def calc_one_fisher(this_info):
'''
routine called by worker bee function to do all the heavy lifting.
calculates many fisher matrices for a given array configuration
(one fishMx for each angular scale to be assessed)
'''
lam=this_info[0]
cfg_file=this_info[1]
cfg_resolution=this_info[2]
min_resolution=this_info[3]
cfg_las=this_info[4]
beamfwhm=this_info[5]
master_norm=this_info[6]
typical_err=this_info[7]
n_samps=this_info[8]
do_constSurfBright=this_info[9]
mytag=this_info[10]
if do_constSurfBright:
print "SURFACE BRIGHTNESS of components held fixed"
else:
print "TOTAL FLUX density of components held fixed"
parvec=sp.array([master_norm,cfg_resolution,cfg_resolution,cfg_resolution,cfg_resolution,25.0*sp.pi/180.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle - last is deg others rad.
# initialize variables
norm_snr=sp.zeros(n_samps)
fwhm_snr=sp.zeros(n_samps)
fwhm2_snr=sp.zeros(n_samps)
pos_err0=sp.zeros(n_samps)
pos_err1=sp.zeros(n_samps)
angle_err=sp.zeros(n_samps)
nzeros=sp.zeros(n_samps,dtype=sp.int_)
# go from resolution/5 to LAS*2
#min_scale=cfg_resolution*0.1
min_scale=min_resolution*0.05
max_scale=cfg_las*2.5
# compute range of models to consider-
step_size=(max_scale-min_scale)/n_samps
signal_fwhm= (sp.arange(n_samps)*step_size+step_size)
# this will return the uv baselines in inverse radians-
bl=tv.getbaselines(cfg_file,lam=lam)
# loop over gaussian component sizes-
print '***',step_size,max_scale,min_scale,cfg_file
if do_constSurfBright:
mystring='-constSB_2'
else:
mystring='-constFlux_2'
test_delta = tv.create_delta_vec(parvec,parvec)
print " *** Representative deltas: {}".format(test_delta)
# save (signal_fwhm,norm_snr, fwhm_snr) here
fh=open(cfg_file+mytag+mystring+'.parErrs.txt','w',1)
for i in range(n_samps):
parvec[3] = signal_fwhm[i] * 1.05
parvec[4] = signal_fwhm[i] / 1.05
if do_constSurfBright:
# normalize total flux so that master_norm is the flux in mJy
# of a component with 1" FWHM - note signal_fwhm here
# is in radians
parvec[0] = master_norm * (signal_fwhm[i] * 206264.8)**2
default_scales = sp.array([parvec[0],cfg_resolution,cfg_resolution,cfg_resolution,cfg_resolution,0.35])
default_par_delta = tv.create_delta_vec(parvec,default_scales)
# put telescope gain scaling in to the errors (which are in mJy)-
this_err = typical_err * (beamfwhm/2.91e-4)**2
f=tv.make_fisher_mx(bl,this_err,default_par_delta,beamfwhm,parvec,brute_force=False,flux_norm=True)
# use SVD pseudo inverse instead of direct
# inverse for stability
#finv=spla.inv(f)
finv=spla.pinv(f)
norm_snr[i]= parvec[0] / (finv[0,0])**0.5
# save position error = average 1D error-
pos_err0[i]= (finv[1,1])**0.5
pos_err1[i] = (finv[2,2])**0.5
fwhm_snr[i]= parvec[3] / (finv[3,3])**0.5
fwhm2_snr[i] = parvec[4]/ (finv[4,4])**0.5
angle_err[i]= (finv[5,5])**0.5
diags = sp.diag(finv)
nzeros[i]=diags[diags==0.0].size
dumpfile='raw_fish/f-'+cfg_file+'-'+mytag+mystring+'{}'.format(i)+'.pkl'
pickle.dump(f,open(dumpfile,"wb"))
dumpfile='raw_fish/finv-'+cfg_file+'-'+mytag+mystring+'{}'.format(i)+'.pkl'
pickle.dump(finv,open(dumpfile,"wb"))
outstr='{0:d} {1:.5e} {2:.5e} {3:.5e} {4:.5e} {5:.5e} {6:.5e} {7:.5e} {8:.5e} {9:d}'.format(i,signal_fwhm[i],beamfwhm,norm_snr[i],fwhm_snr[i],fwhm2_snr[i],angle_err[i],pos_err0[i],pos_err1[i],nzeros[i])
fh.write(outstr+'\n')
print cfg_file,outstr
fh.close()
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle - last is deg others rad.
