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waves (version 0.2.6)

rename: Functions renamed in waves 0.2.0

Description

`r lifecycle::badge('deprecated')`

waves 0.2.0 renamed a number of functions to ensure that every function name adheres to the tidyverse style guide.

* `AggregateSpectra()` -> `aggregate_spectra()` * `DoPreprocessing()` -> `pretreat_spectra()` * `FilterSpectra()` -> `filter_spectra()` * `FormatCV()` -> `format_cv()` * `PlotSpectra()` -> `plot_spectra()` * `PredictFromSavedModel()` -> `predict_spectra()` * `SaveModel()` -> `save_model()` * `TestModelPerformance()` -> `test_spectra()` * `TrainSpectralModel()` -> `train_spectra()`

Usage

AggregateSpectra(
  df,
  grouping.colnames = c("unique.id"),
  reference.value.colname = "reference",
  agg.function = "mean"
)
DoPreprocessing(df, test.data = NULL, pretreatment = 1)
FilterSpectra(
  df,
  filter = TRUE,
  return.distances = FALSE,
  num.col.before.spectra = 4,
  window.size = 10,
  verbose = TRUE
)
FormatCV(
  trial1,
  trial2,
  trial3 = NULL,
  cv.scheme,
  stratified.sampling = TRUE,
  proportion.train = 0.7,
  seed = NULL,
  remove.genotype = FALSE
)
PlotSpectra(
  df,
  num.col.before.spectra = 1,
  window.size = 10,
  detect.outliers = TRUE,
  color = NULL,
  alternate.title = NULL,
  verbose = TRUE
)
PredictFromSavedModel(
  input.data,
  model.stats.location,
  model.location,
  model.method = "pls"
)
SaveModel(
  df,
  save.model = TRUE,
  pretreatment = 1,
  model.save.folder = NULL,
  model.name = "PredictionModel",
  best.model.metric = "RMSE",
  k.folds = 5,
  proportion.train = 0.7,
  tune.length = 50,
  model.method = "pls",
  num.iterations = 10,
  stratified.sampling = TRUE,
  cv.scheme = NULL,
  trial1 = NULL,
  trial2 = NULL,
  trial3 = NULL,
  verbose = TRUE
)
TestModelPerformance(
  train.data,
  num.iterations,
  test.data = NULL,
  pretreatment = 1,
  k.folds = 5,
  proportion.train = 0.7,
  tune.length = 50,
  model.method = "pls",
  best.model.metric = "RMSE",
  stratified.sampling = TRUE,
  cv.scheme = NULL,
  trial1 = NULL,
  trial2 = NULL,
  trial3 = NULL,
  split.test = FALSE,
  verbose = TRUE
)
TrainSpectralModel(
  df,
  num.iterations,
  test.data = NULL,
  k.folds = 5,
  proportion.train = 0.7,
  tune.length = 50,
  model.method = "pls",
  best.model.metric = "RMSE",
  stratified.sampling = TRUE,
  cv.scheme = NULL,
  trial1 = NULL,
  trial2 = NULL,
  trial3 = NULL,
  split.test = FALSE,
  verbose = TRUE
)

Arguments