orderfast: Fast Ordering Function

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

Fast Ordering Function

Description

Orders a dataframe by id and time columns efficiently using base R's order. Optimized for large CGM datasets, it returns the input with rows sorted by subject then timestamp while preserving all columns.

Orders a dataframe by id and time columns

Usage

orderfast(df)

Arguments

df	A dataframe with 'id' and 'time' columns

Value

A dataframe ordered by id and time

A dataframe ordered by id and time

Examples

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

# Shuffle without replacement, then order and compare to baseline
set.seed(123)
shuffled <- example_data_5_subject[sample(seq_len(nrow(example_data_5_subject)),
                                          replace = FALSE), ]
baseline <- orderfast(example_data_5_subject)
ordered_shuffled <- orderfast(shuffled)

# Compare results
print(paste("Identical after ordering:", identical(baseline, ordered_shuffled)))
head(baseline[, c("id", "time", "gl")])
head(ordered_shuffled[, c("id", "time", "gl")])

# Order larger dataset
ordered_large <- orderfast(example_data_hall)
print(paste("Ordered", nrow(ordered_large), "rows in larger dataset"))
df <- data.frame(id = c("b", "a", "a"), time = as.POSIXct(
  c("2024-01-01 01:00:00", "2024-01-01 00:00:00", "2024-01-01 01:00:00"), tz = "UTC"
))
orderfast(df)

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