### Install Specific Release from Source

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Installs a tagged official release (e.g., v0.7) after cloning the repository. Requires checking out the specific tag before installation.

```bash
git checkout v0.7
pip install .
```

--------------------------------

### Install Master Branch from Source

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Installs the latest development version from the master branch after cloning the repository. Use with awareness that the API may not be stable.

```bash
git checkout master
pip install .
```

--------------------------------

### Install Halotools using Pip

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Alternative installation method using pip. Conda-forge is generally recommended due to its more robust dependency solver.

```bash
pip install halotools
```

--------------------------------

### Build Halotools Documentation with Tox

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/development/getting_started.rst

This command builds the project's documentation using tox. Make sure tox is installed and the documentation environment is set up.

```bash
tox -e build_docs
```

--------------------------------

### Binning Host Halo Masses

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/galcat_analysis/intermediate_examples/quenching_gradient_tutorial.ipynb

Prepares bins and midpoints for analyzing the quiescent fraction as a function of host halo mass. This is a setup step for further analysis.

```python
from scipy.stats import binned_statistic

log_mhost_bins = np.linspace(11, 14.85, 25)
mhost_bins = 10**log_mhost_bins
mhost_mids = 10**(0.5*(log_mhost_bins[:-1]+log_mhost_bins[1:]))

quiescent_fraction1, __, __ = binned_statistic(sats['halo_mvir_host_halo'], 

```

--------------------------------

### Install Halotools using Conda-Forge

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Recommended method for installing the latest release of Halotools. Ensure your environment is activated if using a virtual environment.

```bash
conda install -c conda-forge halotools
```

--------------------------------

### Build Behroozi et al. (2010) Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/behroozi10_composite_model.rst

Instantiate the 'behroozi10' composite subhalo model using the PrebuiltSubhaloModelFactory. This is the basic way to get started with the model.

```python
from halotools.empirical_models import PrebuiltSubhaloModelFactory
model = PrebuiltSubhaloModelFactory('behroozi10')
```

--------------------------------

### Instantiate and Populate Zheng07 Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/zheng07_composite_model.rst

Demonstrates how to create a FakeSim, instantiate the 'zheng07' HOD model, and populate the mock simulation with galaxies. This is a starting point for generating mock galaxy catalogs.

```python
from halotools.sim_manager import FakeSim
halocat = FakeSim()
model = PrebuiltHodModelFactory('zheng07')
model.populate_mock(halocat = halocat)  # doctest: +SKIP
```

--------------------------------

### Building Alternative HOD Model with SubhaloPhaseSpace

Source: https://github.com/astropy/halotools/blob/master/docs/usage_tutorials/empirical_models/subhalo_phase_space/subhalo_phase_space_tutorial.rst

This example demonstrates how to construct an alternative HOD model by replacing the default satellite profile with a SubhaloPhaseSpace model, allowing satellites to be placed on subhalos instead of tracing an NFW profile.

```python
from halotools.empirical_models import PrebuiltHodModelFactory
orig_model = PrebuiltHodModelFactory('leauthaud11')

from halotools.empirical_models import SubhaloPhaseSpace
alt_profile_model = SubhaloPhaseSpace('satellites', np.logspace(10.5, 15.2, 15))

from halotools.empirical_models import HodModelFactory

new_model_dictionary = orig_model.model_dictionary
new_model_dictionary['satellites_profile'] = alt_profile_model
```

--------------------------------

### Install Halotools with Clang Compiler on Mac

Source: https://github.com/astropy/halotools/blob/master/docs/installation_troubleshooting.rst

On Mac, if you encounter issues with the default gcc compiler, try switching to clang for installation. This command temporarily sets the C compiler to clang before installing Halotools.

```bash
export CC=clang; pip install halotools
```

--------------------------------

### Initialize Fake Halo Catalogs

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/catalog_analysis/halocat_analysis/crossmatching_halo_catalogs.rst

Generates two fake halo catalogs using FakeSim and extracts their halo tables. This sets up the data for the cross-matching examples.

```python
from halotools.sim_manager import FakeSim
halocat1 = FakeSim()
halo_table1 = halocat1.halo_table

halocat2 = FakeSim()
mask = halocat2.halo_table['halo_mvir'] > 1e11
halo_table2 = halocat2.halo_table[mask]
```

