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Copy pathfuncs_DConeMaps.noMerid.py
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funcs_DConeMaps.noMerid.py
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import sys
import numpy as np
import scipy as sp
import os
import os.path
from scipy import ndimage
from astropy.io import fits as pf
import re
from copy import deepcopy
from astropy.wcs import WCS
from scipy import optimize
import time
from time import gmtime,strftime
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from pylab import *
import matplotlib.colors as colors
include_path='/Users/simon/common/python/include/'
sys.path.append(include_path)
from Resamp import gridding
if not sys.warnoptions:
import os, warnings
#warnings.simplefilter("default") # Change the filter in this process
warnings.simplefilter("ignore") # Change the filter in this process
#os.environ["PYTHONWARNINGS"] = "default" # Also affect subprocesses
os.environ["PYTHONWARNINGS"] = "ignore" # Also affect subprocesses
def cartesian2conicpolar(outcoords, inputshape, origin, inc=0.,tanpsi=0.):
"""Coordinate transform for converting a polar array to Cartesian coordinates.
inputshape is a tuple containing the shape of the polar array. origin is a
tuple containing the x and y indices of where the origin should be in the
output array."""
rindex, thetaindex = outcoords
x0, y0 = origin
theta = float(thetaindex) * 2. * np.pi / float(inputshape[0])
y = rindex*np.cos(theta)
height = tanpsi * rindex
#height = -tanpsi * rindex
x = (rindex*np.sin(theta))/np.cos(inc) + \
(height - (rindex*np.sin(theta))*np.tan(inc))*np.sin(inc)
ix = -x + x0
iy = y + float(y0)
return (iy,ix)
def cartesian2polar(outcoords, inputshape, origin, inc=0.):
"""Coordinate transform for converting a polar array to Cartesian coordinates.
inputshape is a tuple containing the shape of the polar array. origin is a
tuple containing the x and y indices of where the origin should be in the
output array."""
rindex, thetaindex = outcoords
x0, y0 = origin
theta = float(thetaindex) * 2. * np.pi / float(inputshape[0]-1.)
y = rindex*np.cos(theta)
x = rindex*np.sin(theta)*np.cos(inc)
ix = -x + x0
iy = y + float(y0)
return (iy,ix)
def conicpolar2cartesian_ellipse(outcoords, inputshape, origin,inc=0.,tanpsi=0.):
yindex, xindex = outcoords
x0, y0 = origin
nx=inputshape[0]
ny=inputshape[1]
x = -float(xindex - x0)
y = float(yindex - y0)
tanpsi0=tanpsi
a=((np.tan(inc) * tanpsi0)**2-1.0)
b=-2.*x*np.sin(inc)* tanpsi0/(np.cos(inc))**2
c=y**2+(x**2/(np.cos(inc)**2))
Delta=b**2-4.*a*c
rho=(-b-np.sqrt(Delta))/(2.*a)
rindex = rho
if (rho == 0.):
costheta = 0.
else:
costheta = y / rho
theta=np.arccos(costheta)
thetaindex = (theta * float(nx) / (2. * np.pi))
return (rindex,thetaindex)
def polar2cartesian(outcoords, inputshape, origin,inc=0.):
yindex, xindex = outcoords
x0, y0 = origin
nx=inputshape[0]-1
ny=inputshape[1]-1
x = -float(xindex - x0)
y = float(yindex - y0)
rho=np.sqrt((x**2/(np.cos(inc)**2))+y**2)
rindex = rho
if (rho == 0.):
costheta = 0.
else:
costheta = y / rho
# theta=np.arccos(costheta)
theta = np.arctan2((-x/np.cos(inc)), y)
if (theta < 0):
theta = theta + 2.*np.pi
thetaindex = (theta * float(nx) / (2. * np.pi))
return (rindex,thetaindex)
# def exec_flatpolar(filename_fullim,hdr2,aresampim,PA,cosi):
# rotangle= PA - 180.
# # rotangle= PA
# im1rot = ndimage.rotate(aresampim, rotangle, reshape=False)
# fileout_rotated=re.sub('fullim.fits', 'rotated.fits', filename_fullim)
# pf.writeto(fileout_rotated,im1rot, hdr2, overwrite=True)
#
#
# hdr3 = deepcopy(hdr2)
# hdr3['CDELT1']=hdr3['CDELT1']*cosi
# fileout_stretched=re.sub('fullim.fits', 'stretched.fits', filename_fullim)
# im3=np.double(gridding(fileout_rotated,hdr3))
# pf.writeto(fileout_stretched,im3, hdr2, overwrite=True)
#
#
# nx=hdr2['NAXIS1']
# ny=hdr2['NAXIS2']
#
# aim_polar = sp.ndimage.geometric_transform(im3,cartesian2polar,
# order=1,
# output_shape = (im3.shape[0], im3.shape[1]),
# extra_keywords = {'inputshape':im3.shape,
# 'origin':(((float(nx)+1.)/2.)-1.,((float(ny)+1.)/2.)-1.)})
#
# return aim_polar
def carttoconicpolar(im,inc,tanpsi):
(ny,nx)=im.shape
(i0,j0)=(((float(nx)+1.)/2.)-1.,((float(ny)+1.)/2.)-1.)
