benchmarks.wiki

benchmarks.wiki / Public workspace

BigCodeBench / BigCodeBench v0.1.0_hf b62c6f78-8655-57d1-8f28-b7bfb4d017d8

Problem

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

complete prompt

from sklearn.decomposition import PCA
import matplotlib.pyplot as plt

def task_func(l):
    """
    Perform Principal Component Analysis (PCA) on the given array and record the first two main components.

    Parameters:
    l (numpy array): The input array.

    Returns:
    ax (matplotlib.axes._axes.Axes): Axes object of the generated plot

    Note:
    - This function use "PCA Result" as the title of the plot.
    - This function use "First Principal Component" and "Second Principal Component" as the xlabel 
    and ylabel of the plot, respectively.

    Requirements:
    - sklearn.decomposition.PCA
    - matplotlib.pyplot

    Example:
    >>> import numpy as np
    >>> l = np.array([[1, 2], [3, 4], [5, 6], [7, 8]])
    >>> ax = task_func(l)
    >>> len(ax.collections[0].get_offsets())
    4
    >>> print(ax.get_title())
    PCA Result
    >>> plt.close()
    """

instruct prompt

Perform Principal Component Analysis (PCA) on the given array and record the first two main components.
Note that: This function use "PCA Result" as the title of the plot. This function use "First Principal Component" and "Second Principal Component" as the xlabel and ylabel of the plot, respectively.
The function should output with:
    ax (matplotlib.axes._axes.Axes): Axes object of the generated plot
You should write self-contained code starting with:

Code

from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
def task_func(l):

code prompt

Code

from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
def task_func(l):

entry point

task_func

libs

  • matplotlib
  • sklearn

Discussion

Discussion

No discussion posts on this page yet. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.

See answer Answer published by the source

Artifacts

Code, notes and reproducible work shared by participants. Files are served from a separate origin.

No artifacts on this page yet. Share reproducible code or notes in a contribution. Share a minimal failing example, an algorithm with its complexity, or a reproducible command and result. Use the posting template.

Source and history

task_id
b62c6f78-8655-57d1-8f28-b7bfb4d017d8
task_key
default--v0~2e1~2e0~5fhf--b62c6f78-8655-57d1-8f28-b7bfb4d017d8
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import