Fix syntax errors

Author: PussInDasBoot

seismic/ml_classifier/data_harvester/events.py

@@ -4,4 +4,4 @@
 
 GA=loadmat("GA.mat")['GA']
 
-print GA['picks'].keys()
+print(GA['picks'].keys())

seismic/ml_classifier/data_harvester/getwave.py

@@ -25,7 +25,7 @@ def _genTS(fdsnclient,st,ch,starttime,endtime,loc=None,net=None):
             loc=statinfo[2]
         waveforms=fdsnclient.get_waveforms(net,st,loc,ch,starttime,endtime)
         if len(waveforms)>0:
-            print "Got an IRIS waveform!"
+            print("Got an IRIS waveform!")
             ret=waveforms[0]
         else:
             ret=None
@@ -34,7 +34,7 @@ def _genTS(fdsnclient,st,ch,starttime,endtime,loc=None,net=None):
 
 
     if not ret:
-        print "No waveform found."
+        print("No waveform found.")
 
     return ret
 
@@ -46,7 +46,7 @@ def _genTS(fdsnclient,st,ch,starttime,endtime,loc=None,net=None):
 
 def getWave(webclient,st,chloc,starttime,endtime,saveDir="/g/data/ha3/rlt118/neural-datasets/categoriser-teleseismic/",phase='S',ISC=True,network=None):
     global wfctr
-    print starttime
+    print(starttime)
     st=st.strip()
     if '?' in chloc:
         return False

seismic/ml_classifier/data_harvester/process-traces.py

@@ -105,24 +105,19 @@ def genTS(net,st,ch,loc,ptime,stime):
             stime=UTCDateTime(*(stimeint+[smsec]))
         #get a waveform to train against
         wf=genTS(net,st,chan,loc,ptime,stime)
-	if not(wf is None) and len(wf)>100:#discard bad or short waveforms extracted from the database
+    if not(wf is None) and len(wf)>100:#discard bad or short waveforms extracted from the database
             wfctr+=1
             #resample the waveforms to 1000 points, detrend and normalise. The extra 0.01 ensures that the resulting trace
             #does in fact have 1000 points
             wf.resample(1000.01/wf.stats.npts*wf.stats.sampling_rate)
             wf.detrend()
             wf.normalize()
-	    #generate the pick distributions and normalise them
-	    pdist=np.exp(-np.power(wf.times()-(ptime-wf.times("utcdatetime")[0]),2)/(0.02))#sigma is 0.1
-	    sdist=np.exp(-np.power(wf.times()-(stime-wf.times("utcdatetime")[0]),2)/(0.02))
-	    pdist=pdist/np.sum(pdist)
-	    sdist=sdist/np.sum(sdist)
-	    #plot the resulting final waveform to a file
-	    outfname='wftestplot/'+'_'.join((net,st,chan,loc,ptime.ctime(),stime.ctime()))+'.png'
-	    wf.plot(outfile=outfname)
-	    #pickle the data and save it to a file 
-	    
-
-
-
-
+            #generate the pick distributions and normalise them
+            pdist=np.exp(-np.power(wf.times()-(ptime-wf.times("utcdatetime")[0]),2)/(0.02))#sigma is 0.1
+            sdist=np.exp(-np.power(wf.times()-(stime-wf.times("utcdatetime")[0]),2)/(0.02))
+            pdist=pdist/np.sum(pdist)
+            sdist=sdist/np.sum(sdist)
+            #plot the resulting final waveform to a file
+            outfname='wftestplot/'+'_'.join((net,st,chan,loc,ptime.ctime(),stime.ctime()))+'.png'
+            wf.plot(outfile=outfname)
+            #pickle the data and save it to a file

seismic/ml_classifier/data_harvester/save-noise.py

@@ -70,11 +70,11 @@ def genTS(net,st,ch,loc,starttime,endtime):
                 wf.normalize()
                 Sctr+=1
                 os.system('clear')
-                print len(wf)
+                print(len(wf))
                 wf.write(saveDir+str(Sctr)+'_N.pkl',format="PICKLE")
                 np.save(saveDir+str(Sctr)+'_N.npy',wf.data)
 
-            print str(Sctr)+'/'+str(pSctr)
+            print(str(Sctr)+'/'+str(pSctr))
 
 
-print str(Sctr)+'/'+str(pSctr),"waveforms harvested"
+print(str(Sctr)+'/'+str(pSctr),"waveforms harvested")

seismic/ml_classifier/data_harvester/save-traces-3D.py

@@ -61,7 +61,7 @@ def stripChannel(channel):
 
                     break
 
-print simulctr
+print(simulctr)
 
 """
 

seismic/ml_classifier/data_harvester/save-traces-SandP.py

@@ -21,7 +21,7 @@
 def genTS(net,st,ch,loc,starttime,endtime):
 
     #get the trace
-    print "querying database..."
+    print("querying database...")
     try:
         waveforms=fds.get_waveforms(net, st, loc, ch, 
                       starttime, endtime,
@@ -32,7 +32,7 @@ def genTS(net,st,ch,loc,starttime,endtime):
             ret=None
     except:
         ret=None
-    print "done"
+    print("done")
     return ret
 
 
@@ -120,4 +120,4 @@ def genTS(net,st,ch,loc,starttime,endtime):
 
 
 
-print str(Sctr)+'/'+str(pSctr),"waveforms harvested"
+print(str(Sctr)+'/'+str(pSctr),"waveforms harvested")

seismic/ml_classifier/data_harvester/save-traces-justP.py

@@ -70,11 +70,11 @@ def genTS(net,st,ch,loc,starttime,endtime):
                 wf.normalize()
                 Sctr+=1
                 os.system('clear')
-                print len(wf)
+                print(len(wf))
                 wf.write(saveDir+str(Sctr)+'_P.pkl',format="PICKLE")
                 np.save(saveDir+str(Sctr)+'_P.npy',wf.data)
 
-            print str(Sctr)+'/'+str(pSctr)
+            print(str(Sctr)+'/'+str(pSctr))
 
 
-print str(Sctr)+'/'+str(pSctr),"waveforms harvested"
+print(str(Sctr)+'/'+str(pSctr),"waveforms harvested")

seismic/ml_classifier/data_harvester/save-traces-justS.py

@@ -69,11 +69,11 @@ def genTS(net,st,ch,loc,starttime,endtime):
                 wf.normalize()
                 Sctr+=1
                 os.system('clear')
-                print len(wf)
+                print(len(wf))
                 wf.write(saveDir+str(Sctr)+'_S.pkl',format="PICKLE")
                 np.save(saveDir+str(Sctr)+'_S.npy',wf.data)
 
-            print str(Sctr)+'/'+str(pSctr)
+            print(str(Sctr)+'/'+str(pSctr))
 
 
-print str(Sctr)+'/'+str(pSctr),"waveforms harvested"
+print(str(Sctr)+'/'+str(pSctr),"waveforms harvested")

seismic/ml_classifier/data_harvester/save-traces.py

@@ -41,7 +41,7 @@ def genTS(net,st,ch,loc,ptime,stime):
 simulctr=0
 allpickdict={}
 
-print len(GA['events'])
+print(len(GA['events']))
 
 for picki in range(len(GA['picks']['at'])):
     pickarr=np.asarray([GA['picks']['ne'][picki],GA['picks']['st'][picki],GA['picks']['ch'][picki],GA['picks']['ph'][picki]]).T