{"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":"1d8423f8-284f-5a09-8aee-3f64a2731b8e","task_key":"default--v0~2e1~2e0~5fhf--1d8423f8-284f-5a09-8aee-3f64a2731b8e","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 1d8423f8-284f-5a09-8aee-3f64a2731b8e","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nfrom scipy.stats import norm\\nimport matplotlib.pyplot as plt\\ndef task_func(x):\\n\",\"complete_prompt\":\"import numpy as np\\nfrom scipy.stats import norm\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(x):\\n    \\\"\\\"\\\"\\n    Draws a plot visualizing a complex distribution created from two Gaussian distributions.\\n    The real part of the complex distribution is a Gaussian centered at 0 with a standard deviation of 1,\\n    and the imaginary part is a Gaussian centered at 2 with a standard deviation of 2.\\n\\n    Parameters:\\n        x (numpy.ndarray): The range of x values over which to plot the distribution.\\n\\n    Returns:\\n        numpy.ndarray: The complex distribution created from the two Gaussian distributions.\\n\\n    Raises:\\n        TypeError: If `x` is not a numpy.ndarray.\\n    \\n    Requirements:\\n    - numpy\\n    - scipy.stats.norm\\n    - matplotlib.pyplot\\n\\n    Examples:\\n    >>> X = np.linspace(-10, 10, 1000)\\n    >>> result = task_func(X)\\n    >>> result[0]\\n    (7.69459862670642e-23+3.037941424911643e-09j)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Draws a plot visualizing a complex distribution created from two Gaussian distributions. The real part of the complex distribution is a Gaussian centered at 0 with a standard deviation of 1, and the imaginary part is a Gaussian centered at 2 with a standard deviation of 2.\\nThe function should raise the exception for: TypeError: If `x` is not a numpy.ndarray.\\nThe function should output with:\\n    numpy.ndarray: The complex distribution created from the two Gaussian distributions.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nfrom scipy.stats import norm\\nimport matplotlib.pyplot as plt\\ndef task_func(x):\\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":[]}