apply_methods {CellBench} | R Documentation |
apply_methods() and its aliases apply_metrics and begin_benchmark take either lists of datasets or benchmark_tbl objects and applies a list of functions. The output is a benchmark_tbl where each method has been applied to each dataset or preceeding result.
apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE) ## S3 method for class 'list' apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE) ## S3 method for class 'benchmark_tbl' apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE) ## S3 method for class 'tbl_df' apply_methods(x, fn_list, name = NULL, suppress.messages = TRUE) apply_metrics(x, fn_list, name = NULL, suppress.messages = TRUE) begin_benchmark(x, fn_list, name = NULL, suppress.messages = TRUE)
x |
the list of data or benchmark tibble to apply methods to |
fn_list |
the list of methods to be applied |
name |
(optional) the name of the column for methods applied |
suppress.messages |
TRUE if messages from running methods should be suppressed |
benchmark_tbl object containing results from methods applied, the first column is the name of the dataset as factors, middle columns contain method names as factors and the final column is a list of results of applying the methods.
# list of data datasets <- list( set1 = rnorm(500, mean = 2, sd = 1), set2 = rnorm(500, mean = 1, sd = 2) ) # list of functions add_noise <- list( none = identity, add_bias = function(x) { x + 1 } ) res <- apply_methods(datasets, add_noise)