def test_bbfit():
temperatures = [5,10,15,20,25]
betas = [1,1.25,1.5,1.75,2.0,2.25,2.5]
columns = [22,23,24]
wavelengths = [#np.array([70,160,250,350,500,850,1100],dtype='float'),
np.array([160,250,350,500,1100],dtype='float'),
np.array([160,250,350,500],dtype='float')]
errlevels = [0.1,0.2,0.05]
temperature = 20.*u.K
beta = 1.75
column = 1e22*u.cm**-2
wavelength = wavelengths[0]*u.um
errlevel = errlevels[0]
#for temperature,beta,column in itertools.product(temperatures,betas,columns):
tguess=20
bguess=1.5
nguess=21
tguess=temperature
bguess=beta
nguess=column
flux = modified_blackbody(wavelength.to(u.Hz,u.spectral()), temperature,
beta=beta)
err = errlevel*flux.unit
p = PixelFitter()
mp = p(wavelength, flux, err)
def test_fit_cube():
"""
Performance test of cube fitting
"""
for nt,nb in zip([5,50],[5,50]):
wavelengths = ([70,160,250,350,500] * u.um).to(u.GHz, u.spectral())
#parameters = np.array([(tem,beta)
# for tem in np.linspace(15,100,nt)*u.K
# for beta in np.linspace(1,2,nb)]).reshape(2,nt,nb).T
imagecube = np.array([modified_blackbody(wavelengths, tem, beta=beta)
for tem in np.linspace(15,100,nt)*u.K
for beta in np.linspace(1,2,nb)]).reshape([wavelengths.size,nt,nb])*u.erg/u.s/u.cm**2/u.Hz
import time
tt = time.time()
result = fit_modified_blackbody_to_imagecube(imagecube.to(u.MJy).value, fits.Header(), ncores=1)
stime = (time.time()-tt)
tt = time.time()
result = fit_modified_blackbody_to_imagecube(imagecube.to(u.MJy).value, fits.Header(), ncores=4)
ptime = (time.time()-tt)
print
print 'nt,nb = %i,%i parallel map in %g secs' % (nt,nb,ptime)
print 'nt,nb = %i,%i serial map in %g secs' % (nt,nb,stime)
