Commit c66825d3 by perdereau

### add ratio between sqrt(variance) and signal for autos

parent af9c409b
 ... ... @@ -77,7 +77,7 @@ names = ['1H','2H','3H','4H','1V','2V','3V','4V','1Hx2H','1Hx3H','1Hx4H','2Hx3H' def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False, raplot=False,timeplot=False,mtitle="",clean=True,mod=False, arg=False,cmplx=False,noplo=False,verb=False,yrcm=False,cor=[],cimag=False,creal=False,hasvar=True, ramod=False,plras=[],nmras=[],mask=False): ramod=False,plras=[],nmras=[],mask=False,logsc=False,snratio=False): if verb : print len(cor) ... ... @@ -139,13 +139,18 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False, raplot=False,timeplot=F fig,ax1=plt.subplots(figsize=winwid) img = hdulist[ i].data # gets what is asked for : # sqrt(variance)/signa if (snratio) : imgvar = hdulist[ i+1].data # variance img = np.sqrt(imgvar)/img # imaginary part is demanded if(cimag): img = hdulist[ i+1].data if (verb) : print 'Image shape :' print np.shape(img) # gets what is asked for # module if mod : if num>7 : ... ... @@ -155,7 +160,7 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False, raplot=False,timeplot=F imca = hdulist[cor[0]].data imcb = hdulist[4+cor[1]].data img=img/np.sqrt(imca*imcb) # argument if arg : if num>7 : imgi= hdulist[ i+1].data ... ... @@ -167,6 +172,7 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False, raplot=False,timeplot=F print "arg demande mais auto selectionne : ERREUR " exit mskdat=img*0. # complex number representation if cmplx : imgi= hdulist[ i+1].data zmod = np.sqrt(img**2+imgi**2) ... ... @@ -185,7 +191,10 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False, raplot=False,timeplot=F for jj in np.arange(np.shape(aa)[1]): iimg.append( hls_to_rgb(aa[ii,jj], bb[ii,jj],cc[ii,jj] )) img = np.reshape( iimg,(np.shape(aa)[0],np.shape(aa)[1],3)) # log scale if logsc : img = np.log10(img) if mask : # reads mask file if cmplx : print "mask & cmplx not yet compatible " ... ... @@ -197,6 +206,10 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False, raplot=False,timeplot=F mskdat = np.fabs(hdmskl[num+1].data-1.) img = img*mskdat filename=filename+"_masked" if logsc : filename=filename+" (log)" if mod : filename=filename+" Module " # set min and max of color scale if not cmplx : # in "normal range" vmin = np.asarray(img[bfnor[0]:bfnor[1],]).min() ... ...
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!