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test multiple os
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.github/workflows/R-CMD-check.yml

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@@ -8,7 +8,16 @@ name: R-CMD-check
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jobs:
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R-CMD-check:
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runs-on: ubuntu-latest
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runs-on: ${{ matrix.config.os }}
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name: ${{ matrix.config.os }} (${{ matrix.config.r }})
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strategy:
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fail-fast: false
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matrix:
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config:
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- {os: ubuntu-latest, r: 'release'}
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- {os: windows-latest, r: 'release'}
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env:
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GITHUB_PAT: ${{ secrets.BLOCKCV_TOKEN }}
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- name: Setting up pandoc for Rmd docs
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uses: r-lib/actions/setup-pandoc@v2
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- uses: r-lib/actions/setup-tinytex@v2
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if: runner.os != 'Windows'
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- uses: r-lib/actions/setup-r@v2
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with:
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r-version: ${{ matrix.config.r }}
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use-public-rspm: true
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- uses: r-lib/actions/setup-r-dependencies@v2
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uses: r-lib/actions/check-r-package@v2
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- name: Test coverage
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if: matrix.config.os == 'ubuntu-latest'
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run: |
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covr::codecov(
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quiet = FALSE,
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function_exclusions = c("rangeExplorer", "foldExplorer", "cv_block_size")
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)
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shell: Rscript {0}
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env:
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CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
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CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

R/cv_similarity.R

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@@ -30,13 +30,13 @@
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#' experimental.
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#'
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#' @inheritParams cv_plot
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#' @param x a simple features (sf) or SpatialPoints object of the spatial sample data used for creating
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#' @param x a simple features (sf) object of the spatial sample points used for creating
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#' the \code{cv} object.
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#' @param r a terra SpatRaster object of environmental predictor that are going to be used for modelling. This
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#' is used to calculate similarity between the training and testing points.
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#' @param method the similarity method including: MESS, L1 and L2. Read the details section.
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#' @param num_sample number of random samples from raster to calculate similarity distances (only for L1 and L2).
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#' @param num_plot a vector of indices of folds.
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#' @param num_plot a vector of indices of folds for plotting (default uses all).
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#' @param jitter_width numeric; the width of jitter points.
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#' @param points_size numeric; the size of points.
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#' @param points_alpha numeric; the opacity of points
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#' iteration = 1)
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#'
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#' # compute extrapolation
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#' cv_similarity(cv = sb, r = covars, x = pa_data)
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#' cv_similarity(cv = sb, r = covars, x = pa_data, method = "MESS")
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#'
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#' }
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cv_similarity <- function(

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