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test_config_gsobject.py
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test_config_gsobject.py
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# Copyright (c) 2012-2018 by the GalSim developers team on GitHub
# https://github.com/GalSim-developers
#
# This file is part of GalSim: The modular galaxy image simulation toolkit.
# https://github.com/GalSim-developers/GalSim
#
# GalSim is free software: redistribution and use in source and binary forms,
# with or without modification, are permitted provided that the following
# conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions, and the disclaimer given in the accompanying LICENSE
# file.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions, and the disclaimer given in the documentation
# and/or other materials provided with the distribution.
#
from __future__ import print_function
import numpy as np
import os
import sys
import galsim
from galsim_test_helpers import *
@timer
def test_gaussian():
"""Test various ways to build a Gaussian
"""
config = {
'gal1' : { 'type' : 'Gaussian' , 'sigma' : 2 },
'gal2' : { 'type' : 'Gaussian' , 'fwhm' : 2, 'flux' : 100 },
'gal3' : { 'type' : 'Gaussian' , 'half_light_radius' : 2, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Gaussian' , 'sigma' : 1, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'Gaussian' , 'sigma' : 1.5, 'flux' : 72.5,
'rotate' : -34. * galsim.degrees,
'magnify' : 0.93,
'shear' : galsim.Shear(g1=-0.15, g2=0.2)
},
'gal6' : { 'type' : 'DeltaFunction' , 'flux' : 72.5 },
'bad1' : { 'type' : 'Gaussian' , 'fwhm' : 2, 'sigma' : 3, 'flux' : 100 },
'bad2' : { 'type' : 'Gaussian' },
'bad3' : { 'type' : 'Gaussian', 'sig' : 4 },
'bad4' : { 'sigma' : 2 },
'bad5' : { 'type' : 'Gauss', 'sigma' : 2 },
'bad6' : { 'type' : 'Gaussian', 'resolution' : 1.5 }, # requires psf field.
'bad7' : { 'type' : 'Gaussian', 'sigma' : 2, 'resolution' : 1.5 }, # can't give sigma
'bad8' : { 'type' : 'Gaussian', 'half_light_radius' : 2, 'resolution' : 1.5 }, # or hlr
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Gaussian(sigma = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Gaussian(fwhm = 2, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Gaussian(half_light_radius = 2, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Gaussian(sigma = 1, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gal5b = galsim.Gaussian(sigma = 1.5, flux = 72.5)
gal5b = gal5b.rotate(-34 * galsim.degrees).lens(-0.15, 0.2, 0.93)
gsobject_compare(gal5a, gal5b)
gal6a = galsim.config.BuildGSObject(config, 'gal6')[0]
gal6b = galsim.DeltaFunction(flux = 72.5)
gsobject_compare(gal6a, gal6b, conv=galsim.Gaussian(sigma=0.01))
# DeltaFunction is functionally equivalent to an extremely narrow Gaussian.
gal6c = galsim.Gaussian(sigma = 1.e-10, flux = 72.5)
gsobject_compare(gal6a, gal6c, conv=galsim.Gaussian(sigma=0.01))
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad3')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad4')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad5')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad6')
# Test various invalid ways to use resolution.
# This psf cannot be used for resolution, since no half_light_radius field.
psf_file = os.path.join('SBProfile_comparison_images','gauss_smallshear.fits')
config['psf'] = { 'type' : 'InterpolatedImage', 'image' : psf_file }
psf = galsim.config.BuildGSObject(config, 'psf')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad6')
# This has half_light_radius, but it raises an exception for obscuration != 1
config['psf'] = { 'type' : 'Airy' , 'lam_over_diam' : 0.4, 'obscuration' : 0.3 }
psf = galsim.config.BuildGSObject(config, 'psf')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad6')
# This finally works.
config['psf'] = { 'type' : 'Airy' , 'lam_over_diam' : 0.4 }
psf = galsim.config.BuildGSObject(config, 'psf')
gal = galsim.config.BuildGSObject(config, 'bad6')
