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@@ -31,7 +25,7 @@ This package provides a Julia version of MATLAB's `inpaint_nans` function (origi
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Simply put, [Inpaintings.jl](https://github.com/briochemc/Inpaintings.jl) provides a simple `inpaint` function, which takes an array `A` as input and inpaints its `missing` values by solving a simple *n*-dimensional PDE.
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The `inpaint` function can also be used to inpaint `NaN`s or any other values, thanks to the syntax described below and in the [documentation](https://briochemc.github.io/Inpaintings.jl/stable).
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## Usage:
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## Usage:
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Like every Julia package you must first add it via `]add Inpaintings`.
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And every time you want to use [Inpaintings.jl](https://github.com/briochemc/Inpaintings.jl), you must start with
@@ -43,7 +37,7 @@ In order to `inpaint` an array `A`'s `missing` values, simply apply `inpaint` to
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```julia
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julia>inpaint(A) # will inpaint missing values
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```
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The array to be inpainted can be a vector, a matrix, or even an *n*-dimensional array.
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The array to be inpainted can be a vector, a matrix, or even an *n*-dimensional array.
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If your array `A` has some `NaN` values and is filled with floats otherwise, then
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```julia
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In this case, the values of `A` for which `f` returns `true` will be inpainted.
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(For example, `f` can be, e.g., `ismissing` or `isnan`, but it can also be `x -> x < 0`.)
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Finally, [Inpaintings.jl](https://github.com/briochemc/Inpaintings.jl) provides a syntax to allow some dimensions to be assumed cyclic:
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Finally, [Inpaintings.jl](https://github.com/briochemc/Inpaintings.jl) provides a syntax to allow some dimensions to be assumed cyclic:
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```julia
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julia>inpaint(A, cycledims=[1]) # will inpaint A with dimension 1 as cyclic
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