--------------------------------

### Run Halotools Tests with Tox

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/development/getting_started.rst

Use this command to run the test suite for Halotools. Ensure you have tox installed and configured.

```bash
tox -e test
```

--------------------------------

### Allocate Memory for Galaxy Table

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/hod_mock_factory_source_notes.rst

This snippet shows the initialization of the galaxy_table and the setup of the calling sequence for subsequent mock generation methods within the HodMockFactory.

```python
def allocate_memory(self):

    self.galaxy_table = Table() # ``self`` refers to the ``model.mock`` object
    self._remaining_methods_to_call = copy(self.model._mock_generation_calling_sequence)
```

--------------------------------

### Populate Mock with Hearin et al. (2015) Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/hearin15_composite_model.rst

Populate an N-body simulation with mock galaxy catalogs using the instantiated Hearin et al. (2015) model. This example uses `FakeSim` for demonstration purposes.

```python
from halotools.sim_manager import FakeSim
halocat = FakeSim()
model = PrebuiltHodModelFactory('hearin15')
model.populate_mock(halocat)  # doctest: +SKIP
```

--------------------------------

### Import Libraries and Load Halo Catalog

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/galcat_analysis/intermediate_examples/quenching_gradient_tutorial.ipynb

Imports necessary libraries and loads a cached halo catalog for a specific simulation and redshift. This is the initial setup for data analysis.

```python
%matplotlib inline

import numpy as np 
from matplotlib import pyplot as plt

from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname='bolplanck', redshift=0)
print(halocat.halo_table.keys())
```

--------------------------------

### Setting Up HOD Model Components

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/intrinsic_alignments/measuring_correlations_tutorial.ipynb

Defines and configures the components for a HOD model, including central and satellite galaxy occupation, phase space distribution, and alignment properties. This setup is for a SubhaloAlignment model for satellites.

```python
# MODELS

# Alignment Strengths
satellite_alignment = 0.6
central_alignment = 0.8

# Central galaxy components
cens_occ_model = Zheng07Cens()
cens_prof_model = TrivialPhaseSpace()
cens_orientation_model = CentralAlignment(central_alignment_strength=central_alignment)

# Satellite galaxy Components
sats_occ_model = Zheng07Sats()
prof_args = ("satellites", np.logspace(10.5, 15.2, 15))
sats_prof_model = SubhaloPhaseSpace(*prof_args, inherited_subhalo_props_dict=alignment_inherited_subhalo_props_dict)
sats_orientation_model = SubhaloAlignment(satellite_alignment_strength=satellite_alignment, halocat=halocat)
```

--------------------------------

### Populate Mock with Zu & Mandelbaum et al. (2016) Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/zu_mandelbaum16_composite_model.rst

Populate an N-body simulation with mock galaxy catalogs using the Zu & Mandelbaum et al. (2016) model. This example uses a FakeSim for demonstration purposes.

```python
from halotools.sim_manager import FakeSim
halocat = FakeSim()
model = PrebuiltHodModelFactory('zu_mandelbaum16')
model.populate_mock(halocat)  # doctest: +SKIP
```

--------------------------------

### Instantiate HodMockFactory and Populate Mock

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/hod_mock_factory_source_notes.rst

Demonstrates the common workflow of creating a PrebuiltHodModelFactory, loading a halo catalog, and populating a mock galaxy catalog.

```python
from halotools.empirical_models import PrebuiltHodModelFactory
zheng07_model = PrebuiltHodModelFactory('zheng07')

from halotools.sim_manager import CachedHaloCatalog
default_halocat = CachedHaloCatalog()

zheng07_model.populate_mock(default_halocat)
```

--------------------------------

### Build Documentation Locally

Source: https://github.com/astropy/halotools/wiki/Building-the-documentation

Run this command to build the documentation locally. The `-o` flag will automatically open the documentation in your browser.

```bash
python setup.py build_sphinx -o
```

--------------------------------

### Load Prebuilt Subhalo Model and Halo Catalog

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/galcat_analysis/basic_examples/galaxy_catalog_analysis_tutorial3.ipynb

