diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/tests/test_multiarray.py | 172 | ||||
| -rw-r--r-- | numpy/core/tests/test_numeric.py | 2 |
2 files changed, 173 insertions, 1 deletions
diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py index b7235d05f..d37bcd331 100644 --- a/numpy/core/tests/test_multiarray.py +++ b/numpy/core/tests/test_multiarray.py @@ -2399,7 +2399,178 @@ class TestView(TestCase): assert_array_equal(y, z) assert_array_equal(y, [67305985, 134678021]) +def _mean(a, **args): + return a.mean(**args) + +def _var(a, **args): + return a.var(**args) + +def _std(a, **args): + return a.std(**args) + class TestStats(TestCase): + + funcs = [_mean, _var, _std] + + def setUp(self): + np.random.seed(range(3)) + self.rmat = np.random.random((4, 5)) + self.cmat = self.rmat + 1j * self.rmat + + def test_keepdims(self): + mat = np.eye(3) + for f in self.funcs: + for axis in [0, 1]: + res = f(mat, axis=axis, keepdims=True) + assert_(res.ndim == mat.ndim) + assert_(res.shape[axis] == 1) + for axis in [None]: + res = f(mat, axis=axis, keepdims=True) + assert_(res.shape == (1, 1)) + + def test_out(self): + mat = np.eye(3) + for f in self.funcs: + out = np.zeros(3) + tgt = f(mat, axis=1) + res = f(mat, axis=1, out=out) + assert_almost_equal(res, out) + assert_almost_equal(res, tgt) + out = np.empty(2) + assert_raises(ValueError, f, mat, axis=1, out=out) + out = np.empty((2, 2)) + assert_raises(ValueError, f, mat, axis=1, out=out) + + def test_dtype_from_input(self): + icodes = np.typecodes['AllInteger'] + fcodes = np.typecodes['AllFloat'] + + # integer types + for f in self.funcs: + for c in icodes: + mat = np.eye(3, dtype=c) + tgt = np.float64 + res = f(mat, axis=1).dtype.type + assert_(res is tgt) + # scalar case + res = f(mat, axis=None).dtype.type + assert_(res is tgt) + # mean for float types + for f in [_mean]: + for c in fcodes: + mat = np.eye(3, dtype=c) + tgt = mat.dtype.type + res = f(mat, axis=1).dtype.type + assert_(res is tgt) + # scalar case + res = f(mat, axis=None).dtype.type + assert_(res is tgt) + # var, std for float types + for f in [_var, _std]: + for c in fcodes: + mat = np.eye(3, dtype=c) + tgt = mat.real.dtype.type + res = f(mat, axis=1).dtype.type + assert_(res is tgt) + # scalar case + res = f(mat, axis=None).dtype.type + assert_(res is tgt) + + def test_dtype_from_dtype(self): + icodes = np.typecodes['AllInteger'] + fcodes = np.typecodes['AllFloat'] + mat = np.eye(3) + + # stats for integer types + # fixme: + # this needs definition as there are lots places along the line + # where type casting may take place. + #for f in self.funcs: + #for c in icodes: + #tgt = np.dtype(c).type + #res = f(mat, axis=1, dtype=c).dtype.type + #assert_(res is tgt) + ## scalar case + #res = f(mat, axis=None, dtype=c).dtype.type + #assert_(res is tgt) + + # stats for float types + for f in self.funcs: + for c in fcodes: + tgt = np.dtype(c).type + res = f(mat, axis=1, dtype=c).dtype.type + assert_(res is tgt) + # scalar case + res = f(mat, axis=None, dtype=c).dtype.type + assert_(res is tgt) + + def test_ddof(self): + for f in [_var]: + for ddof in range(3): + dim = self.rmat.shape[1] + tgt = f(self.rmat, axis=1) * dim + res = f(self.rmat, axis=1, ddof=ddof) * (dim - ddof) + for f in [_std]: + for ddof in range(3): + dim = self.rmat.shape[1] + tgt = f(self.rmat, axis=1) * np.sqrt(dim) + res = f(self.rmat, axis=1, ddof=ddof) * np.sqrt(dim - ddof) + assert_almost_equal(res, tgt) + assert_almost_equal(res, tgt) + + def test_ddof_too_big(self): + dim = self.rmat.shape[1] + for f in [_var, _std]: + for ddof in range(dim, dim + 2): + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') + res = f(self.rmat, axis=1, ddof=ddof) + assert_(not (res < 0).any()) + assert_(len(w) > 0) + assert_(issubclass(w[0].category, RuntimeWarning)) + + def test_empty(self): + A = np.zeros((0,3)) + for f in self.funcs: + for axis in [0, None]: + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') + assert_(np.isnan(f(A, axis=axis)).all()) + assert_(len(w) > 0) + assert_(issubclass(w[0].category, RuntimeWarning)) + for axis in [1]: + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') + assert_equal(f(A, axis=axis), np.zeros([])) + + def test_mean_values(self): + for mat in [self.rmat, self.cmat]: + for axis in [0, 1]: + tgt = mat.sum(axis=axis) + res = _mean(mat, axis=axis) * mat.shape[axis] + assert_almost_equal(res, tgt) + for axis in [None]: + tgt = mat.sum(axis=axis) + res = _mean(mat, axis=axis) * np.prod(mat.shape) + assert_almost_equal(res, tgt) + + def test_var_values(self): + for mat in [self.rmat, self.cmat]: + for axis in [0, 1, None]: + msqr = _mean(mat * mat.conj(), axis=axis) + mean = _mean(mat, axis=axis) + tgt = msqr - mean * mean.conj() + res = _var(mat, axis=axis) + assert_almost_equal(res, tgt) + + def test_std_values(self): + for mat in [self.rmat, self.cmat]: + for axis in [0, 1, None]: + tgt = np.sqrt(_var(mat, axis=axis)) + res = _std(mat, axis=axis) + assert_almost_equal(res, tgt) + + def test_subclass(self): class TestArray(np.ndarray): def __new__(cls, data, info): @@ -2409,6 +2580,7 @@ class TestStats(TestCase): return result def __array_finalize__(self, obj): self.info = getattr(obj, "info", '') + dat = TestArray([[1,2,3,4],[5,6,7,8]], 'jubba') res = dat.mean(1) assert_(res.info == dat.info) diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py index 2b6b07721..341884f04 100644 --- a/numpy/core/tests/test_numeric.py +++ b/numpy/core/tests/test_numeric.py @@ -202,7 +202,7 @@ class TestNonarrayArgs(TestCase): with warnings.catch_warnings(record=True) as w: warnings.filterwarnings('always', '', RuntimeWarning) - assert_(isnan(mean([]))) + assert_(isnan(var([]))) assert_(w[0].category is RuntimeWarning) |