im_polar = sp.ndimage.geometric_transform(im,cartesian2conicpolar,
order=1,
output_shape = (im.shape[0], im.shape[1]),
extra_keywords = {
'inputshape':im.shape,
'inc':inc,'tanpsi':tanpsi,
'origin':(i0,j0)})
return im_polar
def carttopolar(im,inc):
(ny,nx)=im.shape
(i0,j0)=(((float(nx)+1.)/2.)-1.,((float(ny)+1.)/2.)-1.)
im_polar = sp.ndimage.geometric_transform(im,cartesian2polar,
order=1,
output_shape = (im.shape[0], im.shape[1]),
extra_keywords = {
'inputshape':im.shape,
'inc':inc,
'origin':(i0,j0)})
return im_polar
def conicpolartocart(im_polar,inc,tanpsi):
(ny,nx)=im_polar.shape
(i0,j0)=(((float(nx)+1.)/2.)-1.,((float(ny)+1.)/2.)-1.)
im_cart = sp.ndimage.geometric_transform(im_polar,conicpolar2cartesian_ellipse,
order=1,
output_shape = (im_polar.shape[0], im_polar.shape[1]),
extra_keywords = {'inputshape':im_polar.shape,
'inc':inc,'tanpsi':tanpsi,
'origin':(i0,j0)})
im_cart=np.nan_to_num(im_cart)
return im_cart
def polartocart(im_polar,inc):
(ny,nx)=im_polar.shape
(i0,j0)=(((float(nx)+1.)/2.)-1.,((float(ny)+1.)/2.)-1.)
im_cart = sp.ndimage.geometric_transform(im_polar,polar2cartesian,
order=1,
output_shape = (im_polar.shape[0], im_polar.shape[1]),
extra_keywords = {'inputshape':im_polar.shape,
'inc':inc,
'origin':(i0,j0)})
im_cart=np.nan_to_num(im_cart)
return im_cart
def exec_prep_files(M):
filename_source=M.filename_source
workdir=M.workdir
DumpAllFitsFiles=M.DumpAllFitsFiles
inbasename=os.path.basename(filename_source)
filename_fullim=re.sub('.fits', '_fullim.fits', inbasename)
filename_fullim=workdir+filename_fullim
if (M.DoErrorMap):
inbasenameerr=os.path.basename(M.filename_errormap)
filename_fullimerr=re.sub('.fits', '_fullim.fits', inbasenameerr)
filename_fullimerr=workdir+filename_fullimerr
filename_fullimw=re.sub('.fits', '_fullimw.fits', inbasenameerr)
filename_fullimw=workdir+filename_fullimw
if (M.Verbose): #
print( "BUILDING WORKDIR AND GENERATING CENTERED IMAGE")
hdu = pf.open(filename_source)
hdr0=hdu[0].header
if (hdr0['NAXIS'] > 2):
if (M.Verbose): #
print( "running cube2im")
hdu=cube2im(filename_source,False)
im1=hdu[0].data
im1=im1*M.unitscale
print( "applied unit scale factor:",M.unitscale)
hdr1=hdu[0].header
typicalerror=M.ExpectedError
if (M.InjectNoise):
print( "INJECTING NOISE")
im1=im1 + np.random.normal(loc=0.0, scale=typicalerror, size=im1.shape)
if (DumpAllFitsFiles):
pf.writeto(filename_fullim,im1, hdr1, overwrite=True)
hdu[0].data=im1
hduw=False
if (M.DoErrorMap):
hduerr = pf.open(M.filename_errormap)
hdrerr = hduerr[0].header
if (hdrerr['NAXIS'] > 2):
hduerr=cube2im(M.filename_errormap,False)
imerr1=hduerr[0].data
imerr1=imerr1*M.unitscale
#typicalerror=np.median(imerr1)
#imerr1[np.where(imerr1 < (typicalerror/3.))] = typicalerror
#imerr1[np.where(imerr1 > (100.*typicalerror))] = 1E20
hdrerr1=hduerr[0].header
imw0=1./imerr1**2
imw0=np.nan_to_num(imw0)
imw0[np.where(np.fabs(imw0) > 1E10)] = 0.