# initialize variables
norm_snr = sp.zeros(n_samps)
fwhm_snr = sp.zeros(n_samps)
fwhm2_snr = sp.zeros(n_samps)
pos_err0 = sp.zeros(n_samps)
pos_err1 = sp.zeros(n_samps)
# go from resolution/5 to LAS*2
#min_scale=cfg_resolution[j]*0.1
min_scale = min_resolution * 0.05
max_scale = cfg_las[j] * 2.5
# compute range of models to consider-
step_size = (max_scale - min_scale) / n_samps
signal_fwhm = (sp.arange(n_samps) * step_size + step_size)
# this will return the uv baselines in inverse radians-
bl = tv.getbaselines(cfg_files[j], lam=lam)
# loop over gaussian component sizes-
print '***', j, step_size, max_scale, min_scale, cfg_files[j]
for i in range(n_samps):
parvec[3] = signal_fwhm[i] * 1.05
parvec[4] = signal_fwhm[i] / 1.05
if do_constSurfBright:
# normalize total flux so that master_norm is the flux in mJy
# of a component with 1" FWHM - note signal_fwhm here
# is in radians
parvec[0] = master_norm * (signal_fwhm[i] * 206264.8)**2
# set default deltas for calculating the numerical derivative
# default to 1% for nonzero params; 0.1xsynth beam for positions;
# and 0.5 deg for the axis angle-
default_par_delta = sp.copy(parvec * 0.01)
default_par_delta[1] = cfg_resolution[j] * 0.1
def calc_one_fisher(this_info):
'''
routine called by worker bee function to do all the heavy lifting.
'''
lam = this_info[0]
cfg_file = this_info[1]
cfg_resolution = this_info[2]
min_resolution = this_info[3]
cfg_las = this_info[4]
beamfwhm = this_info[5]
master_norm = this_info[6]
typical_err = this_info[7]
n_samps = this_info[8]
do_constSurfBright = this_info[9]
if do_constSurfBright:
print "SURFACE BRIGHTNESS of components held fixed"
else:
print "TOTAL FLUX density of components held fixed"
deltax = beamfwhm * 0.01
parvec = sp.array(
[master_norm, deltax, deltax, cfg_resolution, cfg_resolution, 10.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle - last is deg others rad.
# initialize variables
norm_snr = sp.zeros(n_samps)
fwhm_snr = sp.zeros(n_samps)
fwhm2_snr = sp.zeros(n_samps)
pos_err0 = sp.zeros(n_samps)
pos_err1 = sp.zeros(n_samps)
angle_err = sp.zeros(n_samps)
# go from resolution/5 to LAS*2
#min_scale=cfg_resolution*0.1
min_scale = min_resolution * 0.05
max_scale = cfg_las * 2.5
# compute range of models to consider-
step_size = (max_scale - min_scale) / n_samps
signal_fwhm = (sp.arange(n_samps) * step_size + step_size)
# this will return the uv baselines in inverse radians-
bl = tv.getbaselines(cfg_file, lam=lam)
