vspline-dev - 0.4.1-1 main

vspline aims to be as fast as possible, it's main focus is processing
of bulk raster data, especially images. vspline can handle
.
- splines over real and integer data types and their aggregates
- a reasonable selection of boundary conditions
- spline degree up to 45
- arbitrary dimensionality of the spline
- using multithreaded code
- using the CPU's vector units if possible
.
On the evaluation side it provides
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- evaluation of the spline at point locations in the defined range
- evaluation of the spline's derivatives
- specialized code for degrees 0 and 1 (nearest neighbour and n-linear)
- mapping of arbitrary coordinates into the defined range
- evaluation of nD arrays of coordinates ('remap' function)
- coordinate-fed remap function ('index_remap')
- functor-based remap, aka 'transform' functions
- functor-based 'apply' function
- restoration of the original data from the coefficients
.
To produce maximum performance, vspline has a fair amount of collateral code,
and some of this code may be helpful beyond vspline:
.
- range-based multithreading with a thread pool
- functional constructs using vspline::unary_functor
- forward-backward n-pole recursive filtering
- separable convolution
- efficient access to the b-spline basis functions
- extremely precise precalculated constants
.
data handling is done with vigra data types, using vigra::MultiArrayView
for handling strided nD arrays, and vigra::TinyVector for small aggregates.
vspline optionally uses horizontal vectorization with Vc, but without Vc
present, it attempts to trigger the compiler's autovectorization by producing
deliberately vector-friendly inner loops.
bulk data processing is automatically multithreaded.