Python toolbox for the analysis of time series and terrestrial reference frames

Copyright IGN France. Licensed under MIT license, see LICENSE.md.

Table of Contents

1. Installation
   1. Requirements
   2. Clone the repository
   3. Install pytrf
   4. Update with latest version
2. Documentation
   1. Training slides
   2. API documentation
   3. Complete documentation
3. Getting started
   1. Time series analysis examples
   2. SINEX combination examples
4. How to cite

• python3. See installation instructions.
• pip. See installation instructions.
• git. See installation instructions.

• Create a github account if you don't already have one.

• Create a personal access token for your github account. Copy-paste your token value somewhere.

• Open a terminal and clone the repository with the following command.
  IMPORTANT: you will be asked to enter your github username and password. The password is your token, not your usual github password.

  git clone https://github.com/IGNF/pytrf

• A pytrf directory should have been created in the current directory. Run:

  cd pytrf

• If you work with a package manager, e.g., conda, you may want to create and activate a specific environment for pytrf.

• Within the pytrf directory, run one of the two following commands. Use the -e option if you plan on coding within pytrf — you won't need to reinstall it after every change.

  Note: This will automatically install the missing required packages.

  Note: Don't miss the dot . at the end of both commands.

  pip install .

  OR

  pip install -e .

• Open a python interpreter and try to import pytrf.

  >>> import pytrf

  You should hopefully be able to import the library without any error.

• This may be a good time for you to set the 3-character name of your institution/agency as you would like it to appear in the SINEX files produced by pytrf, e.g.:

  >>> pytrf.config.set_agency('ROB')

Within the pytrf directory, run:

git pull

Then re-install pytrf.

The slides used for the latest training session to pytrf are available here.

Recordings of the training session are available upon request.

You can generate API documentation about pytrf modules and functions by running:

pdoc --html pytrf

in the pytrf directory. This should create a pytrf/html directory with the API documentation.

Available soon.

Different usage examples are provided in the examples directory.

• Reading GNSS station position time series in different formats
• Modeling of a GNSS station position time series
• Modeling of a GNSS station position time series with post-seismic deformation
• Automatic offset detection in a GNSS station position time series
• Automatic modeling of a GPS satellite z-PCO time series
• Simulation and Wiener filtering

• Combination of daily IGS AC solutions
• Weekly combination of daily IGS solutions
• Long-term stacking of daily IGS solutions

Please use the reference provided by GitHub's "Cite this repository" button.