Generates a synthetic aniframe 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_aniframe(
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 aniframe 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_aniframe()
#> # 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
#> session trial individual keypoint time x y confidence
#> <int> <int> <fct> <fct> <int> <dbl> <dbl> <dbl>
#> 1 1 1 1 head 1 -1.76 0.330 0.847
#> 2 1 1 1 head 2 -0.691 0.173 0.795
#> 3 1 1 1 head 3 -0.559 0.427 0.761
#> 4 1 1 1 head 4 -0.537 -0.814 0.635
#> 5 1 1 1 head 5 0.227 0.651 0.721
#> 6 1 1 1 head 6 0.978 0.920 0.651
#> 7 1 1 1 head 7 -0.209 0.390 0.757
#> 8 1 1 1 head 8 -1.40 0.957 0.675
#> 9 1 1 1 head 9 0.259 -0.170 0.795
#> 10 1 1 1 head 10 -0.442 -0.380 0.732
#> # ℹ 1,640 more rows
# Create a 1D example
example_aniframe(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
#> session trial individual keypoint time x confidence
#> <int> <int> <fct> <fct> <int> <dbl> <dbl>
#> 1 1 1 1 head 1 0.0854 0.932
#> 2 1 1 1 head 2 0.00483 0.714
#> 3 1 1 1 head 3 0.875 0.735
#> 4 1 1 1 head 4 2.53 0.890
#> 5 1 1 1 head 5 0.672 0.921
#> 6 1 1 1 head 6 -0.378 0.843
#> 7 1 1 1 head 7 0.820 0.689
#> 8 1 1 1 head 8 -1.23 0.706
#> 9 1 1 1 head 9 0.853 0.696
#> 10 1 1 1 head 10 -1.40 0.672
#> # ℹ 1,640 more rows
# Create a 3D example
example_aniframe(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
#> session trial individual keypoint time x y z confidence
#> <int> <int> <fct> <fct> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 1 head 1 -0.102 0.442 0.410 0.455
#> 2 1 1 1 head 2 0.904 -0.186 0.816 0.739
#> 3 1 1 1 head 3 1.05 0.541 -1.94 0.706
#> 4 1 1 1 head 4 0.441 -1.65 -1.23 0.700
#> 5 1 1 1 head 5 2.94 0.622 -1.35 0.892
#> 6 1 1 1 head 6 -1.66 -0.323 -1.60 0.576
#> 7 1 1 1 head 7 0.130 0.0668 -1.03 0.588
#> 8 1 1 1 head 8 -0.483 1.05 -0.888 0.919
#> 9 1 1 1 head 9 1.16 1.20 -0.304 0.898
#> 10 1 1 1 head 10 0.689 -0.620 -0.696 0.674
#> # ℹ 1,640 more rows
# Create a smaller example with 2 individuals and 5 keypoints
example_aniframe(n_individuals = 2, n_keypoints = 5)
#> # Individuals: 1, 2
#> # Keypoints: head, neck, shoulder_right, shoulder_left, abdomen
#> # Sessions: 1
#> # Trials: 1
#> session trial individual keypoint time x y confidence
#> <int> <int> <fct> <fct> <int> <dbl> <dbl> <dbl>
#> 1 1 1 1 head 1 -0.734 0.0916 0.789
#> 2 1 1 1 head 2 -0.363 -1.16 0.701
#> 3 1 1 1 head 3 -0.462 0.231 0.794
#> 4 1 1 1 head 4 -1.40 1.08 0.919
#> 5 1 1 1 head 5 1.18 -0.288 0.739
#> 6 1 1 1 head 6 0.699 0.739 0.802
#> 7 1 1 1 head 7 0.104 0.515 0.673
#> 8 1 1 1 head 8 -1.61 0.719 0.771
#> 9 1 1 1 head 9 0.290 -0.797 0.764
#> 10 1 1 1 head 10 1.24 0.577 0.955
#> # ℹ 490 more rows
# Create example with multiple trials and sessions
example_aniframe(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: 2
#> # Trials: 1, 2, 3
#> session trial individual keypoint time x y confidence
#> <int> <int> <fct> <fct> <int> <dbl> <dbl> <dbl>
#> 1 1 1 1 head 1 0.127 0.123 0.697
#> 2 1 1 1 head 2 1.91 -0.585 0.810
#> 3 1 1 1 head 3 0.856 2.41 0.602
#> 4 1 1 1 head 4 -0.777 0.421 0.890
#> 5 1 1 1 head 5 -0.725 -0.408 0.803
#> 6 1 1 1 head 6 -0.584 -0.921 0.509
#> 7 1 1 1 head 7 0.176 2.63 0.656
#> 8 1 1 1 head 8 2.01 1.59 0.372
#> 9 1 1 1 head 9 -0.0628 1.03 0.849
#> 10 1 1 1 head 10 0.0634 -0.366 0.792
#> # ℹ 19,790 more rows
# Create minimal example with just centroid in 3D
example_aniframe(n_keypoints = 1, n_dims = 3)
#> # Individuals: 1, 2, 3
#> # Keypoints: centroid
#> # Sessions: 1
#> # Trials: 1
#> session trial individual keypoint time x y z confidence
#> <int> <int> <fct> <fct> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 1 centroid 1 0.681 -0.293 -0.799 0.775
#> 2 1 1 1 centroid 2 0.346 1.09 0.722 0.897
#> 3 1 1 1 centroid 3 -0.0847 -0.699 0.936 0.468
#> 4 1 1 1 centroid 4 0.557 -1.51 -1.67 0.572
#> 5 1 1 1 centroid 5 0.0176 -0.236 0.260 0.710
#> 6 1 1 1 centroid 6 -0.281 -1.97 -0.274 0.541
#> 7 1 1 1 centroid 7 0.320 1.36 1.27 0.679
#> 8 1 1 1 centroid 8 2.46 1.33 0.389 0.844
#> 9 1 1 1 centroid 9 -0.0933 -0.120 0.419 0.471
#> 10 1 1 1 centroid 10 0.270 0.727 -0.583 0.706
#> # ℹ 140 more rows