--- title: "Changing Default Parameters" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Changing Default Parameters} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` ```{r setup} library(walkboutr) ``` `walkboutr` comes with several preset parameters. The parameters that we are using are:

- **Epoch length** `epoch_length = 30` Epoch length is the length of an epoch in seconds. - **CPE associated with being active** `active_counts_per_epoch_min = 500` The number of CPE associated with being active are the accelerometry counts, in CPE, that are considered to reflect someone who is active (compared to inactive or at a very low activity level) - **Minimum bout length** `minimum_bout_length = 10` The minimum bout length is in epochs and is the minimum amount of time that must elapse for something to be considered a bout. A minimum bout length is equal to a minimum bout length of 5 minutes. - **Local time zone** `local_time_zone = "America/Los_Angeles"` For the purposes of evaluating whether we have a complete day of data (a flag that is passed as an output of this package), we use the local time zone of your data. - **Maximum number of consecutive inactive epochs in a bout** `maximum_number_consec_inactive_epochs_in_bout = 3` A bout of walking, or activity, is allowed to have up to a certain number of consecutive epochs of inactivity (or low activity) before the bout would terminate. The standard amount of inactive time that can interrupt a bout is 2 minutes, and thus the maximum number of consecutive inactive epochs in a bout is 3, or 1.5 minutes. After that, we would hit the 2 minute threshold and the bout would end rather than be interrupted. If you want to set any of these parameters yourself, you can simply pass them into the functions. If you pass nothing, the above default parameter values will be used. For example, if we generate some sample data, we can then pass in a different parameter value. ```{r generate sample data} gps_data <- generate_walking_in_seattle_gps_data() accelerometry_counts <- make_full_day_bout_without_metadata() ``` Now that we have sample data, we can look at how `walkboutr` generates bouts: ```{r run walkbout functions, message = FALSE, warning = FALSE, results = 'hide'} walk_bouts <- identify_walk_bouts_in_gps_and_accelerometry_data(gps_data, accelerometry_counts, epoch_length = 15) summary_walk_bouts <- summarize_walk_bouts(walk_bouts) ``` This will change the way we treat epochs to regard them as 15 second intervals rather than 30 second intervals. The same can be done with any parameters listed above.