numpy.ma.anom(self, axis=None, dtype=None) = Compute the anomalies (deviations from the arithmetic mean) along the given axis. Returns an array of anomalies, with the same shape as the input and where the arithmetic mean is computed along the given axis. Parameters: axis : int, optional Axis over which the anomalies are taken. The default is to use the mean of the flattened array as reference. dtype : dtype, optional Type to use in computing the variance. For arrays of integer type th

numpy.ma.corrcoef(x, y=None, rowvar=True, bias=, allow_masked=True, ddof=) [source] Return Pearson product-moment correlation coefficients. Except for the handling of missing data this function does the same as numpy.corrcoef. For more details and examples, see numpy.corrcoef. Parameters: x : array_like A 1-D or 2-D array containing multiple variables and observations. Each row of x represents a variable, and each column a single observation of all those variables. Also see rowvar below.

matrix.ravel(order='C') [source] Return a flattened matrix. Refer to numpy.ravel for more documentation. Parameters: order : {?C?, ?F?, ?A?, ?K?}, optional The elements of m are read using this index order. ?C? means to index the elements in C-like order, with the last axis index changing fastest, back to the first axis index changing slowest. ?F? means to index the elements in Fortran-like index order, with the first index changing fastest, and the last index changing slowest. Note that

numpy.matlib.identity(n, dtype=None) [source] Returns the square identity matrix of given size. Parameters: n : int Size of the returned identity matrix. dtype : data-type, optional Data-type of the output. Defaults to float. Returns: out : matrix n x n matrix with its main diagonal set to one, and all other elements zero. See also numpy.identity Equivalent array function. matlib.eye More general matrix identity function. Examples >>> import numpy.matlib >>&g

numpy.linalg.eigvalsh(a, UPLO='L') [source] Compute the eigenvalues of a Hermitian or real symmetric matrix. Main difference from eigh: the eigenvectors are not computed. Parameters: a : (..., M, M) array_like A complex- or real-valued matrix whose eigenvalues are to be computed. UPLO : {?L?, ?U?}, optional Same as lower, with ?L? for lower and ?U? for upper triangular. Deprecated. Returns: w : (..., M,) ndarray The eigenvalues in ascending order, each repeated according to its mult

generic.__array__() sc.__array__(|type) return 0-dim array

numpy.fliplr(m) [source] Flip array in the left/right direction. Flip the entries in each row in the left/right direction. Columns are preserved, but appear in a different order than before. Parameters: m : array_like Input array, must be at least 2-D. Returns: f : ndarray A view of m with the columns reversed. Since a view is returned, this operation is . See also flipud Flip array in the up/down direction. rot90 Rotate array counterclockwise. Notes Equivalent to A[:,::-1].

numpy.diagonal(a, offset=0, axis1=0, axis2=1) [source] Return specified diagonals. If a is 2-D, returns the diagonal of a with the given offset, i.e., the collection of elements of the form a[i, i+offset]. If a has more than two dimensions, then the axes specified by axis1 and axis2 are used to determine the 2-D sub-array whose diagonal is returned. The shape of the resulting array can be determined by removing axis1 and axis2 and appending an index to the right equal to the size of the res

numpy.random.standard_exponential(size=None) Draw samples from the standard exponential distribution. standard_exponential is identical to the exponential distribution with a scale parameter of 1. Parameters: size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned. Returns: out : float or ndarray Drawn samples. Examples Output a 3x8000 array: >>> n

numpy.info(object=None, maxwidth=76, output=', mode 'w' at 0x402ae078>, toplevel='numpy') [source] Get help information for a function, class, or module. Parameters: object : object or str, optional Input object or name to get information about. If object is a numpy object, its docstring is given. If it is a string, available modules are searched for matching objects. If None, information about info itself is returned. maxwidth : int, optional Printing width. output : file like obje