EAZY

(Exported from code.google.com/p/eazy-photoz, April 20, 2015.)

EAZY is a photometric redshift code designed to produce high-quality redshifts for situations where complete spectroscopic calibration samples are not available. Details of the algorithm and tests of the code on public multi-wavelength photometric datasets are presented by Brammer, van Dokkum & Coppi (2008).

Please include a citation to "Brammer, van Dokkum & Coppi, 2008, ApJ, 686, 1503" in the bibliography of any published work that makes use of EAZY.

For a summary of recent changes see also Updates.md.

Installation and download

In the terminal:

### If you have the Github SSH key enabled
git clone [email protected]:gbrammer/eazy-photoz.git eazy-photoz

### Otherwise just use https
git clone https://github.com/gbrammer/eazy-photoz.git eazy-photoz

cd eazy-photoz/src
make

Run the example HDF-N catalog Fernandez-Soto et al. 1999:

cd ../inputs
mkdir OUTPUT
../src/eazy # generates param file
../src/eazy -p zphot.param.default

To get updates to the repository committed since you checked out the code:

cd [path-to-eazy-photoz]
git pull

Python helpers

Some scripts to interact with the EAZY input/outputs are available in the threedhst module, specifically eazyPy.

doc/PythonDemo/eazy.py

"""
Demo of the Eazy python helpers in threedhst/eazyPy

https://github.com/gbrammer/threedhst/blob/master/eazyPy.py

"""
import os
import matplotlib.pyplot as plt
import threedhst.eazyPy as eazy

################################################
#### z_phot vs z_spec
################################################
eazy.zPhot_zSpec('OUTPUT/photz.zout')
plt.savefig('zphot_zspec.png'); plt.close()

################################################
#### Example object.  `idx` is zero-indexed
################################################
axes = eazy.plotExampleSED(idx=17, writePNG=False, MAIN_OUTPUT_FILE='photz',
                           OUTPUT_DIRECTORY='OUTPUT', CACHE_FILE='Same', lrange=[3800, 3.e4],
                           axes=None, individual_templates=True, fnu=False)
                           
plt.savefig('eazy_fit.png'); plt.close()

################################################
#### Pull out data from the BINARY_OUTPUTS files
################################################

## SED, data & fit
sed = eazy.getEazySED(17, MAIN_OUTPUT_FILE='photz', OUTPUT_DIRECTORY='./OUTPUT',
                      CACHE_FILE='Same', scale_flambda=True, verbose=False,
                      individual_templates=False)

lambdaz, temp_sed, lci, obs_sed, fobs, efobs = sed
axes[0].scatter(lci, obs_sed, color='orange', zorder=2)
axes[0].scatter(lci, fobs, color='green', marker='s', s=150, zorder=2)

## p(z)
zgrid, pzi, prior = eazy.getEazyPz(17, MAIN_OUTPUT_FILE='photz', OUTPUT_DIRECTORY='./OUTPUT',
                                   CACHE_FILE='Same', binaries=None, get_prior=True)
                                   
axes[1].plot(zgrid, pzi, color='black')
axes[1].plot(zgrid, prior/prior.max()*pzi.max(), color='purple')
plt.savefig('eazy_fit_2.png')

################################################
#### Investigate template fit residuals for zeropoints
################################################
eazy.show_fit_residuals(root='photz', PATH='./OUTPUT/', savefig='fit_residuals.png', adjust_zeropoints='zphot.zeropoint', fix_filter=None, ref_filter=28, get_resid=False, wclip=[1200, 30000.0])

## Run again using the zphot.zeropoint file you just made, this can be done iteratively
params = eazy.EazyParam('zphot.param.default')
params['GET_ZP_OFFSETS'] = 'y'
params.write('zphot.param')
os.system('../src/eazy -p zphot.param -z zphot.zeropoint')

## Check z_phot vs z_spec again.  Improves though modificaton was done with *all* objects in the 
## catalog, not just (biased) subsample with z_spec.
eazy.zPhot_zSpec('OUTPUT/photz.zout')
plt.savefig('zphot_zspec_2.png'); plt.close()