# Can't give a different size along with resolution.
with assert_raises(galsim.GalSimConfigError):
gal = galsim.config.BuildGSObject(config, 'bad7')
with assert_raises(galsim.GalSimConfigError):
gal = galsim.config.BuildGSObject(config, 'bad8')
@timer
def test_moffat():
"""Test various ways to build a Moffat
"""
config = {
'gal1' : { 'type' : 'Moffat' , 'beta' : 1.4, 'scale_radius' : 2 },
'gal2' : { 'type' : 'Moffat' , 'beta' : 3.5, 'fwhm' : 2, 'trunc' : 5, 'flux' : 100 },
'gal3' : { 'type' : 'Moffat' , 'beta' : 2.2, 'half_light_radius' : 2, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Moffat' , 'beta' : 1.7, 'fwhm' : 1, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'Moffat' , 'beta' : 2.8, 'flux' : 22, 'fwhm' : 0.2, 'trunc' : 0.7,
'shear' : galsim.Shear(g1=-0.15, g2=0.2),
'gsparams' : { 'maxk_threshold' : 1.e-2 }
},
'bad1' : { 'type' : 'Moffat' , 'beta' : 1.4, 'scale_radius' : 2, 'fwhm' : 3 },
'bad2' : { 'type' : 'Moffat' , 'beta' : 1.4 },
'bad3' : { 'type' : 'Moffat' , 'beth' : 1.4, 'fwhm' : 8 },
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Moffat(beta = 1.4, scale_radius = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Moffat(beta = 3.5, fwhm = 2, trunc = 5, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Moffat(beta = 2.2, half_light_radius = 2, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Moffat(beta = 1.7, fwhm = 1, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
# Note: this needs to be rather small otherwise maxk_threshold is obviated by other
# adjustments we make to the parameters in SBProfile.cpp
gsparams = galsim.GSParams(maxk_threshold=1.e-2)
gal5b = galsim.Moffat(beta=2.8, fwhm=0.2, flux=22, trunc=0.7, gsparams=gsparams)
gal5b = gal5b.shear(g1=-0.15, g2=0.2)
# convolve to test the k-space gsparams (with an even smaller profile)
gsobject_compare(gal5a, gal5b, conv=galsim.Gaussian(sigma=0.01))
# Make sure they don't match when using the default GSParams
gal5c = galsim.Moffat(beta=2.8, fwhm=0.3, flux=22, trunc=0.7)
gal5c = gal5c.shear(g1=-0.15, g2=0.2)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c, conv=galsim.Gaussian(sigma=0.01))
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad3')
@timer
def test_airy():
"""Test various ways to build a Airy
"""
config = {
'gal1' : { 'type' : 'Airy' , 'lam_over_diam' : 2 },
'gal2' : { 'type' : 'Airy' , 'lam_over_diam' : 0.4, 'obscuration' : 0.3, 'flux' : 100 },
'gal3' : { 'type' : 'Airy' , 'lam_over_diam' : 1.3, 'obscuration' : 0, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Airy' , 'lam_over_diam' : 1, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'Airy' , 'lam_over_diam' : 45,
'gsparams' : { 'xvalue_accuracy' : 1.e-2 }
},
'gal6' : { 'type' : 'Airy' , 'lam' : 400., 'diam' : 4.0, 'scale_unit' : 'arcmin' },
'bad1' : { 'type' : 'Airy' , 'lam_over_diam' : 0.4, 'lam' : 400, 'diam' : 10 },
'bad2' : { 'type' : 'Airy' , 'flux' : 1.3 },
'bad3' : { 'type' : 'Airy' , 'lam_over_diam' : 0.4, 'obsc' : 0.3, 'flux' : 100 },
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Airy(lam_over_diam = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Airy(lam_over_diam = 0.4, obscuration = 0.3, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Airy(lam_over_diam = 1.3, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Airy(lam_over_diam = 1, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
# The approximation from xvalue_accuracy here happens at the core, so you need a very
# large size to notice. (Which tells me this isn't that useful an approximation, but
# so be it.)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(xvalue_accuracy=1.e-2)
gal5b = galsim.Airy(lam_over_diam=45, gsparams=gsparams)
gsobject_compare(gal5a, gal5b)
gal6a = galsim.config.BuildGSObject(config, 'gal6')[0]
gal6b = galsim.Airy(lam=400., diam=4., scale_unit=galsim.arcmin)
gsobject_compare(gal6a, gal6b)
# Make sure they don't match when using the default GSParams
gal5c = galsim.Airy(lam_over_diam=45)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c)
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad3')
@timer
