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I have a list of lists, where each list is associated with a score/weight. I want to produce a new list of lists by randomly selecting from the first one so that those with higher scores will appear more often. The line below works fine when population is just a normal list. But I want to have it for a list of lists.

population = [['a','b'],['b','a'],['c','b']]
list_of_prob = [0.2, 0.2, 0.6]

population = np.random.choice(population, 10, replace=True, p=list_of_prob)

This will give the output ValueError: a must be 1-dimensional

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  • @Chicony you should mention in the question that it's not necessary should be numpy Commented Oct 11, 2016 at 9:06

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Instead of passing the actual list, pass a list with indexes into the list.

np.random.choice already allows this, if you pass an int n then it works as if you passed np.arange(n).

So

choice_indices = np.random.choice(len(population), 10, replace=True, p=list_of_prob)
choices = [population[i] for i in choice_indices]
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6 Comments

TypeError: only integer arrays with one element can be converted to an index
@roganjosh use range(len(population))
This will actually work like a charm, just if you do choice = [population[i] for i in choice_index], instead of choice = population[choice_index] as choice_index is a list
@SardorbekImomaliev still the same error. It comes from line choice = population[choice_index]
@roganjosh: sorry, I didn't notice you were getting 10 values, assumed 1. Will edit.
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