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- Astropy v1.1.1 »
- Convolution and filtering (`astropy.convolution`) »
- Model1DKernel

# Model1DKernel

class `astropy.convolution.``Model1DKernel`(model, **kwargs)

  Bases: `astropy.convolution.Kernel1D`

  Create kernel from 1D model.

  The model has to be centered on x = 0.

  Parameters:

  model : `Fittable1DModel`

  > Kernel response function model

  x_size : odd int, optional

  > Size in x direction of the kernel array. Default = 8 * width.

  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.

  factor : number, optional

  > Factor of oversampling. Default factor = 10.

  Raises:

  TypeError

  > If model is not an instance of `Fittable1DModel`

  See also

  `Model2DKernel`
    Create kernel from `Fittable2DModel`
  `CustomKernel`
    Create kernel from list or array

  Examples

  Define a Gaussian1D model:

      >>> from astropy.modeling.models import Gaussian1D
      >>> from astropy.convolution.kernels import Model1DKernel
      >>> gauss = Gaussian1D(1, 0, 2)

  And create a custom one dimensional kernel from it:

      >>> gauss_kernel = Model1DKernel(gauss, x_size=9)

  This kernel can now be used like a usual Astropy kernel.