{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"fcd3ef0b-fc37-5a0e-a7b9-fee24e05748d","task_key":"default--v0~2e1~2e0~5fhf--fcd3ef0b-fc37-5a0e-a7b9-fee24e05748d","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf fcd3ef0b-fc37-5a0e-a7b9-fee24e05748d","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\ndef task_func(mean, std_dev, n):\\n\",\"complete_prompt\":\"import numpy as np\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(mean, std_dev, n):\\n    \\\"\\\"\\\"\\n    Generates a set of samples from a normal distribution with a specified mean and standard deviation.\\n    It also visualizes the generated samples by plotting their histogram and the probability density function.\\n\\n    Parameters:\\n    mean (float): The mean (mu) of the normal distribution.\\n    std_dev (float): The standard deviation (sigma) of the distribution.\\n    n (int): The number of samples to generate.\\n\\n    Returns:\\n    numpy.ndarray: An array of generated samples from the normal distribution.\\n\\n    Requirements:\\n    - numpy\\n    - scipy.stats\\n    - matplotlib.pyplot\\n\\n    Examples:\\n    Generate 1000 samples from a normal distribution with mean 0 and standard deviation 1.\\n    >>> len(task_func(0, 1, 1000))\\n    1000\\n\\n    Generate 500 samples from a normal distribution with mean 5 and standard deviation 2.\\n    >>> len(task_func(5, 2, 500))\\n    500\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generates a set of samples from a normal distribution with a specified mean and standard deviation. It also visualizes the generated samples by plotting their histogram and the probability density function. Generate 500 samples from a normal distribution with mean 5 and standard deviation 2. >>> len(task_func(5, 2, 500)) 500\\nThe function should output with:\\n    numpy.ndarray: An array of generated samples from the normal distribution.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\ndef task_func(mean, std_dev, n):\\n```\",\"libs\":\"['numpy', 'matplotlib', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}