BigCodeBench / BigCodeBench v0.1.0_hf 7fa75c7c-8164-518a-9a38-c8ddfe4d5638

complete prompt

import numpy as np
from scipy.stats import mode
from scipy.stats import entropy


def task_func(numbers):
    """
    Creates and returns a dictionary with the mode and entropy of a numpy array constructed from a given list.
    The function first converts the list into a numpy array, then calculates the mode and the entropy (base 2) of this array,
    and finally adds them to the initial dictionary with the keys 'mode' and 'entropy'.

    Parameters:
        numbers (list): A non-empty list of numbers from which a numpy array is created to calculate mode and entropy.

    Returns:
        dict: A dictionary containing the 'mode' and 'entropy' of the array with their respective calculated values.

    Raises:
        ValueError if the input list `numbers` is empty

    Requirements:
        - numpy
        - scipy.stats.mode
        - scipy.stats.entropy

    Examples:
        >>> result = task_func([1, 2, 2, 3, 3, 3])
        >>> 'mode' in result and result['mode'] == 3 and 'entropy' in result
        True
    """

instruct prompt

Creates and returns a dictionary with the mode and entropy of a numpy array constructed from a given list. The function first converts the list into a numpy array, then calculates the mode and the entropy (base 2) of this array, and finally adds them to the initial dictionary with the keys 'mode' and 'entropy'.
The function should raise the exception for: ValueError if the input list `numbers` is empty
The function should output with:
    dict: A dictionary containing the 'mode' and 'entropy' of the array with their respective calculated values.
You should write self-contained code starting with:

Code

import numpy as np
from scipy.stats import mode
from scipy.stats import entropy
def task_func(numbers):

code prompt

Code

import numpy as np
from scipy.stats import mode
from scipy.stats import entropy
def task_func(numbers):

entry point

task_func

libs

• numpy
• scipy