# loop over gaussian component sizes-
print '***', step_size, max_scale, min_scale, cfg_file
for i in range(n_samps):
parvec[3] = signal_fwhm[i] * 1.05
parvec[4] = signal_fwhm[i] / 1.05
if do_constSurfBright:
# normalize total flux so that master_norm is the flux in mJy
# of a component with 1" FWHM - note signal_fwhm here
# is in radians
parvec[0] = master_norm * (signal_fwhm[i] * 206264.8)**2
# set default deltas for calculating the numerical derivative
# default to 1% for nonzero params; 0.1xsynth beam for positions;
# and 0.5 deg for the axis angle-
default_par_delta = sp.copy(parvec * 0.01)
default_par_delta[1] = cfg_resolution * 0.1
default_par_delta[2] = cfg_resolution * 0.1
default_par_delta[5] = 0.5
# put telescope gain scaling in to the errors (which are in mJy)-
this_err = typical_err * (beamfwhm / 2.91e-4)**2
f = tv.make_fisher_mx(bl,
this_err,
default_par_delta,
beamfwhm,
parvec,
brute_force=False,
flux_norm=True)
# use SVD pseudo inverse instead of direct
# inverse for stability
#finv=spla.inv(f)
finv = spla.pinv(f)
norm_snr[i] = parvec[0] / (finv[0, 0])**0.5
# save position error = average 1D error-
pos_err0[i] = (finv[1, 1])**0.5
pos_err1[i] = (finv[2, 2])**0.5
fwhm_snr[i] = parvec[3] / (finv[3, 3])**0.5
fwhm2_snr[i] = parvec[4] / (finv[4, 4])**0.5
angle_err[i] = (finv[5, 5])**0.5
print cfg_file, i, norm_snr[i], fwhm_snr[i], pos_err0[i]
# save fisher mx i here
# save (signal_fwhm,norm_snr, fwhm_snr) here
if do_constSurfBright:
mystring = '-constSB'
else:
mystring = '-constFlux'
fh = open(cfg_file + mystring + '.parErrs.txt', 'w')
for i in range(n_samps):
outstr = '{0:.3e} {1:.3e} {2:.3e} {3:.4e} {3:.4e} {4:.3e} {4:.3e} {4:.3e}'.format(
signal_fwhm[i], beamfwhm, norm_snr[i], fwhm_snr[i], fwhm2_snr[i],
angle_err[i], pos_err0[i], pos_err1[i])
fh.write(outstr + '\n')
fh.close()
#b3=tv.getbaselines('c40-3n.cfg',lam=lam)
#b4=tv.getbaselines('c40-4n.cfg',lam=lam)
#b5=tv.getbaselines('c40-5n.cfg',lam=lam)
#b6=tv.getbaselines('c40-6n.cfg',lam=lam)
#b7=tv.getbaselines('c40-7n2.cfg',lam=lam)
#b8=tv.getbaselines('c40-8n2.cfg',lam=lam)
#b9=tv.getbaselines('c40-9n2.cfg',lam=lam)
#baca=tv.getbaselines('aca.std10.cfg',lam=lam)
filelist = [
'aca.std10.cfg', 'c40-1n.cfg', 'c40-2n.cfg', 'c40-3n.cfg', 'c40-4n.cfg',
'c40-5n.cfg', 'c40-6n.cfg', 'c40-7n2.cfg', 'c40-8n2.cfg', 'c40-9n2.cfg'
]
for ff in filelist:
b = tv.getbaselines(ff, lam=lam)
lasmin = 0.5 / (b['qspecial'])[0] * 206265.
las5 = 0.5 / (b['qspecial'])[1] * 206265.
las10 = 0.5 / (b['qspecial'])[2] * 206265.
