make_2dgaussian_kernel¶
- photutils.segmentation.make_2dgaussian_kernel(fwhm, size, mode='oversample', oversampling=10)[source]¶
Make a normalized 2D circular Gaussian kernel.
The kernel must have odd sizes in both X and Y, be centered in the central pixel, and normalized to sum to 1.
- Parameters:
- fwhmfloat
The full-width at half-maximum (FWHM) of the 2D circular Gaussian kernel.
- sizeint or (2,) int array_like
The size of the kernel along each axis. If
size
is a scalar then a square size ofsize
will be used. Ifsize
has two elements, they must be in(ny, nx)
(i.e., array shape) order.size
must have odd values for both axes.- mode{‘oversample’, ‘center’, ‘linear_interp’, ‘integrate’}, optional
- The mode to use for discretizing the 2D Gaussian model:
‘oversample’ (default): Discretize model by taking the average on an oversampled grid.
‘center’: 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.
‘integrate’: Discretize model by integrating the model over the bin.
- oversamplingint, optional
The oversampling factor used when
mode='oversample'
.
- Returns:
- kernel
astropy.convolution.Kernel2D
The output smoothing kernel, normalized such that it sums to 1.
- kernel