2D Histogram Wasserstein Distance via POT Library

testOt.py

"""
Programmer: Chris Tralie
Purpose: To use the POT library (https://github.com/rflamary/POT)
to compute the Entropic regularized Wasserstein distance 
between points on a 2D grid
"""
import numpy as np
import matplotlib.pyplot as plt
import ot

def testMovingDisc():
    """
    Show optimal transport on a moving disc in a 50x50 grid
    """
    ## Step 1: Setup problem
    pix = np.linspace(-1, 1, 80)
    # Setup grid
    X, Y = np.meshgrid(pix, pix)
    # Compute pariwise distances between points on 2D grid so we know
    # how to score the Wasserstein distance
    coords = np.array([X.flatten(), Y.flatten()]).T
    coordsSqr = np.sum(coords**2, 1)
    M = coordsSqr[:, None] + coordsSqr[None, :] - 2*coords.dot(coords.T)
    M[M < 0] = 0
    M = np.sqrt(M)
    ts = np.linspace(-0.8, 0.8, 100)
    
    ## Step 2: Compute L2 distances and Wasserstein
    Images = []
    radius = 0.2
    L2Dists = [0.0]
    WassDists = [0.0]
    for i, t in enumerate(ts):
        I = 1e-5 + np.array((X-t)**2 + (Y-t)**2 < radius**2, dtype=float)
        I /= np.sum(I)
        Images.append(I)
        if i > 0:
            L2Dists.append(np.sqrt(np.sum((I-Images[0])**2)))
            wass = ot.sinkhorn2(Images[0].flatten(), I.flatten(), M, 1.0)
            print(wass)
            WassDists.append(wass)
    
    ## Step 3: Make Animation
    L2Dist = np.array(L2Dists)
    WassDists = np.array(WassDists)
    I0 = Images[0]
    plt.figure(figsize=(15, 5))
    displacements = np.sqrt(2)*(ts - ts[0])
    for i, I in enumerate(Images):
        plt.clf()
        D = np.concatenate((I0[:, :, None], I[:, :, None], 0*I[:, :, None]), 2)
        D = D*255/np.max(I0)
        D = np.array(D, dtype=np.uint8)
        plt.subplot(131)
        plt.imshow(D, extent = (pix[0], pix[-1], pix[-1], pix[0]))
        plt.subplot(132)
        plt.plot(displacements, L2Dists)
        plt.stem([displacements[i]], [L2Dists[i]])
        plt.xlabel("Displacements")
        plt.ylabel("L2 Dist")
        plt.title("L2 Dist")
        plt.subplot(133)
        plt.plot(displacements, WassDists)
        plt.stem([displacements[i]], [WassDists[i]])
        plt.xlabel("Displacements")
        plt.ylabel("Wasserstein Dist")
        plt.title("Wasserstein Dist")
        plt.savefig("%i.png"%i, bbox_inches='tight')

if __name__ == '__main__':
    testMovingDisc()

This gist is perfect for describing earth movers distance. Thank you!

Yaaay so glad it helped! Usually when I get these notifications there's a bug, so I'm happy to see a fun one for a change

…

On Mon, Mar 23, 2020 at 5:40 PM Justin ***@***.***> wrote: ***@***.**** commented on this gist. ------------------------------ This gist is perfect for describing earth movers distance. Thank you! — You are receiving this because you authored the thread. Reply to this email directly, view it on GitHub <https://gist.github.com/66352ae6ab06c009f02c705385a446f3#gistcomment-3224778>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAJWDZXKDMCRTLPKGZNYYBLRI7JLXANCNFSM4IE2C44A> .