Metadata-Version: 2.4
Name: BCemu
Version: 1.1.3
Summary: Using emulators to implement baryonic effects.
Home-page: https://github.com/sambit-giri/BCemu.git
Author: Sambit Giri
Author-email: sambit.giri@gmail.com
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cython
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: astropy
Requires-Dist: scikit-learn
Requires-Dist: smt==1.0.0
Requires-Dist: wget
Requires-Dist: pandas
Requires-Dist: importlib-resources
Requires-Dist: pytest
Requires-Dist: nose
Dynamic: author
Dynamic: author-email
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Dynamic: home-page
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# BCemu

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[![PyPI version](https://badge.fury.io/py/BCemu.svg)](https://badge.fury.io/py/BCemu)

A Python package for modelling baryonic effects in cosmological simulations.

## Package details

The package provides emulators to model the suppression in the power spectrum due to baryonic feedback processes. These emulators are based on the baryonification model ([Schneider et al. 2019](#1)), where gravity-only *N*-body simulation results are manipulated to include the impact of baryonic feedback processes. For a detailed description, see [Giri & Schneider (2021)](#2).

## INSTALLATION

One can install a stable version of this package using pip by running the following command::

    pip install BCemu

In order to use the latest version, one can clone this package running the following::

    git clone https://github.com/sambit-giri/BCemu.git

To install the package in the standard location, run the following in the root directory::

    python setup.py install

In order to install it in a separate directory::

    python setup.py install --home=directory

One can also install it using pip by running the following command::

    pip install git+https://github.com/sambit-giri/BCemu.git

The dependencies should be installed automatically during the installation process. If they fail, you can install them manually before installing BCemu. The list of required packages can be found in the requirements.txt file in the root directory.

### Tests

For testing, one can use [pytest](https://docs.pytest.org/en/stable/) or [nosetests](https://nose.readthedocs.io/en/latest/). Both packages can be installed using pip. To run all the test script, run either of the following::

    python -m pytest tests
    
	nosetests -v

## 📖 Citation

If you use `BCemu` in your research, please cite the following paper:

> Giri, S. K., & Schneider, A. (2021). Emulation of baryonic effects on the matter power spectrum and constraints from galaxy cluster data. Journal of Cosmology and Astroparticle Physics, 2021(12), 046. 
> [https://doi.org/10.1088/1475-7516/2021/12/046](https://doi.org/10.1088/1475-7516/2021/12/046)

BibTeX entries:
```bibtex
@article{giri2021emulation,
  title={Emulation of baryonic effects on the matter power spectrum and constraints from galaxy cluster data},
  author={Giri, Sambit K and Schneider, Aurel},
  journal={Journal of Cosmology and Astroparticle Physics},
  volume={2021},
  number={12},
  pages={046},
  year={2021},
  publisher={IOP Publishing}
}
```

## USAGE

Script to get the baryonic power suppression.

```python
import numpy as np 
import matplotlib.pyplot as plt
import BCemu

bfcemu = BCemu.BCM_7param(Ob=0.05, Om=0.27)
bcmdict = {'log10Mc': 13.32,
           'mu'     : 0.93,
           'thej'   : 4.235,  
           'gamma'  : 2.25,
           'delta'  : 6.40,
           'eta'    : 0.15,
           'deta'   : 0.14,
           }

z = 0
k_eval = 10**np.linspace(-1,1.08,50)
p_eval = bfcemu.get_boost(z, bcmdict, k_eval)

plt.semilogx(k_eval, p_eval, c='C0', lw=3)
plt.axis([1e-1,12,0.73,1.04])
plt.yticks(fontsize=14)
plt.xticks(fontsize=14)
plt.xlabel(r'$k$ (h/Mpc)', fontsize=14)
plt.ylabel(r'$\frac{P_{\rm DM+baryon}}{P_{\rm DM}}$', fontsize=21)
plt.tight_layout()
plt.show()

```

<img src="images/Sk_z0_7param.png" width="400">

The package also has a three-parameter baryonification model. Model A assumes all three parameters to be independent of redshift while model B assumes the parameters to be redshift-dependent via the following form: 

![](https://latex.codecogs.com/svg.latex?\inline&space;X(z)&space;=&space;X_0(1&plus;z)^{-\nu}).