def test_kolmogorov():
"""Test various ways to build a Kolmogorov
"""
config = {
'gal1' : { 'type' : 'Kolmogorov' , 'lam_over_r0' : 2 },
'gal2' : { 'type' : 'Kolmogorov' , 'fwhm' : 2, 'flux' : 100 },
'gal3' : { 'type' : 'Kolmogorov' , 'half_light_radius' : 2, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Kolmogorov' , 'lam' : 400, 'r0_500' : 0.15, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'Kolmogorov' , 'lam_over_r0' : 1, 'flux' : 50,
'gsparams' : { 'integration_relerr' : 1.e-2, 'integration_abserr' : 1.e-4 }
},
'bad1' : { 'type' : 'Kolmogorov' , 'fwhm' : 2, 'lam_over_r0' : 3, 'flux' : 100 },
'bad2' : { 'type' : 'Kolmogorov', 'flux' : 100 },
'bad3' : { 'type' : 'Kolmogorov' , 'lam_over_r0' : 2, 'lam' : 400, 'r0' : 0.15 },
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Kolmogorov(lam_over_r0 = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Kolmogorov(fwhm = 2, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Kolmogorov(half_light_radius = 2, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Kolmogorov(lam=400, r0_500=0.15, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees)
gal4b = gal4b.lens(0.03, -0.05, 1.03).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(integration_relerr=1.e-2, integration_abserr=1.e-4)
gal5b = galsim.Kolmogorov(lam_over_r0=1, flux=50, gsparams=gsparams)
gsobject_compare(gal5a, gal5b)
# Make sure they don't match when using the default GSParams
gal5c = galsim.Kolmogorov(lam_over_r0=1, flux=50)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c)
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad3')
@timer
def test_opticalpsf():
"""Test various ways to build a OpticalPSF
"""
config = {
'gal1' : { 'type' : 'OpticalPSF' , 'lam_over_diam' : 2 },
'gal2' : { 'type' : 'OpticalPSF' , 'lam_over_diam' : 2, 'flux' : 100,
'defocus' : 0.23, 'astig1' : -0.12, 'astig2' : 0.11,
'coma1' : -0.09, 'coma2' : 0.03, 'spher' : 0.19,
'pad_factor' : 1.4, 'oversampling' : 1.2
},
'gal3' : { 'type' : 'OpticalPSF' , 'lam_over_diam' : 2, 'flux' : 1.e6,
'defocus' : 0.23, 'astig1' : -0.12, 'astig2' : 0.11,
'circular_pupil' : False, 'obscuration' : 0.3,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'OpticalPSF' , 'lam_over_diam' : 0.05, 'flux' : 50,
'defocus' : 0.03, 'astig1' : -0.04, 'astig2' : 0.07,
'coma1' : -0.09, 'coma2' : 0.03, 'spher' : -0.09,
'circular_pupil' : True, 'obscuration' : 0.2,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type': 'OpticalPSF' , 'lam' : 900, 'diam' : 2.4, 'flux' : 1.8,
'defocus' : 0.1, 'obscuration' : 0.18,
'pupil_plane_im' :
os.path.join(".","Optics_comparison_images","sample_pupil_rolled.fits"),
'pupil_angle' : 27.*galsim.degrees },
'gal6' : {'type' : 'OpticalPSF' , 'lam' : 874.0, 'diam' : 7.4, 'flux' : 70.,
'aberrations' : [0.06, 0.12, -0.08, 0.07, 0.04, 0.0, 0.0, -0.13],
'obscuration' : 0.1 },
'gal7' : {'type' : 'OpticalPSF' , 'lam' : 874.0, 'diam' : 7.4, 'aberrations' : []},
'bad1' : {'type' : 'OpticalPSF' , 'lam' : 874.0, 'diam' : 7.4, 'lam_over_diam' : 0.2},
'bad2' : {'type' : 'OpticalPSF' , 'lam_over_diam' : 0.2,
'aberrations' : "0.06, 0.12, -0.08, 0.07, 0.04, 0.0, 0.0, -0.13"},
'bad3' : {'type' : 'OpticalPSF' , 'lam_over_diam' : 0.2, 'aberr' : []},
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.OpticalPSF(lam_over_diam = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.OpticalPSF(lam_over_diam = 2, flux = 100,
defocus = 0.23, astig1 = -0.12, astig2 = 0.11,
coma1 = -0.09, coma2 = 0.03, spher = 0.19,
pad_factor = 1.4, oversampling = 1.2)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.OpticalPSF(lam_over_diam = 2, flux = 1.e6,
defocus = 0.23, astig1 = -0.12, astig2 = 0.11,
circular_pupil = False, obscuration = 0.3)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.OpticalPSF(lam_over_diam = 0.05, flux = 50,
defocus = 0.03, astig1 = -0.04, astig2 = 0.07,
coma1 = -0.09, coma2 = 0.03, spher = -0.09,
circular_pupil = True, obscuration = 0.2)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gal5b = galsim.OpticalPSF(
lam=900, diam=2.4, flux=1.8, defocus=0.1, obscuration=0.18,
