ndarray.cumprod(axis=None, dtype=None, out=None) Return the cumulative product of the elements along the given axis. Refer to numpy.cumprod for full documentation. See also numpy.cumprod equivalent function

numpy.linalg.pinv(a, rcond=1e-15) [source] Compute the (Moore-Penrose) pseudo-inverse of a matrix. Calculate the generalized inverse of a matrix using its singular-value decomposition (SVD) and including all large singular values. Parameters: a : (M, N) array_like Matrix to be pseudo-inverted. rcond : float Cutoff for small singular values. Singular values smaller (in modulus) than rcond * largest_singular_value (again, in modulus) are set to zero. Returns: B : (N, M) ndarray The ps

MaskedArray.prod(axis=None, dtype=None, out=None) [source] Return the product of the array elements over the given axis. Masked elements are set to 1 internally for computation. Parameters: axis : {None, int}, optional Axis over which the product is taken. If None is used, then the product is over all the array elements. dtype : {None, dtype}, optional Determines the type of the returned array and of the accumulator where the elements are multiplied. If dtype has the value None and the

matrix.getI() [source] Returns the (multiplicative) inverse of invertible self. Parameters: None Returns: ret : matrix object If self is non-singular, ret is such that ret * self == self * ret == np.matrix(np.eye(self[0,:].size) all return True. Raises: numpy.linalg.LinAlgError: Singular matrix If self is singular. See also linalg.inv Examples >>> m = np.matrix('[1, 2; 3, 4]'); m matrix([[1, 2], [3, 4]]) >>> m.getI() matrix([[-2. , 1. ], [ 1.5,

record.view() Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit unimplemented, all the attributes of the ndarray class so as to provide a uniform API. See also The

recarray.sum(axis=None, dtype=None, out=None, keepdims=False) Return the sum of the array elements over the given axis. Refer to numpy.sum for full documentation. See also numpy.sum equivalent function

dtype.descr Array-interface compliant full description of the data-type. The format is that required by the ?descr? key in the __array_interface__ attribute.

numpy.ma.masked_array [source] alias of MaskedArray

numpy.arctanh(x[, out]) = Inverse hyperbolic tangent element-wise. Parameters: x : array_like Input array. Returns: out : ndarray Array of the same shape as x. See also emath.arctanh Notes arctanh is a multivalued function: for each x there are infinitely many numbers z such that tanh(z) = x. The convention is to return the z whose imaginary part lies in [-pi/2, pi/2]. For real-valued input data types, arctanh always returns real output. For each value that cannot be expressed as

MaskedArray.__deepcopy__(memo=None) [source]