ndarray.itemsize Length of one array element in bytes. Examples >>> x = np.array([1,2,3], dtype=np.float64) >>> x.itemsize 8 >>> x = np.array([1,2,3], dtype=np.complex128) >>> x.itemsize 16

numpy.split(ary, indices_or_sections, axis=0) [source] Split an array into multiple sub-arrays. Parameters: ary : ndarray Array to be divided into sub-arrays. indices_or_sections : int or 1-D array If indices_or_sections is an integer, N, the array will be divided into N equal arrays along axis. If such a split is not possible, an error is raised. If indices_or_sections is a 1-D array of sorted integers, the entries indicate where along axis the array is split. For example, [2, 3] would

numpy.polynomial.hermite.hermdomain = array([-1, 1])

ndarray.__idiv__ x.__idiv__(y) <==> x/=y

MaskedArray.mask Mask

masked_array.mask Mask

record.searchsorted() 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.sqrt(x[, out]) = Return the positive square-root of an array, element-wise. Parameters: x : array_like The values whose square-roots are required. out : ndarray, optional Alternate array object in which to put the result; if provided, it must have the same shape as x Returns: y : ndarray An array of the same shape as x, containing the positive square-root of each element in x. If any element in x is complex, a complex array is returned (and the square-roots of negative reals

ndarray.__le__ x.__le__(y) <==> x<=y

MaskedArray.dumps() Returns the pickle of the array as a string. pickle.loads or numpy.loads will convert the string back to an array. Parameters: None