# -*- coding: utf-8 -*-
'''
Created on 28.07.2012

@author: frank
'''
import numpy as np
from stim_movie import StimulusSet
from objsimpy.stimview import run_stimview
import os

def main():
    file_path = "gauss.idlmov"
    generate_gauss_stim(file_path,
                        output_width=20, 
                        output_height=20, 
                        fwhm=0.15, shift_x=1, 
                        shift_y=1, 
                        nx=20, 
                        ny=20, 
                        start_shifted=False,
                        xy_ratio=1.7)
    run_stimview(file_path)
    
def generate_gauss_stim(file_path="gauss.idlmov", output_width=20, output_height=20, fwhm=0.17,
                        shift_x=1, shift_y=1, nx=20, ny=20, start_shifted=False, xy_ratio=None):
    """Generate a stimulus set of Gaussian blobs at different positions"""
    
    pic_prototype = make_gaussian_2d(output_width, output_height, fwhm, xy_ratio)
    if start_shifted:
        pic_prototype = np.roll(pic_prototype, 1-output_width/2, axis=1)
        pic_prototype = np.roll(pic_prototype, 1-output_height/2, axis=0)
    pics = []
    for y in range(ny):
        y_rolled = np.roll(pic_prototype, y * shift_y, axis=0)
        for x in range(nx):
            x_rolled = np.roll(y_rolled, x * shift_x, axis=1)
            pics.append(x_rolled)
    stim_set = StimulusSet(pics=pics)
    stim_set.save(file_path)
    
    
def make_gaussian_2d(output_width, output_height, fwhm, xy_ratio=None):
    """ Make gaussian kernel
    
    parameters:
    @param output_width: image width in pixels
    @param output_height: image height in pixels
    @param fwhm: full-width-at-half_maximum, value between 0 and 1, relative to output_width
    @return: numpy array with centered gaussian
    """
    if xy_ratio is None:
        xy_ratio = float(output_width) / float(output_height)   
    x = np.linspace(-0.5, 0.5, output_width)
    y = np.linspace(-0.5/xy_ratio, 0.5/xy_ratio, output_height)
    y = y[:,np.newaxis]
    sigma = fwhm / (2 * np.sqrt(2*np.log(2)))
    return np.exp(-(x**2 + y**2) / (2*sigma*sigma))

def generate_single_stim(file_path="single.idlmov", output_width=20, output_height=20):
    pic = np.zeros([output_width, output_height])
    pic[int(output_width/2)+4,int(output_height/2)+4] = 1.
    stim_set = StimulusSet(pics = [pic])
    stim_set.save(file_path)


if __name__ == '__main__':
    main()