#!/usr/bin/env python
# coding: utf-8

# # Extragalactic catalogs: mass relations
# 
# > Notebook owner: Yao-Yuan Mao [@yymao](https://github.com/LSSTDESC/DC2-analysis/issues/new?body=@yymao). Last run: Nov 30, 2018
# 
# In this notebook we demostrate how to plot the halo mass-stellar mass relation and also the BH mass-bulge mass relation for the protoDC2/cosmoDC2 galaxy catalog.
# 
# ## Learning objectives
# - Use `GCRCatalogs` to access the protoDC2 or cosmoDC2 catalogs. 
# - Be able to explore useful quantities using `GCRCatalogs`.
# - Be able to use filters when accessing quantities.

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import GCRCatalogs


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import numpy as np
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')


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gc = GCRCatalogs.load_catalog('cosmoDC2_v1.1.4_small')


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# let's see what masses are availble 
sorted(c for c in gc.list_all_quantities(True) if 'mass' in c.lower())


# ## stellar mass - halo mass relation for low-z central galaxies

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data = gc.get_quantities(['stellar_mass', 'halo_mass'], filters=['redshift < 0.2', 'is_central'])
cs = plt.hexbin(np.log10(data['halo_mass']), np.log10(data['stellar_mass']), cmap='Blues', bins='log');
plt.colorbar(cs, label='log population');
plt.xlabel(r'$\log \, {\rm M}_h \, / \, {\rm M}_\odot$');
plt.ylabel(r'$\log \, {\rm M}_* \, / \, {\rm M}_\odot$');
plt.title(r'$z < 0.2$');


# let's see if the relation changes with redshift

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data = gc.get_quantities(['stellar_mass', 'halo_mass'], filters=['redshift > 0.9', 'redshift < 1', 'is_central'])
cs = plt.hexbin(np.log10(data['halo_mass']), np.log10(data['stellar_mass']), cmap='Blues', bins='log');
plt.colorbar(cs, label='log population');
plt.xlabel(r'$\log \, {\rm M}_h \, / \, {\rm M}_\odot$');
plt.ylabel(r'$\log \, {\rm M}_* \, / \, {\rm M}_\odot$');
plt.title(r'$0.9 < z < 1.0$');


# ## bulge mass - black hole mass relation for low-z central galaxies

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data = gc.get_quantities(['stellar_mass_bulge', 'blackHoleMass'], filters=['redshift < 0.2', 'is_central'])
cs = plt.hexbin(np.log10(data['stellar_mass_bulge']), np.log10(data['blackHoleMass']), cmap='Blues', bins='log');
plt.colorbar(cs, label='log population');
plt.xlabel(r'$\log \, {\rm M}_{\rm bulge} \, / \, {\rm M}_\odot$');
plt.ylabel(r'$\log \, {\rm M}_{\rm BH} \, / \, {\rm M}_\odot$');