print ff, ' ', lasmin, ' ', las5, ' ', las10
### RESULTS - 100GHz; 0.5 lambda/B_min , 0.5 lam/B_5 , 0.5 lam/B_10
#
#aca.std10.cfg 34.8 34.1 32.2
#c40-1n.cfg 20.6 14.6 11.2
#c40-2n.cfg 20.5 11.2 8.0
#c40-3n.cfg 20.5 6.9 5.1
#c40-4n.cfg 20.5 4.5 3.2
#c40-5n.cfg 18.5 3.0 1.9
#c40-6n.cfg 20.2 1.56 1.11
#c40-7n2.cfg 3.80 0.82 0.65
i_poserr=7
i_pos2err=8
i_zeros=9
c1=pl.genfromtxt('c40-1n.cfgnew-constFlux_2.parErrs.txt')
c2=pl.genfromtxt('c40-2n.cfgnew-constFlux_2.parErrs.txt')
c3=pl.genfromtxt('c40-3n.cfgnew-constFlux_2.parErrs.txt')
c4=pl.genfromtxt('c40-4n.cfgnew-constFlux_2.parErrs.txt')
c5=pl.genfromtxt('c40-5n.cfgnew-constFlux_2.parErrs.txt')
c6=pl.genfromtxt('c40-6n.cfgnew-constFlux_2.parErrs.txt')
c7=pl.genfromtxt('c40-7n2.cfgnew-constFlux_2.parErrs.txt')
c8=pl.genfromtxt('c40-8n2.cfgnew-constFlux_2.parErrs.txt')
c9=pl.genfromtxt('c40-9n2.cfgnew-constFlux_2.parErrs.txt')
lam=3e8/(100e9)
b1=tv.getbaselines('c40-1n.cfg',lam=lam)
b2=tv.getbaselines('c40-2n.cfg',lam=lam)
b3=tv.getbaselines('c40-3n.cfg',lam=lam)
b4=tv.getbaselines('c40-4n.cfg',lam=lam)
b5=tv.getbaselines('c40-5n.cfg',lam=lam)
b6=tv.getbaselines('c40-6n.cfg',lam=lam)
b7=tv.getbaselines('c40-7n2.cfg',lam=lam)
b8=tv.getbaselines('c40-8n2.cfg',lam=lam)
b9=tv.getbaselines('c40-9n2.cfg',lam=lam)
sbfac = sp.ones(c1[:,0].size)
# or
sbfac = sp.ones(c1[:,0].size) * (c1[:,i_theta]/c1[5,i_pb])**2 * 10
##########################
#
filelist = [
"aca.std10.cfg",
"c40-1n.cfg",
"c40-2n.cfg",
"c40-3n.cfg",
"c40-4n.cfg",
"c40-5n.cfg",
"c40-6n.cfg",
"c40-7n2.cfg",
"c40-8n2.cfg",
"c40-9n2.cfg",
]
for ff in filelist:
b = tv.getbaselines(ff, lam=lam)
lasmin = 0.5 / (b["qspecial"])[0] * 206265.0
las5 = 0.5 / (b["qspecial"])[1] * 206265.0
las10 = 0.5 / (b["qspecial"])[2] * 206265.0
print ff, " ", lasmin, " ", las5, " ", las10
### RESULTS - 100GHz; 0.5 lambda/B_min , 0.5 lam/B_5 , 0.5 lam/B_10
#
# aca.std10.cfg 34.8 34.1 32.2
# c40-1n.cfg 20.6 14.6 11.2
# c40-2n.cfg 20.5 11.2 8.0
# c40-3n.cfg 20.5 6.9 5.1
# c40-4n.cfg 20.5 4.5 3.2
# c40-5n.cfg 18.5 3.0 1.9
# c40-6n.cfg 20.2 1.56 1.11
# c40-7n2.cfg 3.80 0.82 0.65
# loop over configurations
for j in range(n_configs):
parvec=sp.array([master_norm,0.0,0.0,cfg_resolution[j],cfg_resolution[j],0.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle
# initialize variables
norm_snr=sp.zeros(n_samps)
fwhm_snr=sp.zeros(n_samps)
pos_err=sp.zeros(n_samps)
# go from resolution/5 to LAS*2
min_scale=cfg_resolution[j]*0.1
max_scale=cfg_las[j]*2.5
# compute range of models to consider-
step_size=(max_scale-min_scale)/n_samps
signal_fwhm= (sp.arange(n_samps)*step_size+step_size)
# this will return the uv baselines in inverse radians-
bl=tv.getbaselines(cfg_files[j],lam=lam)
# loop over gaussian component sizes-
print '***',j,step_size,max_scale,min_scale,cfg_files[j]
for i in range(n_samps):
parvec[3] = signal_fwhm[i]
parvec[4] = signal_fwhm[i]
# set default deltas for calculating the numerical derivative
# default to 1% for nonzero params; 0.1xsynth beam for positions;
# and 0.5 deg for the axis angle-
default_par_delta=sp.copy(parvec*0.01)
default_par_delta[1]=cfg_resolution[j]*0.1
default_par_delta[2]=cfg_resolution[j]*0.1
default_par_delta[5]=0.5
f=tv.make_fisher_mx(bl,typical_err,default_par_delta,beamfwhm[j],parvec,brute_force=False,flux_norm=True)
