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Make functions pipe-friendly #320

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afdd732
Make functions pipe-friendly
strengejacke Jan 10, 2025
9ef3399
Merge branch 'main' into strengejacke/issue304
DominiqueMakowski Jan 12, 2025
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3 changes: 3 additions & 0 deletions NAMESPACE
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Original file line number Diff line number Diff line change
@@ -3,6 +3,9 @@
S3method(describe_nonlinear,data.frame)
S3method(describe_nonlinear,estimate_predicted)
S3method(describe_nonlinear,numeric)
S3method(estimate_contrasts,default)
S3method(estimate_contrasts,estimate_means)
S3method(estimate_contrasts,estimate_slopes)
S3method(format,estimate_contrasts)
S3method(format,estimate_grouplevel)
S3method(format,estimate_means)
46 changes: 35 additions & 11 deletions R/estimate_contrasts.R
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Original file line number Diff line number Diff line change
@@ -98,17 +98,24 @@
#'
#' @return A data frame of estimated contrasts.
#' @export
estimate_contrasts <- function(model,
contrast = NULL,
by = NULL,
predict = NULL,
ci = 0.95,
p_adjust = "holm",
comparison = "pairwise",
backend = getOption("modelbased_backend", "emmeans"),
transform = NULL,
verbose = TRUE,
...) {
estimate_contrasts <- function(model, ...) {
UseMethod("estimate_contrasts")
}


#' @export
#' @rdname estimate_contrasts
estimate_contrasts.default <- function(model,
contrast = NULL,
by = NULL,
predict = NULL,
ci = 0.95,
p_adjust = "holm",
comparison = "pairwise",
backend = getOption("modelbased_backend", "emmeans"),
transform = NULL,
verbose = TRUE,
...) {
## TODO: remove deprecation warning later
if (!is.null(transform)) {
insight::format_warning("Argument `transform` is deprecated. Please use `predict` instead.")
@@ -173,3 +180,20 @@ estimate_contrasts <- function(model,
class(out) <- c("estimate_contrasts", "see_estimate_contrasts", class(out))
out
}


#' @export
estimate_contrasts.estimate_means <- function(model, ...) {
x <- attributes(model)$model
contrast <- attributes(model)$by
# prepare dots - `by` must be removed
dot_args <- list(...)
dot_args$by <- NULL
# function arguments
fun_args <- c(list(x, contrast = contrast), dot_args)
# call contrasts function
do.call(estimate_contrasts, insight::compact_list(fun_args))
}

#' @export
estimate_contrasts.estimate_slopes <- estimate_contrasts.estimate_means
9 changes: 6 additions & 3 deletions man/estimate_contrasts.Rd
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R/estimate_grouplevel.R
attr(random, "type") <- type
attr(random, "model") <- model
attr(random, "parameters") <- params
attr(random, "data") <- insight::get_data(model, verbose = FALSE)[insight::find_random(model, split_nested = TRUE, flatten = TRUE)]

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file=R/estimate_grouplevel.R,line=92,col=121,[line_length_linter] Lines should not be more than 120 characters. This line is 133 characters.
class(random) <- c("estimate_grouplevel", class(random))
random
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R/format.R
#' @export
format.marginaleffects_contrasts <- function(x, model, p_adjust, comparison, ...) {
predict <- attributes(x)$predict

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file=R/format.R,line=108,col=3,[object_overwrite_linter] 'predict' is an exported object from package 'stats'. Avoid re-using such symbols.
groups <- attributes(x)$by
contrast <- attributes(x)$contrast
focal_terms <- attributes(x)$focal_terms
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R/get_emcontrasts.R
.format_emmeans_contrasts <- function(model, estimated, ci, p_adjust, ...) {
predict <- attributes(estimated)$predict

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file=R/get_emcontrasts.R,line=111,col=3,[object_overwrite_linter] 'predict' is an exported object from package 'stats'. Avoid re-using such symbols.
# Summarize and clean
if (insight::model_info(model)$is_bayesian) {
out <- cbind(estimated@grid, bayestestR::describe_posterior(estimated, ci = ci, verbose = FALSE, ...))
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R/get_emmeans.R
.format_emmeans_means <- function(x, model, ci = 0.95, verbose = TRUE, ...) {
predict <- attributes(x)$predict

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file=R/get_emmeans.R,line=145,col=3,[object_overwrite_linter] 'predict' is an exported object from package 'stats'. Avoid re-using such symbols.
# Summarize and clean
if (insight::model_info(model)$is_bayesian) {
means <- parameters::parameters(x, ci = ci, ...)
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R/reshape_grouplevel.R
# Get original dataframe of random
data <- attributes(x)$data

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file=R/reshape_grouplevel.R,line=27,col=3,[object_overwrite_linter] 'data' is an exported object from package 'utils'. Avoid re-using such symbols.
# Random parameters
if (all(group == "all")) group <- unique(x$Group)
# Merge while preserving order of original random
data[["__sort_id"]] <- seq_len(nrow(data))
data <- merge(data, data_wide, by = g, sort = FALSE)

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file=R/reshape_grouplevel.R,line=70,col=5,[object_overwrite_linter] 'data' is an exported object from package 'utils'. Avoid re-using such symbols.
data <- data[order(data[["__sort_id"]]), ]

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file=R/reshape_grouplevel.R,line=71,col=5,[object_overwrite_linter] 'data' is an exported object from package 'utils'. Avoid re-using such symbols.
data[["__sort_id"]] <- NULL
}
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R/smoothing.R
for (i in seq_len(nrow(combinations))) {
current_row <- paste(t(combinations[i, ]), collapse = "_")
x[x$temp == current_row, nums] <- sapply(x[x$temp == current_row, nums], smoothing, method = method, strength = strength, ...)

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file=R/smoothing.R,line=86,col=121,[line_length_linter] Lines should not be more than 120 characters. This line is 132 characters.
}
x$temp <- NULL
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R/standardize_methods.R
#' @export
standardize.estimate_predicted <- function(x, include_response = TRUE, ...) {
# Get data of predictors
data <- insight::get_data(attributes(x)$model, ...)

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file=R/standardize_methods.R,line=6,col=3,[object_overwrite_linter] 'data' is an exported object from package 'utils'. Avoid re-using such symbols.
data[[attributes(x)$response]] <- NULL # Remove resp from data
# Standardize predictors
x[names(data)] <- datawizard::standardize(as.data.frame(x)[names(data)], reference = data, ...)
# Standardize response
if (include_response == TRUE && insight::model_info(attributes(x)$model)$is_linear) {

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file=R/standardize_methods.R,line=13,col=7,[redundant_equals_linter] Using == on a logical vector is redundant. Well-named logical vectors can be used directly in filtering. For data.table's `i` argument, wrap the column name in (), like `DT[(is_treatment)]`.
resp <- insight::get_response(attributes(x)$model)
disp <- attributes(datawizard::standardize(resp, ...))$scale