if (M.Verbose):
print( "fullim weights: max",np.max(imw0)," min ",np.min(imw0))
imerr=np.sqrt(1./imw0)
imerr=np.nan_to_num(imerr)
imerr[np.where(np.fabs(imw0) < 1E-30)] = 1E20
typicalerror=np.median(imerr)
if (M.Verbose):
print( "resamp errors: max",np.max(imerr)," min ",np.min(imerr))
print( "typicalerror= ",typicalerror," vs", M.ExpectedError)
if (DumpAllFitsFiles):
pf.writeto(filename_fullimw,imw0, hdrerr1, overwrite=True)
hduw=pf.PrimaryHDU()
hduw.data=imw0
hduw.header=hdrerr1
M.Hdu=hdu
M.Hduw=hduw
return
def exec_grid_4center(M):
workdir=M.workdir
RA=M.RA
DEC=M.DEC
x_center=M.x_center
y_center=M.y_center
fieldscale=M.fieldscale # shrink radial field of view of polar maps by this factor
hdu=M.Hdu
hduw=M.Hduw
filename_source=M.filename_source
inbasename=os.path.basename(filename_source)
filename_fullim=re.sub('.fits', '_fullim.fits', inbasename)
filename_fullim=workdir+filename_fullim
fileout_centered=re.sub('fullim.fits', 'centered.fits', filename_fullim)
if (M.DoErrorMap):
inbasenameerr=os.path.basename(M.filename_errormap)
filename_fullimerr=re.sub('.fits', '_fullim.fits', inbasenameerr)
filename_fullimerr=workdir+filename_fullimerr
filename_fullimw=re.sub('.fits', '_fullimw.fits', inbasenameerr)
filename_fullimw=workdir+filename_fullimw
fileout_centerederr=re.sub('fullim.fits', 'centered.fits', filename_fullimerr)
fileout_centeredw=re.sub('fullim.fits', 'wcentered.fits', filename_fullimerr)
hdr1=hdu[0].header
if (not (isinstance(y_center,bool))):
if (not isinstance(RA,float)):
RA=hdr1['CRVAL1']
DEC=hdr1['CRVAL2']
if (M.Verbose):
print( "using center of coords CRVAL1 CRVAL2")
#RA=RA+(np.sin(x_center*np.pi/180.)*y_center/3600.)/np.cos(DEC*np.pi/180.)
RA=RA+((x_center/3600.)/np.cos(DEC*np.pi/180.))
#DEC=DEC+np.cos(x_center*np.pi/180.)*y_center/3600.
DEC=DEC+((y_center/3600.)*np.pi/180.)
if (M.Verbose):
print( "RA =", RA)
print( "DEC =",DEC)
nx=int(hdr1['NAXIS1']/(M.pixscale_factor*M.fieldscale))
ny=nx
if ( (nx % 2) == 0):
nx=nx+1
ny=ny+1
hdr2 = deepcopy(hdr1)
hdr2['NAXIS1']=nx
hdr2['NAXIS2']=ny
hdr2['CRPIX1']=(nx+1)/2
hdr2['CRPIX2']=(ny+1)/2
hdr2['CRVAL1']=RA
hdr2['CRVAL2']=DEC
hdr2['CDELT1']=M.pixscale_factor*hdr2['CDELT1']
hdr2['CDELT2']=M.pixscale_factor*hdr2['CDELT2']
resamp=gridding(hdu,hdr2, fullWCS=False)
resamp=np.nan_to_num(resamp)
if (M.DumpAllFitsFiles):
fileout_centered=re.sub('fullim.fits', 'centered.fits', filename_fullim)
pf.writeto(fileout_centered,resamp, hdr2, overwrite=True)
hducentered=pf.PrimaryHDU()
hducentered.data=resamp
hducentered.header=hdr2
hduwcentered=False
if (M.DoErrorMap):
resampw=gridding(hduw,hdr2, fullWCS=False)
resampw=np.nan_to_num(resampw)
resampw[np.where(resampw < 0.)] =0.
