lcsim

Blazar light curve simulation package in python3

https://github.com/skiehl/lcsim

Science Score: 44.0%

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    Low similarity (13.3%) to scientific vocabulary

Keywords

astrophysics blazar light-curve simulation stochastic-processes time-series
Last synced: 6 months ago · JSON representation ·

Repository

Blazar light curve simulation package in python3

Basic Info
  • Host: GitHub
  • Owner: skiehl
  • License: bsd-3-clause
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 2.14 MB
Statistics
  • Stars: 6
  • Watchers: 1
  • Forks: 4
  • Open Issues: 2
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Topics
astrophysics blazar light-curve simulation stochastic-processes time-series
Created about 6 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

ascl:2310.002

lcsim

A python3 package to create artificial blazar light curves with a predefined power spectral density (PSD) and probability density function (PDF).

Requirements

The lcsim script uses the following standard python packages:

  • copy
  • math

The lcsim script uses the following python packages:

  • numpy
  • scipy
  • statsmodels

The simdb script uses the following standard python packages:

  • os
  • sys

The simdb script uses the following python packages:

  • numpy
  • sqlite3

Getting Started

Get the python scripts:

$ git clone https://github.com/skiehl/lcsim.git

Open the jupyter notebook SimulationDemo.ipynb for a demonstation of the code. Either use jupyter lab:

$ jupyter lab

Or jupyter notebook:

$ jupyter notebook SimulationDemo.ipynb

Modules

  • lcsim.py: The main module for simulating light curves.
  • simdb.py: A SQLite3-based database backend to store simulations.
  • run_lcsim.py: A wrapper script to run and save light curve simulations for multiple sources.

Usage

Usage of the package is demonstrated in the jupyter notebook SimulationDemo.ipynb

Note: Documentation of the simdb.py module is not yet included.

A complete code documentation is given in html/.

Citation

Bibtex:

@MISC{2023ascl.soft10002K, author = {{Kiehlmann}, Sebastian}, title = "{lcsim: Light curve simulation code}", keywords = {Software}, howpublished = {Astrophysics Source Code Library, record ascl:2310.002}, year = 2023, month = oct, eid = {ascl:2310.002}, pages = {ascl:2310.002}, archivePrefix = {ascl}, eprint = {2310.002}, adsurl = {https://ui.adsabs.harvard.edu/abs/2023ascl.soft10002K}, adsnote = {Provided by the SAO/NASA Astrophysics Data System} }

This software package is indexed on ASCL and ADS.

License

lcsim is licensed under the BSD 3-Clause License - see the LICENSE file.

References

Timmer&Koenig, 1995. Emmanoulopoulos et al., 2013.

Alternatives

At least on other python implementations of the Emmanoulopoulos+ method is available:

Owner

  • Name: Dr. Sebastian Kiehlmann
  • Login: skiehl
  • Kind: user

Citation (CITATION.cff)

cff-version: 1.1.0
message: "Please cite the following works when using this software: https://ui.adsabs.harvard.edu/abs/2023ascl.soft10002K"
authors:
- family-names: Kiehlmann
  given-names: Sebastian
  orcid: "https://orcid.org/0000-0001-6314-9177"
title: "lcsim: Light curve simulation code"
version: 0
date-released:  2020-01-24
identifiers:
 - type: "ascl-id"
   value: "2310.002"
 - type: "bibcode"
   value: "2023ascl.soft10002K"
abstract: "lcsim creates artificial light curves using two algorithms. The first simulates Gaussian distributed light curves following a specific power spectral density (PSD) freely selectable by the user. The second algorithm simulates light curves following a specific PSD and matching a specific probability density function (PDF). The package provides methods to resample the simulated light curves and add "observational" noise. Furthermore, the package provides an interface to a SQLite3-based database to store and access the simulations."

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