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

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

numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0) Create an array. Parameters: object : array_like An array, any object exposing the array interface, an object whose __array__ method returns an array, or any (nested) sequence. dtype : data-type, optional The desired data-type for the array. If not given, then the type will be determined as the minimum type required to hold the objects in the sequence. This argument can only be used to ?upcast? the array. For d

chararray.rsplit(sep=None, maxsplit=None) [source] For each element in self, return a list of the words in the string, using sep as the delimiter string. See also char.rsplit

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

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.hermone = array([1])

numpy.testing.assert_approx_equal(actual, desired, significant=7, err_msg='', verbose=True) [source] Raises an AssertionError if two items are not equal up to significant digits. Note It is recommended to use one of assert_allclose, assert_array_almost_equal_nulp or assert_array_max_ulp instead of this function for more consistent floating point comparisons. Given two numbers, check that they are approximately equal. Approximately equal is defined as the number of significant digits that

record.size number of elements in the gentype