if (M.Verbose): #
print( "resamp weights: max",np.max(resampw)," min ",np.min(resampw))
resamperr=np.sqrt(1./resampw)
if (M.DumpAllFitsFiles):
fileout_centeredw=re.sub('fullim.fits', 'wcentered.fits', filename_fullimerr)
pf.writeto(fileout_centeredw,resampw, hdr2, overwrite=True)
fileout_centerederr=re.sub('fullim.fits', 'centered.fits', filename_fullimerr)
pf.writeto(fileout_centerederr,resamperr, hdr2, overwrite=True)
hduwcentered=pf.PrimaryHDU()
hduwcentered.data=resampw
hduwcentered.header=hdr2
M.Ncorr=(np.pi/(4.*np.log(2)))*M.bmaj*M.bmin/(hdr2['CDELT2']*3600.)**2
M.Hducentered=hducentered
M.Hduwcentered=hduwcentered
def exec_conicpolar_expansions(M):
filename_source=M.filename_source
workdir=M.workdir
inc=M.inc
tanpsi=M.tanpsi
RA=M.RA
DEC=M.DEC
x_center=M.x_center
y_center=M.y_center
DoAzimuthalProfile=M.DoAzimuthalProfile
PlotRadialProfile=M.PlotRadialProfile
a_min=M.a_min
a_max=M.a_max
ExpectedError=M.ExpectedError
InjectNoise=M.InjectNoise
DumpAllFitsFiles=M.DumpAllFitsFiles
DoDCone=M.DoDCone
domain=M.domain
fieldscale=M.fieldscale # shrink radial field of view of polar maps by this factor
DoAccr=M.DoAccr
hdu=M.Hducentered
hduw=M.Hduwcentered
typicalerror=ExpectedError
#cosi=np.cos(inc*np.pi/ 180.)
inbasename=os.path.basename(filename_source)
filename_fullim=re.sub('.fits', '_fullim.fits', inbasename)
filename_fullim=workdir+filename_fullim
fileout_centered=re.sub('fullim.fits', 'centered.fits', filename_fullim)
if (M.DoErrorMap):
inbasenameerr=os.path.basename(M.filename_errormap)
filename_fullimerr=re.sub('.fits', '_fullim.fits', inbasenameerr)
filename_fullimerr=workdir+filename_fullimerr
filename_fullimw=re.sub('.fits', '_fullimw.fits', inbasenameerr)
filename_fullimw=workdir+filename_fullimw
fileout_centerederr=re.sub('fullim.fits', 'centered.fits', filename_fullimerr)
fileout_centeredw=re.sub('fullim.fits', 'wcentered.fits', filename_fullimerr)
resamp=hdu.data
hdr2=hdu.header
nx=hdr2['NAXIS1']
ny=hdr2['NAXIS2']
if M.Verbose:
print( "M.Ncorr = ",M.Ncorr)
if (M.DoErrorMap):
resampw=hduw.data
if (M.InheritMumap):
if (M.mumap is None):
mumap=np.ones(resamp.shape)
else:
mumap=M.mumap
else:
mumap=np.ones(resamp.shape)
#rotangle= M.PA - 180.
rotangle= M.PA
im1rot = ndimage.rotate(resamp, rotangle, reshape=False)
hdr3 = deepcopy(hdr2)
im3=np.double(im1rot)
if (DumpAllFitsFiles):
fileout_rotated=re.sub('fullim.fits', 'rotated.fits', filename_fullim)
pf.writeto(fileout_rotated,im1rot, hdr2, overwrite=True)
if (M.DoErrorMap):
if (np.any(resampw < 0.)):
print("min / max:",np.min(resampw),np.max(resampw))
sys.exit("negative sky weights!!!!")
im1rotw = ndimage.rotate(resampw, rotangle, reshape=False,order=0)
im3w=np.double(im1rotw)
if (DumpAllFitsFiles):
fileout_rotatedw=re.sub('fullim.fits', 'wrotated.fits', filename_fullimerr)
pf.writeto(fileout_rotatedw,im1rotw, hdr2, overwrite=True)
if (np.any(im1rotw < 0.)):
print("min / max:",np.min(im1rotw),np.max(im1rotw))
sys.exit("negative rot sky weights!!!!")
# #####################################################################
# take conic polar transforms
if (M.Verbose):
print( "CARTESIAN2CONICPOLAR TRANSFORM START")
print( "using inc ",inc*np.pi/180.," tanpsi ",tanpsi)
im_polar = carttoconicpolar(im3,inc,tanpsi)
if (DoDCone):
mumap_polarpos = carttoconicpolar(mumap,inc,tanpsi)
nphis,nrs=im_polar.shape
if ((nphis != nx) or (nrs != ny)):
sys.exit("bug")
hdupolar = pf.PrimaryHDU()
hdupolar.data = im_polar
hdrpolar=hdupolar.header
hdrpolar['CRPIX1']=1
hdrpolar['CRVAL1']=0.
hdrpolar['CDELT1']=2. * np.pi / nphis
hdrpolar['CRPIX2']=1
hdrpolar['CRVAL2']=0.