Initializes a PrebuiltSubhaloModelFactory and loads a CachedHaloCatalog. This is the first step in setting up the mock galaxy population.

```python
from halotools.empirical_models import PrebuiltSubhaloModelFactory
model = PrebuiltSubhaloModelFactory('behroozi10')

from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname='bolshoi', redshift=0, halo_finder='rockstar')
model.populate_mock(halocat)
```

--------------------------------

### Find Halotools Installation Location

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Determine the file path of the active Halotools installation to resolve version conflicts.

```python
import halotools
print(halotools.__file__)
```

--------------------------------

### Generate Mock Galaxy Catalog with Prebuilt Model

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/galcat_analysis/intermediate_examples/galaxy_catalog_intermediate_analysis_tutorial1.ipynb

Initializes a prebuilt subhalo model for generating mock galaxy catalogs. This is the first step in creating a mock universe.

```python
from halotools.empirical_models import PrebuiltSubhaloModelFactory
model = PrebuiltSubhaloModelFactory('smhm_binary_sfr')
```

--------------------------------

### Custom Concentration-Mass Relation Example

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/phase_space_models/nfw_profile_source_notes.rst

Example of how to define and use a custom concentration-mass relation with the NFWPhaseSpace class. This function takes a table and returns a constant concentration value.

```python
def custom_conc_mass(table):
	mass = table['halo_mvir']
	return np.zeros_like(mass) + 5.

nfw_model = NFWPhaseSpace(conc_mass_model=custom_conc_mass)
```

--------------------------------

### Clone Halotools Repository

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Initial step for building Halotools from source. Clones the repository and navigates into the directory.

```bash
git clone https://github.com/astropy/halotools.git
cd halotools
```

--------------------------------

### Minimal HOD Occupation Component Example

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/hod_modeling/writing_your_own_hod_occupation_component.rst

A basic example demonstrating the structure of a custom occupation component. It subclasses `OccupationComponent` and defines a `mean_occupation` method that returns a constant probability.

```python
from halotools.empirical_models import OccupationComponent 

class MyCentralOccupation(OccupationComponent):

	def __init__(self, gal_type, threshold):

		OccupationComponent.__init__(self, 
			gal_type = gal_type, 
			threshold = threshold, 
			upper_occupation_bound = 1)

	def mean_occupation(self, **kwargs):
		table = kwargs['table']
		return np.zeros(len(table)) + 0.1
```

--------------------------------

### Populating Mock Catalogs with a New Model

Source: https://github.com/astropy/halotools/blob/master/docs/usage_tutorials/empirical_models/subhalo_phase_space/subhalo_phase_space_tutorial.rst

Demonstrates how to create a new Halotools composite model and use it to populate a mock catalog. It also shows how to populate a mock catalog with an original model for comparison.

```python
from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname='bolplanck')
new_model.populate_mock(halocat, seed=43)
orig_model.populate_mock(halocat, seed=43)
```

--------------------------------

### Check Halotools Version

Source: https://github.com/astropy/halotools/blob/master/docs/install.rst

Verify the installed version of the Halotools package.

```python
import halotools
print(halotools.__version__)
```

--------------------------------

### Instantiate and Populate Mock Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/mock_observations/mock_obs_pos_formatting.rst

Instantiates a prebuilt subhalo model and populates it with a fake simulation catalog. This sets up the mock object with a galaxy table.

```python
model = PrebuiltSubhaloModelFactory('smhm_binary_sfr')
from halotools.sim_manager import FakeSim
halocat = FakeSim()
model.populate_mock(halocat)
```

--------------------------------

### Example of _galprop_dtypes_to_allocate usage

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/model_factory_composite_sequence_mechanisms.rst

Instances of your model component must have a `_galprop_dtypes_to_allocate` attribute. Assign any `numpy.dtype` object to this attribute during the `__init__` constructor.

```python
import numpy as np

class MyComponent:
    def __init__(self, **kwargs):
        # ... other initialization
        self._galprop_dtypes_to_allocate = np.dtype(float) # or any other numpy dtype
        # ... rest of initialization
```

--------------------------------

### Modify Model Parameters

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/zheng07_composite_model.rst

