add comments (viewtfmap) + set pressure to 0 (altaz.py)

Python/viewtfmap.py

@@ -13,20 +13,75 @@ import time
 from colorsys import hsv_to_rgb, hls_to_rgb
 #    Choices: ['auto', 'gtk', 'gtk3', 'inline', 'nbagg', 'notebook', 'osx', 'qt', 'qt4', 'qt5', 'tk', 'wx']
 
+# values of the freqs for the slices
 rfreq = [1381.,1390.,1420.5,1430.]
-normf=[1325.,1465.]
+
+normf=[1325.,1465.] # "normal frequencies" 
+
 names = ['1H','2H','3H','4H','1V','2V','3V','4V','1Hx2H','1Hx3H','1Hx4H','2Hx3H','2Hx4H','3Hx4H',
          '1Vx2V','1Vx3V','1Vx4V','2Vx3V','2Vx4V','3Vx4V','1Hx1V','1Hx2V','1Hx3V','1Hx4V','2Hx1V','2Hx2V','2Hx3V','2Hx4V',
          '3Hx1V','3Hx2V','3Hx3V','3Hx4V','4Hx1V','4Hx2V','4Hx3V','4Hx4V']
 
+# viewtfmap reads and returns data stored in the TF maps fits files build by visiavg (code in AnaPAON4)
+
+# all TF maps are stored as hdu in the fits file, with some additional data at the end.
+# First the autocorrelations for 1H->4V two consecutive HDUs with mean of FFT amplitudes , then variance
+# the for the cross-correlations - the TF amplitudes are complex : in each case one HDU with real part, one with imaginary part averages
+# and two for their respective variances
+# NB the variance computation is optional 
+# at the end of the fits files, acddition HDUs contain 1D data (in reverse order) : times (center of bins), frequencies and RA
+# (omitted in the case od RA-freq maps 
+# 
+
+# --------------------------------
+# main arguments of viewtfmap
+# --------------------------------
+
+# folder = path to the fits files (w/o extension
+# num = indez in the array of auto and cross-correlation (named in 'names' list above) of the quantity we want to plot/read
+# mvmin/max : min and max values of the color scale (if not doable from the plot window)
+# save : set tu True to save png files of the plots 
+# cor : to compute the correlation coefficient between 2 auto-cor channels [deprecated]
+# clean : cleans previous plot (external window) 
+# mod : in case of cross-correlation computes the module of the complex amplitude
+# (default = real part only)
+# arg : in case of cross-correlation computes the argument  of the complex amplitude
+# cimag : to view the imaginary part 
+# creal : to view the real part [deprecated, default]
+# cmplx :get a complete visu of the complex : color <> argument, hue <> amplitude 
+# hasvar : nadle varianvces if they have been stored (default)
+# mtitle= string to set  title to plots
+# verb : verbosity level 
+# noplo : does not make any plot, only read and output 
+# hasvar : to handle the cas where there are no variances 
+# ramod : to handle the case where the time-freq maps are ra-frequency maps [deprecated]
+# mask : if true, also looks for a 'mask' file (same name+'_mask') to mask RFIs and satellites 
+# yrcm : to use another color map (
+# raplot : also shows slices at some frequencies [see array rfreq above] as a fct of RA [deprecated - don't ew
+# timeplot  : also shows slices at soem frequencies as a fct of time [deprecated - don't use]
+
+
+#returns :
+#  times (in hours) [1d array]
+#  time-freq (or ra-freq) map [2d array] of demanded channel
+#  frequencies (MHz) [1D] ,
+#  ras RAs (in h)[ 1D]
+#  list of 1D array with slices for ewach freq in bfreq (if any)
+#  only if map plotted, some plot info : 3 items  ax1,bnext,bprev
+#  mskdat  : time-freq map, with masked values set to 0 
+# 
+#
+#
+#
+#
+
 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):
+    
     if verb :
         print len(cor)
     filename = folder
-    #print   i
-    #print num
     if noplo :
         clean=False
     if clean:
@@ -35,15 +90,16 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
 
     hdulist = fits.open(folder+'.fits')
 
-    winwid = (18,8)
+    winwid = (18,8) # window size 
 
-    times=hdulist[len(hdulist)-1].data
-    ras=hdulist[len(hdulist)-2].data #41 in 43
-    freqs= hdulist[len(hdulist)-3].data
+    times=hdulist[len(hdulist)-1].data  # time @ bin centers, in seconds
+    ras=hdulist[len(hdulist)-2].data #   RA @ bin centers (hdu e.g. 41 in 43)
+    freqs= hdulist[len(hdulist)-3].data # frequnencies @ bin centers , MHz
     if ramod :
         ras=hdulist[len(hdulist)-1].data #41 in 43
         freqs= hdulist[len(hdulist)-2].data
-        
+
+    #gets the index of the HDU in the fits file from the index on names 
     i=2*num
     if num>7 :
         i= 16 + 4*(num-8)
@@ -58,11 +114,14 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
 
