chararray.find(sub, start=0, end=None) [source] For each element, return the lowest index in the string where substring sub is found. See also char.find

numpy.hamming(M) [source] Return the Hamming window. The Hamming window is a taper formed by using a weighted cosine. Parameters: M : int Number of points in the output window. If zero or less, an empty array is returned. Returns: out : ndarray The window, with the maximum value normalized to one (the value one appears only if the number of samples is odd). See also bartlett, blackman, hanning, kaiser Notes The Hamming window is defined as The Hamming was named for R. W. Hammin

numpy.polynomial.legendre.leggrid3d(x, y, z, c) [source] Evaluate a 3-D Legendre series on the Cartesian product of x, y, and z. This function returns the values: where the points (a, b, c) consist of all triples formed by taking a from x, b from y, and c from z. The resulting points form a grid with x in the first dimension, y in the second, and z in the third. The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars.

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.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.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.

class numpy.errstate(**kwargs) [source] Context manager for floating-point error handling. Using an instance of errstate as a context manager allows statements in that context to execute with a known error handling behavior. Upon entering the context the error handling is set with seterr and seterrcall, and upon exiting it is reset to what it was before. Parameters: kwargs : {divide, over, under, invalid} Keyword arguments. The valid keywords are the possible floating-point exceptions. Ea

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