Generates a synthetic anipoint object with random coordinates for testing and demonstration purposes. The function creates a complete design with all combinations of time points, individuals, keypoints, trials, and sessions.
Usage
example_anipoint(
n_obs = 50,
n_individuals = 3,
n_keypoints = 11,
n_trials = 1,
n_sessions = 1,
n_dims = 2
)Arguments
- n_obs
Integer. Number of time observations per combination. Default is 50.
- n_individuals
Integer. Number of individuals to simulate. Default is 3.
- n_keypoints
Integer. Number of keypoints per individual (max 11). Default is 11. When set to 1, only "centroid" is used. Otherwise, anatomical keypoints are used (head, neck, shoulders, etc.).
- n_trials
Integer. Number of trials per session. Default is 1.
- n_sessions
Integer. Number of sessions. Default is 1.
- n_dims
Integer. Number of spatial dimensions (1, 2, or 3). Default is 2. If 1, only x coordinates are generated. If 2, x and y coordinates are generated. If 3, x, y, and z coordinates are generated.
Value
An anipoint object containing randomly generated tracking data with
columns for individual, keypoint, time, trial, session, and spatial coordinates
(x, y, and/or z depending on n_dims). The coordinates are drawn from a
standard normal distribution.
Examples
# Create a basic example with default parameters (2D)
example_anipoint()
#> # Individuals: 1, 2, 3
#> # Keypoints: head, neck, shoulder_right, shoulder_left, abdomen, hip_right,
#> # hip_left, knee_right, knee_left, foot_right, foot_left
#> # Sessions: 1
#> # Trials: 1
#> individual keypoint session trial time x y confidence
#> <int> <fct> <int> <int> <int> <dbl> <dbl> <dbl>
#> 1 1 head 1 1 1 -0.230 1.78 0.568
#> 2 1 head 1 1 2 -1.51 1.32 0.955
#> 3 1 head 1 1 3 -0.584 -0.724 0.818
#> 4 1 head 1 1 4 -2.02 -0.263 0.444
#> 5 1 head 1 1 5 0.404 -0.349 0.810
#> 6 1 head 1 1 6 0.550 -0.213 0.556
#> 7 1 head 1 1 7 0.0284 0.749 0.833
#> 8 1 head 1 1 8 0.893 -3.00 0.825
#> 9 1 head 1 1 9 -0.377 -0.206 0.914
#> 10 1 head 1 1 10 0.606 -0.144 0.630
#> # ℹ 1,640 more rows
# Create a 1D example
example_anipoint(n_dims = 1)
#> # Individuals: 1, 2, 3
#> # Keypoints: head, neck, shoulder_right, shoulder_left, abdomen, hip_right,
#> # hip_left, knee_right, knee_left, foot_right, foot_left
#> # Sessions: 1
#> # Trials: 1
#> individual keypoint session trial time x confidence
#> <int> <fct> <int> <int> <int> <dbl> <dbl>
#> 1 1 head 1 1 1 0.539 0.861
#> 2 1 head 1 1 2 1.80 0.784
#> 3 1 head 1 1 3 -0.232 0.704
#> 4 1 head 1 1 4 0.758 0.674
#> 5 1 head 1 1 5 0.552 0.846
#> 6 1 head 1 1 6 -0.864 0.516
#> 7 1 head 1 1 7 -0.348 0.849
#> 8 1 head 1 1 8 -1.18 0.840
#> 9 1 head 1 1 9 -2.38 0.529
#> 10 1 head 1 1 10 -0.0452 0.712
#> # ℹ 1,640 more rows
# Create a 3D example
example_anipoint(n_dims = 3)
#> # Individuals: 1, 2, 3
#> # Keypoints: head, neck, shoulder_right, shoulder_left, abdomen, hip_right,
#> # hip_left, knee_right, knee_left, foot_right, foot_left
#> # Sessions: 1
