Module PINNacle.src.utils.random

Input args:
    size (integer): The size of the coordinate array to create
Returns:
    k_ind, numpy array of shape (2, size, size) with:
        k_ind[0,:,:]:  k_x components
        k_ind[1,:,:]:  k_y components

Example:

    print(fftind(5))

    [[[ 0  1 -3 -2 -1]
    [ 0  1 -3 -2 -1]
    [ 0  1 -3 -2 -1]
    [ 0  1 -3 -2 -1]
    [ 0  1 -3 -2 -1]]
    [[ 0  0  0  0  0]
    [ 1  1  1  1  1]
    [-3 -3 -3 -3 -3]
    [-2 -2 -2 -2 -2]
    [-1 -1 -1 -1 -1]]]

Input args:
    alpha (double, default = 3.0):
        The power of the power-law momentum distribution
    size (integer, default = 128):
        The size of the square output Gaussian Random Fields
    flag_normalize (boolean, default = True):
        Normalizes the Gaussian Field:
            - to have an average of 0.0
            - to have a standard deviation of 1.0
Returns:
    gfield (numpy array of shape (size, size)):
        The random gaussian random field

Example:
import matplotlib
import matplotlib.pyplot as plt
example = gaussian_random_field()
plt.imshow(example)