Alter model parameters after instantiation by modifying the param_dict. This example changes the minimum halo mass for hosting a central galaxy.

```python
model.param_dict['logMmin'] = 12.5
```

--------------------------------

### Instantiate and Populate Subhalo Mock

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/subhalo_mock_factory_source_notes.rst

Demonstrates the common usage pattern for creating a SubhaloMockFactory instance and populating it with mock galaxies using a pre-built model and a cached halo catalog.

```python
from halotools.empirical_models import PrebuiltSubhaloModelFactory
behroozi10_model = PrebuiltSubhaloModelFactory('behroozi10')

from halotools.sim_manager import CachedHaloCatalog
default_halocat = CachedHaloCatalog()

behroozi10_model.populate_mock(default_halocat)
```

--------------------------------

### Create and Populate HodModelFactory

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/intrinsic_alignments/measuring_correlations_tutorial.ipynb

Initializes a HodModelFactory with specified occupation and profile models, then populates the mock galaxy catalog.

```python
model_instance = HodModelFactory(centrals_occupation = cens_occ_model,
                                     centrals_profile = cens_prof_model,
                                     satellites_occupation = sats_occ_model,
                                     satellites_profile = sats_prof_model,
                                     centrals_orientation = cens_orientation_model,
                                     satellites_orientation = sats_orientation_model,
                                     model_feature_calling_sequence = (
                                     'centrals_occupation',
                                     'centrals_profile',
                                     'satellites_occupation',
                                     'satellites_profile',
                                     'centrals_orientation',
                                     'satellites_orientation')
                                    )

#seed=132358712
seed=None
model_instance.populate_mock(halocat, seed=seed)
```

--------------------------------

### Create a Mock Galaxy Population

Source: https://github.com/astropy/halotools/blob/master/README.rst

This snippet demonstrates how to select a pre-built HOD model and a halo catalog, then populate the catalog with a mock galaxy population.

```python
from halotools.empirical_models import PrebuiltHodModelFactory
model = PrebuiltHodModelFactory('zheng07')

from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname='bolshoi', redshift=0, halo_finder='rockstar')

model.populate_mock(halocat)
```

--------------------------------

### Modify Cacciato et al. (2009) Model Parameter

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/cacciato09_composite_model.rst

Change model parameters after instantiation by modifying the 'param_dict'. This example changes the scatter in the mass-to-light ratio.

```python
model.param_dict['sigma'] = 0.2
```

--------------------------------

### Initialize DownloadManager

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/quickstart_guides/working_with_halotools_provided_catalogs.rst

Import and instantiate the DownloadManager class to manage catalog downloads.

```python
from halotools.sim_manager import DownloadManager
dman = DownloadManager()
```

--------------------------------

### Define a custom central occupation model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/hod_modeling/zheng07_using_cenocc_model_tutorial.rst

Create a new OccupationComponent subclass for central galaxies. This example defines a trivial model with a single parameter 'new_cen_param'.

```python
from halotools.empirical_models import OccupationComponent
class MyCenModel(OccupationComponent):

    def __init__(self, threshold):
        OccupationComponent.__init__(self, gal_type='centrals',
        				threshold=threshold, upper_occupation_bound=1.)

        self.param_dict['new_cen_param'] = 0.5

    def mean_occupation(self, **kwargs):
    	halo_table = kwargs['table']
    	result = np.zeros(len(halo_table)) + self.param_dict['new_cen_param']
        return result
```

--------------------------------

### Build Documentation Locally (Offline)

Source: https://github.com/astropy/halotools/wiki/Building-the-documentation

Use this command to build the documentation when an internet connection is unavailable. The `-o` flag will automatically open the documentation in your browser.

```bash
python setup.py --offline build_sphinx -o
```

--------------------------------

### Instantiate Pre-built HOD Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/getting_started_overview.rst

Shows how to instantiate a pre-built HOD model factory for galaxy-halo connection studies.

```python
from halotools.empirical_models import PrebuiltHodModelFactory
zheng07_model = PrebuiltHodModelFactory('zheng07', threshold = -19.5, redshift = 0.5)
```

