start_finder: Find Start Points for Event Analysis

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

Find Start Points for Event Analysis

Description

Finds R-based (1-indexed) positions where the value is 1 in an integer vector of 0s and 1s, specifically identifying episode start points. This function looks for positions where a 1 follows a 0 or is at the beginning of the vector, which is useful for identifying the start of glycemic events or episodes.

Usage

start_finder(df)

Arguments

df	A dataframe with the first column containing an integer vector of 0s and 1s

Value

A tibble containing start_indices with R-based (1-indexed) positions where episodes start Note: These indices refer to positions in the provided input vector/dataframe, not necessarily rows of the original CGM df unless that vector was derived directly from df in row order.

Notes

- Returns R-based start_indices positions relative to the provided input vector/dataframe. - If used on vectors derived from a CGM df, indices map directly to df rows.

See Also

grid, mod_grid

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

Examples

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

# Create a binary vector indicating episode starts
binary_vector <- c(0, 0, 1, 1, 0, 1, 0, 0, 1, 1)
df <- data.frame(episode_starts = binary_vector)

# Find R-based indices where episodes start
start_points <- start_finder(df)
print(paste("Start indices:", paste(start_points$start_indices, collapse = ", ")))

# Use with actual GRID results
grid_result <- grid(example_data_5_subject, gap = 15, threshold = 130)
grid_starts <- start_finder(grid_result$grid_vector)
print(paste("GRID episode starts:", length(grid_starts$start_indices)))

# Analysis on larger dataset
large_grid <- grid(example_data_hall, gap = 15, threshold = 130)
large_starts <- start_finder(large_grid$grid_vector)
print(paste("GRID episode starts in larger dataset:", length(large_starts$start_indices)))

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