In [10]:

    

# this notebook measures how much time does it take to converge as a function of different parameters
# lets start with number of images!
%pylab inline

import numpy
import astrohack_projections
import matplotlib.pyplot as plt

# plot parameters
plt.rcParams['figure.figsize'] = 16, 16
plot_kwargs = {"interpolation": "nearest",
          "cmap": "afmhot",
          "origin": "lower"}

# initial galaxy data
file_path = "./illustris_galaxies/cutout_83.hdf5"
illustris_gal = astrohack_projections.illustris_model_and_image(file_path)
illustris_gal.set_image_shape((30, 40))

shape = (30, 40)
number_of_gauss = [1, 2, 3, 4, 5]
albums = []
img_num = 32

for n, num_g in enumerate(number_of_gauss):
    # build the galaxy
    gal_model = astrohack_projections.galaxy_model_3d()
    for g in xrange(num_g):
        v = numpy.random.uniform(-3, 3, size=3)
        mu = numpy.random.uniform(-3, 3, size=3)
        gal_model.add_gaussian(1.0, mu, basevar + numpy.outer(v,v))
        
    # album and PSF initialisation
    album = astrohack_projections.album_and_model()
    psf = astrohack_projections.mixture_of_gaussians(2)
    psf.add_gaussian(1., numpy.array([0., 0.]), numpy.eye(2)*1.)
    illustris_gal.set_image_shape(shape)
    
    for i in xrange(img_num):
        # projection parameters
        xi_hat, eta_hat = astrohack_projections.choose_random_projection()
        alpha, beta, gamma = numpy.random.uniform(0.0, 360.0, 3)
        intensity = 150
        scale = 0.18 * numpy.exp(numpy.random.uniform())
        xshift = numpy.random.uniform(shape[0]/2 - 1, shape[0]/2 + 1)
        yshift = numpy.random.uniform(shape[1]/2 - 1, shape[1]/2 + 1)
        psf_size = 1
        bg = 0.
        # illustris galaxy
        kwargs = {'alpha':alpha, 'beta':beta, 'gamma':gamma, 'intensity':intensity, 'scale':scale, 'xshift': xshift, 'yshift': yshift, 'bg':0.0, 'psf_size':psf_size}
        illustris_gal.set_image_parameters(**kwargs)
        illustris_gal.construct_image(xi_hat, eta_hat)
        # image
        image = astrohack_projections.image_and_model()
        image.set_shape(shape)
        image.set_psf(psf)
        kwargs = {'alpha':alpha, 'beta':beta, 'gamma':gamma, 'intensity':intensity, 'scale':scale, 'xshift': xshift, 'yshift': yshift, 'bg':0.0}
        image.set_parameters(**kwargs)
        image.set_galaxy(gal_model)
        image.set_ivar(numpy.ones(image.get_shape()))
        image.set_data(illustris_gal.get_image() + numpy.random.normal(size=image.get_shape())/ numpy.sqrt(image.ivar))
        # album
        album.add_image(image)
        print "num of galpars:", len(image.galaxy.get_parameters_vector())

    albums.append(album)
print len(albums)
print "new"


    

    




Populating the interactive namespace from numpy and matplotlib
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5
new






    




WARNING: pylab import has clobbered these variables: ['gamma', 'beta', 'shape']
`%matplotlib` prevents importing * from pylab and numpy

In [11]:

    

def showme(album):
    plt.rcParams['figure.figsize'] = 16, len(album)*2
    plot_kwargs = {"interpolation": "nearest",
          "cmap": "afmhot",
          "origin": "lower"}
    for i in xrange(len(album)):
        image = album.get_all_images()[i]
        plt.subplot(len(album)/2, 4, 2*i+1)
        vmin = -5. / numpy.sqrt(numpy.median(image.get_ivar())) # assumes bg = 0
        vmax = -2. * vmin # assumes bg = 0
        plt.imshow(numpy.nan_to_num(numpy.sqrt(image.get_data())), **plot_kwargs)
        plt.colorbar()
        plt.subplot(len(album)/2, 4, 2*i+2)
        plt.imshow(numpy.nan_to_num(numpy.sqrt(image.get_synthetic())), **plot_kwargs)
        plt.colorbar()
        
showme(albums[0])