pupil_plane_im=os.path.join(".","Optics_comparison_images","sample_pupil_rolled.fits"),
pupil_angle=27.*galsim.degrees)
gsobject_compare(gal5a, gal5b)
gal6a = galsim.config.BuildGSObject(config, 'gal6')[0]
aberrations = np.zeros(12, dtype=float)
aberrations[4:] = [0.06, 0.12, -0.08, 0.07, 0.04, 0.0, 0.0, -0.13]
gal6b = galsim.OpticalPSF(lam=874., diam=7.4, flux=70., obscuration=0.1,
aberrations=aberrations)
gsobject_compare(gal6a, gal6b)
gal7a = galsim.config.BuildGSObject(config, 'gal7')[0]
gal7b = galsim.OpticalPSF(lam=874., diam=7.4)
gsobject_compare(gal7a, gal7b)
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad3')
@timer
def test_exponential():
"""Test various ways to build a Exponential
"""
config = {
'gal1' : { 'type' : 'Exponential' , 'scale_radius' : 2 },
'gal2' : { 'type' : 'Exponential' , 'scale_radius' : 1.7, 'flux' : 100 },
'gal3' : { 'type' : 'Exponential' , 'half_light_radius' : 2, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Exponential' , 'scale_radius' : 1, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'Exponential' , 'scale_radius' : 1, 'flux' : 50,
'gsparams' : { 'kvalue_accuracy' : 1.e-2 }
},
'bad1' : { 'type' : 'Exponential' , 'scale_radius' : 2, 'half_light_radius' : 3 },
'bad2' : { 'type' : 'Exponential' },
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Exponential(scale_radius = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Exponential(scale_radius = 1.7, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Exponential(half_light_radius = 2, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Exponential(scale_radius = 1, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(kvalue_accuracy=1.e-2)
gal5b = galsim.Exponential(scale_radius=1, flux=50, gsparams=gsparams)
gsobject_compare(gal5a, gal5b, conv=galsim.Gaussian(sigma=1))
# Make sure they don't match when using the default GSParams
gal5c = galsim.Exponential(scale_radius=1, flux=50)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c, conv=galsim.Gaussian(sigma=1))
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
@timer
def test_sersic():
"""Test various ways to build a Sersic
"""
config = {
'gal1' : { 'type' : 'Sersic' , 'n' : 1.2, 'half_light_radius' : 2 },
'gal2' : { 'type' : 'Sersic' , 'n' : 3.5, 'half_light_radius' : 1.7, 'flux' : 100 },
'gal3' : { 'type' : 'Sersic' , 'n' : 2.2, 'half_light_radius' : 3.5, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Sersic' , 'n' : 0.7, 'half_light_radius' : 1, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'Sersic' , 'n' : 0.7, 'half_light_radius' : 1, 'flux' : 50,
'gsparams' : { 'minimum_fft_size' : 256 }
},
'gal6' : { 'type' : 'Sersic' , 'n' : 0.7, 'half_light_radius' : 1, 'flux' : 50,
'gsparams' : { 'maximum_fft_size' : 64 }
},
'gal7' : { 'type' : 'Sersic' , 'n' : 3.2, 'half_light_radius' : 1.7, 'flux' : 50,
'trunc' : 4.3,
'gsparams' : { 'realspace_relerr' : 1.e-2 , 'realspace_abserr' : 1.e-4 }
},
'bad1' : { 'type' : 'Sersic' , 'n' : 0.1, 'half_light_radius' : 3.5 },
'bad2' : { 'type' : 'Sersic' , 'n' : 11.1, 'half_light_radius' : 3.5 },
'bad3' : { 'type' : 'Sersic' , 'n' : 1.1 },
'bad4' : { 'type' : 'Sersic' , 'n' : 1.1, 'half_light_radius' : 3.5, 'scale_radius' : 2 },
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Sersic(n = 1.2, half_light_radius = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Sersic(n = 3.5, half_light_radius = 1.7, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Sersic(n = 2.2, half_light_radius = 3.5, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Sersic(n = 0.7, half_light_radius = 1, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees)
gal4b = gal4b.lens(0.03, -0.05, 1.03).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(minimum_fft_size=256)
gal5b = galsim.Sersic(n=0.7, half_light_radius=1, flux=50, gsparams=gsparams)
gsobject_compare(gal5a, gal5b, conv=galsim.Gaussian(sigma=1))
# Make sure they don't match when using the default GSParams
gal5c = galsim.Sersic(n=0.7, half_light_radius=1, flux=50)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c, conv=galsim.Gaussian(sigma=1))
