Subset rows randomly
Usage
# S3 method for flowSet
slice_sample(.data, ..., n, prop, by = NULL, weight_by = NULL, replace = FALSE)Arguments
- .data
A
flowSet- ...
Unused.
- n, prop
Provide either n, the number of rows, or prop, the proportion of rows to select. If neither are supplied, n = 1 will be used. If n is greater than the number of rows in the group (or prop > 1), the result will be silently truncated to the group size. prop will be rounded towards zero to generate an integer number of rows.
A negative value of n or prop will be subtracted from the group size. For example, n = -2 with a group of 5 rows will select 5 - 2 = 3 rows; prop = -0.25 with 8 rows will select 8 * (1 - 0.25) = 6 rows.
- by
Optionally, an unquoted selection of columns to group by for just this operation. An alternative to group_by.
- weight_by
Sampling weights. This must evaluate to a vector of non-negative numbers the same length as the input. Weights are automatically standardized to sum to 1.
- replace
Should sampling be performed with (TRUE) or without (FALSE, the default) replacement.
Value
An object of the same type as .data. The output has the following properties:
* Each row may appear 0, 1, or many times in the output.
* Columns are not modified.
* Groups are not modified.
* A flowSet's pData is preserved.
Examples
my_flowset <- simulate_cytometry_data()$flowset
my_flowset |>
dplyr::slice_sample(n = 10)
#> A flowSet with 5 experiments.
#>
#> column names(10): feature_1 feature_2 ... feature_9 feature_10
#>