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release: 0.6.0 (#98)
* fix: throw an error when X and Y columns are present in an sf object * ... * release: 0.6.0 * ... * ... * ... * ... * ... * ...
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.github/workflows/dev-cmd-check.yml

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# dev cmd check workflow of the mlr3 ecosystem v0.1.0
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# dev cmd check workflow of the mlr3 ecosystem v0.4.0
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# https://github.com/mlr-org/actions
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on:
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workflow_dispatch:
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inputs:
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debug_enabled:
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type: boolean
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description: 'Run the build with tmate debugging enabled'
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required: false
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default: false
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push:
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branches:
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- main
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matrix:
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config:
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- {os: ubuntu-latest, r: 'release', dev-package: 'mlr-org/mlr3'}
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- {os: ubuntu-latest, r: 'release', dev-package: "mlr-org/paradox', 'mlr-org/mlr3learners"}
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steps:
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- uses: actions/checkout@v3
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- uses: r-lib/actions/setup-pandoc@v2
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- uses: r-lib/actions/setup-r@v2
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with:
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r-version: ${{ matrix.config.r }}
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with:
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extra-packages: any::rcmdcheck
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needs: check
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error-on: '"note"'
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- name: Install dev versions
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run: pak::pkg_install(c('${{ matrix.config.dev-package }}'))
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run: pak::pkg_install('${{ matrix.config.dev-package }}')
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shell: Rscript {0}
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- uses: mxschmitt/action-tmate@v3
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if: ${{ github.event_name == 'workflow_dispatch' && inputs.debug_enabled }}
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with:
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limit-access-to-actor: true
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- uses: r-lib/actions/check-r-package@v2
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with:
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args: 'c("--no-manual", "--as-cran")'

.github/workflows/r-cmd-check.yml

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# r cmd check workflow of the mlr3 ecosystem v0.1.0
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# r cmd check workflow of the mlr3 ecosystem v0.4.0
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# https://github.com/mlr-org/actions
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on:
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workflow_dispatch:
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inputs:
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debug_enabled:
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type: boolean
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description: 'Run the build with tmate debugging enabled'
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required: false
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default: false
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push:
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branches:
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- main
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config:
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- {os: ubuntu-latest, r: 'devel'}
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- {os: ubuntu-latest, r: 'release'}
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- {os: ubuntu-latest, r: 'release', dev-package: 'mlr-org/mlr3@weights_reworked'}
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steps:
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- uses: actions/checkout@v3
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- uses: r-lib/actions/setup-pandoc@v2
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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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with:
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extra-packages: any::rcmdcheck
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needs: check
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error-on: '"note"'
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- uses: mxschmitt/action-tmate@v3
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if: ${{ github.event_name == 'workflow_dispatch' && inputs.debug_enabled }}
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with:
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limit-access-to-actor: true
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- uses: r-lib/actions/check-r-package@v2
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with:
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args: 'c("--no-manual", "--as-cran")'

DESCRIPTION

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Package: mlr3spatial
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Title: Support for Spatial Objects Within the 'mlr3' Ecosystem
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Version: 0.5.0.9000
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Date: 2024-03-09
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Version: 0.6.0
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Date: 2025-07-18
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Authors@R:
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c(
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person("Marc", "Becker", , "marcbecker@posteo.de", role = c("aut", "cre"),

NEWS.md

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# mlr3spatial (development version)
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# mlr3spatial 0.6.0
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* fix: Throw an error when `X` and `Y` columns are present in an sf object
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R/DataBackendRaster.R

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#' @title Coerce to spatial DataBackend
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#'
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#' @description
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#' Wraps a [DataBackend] around spatial objects.
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#' Wraps a [mlr3::DataBackend] around spatial objects.
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#' Currently these S3 methods are only alternative ways for writing `DataBackendRaster$new()`.
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#' They do not support coercing from other backends yet.
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#'
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#' @param ... (`any`)\cr
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#' Not used.
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#'
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#' @return [DataBackend].
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#' @return [mlr3::DataBackend].
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#' @rdname as_data_backend
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#'
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#' @exportS3Method

R/TaskClassifST.R

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#' @title Spatiotemporal Classification Task
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#'
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#' @description
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#' This task specializes [TaskClassif] for spatiotemporal classification problems.
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#' This task specializes [mlr3::TaskClassif] for spatiotemporal classification problems.
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#'
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#' A spatial example task is available via `tsk("ecuador")`.
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#'
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#' @description
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#' Returns coordinates of observations.
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#'
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#' @param row_ids (`integer()`)\cr
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#' @param row_ids (`integer()`)
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#' Vector of rows indices as subset of `task$row_ids`.
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#'
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#' @return [data.table::data.table()]

R/TaskRegrST.R

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#' @title Spatiotemporal Regression Task
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#'
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#' @description
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#' This task specializes [TaskRegr] for spatiotemporal regression problems.
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#' This task specializes [mlr3::TaskRegr] for spatiotemporal regression problems.
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#'
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#' A spatial example task is available via `tsk("cookfarm_mlr3")`.
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#'

R/as_task_classif_st.R

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#' This is a S3 generic, specialized for at least the following objects:
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#'
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#' 1. [TaskClassifST]: Ensure the identity.
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#' 2. [data.frame()] and [DataBackend]: Provides an alternative to the constructor of [TaskClassifST].
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#' 2. [data.frame()] and [mlr3::DataBackend]: Provides an alternative to the constructor of [TaskClassifST].
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#' 3. [sf::sf]: Extracts spatial meta data before construction.
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#' 4. [TaskRegr]: Calls [convert_task()].
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#' 4. [mlr3::TaskRegr]: Calls [mlr3::convert_task()].
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#'
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#' @inheritParams mlr3::as_task_classif
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#' @template param_coords_as_features

R/as_task_regr_st.R

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#' This is a S3 generic, specialized for at least the following objects:
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#'
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#' 1. [TaskRegrST]: Ensure the identity.
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#' 2. [data.frame()] and [DataBackend]: Provides an alternative to the constructor of [TaskRegrST].
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#' 2. [data.frame()] and [mlr3::DataBackend]: Provides an alternative to the constructor of [TaskRegrST].
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#' 3. [sf::sf]: Extracts spatial meta data before construction.
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#' 4. [TaskClassif]: Calls [convert_task()].
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#' 4. [mlr3::TaskClassif]: Calls [mlr3::convert_task()].
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#'
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#' @inheritParams mlr3::as_task_regr
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#' @template param_coords_as_features

R/predict_spatial.R

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#'
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#' @param newdata ([terra::SpatRaster] | `stars::stars` | [sf::sf] | `raster::RasterStack` | `raster::RasterBrick`).
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#' New data to predict on. All spatial data formats convertible by `as_data_backend()` are supported e.g. [terra::SpatRaster] or [sf::sf].
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#' @param learner ([Learner]).
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#' @param learner ([mlr3::Learner]).
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#' Learner with trained model.
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#' @template param-chunksize
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#' @param format (`character(1)`)\cr

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