    

    




/Users/dalyabaron/.virtualenvs/astro/lib/python2.7/site-packages/ipykernel/__main__.py:11: RuntimeWarning: invalid value encountered in sqrt






    

In [4]:

    

# INITIALIZATION BLOCK!
import scipy.optimize as op

galpar0 = numpy.array([1., 2., 0., 0., 1., 1., 1., 0., 0., 0.,
                       1., 0., 2., 0., 1., 1., 1., 0., 0., 0.,
                       1., 0., 0., 2., 1., 1., 1., 0., 0., 0.])
imgpar0 = (10., 30., 30., 0.1, 0.5, 14., 20., 0.)

for album in albums:
    print "album before", album(galpar0)
    for image in album:
        print "image before", image(imgpar0)

    #showme(album)
    #plt.savefig("./fitting_pngs/time_simulations/initialisation_album_%s.pdf" % (len(album)))
    #plt.close()


    

    




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In [12]:

    

import time
# for every album, run two galpar and two imagepar minimisations

times_dict = {1:[], 2:[], 3:[], 4:[], 5:[]}

shape = (30, 40)
number_of_gauss = [1, 2, 3, 4, 5]

for n, num_g in enumerate(number_of_gauss):
    print img_num
    
    album = albums[n]
    num_runs = 4
    
    for i in xrange(num_runs):
        # album optimisation
        time_start = time.time()      
        galpar0 = album.get_all_images()[0].galaxy.get_parameters_vector()
        print "album before", album(galpar0), len(galpar0)
        result = op.minimize(album, galpar0, method="Powell")
        galpar = result['x']
        print "album after", album(galpar)
        time_end = time.time()
        
        times_dict[num_g].append(time_end - time_start)
        showme(album)
        plt.savefig("./fitting_pngs/time_simulations3/album_%s_run_%s.pdf" % (num_g, str(2* i).zfill(2)))
        plt.close()

        # image optimisation
        time_start = time.time()
        for image in album:
            imgpar0 = image.get_parameters_vector()
            print "image before", image(imgpar0)
            result = op.minimize(image, imgpar0)
            imgpar = result['x']
            print "image after", image(imgpar)
        time_end = time.time()
        times_dict[num_g].append(time_end - time_start)

        showme(album)
        plt.savefig("./fitting_pngs/time_simulations3/album_%s_run_%s.pdf" % (num_g, str(2*i+1).zfill(2) ))
        plt.close()


    

    




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/Users/dalyabaron/.virtualenvs/astro/lib/python2.7/site-packages/ipykernel/__main__.py:11: RuntimeWarning: invalid value encountered in sqrt
/Users/dalyabaron/.virtualenvs/astro/lib/python2.7/site-packages/ipykernel/__main__.py:14: RuntimeWarning: invalid value encountered in sqrt






    




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/Users/dalyabaron/.virtualenvs/astro/lib/python2.7/site-packages/scipy/optimize/optimize.py:2108: RuntimeWarning: invalid value encountered in double_scalars
  w = xb - ((xb - xc) * tmp2 - (xb - xa) * tmp1) / denom

In [13]:

    

print times_dict


    

    




{1: [50.69012093544006, 21.3942768573761, 13.968705177307129, 17.20725703239441, 14.51300597190857, 12.829061031341553, 10.308454036712646, 13.29848599433899], 2: [327.0866770744324, 31.141858100891113, 83.83874607086182, 25.850762128829956, 74.26261496543884, 21.04110097885132, 77.10531783103943, 20.890804052352905], 3: [601.7877261638641, 40.61768102645874, 265.4567720890045, 30.979303121566772, 151.391371011734, 29.630604028701782, 75.49631690979004, 26.64721393585205], 4: [2295.280686855316, 51.64630484580994, 1151.7531900405884, 40.87672805786133, 198.54106092453003, 34.75434494018555, 194.39383101463318, 34.34956097602844], 5: [3172.4312369823456, 65.26921200752258, 847.8415880203247, 43.02193903923035, 466.4366099834442, 40.69065594673157, 649.7673718929291, 40.427730083465576]}