- LINEAR
- Linear convolution
- CIRCULAR
- Circular Convolution
This class does convolutions by multiplying the Fourier transforms of the supplied Lattices and returning the inverse transform of the product. This is the best algorithm to use when the point spread function is large. This class does all the padding with zeros necessary to implement this algorithm. Hence the
Create a convolver that is initialised to do circular convolution with the specified point spread function. It is assumed that the supplied model will be the same shape as the point spread function.
Create a convolver that is initialised to do linear convolution with the specified point spread function. The size of the model you will convolve with must be specified.
Create a convolver that is initialised to do the specified type of convolution with the specified point spread function. The size of the model you expect to convolve with must be specified.
The copy constructor uses reference semantics
The assignment operator also uses reference semantics
The destructor does nothing special.
Perform linear convolution of the model with the previously specified psf. The supplied Lattices must be the same shape.
Perform in-place linear convolution of the model with the previously specified psf. Return the result in the same Lattice as the model.
Perform circular convolution of the model with the previously specified psf. Return the answer in result.
Perform in-place linear convolution of the model with the previously specified psf. Return the result in the same Lattice as the model.
Perform convolution on the specified model using the currently initialised convolution type (linear or circular). These functions will not resize the LatticeConvolver if the supplied Lattice is the wrong shape.
If the LatticeConvolver is setup for circular Convolution then the size of the supplied model must be less than or equal to the shape returned by the fftshape() function, which is usually the same as the shape of the psf.
If the LatticeConvolver is setup to do linear convolution the the input and output Lattices must have the same shape as the result from the shape() member function. The convolution may be either in-place or not.
Return the psf currently used by this convolver. The supplied Lattice must be the correct shape ie., the same as returned by the psfShape member function.
Resize the LatticeConvolver to do convolutions of the specified type and shape. The supplied function must always have the same number of dimensions as the internal point spread function (which can be found using the shape member function). The LatticeConvolver will be set up to do circular or linear convolutions depending on the supplied type
Returns the shape of the Lattices that the convolver will convolve. This shape will always have as many dimensions as the psf that was used to initialise the LatticeConvolver. If the LatticeConvolver is setup to do circular convolutions then every axis of the returned IPosition will be zero length. If the LatticeConvolver is setup to do linear convolutions then the returned IPosition will have a positive values on each axis that indicate the expected shape of the input model.
Returns the shape of the point spread function that the LatticeConvolver was initialised with.
Returns the type of convolution the LatticeConvolver is currently set up to do.
Returns the shape of the FFT's that the LatticeConvolver will do when performing the convolution. Not really useful except as a diagnostic tool. If the shape contains a lot of poorly factorisable lengths then the convolution will be slow.
Set usage of fast convolve with lesser flips