find_min_before_hours: Find Minimum Glucose Before Specified Hours

In cgmguru: Advanced Continuous Glucose Monitoring Analysis with High-Performance C++ Backend

Find Minimum Glucose Before Specified Hours

Description

Identifies the minimum glucose value occurring within a specified time window before a given start point. This function is useful for analyzing glucose patterns preceding specific events or time points.

Usage

find_min_before_hours(df, start_point_df, hours)

Arguments

df	A dataframe containing continuous glucose monitoring (CGM) data. Must include columns: id: Subject identifier (string or factor) time: Time of measurement (POSIXct) gl: Glucose value (integer or numeric, mg/dL)
start_point_df	A dataframe with column start_indices (R-based indices into df)
hours	Number of hours to look back from the start point

Value

A list containing:

• min_indices: Tibble with R-based (1-indexed) row numbers of minimum glucose (min_indices). The corresponding occurrence time is df$time[min_indices] and glucose is df$gl[min_indices].

• episode_counts: Tibble with episode counts per subject (id, episode_counts)

• episode_start: Tibble with all episode starts with columns:

  • id: Subject identifier

  • time: Timestamp at which the minimum occurs; equivalent to df$time[indices]

  • gl: Glucose value at the minimum; equivalent to df$gl[indices]

  • indices: R-based (1-indexed) row number(s) in df denoting where the minimum occurs

See Also

mod_grid, find_local_maxima

Other GRID pipeline: detect_between_maxima(), find_local_maxima(), find_max_after_hours(), find_max_before_hours(), find_min_after_hours(), find_new_maxima(), grid(), maxima_grid(), mod_grid(), start_finder(), transform_df()

Examples

# Load sample data
library(iglu)
data(example_data_5_subject)
data(example_data_hall)

# Create start points for demonstration (using row indices)
start_indices <- seq(1, nrow(example_data_5_subject), by = 100)
start_points <- data.frame(start_indices = start_indices)

# Find minimum glucose in previous 2 hours
min_before <- find_min_before_hours(example_data_5_subject, start_points, hours = 2)
print(paste("Found", length(min_before$min_indices), "minimum points"))

# Find minimum glucose in previous 1 hour
min_before_1h <- find_min_before_hours(example_data_5_subject, start_points, hours = 1)

# Analysis on larger dataset
large_start_indices <- seq(1, nrow(example_data_hall), by = 200)
large_start_points <- data.frame(start_indices = large_start_indices)
large_min_before <- find_min_before_hours(example_data_hall, large_start_points, hours = 2)
print(paste("Found", length(large_min_before$min_indices), "minimum points in larger dataset"))

cgmguru documentation built on Nov. 6, 2025, 1:07 a.m.