`R/utility_functions.R`

`rotate_tunnel.Rd`

The rotation is applied about the height axis and affects tunnel length and width only, i.e. no rotation of height.

```
rotate_tunnel(
obj_name,
all_heights_min = 0.11,
all_heights_max = 0.3,
perch1_len_min = -0.06,
perch1_len_max = 0.06,
perch2_len_min = 2.48,
perch2_len_max = 2.6,
perch1_wid_min = 0.09,
perch1_wid_max = 0.31,
perch2_wid_min = 0.13,
perch2_wid_max = 0.35,
...
)
```

- obj_name
The input viewr object; a tibble or data.frame with attribute

`pathviewr_steps`

that includes`"viewr"`

that has been passed through`relabel_viewr_axes()`

and`gather_tunnel_data()`

(or is structured as though it has been passed through those functions).- all_heights_min
Minimum perch height

- all_heights_max
Maximum perch height

- perch1_len_min
Minimum length value of perch 1

- perch1_len_max
Maximum length value of perch 1

- perch2_len_min
Minimum length value of perch 2

- perch2_len_max
Maximum length value of perch 2

- perch1_wid_min
Minimum width value of perch 1

- perch1_wid_max
Maximum width value of perch 1

- perch2_wid_min
Minimum width value of perch 2

- perch2_wid_max
Maximum width value of perch 2

- ...
Additional arguments passed to/from other pathviewr functions

A viewr object (tibble or data.frame with attribute
`pathviewr_steps`

that includes `"viewr"`

) in which data have
been rotated according to user specifications.

The user first estimates the locations of the perches by specifying bounds for where each perch is located. The function then computes the center of each bounding box and estimates that to be the midpoint of each perch. Then the center point of the tunnel (center between the perch midpoints) is estimated. The angle between perch1_center, tunnel_center_point, and arbitrary point along the length axis (tunnel_center_point - 1 on length) is estimated. That angle is then used to rotate the data, again only in the length and width dimensions. Height is standardized by (approximate) perch height; values greater than 0 are above the perch and values less than 0 are below the perch level.

Other data cleaning functions:
`gather_tunnel_data()`

,
`get_full_trajectories()`

,
`quick_separate_trajectories()`

,
`redefine_tunnel_center()`

,
`relabel_viewr_axes()`

,
`rename_viewr_characters()`

,
`select_x_percent()`

,
`separate_trajectories()`

,
`standardize_tunnel()`

,
`trim_tunnel_outliers()`

,
`visualize_frame_gap_choice()`

Other tunnel standardization functions:
`redefine_tunnel_center()`

,
`standardize_tunnel()`

```
## Import the example Motive data included in the package
motive_data <-
read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv",
package = 'pathviewr'))
## Clean the file. It is generally recommended to clean up to the
## "trimmed" step before running rotate_tunnel().
motive_trimmed <-
motive_data %>%
relabel_viewr_axes() %>%
gather_tunnel_data() %>%
trim_tunnel_outliers()
## Now rotate the tunnel using default values
motive_rotated <-
motive_trimmed %>%
rotate_tunnel()
## The following attributes store information about
## how rotation & translation was applied
attr(motive_rotated, "rotation_degrees")
#> [1] 0.9022212
attr(motive_rotated, "rotation_radians")
#> [1] 0.01574673
attr(motive_rotated, "perch1_midpoint_original")
#> [1] 0.000 0.200 0.205
attr(motive_rotated, "perch1_midpoint_current")
#> [1] -1.270157e+00 4.645589e-15 2.050000e-01
attr(motive_rotated, "tunnel_centerpoint_original")
#> [1] 1.270 0.220 0.205
attr(motive_rotated, "perch2_midpoint_original")
#> [1] 2.540 0.240 0.205
attr(motive_rotated, "perch2_midpoint_current")
#> [1] 1.270157e+00 -4.645589e-15 2.050000e-01
```