# For the maximum_fft_size test, we need to do things a little differently
# We lower maximum_fft_size below the size that it normally wants this to be,
# and we check to make sure an exception is thrown. Of course, this isn't how you
# would normally use maximum_fft_size. Normally, you would raise it when the default
# is too small. But to construct the test that way would require a lot of memory
# and would be rather slow.
gal6a = galsim.config.BuildGSObject(config, 'gal6')[0]
gal6b = galsim.Sersic(n=0.7, half_light_radius=1, flux=50)
with assert_raises(galsim.GalSimFFTSizeError):
gsobject_compare(gal6a, gal6b, conv=galsim.Gaussian(sigma=1))
gal7a = galsim.config.BuildGSObject(config, 'gal7')[0]
gsparams = galsim.GSParams(realspace_relerr=1.e-2, realspace_abserr=1.e-4)
gal7b = galsim.Sersic(n=3.2, half_light_radius=1.7, flux=50, trunc=4.3, gsparams=gsparams)
# Convolution with a truncated Moffat will use realspace convolution
conv = galsim.Moffat(beta=2.8, fwhm=1.3, trunc=3.7)
gsobject_compare(gal7a, gal7b, conv=conv)
# Make sure they don't match when using the default GSParams
gal7c = galsim.Sersic(n=3.2, half_light_radius=1.7, flux=50, trunc=4.3)
with assert_raises(AssertionError):
gsobject_compare(gal7a, gal7c, conv=conv)
with assert_raises(galsim.GalSimRangeError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimRangeError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad3')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad4')
@timer
def test_devaucouleurs():
"""Test various ways to build a DeVaucouleurs
"""
config = {
'gal1' : { 'type' : 'DeVaucouleurs' , 'half_light_radius' : 2 },
'gal2' : { 'type' : 'DeVaucouleurs' , 'half_light_radius' : 1.7, 'flux' : 100 },
'gal3' : { 'type' : 'DeVaucouleurs' , 'half_light_radius' : 3.5, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'DeVaucouleurs' , 'half_light_radius' : 1, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'DeVaucouleurs' , 'half_light_radius' : 1, 'flux' : 50,
'gsparams' : { 'folding_threshold' : 1.e-4 }
}
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.DeVaucouleurs(half_light_radius = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.DeVaucouleurs(half_light_radius = 1.7, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.DeVaucouleurs(half_light_radius = 3.5, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.DeVaucouleurs(half_light_radius = 1, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(folding_threshold=1.e-4)
gal5b = galsim.DeVaucouleurs(half_light_radius=1, flux=50, gsparams=gsparams)
gsobject_compare(gal5a, gal5b, conv=galsim.Gaussian(sigma=1))
# Make sure they don't match when using the default GSParams
gal5c = galsim.DeVaucouleurs(half_light_radius=1, flux=50)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c, conv=galsim.Gaussian(sigma=1))
@timer
def test_inclined_exponential():
"""Test various ways to build an InclinedExponential
"""
config = {
'gal1' : { 'type' : 'InclinedExponential' , 'inclination' : 0.1 * galsim.radians,
'half_light_radius' : 2 },
'gal2' : { 'type' : 'InclinedExponential' , 'inclination' : 21 * galsim.degrees,
'scale_radius' : 0.7, 'flux' : 100 },
'gal3' : { 'type' : 'InclinedExponential' , 'inclination' : 0.3 * galsim.radians,
'scale_radius' : 0.35, 'scale_height' : 0.23, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'InclinedExponential' , 'inclination' : 0.7 * galsim.radians,
'half_light_radius' : 1, 'scale_h_over_r' : 0.2, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' :-1.2 }
},
'gal5' : { 'type' : 'InclinedExponential' , 'inclination' : 0.7 * galsim.radians,
'half_light_radius' : 1, 'flux' : 50,
'gsparams' : { 'minimum_fft_size' : 256 }
},
'bad1' : { 'type' : 'InclinedExponential' , 'inclination' : 0.7 * galsim.radians,
'half_light_radius' : 1, 'scale_radius' : 2 },
'bad2' : { 'type' : 'InclinedExponential' , 'inclination' : 0.7 * galsim.radians,
'scale_h_over_r' : 0.2 },
'bad3' : { 'type' : 'InclinedExponential' , 'inclination' : 0.7 * galsim.radians,
'scale_radius' : 1, 'scale_h_over_r' : 0.2, 'scale_height' : 0.1 },
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.InclinedExponential(inclination=0.1 * galsim.radians, half_light_radius=2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.InclinedExponential(inclination=21 * galsim.degrees, scale_radius=0.7, flux=100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.InclinedExponential(inclination=0.3 * galsim.radians, scale_radius=0.35,
