Question

I am plotting tiled images in a similar way to the working code shown below:

import Image
import matplotlib.pyplot as plt
import random
import numpy

def r():
    return random.randrange(50,200)

imsize = 100
rngsize = 5

rng = range(rngsize)
for i in rng:
    for j in rng:
        im = Image.new('RGB', (imsize, imsize), (r(),r(),r()))
        plt.imshow(im, aspect='equal', extent=numpy.array([i, i+1, j, j+1])*imsize)

plt.xlim(-5,imsize * rngsize + 5)
plt.ylim(-5,imsize * rngsize + 5)
plt.show()

The problem is: as you pan and zoom, zoomscale-independent white stripes appear between the image edges, which is very undesireable. I guess this has to do with resampling and antialiasing, but have no idea how to solve it “the right way”, specialy for not knowing exact implementation details of matplotlib’s rendering engine.

With Cairo and HTML Canvas, you can draw “to the pixel corner” or “to the pixel center” (translating by 0.5 pixel) thus avoiding anti-aliasing effects. Would there be a way to do that with Matplotlib?

Thanks for any help!

Answer 1

You can simply fill in the values to a larger numpy array and plot the entire composite image in one shot. I’ve adapted your code above for a minimal example but with different sized images you’ll need to take a different step size.

F = numpy.zeros((imsize*rngsize,imsize*rngsize,3))

for i in rng:
    for j in rng:
        F[i*imsize:(i+1)*imsize, 
          j*imsize:(j+1)*imsize, :] = (r(), r(), r())

plt.imshow(F, interpolation = 'nearest')
plt.show()