Usage¶
Can I get to documents working?
fsps-age.py – Estimates the age of a Photometric SED using FSPS.
- Science goal:
- Check local environment effects on SNIa by looking for correlations between HR and the age of the local environment calculated from SDSS Scene Modeling Photometry
- Usage:
- fspsage.py burnin OBJID fspsage.py run DATASET JOBID JOBLENGTH [-d | –debug] fspsage.py (-h | –help) fspsage.py –version
- Option:
- burnin run a shorter run on specific objects only OBJID the SN (or Messier) ID of the object to observe run estimate age for a given data set DATASET analyses circle, messier, gupta, campbell, campbellG, and riess data sets JOBID the ID for the piece of the data set to be analyzed JOBLENGTH the total number of objects looked at -d –debug run shorter and with more logs -h –help show this screen –version show version
- Benjamin Rose
- brose3@nd.edu
- benjamin.rose@me.com
- University of Notre Dame
- 2017-01-19
- Python 3.5
-
fspsage.
burnin
(cli)[source]¶ Runs a smaller emcee.sampler to see how the sampling is progressing. Hopefully these values will not effect how it samples, but it will likely effect how well it sampled.
-
fspsage.
calculateAge
(SNID)[source]¶ # Get MCMC running and be able to calculate an age with uncertainties.
-
fspsage.
redoGupta
(cli)[source]¶ # Test on global SED’s
We want to redo what Gupta did to make sure we can actually do something before we analyze on new data.
Parameters: cli – The dictionary of the CLI constructed by :docop:.
burnin¶
## run
currently only runs global tests (on SN hosts analsyied by Gupta 2011 or some Messier galaxies). Also runs a circle test.
### Circle
The goal of this is to test the MCMC run. We can put in some star formation parameters into FSPS and get out some magnitudes, can fsps-age properly use MCMC to retrieve these star formation parameters?
Using the stellar popultion [used in the analsysis](https://github.com/benjaminrose/SNIa-Local-Environments/blob/3ee9b1f508c2583bcd8a314827ab7c0497526f93/calculateAge.py#L293), I was able to get a set of SED’s. The resulting “data” can be found as [circlePhotometry.tsv](https://github.com/benjaminrose/SNIa-Local-Environments/blob/master/data/circlePhotometry.tsv). The details of its creation are below.
We used the operation in [the code](https://github.com/benjaminrose/SNIa-Local-Environments/blob/3ee9b1f508c2583bcd8a314827ab7c0497526f93/calculateAge.py#L84) of dust1 = 2.0*dust2.
We choose our redshift to be 0.05 resulting in the age of emission being 13.18 Gyr using the [standard cosmology](https://github.com/benjaminrose/SNIa-Local-Environments/blob/3ee9b1f508c2583bcd8a314827ab7c0497526f93/calculateAge.py#L43).
ID | comment | log(z_sol) | tau_dust | tau | t_start | t_transition | m_sf —|------------------|————|----------|—–|---------|————–|——- 1 | old w/ metals | -0.5 | 0.1 | 0.5 | 1.5 | 9.0 | -1.0 2 | old & young | -0.5 | 0.1 | 0.5 | 1.5 | 9.0 | 15.0 3 | young & younger | -0.5 | 0.1 | 7.0 | 3.0 | 10 | 15.0 4 | young | -0.5 | 0.1 | 7.0 | 3.0 | 13 | 0 5 | old & metal poor | -1.5 | 0.1 | 0.5 | 1.5 | 9.0 | -1.0 6 | young & dusty | -0.5 | 0.8 | 7.0 | 3.0 | 10 | 15.0
ID | comment | u - g | u | g | r | i | z —|------------------|——–|-------|——-|-------|——-|——- 1 | old w/ metals | 1.60 | 45.36 | 43.76 | 42.99 | 42.67 | 42.39 2 | old & young | 1.57 | 45.31 | 43.74 | 42.98 | 42.66 | 42.39 3 | young & younger | 0.72 | 41.15 | 40.43 | 40.40 | 40.19 | 40.21 4 | young | 0.91 | 42.65 | 41.74 | 41.49 | 41.26 | 41.16 5 | old & metal poor | 1.40 | 44.69 | 43.29 | 42.70 | 42.45 | 42.29 6 | young & dusty | 1.08 | 42.66 | 41.58 | 41.25 | 41.01 | 40.86
Adding a c = -25 we get the SED’s in [circlePhotometry.tsv](https://github.com/benjaminrose/SNIa-Local-Environments/blob/master/data/circlePhotometry.tsv).