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- Astropy v1.1.1 »
- Convolution and filtering (`astropy.convolution`) »
- Gaussian1DKernel

# Gaussian1DKernel

class `astropy.convolution.``Gaussian1DKernel`(stddev, **kwargs)

  Bases: `astropy.convolution.Kernel1D`

  1D Gaussian filter kernel.

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

  Parameters:

  stddev : number

  > Standard deviation of the Gaussian kernel.

  x_size : odd int, optional

  > Size 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 linearly interpolating 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. Very slow.

  factor : number, optional

  > Factor of oversampling. Default factor = 10. If the factor is too large, evaluation can be very slow.

  See also

  `Box1DKernel`, `Trapezoid1DKernel`, `MexicanHat1DKernel`

  Examples

  Kernel response:

  >     import matplotlib.pyplot as plt
  >     from astropy.convolution import Gaussian1DKernel
  >     gauss_1D_kernel = Gaussian1DKernel(10)
  >     plt.plot(gauss_1D_kernel, drawstyle='steps')
  >     plt.xlabel('x [pixels]')
  >     plt.ylabel('value')
  >     plt.show()

  > (Source code, png, hires.png, pdf)