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hod 1.1.2

A HOD calculator built on hmf

Latest Version: 1.1.6

Readme for hod

hod is a python application that provides a flexible and simple interface for dealing with the Halo Model of Dark Matter Halos. It comes with several HOD models, halo density profiles, bias models and Mass Function models (through the hmf package, by the same people).

For a given choice of parameters (for each of the above models), it can calculate the large-scale structure correlation function. There is also a module which enables fitting the correlation function model to data via MCMC.

It includes some parallelisation capabilities also (which are necessary for the MCMC fitting for more than a couple of parameters).

INSTALLATION

The only tricky part of the installation should be installing pycamb. See notes in the readme of hmf. You will also need a fortran compiler. Once hmf is installed properly, simply use pip install hod.

USAGE

hod can be used interactively (for instance in ipython) or in a script. To use interactively, in ipython do something like the following:

>>> from hod import HOD
>>> h = HOD()
>>> galcorr = h.corr_gal
>>> bias = h.bias.bias
>>> ...

All parameters to HOD() have defaults so none must be specified. There are quite a few that CAN be specified however. Check the docstring to see the details. Furthermore, as hod extends the functionality of hmf, almost all parameters accepted by hmf.Perturbations() can be used (check its docstring). The exception is cut_fit, which is necessarily set to False in hod.

To change the parameters (cosmological or otherwise), one should use the update() method, if a HOD() object already exists. For example

>>> h = HOD()
>>> h.update(r=np.linspace(0.1,1,1000)) #update scale vector
>>> corr_2h = h.corr_gal_2h #The 2-halo term of the galaxy correlation function

One can access any of the properties of the Perturbations() class for the given parameters through the pert attribute of HOD:

>>> h = HOD()
>>> mass_variance = h.pert.sigma
>>> mass_function = h.pert.dndlnm

HISTORY

1.1.2 - December 10, 2013
A few bugfixes to match the slightly modified API of hmf v1.2.x
1.1.1 - December 6, 2013
Bugfixes to fit_hod() routine
1.1.0 - December 5, 2013
Added multivariate guassian priors Updated to reflect changes in hmf API
1.0.0 - November 22, 2013
MCMC routines now work properly -- all basic routines are in place.
0.7.0 - October 16, 2013
Added ability to get HOD, cosmo params from given xi(r) data using mcmc
0.6.1 - October 10, 2013
Added schneider halo_exclusion option
0.6.0 - October 4, 2013
Added halo exclusion options (Most Buggy) Added scale-dependent bias Added lower mvir bound on 1h term Fixed nonlinear P(k)
0.5.1 - October 2, 2013
Added nonlinear P(k) option
0.5.0 - October 2, 2013
First working version
 
File Type Py Version Uploaded on Size
hod-1.1.2-py2.7-macosx-10.5-x86_64.egg (md5) Python Egg 2.7 2013-12-10 68KB
hod-1.1.2.tar.gz (md5) Source 2013-12-10 16KB
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