--------------------------------

### Load Halo Catalog and Get Properties

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/cam_tutorial_pages/cam_tutorial.rst

Loads the CachedHaloCatalog for a specific simulation and redshift, then extracts halo mass and accretion rate. Requires halotools library.

```python
from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname='bolplanck', redshift=0)
halo_mass = halocat.halo_table['halo_mvir']
from halotools.empirical_models import Behroozi10SmHm
model = Behroozi10SmHm(redshift=0)
halo_mstar = model.mc_stellar_mass(prim_haloprop=halo_mass)
halo_acc_rate = halocat.halo_table['halo_dmvir_dt_100myr']
```

--------------------------------

### Command-line Download Script Usage

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/quickstart_guides/working_with_halotools_provided_catalogs.rst

Illustrates how to use the command-line script for downloading halo catalogs. Use the --help flag to see the full argument list.

```bash
python scripts/download_additional_halocat.py --help
```

--------------------------------

### Initialize Mock Galaxy Catalog

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/galcat_analysis/basic_examples/galaxy_catalog_analysis_tutorial4.ipynb

Loads a pre-built HOD model and a cached halo catalog to populate a mock galaxy population. Requires `PrebuiltHodModelFactory` and `CachedHaloCatalog`.

```python
from halotools.empirical_models import PrebuiltHodModelFactory
model = PrebuiltHodModelFactory('tinker13', threshold = 10.25)

from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname='bolshoi', redshift=0, halo_finder='rockstar')

model.populate_mock(halocat)
```

--------------------------------

### Example Usage of Leauthaud11 Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/leauthaud11_composite_model.rst

This snippet demonstrates how to use the Leauthaud11 composite model to infer halo mass from stellar mass. Ensure the model is properly instantiated before use.

```python
>>> inferred_log_halo_mass = model.mean_log_halo_mass_centrals(log_stellar_mass)
```

--------------------------------

### Populate Mock with Halo Catalog

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/getting_started_overview.rst

Populates a pre-built galaxy-halo model with data from a halo catalog.

```python
zheng07_model.populate_mock(halocat) # doctest: +SKIP
```

--------------------------------

### Composing Models with a New Component

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/subhalo_modeling/subhalo_modeling_tutorial4.rst

Incorporate a new component model into a composite model using SubhaloModelFactory. This example shows how to add a 'shape' component to an existing 'behroozi10' model.

```python
galaxy_shape = Shape('halo_mvir')
from halotools.empirical_models import PrebuiltSubhaloModelFactory, SubhaloModelFactory
behroozi_model = PrebuiltSubhaloModelFactory('behroozi10')
new_model = SubhaloModelFactory(baseline_model_instance = behroozi_model, 
    shape = galaxy_shape)
```

--------------------------------

### Populating Alternative Halo Catalog with HodModelFactory

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/hod_model_factory_source_notes.rst

Illustrates how to populate a specific, alternative halo catalog using the populate_mock method. This can be used with any instance of CachedHaloCatalog or UserSuppliedHaloCatalog.

```python
from halotools.sim_manager import CachedHaloCatalog
my_halocat = CachedHaloCatalog(simname = my_simname, redshift = my_redshift)
model.populate_mock(my_halocat)
```

--------------------------------

### Modify Leauthaud et al. (2011) Model Parameters

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/leauthaud11_composite_model.rst

Change model parameters after instantiation by modifying the 'param_dict'. This example changes the power law slope for satellite occupation number.

```python
model.param_dict['alphasat'] = 1.1
```

--------------------------------

### Generate Mock Galaxy Catalog

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/catalog_analysis/galcat_analysis/basic_examples/clustering_examples/galaxy_catalog_analysis_tutorial9.rst

Initializes a mock galaxy catalog using a prebuilt model and a cached halo catalog. Requires Halotools library.

```python
from halotools.empirical_models import PrebuiltSubhaloModelFactory
model = PrebuiltSubhaloModelFactory('behroozi10')

from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname = 'bolshoi', redshift=0)
model.populate_mock(halocat)
```

--------------------------------

### Initialize Occupation and Bookkeeping Dictionaries

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/hod_mock_factory_source_notes.rst

