tintervals

A python package collecting functions and tools to work with time intervals and to convert time data.

The package also provides utilities for handling optical link data developed for the EMPIR project ROCIT and for the European Partnership on Metrology Project TOCK..

Development is available at

• https://github.com/INRIM/tintervals
• https://gitlab.ininrim.it/m.pizzocaro/tintervals (INRIM only)

Documentation is available at https://tintervals.readthedocs.io

Package is available at https://pypi.org/project/tintervals/

Installation

The package can be installed using pip:

pip install tintervals

or directly from github:

pip install git+https://github.com/INRIM/tintervals.git

Requirements

• numpy, scipy
• ciso8601 (for fast ISO format reading)

Basic usage

import tintervals as ti

Functions to convert timetag formats. Fast functions used as converters when importing files:

Starred inputs (*), if naive are considered as system/local time. K+K format is always naive and interpreted as sytem/local time. ISO format can be read with microseconds but it is printed without. Conversion from Epoch time (Unix) and MJD is done by simple affine function, as both are aligned with UTC and basically ignore leap seconds.

Vectorized functions:

Functions to manipulate array of timetags or array of start/stop intervals:

Functions to calculate deadtime uncertainty:

Advanced usage

For handling optical links:

pip install "tintervals[rocitlinks]"

import tintervals.rocitlinks as rl

See the docs for more details.

Extra dependencies:

• pandas (used only for fast file loading)
• pyyaml

License

MIT

Acknowledgments

This work is partially funded by the European Metrology Program for Innovation and Research (EMPIR) project 18SIB05 ROCIT. The EMPIR initiative is cofunded by the European Union’s Horizon 2020 research and innovation programme and the EMPIR Participating States.

This work was supported by the projects 22IEM01 TOCK and 25IEM09 Arcsecond. The projects 22IEM01 TOCK and 25IEM09 Arcsecond has received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.

Authors

(c) 2021-2026 Marco Pizzocaro - Istituto Nazionale di Ricerca Metrologica (INRIM)

Speed test

ti.kk2iso('210922*161141.810')
166 ns ± 2.09 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
ti.kk2epoch('210922*161141.810')
658 ns ± 1.24 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
ti.iso2datetime('20210922T161141.810Z')
222 ns ± 18 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
ti.iso2epoch('20210922T161141.810Z')
473 ns ± 5.11 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
ti.datetime2iso(datetime(2021,9,22,11,12,tzinfo=timezone.utc))
2.51 µs ± 9.92 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
ti.datetime2epoch(datetime(2021,9,22,11,12,tzinfo=timezone.utc))
613 ns ± 3.99 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
ti.epoch2datetime(1632319901)
406 ns ± 2.87 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)
ti.mjd_from_epoch(1632319901)
131 ns ± 0.334 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
ti.epoch_from_mjd(59479.356)
99.4 ns ± 0.228 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
ti.iso_from_epoch(1632319901)
19.8 µs ± 86.8 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
ti.iso_from_mjd(59479.356)
23 µs ± 266 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)