# Gaussian2DKernel¶

class astropy.convolution.Gaussian2DKernel(x_stddev, y_stddev=None, theta=0.0, **kwargs)[source]

2D Gaussian filter kernel.

The Gaussian filter is a filter with great smoothing properties. It is isotropic and does not produce artifacts.

Parameters: x_stddev : float Standard deviation of the Gaussian in x before rotating by theta. y_stddev : float Standard deviation of the Gaussian in y before rotating by theta. theta : float Rotation angle in radians. The rotation angle increases counterclockwise. x_size : odd int, optional Size in x direction of the kernel array. Default = 8 * stddev. y_size : odd int, optional Size in y direction of the kernel array. Default = 8 * stddev. mode : str, optional One of the following discretization modes: ‘center’ (default) Discretize model by taking the value at the center of the bin. ‘linear_interp’ Discretize model by performing a bilinear interpolation between the values at the corners of the bin. ‘oversample’ Discretize model by taking the average on an oversampled grid. ‘integrate’ Discretize model by integrating the model over the bin. factor : number, optional Factor of oversampling. Default factor = 10.

Examples

Kernel response:

import matplotlib.pyplot as plt
from astropy.convolution import Gaussian2DKernel
gaussian_2D_kernel = Gaussian2DKernel(10)
plt.imshow(gaussian_2D_kernel, interpolation='none', origin='lower')
plt.xlabel('x [pixels]')
plt.ylabel('y [pixels]')
plt.colorbar()
plt.show()


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