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- import numpy as np
- from scipy.stats import dirichlet
- import ternary
- scale = 60
- x = np.load("votes_distrib.npz")
- alphas = x["alphas"].mean(axis=0)
- def prob(p):
- p = np.array(p)
- print(p)
- if np.all(p>0):
- return dirichlet.logpdf(p, alphas)
- else:
- return 0
- figure, tax = ternary.figure(scale=scale)
- tax.heatmapf(prob, boundary=True, style="triangular")
- tax.boundary(linewidth=2.0)
- tax.set_title("Shannon Entropy Heatmap")
- tax.savefig("votes_distrib.eps")
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