ndarray.__mod__ x.__mod__(y) <==> x%y

numpy.random.gumbel(loc=0.0, scale=1.0, size=None) Draw samples from a Gumbel distribution. Draw samples from a Gumbel distribution with specified location and scale. For more information on the Gumbel distribution, see Notes and References below. Parameters: loc : float The location of the mode of the distribution. scale : float The scale parameter of the distribution. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples a

numpy.polynomial.legendre.legval3d(x, y, z, c) [source] Evaluate a 3-D Legendre series at points (x, y, z). This function returns the values: 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 and they must have the same shape after conversion. In either case, either x, y, and z or their elements must support multiplication and addition both with themselves and with the elements of c. If c has fewer than 3 dimens

numpy.testing.Tester [source] alias of NoseTester

numpy.mask_indices(n, mask_func, k=0) [source] Return the indices to access (n, n) arrays, given a masking function. Assume mask_func is a function that, for a square array a of size (n, n) with a possible offset argument k, when called as mask_func(a, k) returns a new array with zeros in certain locations (functions like triu or tril do precisely this). Then this function returns the indices where the non-zero values would be located. Parameters: n : int The returned indices will be vali

numpy.iscomplexobj(x) [source] Check for a complex type or an array of complex numbers. The type of the input is checked, not the value. Even if the input has an imaginary part equal to zero, iscomplexobj evaluates to True. Parameters: x : any The input can be of any type and shape. Returns: iscomplexobj : bool The return value, True if x is of a complex type or has at least one complex element. See also isrealobj, iscomplex Examples >>> np.iscomplexobj(1) False >>&

numpy.core.defchararray.greater(x1, x2) [source] Return (x1 > x2) element-wise. Unlike numpy.greater, this comparison is performed by first stripping whitespace characters from the end of the string. This behavior is provided for backward-compatibility with numarray. Parameters: x1, x2 : array_like of str or unicode Input arrays of the same shape. Returns: out : ndarray or bool Output array of bools, or a single bool if x1 and x2 are scalars. See also equal, not_equal, greater_e

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

numpy.polynomial.laguerre.lagder(c, m=1, scl=1, axis=0) [source] Differentiate a Laguerre series. Returns the Laguerre series coefficients c differentiated m times along axis. At each iteration the result is multiplied by scl (the scaling factor is for use in a linear change of variable). The argument c is an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the series 1*L_0 + 2*L_1 + 3*L_2 while [[1,2],[1,2]] represents 1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y

recarray.field(attr, val=None) [source]