hdrpolar['CDELT2']=(hdr3['CDELT2'])
hdupolar.header = hdrpolar
fileout_polar=re.sub('fullim.fits', 'polar.fits', filename_fullim)
if (DumpAllFitsFiles):
hdupolar.writeto(fileout_polar, overwrite=True)
if (M.DoErrorMap):
im_polarw = carttoconicpolar(im3w,inc,tanpsi)
nphis,nrs=im_polarw.shape
hdupolarw = pf.PrimaryHDU()
hdupolarw.data = im_polarw
hdupolarw.header = hdrpolar
fileout_polarw=re.sub('fullim.fits', 'wpolar.fits', filename_fullimerr)
if (DumpAllFitsFiles):
hdupolarw.writeto(fileout_polarw, overwrite=True)
else:
im_polarw=np.ones(im_polar.shape)/typicalerror**2
######################################################################
# take azimuthal averages on polar maps
weights=im_polarw.copy()
im_Npolcorr=np.ones(im_polarw.shape)
if (np.any(weights < 0.)):
print("min / max:",np.min(weights),np.max(weights))
sys.exit("negative polarweights!!")
im_polar_av = np.copy(im_polar)
rrs = 3600.*(np.arange(hdrpolar['NAXIS2'])-hdrpolar['CRPIX2']+1.0)*hdrpolar['CDELT2']+hdrpolar['CRVAL2']
phis = (180./np.pi)*((np.arange(hdrpolar['NAXIS1'])-hdrpolar['CRPIX1']+1.0)*hdrpolar['CDELT1']+hdrpolar['CRVAL1'])
phis_rad = np.double(((np.arange(hdrpolar['NAXIS1'])-hdrpolar['CRPIX1']+1.0)*hdrpolar['CDELT1']+hdrpolar['CRVAL1']))
KepAmps= np.double(np.zeros(len(rrs)))
sKepAmps= np.double(np.zeros(len(rrs)))
AccrAmps= np.double(np.zeros(len(rrs)))
sAccrAmps= np.double(np.zeros(len(rrs)))
vsysts=np.zeros(hdrpolar['NAXIS2'])
if (a_min > 0):
ia_min = np.argmin(np.abs(rrs - a_min))
if (a_max > 0):
ia_max = np.argmin(np.abs(rrs - a_max))
if (M.ComputeSystVelo):
if (M.DoErrorMap):
for irrs in range(len(rrs)):
v0_vec=im_polar[irrs,:]
w_vec=im_polarw[irrs,:]
av_v0=np.sum(w_vec*v0_vec)/np.sum(w_vec)
av_cosphi=np.sum(w_vec*np.cos(phis_rad))/np.sum(w_vec)
KepAmp = np.sum( (v0_vec - av_v0) * w_vec * np.cos(phis_rad)) / np.sum( w_vec * (np.cos(phis_rad))**2 - w_vec * np.cos(phis_rad) * av_cosphi)
vsysts[irrs]=np.sum(w_vec*(v0_vec - KepAmp*np.cos(phis_rad)))/np.sum(w_vec)
else:
for irrs in range(len(rrs)):
v0_vec=im_polar[irrs,:]
KepAmp = np.sum( (v0_vec - np.average(v0_vec)) * np.cos(phis_rad)) / np.sum( (np.cos(phis_rad))**2 - np.cos(phis_rad)* np.average(np.cos(phis_rad)))
vsysts[irrs]=np.average(v0_vec - KepAmp*np.cos(phis_rad))
vsyst=np.asscalar(np.median(vsysts[ia_min:ia_max]))
sigma_vsyst=np.asscalar(np.std(vsysts[ia_min:ia_max]))
print( "vsyst calculated = ",vsyst,"+-",sigma_vsyst)
M.vsyst=vsyst
else:
vsyst=M.vsyst
if (M.Verbose):
print( "vsyst from M = ",vsyst)
for irrs in range(len(rrs)):
v0_vec=im_polar[irrs,:]-vsyst
if (M.DoErrorMap):
w_vec=weights[irrs,:]
else:
w_vec=1/typicalerror**2
mask=(w_vec < 1E-10)
w_vec_nozeros=w_vec
w_vec_nozeros[mask]=1E-10
err_vec=(1.0/np.sqrt(w_vec_nozeros))
err_vec[mask] = 1E20 # np.inf
w_vec[mask]=0.
thisradius=rrs[irrs] #arcsec
cosi=np.cos(M.inc)
Nind=2.*np.pi*thisradius * cosi /(M.bmaj) # aprox number of beams at each radius
Nsum=len(w_vec)
Npolcorr=Nsum/Nind
if Npolcorr < 1:
Npolcorr=1.
im_Npolcorr[irrs,:]=Npolcorr
if ( (np.sum(w_vec) == 0.) or ( np.sum( w_vec * (np.cos(phis_rad))**2)**2 == 0.)):
KepAmp=0.
sKepAmp=0.
