Estimate the spatial frequency of visual stimuli from the subject's perspective in an experimental tunnel.

get_sf(obj_name)

Arguments

obj_name

The input viewr object; a tibble or data.frame with attribute pathviewr_steps that includes "viewr" and vis_angles_calculated.

Value

A tibble or data.frame with added variables for sf_pos, sf_neg, and sf_end. angle.

Details

get_sf() assumes the following:

  • The subject's gaze is fixed at the point on the either side of the tunnel that minimizes the distance to visual stimuli and therefore maximizes visual angles.

  • The subject's head is facing parallel to the length axis of the tunnel. Visual perception functions in future versions of pathviewr will integrate head orientation coordinates. Spatial frequency is reported in cycles/degree and is the inverse of visual angle (degrees/cycle).

See also

Other visual perception functions: calc_min_dist_box(), get_vis_angle()

Author

Eric R. Press

Examples

## Import sample data from package motive_data <- read_motive_csv(system.file("extdata", "pathviewr_motive_example_data.csv", package = 'pathviewr')) flydra_data <- read_flydra_mat(system.file("extdata", "pathviewr_flydra_example_data.mat", package = 'pathviewr'), subject_name = "birdie_sanders") ## Process data up to and including get_vis_angle() 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") %>% calc_min_dist_v(simplify_output = TRUE) %>% get_vis_angle() %>% ## Now calculate the spatial frequencies get_sf()
#> autodetect is an experimental feature -- please report issues.
flydra_data_full <- flydra_data %>% redefine_tunnel_center(length_method = "middle", height_method = "user-defined", height_zero = 1.44) %>% select_x_percent(desired_percent = 50) %>% separate_trajectories(max_frame_gap = "autodetect") %>% get_full_trajectories(span = 0.95) %>% insert_treatments(tunnel_config = "box", tunnel_length = 3, tunnel_width = 1, 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") %>% calc_min_dist_box() %>% get_vis_angle() %>% ## Now calculate the spatial frequencies get_sf()
#> autodetect is an experimental feature -- please report issues.