Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Change default accuracy of transforms #38

Merged
merged 1 commit into from
Oct 24, 2024
Merged

Change default accuracy of transforms #38

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 8 additions & 0 deletions CHANGELOG.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
This is disabled by default, and can be enabled by passing `gpu_method = :shared_memory`
(default is `:global_memory`).

### Changed

- [BREAKING] Change default precision of transforms.
By default, transforms on `Float64` or `ComplexF64` now have a relative precision of the order of $10^{-7}$.
This corresponds to setting `m = HalfSupport(4)` and oversampling factor `σ = 2.0`.
Previously, the default was `m = HalfSupport(8)` and `σ = 2.0`, corresponding
to a relative precision of the order of $10^{-14}$.

## [v0.5.6](https://github.com/jipolanco/NonuniformFFTs.jl/releases/tag/v0.5.6) - 2024-10-17

### Changed
Expand Down
7 changes: 5 additions & 2 deletions src/plan.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -78,7 +78,10 @@ The created plan contains all data needed to perform NUFFTs for non-uniform data
## NUFFT parameters
- `m = HalfSupport(8)`: the half-support of the convolution kernels. Large values
The following parameters control transform accuracy. The default values give a relative accuracy of
the order of ``10^{-7}`` for `Float64` or `ComplexF64` data.
- `m = HalfSupport(4)`: the half-support of the convolution kernels. Large values
increase accuracy at the cost of performance.
- `σ = 2.0`: NUFFT oversampling factor. Typical values are 2.0 (more accurate) and 1.25 (faster),
Expand Down Expand Up @@ -421,7 +424,7 @@ end
@inline to_static(ntrans::Int) = Val(ntrans)

# This constructor relies on constant propagation to make the output fully inferred.
Base.@constprop :aggressive function PlanNUFFT(::Type{T}, Ns::Dims; m = 8, kws...) where {T <: Number}
Base.@constprop :aggressive function PlanNUFFT(::Type{T}, Ns::Dims; m = 4, kws...) where {T <: Number}
h = to_halfsupport(m)
PlanNUFFT(T, Ns, h; kws...)
end
Expand Down