ds.resample_times: This function resample times to be consistent across labs.

In langcog/peekbankr: Accessing the Peekbank Database and working with Peekbank data

This function resample times to be consistent across labs.

Description

Resampling is done by the following steps:

Usage

ds.resample_times(df_table, table_type)

Arguments

df_table	to-be-resampled dataframe with t, aoi/xy values, trial_id and administration_id
table_type	table name, can only be "aoi_timepoints" or "xy_timepoints"

Details

1. iterate through every trial for every administration

2. create desired timepoint sequence with equal spacing according to pre-specified SAMPLE_RATE parameter

3. use approxfun to interpolate given data points to align with desired timepoint sequence "constant" interpolation method is used for AOI timepoints; "linear" interpolation method is used for xy timepoints; for more details on approxfun, please see: https://stat.ethz.ch/R-manual/R-devel/library/stats/html/approxfun.html

4. after resampling, bind resampled dataframes back together and re-assign aoi_timepoint_id

Value

df_out with resampled time, xy or aoi value rows

Examples

## Not run: 
dir_datasets <- "testdataset" # local datasets dir
lab_dataset_id <- "pomper_saffran_2016"
dir_csv <- file.path(dir_datasets, lab_dataset_id, "processed_data")
table_type <- "aoi_timepoints"
file_csv <- file.path(dir_csv, paste0(table_type, '.csv'))
df_table <- utils::read.csv(file_csv)
df_resampled <-ds.resample_times(df_table, table_type = "aoi_timepoints")

## End(Not run)

langcog/peekbankr documentation built on Jan. 6, 2025, 10:09 a.m.