ndarray.T Same as self.transpose(), except that self is returned if self.ndim < 2. Examples >>> x = np.array([[1.,2.],[3.,4.]]) >>> x array([[ 1., 2.], [ 3., 4.]]) >>> x.T array([[ 1., 3.], [ 2., 4.]]) >>> x = np.array([1.,2.,3.,4.]) >>> x array([ 1., 2., 3., 4.]) >>> x.T array([ 1., 2., 3., 4.])

numpy.issctype(rep) [source] Determines whether the given object represents a scalar data-type. Parameters: rep : any If rep is an instance of a scalar dtype, True is returned. If not, False is returned. Returns: out : bool Boolean result of check whether rep is a scalar dtype. See also issubsctype, issubdtype, obj2sctype, sctype2char Examples >>> np.issctype(np.int32) True >>> np.issctype(list) False >>> np.issctype(1.1) False Strings are also a scalar

MaskedArray.var(axis=None, dtype=None, out=None, ddof=0) [source] Compute the variance along the specified axis. Returns the variance of the array elements, a measure of the spread of a distribution. The variance is computed for the flattened array by default, otherwise over the specified axis. Parameters: a : array_like Array containing numbers whose variance is desired. If a is not an array, a conversion is attempted. axis : None or int or tuple of ints, optional Axis or axes along wh

MaskedArray.recordmask Return the mask of the records. A record is masked when all the fields are masked.

iinfo.max Maximum value of given dtype.

ndarray.nonzero() Return the indices of the elements that are non-zero. Refer to numpy.nonzero for full documentation. See also numpy.nonzero equivalent function

numpy.ma.median(a, axis=None, out=None, overwrite_input=False) [source] Compute the median along the specified axis. Returns the median of the array elements. Parameters: a : array_like Input array or object that can be converted to an array. axis : int, optional Axis along which the medians are computed. The default (None) is to compute the median along a flattened version of the array. out : ndarray, optional Alternative output array in which to place the result. It must have the sa

MaskedArray.__ne__(other) [source] Check whether other doesn?t equal self elementwise

MaskedArray.__ifloordiv__(other) [source] Floor divide self by other in-place.

numpy.linalg.eigh(a, UPLO='L') [source] Return the eigenvalues and eigenvectors of a Hermitian or symmetric matrix. Returns two objects, a 1-D array containing the eigenvalues of a, and a 2-D square array or matrix (depending on the input type) of the corresponding eigenvectors (in columns). Parameters: a : (..., M, M) array Hermitian/Symmetric matrices whose eigenvalues and eigenvectors are to be computed. UPLO : {?L?, ?U?}, optional Specifies whether the calculation is done with the l