Below an example fit to the BAHAMAS simulation result is shown.

```python
import numpy as np 
import matplotlib.pyplot as plt
import BCemu
import pickle

BAH = pickle.load(open('examples/BAHAMAS_data.pkl', 'rb'))

bfcemu = BCemu.BCM_3param(Ob=0.0463, Om=0.2793)
bcmdict = {'log10Mc': 13.25, 
           'thej'   : 4.711,  
           'deta'   : 0.097}

zs = [0,0.5]
k_eval  = 10**np.linspace(-1,1.08,50)
p0_eval1 = bfcemu.get_boost(zs[0], bcmdict, k_eval)
p1_eval1 = bfcemu.get_boost(zs[1], bcmdict, k_eval)

bfcemu = BCemu.BCM_3param(Ob=0.0463, Om=0.2793)
bcmdict = {'log10Mc': 13.25, 
           'thej'   : 4.711,  
           'deta'   : 0.097,
           'nu_Mc'  : 0.038,
           'nu_thej': 0.0,
           'nu_deta': 0.060}

zs = [0,0.5]
k_eval  = 10**np.linspace(-1,1.08,50)
p0_eval2 = bfcemu.get_boost(zs[0], bcmdict, k_eval)
p1_eval2 = bfcemu.get_boost(zs[1], bcmdict, k_eval)

plt.figure(figsize=(10,4.5))
plt.subplot(121); plt.title('z=0')
plt.semilogx(BAH['z=0']['k'], BAH['z=0']['S'], '-', c='k', lw=5, alpha=0.2, label='BAHAMAS')
plt.semilogx(k_eval, p0_eval1, c='C0', lw=3, label='A', ls='--')
plt.semilogx(k_eval, p0_eval1, c='C2', lw=3, label='B', ls=':')
plt.axis([1e-1,12,0.73,1.04])
plt.yticks(fontsize=14)
plt.xticks(fontsize=14)
plt.legend()
plt.xlabel(r'$k$ (h/Mpc)', fontsize=14)
plt.ylabel(r'$\frac{P_{\rm DM+baryon}}{P_{\rm DM}}$', fontsize=21)
plt.subplot(122); plt.title('z=0.5')
plt.semilogx(BAH['z=0.5']['k'], BAH['z=0.5']['S'], '-', c='k', lw=5, alpha=0.2, label='BAHAMAS')
plt.semilogx(k_eval, p1_eval1, c='C0', lw=3, label='A', ls='--')
plt.semilogx(k_eval, p1_eval2, c='C2', lw=3, label='B', ls=':')
plt.axis([1e-1,12,0.73,1.04])
plt.yticks(fontsize=14)
plt.xticks(fontsize=14)
plt.xlabel(r'$k$ (h/Mpc)', fontsize=14)
plt.ylabel(r'$\frac{P_{\rm DM+baryon}}{P_{\rm DM}}$', fontsize=21)
plt.tight_layout()
plt.show()



```

<img src="images/Sk_3param_multiz.png" width="800">


## CONTRIBUTING

If you find any bugs or unexpected behaviour in the code, please feel free to open a [Github issue](https://github.com/sambit-giri/BCMemu/issues). The issue page is also good if you seek help or have suggestions for us. 

## References
<a id="1">[1]</a> 
Schneider, A., Teyssier, R., Stadel, J., Chisari, N. E., Le Brun, A. M., Amara, A., & Refregier, A. (2019). Quantifying baryon effects on the matter power spectrum and the weak lensing shear correlation. Journal of Cosmology and Astroparticle Physics, 2019(03), 020. [arXiv:1810.08629](https://arxiv.org/abs/1810.08629).

<a id="2">[2]</a> 
Giri, S. K. & Schneider, A. (2021). Emulation of baryonic effects on the matter power spectrum and constraints from galaxy cluster data. Journal of Cosmology and Astroparticle Physics, 2021(12), 046. [arXiv:2108.08863](https://arxiv.org/abs/2108.08863).

