def disc_analysis (path, threshold=0.1, sigma=4, verbose=False):
"""read in and peform a fitting on the fits file at path containing an imcube and write out
the results to a new fits file called Xfitted.fits of shape [7,x,y] where the 7 planes of the
output are fitting parameters amplitude sigma and mean of the 2 gaussians and the baseline level"""
im=cube_convolve(P.getdata(path), sigma)
print('starting: '+path)
# data=[i for i in xrange(im.shape[1]) if im[:,i,:].sum()/im.shape[0]/im.shape[-1] > np.power(10, -1.5)]
mn,mx=70,130#min(data),max(data)
# res=scipy_double_gaussian_fit(im, verbose=verbose)
res=double_gaussian_fit_wCentral(im[:,mn:mx,:], verbose=verbose)
ans=np.ones(res.shape, dtype=np.float)
ans+=np.nan
shape=res.shape
for i in xrange(shape[1]):
for j in xrange(shape[2]):
ele=res[:,i,j]
if abs(ele[0])>=abs(ele[3]) and not(1.6<abs(ele[1])<2.1 and 122<abs(ele[2])<128 and ele[0]<-4):
ans[:,i,j]=ele
else:
ans[:,i,j]=(ele[3],ele[4],ele[5],ele[0],ele[1],ele[2],ele[6])
try :
print('writting: '+path)
P.writeto(path[:-5]+'_fitted.fits', ans)
except IOError as msg: print msg
return ans
def produce_figs (path, name=''):
if name=='': name=''.join(path.split('.')[:-1])
hdr=P.getheader(path)
im=P.getdata(path)
if len(im.shape)==4 and im.shape[1]==1: im=stripStokes(im)
cube_convolve(im,1.0)
nchan=hdr.get('NAXIS3')
vcentre=nchan/2
pixels=hdr.get('NAXIS2')
pcentre=pixels/2
imres=round(hdr.get('CDELT2')*3600*10000)/10000
if 'STOKES' in hdr.get('CTYPE3'):
velres=hdr.get('CDELT4')
if 'FREQ' in hdr.get('CTYPE4'): velres=velres/hdr.get('CRVAL4')*2.99792458e8
else:
velres=hdr.get('CDELT3')
if 'FREQ' in hdr.get('CTYPE3'): velres=velres/hdr.get('CRVAL3')*2.99792458e8
im_cs=im-im[-1,...]
mom0=im_cs[:round(vcentre-500/velres),...].sum(0)*velres/1000.+im_cs[round(vcentre+500/velres):,...].sum(0)*velres/1000.
extent=sorted(abs(mom0).flat)[mom0.size*999/1000]
F=pylab.figure();pylab.clf();pylab.imshow(mom0, interpolation='nearest', cmap=cm , vmin=-extent, vmax=extent, origin='image');c=pylab.colorbar();c.set_label('K km/s')
decorate_image(F, pixels-1,imres)
pylab.draw()
pylab.savefig(name+'_contSub.eps')
cbar=pv(im_cs[:,pcentre,:],contSub=False, spatRes=imres, velRes=velres/1000., cutFrac=0.003)
cbar.set_label('K')
decorate_pv(F, pixels-1,imres, nchan-1,velres)
draw()
savefig(name+'_PV_centre.eps')
im_cs[round(vcentre-500/velres):round(vcentre+500/velres),...]=(im_cs[round(vcentre-500/velres),...]+im_cs[round(vcentre+500/velres),...])/2
mask=abs(mom0)>abs(mom0).max()/100
cbar=mom1map(im_cs*mask, contSub=False, velwidth=velres/1000.)
cbar.set_label('km/s')
decorate_image(F, pixels-1,imres)
draw()
savefig(name+'_mom1.eps')
def produce_normal_figs (path, name='', pv_plane=100, mom0_centred_on_0=0):
if name=='': name=''.join(path.split('.')[:-1])
hdr=P.getheader(path)
im=P.getdata(path)
cube_convolve(im,1.0)
nchan=hdr.get('NAXIS3')
vcentre=nchan/2
pixels=hdr.get('NAXIS2')
imres=round(hdr.get('CDELT2')*3600*10000)/10000
velres=hdr.get('CDELT3')
mom0=im.sum(0)*velres/1000.
F=figure()
clf()
if mom0_centred_on_0:
extent=sorted(abs(mom0).flat)[mom0.size*999/1000]
imshow(mom0, interpolation='nearest', vmax=extent, vmin=-extent, cmap=cm , origin='image')
else:
imshow(mom0, interpolation='nearest', cmap=cm , origin='image')
c=colorbar();c.set_label('K km/s')
decorate_image(F, pixels,imres)
draw()
savefig(name+'.png')
cbar=pv(im[:,pv_plane,:],contSub=False, spatRes=imres, velRes=velres/1000., cutFrac=0.003)
cbar.set_label('K')
decorate_pv(F, pixels,imres, nchan,velres)
draw()
savefig(name+'_PV_centre.png')
mask=abs(mom0)>abs(mom0).max()/1000
cbar=mom1map(im*mask, contSub=False, velwidth=velres/1000.)
cbar.set_label('km/s')
decorate_image(F, pixels,imres)
draw()
savefig(name+'_mom1.png')
