A simple calculator for cosmic variance
Project description
galcv
WARNING: This package is still in its alpha stage
This package provides predictions of cosmic variance for the high-z UV luminosity function (UVLF) of galaxies. The methods for this code are described in Trapp & Furlanetto (2020, in prep.).
This package provides the relative cosmic variance of the UVLF for the following parameter ranges:
Apparent rest-UV AB magnitude: 22 -> 34
Redshift: 5 -> 15
Survey Area (sqr arcmin): 1 -> 31640
Note: Cosmic variance is not available for all combinations of these parameters, even within these ranges. This occurs most often at the lowest survey areas and brightest apparent magnitudes. The code will print a warning if this is the case.
Installation and Use
The simplest way to install and use galcv
is through 'pip' in a python environment:
> pip install galcv
The package can then be imported in any python environment or in a script using:
> import galcv
There is currently one user-facing function: getcv()
. The rest of the functions are intended for internal use. Example use:
> galcv.getcv(mag=[30,29,28], area=100, z=9)
> [0.178, 0.208, 0.245]
getcv()
takes three required parameters (mag, area, z), and has four default parameters (zW, appOrAbs, CMF_method, interpWarning). The following is the docstring for getcv()
that explains the inputs and output:
This function returns relative cosmic variance results. This function is a wrapper function for formatting. The actual calculation happens in singlecv()
Parameters
-------------------------
mag : int, float, list, or numpy.ndarray
The magnitude(s) to consider. This must be in APPARENT rest-UV (1500 - 2800 Angstroms) AB magnitude
area : int or float
The area of a survey in arcmin^2 (square survey pattern only)
z : int or float
The central redshift of the survey
zW : int or float
The width of the redshift bin the survey is considering. Default is 1.
appOrAbs: 'apparent' or 'absolute'
Whether the mag input(s) are in apparent magnitudes or in absolute magnitudes
CMF_method: 'nu-scaling' or 'PS-scaling'
The method used for generating the conditional mass function. See Trapp & Furlanetto (2020) for details.
interpWarning: int or float
Flag for displaying interpolation warning message. 0 for no message, 1 for short message (Default), 2 for long message
Returns
-------------------------
A Python list of cosmic variance values of the same length as the mag input
Alternate Installation and Use Methods
If 'pip' is not working, or you would prefer to run the code yourself, you may clone the github repo and run the __init__.py script (in the /galcv folder) in a python environment. You will then have access to the getcv()
function.
In fact, all the code needs to run is the __init__.py script along with all of the .pkl files that are in the /galcv folder.
If you would like to use the getcv()
function in your script (without installing it with pip and importing it), you may do the following:
- Copy the __init__.py file into the same directory as your script
- Also copy all of the .pkl files from the /galcv folder to that same directory
- At the beginning of your script, include the line:
from __init__ import *
- You should then be able to use
getcv()
in that script.
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