Circadian Rest-Activity Rhythm Analysis // Quantifies the circadian rest-activity rhythm, the roughly 24-hour cycle of activity and rest, from activity counts and raw accelerometer recordings. Analyses run on an activity-count vector and its timestamps, and a built-in reader loads 'ActiGraph' '.agd' files (an 'SQLite' database) directly. Computes nonparametric metrics (interdaily stability (IS) and intradaily variability (IV) following Witting et al. (1990) doi:10.1016/0006-3223(90)90523-5; relative amplitude (RA), the least-active 5-hour window (L5), and the most-active 10-hour window (M10) following Van Someren et al. (1999) doi:10.3109/07420529908998724), cosinor models with a rhythmicity test, confidence ellipses, population-mean cosinor, and two-group parameter comparison (Cornelissen (2014) doi:10.1186/1742-4682-11-16; Marler et al. (2006) doi:10.1002/sim.2466), period estimation by Lomb-Scargle (Lomb (1976) doi:10.1007/BF00648343; Scargle (1982) doi:10.1086/160554) and chi-square (Sokolove and Bushell (1978) doi:10.1016/0022-5193(78)90022-X) periodograms with bootstrap confidence intervals and a sliding-window spectrogram, fractal and nonlinear measures (Peng et al. (1994) doi:10.1103/PhysRevE.49.1685; Kantelhardt et al. (2002) doi:10.1016/S0378-4371(02)01383-3), the Sleep Regularity Index (Phillips et al. (2017) doi:10.1038/s41598-017-03171-4), social jet lag, rest-activity state transitions, and locomotor inactivity during sleep (Winnebeck et al. (2018) doi:10.1016/j.cub.2017.11.063). It also reads raw accelerometer files ('ActiGraph' '.gt3x', 'Axivity' '.cwa', 'GENEActiv' '.bin'), auto-calibrates them (van Hees et al. (2014) doi:10.1152/japplphysiol.00421.2014), and derives the ENMO, MAD, and z-angle metrics with diary-free sleep-period detection (van Hees et al. (2018) doi:10.1038/s41598-018-31266-z), cross- checked against 'GGIR'. A batch mode runs the analysis over a folder of files and writes a multi-sheet 'Excel' workbook.