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Random Walk Image Generation
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""" | |
Random Walk Image Generator | |
@Author: Shubhanshu Mishra | |
@Website: http://shubhanshu.com | |
@LICENSE: MIT | |
""" | |
# coding: utf-8 | |
# In[1]: | |
import numpy as np | |
import matplotlib.pyplot as plt | |
# In[2]: | |
def get_color(colors=None, color_channels=3): | |
if colors is None: | |
return np.random.rand(color_channels) | |
else: | |
return colors[np.random.randint(len(colors))] | |
def gen_image(n = 200, walks = 5, fig_dim = 10, density = 0.5, bg_grey = 1, color_change_steps=50,\ | |
colors_rgb = True, colors = None, filename=None, verbose=False): | |
color_channels = 3 | |
if not colors_rgb: | |
color_channels = 1 | |
figsize = (fig_dim, )*2 | |
img = np.ones((n,n,3)) * bg_grey | |
mat = np.zeros((n,n)) | |
for i in xrange(walks): | |
init_x, init_y = np.random.randint(0,2, size=(2)) | |
color = get_color(colors=colors, color_channels=color_channels) | |
img[init_x, init_y] = color | |
mat[init_x, init_y] = 1 | |
num_steps = np.random.randint(int(n*n*density)) | |
num_steps = int(np.random.rand()*n*n*density) | |
next_x, next_y = init_x, init_y | |
change_steps = 0 | |
for j in xrange(num_steps): | |
nudge = np.random.randint(-1,2, size=2) | |
next_x, next_y = (next_x + nudge[0]) % n, (next_y + nudge[1]) % n | |
if mat[next_x, next_y] == 1 or change_steps >= color_change_steps: | |
color = get_color(colors=colors, color_channels=color_channels) | |
change_steps = 0 | |
change_steps += 1 | |
img[next_x, next_y] = color | |
if verbose: | |
print "Walk %s with %s steps" % (i, num_steps) | |
plt.clf() | |
plt.figure(figsize=figsize) | |
plt.imshow(img) | |
plt.axis('off') | |
if filename is not None: | |
plt.savefig(filename) | |
else: | |
plt.show() | |
# In[3]: | |
# In[ ]: | |
if __name__ == "__main__": | |
base_file = "rand_img_%s.png" | |
num_images = 500 | |
for i in xrange(num_images): | |
gen_image(filename=base_file % i) | |
print "Finished generating %s images" % (i + 1) | |
# In[ ]: | |
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