class numpy.busdaycalendar [source] A business day calendar object that efficiently stores information defining valid days for the busday family of functions. The default valid days are Monday through Friday (?business days?). A busdaycalendar object can be specified with any set of weekly valid days, plus an optional ?holiday? dates that always will be invalid. Once a busdaycalendar object is created, the weekmask and holidays cannot be modified. New in version 1.7.0. Parameters: weekma

numpy.prod(a, axis=None, dtype=None, out=None, keepdims=False) [source] Return the product of array elements over a given axis. Parameters: a : array_like Input data. axis : None or int or tuple of ints, optional Axis or axes along which a product is performed. The default, axis=None, will calculate the product of all the elements in the input array. If axis is negative it counts from the last to the first axis. New in version 1.7.0. If axis is a tuple of ints, a product is performed

record.min() 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

record.size number of elements in the gentype

record.astype() 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

numpy.polynomial.hermite_e.hermegrid2d(x, y, c) [source] Evaluate a 2-D HermiteE series on the Cartesian product of x and y. This function returns the values: where the points (a, b) consist of all pairs formed by taking a from x and b from y. The resulting points form a grid with x in the first dimension and y in the second. The parameters x and y are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars. In either case, either x and y or their

generic.diagonal() 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

chararray.decode(encoding=None, errors=None) [source] Calls str.decode element-wise. See also char.decode

RandomState.normal(loc=0.0, scale=1.0, size=None) Draw random samples from a normal (Gaussian) distribution. The probability density function of the normal distribution, first derived by De Moivre and 200 years later by both Gauss and Laplace independently [R179], is often called the bell curve because of its characteristic shape (see the example below). The normal distributions occurs often in nature. For example, it describes the commonly occurring distribution of samples influenced by a

MaskedArray.__rand__ x.__rand__(y) <==> y&x