Metadata-Version: 2.1
Name: galcv
Version: 1.0.0a2
Summary: A simple calculator for cosmic variance
Home-page: https://github.com/adamtrapp/galcv
Author: Adam Trapp
Author-email: atrapp@astro.ucla.edu
License: MIT
Description: # galcv
        
        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: 23 -> 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 three default parameters (zW, 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.
            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.
        
Keywords: Cosmology Cosmic Variance Galaxies
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering
Requires-Python: ~=3.3
Description-Content-Type: text/markdown
