RandomState.noncentral_f(dfnum, dfden, nonc, size=None) Draw samples from the noncentral F distribution. Samples are drawn from an F distribution with specified parameters, dfnum (degrees of freedom in numerator) and dfden (degrees of freedom in denominator), where both parameters > 1. nonc is the non-centrality parameter. Parameters: dfnum : int Parameter, should be > 1. dfden : int Parameter, should be > 1. nonc : float Parameter, should be >= 0. size : int or tuple of

record.squeeze() 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

ndarray.__setslice__ x.__setslice__(i, j, y) <==> x[i:j]=y Use of negative indices is not supported.

numpy.core.records.array(obj, dtype=None, shape=None, offset=0, strides=None, formats=None, names=None, titles=None, aligned=False, byteorder=None, copy=True) [source] Construct a record array from a wide-variety of objects.

MaskedArray.__rsub__(other) [source] Subtract self from other, and return a new masked array.

chararray.upper() [source] Return an array with the elements of self converted to uppercase. See also char.upper

ndarray.__contains__ x.__contains__(y) <==> y in x

generic.std() 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

nditer.remove_multi_index() When the ?multi_index? flag was specified, this removes it, allowing the internal iteration structure to be optimized further.

matrix.conj() Complex-conjugate all elements. Refer to numpy.conjugate for full documentation. See also numpy.conjugate equivalent function