Source code for pyabc.random_choice.random_choice

import numpy as np

[docs] def fast_random_choice(weights): """ This is at least for small arrays much faster than numpy.random.choice. For the Gillespie, overall this brings for 3 reactions a speedup factor of 2. """ # rough heuristic when it makes sense to use numpy's implementation if len(weights) >= 15: return np.random.choice(len(weights), p=weights) # cumulative weights cs = 0 # draw a uniform random number u = np.random.rand() # return weight index at random variable for k in range(len(weights)): cs += weights[k] if u <= cs: return k # error when u > sum(weights) < 1 (not checked pro-actively) raise ValueError("Random choice error {}".format(weights))