scale_height=0.23, flux=1.e6)
gal3b = gal3b.shear(q=0.6, beta=0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.InclinedExponential(inclination=0.7 * galsim.radians, half_light_radius=1,
scale_h_over_r=0.2, flux=50)
gal4b = gal4b.dilate(3).shear(e1=0.3).rotate(12 * galsim.degrees)
gal4b = gal4b.lens(0.03, -0.05, 1.03).shift(dx=0.7, dy=-1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(minimum_fft_size=256)
gal5b = galsim.InclinedExponential(inclination=0.7 * galsim.radians, half_light_radius=1,
flux=50, gsparams=gsparams)
gsobject_compare(gal5a, gal5b, conv=galsim.Gaussian(sigma=1))
# Make sure they don't match when using the default GSParams
gal5c = galsim.InclinedExponential(inclination=0.7 * galsim.radians, half_light_radius=1,
flux=50)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c, conv=galsim.Gaussian(sigma=1))
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
with assert_raises(galsim.GalSimError):
galsim.config.BuildGSObject(config, 'bad3')
@timer
def test_inclined_sersic():
"""Test various ways to build an InclinedSersic
"""
config = {
'gal1' : { 'type' : 'InclinedSersic' , 'n' : 1.2, 'inclination' : 0.1 * galsim.radians,
'half_light_radius' : 2 },
'gal2' : { 'type' : 'InclinedSersic' , 'n' : 3.5, 'inclination' : 21 * galsim.degrees,
'scale_radius' : 0.007, 'flux' : 100 },
'gal3' : { 'type' : 'InclinedSersic' , 'n' : 2.2, 'inclination' : 0.3 * galsim.radians,
'scale_radius' : 0.35, 'scale_height' : 0.23, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'InclinedSersic' , 'n' : 0.7, 'inclination' : 0.7 * galsim.radians,
'half_light_radius' : 1, 'scale_h_over_r' : 0.2, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' :-1.2 }
},
'gal5' : { 'type' : 'InclinedSersic' , 'n' : 0.7, 'inclination' : 0.7 * galsim.radians,
'half_light_radius' : 1, 'flux' : 50,
'gsparams' : { 'minimum_fft_size' : 256 }
},
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.InclinedSersic(n=1.2, inclination=0.1 * galsim.radians, half_light_radius=2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.InclinedSersic(n=3.5, inclination=21 * galsim.degrees, scale_radius=0.007,
flux=100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.InclinedSersic(n=2.2, inclination=0.3 * galsim.radians, scale_radius=0.35,
scale_height=0.23, flux=1.e6)
gal3b = gal3b.shear(q=0.6, beta=0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b)
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.InclinedSersic(n=0.7, inclination=0.7 * galsim.radians, half_light_radius=1,
scale_h_over_r=0.2, flux=50)
gal4b = gal4b.dilate(3).shear(e1=0.3).rotate(12 * galsim.degrees)
gal4b = gal4b.lens(0.03, -0.05, 1.03).shift(dx=0.7, dy=-1.2)
gsobject_compare(gal4a, gal4b)
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gsparams = galsim.GSParams(minimum_fft_size=256)
gal5b = galsim.InclinedSersic(n=0.7, inclination=0.7 * galsim.radians, half_light_radius=1,
flux=50, gsparams=gsparams)
gsobject_compare(gal5a, gal5b, conv=galsim.Gaussian(sigma=1))
# Make sure they don't match when using the default GSParams
gal5c = galsim.InclinedSersic(n=0.7, inclination=0.7 * galsim.radians, half_light_radius=1,
flux=50)
with assert_raises(AssertionError):
gsobject_compare(gal5a, gal5c, conv=galsim.Gaussian(sigma=1))
@timer
def test_pixel():
"""Test various ways to build a Pixel
"""
config = {
'gal1' : { 'type' : 'Pixel' , 'scale' : 2 },
'gal2' : { 'type' : 'Pixel' , 'scale' : 1.7, 'flux' : 100 },
'gal3' : { 'type' : 'Box' , 'width' : 2, 'height' : 2.1, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'Box' , 'width' : 1, 'height' : 1.2, 'flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
}
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.Pixel(scale = 2)
gsobject_compare(gal1a, gal1b)
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.Pixel(scale = 1.7, flux = 100)
gsobject_compare(gal2a, gal2b)
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.Box(width = 2, height = 2.1, flux = 1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
# Drawing sheared Pixel without convolution doesn't work, so we need to
# do the extra convolution by a Gaussian here
gsobject_compare(gal3a, gal3b, conv=galsim.Gaussian(0.1))
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.Box(width = 1, height = 1.2, flux = 50)
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b, conv=galsim.Gaussian(0.1))
@timer
def test_realgalaxy():
"""Test various ways to build a RealGalaxy
"""
