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BigCodeBench / BigCodeBench v0.1.0_hf cf9fb6c4-0490-535a-bd83-7f70f37de2f4

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import numpy as np
import matplotlib.pyplot as plt
import itertools

def task_func(n_walks, n_steps, seed=None):
    """
    Create and plot `n_walks` number of random walks, each with `n_steps` steps.

    The function checks for valid n_walks and n_steps, then generates walks via numpy.
    Each walk is plotted in a different color cycling through a predefined set of colors:
    ['b', 'g', 'r', 'c', 'm', 'y', 'k'].

    Parameters:
    - n_walks (int): The number of random walks to be generated and plotted.
    - n_steps (int): The number of steps in each random walk.
    - seed (int, optional): Seed for random number generation. Default is None.

    Returns:
    - ax (plt.Axes): A Matplotlib Axes containing the plotted random walks.

    Requirements:
    - numpy
    - matplotlib
    - itertools

    Example:
    >>> ax = task_func(5, 100, seed=42)
    >>> type(ax)
    <class 'matplotlib.axes._axes.Axes'>
    >>> ax.get_xticklabels()
    [Text(-20.0, 0, '−20'), Text(0.0, 0, '0'), Text(20.0, 0, '20'), Text(40.0, 0, '40'), Text(60.0, 0, '60'), Text(80.0, 0, '80'), Text(100.0, 0, '100'), Text(120.0, 0, '120')]
    """

instruct prompt

Create and plot `n_walks` number of random walks, each with `n_steps` steps. The function checks for valid n_walks and n_steps, then generates walks via numpy. Each walk is plotted in a different color cycling through a predefined set of colors: ['b', 'g', 'r', 'c', 'm', 'y', 'k'].
The function should output with:
    ax (plt.Axes): A Matplotlib Axes containing the plotted random walks.
You should write self-contained code starting with:

Code

import numpy as np
import matplotlib.pyplot as plt
import itertools
def task_func(n_walks, n_steps, seed=None):

code prompt

Code

import numpy as np
import matplotlib.pyplot as plt
import itertools
def task_func(n_walks, n_steps, seed=None):

entry point

task_func

libs

  • itertools
  • numpy
  • matplotlib

Discussion

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Source and history

task_id
cf9fb6c4-0490-535a-bd83-7f70f37de2f4
task_key
default--v0~2e1~2e0~5fhf--cf9fb6c4-0490-535a-bd83-7f70f37de2f4
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import