wehub-resource-sync
37 lines
879 B
Python
Executable File
37 lines
879 B
Python
Executable File
import random
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import numpy as np
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def metropolis(func, rv, n, downsample=1):
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"""
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Metropolis algorithm
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Parameters
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----------
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func : callable
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(un)normalized distribution to be sampled from
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rv : RandomVariable
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proposal distribution which is symmetric at the origin
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n : int
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number of samples to draw
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downsample : int
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downsampling factor
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Returns
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-------
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sample : (n, ndim) ndarray
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generated sample
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"""
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x = np.zeros((1, rv.ndim))
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sample = []
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for i in range(n * downsample):
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x_new = x + rv.draw()
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accept_proba = func(x_new) / func(x)
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if random.random() < accept_proba:
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x = x_new
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if i % downsample == 0:
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sample.append(x[0])
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sample = np.asarray(sample)
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assert sample.shape == (n, rv.ndim), sample.shape
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return sample
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