To simulate a random self-avoiding walk in Python, we can use an algorithm that generates a path of random steps and checks each step to ensure that it does not intersect with any of the previous steps. Here's an example implementation:
main.py590 chars20 lines
This function generates a self-avoiding walk of length n
starting at the origin. It uses random.choice
to select a random direction to move in (up, down, left, or right) and checks if the new step intersects with any of the previous steps using the built-in in
operator. If the new step is valid, it is added to the path and the process repeats until the desired length is reached.
Note that this algorithm can take a long time to generate long walks, as the probability of finding a valid step decreases as the path gets longer. There are more efficient algorithms for generating self-avoiding walks, but this simple approach is easy to understand and implement.
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