This code initializes dictionaries to store galaxy occupation numbers, total abundances, and indices for different galaxy types. This setup is crucial before calling the `mc_occupation_` methods.

```python
self._occupation = {}
self._total_abundance = {}
self._gal_type_indices = {}

first_galaxy_index = 0
for gal_type in self.gal_types:
    occupation_func_name = 'mc_occupation_'+gal_type
    occupation_func = getattr(self.model, occupation_func_name)
    # Call the component model to get a Monte Carlo
    # realization of the abundance of gal_type galaxies
    self._occupation[gal_type] = occupation_func(table=self.halo_table)

    # Now use the above result to set up the indexing scheme
    self._total_abundance[gal_type] = (
        self._occupation[gal_type].sum()
        )
    last_galaxy_index = first_galaxy_index + self._total_abundance[gal_type]
    # Build a bookkeeping device to keep track of
    # which array elements pertain to which gal_type.
    self._gal_type_indices[gal_type] = slice(
        first_galaxy_index, last_galaxy_index)
    first_galaxy_index = last_galaxy_index
    # Remove the mc_occupation function from the list of methods to call
    self._remaining_methods_to_call.remove(occupation_func_name)
    self.additional_haloprops.append('halo_num_'+gal_type)
```

--------------------------------

### Create and Populate Mock Galaxy Catalog with IA

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/intrinsic_alignments/hod_modeling_tutorial_with_alignments.ipynb

Instantiates the HodModelFactory with the previously defined galaxy components, ensuring the IA strength model precedes the orientation model. Then, populates the mock galaxy catalog with the specified Halotools halo catalog and an optional seed for reproducibility.

```python
# Initially create the mock with SubhaloAlignment to overwrite the host information with subhalo
model_instance = HodModelFactory(centrals_occupation = cens_occ_model,
                                     centrals_profile = cens_prof_model,
                                     satellites_occupation = sats_occ_model,
                                     satellites_profile = sats_prof_model,
                                     satellites_radial_alignment_strength = sats_strength_model,
                                     centrals_orientation = cens_orientation_model,
                                     satellites_orientation = sats_orientation_model,
                                     model_feature_calling_sequence = (
                                     'centrals_occupation',
                                     'centrals_profile',
                                     'satellites_occupation',
                                     'satellites_profile',
                                     'satellites_radial_alignment_strength',
                                     'centrals_orientation',
                                     'satellites_orientation')
                                    )

#seed=132358712
seed=None
model_instance.populate_mock(halocat, seed=seed)
```

--------------------------------

### Access Analytical Relations in Behroozi et al. (2010) Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/behroozi10_composite_model.rst

Access the underlying analytical relations of the 'behroozi10' model, such as the stellar-to-halo mass relation. This example demonstrates generating halo masses for analysis.

```python
import numpy as np
halo_mass = np.logspace(11, 15, 100)
```

--------------------------------

### Example of new_haloprop_func_dict usage

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/model_factory_composite_sequence_mechanisms.rst

To use the `new_haloprop_func_dict` mechanism, create this attribute in your component model's `__init__` constructor. The dictionary keys are new column names, and values are functions that accept and return length-Nhalos arrays.

```python
class MyComponent:
    def __init__(self, **kwargs):
        # ... other initialization
        self.new_haloprop_func_dict = {
            "my_new_halo_property": my_halo_property_func
        }
        # ... rest of initialization

def my_halo_property_func(table):
    # Calculate and return a length-Nhalos array
    return calculated_array
```

--------------------------------

### Populate Default Halo Catalog with SubhaloModelFactory

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/subhalo_model_factory_source_notes.rst

Instantiate a SubhaloModelFactory and use its `populate_mock` method to populate the default halo catalog. Ensure `CachedHaloCatalog` is imported.

```python
model = SubhaloModelFactory(**model_dictionary)
from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog()
model.populate_mock(halocat)
```

--------------------------------

### Download Initial Halo Catalog

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/getting_started_overview.rst

Execute the download script to obtain the default halo catalog. This script sets up the cache directory and downloads the catalog to the default location.

```bash
$ download_initial_halocat.py -h
```

--------------------------------

### Instantiate HaloMassInterpolQuenching Models

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/hod_modeling/hod_modeling_tutorial2.rst

