BigCodeBench / BigCodeBench v0.1.0_hf e72418c7-4429-5a58-8199-294bad97e33c

complete prompt

import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_filter

def task_func(image, sigma=2):
    """
    Apply a Gaussian filter to a given image and draw the original and filtered images side by side.

    Parameters:
    - image (numpy.ndarray): The input image to apply the filter on.
    - sigma (float, optional): The sigma value for the Gaussian filter. Default is 2.

    Returns:
    - ax (matplotlib.axes.Axes): Axes object containing the plot. Two plots with titles 'Original' and 'Filtered'. 
    - filtered_image (numpy.ndarray): The numpy array of pixel values for the filtered image.

    Raises:
    - ValueError: If sigma is non-positive.
    - TypeError: If the input is not a numpy array.

    Requirements:
    - numpy
    - matplotlib.pyplot
    - scipy.ndimage

    Example:
    >>> from skimage import data
    >>> ax, filtered_image = task_func(data.coins())
    >>> ax[0].get_title()  # Checking the title of the first subplot
    'Original'
    >>> ax[1].get_title()  # Checking the title of the second subplot
    'Filtered'
    """

instruct prompt

Apply a Gaussian filter to a given image and draw the original and filtered images side by side.
The function should raise the exception for: ValueError: If sigma is non-positive. TypeError: If the input is not a numpy array.
The function should output with:
    ax (matplotlib.axes.Axes): Axes object containing the plot. Two plots with titles 'Original' and 'Filtered'.
    filtered_image (numpy.ndarray): The numpy array of pixel values for the filtered image.
You should write self-contained code starting with:

Code

import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_filter
def task_func(image, sigma=2):

code prompt

Code

import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import gaussian_filter
def task_func(image, sigma=2):

entry point

task_func

libs

• numpy
• matplotlib
• scipy