Sampling from joint probability mass function in python - Stack Overflow

admin管理员组

文章数量:1435859

I have a non-negative normalized vector p. I would like to sample an index from the index set of the vector. The probability getting sample k is p[k]. Using np.random.choice function, I can write the following code.

p = [0.2, 0.3, 0.1, 0.3, 0.1]
indices = np.arange(len(p))
k = np.random.choice(indices, p=p)

My question is, how can I generalize this code for multi-dimensional arrays? For example, given three dimensional non-negative normalized IxJxK tensor p = np.random.rand(I,J,K) how can I sample the index (i,j,k) with the probability p[i,j,k]?

I have a non-negative normalized vector p. I would like to sample an index from the index set of the vector. The probability getting sample k is p[k]. Using np.random.choice function, I can write the following code.

p = [0.2, 0.3, 0.1, 0.3, 0.1]
indices = np.arange(len(p))
k = np.random.choice(indices, p=p)

My question is, how can I generalize this code for multi-dimensional arrays? For example, given three dimensional non-negative normalized IxJxK tensor p = np.random.rand(I,J,K) how can I sample the index (i,j,k) with the probability p[i,j,k]?

• python
• probability
• sampling

Share Improve this question Follow edited Nov 17, 2024 at 6:19 Robert Dodier 17.6k22 gold badges3434 silver badges5454 bronze badges asked Nov 16, 2024 at 2:52 Sakurai.JJSakurai.JJ 69444 silver badges1313 bronze badges

Add a comment  | 

1 Answer 1

Sorted by: Reset to default 2

Suppose that x is a probability matrix:

x = np.random.random((3, 4, 5))
x /= np.sum(x)

You can use flatten(x) and np.random.choice() to get values in the range 0..3x4x5 with the associated probabilities:

flat = x.flatten()
temp = np.random.choice(np.arange(len(flat)), 10, p=flat)
print(temp)

You can now convert the indices in temp into indices in the original array:

np.unravel_index(temp, x.shape))

Note that this will return a tuple of three numpy arrays, with the first array being the first index, the second element being the second index, and so on.

本文标签： Sampling from joint probability mass function in pythonStack Overflow