find_sections: Retrieve track sections based on conditions from multiple...
In Ax3man/trackr: Analyze and Visualize Tracking Data

Description Usage Arguments Details Value Functions Example use case

Similar to filter, but does not filter on each table seperately, but filters frames for which all conditions from seperate tables apply. That is, one can filter frames based on a variable in e.g. the tr table and tr, soc and group will be filtered for the frames where that condition is TRUE.

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find_sections(tracks, ..., tol = 1, pad = 0, add_times = TRUE)

find_sections_(tracks, ..., tol = 1, pad = 0, add_times = TRUE, .dots)

`tracks`	A tracks object.
`...`	Conditions.
`tol`	Combine sequences that are `tol` frames apart.
`pad`	Add padding of this many frames around each section. This allows for capturing context around sections of interest.
`add_times`	When `TRUE`, three columns will be added to the sections table that give human readable times, instead of only frame numbers.
`.dots`	Used to work around non-standard evaluation. See vignette("nse") for details.

It returns a list with tracks tables as well as a summary table of sequences. The first is named tracks, tables are grouped appropriately. The second list enty is named sections and provides an overview of the track sections that were found. It is grouped by trial, with a start, stop and length column.

The function supports a tolerance level which allows for combining sequences that are close together.

Any variables used as conditions will be looked up in the tr, soc and group tables and applied when present.

A tbl_df.

find_sections_: Retrieve the timestamps for track section based on conditions.

If one wants to select all sequences of frames where animals are chasing each other (to plot them, for example), one could filter for a high mean speed of the pair, and a small pairwise distance.

Ax3man/trackr documentation built on Oct. 8, 2019, 10:53 p.m.