Initializes HaloMassInterpolQuenching models for both satellites and centrals, specifying halo mass control points and corresponding quiescent fractions.

```python
from halotools.empirical_models import HaloMassInterpolQuenching
sat_quenching = HaloMassInterpolQuenching('halo_mvir', 
	[1e12, 1e13, 1e14, 1e15], [0.35, 0.5, 0.6, 0.9], 
	gal_type = 'satellites')
cen_quenching = HaloMassInterpolQuenching('halo_mvir', 
	[1e12, 1e15], [0.25, 0.95], 
	gal_type = 'centrals')
```

--------------------------------

### Create Fake Subhalo Data

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/merger_tree_analysis_example.rst

Generates sample `astropy.table.Table` objects for subhalos at two different snapshots, including halo IDs, descendant IDs, and halo masses. This setup is necessary for demonstrating merger tree analysis.

```python
from astropy.table import Table
import numpy as np

subhalos_z0 = Table()
num_subhalos_z0 = 47893
subhalos_z0['halo_id'] = np.arange(num_subhalos_z0).astype('i8')

subhalos_z1 = Table()
num_subhalos_z1 = 58105
subhalos_z1['halo_id'] = np.arange(num_subhalos_z0, num_subhalos_z0+num_subhalos_z1).astype('i8')
subhalos_z1['desc_id'] = np.random.randint(0, 2*num_subhalos_z0, num_subhalos_z1)
subhalos_z1['halo_mass'] = np.random.uniform(1e10, 1e15, num_subhalos_z1)
```

--------------------------------

### Instantiate Zheng07 HOD Model and Populate Mock

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/hod_modeling/hod_modeling_tutorial1.rst

This snippet shows how to instantiate the Zheng07 HOD model by combining occupation and profile models for centrals and satellites, and then populates a mock galaxy catalog using the composite model instance.

```python
from halotools.empirical_models import HodModelFactory

from halotools.empirical_models import TrivialPhaseSpace, Zheng07Cens
cens_occ_model =  Zheng07Cens()
cens_prof_model = TrivialPhaseSpace()

from halotools.empirical_models import NFWPhaseSpace, Zheng07Sats
sats_occ_model =  Zheng07Sats()
sats_prof_model = NFWPhaseSpace()

model_instance = HodModelFactory(
	centrals_occupation = cens_occ_model, 
	centrals_profile = cens_prof_model, 
	satellites_occupation = sats_occ_model, 
	satellites_profile = sats_prof_model)

# The model_instance is a composite model 
# All composite models can directly populate N-body simulations 
# with mock galaxy catalogs using the populate_mock method:

from halotools.sim_manager import FakeSim
halocat = FakeSim()
model_instance.populate_mock(halocat)

# Setting simname to 'fake' populates a mock into a fake halo catalog 
# that is generated on-the-fly, but you can use the populate_mock 
# method with any Halotools-formatted catalog 

```

--------------------------------

### Instantiate Hearin et al. (2015) Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/preloaded_models/hearin15_composite_model.rst

Build an instance of the Hearin et al. (2015) composite HOD model using the `PrebuiltHodModelFactory`. This is the standard way to create the model for use in simulations.

```python
from halotools.empirical_models import PrebuiltHodModelFactory
model = PrebuiltHodModelFactory('hearin15')
```

--------------------------------

### Generate Monte Carlo Realization of Galaxy Population

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/cam_tutorial_pages/cam_tutorial.rst

Creates a Monte Carlo realization of a galaxy population with stellar mass and star formation rate (SFR). This example demonstrates generating random variables and interpolating to define means for a normal distribution.

```python
import numpy as np
ngals = int(1e4)
log_mstar = np.random.uniform(10, 12, ngals)
galaxy_mstar = 10**log_mstar
mean_log_sfr = np.interp(log_mstar, [10, 11, 12], [0, 1, 2])
log_sfr = np.random.normal(loc=mean_log_sfr, scale=0.2, size=ngals)
galaxy_sfr = 10**log_sfr
```

