View source: R/analytical_functions.R
| calc_min_dist_v | R Documentation | 
Calculate minimum distance to lateral and end walls in a V-shaped experimental tunnel
calc_min_dist_v(obj_name, simplify_output = TRUE)
| obj_name | The input viewr object; a tibble or data.frame with attribute
 | 
| simplify_output | If TRUE, the returned object includes only the minimum distance between the subject and the lateral/end walls. If FALSE, the returned object includes all variables internal to the calculation. | 
For tunnels in which vertex_angle is >90 degree,
bound_pos and bound_neg represent a planes orthogonal to the
lateral walls and are used to modify min_dist_pos and
min_dist_neg calculations to prevent erroneous outputs.
calc_min_dist_v() assumes the subject locomotes facing forward,
therefore min_dist_end represents the minimum distance between the
subject and the end wall to which it is moving towards All outputs are in
meters.
A tibble or data.frame with added variables for
height_2_vertex, height_2_screen, width_2_screen_pos,
width_2_screen_neg, min_dist_pos, min_dist_neg,
min_dist_end, bound_pos, and bound_neg.
Eric R. Press
Other mathematical functions: 
deg_2_rad(),
find_curve_elbow(),
get_2d_angle(),
get_3d_angle(),
get_3d_cross_prod(),
get_dist_point_line(),
get_traj_velocities(),
get_velocity(),
rad_2_deg()
 ## Import sample data from package
motive_data <-
  read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv",
                              package = 'pathviewr'))
 ## Process data up to and including insert_treatments()
motive_data_full <-
  motive_data %>%
  relabel_viewr_axes() %>%
  gather_tunnel_data() %>%
  trim_tunnel_outliers() %>%
  rotate_tunnel() %>%
  select_x_percent(desired_percent = 50) %>%
  separate_trajectories(max_frame_gap = "autodetect") %>%
  get_full_trajectories(span = 0.95) %>%
  insert_treatments(tunnel_config = "v",
                   perch_2_vertex = 0.4,
                   vertex_angle = 90,
                   tunnel_length = 2,
                   stim_param_lat_pos = 0.1,
                   stim_param_lat_neg = 0.1,
                   stim_param_end_pos = 0.3,
                   stim_param_end_neg = 0.3,
                   treatment = "lat10_end_30") %>%
 ## Now calculate the minimum distances to each wall
  calc_min_dist_v(simplify_output = TRUE)
  ## See 3 new variables for calculations to lateral and end walls
  names(motive_data_full)
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