make_metric_df: Use a set of (continuous) columns to choose a good set of...

In Acanthiza/envFunc: Functions to help with Environmental Science

Use a set of (continuous) columns to choose a good set of rows

Description

Use a set of (continuous) columns to choose a good set of rows

Usage

make_metric_df(
  df,
  mets_df = tibble::tibble(metric = "av_clust_size", high_good = TRUE, clust_sum = TRUE,
    level = "clustering"),
  context = c("method", "groups"),
  mets_col = "summary_mets",
  summarise_method = median,
  scale = FALSE,
  top_thresh = 0.25,
  best_thresh = 5,
  level = c("across", "within")
)

Arguments

df	Dataframe with columns over which to find good rows
mets_df	Dataframe mapping the name of possible metrics to cases (columns) in which to use that metric.
context	Character. Name of columns in df that define context.
mets_col	Character. Name of mets_df column to use in this instance.
summarise_method	Character. Name of method to use in summarising if there is more than one row per context.
scale	Logical. If true, all metrics will be rescale 0 ('worst') to 1 ('best').
top_thresh	Numeric specifying the proportion of rows considered 'top'.
best_thresh	Numeric specifying the absolute number of rows considered 'best'.
level	Either 'across' or 'within'. If the latter, only metrics that are set up to work 'within' clusters (rather than 'across' clusterings) are used.

Acanthiza/envFunc documentation built on Dec. 14, 2024, 10:47 p.m.