def pltatheight(filename, component, zindex):
data = readzeus.z2d(filename)
titlestring = component + ' at t = ' + str(data['time']) + ' sec.'
labelstring = 'z = ' + str(data['z'][zindex])
plot(data['r'], data[component][:,zindex], label=labelstring)
title(titlestring)
xlabel("r [cm]")
legend()
def pltvthetacontour(filename):
clf()
data = readzeus.z2d(filename)
titlestring = 'Azimuthal velocity [cm/sec] at t = ' + str(data['time']) + ' sec.'
contourf(data['r'], data['z'], data['vtheta'].T, 75)
colorbar()
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
def pltstreamcontour(filename):
clf()
data = readzeus.z2d(filename)
stream = generatestream(filename)
titlestring = 'Stream function at t = ' + str(data['time']) + ' sec.'
contour(data['r'], data['z'], stream.T, 50, colors='k')
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
def generatestream(filename):
data = readzeus.z2d(filename)
# Generates stream function array of correct size
stream = data['vr']
dz = data['z'][10]-data['z'][9]
for i in range(stream.shape[0]):
for j in range(stream.shape[1]):
stream[i,j]=-dz*data['r'][i]*data['vr'][i,j]
if j != 0:
stream[i,j]=stream[i,j]+stream[i,j-1]
return stream
def pltheightavgprofile(file, omegain, omegaout):
data = readzeus.z2d(file)
avgprofile = numpy.mean(data['vtheta'],1)
stdprofile = numpy.std(data['vtheta'],1)
couette = gencouette(data['r'], omegain, omegaout, protorin, protorout)
titlestring = 'Z-averaged V_theta'
plot(couette['r'], couette['vtheta'], label='Ideal Couette')
errorbar(data['r'], avgprofile, yerr=stdprofile, label='Avg. Profile')
title(titlestring)
xlabel("r [cm]")
ylabel("V_theta [cm/sec]")
legend()
def avgr(minfile, maxfile, zindex, component):
allfiles = glob.glob('*.h5')
files=[]
for file in allfiles:
if (file >= minfile) and (file <= maxfile):
files.append(file)
numfiles=len(files)
data=readzeus.z2d(files[0])
valuearray = numpy.zeros((numfiles,data[component].shape[0]),
dtype=float32)
i=0
for file in files:
data=readzeus.z2d(file)
valuearray[i,]=data[component][:,zindex]
print "Now reading " + file
i=i+1
valuemean=numpy.mean(valuearray,0)
valuestd=numpy.std(valuearray,0)
valuereturn = {'r': data['r'], 'z': data['z'][zindex], 'mean': valuemean, 'std': valuestd}
return valuereturn