# I don't want to gratuitously copy the real_catalog catalog, so use the
# version in the examples directory.
real_gal_dir = os.path.join('..','examples','data')
real_gal_cat = 'real_galaxy_catalog_23.5_example.fits'
config = {
'input' : { 'real_catalog' :
{ 'dir' : real_gal_dir ,
'file_name' : real_gal_cat ,
'preload' : True }
},
'gal1' : { 'type' : 'RealGalaxy' },
'gal2' : { 'type' : 'RealGalaxy' , 'index' : 23, 'flux' : 100 },
'gal3' : { 'type' : 'RealGalaxy' , 'id' : 103176, 'flux' : 1.e6,
'ellip' : { 'type' : 'QBeta' , 'q' : 0.6, 'beta' : 0.39 * galsim.radians }
},
'gal4' : { 'type' : 'RealGalaxy' , 'index' : 5, 'scale_flux' : 50,
'dilate' : 3, 'ellip' : galsim.Shear(e1=0.3),
'rotate' : 12 * galsim.degrees,
'magnify' : 1.03, 'shear' : galsim.Shear(g1=0.03, g2=-0.05),
'shift' : { 'type' : 'XY', 'x' : 0.7, 'y' : -1.2 }
},
'gal5' : { 'type' : 'RealGalaxy' , 'index' : 23, 'noise_pad_size' : 10 },
'gal6' : { 'type' : 'RealGalaxyOriginal' },
'gal7' : { 'type' : 'RealGalaxy' , 'random' : True},
# I admit the one below is odd (why would you specify "random" and have it be False?) but
# one could imagine setting it based on some probabilistic process...
'gal8' : { 'type' : 'RealGalaxy' , 'random' : False},
'bad1' : { 'type' : 'RealGalaxy' , 'index' : -3 },
'bad2' : { 'type' : 'RealGalaxy' , 'index' : 3000 },
}
rng = galsim.UniformDeviate(1234)
config['rng'] = galsim.UniformDeviate(1234) # A second copy starting with the same seed.
galsim.config.ProcessInput(config)
real_cat = galsim.RealGalaxyCatalog(
dir=real_gal_dir, file_name=real_gal_cat, preload=True)
# For these profiles, we convolve by a gaussian to smooth out the profile.
# This makes the comparison much faster without changing the validity of the test.
conv = galsim.Gaussian(sigma = 1)
config['obj_num'] = 0
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = galsim.RealGalaxy(real_cat, index=0)
# The convolution here
gsobject_compare(gal1a, gal1b, conv=conv)
config['obj_num'] = 1
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = galsim.RealGalaxy(real_cat, index = 23, flux=100)
gsobject_compare(gal2a, gal2b, conv=conv)
config['obj_num'] = 2
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = galsim.RealGalaxy(real_cat, index = 17, flux=1.e6)
gal3b = gal3b.shear(q = 0.6, beta = 0.39 * galsim.radians)
gsobject_compare(gal3a, gal3b, conv=conv)
config['obj_num'] = 3
gal4a = galsim.config.BuildGSObject(config, 'gal4')[0]
gal4b = galsim.RealGalaxy(real_cat, index = 5)
gal4b *= 50
gal4b = gal4b.dilate(3).shear(e1 = 0.3).rotate(12 * galsim.degrees).magnify(1.03)
gal4b = gal4b.shear(g1 = 0.03, g2 = -0.05).shift(dx = 0.7, dy = -1.2)
gsobject_compare(gal4a, gal4b, conv=conv)
config['obj_num'] = 4
gal5a = galsim.config.BuildGSObject(config, 'gal5')[0]
gal5b = galsim.RealGalaxy(real_cat, index = 23, rng = rng, noise_pad_size = 10)
gsobject_compare(gal5a, gal5b, conv=conv)
# Also check that the noise attribute is correct.
gsobject_compare(gal5a.noise._profile, gal5b.noise._profile, conv=conv)
# Should work if rng not in base config dict.
del config['rng']
galsim.config.RemoveCurrent(config) # Clear the cached values, so it rebuilds.
galsim.config.BuildGSObject(config, 'gal5')
# If there is a logger, there should be a warning message emitted.
with CaptureLog() as cl:
galsim.config.RemoveCurrent(config)
galsim.config.BuildGSObject(config, 'gal5', logger=cl.logger)
assert "No base['rng'] available" in cl.output
config['obj_num'] = 5
gal6a = galsim.config.BuildGSObject(config, 'gal6')[0]
gal6b = galsim.RealGalaxy(real_cat, index=5).original_gal
gsobject_compare(gal6a, gal6b, conv=conv)
