A halo mass function calculator
Project description
The halo mass function calculator.
hmf is a python application that provides a flexible and simple way to calculate the Halo Mass Function for a range of varying parameters. It is also the backend to HMFcalc, the online HMF calculator.
Full Documentation
Features
Calculate mass functions and related quantities extremely easily.
Very simple to start using, but wide-ranging flexibility.
Caching system for optimal parameter updates, for efficient iteration over parameter space.
Support for all LambdaCDM cosmologies.
Focus on flexibility in models. Each “Component”, such as fitting functions, filter functions, growth factor models and transfer function fits are implemented as generic classes that can easily be altered by the user without touching the source code.
Focus on simplicity in frameworks. Each “Framework” mixes available “Components” to derive useful quantities – all given as attributes of the Framework.
Comprehensive in terms of output quantities: access differential and cumulative mass functions, mass variance, effective spectral index, growth rate, cosmographic functions and more.
Comprehensive in terms of implemented Component models:
5+ models of transfer functions including directly from CAMB
4 filter functions
20 hmf fitting functions
Includes models for Warm Dark Matter
Nonlinear power spectra via HALOFIT
Functions for sampling the mass function.
CLI scripts both for producing any quantity included, or fitting any quantity.
Python 2 and 3 compatible
Note
From v3.1, hmf supports Python 3.6+, and has dropped support for Python 2.
Quickstart
Once you have hmf installed, you can quickly generate a mass function by opening an interpreter (e.g. IPython/Jupyter) and doing:
>>> from hmf import MassFunction >>> hmf = MassFunction() >>> mass_func = hmf.dndlnm
Note that all parameters have (what I consider reasonable) defaults. In particular, this will return a Tinker (2008) mass function between 10^10 and 10^15 solar masses, at z=0 for the default PLANCK15 cosmology. Nevertheless, there are several parameters which can be input, either cosmological or otherwise. The best way to see these is to do:
>>> MassFunction.parameter_info()
We can also check which parameters have been set in our “default” instance:
>>> hmf.parameter_values
To change the parameters (cosmological or otherwise), one should use the update() method, if a MassFunction() object already exists. For example:
>>> hmf = MassFunction()
>>> hmf.update(cosmo_params={"Ob0": 0.05}, z=10) #update baryon density and redshift
>>> cumulative_mass_func = hmf.ngtm
For a more involved introduction to hmf, check out the tutorials, which are currently under construction, or the API docs.
Versioning
From v3.1.0, hmf will be using strict semantic versioning, such that increases in the major version have potential API breaking changes, minor versions introduce new features, and patch versions fix bugs and other non-breaking internal changes.
If your package depends on hmf, set the dependent version like this:
hmf>=3.1<4.0
Attribution
Please cite Murray, Power and Robotham (2013) and/or https://ascl.net/1412.006 (whichever is more appropriate) if you find this code useful in your research. Please also consider starring the GitHub repository.
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