AccrAmp=0.
sAccrAmp=1E20
else:
if (M.InheritMumap):
mumap_vec=mumap_polarpos[irrs,:]
if (DoAccr):
sys.exit("Not yet programmed DoAccr with mumap")
else:
KepAmp = np.sum(w_vec* v0_vec * mumap_vec * np.cos(phis_rad)) / np.sum(w_vec * mumap_vec *(np.cos(phis_rad))**2)
AccrAmp = 0.
else:
if (DoAccr):
subsum1=np.sum(w_vec * v0_vec * np.cos(phis_rad)) / np.sum( w_vec * (np.cos(phis_rad))**2)
varsubsum1=np.sum((np.sqrt(w_vec) * np.cos(phis_rad)) / np.sum( w_vec * (np.cos(phis_rad))**2)**2)
numerator=np.sum(w_vec * np.sin(phis_rad) * (v0_vec - np.cos(phis_rad) * subsum1))
#dum1=w_vec**2 * np.sin(phis_rad)**2
##if ((~np.isfinite(varsubsum1)).any()):
## print("varsubsum1 bad values")
#dum2=np.cos(phis_rad)**2 * varsubsum1
#dum3=((err_vec)**2 + dum2)
#varnumerator=np.sum(dum1*dum3)
varnumerator=np.sum(w_vec**2 * np.sin(phis_rad)**2 * ((err_vec)**2 + np.cos(phis_rad)**2 * varsubsum1))
subsum2=np.sum(w_vec * np.sin(phis_rad) * np.cos(phis_rad)) / np.sum( w_vec * (np.cos(phis_rad))**2)
denom=np.sum(w_vec * ( (np.sin(phis_rad))**2 - subsum2))
AccrAmp=numerator/denom
sAccrAmp=np.sqrt(varnumerator)/denom
KepAmp = np.sum(w_vec * (v0_vec - AccrAmp*np.sin(phis_rad)) * np.cos(phis_rad)) / np.sum(w_vec * (np.cos(phis_rad))**2)
sKdenom=np.sum(w_vec * (np.cos(phis_rad))**2)
varKnum=np.sum( w_vec**2 * (err_vec**2 + sAccrAmp**2 * np.sin(phis_rad)**2) * np.cos(phis_rad)**2)
sKnum=np.sqrt(varKnum)
sKepAmp = sKnum/sKdenom
#print("sKepAmp>",rrs[irrs],KepAmp, varKnum, sKnum,sKdenom, sKepAmp, sAccrAmp)
sAccrAmp *= np.sqrt(Npolcorr)
sKepAmp *= np.sqrt(Npolcorr)
else:
denom=np.sum(w_vec * (np.cos(phis_rad))**2)
numerator = np.sum(w_vec* v0_vec * np.cos(phis_rad))
KepAmp = numerator / denom
sdenom=np.sqrt(np.sum(w_vec * (np.cos(phis_rad))**2))
sKepAmp = 1./sdenom
#print( "bmaj = ",M.bmaj, " thisradius ",thisradius, " inc ", M.inc ,"Nind ",Nind," Ncorr ",Ncorr, " \n")
sKepAmp *= np.sqrt(Npolcorr)
AccrAmp = 0.
sAccrAmp=0.
# else:
# v0_vec=im_polar[irrs,:]-vsyst
# KepAmp = np.sum(v0_vec * np.cos(phis_rad)) / np.sum((np.cos(phis_rad))**2)
if (M.Verbose and (KepAmp < 0.) and (irrs == int(len(rrs)/4.))):
print( "KepAmp negative, wrong PA: KepAmp=",KepAmp," PA: ",M.PA," inc",M.inc*np.pi/180.,"deg tanpsi",tanpsi )
print((np.array(zip(v0_vec,np.cos(phis_rad)))))
KepAmps[irrs] = KepAmp
sKepAmps[irrs] = sKepAmp
AccrAmps[irrs] = AccrAmp
sAccrAmps[irrs] = sAccrAmp
if (DoAccr):
v0_vec_av = KepAmp * np.cos(phis_rad) + AccrAmp * np.sin(phis_rad)
im_polar_av[irrs,:] = v0_vec_av + vsyst
else:
v0_vec_av = KepAmp * np.cos(phis_rad)
im_polar_av[irrs,:] = v0_vec_av + vsyst
v_Phi_prof = KepAmps
sv_Phi_prof = sKepAmps
v_Phi_prof = np.nan_to_num(v_Phi_prof)
sv_Phi_prof = np.nan_to_num(sv_Phi_prof)
#v_Phi_prof[np.isnan(v_Phi_prof)]=0.
