wrap_long: Wrapper for long data (tidy) for a variety of functions

In sbpdata/compost: Compute Complexity Metrics

Description

Takes input in long data format and applies the compost-package function listed in 'fun'. Outputs long format data as well.

Usage

wrap_long(fun, args = NULL, int_df = NULL, rca_df = NULL,
  sim_df = NULL)

Arguments

fun	selects the function to apply to the input data. Possible values are: 'get_rca', 'get_similarity'
args	list with arguments to the function listed in fun. Possible arguments depends on the function. 'get_rca': - 'binary' (logical) decides whether RCA values are binarized. Possible values are 'TRUE' or 'FALSE'. 'get_similarity': - 'method' (string) selects equation to use for similarity calculations. Possible values are 'jaccard', 'association', or 'proximity' 'get_average_sim': - 'exclude0' (logical) decides if 0s should be excluded (as NA values) when taking average_sim. Possible values are 'TRUE' or 'FALSE' 'get_density': - 'binary' (logical) decides if it is allowed for RCA matrix to be non-binary. If 'FALSE' RCA values (non binary) can act as weights for similarity values. Note: 'get_closest_sim', and 'get_weighted_average_sim' does not have any additional arguments.
int_df	data frame that contains four variables: time, region, unit, intensity. Default is NULL.
rca_df	data frame that contains four variables: time, region, unit, rca. Default is NULL.
sim_df	data frame that contains four variables: time, from_unit, to_unit, similarity. Default is NULL.

sbpdata/compost documentation built on Nov. 5, 2019, 6:17 a.m.