#56 Doesn't use the fact a 2d gaussian is separable and only works for mu=0.0

The implementation in the answers for question 56 doesn't make use of the fact that a 2d gaussian is separable and can be implemented as two 1d gaussians - which is an order of magnitude faster on my machine. Also, the implementation is incorrect for mu != 0.0.

import numpy as np
import matplotlib.pyplot as plt

def original(m= 10, n=10, sigma=1.0, mu=0.0):
    X, Y = np.meshgrid(np.linspace(-1,1,m), np.linspace(-1,1,n))
    D = np.sqrt(X*X+Y*Y)
    G = np.exp(-( (D-mu)**2 / ( 2.0 * sigma**2 ) ) )
    return G

def corrected(m=10, n=10, sigma=1.0, mu=0.0):
    x, y = np.meshgrid(np.linspace(-1,1,m), np.linspace(-1,1,n))
    g = np.exp(-( ((x-mu)**2 + (y-mu) **2) / ( 2.0 * sigma**2 ) ) )
    return g

def separable(m=10, n = 10, sigma=1.0, mu=0.0):
    x = np.linspace(-1,1,m)
    y = np.linspace(-1,1,n)
    gx = np.exp(-( (x-mu)**2 / ( 2.0 * sigma**2 ) ) )
    gy = np.exp(-( (y-mu)**2 / ( 2.0 * sigma**2 ) ) )
    return gy[:, None] * gx[None, :]

Test for mu != 0.0

assert np.allclose(original(mu=0.0, sigma=2.9), separable(mu=0.0, sigma=2.9))
assert np.allclose(original(mu=0.0, sigma=2.9), corrected(mu=0.0, sigma=2.9))
assert np.allclose(separable(mu=0.5, sigma=2.9), corrected(mu=0.5, sigma=2.9))
assert np.allclose(separable(mu=0.5, sigma=2.9), original(mu=0.5, sigma=2.9))

Raises:

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
Untitled-1.ipynb Cell 2 line 4
      [2](vscode-notebook-cell:Untitled-1.ipynb?jupyter-notebook#W3sdW50aXRsZWQ%3D?line=1) assert np.allclose(original(mu=0.0, sigma=2.9), corrected(mu=0.0, sigma=2.9))
      [3](vscode-notebook-cell:Untitled-1.ipynb?jupyter-notebook#W3sdW50aXRsZWQ%3D?line=2) assert np.allclose(separable(mu=0.5, sigma=2.9), corrected(mu=0.5, sigma=2.9))
----> [4](vscode-notebook-cell:Untitled-1.ipynb?jupyter-notebook#W3sdW50aXRsZWQ%3D?line=3) assert np.allclose(separable(mu=0.5, sigma=2.9), original(mu=0.5, sigma=2.9))

AssertionError:

Plot the functions:

plt.figure()
plt.title("Original")
plt.imshow(original(mu=0.5, sigma=5.0))
plt.colorbar()
plt.figure()
plt.title("Corrected")
plt.imshow(corrected(mu=0.5, sigma=5.0))
plt.colorbar()
plt.figure()
plt.title("Separable")
plt.imshow(separable(mu=0.5, sigma=5.0))
plt.colorbar()

output output output

Time the functions:

%timeit original(1000, 1001, 10)
%timeit corrected(1000, 1001, 10)
%timeit separable(1000, 1001, 10)

Output:

9.47 ms ± 295 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
7.59 ms ± 198 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
894 µs ± 32.9 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each)

rougier / numpy-100

#56 Doesn't use the fact a 2d gaussian is separable and only works for mu=0.0 #205