Releases: JuliaApproximation/BasisFunctions.jl
Releases · JuliaApproximation/BasisFunctions.jl
v0.7.3
BasisFunctions v0.7.3
v0.7.2
v0.7.1
BasisFunctions v0.7.1
This is a non-breaking release. New features:
- the inverse of a function can be computed in a number of limited cases (monotonic function on an interval)
- Gram Schmidt orthogonalisation of a basis was added (using the modified Gram Schmidt algorithm)
v0.7.0
BasisFunctions v0.7.0
Breaking changes
- an expansion (dictionary+coefficients) no longer acts as the vector of coefficients. This means it cannot be indexed (as in
e[2]
returning the second coefficient) and cannot be iterated over - there are some interface cleanups. The
norm
andmoment
functions with a combination of dictionary and coefficient as arguments are renamed todict_norm
anddict_moment
instead. One can still invokenorm
on a basisfunction, e.g.,norm(dict[3])
Features
- computing with expansions has improved. For example, computing the diagonal of the Christoffel-Darboux kernel of a polynomial basis can be done as follows:
julia> basis = orthogonalize(Legendre(3))
DiagonalOperator(v) * Legendre(3)
v = 3-element Vector{Float64}:
0.707107
1.22474
1.58114
julia> k = sum(phi^2 for phi in basis)
Expansion(Legendre(5), v)
v = 5-element Vector{Float64}:
1.5
8.28036e-16
1.71429
1.14325e-15
1.28571
v0.6.5
BasisFunctions v0.6.5
- supporting routines for the Plots package have been moved to an extension conditional on loading RecipesBase
- similarly, support for PGFPlotsX has moved to an extension
Closed issues:
- FillArrays compat very tight (#56)