apply_methods {CellBench} | R Documentation

## Apply methods

### Description

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.

### Usage

    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)

### Arguments

`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

### Value

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.

### See Also

`time_methods`

### Examples

    # 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)

[Package CellBench version 1.0.1 Index]