python - Random Walkers model running too slow

Question

I'm writing a simple model to investigate the branching of rivers using random walks. The walkers move across a 2D lattice and if they come into contact with the cluster (the river channel) they stop walking. The code works and produces the expected results of a branching river, but I've only used it for a small lattice. I want to run the model for a much larger lattice and for more iterations but it just seems too slow to do at the moment.

I think it is the way that I check if a walker is in the cluster. If a walker is next to the cluster it has a certain probability of sticking and stop walking.

I'm wondering if there is a more efficient way of doing this to speed up the model.

This is the loop for the model:

while iteration_number < iteration_total:
    Walker.step_all()  # move all walkers
    lattice = np.zeros((L, L), dtype='uint8')

    #add the walkers and source to the lattice 
    lattice[tuple(np.array([walker.xy for walker in walkers]).T)] = 1
    lattice[source] = 2

    # cluster analysis, set those in cluster to stop walking
    cluster, cluster_num = nd.label(lattice)

    for walker in (walker for walker in walkers if walker.walking == True):
        if (walker.xy == np.argwhere(np.isin(cluster, cluster[lattice == 2]))).all(axis=1).any():
            #decision returns a true or false value based on the probability
            walker.walking = decision(probability) 

    #Track the number of iterations
    iteration_number += 1
    print('Iteration:' + str(int(iteration_number)), end='
')

Any help would be appreciated.

question from:https://stackoverflow.com/questions/66049217/random-walkers-model-running-too-slow

Answer 1

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