#> # Trials: 1
#> individual keypoint session trial time x y z confidence
#> <int> <fct> <int> <int> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 head 1 1 1 -1.14 1.17 -0.854 0.644
#> 2 1 head 1 1 2 -1.58 -0.398 -0.207 0.544
#> 3 1 head 1 1 3 -1.78 -0.761 0.646 0.855
#> 4 1 head 1 1 4 -1.33 0.0570 -0.830 0.490
#> 5 1 head 1 1 5 0.125 -0.608 0.414 0.952
#> 6 1 head 1 1 6 1.42 -1.15 -1.76 0.826
#> 7 1 head 1 1 7 -3.17 -1.23 1.40 0.944
#> 8 1 head 1 1 8 0.959 0.287 -1.95 0.366
#> 9 1 head 1 1 9 0.231 -0.887 -0.243 0.578
#> 10 1 head 1 1 10 0.0745 -0.696 1.08 0.893
#> # ℹ 1,640 more rows
# Create a smaller example with 2 individuals and 5 keypoints
example_anipoint(n_individuals = 2, n_keypoints = 5)
#> # Individuals: 1, 2
#> # Keypoints: head, neck, shoulder_right, shoulder_left, abdomen
#> # Sessions: 1
#> # Trials: 1
#> individual keypoint session trial time x y confidence
#> <int> <fct> <int> <int> <int> <dbl> <dbl> <dbl>
#> 1 1 head 1 1 1 -0.0613 0.771 0.692
#> 2 1 head 1 1 2 -1.40 -0.267 0.785
#> 3 1 head 1 1 3 1.00 -0.397 0.801
#> 4 1 head 1 1 4 1.26 1.67 0.667
#> 5 1 head 1 1 5 -0.763 -0.357 0.884
#> 6 1 head 1 1 6 0.791 -0.489 0.928
#> 7 1 head 1 1 7 0.181 -0.885 0.663
#> 8 1 head 1 1 8 -0.562 -0.974 0.941
#> 9 1 head 1 1 9 -1.20 -1.13 0.334
#> 10 1 head 1 1 10 -0.338 -1.74 0.897
#> # ℹ 490 more rows
# Create example with multiple trials and sessions
example_anipoint(n_obs = 100, n_trials = 3, n_sessions = 2)
#> # Individuals: 1, 2, 3
#> # Keypoints: head, neck, shoulder_right, shoulder_left, abdomen, hip_right,
#> # hip_left, knee_right, knee_left, foot_right, foot_left
#> # Sessions: 1, 2
#> # Trials: 1, 2, 3
#> individual keypoint session trial time x y confidence
#> <int> <fct> <int> <int> <int> <dbl> <dbl> <dbl>
#> 1 1 head 1 1 1 -0.552 -0.851 0.689
#> 2 1 head 1 1 2 -0.711 1.86 0.866
#> 3 1 head 1 1 3 -1.52 1.24 0.686
#> 4 1 head 1 1 4 0.576 -0.596 0.887
#> 5 1 head 1 1 5 0.775 0.911 0.523
#> 6 1 head 1 1 6 0.0397 -0.266 0.971
#> 7 1 head 1 1 7 1.21 0.318 0.198
#> 8 1 head 1 1 8 0.520 0.378 0.724
#> 9 1 head 1 1 9 0.0752 -0.902 0.661
#> 10 1 head 1 1 10 0.553 1.21 0.608
#> # ℹ 19,790 more rows
# Create minimal example with just centroid in 3D
example_anipoint(n_keypoints = 1, n_dims = 3)
#> # Individuals: 1, 2, 3
#> # Keypoints: centroid
#> # Sessions: 1
#> # Trials: 1
#> individual keypoint session trial time x y z confidence
#> <int> <fct> <int> <int> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 centroid 1 1 1 0.713 0.757 -0.735 0.703
#> 2 1 centroid 1 1 2 1.32 -0.995 1.67 0.468
#> 3 1 centroid 1 1 3 -1.18 -0.549 -0.332 0.658
#> 4 1 centroid 1 1 4 -2.41 -1.51 -0.00790 0.806
#> 5 1 centroid 1 1 5 -0.582 -1.41 0.487 0.858
#> 6 1 centroid 1 1 6 1.74 -1.51 1.62 0.829
#> 7 1 centroid 1 1 7 -0.191 -0.861 0.651 0.889
#> 8 1 centroid 1 1 8 -0.199 2.17 -1.52 0.708
#> 9 1 centroid 1 1 9 0.0163 -0.787 -0.578 0.746
#> 10 1 centroid 1 1 10 -1.65 1.51 -1.48 0.895
#> # ℹ 140 more rows