--------------------------------

### Load Halo Catalog and Populate Mock

Source: https://github.com/astropy/halotools/blob/master/docs/notebooks/galcat_analysis/intermediate_examples/galaxy_catalog_intermediate_analysis_tutorial1.ipynb

Loads a cached halo catalog for a specific simulation and redshift, then populates the previously defined mock model with this catalog.

```python
from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname = 'bolshoi', redshift = 0, halo_finder = 'rockstar')

model.populate_mock(halocat)
```

--------------------------------

### Download Alternate Halo Catalogs

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/getting_started_overview.rst

Use the download script to fetch alternative halo catalogs, specifying simulation name, halo finder, version, and redshift. The --help flag provides usage information.

```bash
$ download_additional_halocat.py multidark rockstar most_recent 0.5
```

```bash
$ download_alternate_halocats.py --help
```

--------------------------------

### Custom Satellite Occupation Component

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/hod_modeling/writing_your_own_hod_occupation_component.rst

Defines a custom satellite occupation component with a non-standard mc_occupation method. This example overrides the default behavior to model a scenario where a halo has either 0 or 5 satellites, useful for studying occupation statistics beyond nearest-integer or Poisson distributions.

```python
from halotools.empirical_models import OccupationComponent 

class MySatelliteOccupation(OccupationComponent):

	def __init__(self, threshold):

		OccupationComponent.__init__(self, 
			gal_type = 'satellites',
			threshold = threshold,
			upper_occupation_bound = 5)

	def mean_occupation(self, **kwargs):
		table = kwargs['table']
		return np.zeros(len(table)) + 2.5

	def mc_occupation(self, **kwargs):
		table = kwargs['table']
		meanocc = self.mean_occupation(**kwargs)
		result = np.where(meanocc < 2.5, 0, 5)
		table['halo_num_satellites'] = result
		return result
```

--------------------------------

### Initialize Galaxy Positions and Velocities

Source: https://github.com/astropy/halotools/blob/master/docs/source_notes/empirical_models/factories/hod_mock_factory_source_notes.rst

Initializes the host-centric positions and velocities of galaxies to match their host halo's properties. This is a preliminary step before detailed intra-halo distribution modeling.

```python
    self.galaxy_table['x'] = self.galaxy_table['halo_x']
    self.galaxy_table['y'] = self.galaxy_table['halo_y']
    self.galaxy_table['z'] = self.galaxy_table['halo_z']
    self.galaxy_table['vx'] = self.galaxy_table['halo_vx']
    self.galaxy_table['vy'] = self.galaxy_table['halo_vy']
    self.galaxy_table['vz'] = self.galaxy_table['halo_vz']
```

--------------------------------

### Instantiate and Populate Subhalo Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/subhalo_modeling/subhalo_modeling_tutorial1.rst

This snippet demonstrates instantiating a Behroozi10SmHm model, creating a SubhaloModelFactory with a custom nickname for stellar mass, and populating a mock galaxy population using a CachedHaloCatalog. It then prints the first 5 rows of the resulting galaxy table.

```python
sm_model =  Behroozi10SmHm(redshift = 0)
model_instance = SubhaloModelFactory(mstar = sm_model)
from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname = 'bolshoi')
model_instance.populate_mock(halocat)
print(model_instance.mock.galaxy_table[0:5])
```

--------------------------------

### Build and Populate a Composite HOD Model

Source: https://github.com/astropy/halotools/blob/master/docs/quickstart_and_tutorials/tutorials/model_building/composing_models/hod_modeling/hod_modeling_tutorial3.rst

Instantiate custom component models for different galaxy types (centrals, satellites), then use HodModelFactory to combine them with a pre-built HOD model. Finally, populate a mock catalog using the new composite model.

```python
cen_size = Size('centrals')
sat_size = Size('satellites')
from halotools.empirical_models import PrebuiltHodModelFactory, HodModelFactory
zheng_model = PrebuiltHodModelFactory('zheng07')
new_model = HodModelFactory(baseline_model_instance = zheng_model, centrals_size = cen_size, satellites_size = sat_size)

# Your new model can generate a mock in the same way as always
from halotools.sim_manager import CachedHaloCatalog
halocat = CachedHaloCatalog(simname = 'bolshoi')
new_model.populate_mock(halocat)
```