w) == 3) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: # Check scalar Chris@87: assert_(np.isnan(np.nanmedian(np.nan))) Chris@87: if axis is None: Chris@87: assert_(len(w) == 2) Chris@87: else: Chris@87: assert_(len(w) == 4) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: Chris@87: def test_empty(self): Chris@87: mat = np.zeros((0, 3)) Chris@87: for axis in [0, None]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(np.nanmedian(mat, axis=axis)).all()) Chris@87: assert_(len(w) == 1) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: for axis in [1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_equal(np.nanmedian(mat, axis=axis), np.zeros([])) Chris@87: assert_(len(w) == 0) Chris@87: Chris@87: def test_scalar(self): Chris@87: assert_(np.nanmedian(0.) == 0.) Chris@87: Chris@87: def test_extended_axis_invalid(self): Chris@87: d = np.ones((3, 5, 7, 11)) Chris@87: assert_raises(IndexError, np.nanmedian, d, axis=-5) Chris@87: assert_raises(IndexError, np.nanmedian, d, axis=(0, -5)) Chris@87: assert_raises(IndexError, np.nanmedian, d, axis=4) Chris@87: assert_raises(IndexError, np.nanmedian, d, axis=(0, 4)) Chris@87: assert_raises(ValueError, np.nanmedian, d, axis=(1, 1)) Chris@87: Chris@87: def test_float_special(self): Chris@87: with warnings.catch_warnings(record=True): Chris@87: warnings.simplefilter('ignore', RuntimeWarning) Chris@87: a = np.array([[np.inf, np.nan], [np.nan, np.nan]]) Chris@87: assert_equal(np.nanmedian(a, axis=0), [np.inf, np.nan]) Chris@87: assert_equal(np.nanmedian(a, axis=1), [np.inf, np.nan]) Chris@87: assert_equal(np.nanmedian(a), np.inf) Chris@87: Chris@87: # minimum fill value check Chris@87: a = np.array([[np.nan, np.nan, np.inf], [np.nan, np.nan, np.inf]]) Chris@87: assert_equal(np.nanmedian(a, axis=1), np.inf) Chris@87: Chris@87: # no mask path Chris@87: a = np.array([[np.inf, np.inf], [np.inf, np.inf]]) Chris@87: assert_equal(np.nanmedian(a, axis=1), np.inf) Chris@87: Chris@87: Chris@87: class TestNanFunctions_Percentile(TestCase): Chris@87: Chris@87: def test_mutation(self): Chris@87: # Check that passed array is not modified. Chris@87: ndat = _ndat.copy() Chris@87: np.nanpercentile(ndat, 30) Chris@87: assert_equal(ndat, _ndat) Chris@87: Chris@87: def test_keepdims(self): Chris@87: mat = np.eye(3) Chris@87: for axis in [None, 0, 1]: Chris@87: tgt = np.percentile(mat, 70, axis=axis, out=None, Chris@87: overwrite_input=False) Chris@87: res = np.nanpercentile(mat, 70, axis=axis, out=None, Chris@87: overwrite_input=False) Chris@87: assert_(res.ndim == tgt.ndim) Chris@87: Chris@87: d = np.ones((3, 5, 7, 11)) Chris@87: # Randomly set some elements to NaN: Chris@87: w = np.random.random((4, 200)) * np.array(d.shape)[:, None] Chris@87: w = w.astype(np.intp) Chris@87: d[tuple(w)] = np.nan Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always', RuntimeWarning) Chris@87: res = np.nanpercentile(d, 90, axis=None, keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 1, 1)) Chris@87: res = np.nanpercentile(d, 90, axis=(0, 1), keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 7, 11)) Chris@87: res = np.nanpercentile(d, 90, axis=(0, 3), keepdims=True) Chris@87: assert_equal(res.shape, (1, 5, 7, 1)) Chris@87: res = np.nanpercentile(d, 90, axis=(1,), keepdims=True) Chris@87: assert_equal(res.shape, (3, 1, 7, 11)) Chris@87: res = np.nanpercentile(d, 90, axis=(0, 1, 2, 3), keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 1, 1)) Chris@87: res = np.nanpercentile(d, 90, axis=(0, 1, 3), keepdims=True) Chris@87: assert_equal(res.shape, (1, 1, 7, 1)) Chris@87: Chris@87: def test_out(self): Chris@87: mat = np.random.rand(3, 3) Chris@87: nan_mat = np.insert(mat, [0, 2], np.nan, axis=1) Chris@87: resout = np.zeros(3) Chris@87: tgt = np.percentile(mat, 42, axis=1) Chris@87: res = np.nanpercentile(nan_mat, 42, axis=1, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: # 0-d output: Chris@87: resout = np.zeros(()) Chris@87: tgt = np.percentile(mat, 42, axis=None) Chris@87: res = np.nanpercentile(nan_mat, 42, axis=None, out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: res = np.nanpercentile(nan_mat, 42, axis=(0, 1), out=resout) Chris@87: assert_almost_equal(res, resout) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_result_values(self): Chris@87: tgt = [np.percentile(d, 28) for d in _rdat] Chris@87: res = np.nanpercentile(_ndat, 28, axis=1) Chris@87: assert_almost_equal(res, tgt) Chris@87: tgt = [np.percentile(d, (28, 98)) for d in _rdat] Chris@87: res = np.nanpercentile(_ndat, (28, 98), axis=1) Chris@87: assert_almost_equal(res, tgt) Chris@87: Chris@87: def test_allnans(self): Chris@87: mat = np.array([np.nan]*9).reshape(3, 3) Chris@87: for axis in [None, 0, 1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(np.nanpercentile(mat, 60, axis=axis)).all()) Chris@87: if axis is None: Chris@87: assert_(len(w) == 1) Chris@87: else: Chris@87: assert_(len(w) == 3) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: # Check scalar Chris@87: assert_(np.isnan(np.nanpercentile(np.nan, 60))) Chris@87: if axis is None: Chris@87: assert_(len(w) == 2) Chris@87: else: Chris@87: assert_(len(w) == 4) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: Chris@87: def test_empty(self): Chris@87: mat = np.zeros((0, 3)) Chris@87: for axis in [0, None]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_(np.isnan(np.nanpercentile(mat, 40, axis=axis)).all()) Chris@87: assert_(len(w) == 1) Chris@87: assert_(issubclass(w[0].category, RuntimeWarning)) Chris@87: for axis in [1]: Chris@87: with warnings.catch_warnings(record=True) as w: Chris@87: warnings.simplefilter('always') Chris@87: assert_equal(np.nanpercentile(mat, 40, axis=axis), np.zeros([])) Chris@87: assert_(len(w) == 0) Chris@87: Chris@87: def test_scalar(self): Chris@87: assert_(np.nanpercentile(0., 100) == 0.) Chris@87: Chris@87: def test_extended_axis_invalid(self): Chris@87: d = np.ones((3, 5, 7, 11)) Chris@87: assert_raises(IndexError, np.nanpercentile, d, q=5, axis=-5) Chris@87: assert_raises(IndexError, np.nanpercentile, d, q=5, axis=(0, -5)) Chris@87: assert_raises(IndexError, np.nanpercentile, d, q=5, axis=4) Chris@87: assert_raises(IndexError, np.nanpercentile, d, q=5, axis=(0, 4)) Chris@87: assert_raises(ValueError, np.nanpercentile, d, q=5, axis=(1, 1)) Chris@87: Chris@87: Chris@87: if __name__ == "__main__": Chris@87: run_module_suite()