Skip to content

Latest commit

 

History

History
83 lines (66 loc) · 4.53 KB

NEWS.md

File metadata and controls

83 lines (66 loc) · 4.53 KB
Raw

version 3.1.5

  • Resolved background pattern artifacts in raster plotting; issue #50 by Camila Neder.

version 3.1.4

  • Just the biomod2 example is updated in vignettes; and the link in help file

version 3.1.3

  • the biomod2 and gstat packages are added to the Suggests section
  • Some minor edits in messages

version 3.1.2

  • The iteration in cv_spatial and spatialBlock is increased to 100 to make the result matches with v2.1.4
  • Removed the requirement of C++11
  • Some warnings are added for the miss use of the column argument

version 3.1.1

  • some internal fix.
  • the extend parameter is now added to spatialBlock and the function now uses cv_spatial internally.
  • the user_blocks in cv_spatial is restricted to random and predefined and systematic selection.
  • no raster package dependency

version 3.1.0

  • the result of the cv_spatial function for square blocks now matches the one of version 2 function spatialBlock (i.e. fold assignment starts from top-right corner; this is not the case for hexagon blocks)
  • square spatial blocks can be expanded to ensure no points fall outside the border of the blocks. This can be controlled by extend parameter now.

version 3.0.3

  • fixing a bug in counting records in the reporting of cv_spatial

version 3.0.2

  • fixing fold numbering of cv_spatial to reproducibility of earlier versions

version 3.0.1

  • Massive performance improvement in the C++ code of cv_nndm function for large datasets

version 3.0

  • Dependency to rgdal and rgeos are removed, and overall less dependency
  • Function names have been changed, with all functions now starting with cv_
  • The old functions (v2.x) still work to allow appropriate time for adapting the new code
  • The CV blocking functions are now: cv_spatial, cv_cluster, cv_buffer, and cv_nndm
  • Spatial blocks now support hexagonal (default), rectangular, and user-defined blocks
  • A fast C++ implementation of Nearest Neighbour Distance Matching (NNDM) algorithm (Milà et al. 2022) is now added
  • The NNDM algorithm can handle species presence-background data and other types of data
  • The cv_cluster function generates blocks based on kmeans clustering. It now works on both environmental rasters and the spatial coordinates of sample points
  • The cv_spatial_autocor function now calculates the spatial autocorrelation range for both the response (i.e. the binary or continuous data) and a set of continuous raster covariates
  • The new cv_plot function allows for visualization of folds from all blocking strategies using ggplot facets
  • The terra package is now used for all raster processing and supports both stars and raster objects, as well as files on disk.
  • The new cv_similarity provides measures on possible extrapolation to testing folds

version 2.1.4

  • fixed CRAN error for ggplot guide
  • added rgdal as a suggest
  • changed the crs of raster data in the package to avoid datum warnings

version 2.1.3

  • fix the warning for spatialBlock function on geographic coordinate system

version 2.1.2

  • predefined folds from user-defined blocks are noe accepted
  • add seed argument to spatialBlock to have consistent results where needed

version 2.1.0

  • snowfall package for parallel processing is replaces by future.apply package; #7
  • future.apply, shiny, shinydashboard, geosphere and ggplot2 packages moved to SUGGESTION packages. These are not install by default and the user is asked if needed. #7
  • RStoolbox is no longer used for clustering
  • an argument is added to envBlock function for sampling from raster layers
  • no dependency on sp package any more
  • doParallel = FALSE by default in spatialAutoRange function

version 2.0.1

  • print() and cat() are removed from the functions and verbose argument is added instead

version 2.0.0

  • most of the underlying functions are migrated to sf functions;
  • the parallel processing changed from foreach to snowfall;
  • the species argument in spatialBlock function accepts multi-class responses to find evenly distributed records in train and test folds;

version 1.1.0

  • change spatialAutoRange function to accepts rasters with low number of pixels; #2
  • the maskBySpecies = FALSE in spatialBlock function is no longer supported;
  • the numLimit argument in spatialBlock function is only accepts numeric values, and 0 means searching for evenly distributed folds;

version 1.0.1

  • add speciesData to spatialAutoRange function;