From d12c6cf22aae9ce1d82437746b0b80abd866fa84 Mon Sep 17 00:00:00 2001
From: 0xCoto <cotothearcher@gmail.com>
Date: Sat, 22 Feb 2020 04:53:50 +0200
Subject: [PATCH] Update rfi_plotter.py

---
 rfi_plotter.py | 50 +++++++++-----------------------------------------
 1 file changed, 9 insertions(+), 41 deletions(-)

diff --git a/rfi_plotter.py b/rfi_plotter.py
index c1f44ce..72c03e4 100644
--- a/rfi_plotter.py
+++ b/rfi_plotter.py
@@ -1,5 +1,5 @@
 #!/usr/bin/env python
-if True:
+try:
     import matplotlib
     matplotlib.use('Agg')
     
@@ -35,27 +35,19 @@ def decibel(x):
         exec(args.fminimum)
         exec(args.fmaximum)
         
-        #freq=300000000
         frequency=freq
-        #samp_rate=2400000
-        #nchan=1024
-        #nbin=23436
         
         #Load data
         z=1000*(np.fromfile("0.dat", dtype="float32").reshape(-1, nchan)/nbin)
         allarrays=[]
-        #N=1 #amount_of_.dat_files
+        
+        #N = amount of .dat files
         for i in range(int(n)):
             final = 1000*(np.fromfile(str(i)+".dat", dtype="float32").reshape(-1, nchan)/nbin)
-            #print(final.shape)
             allarrays.append(final)
         z_final = np.concatenate(allarrays,axis=1)
-        #print(type(z_final))
-        #print(z_final.shape)
-        #z_final[z_final > 4000] = 4000
         
         #Define numpy array for Power vs Time plot
-        #w = np.mean(a=z, axis=1)
         
         #Number of sub-integrations
         nsub = z_final.shape[0]
@@ -67,21 +59,17 @@ def decibel(x):
         tint = float(nbin*nchan)/samp_rate
         t = tint*np.arange(nsub)
         
-        #v = np.arange(0, np.max(t)+tint, tint)
-        
         #Compute frequency axis (convert to MHz)
         allfreq=[]
         for i in range(int(n)):
             freq = np.linspace((frequency+samp_rate*i)-0.5*samp_rate, (frequency+samp_rate*i)+0.5*samp_rate, nchan, endpoint=False)*1e-6
             allfreq.append(freq)
         freq = np.concatenate(allfreq)
-        #print(999,freq)
-        #freq = freq*i
-        #print(freq.shape)
+        
         #Initialize plot
         fig = plt.figure(figsize=(5*n,20.25))
-        gs = GridSpec(1,1) #2,1
-        
+        gs = GridSpec(1,1)
+                
         #Plot average spectrum
         ax1 = fig.add_subplot(gs[0,0])
         ax1.plot(freq, decibel(zmean), '#3182bd')
@@ -95,28 +83,8 @@ def decibel(x):
         ax1.annotate('Frequency range scanned: '+str(float(fminimum)/1000000)+'-'+str(float(fmaximum)/1000000)+' MHz ($\\Delta\\nu$ = '+str(float((fmaximum)-float(fminimum))/1000000)+' MHz)\nBandwidth per spectrum: '+str(float(samp_rate)/1000000)+' MHz\nIntegration time per spectrum: '+str(dur)+" sec\nNumber of channels per spectrum (FFT size): "+str(nchan), xy=(17, 1179), xycoords='axes points', size=32, ha='left', va='top', color='brown')
         ax1.grid()
         
-        #Plot dynamic spectrum
-        #ax2 = fig.add_subplot(gs[1,0])
-        #ax2.imshow(decibel(z_final), origin="lower", interpolation="None", aspect="auto",
-        #           extent=[np.min(freq), np.max(freq), np.min(t), np.max(t)])
-        #ax2.ticklabel_format(useOffset=False)
-        #ax2.set_xlabel("Frequency (MHz)")
-        #ax2.set_ylabel("Time (s)")
-        #ax2.set_title("Dynamic Spectrum (Waterfall)")
-        
-        #Plot Power vs Time
-        #ax3 = fig.add_subplot(gs[1,:])
-        #ax3.plot(v,w)
-        #ax3.axvline(x=9180, color='blue', linestyle='--', linewidth=2)
-        #ax3.axvline(x=8100, color='red', linestyle='--', linewidth=2)
-        #ax3.axvline(x=7200, color='orange', linestyle='--', linewidth=2)
-        #ax3.set_xlim(0,np.max(t)+tint)
-        #ax3.set_xlabel("Time (s)")
-        #ax3.set_ylabel("Relative Power")
-        #ax3.set_title("Power vs Time")
-        
         plt.tight_layout()
         plt.savefig("rfi_plot.png")
-#except Exception as e:
-#    print(e)
-#    pass
+except Exception as e:
+    print(e)
+    pass