#sv_Phi_prof[np.isnan(sv_Phi_prof)]=0.
v_R_prof = AccrAmps
sv_R_prof = sAccrAmps
v_R_prof = np.nan_to_num(v_R_prof)
sv_R_prof = np.nan_to_num(sv_R_prof)
#bmaj=hdr2['BMAJ']
#print( "bmaj = ",bmaj,"\n";)
#Nind=2.*np.pi*rrs /(cosi * bmaj*3600.)
#dispv_Phi_prof=sv_Phi_prof.copy()
#sv_Phi_prof=sv_Phi_prof/np.sqrt(Nind)
######################################################################
# now compute chi2 in polar coords
if (DoDCone):
imazim_far=conicpolartocart(im_polar_av,inc,-tanpsi)
im_polar_av_far_near=carttoconicpolar(imazim_far,inc,tanpsi)
for irrs in range(len(rrs)):
v0_vec=im_polar[irrs,:]-vsyst
v0_vec_m=im_polar_av[irrs,:]-vsyst
v0_vec_FN_m=im_polar_av_far_near[irrs,:]-vsyst
if (M.DoErrorMap):
w_vec=weights[irrs,:]
else:
w_vec=1./typicalerror**2
Delta_o=v0_vec - v0_vec_FN_m
Delta_m=v0_vec_m - v0_vec_FN_m
cos_vec = np.fabs(np.cos(phis_rad))
A = np.sum(w_vec * cos_vec * Delta_m * (Delta_m - Delta_o)) / np.sum(w_vec * cos_vec**2 * Delta_m**2)
if (A < 0.):
A=0.
# sys.exit("BUG")
if (A > 0.5):
#print( "setting A",A,"to 1")
A=0.5
mu_vec=(1. - A * cos_vec)
mumap_polarpos[irrs,:]=mu_vec
# testing for chi2 improvement:
TestChi2Improv=False
if TestChi2Improv:
subchi2 = np.sum(w_vec * (v0_vec - v0_vec_m)**2)
subchi2_mumap = np.sum(w_vec * (v0_vec - (v0_vec_m * mu_vec + v0_vec_FN_m * (1. -mu_vec)) )**2)
flag=''
if (subchi2_mumap > subchi2):
flag='<<'
print(("irrs %d irrs r %f A %f chi2 %f chi2_mu %f %s " % (irrs,rrs[irrs],A,subchi2,subchi2_mumap,flag)))
#(nr,nphis)=im_polar_av.shape
#im_phi=np.tile(phis_rad,(nphis,1))
#im_cosphi=np.tile(np.cos(phis_rad),(nphis,1))
zeimage = weights*im_Npolcorr*(im_polar-im_polar_av)**2
zeimage = np.nan_to_num(zeimage)
deltaChi2 = np.sum(zeimage,axis=1)
deltaimage=im_polar-im_polar_av
velodev_med=np.sqrt( np.median(deltaimage[ia_min:ia_max]**2))
velodev_std=np.std(deltaimage[ia_min:ia_max,:])
velodev_std_vec=np.std(deltaimage,axis=1)
velodev_std2=np.std(velodev_std_vec[ia_min:ia_max])
im_polar_av_DCone = im_polar_av * mumap_polarpos + im_polar_av_far_near * (1. - mumap_polarpos)
#M.DConeDeltaChi2=False
zeimage_DCone=weights*(im_polar - im_polar_av_DCone)**2
deltaChi2_DCone=np.sum(zeimage_DCone,axis=1)
chi2=sum(deltaChi2[ia_min:ia_max])
#chi2_DCone=sum(deltaChi2_DCone[ia_min:ia_max])
if (((np.fabs(chi2 - M.chi2_prev)/chi2) < 1E-8) and not M.DConeDeltaChi2):
print( "using DConeDeltaChi2 chi2: ",chi2," chi2_prev", M.chi2_prev)
M.DConeDeltaChi2=True
if M.DConeDeltaChi2:
deltaChi2 = deltaChi2_DCone
#zeimage_N=weights*mumap_polarpos*(im_polar-im_polar_av)**2
#zeimage_N=sp.nan_to_num(zeimage_N)
#deltaChi2_N = np.sum(zeimage_N,axis=1)
#zeimage_F=weights*(1.-mumap_polarpos)*(im_polar-im_polar_av_far_near)**2
#zeimage_F=sp.nan_to_num(zeimage_F)
#deltaChi2_F = np.sum(zeimage_F,axis=1)
#deltaChi2= deltaChi2_N + deltaChi2_F
dispv_Phi_prof = np.sqrt(deltaChi2/np.sum(weights,axis=1))
dispv_Phi_prof=np.nan_to_num(dispv_Phi_prof)
else:
zeimage=weights*(im_polar-im_polar_av)**2
zeimage=np.nan_to_num(zeimage)
if (np.any(weights < 0.)):
sys.exit("negative weights!!!!")
