def importAndMakeDoubleAveragedLogMags(fileList=-1):
"""
Lets just average together a few in the time domain, then a few in the freq domain
"""
eventAvgNum = 16
if fileList==-1:
baseDir=localDir+"/Attempt_3_23July2012/NewSeavey/Hpol/*degCW*"
fileList = glob.glob(baseDir+"*.dat")
else:
try:
fileList[0]
except:
fileList = [fileList]
avgFFTs = {}
for fileName in fileList:
shortName = fileName.split("/")[-1]
print shortName
allEvents = importAll(fileName)
avgFFT = ""
numAvgs = len(allEvents)/eventAvgNum
print "Number of Big Averages: "+str(numAvgs)
print "Using "+str(numAvgs*eventAvgNum)
for i in range(0,numAvgs):
avgEvent = tf.correlateAndAverage(allEvents[i*eventAvgNum:(i+1)*eventAvgNum])
if avgFFT == "":
avgFFT = np.array(tf.genLogMag(avgEvent[0]*1e9,avgEvent[1]))
print avgFFT[1]
else:
avgFFT[1] += tf.genLogMag(avgEvent[0],avgEvent[1])[1]
avgFFTs[shortName] = (avgFFT[0],avgFFT[1]/numAvgs)
return avgFFTs
def getLogMags(avgEvents):
logMags = []
for event in avgEvents:
logMags.append(tf.genLogMag(np.array(event[0]),np.array(event[1])))
return logMags
def getDictLogMags(avgEvents):
keys = avgEvents.keys()
keys.sort()
logMags = {}
for shortName in keys:
currPlot = avgEvents[shortName]
logMags[shortName] = tf.genLogMag(np.array(currPlot[0]),np.array(currPlot[1]))
return logMags
def main():
"""
does whatever silly thing I am trying on the command line
"""
files = localFileList_ANITA2chamberHPol()
fig = lab.figure()
axes = []
colors=["red","blue"]
numFiles = len(files)
index=1
logMags = {}
for file in files:
if index!=1:
axes.append(fig.add_subplot(numFiles,1,index,sharex=axes[0]))
else:
axes.append(fig.add_subplot(numFiles,1,index))
for chan in range(0,2):
events = importAll(file,numEvents=100,channel=chan)
avgEvent = tf.correlateAndAverage(events)
peak = np.argmax(np.abs(avgEvent[1])) + 500
procAvgEvent = processAllEvents([avgEvent],totalWidth=2000,peak=peak)[0]
logMag = tf.genLogMag(procAvgEvent[0],procAvgEvent[1]*1000)
grpDly = tf.genGroupDelay(procAvgEvent[0]*1e9,procAvgEvent[1]*1000)
offPhi = file.split("/")[-1].split("_")[1][1:4]
offTheta = file.split("/")[-1].split("_")[2][1:4]
print "Phi="+str(offPhi)+" Theta="+str(offTheta)
label = str(offPhi)+","+str(offTheta)
axes[-1].plot(grpDly[0], grpDly[1], label = label, color = colors[chan])
# axes[-1].plot(grpDly[0][1:],grpDly[1][1:],label=label,color=colors[chan])
index += 1
for ax in axes:
ax.legend()
fig.show()
return
def ANITA2_HchamberAnglePlot():
files = localFileList_ANITA2chamberHPol()
#Where on the grid the antenna was pointing for the chamber data
graphPositions = (2,4,5,6,8)
fig = lab.figure()
axes = []
colors=["red","blue"]
index=0
logMags = {}
for file in files:
if index!=0:
axes.append(fig.add_subplot(3,3,graphPositions[index],sharex=axes[0]))
else:
axes.append(fig.add_subplot(3,3,graphPositions[index]))
for chan in range(0,2):
events = importAll(file,numEvents=100,channel=chan)
avgEvent = tf.correlateAndAverage(events)
peak = np.argmax(np.abs(avgEvent[1])) + 500
procAvgEvent = processAllEvents([avgEvent],totalWidth=2000,peak=peak)[0]
logMag = tf.genLogMag(procAvgEvent[0],procAvgEvent[1]*1000)
grpDly = tf.genGroupDelay(procAvgEvent[0]*1e9,procAvgEvent[1]*1000)
offPhi = file.split("/")[-1].split("_")[1][1:4]
offTheta = file.split("/")[-1].split("_")[2][1:4]
print "Phi="+str(offPhi)+" Theta="+str(offTheta)
label = str(offPhi)+","+str(offTheta)
# axes[-1].plot(grpDly[0][1:],grpDly[1][1:],label=label,color=colors[chan])
axes[-1].plot(logMag[0][:200],logMag[1][:200],label=label,color=colors[chan])
# axes[-1].plot(logMag[0][1:200],logMag[1][1:200],label=label,color=colors[chan])
index += 1
for ax in axes:
ax.legend()
fig.show()
return
def ANITA3_rooftopResponse(files=-1,rotate="phi",channel=0,eventAvgs=50):
"""
imports and generates some arrays for angle, frequency, and spectral
magnitude of correlated and averaged waveforms in a series of chamber
data
the defaults are for HPol rotating in phi, but you can do others.
channel==0 is Vpol and channel==1 is Hpol (I think)
"""
if files==-1:
files = localFileList_ANITA3rooftopHPol()
print "number of files:"+str(len(files))
freqs = []
allFreqs = []
mags = []
allMags = []
angles = []
#params
numFreqs = 25
stop = 100 #~1GHz
start = 2
step = stop/float(numFreqs)
sns.set_palette(sns.color_palette("husl",numFreqs))
inPulse = antChamberResponse(chamberRefPulse,channel=0)
for file in files:
events = importAll(file,channel=channel)
print len(events)
fftAvgs = len(events)/eventAvgs
for fftAvgNum in range(0,fftAvgs):
avgEvent = tf.correlateAndAverage(events[eventAvgs*fftAvgNum:eventAvgs*(fftAvgNum+1)])
peak = np.argmax(np.abs(avgEvent[1])) + 500
procAvgEvent = processAllEvents([avgEvent],totalWidth=2000,peak=peak).T
transFunc = HpolTransferFunctionAnalysis(pulse=inPulse,respo=procAvgEvent)
logMag = tf.genLogMag(transFunc[0],transFunc[1]*1000)
if freqs == []:
freqs = np.ceil(logMag[0][start:stop:step]/1e6)
print freqs
allFreqs = np.ceil(logMag[0][start:stop]/1e6)
if fftAvgNum == 0:
logMagAvg = logMag[1]/fftAvgs
else:
logMagAvg += logMag[1]/fftAvgs
mags.append(logMagAvg[start:stop:step])
allMags.append(logMagAvg[start:stop])
try:
angle = file.split("/")[-1].split("_")[1].split("deg")[0]
direction = file.split("/")[-1].split("_")[1].split("deg")[1]
if direction == "CW":
angles.append(float(angle))
elif direction == "CCW":
angles.append(-1*float(angle))
except:
angles.append("0")
print angles[-1]
lab.close("all")
fig = lab.figure()
ax = fig.add_subplot(111)
for freqNum in range(0,numFreqs):
curve = []
for angleNum in range(0,len(angles)):
curve.append(mags[angleNum][freqNum])
curve = np.array(curve)-np.max(curve)
ax.plot(angles,curve,label=freqs[freqNum])
ax.legend()
fig.show()
return angles,allFreqs,allMags