finv=spla.inv(f)
norm_snr[i]= parvec[0] / (finv[0,0])**0.5
import scipy.linalg as spla
import scipy as sp
import testvis as tv
nu=100.0
lam=3e8/(nu*1e9)
# this will return the uv baselines in inverse radians-
bl=tv.getbaselines('Alma_cycle1_2.cfg.txt',lam=lam)
# beam fwhm in rad- (B3 alma) - 1' fwhm = 2.91e-4 radians fwhm
beamfwhm=2.91e-4
parvec=sp.array([0.01,0.0,0.0,2e-5,2e-5,0.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle
parvec += 1e-9
print tv.visval(beamfwhm,0,0,parvec[0],parvec[1],parvec[2],parvec[3],parvec[4],parvec[5],brute_force=False)
# this is a typical visibility value. set the error in make_fisher_mx to something of this order
signal_fwhm= (sp.arange(100)*0.02+0.02) * beamfwhm
norm_snr=sp.zeros(100)
fwhm_snr=sp.zeros(100)
for i in range(100):
parvec[3] = signal_fwhm[i]
parvec[4] = signal_fwhm[i]
f=tv.make_fisher_mx(bl,1e-12,0.01,beamfwhm,parvec,brute_force=False)
finv=spla.inv(f)
norm_snr[i]= parvec[0] / (finv[0,0])**0.5
fwhm_snr[i]= parvec[3] / (finv[3,3])**0.5
import scipy.linalg as spla
import scipy as sp
import testvis as tv
nu = 100.0
lam = 3e8 / (nu * 1e9)
# this will return the uv baselines in inverse radians-
bl = tv.getbaselines('Alma_cycle1_2.cfg.txt', lam=lam)
# beam fwhm in rad- (B3 alma) - 1' fwhm = 2.91e-4 radians fwhm
beamfwhm = 2.91e-4
parvec = sp.array([0.01, 0.0, 0.0, 2e-5, 2e-5, 0.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle
parvec += 1e-9
print tv.visval(beamfwhm,
0,
0,
parvec[0],
parvec[1],
parvec[2],
parvec[3],
parvec[4],
parvec[5],
brute_force=False)
# this is a typical visibility value. set the error in make_fisher_mx to something of this order
signal_fwhm = (sp.arange(100) * 0.02 + 0.02) * beamfwhm
norm_snr = sp.zeros(100)
fwhm_snr = sp.zeros(100)
cfg_las = sp.array([25.0,25.0,25.0,10.0,8.0,5.0,1.5,1.1])*3.1415/180.0/3600.0
# beam fwhm in rad- (B3 alma) - 1' fwhm = 2.91e-4 radians fwhm
beamfwhm= sp.array([2.91e-4,2.91e-4,2.91e-4,2.91e-4,2.91e-4,2.91e-4,2.91e-4,])*(100.0/nu)
# TBD - the ACA one crashed for some reason :/
# keep integrated flux density of Gaussian constant as the size of the Gaussina changes?
do_const_flux=True
# get some typical #s...
# master normalization
master_norm=1.0
ref_cfg=4
parvec=sp.array([master_norm,0.0,0.0,cfg_resolution[ref_cfg],cfg_resolution[ref_cfg],0.0])
if do_const_flux:
parvec[0] = master_norm / (parvec[3]*parvec[4])
bl=tv.getbaselines(cfg_files[ref_cfg],lam=lam)
typical_q = sp.median(bl['q'])*0.7
# compute a typical visibility value and use it as typical error (SNR per vis = 1)
#typical_err=sp.median(abs(tv.visval(beamfwhm[ref_cfg],typical_q,typical_q,parvec[0],parvec[1],parvec[2],parvec[3],parvec[4],parvec[5],brute_force=False)))
# assuming 1 mJy typical error per visibility
typical_err = 1.0
# number of x-axis samples at which to evaluate the parameter uncertainties of interest-
n_samps=100
# n_configs=1
# loop over configurations
for j in range(n_configs):
parvec=sp.array([master_norm,0.0,0.0,cfg_resolution[j],cfg_resolution[j],0.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle
if do_const_flux:
parvec[0] = master_norm / (parvec[3]*parvec[4])
def calc_one_fisher(this_info):
'''
routine called by worker bee function to do all the heavy lifting.
