numpy.ma.set_fill_value(a, fill_value) [source] Set the filling value of a, if a is a masked array. This function changes the fill value of the masked array a in place. If a is not a masked array, the function returns silently, without doing anything. Parameters: a : array_like Input array. fill_value : dtype Filling value. A consistency test is performed to make sure the value is compatible with the dtype of a. Returns: None Nothing returned by this function. See also maximum_

ndarray.mean(axis=None, dtype=None, out=None, keepdims=False) Returns the average of the array elements along given axis. Refer to numpy.mean for full documentation. See also numpy.mean equivalent function

ndarray.ravel([order]) Return a flattened array. Refer to numpy.ravel for full documentation. See also numpy.ravel equivalent function ndarray.flat a flat iterator on the array.

Legendre.trim(tol=0) [source] Remove trailing coefficients Remove trailing coefficients until a coefficient is reached whose absolute value greater than tol or the beginning of the series is reached. If all the coefficients would be removed the series is set to [0]. A new series instance is returned with the new coefficients. The current instance remains unchanged. Parameters: tol : non-negative number. All trailing coefficients less than tol will be removed. Returns: new_series : seri

numpy.count_nonzero(a) Counts the number of non-zero values in the array a. Parameters: a : array_like The array for which to count non-zeros. Returns: count : int or array of int Number of non-zero values in the array. See also nonzero Return the coordinates of all the non-zero values. Examples >>> np.count_nonzero(np.eye(4)) 4 >>> np.count_nonzero([[0,1,7,0,0],[3,0,0,2,19]]) 5

chararray.resize(new_shape, refcheck=True) Change shape and size of array in-place. Parameters: new_shape : tuple of ints, or n ints Shape of resized array. refcheck : bool, optional If False, reference count will not be checked. Default is True. Returns: None Raises: ValueError If a does not own its own data or references or views to it exist, and the data memory must be changed. SystemError If the order keyword argument is specified. This behaviour is a bug in NumPy. See al

numpy.vander(x, N=None, increasing=False) [source] Generate a Vandermonde matrix. The columns of the output matrix are powers of the input vector. The order of the powers is determined by the increasing boolean argument. Specifically, when increasing is False, the i-th output column is the input vector raised element-wise to the power of N - i - 1. Such a matrix with a geometric progression in each row is named for Alexandre- Theophile Vandermonde. Parameters: x : array_like 1-D input arr

numpy.histogramdd(sample, bins=10, range=None, normed=False, weights=None) [source] Compute the multidimensional histogram of some data. Parameters: sample : array_like The data to be histogrammed. It must be an (N,D) array or data that can be converted to such. The rows of the resulting array are the coordinates of points in a D dimensional polytope. bins : sequence or int, optional The bin specification: A sequence of arrays describing the bin edges along each dimension. The number of

numpy.ptp(a, axis=None, out=None) [source] Range of values (maximum - minimum) along an axis. The name of the function comes from the acronym for ?peak to peak?. Parameters: a : array_like Input values. axis : int, optional Axis along which to find the peaks. By default, flatten the array. out : array_like Alternative output array in which to place the result. It must have the same shape and buffer length as the expected output, but the type of the output values will be cast if necess

numpy.ma.default_fill_value(obj) [source] Return the default fill value for the argument object. The default filling value depends on the datatype of the input array or the type of the input scalar: datatype default bool True int 999999 float 1.e20 complex 1.e20+0j object ??? string ?N/A? Parameters: obj : ndarray, dtype or scalar The array data-type or scalar for which the default fill value is returned. Returns: fill_value : scalar The default fill value. Examples >>> np