config['obj_num'] = 6
# Since we are comparing the random functionality, we need to reset the RNG.
config['rng'] = galsim.UniformDeviate(1234)
gal7a = galsim.config.BuildGSObject(config, 'gal7')[0]
gal7b = galsim.RealGalaxy(real_cat, random=True, rng=galsim.BaseDeviate(1234))
gsobject_compare(gal7a, gal7b, conv=conv)
config['obj_num'] = 7
gal8a = galsim.config.BuildGSObject(config, 'gal8')[0]
gal8b = galsim.RealGalaxy(real_cat, index=7)
gsobject_compare(gal8a, gal8b, conv=conv)
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad1')
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'bad2')
@timer
def test_cosmosgalaxy():
"""Test various ways to build a COSMOSGalaxy
"""
# I don't want to gratuitously copy the real_catalog catalog, so use the
# version in the examples directory.
real_gal_dir = os.path.join('..','examples','data')
real_gal_cat = 'real_galaxy_catalog_23.5_example.fits'
config = {
'input' : { 'cosmos_catalog' :
{ 'dir' : real_gal_dir ,
'file_name' : real_gal_cat,
'preload' : True}
},
# First one uses defaults for gal_type (real, since we used the actual catalog and not the
# parametric one) and selects a random galaxy using internal routines
# (the default if index is unspecified).
'gal1' : { 'type' : 'COSMOSGalaxy', 'scale_flux' : 3.14 },
# Second uses parametric gal_type and selects a random galaxy using the config sequence
# option. Includes flux modifications and rotation.
'gal2' : { 'type' : 'COSMOSGalaxy', 'gal_type' : 'parametric',
'index' : { 'type' : 'Sequence', 'nitems' : 1},
'scale_flux' : 0.3,
'rotate' : 30 * galsim.degrees },
# Third uses parametric gal_type and a specific galaxy index. Includes flux modifications,
# shear and magnification.
'gal3' : {'type' : 'COSMOSGalaxy', 'gal_type' : 'parametric',
'index' : 27, 'scale_flux' : 1.e6,
'magnify' : 0.9, 'shear' : galsim.Shear(g1=0.01, g2=-0.07)},
# Fourth tries to select outside the catalog; make sure the exception is caught.
'gal4' : {'type' : 'COSMOSGalaxy', 'gal_type' : 'parametric',
'index' : 1001}
}
rng = galsim.UniformDeviate(1234)
config['rng'] = galsim.UniformDeviate(1234) # A second copy starting with the same seed.
galsim.config.ProcessInput(config)
cosmos_cat = galsim.COSMOSCatalog(
dir=real_gal_dir, file_name=real_gal_cat, preload=True)
# For these profiles, we convolve by a gaussian to smooth out the profile.
# This makes the comparison much faster without changing the validity of the test.
conv = galsim.Gaussian(sigma = 1)
config['obj_num'] = 0
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]
gal1b = 3.14*cosmos_cat.makeGalaxy(rng=rng)
gsobject_compare(gal1a, gal1b, conv=conv)
config['obj_num'] = 1
gal2a = galsim.config.BuildGSObject(config, 'gal2')[0]
gal2b = cosmos_cat.makeGalaxy(index=0, gal_type='parametric', rng=rng)
gal2b = gal2b.withScaledFlux(0.3).rotate(30*galsim.degrees)
gsobject_compare(gal2a, gal2b, conv=conv)
config['obj_num'] = 2
gal3a = galsim.config.BuildGSObject(config, 'gal3')[0]
gal3b = cosmos_cat.makeGalaxy(index=27, gal_type='parametric', rng=rng)
gal3b = gal3b.withScaledFlux(1.e6).magnify(0.9).shear(g1=0.01, g2=-0.07)
gsobject_compare(gal3a, gal3b, conv=conv)
config['obj_num'] = 3
with assert_raises(galsim.GalSimConfigError):
galsim.config.BuildGSObject(config, 'gal4')
# One more test: make sure that if we specified from the start not to use real galaxies, that
# failure to specify gal_type is treated properly (should default to parametric).
real_gal_cat = 'real_galaxy_catalog_23.5_example_fits.fits'
config = {
'input' : { 'cosmos_catalog' :
{ 'dir' : real_gal_dir ,
'file_name' : real_gal_cat,
'use_real' : False,
'preload' : True}
},
# Use defaults for gal_type (parametric, since we used the actual catalog and not the
# parametric one) and select a random galaxy using internal routines.
'gal1' : { 'type' : 'COSMOSGalaxy' },
}
rng = galsim.UniformDeviate(1234)
config['rng'] = galsim.UniformDeviate(1234) # A second copy starting with the same seed.
galsim.config.ProcessInput(config)
cosmos_cat = galsim.COSMOSCatalog(
dir=real_gal_dir, file_name=real_gal_cat, use_real=False, preload=True)
config['obj_num'] = 0
# It is going to complain that it doesn't have weight factors. We want to ignore this.
with assert_warns(galsim.GalSimWarning):
gal1a = galsim.config.BuildGSObject(config, 'gal1')[0]