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Analyze the distribution of distances from keypoints to the centroid

Source: R/check_pose.R
check_pose.Rd

This function generates visualizations of the distances from each keypoint to a calculated centroid in the data. By default, it produces histograms of the distance distributions, but it can also create confidence plots if specified.

Usage

check_pose(data, reference_keypoint, type = "histogram")

Arguments

data

A data frame containing at least the columns keypoint, x, and y.

reference_keypoint

The keypoint used as a reference to calculate the distance.

type

Character string specifying the type of plot to create. Options are:

  • "histogram": Histograms of the distance distributions (default)

  • "confidence": Plots showing confidence intervals for the distances

Value

A patchwork object combining plots for each keypoint, visualizing the distances to the centroid.

Details

The centroid is computed using the add_centroid function and distances are calculated with the calculate_distance_to_centroid function. The function automatically excludes the centroid itself from the visualizations. Histograms provide an overview of distance distributions, while confidence plots summarize variability with intervals.

Examples

if (FALSE) { # \dontrun{
# Create sample data
data <- dplyr::tibble(
  keypoint = rep(c("head", "arm", "leg", "torso"), each = 10),
  x = rnorm(40, mean = 0, sd = 1),
  y = rnorm(40, mean = 0, sd = 1)
)

# Plot histogram of distances
check_pose(data, reference_keypoint = "head", type = "histogram")

# Plot confidence intervals
check_pose(data, reference_keypoint = "head", type = "confidence")
} # }