def avgr(minfile, maxfile, zindex, component, nobc=0):
allfiles = glob.glob('*.h5')
files=[]
for file in allfiles:
if (file >= minfile) and (file <= maxfile):
files.append(file)
numfiles=len(files)
if(nobc == 0):
data=readzeus.zmp(files[0])
else:
data=readzeus.zmpnobc(files[0])
valuearray = numpy.zeros((numfiles,data[component].shape[0]))
i=0
for file in files:
if (nobc == 0):
data=readzeus.zmp(file)
else:
data=readzeus.zmpnobc(file)
valuearray[i,]=data[component][:,zindex]
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
def generatejz(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
btheta = data['btheta']
jz = numpy.zeros(btheta.shape)
r = data['r']
#Keep in mind that 'i' is the r coordinate, and 'j' is the z coordinate
#We're going to calculate jz in amps/cm^2. B_theta is in gauss.
#jr in statamps/cm^2 will require multiplying by c/4pi. The converstion
#to amps will require dividing by 2.9979e9. So the total conversion
#factor is 10/(4*pi)
#Jz = (1/r)(d/dr)(rB_theta)
for i in range(1,jz.shape[0]-1):
for j in range(jz.shape[1]):
jz[i,j] = (1.0/r[i])*btheta[i,j] + (btheta[i+1,j] - btheta[i-1,j])/(2*(r[i+1]-r[i-1]))
#for j in range(jz.shape[1]):
# jz[0,j] = (1/r[0])*btheta[0,j] + (btheta[1,j]-btheta[0,j])/(r[1]-r[0])
jz = jz*10.0/(4.0*numpy.pi)
return jz
def pltj2d(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
jr = generatejr(filename, nobc=nobc)
jz = generatejz(filename, nobc=nobc)
quiver(data['r'], data['z'], jr.T, jz.T)
def pltfluxcontour(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
flux = generateflux(filename, nobc=nobc)
titlestring = 'Flux function at t = ' + str(data['time']) + ' sec.'
contour(data['r'], data['z'], flux.T, 50, colors='k')
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
def pltvthetacontour(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(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 pltlcontour(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
titlestring = 'Angular momentum [cm^2/sec] at t = ' + str(data['time']) + 'sec.'
contourf(data['r'], data['z'], data['l'].T, 75)
colorbar()
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
def pltbzcontour(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
titlestring = 'Axial magnetic field [cm/sec] at t = ' + str(data['time']) + ' sec.'
contourf(data['r'], data['z'], data['bz'].T, 75)
colorbar()
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
def pltatheight(filename, component, zindex, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(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()
show()
def pltjz(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
jz = generatejz(filename, nobc=nobc)
titlestring = "$j_z$ at t = " + str(data['time']) + ' sec.'
contourf(data['r'], data['z'], jz.T, 50)
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
colorbar()
def pltstreamcontour(filename, nobc=0, levels=50):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
stream = generatestream(filename, nobc=nobc)
titlestring = 'Stream function at t = ' + str(data['time']) + ' sec.'
contour(data['r'], data['z'], stream.T, levels, colors='k')
title(titlestring)
xlabel("r [cm]")
ylabel("z [cm]")
def plttimeseries(minfile, maxfile, zindex, rindex, component, nobc=0):
allfiles = glob.glob('*.h5')
files=[]
for file in allfiles:
if (file >= minfile) and (file <= maxfile):
files.append(file)
numfiles=len(files)
if(nobc == 0):
data=readzeus.zmp(files[0])
else:
data=readzeus.zmpnobc(files[0])
valuearray = numpy.zeros(numfiles)
time = numpy.zeros(numfiles)
i=0
for file in files:
if(nobc == 0):
data=readzeus.zmp(file)
else:
data=readzeus.zmpnobc(file)
valuearray[i]=data[component][rindex,zindex]
time[i]=data['time']
i=i+1
print(valuearray)
print(time)
titlestring = 'Time series of ' + component
labelstring = 'z=' + str(data['z'][zindex]) + ', r=' + str(data['r'][rindex])
plot(time, valuearray, label=labelstring)
title(titlestring)
xlabel("time [s]")
ylabel(component + " [cm/sec]")
legend()
show()
def pltjstream(filename, nobc=0, color=1):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
jr = generatejr(filename, nobc=nobc)
jz = generatejz(filename, nobc=nobc)
jstream = generatejstream(data['r'], data['z'], jr, jz)
if (color==1):
contourf(data['r'], data['z'], jstream.T, 50)
contour(data['r'], data['z'], jstream.T, 50, colors='k')
xlabel("r [cm]")
ylabel("z [cm]")
def generateflux(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
# Generates flux function array of correct size
flux = data['br']
dz = data['z'][10]-data['z'][9]
for i in range(flux.shape[0]):
for j in range(flux.shape[1]):
flux[i,j]=dz*data['r'][i]*data['br'][i,j]
if j != 0:
flux[i,j]=flux[i,j]+flux[i,j-1]
return flux
def generatestream(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(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, nobc=0):
if (nobc == 0):
data = readzeus.zmp(file)
else:
data = readzeus.zmpnobc(file)
avgprofile = numpy.mean(data['vtheta'],1)
stdprofile = numpy.std(data['vtheta'],1)
couette = gencouette(data['r'], omegain, omegaout, newrin, newrout)
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 generatejr(filename, nobc=0):
if (nobc == 0):
data = readzeus.zmp(filename)
else:
data = readzeus.zmpnobc(filename)
jr = numpy.zeros(data['btheta'].shape)
dz = data['z'][10]-data['z'][9]
#Keep in mind that 'i' is the r coordinate, and 'j' is the z coordinate
#We're going to calculate jr in amps/cm^2. B_theta is in gauss.
#jr in statamps/cm^2 will require multiplying by c/4pi. The converstion
#to amps will require dividing by 2.9979e9. So the total conversion
#factor is 10/(4*pi)
for i in range(jr.shape[0]):
for j in range(1,jr.shape[1]-1):
jr[i,j] = -(data['btheta'][i,j+1]-data['btheta'][i,j-1])/(2*dz)
jr[i,0] = -(data['btheta'][i,1] - data['btheta'][i,0])/dz
jr = jr*10.0/(4.0*numpy.pi)
return jr
def save_omega_at_height(filename, zindex, savefilename):
data = readzeus.zmp(filename)
omega = data['vtheta'][:,zindex]/data['r']
numpy.savetxt(savefilename, c_[data['r'], omega], fmt="%12.6G")
