| Name | echo21 JSON |
| Version |
2.0.1
JSON |
| download |
| home_page | None |
| Summary | Exploring the Cosmos with Hydrogen Observation |
| upload_time | 2025-08-05 12:46:23 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License
Copyright (c) 2025 Shikhar Mittal
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
21-cm
cosmology
global signal
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
numpy
scipy
colossus
mpi4py
pybaselines
requests
tqdm
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
Basics
======
Overview
--------
:Name: Exploring Cosmos with Hydrogen Observation
:Author: `Shikhar Mittal <https://sites.google.com/view/shikharmittal/home>`_
:Paper: `Mittal et al (2025) <https://arxiv.org/abs/2503.11762>`_
:Documentation: `echo21.readthedocs.io <https://echo21.readthedocs.io/en/latest/index.html>`_
Why do you need this code?
--------------------------
Use this code to generate the global 21-cm signal(s) for a given set of astrophysical and cosmological parameters.
Read more about it in the paper `Mittal et al (2025) <https://arxiv.org/abs/2503.11762>`_.
Installation and requirements
-----------------------------
This package can be installed as
.. code:: bash
pip install echo21
We recommend working on a Python version > 3.8. Packages required are
- `numpy <https://pypi.org/project/numpy/>`_ (recommended version 2.1.3)
- `scipy <https://pypi.org/project/scipy/>`_ (recommended version 1.14.1)
- `mpi4py <https://pypi.org/project/mpi4py/>`_ (recommended version 4.0.1)
- `tqdm <https://pypi.org/project/tqdm/>`_ (recommended version 4.67.1)
- `colossus <https://pypi.org/project/colossus/>`_ (recommended version 1.3.6)
- `pybaselines <https://pypi.org/project/pybaselines/>`_ (recommended version 1.1.0)
Quick start
-----------
The following code more or less captures the main functionalities of this package.
.. code:: python
from echo21 import echopipeline
pipe = echopipeline.pipeline()
pipe.glob_sig()
Save the above code as (say) ``my_echo_script.py`` and run it as
.. code:: bash
python my_echo_script.py
Running the above will generate an output folder with the name `output_<YYYYMMDD-hhmmss>` which contains several files. To learn how to set the astrophysical or cosmological parameters, halo mass function, star formation model, redshifts at which to evaluate the global signal, and structure of the output files see the documentation. To learn about the physics of this package see our `paper <https://arxiv.org/abs/2503.11762>`_.
Once you have an understanding of the structure of output files, you can write your own scripts to create figures. To help you get started, see the jupyter notebook `make_figures.ipynb` in the example folder.
Documentation
-------------
For more details on the working of the package and understanding the output files refer to the
`documentation <https://echo21.readthedocs.io/en/latest/index.html>`_.
License and citation
--------------------
The software is free to use on the MIT open-source license. If you use the software then please consider citing `Mittal et al (2025) <https://arxiv.org/abs/2503.11762>`_.
Acknowledgement
---------------
I thank Prakhar Bansal for help with development of the IDM model. I also thank Girish Kulkarni, Peter Sims, and Vikram Rentala for helpful comments and feedback during the development of this code.
Contact
-------
In case of any confusion or suggestions for improvement please do not hesitate to contact me.
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