IMPORTANT : The development of this code has been transferred to a new repository JenapyROQ and will continue there. This repository will remain freezed/archived as of 13/10/2022.

PyROQ

This repository implements a streamlined version of the PyROQ code, branched in March 2022 from the main repository. Please cite the PyROQ paper if you use this code in your research.

Installation and usage

Starting from the PyROQ location, the package can be installed using the command:

python setup.py install

Once PyROQ is installed, it is possible to construct an ROQ approximant through a configuration file and running the main routine of the package:

python -m PyROQ --config-file config.ini

The user can see the full list of options at:

python -m PyROQ --help

A simple example can be run by:

python -m PyROQ --config-file config_files/Test_configs/test_config_IMRPv2_GW150914_LVK.ini

Other examples are available in the config_files directory, see the relative README file.

For MPI-based parallelisation, the command should be modified as follows:

mpiexec -n NTASKS python -m PyROQ --config-file config_files/Test_configs/test_config_IMRPv2_GW150914_LVK.ini

Where NTASKS corresponds to the requested number of parallel tasks. Moreover, the config file should specify the related flag parallel=2 for MPI-based parallelisation and n-processes should correspond to NTASKS.

Output

The run directory will automatically contain a copy of the configuration file, git information and the screen output, stored under PyROQ.log.

Preselection basis and related parameters, together with the enriched basis, its related parameters, the basis interpolant and empirical nodes are stored at each step of the enrichment loop under the ROQ_data directory.

Several diagnostic plots (basis parameters, frequency nodes, outliers and error evolution, a single test waveform comparison and validation tests) are stored under the Plots directory.

Algorithm description

MISSING

Dependencies

The package depends on standard Python libraries, except for: numpy for numeric computation, h5py for data storing and matplotlib for plotting. Moreover, if MPI-based parallelisation is requested, the package has an additional dependency on mpi4py.

Development history

SB (sebastiano.bernuzzi@uni-jena.de) 03/2022:

• Forked PyRQO version 0.1.26 repo
• Added support for TEOBResumS GIOTTO and MLW-BNS
• Refactored code
  • Introduced PyROQ class
  • Simplified code/reduced duplication
  • Added waveform wrapper classes
  • Changed parameter management

GC (gregorio.carullo@uni-jena.de) 05/2022:

• Debugged and simplified refactored branch.
• Switched to config file usage.

GC (gregorio.carullo@uni-jena.de) 05/2022:

• Implemented PyROQ algorithm described in PyROQ paper: pre-selection loop and subsequent enrichment cycles.
• Allow user to determine enrichment cycles properties,
• (Almost) maximally streamline code and move logically separated functions to specific files.
• Parallelise linear and quadratic, add more parallelisation steps where possible.
• Improve post-processing and input storage (git info, config file, stdout/stderr).

MB (matteo.breschi@uni-jena.de) 05/2022:

• Introduce logger
• Implement MPI-based parallelisation and unify pool usage
• Extend setup.py, improve packaging and include main functionalities