'''
lam=this_info[0]
cfg_file=this_info[1]
cfg_resolution=this_info[2]
min_resolution=this_info[3]
cfg_las=this_info[4]
beamfwhm=this_info[5]
master_norm=this_info[6]
typical_err=this_info[7]
n_samps=this_info[8]
do_constSurfBright=this_info[9]
if do_constSurfBright:
print "SURFACE BRIGHTNESS of components held fixed"
else:
print "TOTAL FLUX density of components held fixed"
deltax=beamfwhm * 0.01
parvec=sp.array([master_norm,deltax,deltax,cfg_resolution,cfg_resolution,10.0])
# param order is - norm,l0,m0,fwhm_1,fwhm_2,axis_angle - last is deg others rad.
# initialize variables
norm_snr=sp.zeros(n_samps)
fwhm_snr=sp.zeros(n_samps)
fwhm2_snr=sp.zeros(n_samps)
pos_err0=sp.zeros(n_samps)
pos_err1=sp.zeros(n_samps)
angle_err=sp.zeros(n_samps)
# go from resolution/5 to LAS*2
#min_scale=cfg_resolution*0.1
min_scale=min_resolution*0.05
max_scale=cfg_las*2.5
# compute range of models to consider-
step_size=(max_scale-min_scale)/n_samps
signal_fwhm= (sp.arange(n_samps)*step_size+step_size)
# this will return the uv baselines in inverse radians-
bl=tv.getbaselines(cfg_file,lam=lam)
# loop over gaussian component sizes-
print '***',step_size,max_scale,min_scale,cfg_file
for i in range(n_samps):
parvec[3] = signal_fwhm[i] * 1.05
parvec[4] = signal_fwhm[i] / 1.05
if do_constSurfBright:
# normalize total flux so that master_norm is the flux in mJy
# of a component with 1" FWHM - note signal_fwhm here
# is in radians
parvec[0] = master_norm * (signal_fwhm[i] * 206264.8)**2
# set default deltas for calculating the numerical derivative
# default to 1% for nonzero params; 0.1xsynth beam for positions;
# and 0.5 deg for the axis angle-
default_par_delta=sp.copy(parvec*0.01)
default_par_delta[1]=cfg_resolution*0.1
default_par_delta[2]=cfg_resolution*0.1
default_par_delta[5]=0.5
# put telescope gain scaling in to the errors (which are in mJy)-
this_err = typical_err * (beamfwhm/2.91e-4)**2
f=tv.make_fisher_mx(bl,this_err,default_par_delta,beamfwhm,parvec,brute_force=False,flux_norm=True)
# use SVD pseudo inverse instead of direct
# inverse for stability
#finv=spla.inv(f)
finv=spla.pinv(f)
norm_snr[i]= parvec[0] / (finv[0,0])**0.5
# save position error = average 1D error-
pos_err0[i]= (finv[1,1])**0.5
pos_err1[i] = (finv[2,2])**0.5
fwhm_snr[i]= parvec[3] / (finv[3,3])**0.5
fwhm2_snr[i] = parvec[4]/ (finv[4,4])**0.5
angle_err[i]= (finv[5,5])**0.5
print cfg_file,i, norm_snr[i],fwhm_snr[i],pos_err0[i]
# save fisher mx i here
# save (signal_fwhm,norm_snr, fwhm_snr) here
if do_constSurfBright:
mystring='-constSB'
else:
mystring='-constFlux'
fh=open(cfg_file+mystring+'.parErrs.txt','w')
for i in range(n_samps):
outstr='{0:.3e} {1:.3e} {2:.3e} {3:.4e} {3:.4e} {4:.3e} {4:.3e} {4:.3e}'.format(signal_fwhm[i],beamfwhm,norm_snr[i],fwhm_snr[i],fwhm2_snr[i],angle_err[i],pos_err0[i],pos_err1[i])
fh.write(outstr+'\n')
fh.close()