     if (verb) :
         print hdulist[i].header
-        
+
+    # get the bin indexes for the slices & the "normal range"
     bfreq = [ (np.abs(freqs-rf)).argmin() for rf in rfreq ]
     bfnor = [(np.abs(freqs-rf)).argmin() for rf in normf ]
+
     if (verb) :
-        print ' number of hds ' + str(len(hdulist))
+        print ' number of hdus ' + str(len(hdulist))
+
 
     nfre = np.size(freqs)
     ntim = np.size(times)
@@ -85,18 +144,19 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
     if (verb) :
         print 'Image shape :'
         print np.shape(img)
-        
+
+    # gets what is asked for 
     if mod :
         if num>7 :
             
             imgi= hdulist[  i+1].data
             img = np.sqrt(img**2+imgi**2)
-            if len(cor) ==2 :
+            if len(cor) ==2 : # for correlation coeff
                 imca = hdulist[cor[0]].data
                 imcb = hdulist[4+cor[1]].data
                 img=img/np.sqrt(imca*imcb)
 
-    if arg :
+    if arg : 
         if num>7 :
             imgi= hdulist[  i+1].data
             img = np.arctan2(imgi,img) * 180. / np.pi
@@ -126,7 +186,7 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
                 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))
     
-    if mask :
+    if mask : # reads mask file
         if cmplx :
             print "mask & cmplx not yet compatible "
             exit
@@ -137,13 +197,14 @@ 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 not cmplx :   
+    #   set min and max of color scale 
+    if not cmplx :   # in "normal range" 
         vmin = np.asarray(img[bfnor[0]:bfnor[1],]).min() 
         vmax = np.asarray(img[bfnor[0]:bfnor[1],]).max()
     else :
         vmin=0
         vmax=1 
-    
+    #or for extrernal values
     if mvmin !=0. :
         vmin = mvmin
         
@@ -154,6 +215,7 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
         print vmax,np.asarray(img[300:900,]).max()
 
     if (not noplo) :
+        # plots TF image - dual axes with bin no and values 
         im = ax1.imshow(img,aspect='auto' , interpolation='none',vmin=vmin,vmax=vmax)
         #m = ax1.imshow(img,aspect='auto' ,extent=(timin,timax,frmax,frmin), interpolation='none',vmin=vmin,vmax=vmax)
         if (yrcm) :
@@ -191,7 +253,7 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
             ax3.xaxis.set_view_interval( timin,timax  ,ignore=True)            
             ax3.set_xlabel("time bin",x=0.85)
 
-        if save:
+        if save:  # saves png  with some name
             ext=""
             if creal :
                 ext = ext+"_real"
@@ -205,7 +267,7 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
             else :
                 plt.savefig(filename+"_"+ names[num]+"_TFM"+ext+".png")
             
-
+        # ------------ THIS IS TO SWITCH FROM ONE CMAP TO THE OTHER 
         axnext = fig.add_axes([0.6, 0.04, 0.05, 0.05])
         bnext = Button(axnext,cm_cycle[cm_index+1] )
         axprev = fig.add_axes([0.7, 0.04, 0.05, 0.05])
@@ -255,13 +317,14 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
              
         bnext.on_clicked(cm_next)
         bprev.on_clicked(cm_prev)
+        #----------------- END CMAP SWITCH
         
         #plt.tight_layout()
         plt.subplots_adjust(bottom=0.15)
         plt.show()
 
 
-    if raplot : 
+    if raplot :  # does plots of signal vs RA at some frequencies
         fig,ax1=plt.subplots(figsize=winwid)
     
         [ plt.plot(ras, img[b,],label="F=%6.2f MHz" %(freqs[b]) ) for b in bfreq ]
@@ -285,12 +348,13 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
                 plt.savefig(filename+"_"+ names[num]+"_TFM_ra.png")
     
 
-    if timeplot : 
+    if timeplot : # does plots of sig vs time at some frequencies
         fig,ax1=plt.subplots(figsize=winwid)
         [ plt.plot(times/3600., img[b,],label="F=%6.2f MHz" %(freqs[b]) ) for b in bfreq ]
         plt.xlabel('Time (TU, hour)')
         plt.ylabel("Signal ")
         plt.ylim(np.asarray(img[[bfreq],]).min(),np.asarray(img[[bfreq],]).max())
+        #legend with thicker linewidth
         leg = plt.legend()
         for legobj in leg.legendHandles:
             legobj.set_linewidth(2.0)
@@ -310,6 +374,9 @@ def viewtfmap(folder,num,mvmin=0.,mvmax=0.,save=False,   raplot=False,timeplot=F
         print times.size
     if (verb) :
         print np.shape(img)
+
+
+    #return values 
     if noplo :
         return times/3600.,img,freqs,ras,[ img[b,] for b in bfreq],mskdat
     elif    cmplx:

TrackingSrc/altaz/altaz.py

@@ -54,8 +54,8 @@ def scan_source(source="Moon",
 
     times_period = start + delta_period
 
-    # Compute the Alt-Az frames during the survey
-    frame_period = AltAz(obstime=times_period, location=observer)
+    # Compute the Alt-Az frames during the survey pressure = 0 ==> no refraction
+    frame_period = AltAz(obstime=times_period, location=observer, pressure=0. )
 
     # perform the survey
     source = source.lower()