Data Validation and Preprocessing Functions — validate_melatonin

This file contains functions for validating and preprocessing profile data for analysis. These functions help ensure that profiles meet minimum requirements for rise, length, and ending criteria before proceeding with further analysis.

Arguments

profile: A numeric vector representing the profile data points.
threshold: Numeric value for the minimum rise threshold, default is 2.3.
min_increase_points: Integer specifying the minimum number of consecutive points above the threshold to establish a rise, default is 3.
min_points: Integer specifying the minimum number of data points required for the profile, default is 3.

Value

Depending on the function, returns either a boolean (for validation functions) or a numeric vector (for the processed profile). If criteria are not met, an error message is returned.

Example Usage

profile <- c(1.2, 2.1, 2.4, 2.5, 2.8, 2.9, 1.9, 2.2)

# Check if profile has a significant rise
check_rise_threshold(profile, threshold = 2.3, min_increase_points = 3)

# Check if profile has sufficient data points
check_data_points(profile, min_points = 3)

# Trim nodes below threshold at the end of the profile
trimmed_profile <- trim_end_below_threshold(profile, threshold = 2.3)

# Full preprocessing, with all checks and trimming
processed_profile <- preprocess_profile(profile, threshold = 2.3, min_increase_points = 3, min_points = 3)

Details

Functions included:

check_rise_threshold(): Checks if the profile has a sustained rise above a specified threshold.
check_data_points(): Ensures the profile has a minimum number of data points.
trim_end_below_threshold(): Trims nodes below the threshold at the end of the profile.
preprocess_profile(): Wrapper function that combines all checks and preprocessing steps.