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Use AbstractFFTs instead of FFTW #117

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e2ae064
Use AbstractFFTs instead of FFTW
devmotion Oct 3, 2023
29b595d
Support AbstractFFTs 0.5 for Julia 1.0 tests
devmotion Oct 3, 2023
5e0a937
Merge branch 'master' into dw/abstractffts
devmotion May 30, 2024
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9 changes: 6 additions & 3 deletions Project.toml
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Original file line number Diff line number Diff line change
@@ -1,25 +1,28 @@
name = "KernelDensity"
uuid = "5ab0869b-81aa-558d-bb23-cbf5423bbe9b"
authors = ["Simon Byrne and various contributors"]
version = "0.6.9"
version = "0.7.0"

[deps]
AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"

[compat]
AbstractFFTs = "0.5, 1"
Distributions = "0.23, 0.24, 0.25"
DocStringExtensions = "0.8, 0.9"
FFTW = "1"
Interpolations = "0.9, 0.10, 0.11, 0.12, 0.13, 0.14, 0.15"
StatsBase = "0.33, 0.34"
Test = "<0.0.1, 1"
julia = "1"

[extras]
FFTW = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["Test"]
test = ["FFTW", "Test"]
9 changes: 9 additions & 0 deletions README.md
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Expand Up @@ -7,6 +7,15 @@ Kernel density estimators for Julia.

## Usage

### Prerequisite

The kernel density estimates are computed with fast Fourier transforms (FFTs) internally using the [AbstractFFTs.jl](https://github.com/JuliaMath/AbstractFFTs.jl) interface.
You have to load a backend such as [FFTW.jl](https://github.com/JuliaMath/FFTW.jl) that implements this interface:

```julia
using FFTW
```

### Univariate
The main accessor function is `kde`:

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2 changes: 1 addition & 1 deletion src/KernelDensity.jl
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Expand Up @@ -6,7 +6,7 @@ using Distributions
using Interpolations

import Distributions: twoπ, pdf
import FFTW: rfft, irfft
using AbstractFFTs: rfft, irfft

export kde, kde_lscv, UnivariateKDE, BivariateKDE, InterpKDE, pdf

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1 change: 1 addition & 0 deletions test/bivariate.jl
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@@ -1,6 +1,7 @@
using Test
using Distributions
using KernelDensity
using FFTW

import KernelDensity: kernel_dist, default_bandwidth, kde_boundary, kde_range, tabulate

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1 change: 1 addition & 0 deletions test/interp.jl
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@@ -1,5 +1,6 @@
using Test
using KernelDensity
using FFTW

X = randn(100)
Y = randn(100)
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1 change: 1 addition & 0 deletions test/univariate.jl
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@@ -1,6 +1,7 @@
using Test
using Distributions
using KernelDensity
using FFTW

import KernelDensity: kernel_dist, default_bandwidth, kde_boundary, kde_range, tabulate

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