#!/usr/bin/env python3
"""
Minimal example for reading the record files of this dataset.

The files use the Vital file format. The easiest way to read them is the
open-source `vitaldb` Python package:

    pip install vitaldb

The files can also be opened for visual review with the free Vital Recorder
software (https://vitaldb.net).
"""
import vitaldb

PATH = 'vital/1-1.vital'

# 1. list the tracks stored in the file
vf = vitaldb.VitalFile(PATH)
print('tracks:', vf.get_track_names())
print('length (s):', round(vf.dtend - vf.dtstart))

# 2. read one numeric track, resampled to a fixed 1-second grid.
#    Missing periods are returned as NaN. The output interval is chosen by the
#    user and is not the acquisition rate of the track.
hr = vf.to_numpy(['Infinity/HR'], 1)
print('heart rate samples:', hr.shape)

# 3. read a waveform track at its stored sampling rate (500 Hz here;
#    check track_inventory.csv for the rate of each track in each file)
ecg = vf.to_numpy(['SNUADCM/ECG_II'], 1 / 500)
print('ECG samples:', ecg.shape)

# 4. several tracks on the same time grid
x = vf.to_pandas(['Infinity/HR', 'Infinity/PLETH_SPO2', 'Infinity/ART_MBP'], 1)
print(x.head())

# Notes
# - All timestamps have been shifted so that each case starts at
#   2000-01-01 00:00:00 UTC. Relative timing within a case, including the gaps
#   between files of the same case, is preserved.
# - Not every track is present in every file; see track_inventory.csv.
# - Signals are provided as recorded. No filtering, artifact removal or
#   quality screening has been applied.