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A script to generate contour plots of Dirichlet distributions
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'''Functions for drawing contours of Dirichlet distributions.''' | |
# Author: Thomas Boggs | |
import numpy as np | |
import matplotlib.pyplot as plt | |
import matplotlib.tri as tri | |
from functools import reduce | |
_corners = np.array([[0, 0], [1, 0], [0.5, 0.75**0.5]]) | |
_triangle = tri.Triangulation(_corners[:, 0], _corners[:, 1]) | |
_midpoints = [(_corners[(i + 1) % 3] + _corners[(i + 2) % 3]) / 2.0 \ | |
for i in range(3)] | |
def xy2bc(xy, tol=1.e-3): | |
'''Converts 2D Cartesian coordinates to barycentric. | |
Arguments: | |
`xy`: A length-2 sequence containing the x and y value. | |
''' | |
s = [(_corners[i] - _midpoints[i]).dot(xy - _midpoints[i]) / 0.75 \ | |
for i in range(3)] | |
return np.clip(s, tol, 1.0 - tol) | |
class Dirichlet(object): | |
def __init__(self, alpha): | |
'''Creates Dirichlet distribution with parameter `alpha`.''' | |
from math import gamma | |
from operator import mul | |
self._alpha = np.array(alpha) | |
self._coef = gamma(np.sum(self._alpha)) / \ | |
reduce(mul, [gamma(a) for a in self._alpha]) | |
def pdf(self, x): | |
'''Returns pdf value for `x`.''' | |
from operator import mul | |
return self._coef * reduce(mul, [xx ** (aa - 1) | |
for (xx, aa)in zip(x, self._alpha)]) | |
def sample(self, N): | |
'''Generates a random sample of size `N`.''' | |
return np.random.dirichlet(self._alpha, N) | |
def draw_pdf_contours(dist, border=False, nlevels=200, subdiv=8, **kwargs): | |
'''Draws pdf contours over an equilateral triangle (2-simplex). | |
Arguments: | |
`dist`: A distribution instance with a `pdf` method. | |
`border` (bool): If True, the simplex border is drawn. | |
`nlevels` (int): Number of contours to draw. | |
`subdiv` (int): Number of recursive mesh subdivisions to create. | |
kwargs: Keyword args passed on to `plt.triplot`. | |
''' | |
from matplotlib import ticker, cm | |
import math | |
refiner = tri.UniformTriRefiner(_triangle) | |
trimesh = refiner.refine_triangulation(subdiv=subdiv) | |
pvals = [dist.pdf(xy2bc(xy)) for xy in zip(trimesh.x, trimesh.y)] | |
plt.tricontourf(trimesh, pvals, nlevels, **kwargs) | |
plt.axis('equal') | |
plt.xlim(0, 1) | |
plt.ylim(0, 0.75**0.5) | |
plt.axis('off') | |
if border is True: | |
plt.triplot(_triangle, linewidth=1) | |
def plot_points(X, barycentric=True, border=True, **kwargs): | |
'''Plots a set of points in the simplex. | |
Arguments: | |
`X` (ndarray): A 2xN array (if in Cartesian coords) or 3xN array | |
(if in barycentric coords) of points to plot. | |
`barycentric` (bool): Indicates if `X` is in barycentric coords. | |
`border` (bool): If True, the simplex border is drawn. | |
kwargs: Keyword args passed on to `plt.plot`. | |
''' | |
if barycentric is True: | |
X = X.dot(_corners) | |
plt.plot(X[:, 0], X[:, 1], 'k.', ms=1, **kwargs) | |
plt.axis('equal') | |
plt.xlim(0, 1) | |
plt.ylim(0, 0.75**0.5) | |
plt.axis('off') | |
if border is True: | |
plt.triplot(_triangle, linewidth=1) | |
if __name__ == '__main__': | |
f = plt.figure(figsize=(8, 6)) | |
alphas = [[0.999] * 3, | |
[5] * 3, | |
[2, 5, 15]] | |
for (i, alpha) in enumerate(alphas): | |
plt.subplot(2, len(alphas), i + 1) | |
dist = Dirichlet(alpha) | |
draw_pdf_contours(dist) | |
title = r'$\alpha$ = (%.3f, %.3f, %.3f)' % tuple(alpha) | |
plt.title(title, fontdict={'fontsize': 8}) | |
plt.subplot(2, len(alphas), i + 1 + len(alphas)) | |
plot_points(dist.sample(5000)) | |
plt.savefig('dirichlet_plots.png') | |
print('Wrote plots to "dirichlet_plots.png".') | |
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Minor changes for Python 3