Idea: Gabor Patch without matplotlib dependency

gabor_surface.py

import expyriment
import numpy as np
expyriment.control.set_develop_mode()

exp = expyriment.control.initialize()
expyriment.control.start(skip_ready_screen=True)


def canvas_with_gabor_patch(sigma,theta,Lambda,psi,gamma):
    sigma_x = sigma
    sigma_y = float(sigma)/gamma

    # Bounding box
    nstds = 3
    xmax = max(abs(nstds*sigma_x*np.cos(theta)),abs(nstds*sigma_y*np.sin(theta)))
    xmax = np.ceil(max(1,xmax))
    ymax = max(abs(nstds*sigma_x*np.sin(theta)),abs(nstds*sigma_y*np.cos(theta)))
    ymax = np.ceil(max(1,ymax))
    xmin = -xmax
    ymin = -ymax
    (x,y) = np.meshgrid(np.arange(xmin,xmax+1),np.arange(ymin,ymax+1 ))
    (y,x) = np.meshgrid(np.arange(ymin,ymax+1),np.arange(xmin,xmax+1 ))

    # Rotation
    x_theta=x*np.cos(theta)+y*np.sin(theta)
    y_theta=-x*np.sin(theta)+y*np.cos(theta)

    pattern = np.exp(-.5*(x_theta**2/sigma_x**2+y_theta**2/sigma_y**2))*np.cos(2*np.pi/Lambda*x_theta+psi)

    # make numpy pixel array
    tmp = (np.ones(pattern.shape) * (255 / 2.0) * pattern) + (255 / 2.0)
    pixel_array = np.ones((3, tmp.shape[1], tmp.shape[0])) * tmp.T

    #make stimulus
    stim = expyriment.stimuli.Canvas(pattern.shape)
    stim.set_surface(pixel_array.T)
    return stim

s = canvas_with_gabor_patch(sigma=55,theta=np.pi/2.9,Lambda=12.5,psi=120,gamma=1.)
s.present()
exp.keyboard.wait()


expyriment.control.end()

See Expyriment Gabor Patch: https://github.com/expyriment/expyriment-stash/blob/master/extras/expyriment_stimuli_extras/gaborpatch/_gaborpatch.py