filter_.tracks: Return a subset of a tracks object with matching conditions.
In Ax3man/trackr: Analyze and Visualize Tracking Data

Description Usage Arguments Value Strategy on conflicting dependecies See Also

Method for the dplyr verb filter. Filters the tracks object according to logical filtering statements, in a strict sense. If one of the filtering conditions cannot be be applied to all tables present, it will either give an error (drop = FALSE) or will delete the tables that can't be filtered from the tracks object (drop = FALSE), see details. For another strategy, see find_sections and summarize_sections.

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## S3 method for class 'tracks'
filter_(.data, ..., drop = TRUE, .dots,
  repartition = FALSE)

`.data`	A tracks object.
`...`	The filtering conditions (logical statements).
`drop`	Whether to drop conflicting aggregate data. If the tracks object contains data that was aggregated over a variable that is now being used to filter, drop must be TRUE or an error will be raised. That is, any table that can not be filtered (i.e. it does not contain the variable used to filter) will be dropped. Have to opt in, since aggregation may have been expensive.
`repartition`	If TRUE, will collect and reassign the `tr` and `soc` tables. Useful if worker nodes become empty or unbalanced.

The subsetted tracks object.

It will apply the fitering to all the applicable sections of the tracks object. It will also attempt to check for any dependency problems. This is crucial in order to maintain internal consistency in the tracks object. For example, if you select a sequence of frames, any data that was aggregated over time (such as in the trial table) will now no longer match. If conflicts are found, by default, conflicted tables will be deleted from the tracks object, with a message. By setting drop = FALSE, you can have the function error instead.

filter, find_sections, summarise_sections

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