pycocosn (the package formerly known as 'pycoco')

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v0.9.0

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This is the development repo for the python frontend for the core-collapse SNe template code 'CoCo': https://github.com/UoS-SNe/CoCo (my fork is currently https://github.com/RobFirth/CoCo).

CoCo was originally started by Natasha Karpenka, and is currently being updated and maintained by S. Prajs (https://github.com/SzymonPrajs).

A paper, Firth et. al. 2017, is currently in prep.

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• renamed to pycocosn

• Extending templates now possible with Black Body spectrum, flat and linear

• calling CoCo (or reproduced CoCo functions) now more straightforward

• Added more test cases to test_pycoco

• Travis-CI implemented and Master and dev are passing

• Dependancies now handled in setup.py

• Calling all parts of CoCo from pycoco now operational

• Migrated to better, and clearer code structure and sub-modules

• Mangling now done within python, rather than C++ in CoCo

• File I/O and interaction with CoCo LCfit output now operational - 11/01/17

• Usage of a SN class now solid

• Implementing calls to CoCo LCfit now

• Calls to CoCo specfit now implemented

• Mangling now stable

• Adding tools for calculating magnitude offsets to make it easier to import new data

• regeneration of filter list file now possible

• added colours and bandpasses for LSST filters

• Less dependence on environment variables

• installation through setup.py now possible

• better handing of CoCo sim outputs

• SN position and mu now stored in infofile ./testdata/info/info.dat

• dark sky calculations and integration with LSST Throughputs now done

• Improved stability

• input from astropy tables now more straightforward - better integration with coco.simulate

• can now batch fit light curves and spectra from within python

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To install, run:

git clone https://github.com/RobFirth/verbose-enigma.git

then:

cd verbose-enigma
python setup.py install --user

(The --user argument only installs current user only, omitting flag will install for all users on the system if there are appropriate permissions)

NOTE: make sure that the python used to install is the one that you will use with pycoco

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Ideally set the following environment variables:

COCO_ROOT_DIR (my default is ~/Code/CoCo/) PYCOCO_FILTER_DIR(my default is ~/Code/CoCo/data/filters/) PYCOCO_DATA_DIR (my default is ~/Code/CoCo/data/) SFD_DIR (my default is ~/data/Dust/sfddata-master/; see below) LSST_THROUGHPUTS (my default is ${HOME}/projects/LSST/throughputs) LSST_THROUGHPUTS_BASELINE (my default is ${LSST_THROUGHPUTS}/baseline)

also pycoco/ and CoCo need to be in your path and pythonpath, i.e.:

setenv PATH /Users/berto/Code/pycoco/:$PATH

setenv PYTHONPATH "/Users/berto/Code/pycoco/:$PYTHONPATH

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Requirements

python packages

• matplotlib
• numpy
• scipy
• astropy
• lmfit
• sfdmap (https://github.com/kbarbary/sfdmap)

additionally

• lsst throughputs (https://github.com/lsst/throughputs; $LSST_THROUGHPUTS points to this directory)

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for sfdmap, the environment variable SFD_DIR needs to point at the path to the parent directory of the appropriate dust map files. See the installation instructions here: https://github.com/kbarbary/sfdmap

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