if (np.any(zeimage < 0.)):
sys.exit("negative chi2!!!!")
deltaimage=im_polar-im_polar_av
velodev_med=np.sqrt( np.median(deltaimage[ia_min:ia_max,:]**2))
velodev_std=np.std(deltaimage[ia_min:ia_max,:])
velodev_std_vec=np.std(deltaimage,axis=1)
velodev_std2=np.std(velodev_std_vec[ia_min:ia_max])
deltaChi2 = np.sum(zeimage,axis=1)
colapsed_weights=np.sum(weights,axis=1)
dispv_Phi_prof=colapsed_weights.copy()
mask=(colapsed_weights > 1E-20)
dispv_Phi_prof[mask]=np.sqrt(deltaChi2[mask]/colapsed_weights[mask]) # << weighted dispersion of residuals
dispv_Phi_prof[np.invert(mask)]=np.nan
# dispv_Phi_prof = np.sqrt(deltaChi2/colapsedweights)
#sv_Phi_prof=dispv_Phi_prof.copy()
#cosi=np.cos(M.inc)
#Nind=2.*np.pi*rrs * cosi /(M.bmaj) # number of beams at each radius
#sv_Phi_prof=sv_Phi_prof/np.sqrt(Nind)
#sv_Phi_prof=np.nan_to_num(sv_Phi_prof)
if (M.DoAccr):
M.RadialProfile=[rrs,v_Phi_prof, sv_Phi_prof, v_R_prof, sv_R_prof]
else:
M.RadialProfile=[rrs,v_Phi_prof,sv_Phi_prof]
if (DumpAllFitsFiles):
if DoAccr:
save_prof = np.zeros((hdrpolar['NAXIS2'],5))
save_prof[:,0] = rrs
save_prof[:,1] = v_Phi_prof
save_prof[:,2] = sv_Phi_prof
save_prof[:,3] = v_R_prof
save_prof[:,4] = sv_R_prof
else:
save_prof = np.zeros((hdrpolar['NAXIS2'],3))
save_prof[:,0] = rrs
save_prof[:,1] = v_Phi_prof
save_prof[:,2] = sv_Phi_prof
fileout_radialprofile=re.sub('fullim.fits', 'radial_profile.dat', filename_fullim)
np.savetxt(fileout_radialprofile, save_prof) # x,y,z equal sized 1D arrays
fileout_polar_av=re.sub('fullim.fits', 'polar_av.fits', filename_fullim)
hdupolar.data = im_polar_av
hdupolar.writeto(fileout_polar_av, overwrite=True)
im_polar_diff = im_polar - im_polar_av
fileout_polar_diff=re.sub('fullim.fits', 'polar_diff.fits', filename_fullim)
hdupolar.data = im_polar_diff
hdupolar.writeto(fileout_polar_diff, overwrite=True)
if (DoDCone):
fileout_polar_av_far_near=re.sub('fullim.fits', 'polar_av_far_near.fits', filename_fullim)
hdupolar.data = im_polar_av_far_near
hdupolar.writeto(fileout_polar_av_far_near, overwrite=True)
fileout_polar_av_far_near=re.sub('fullim.fits', 'polar_av_DCone.fits', filename_fullim)
hdupolar.data = im_polar_av_DCone
hdupolar.writeto(fileout_polar_av_far_near, overwrite=True)
######################################################################
# Polar average: back to sky for diff image
if (M.ComputeSkyImages):
if (M.Verbose):
print( "CONICPOLAR2CARTESIAN TRANSFORM FOR AZIM AV START im_polar_av")
print( "using inc ",inc*np.pi/180.,"deg tanpsi ",tanpsi)
start_time=time.time()
imazim=conicpolartocart(im_polar_av,inc,tanpsi)
faceoninc=np.pi
# if (tanpsi < 0.):
# faceoninc=np.pi
if (inc > np.pi/2.):
faceoninc=0.
imazim_faceon=polartocart(im_polar_av,faceoninc)
resamp_faceon=polartocart(im_polar,faceoninc)
im4=imazim #gridding(fileout_stretched_av,hdr3)
if (M.Verbose):
print( "CONICPOLAR2CARTESIAN TRANSFORM FOR AZIM AV DONE in",time.time()-start_time)
if (DumpAllFitsFiles):
fileout_azimav=re.sub('fullim.fits', 'azim_av.fits', filename_fullim)
pf.writeto(fileout_azimav,im4, hdr2, overwrite=True)
# back to sky - rotate
im4drot = ndimage.rotate(im4, -rotangle, reshape=False,order=0)
# diff
diff_im = resamp-im4drot
diff_im_faceon = resamp_faceon-imazim_faceon