read_flydra_mat() is designed to import data from a .mat file that has been exported from Flydra software. The resultant object is a tibble that additionally has important metadata stored as attributes (see Details).

read_flydra_mat(mat_file, file_id = NA, subject_name, frame_rate = 100, ...)

Arguments

mat_file

A file (or path to file) in .mat format, exported from Flydra

file_id

(Optional) identifier for this file. If not supplied, this defaults to basename(file_name).

subject_name

Name that will be assigned to the subject

frame_rate

The capture frame rate of the session

...

Additional arguments that may be passed from other pathviewr functions

Value

A tibble with numerical data in columns. The first two columns will have frame numbers and time (assumed to be in secs), respectively. Columns 3 through 5 will contain position data. Note that unlike the behavior of read_motive_csv() this function produces "tidy" data that have already been gathered into key-value pairs based on subject.

See also

read_motive_csv for importing Motive data

Other data import functions: as_viewr(), import_and_clean_batch(), import_batch(), read_motive_csv()

Author

Vikram B. Baliga

Examples

library(pathviewr)

## Import the example Flydra data included in the package
flydra_data <-
  read_flydra_mat(system.file("extdata", "pathviewr_flydra_example_data.mat",
                             package = 'pathviewr'),
                  subject_name = "birdie_wooster")

## Names of variables in the resulting tibble
names(flydra_data)
#>  [1] "frame"           "time_sec"        "subject"         "position_length"
#>  [5] "position_width"  "position_height" "velocity"        "length_inst_vel"
#>  [9] "width_inst_vel"  "height_inst_vel"

## A variety of metadata are stored as attributes. Of particular interest:
attr(flydra_data, "pathviewr_steps")
#> [1] "viewr"           "renamed_tunnel"  "gathered_tunnel"