def plotEvolution():
#ky_list = linspace(0.3, pi, 17)
ky_list = logspace(-1, log10(pi), 3)
results = []
"""
for w0 in [ -0.4 + 0.05j , -0.2 + 0.01j, - 0.8 - 0.01j, - 1.2 - 0.04j ]:
res = []
for n in range(len(ky_list)):
w0 = solveDispersion(ky_list[n], (w0, w0+0.01, w0+0.001j), doPlots=False)
res.append(w0)
results.append(res)
"""
w0 = -0.4 + 0.05j
for w0_init in [ -0.25 + 0.05j, -0.5 + 0.01j, -0.4 + 0.02 ]:
res = []
idx_l = where(ky_list < 2.55)
idx_u = where(ky_list >= 2.55)
idx = append(idx_u, idx_l[0][::-1])
ky_list_mod = ky_list[idx]
for n in range(len(ky_list)):
print " ky ---> " , ky_list[idx][n]
if (abs(ky_list[idx][n] - 2.55) < 0.1) : w0 = w0_init
w0 = solveDispersion(ky_list[idx][n], (w0, w0+0.01, w0+0.001j), doPlots=False)
res.append(w0)
res = array(res)
results.append(res[idx])
results = array(results)
#fig = gkcStyle.newFigure(ratio='1.41:1', basesize=9)
fig = gkcStyle.newFigure(ratio='1.41:1', basesize=18)
subplot(121)
for res in results:
semilogx(ky_list, imag(res), '-', label='imag')
gkcStyle.plotZeroLine(min(ky_list), max(ky_list))
xlim((min(ky_list), max(ky_list)))
xlabel("$k_y$")
ylabel("Growthrates $\\gamma$")
#savefig("Growthrate.pdf", bbox_inches='tight')
subplot(122)
#clf()
for res in results:
semilogx(ky_list, real(res), '-', label='imag')
gkcStyle.plotZeroLine(min(ky_list), max(ky_list))
xlim((min(ky_list), max(ky_list)))
xlabel("$k_y$")
ylabel("Frequency $\\gamma$")
savefig("Frequency.pdf", bbox_inches='tight')
# Save max tendency
savetxt("Tendency.txt", array([ky_list, real(results), imag(results)]).T)
def plotEigenvalues(fileh5, **kwargs):
"""
Plot the eigenvalues of the phase space function
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*offset* Offset due to zeroset to 2 .
"""
import gkcStyle
D = gkcData.getDomain(fileh5)
try:
eigv = fileh5.root.Eigenvalue.EigenValues.cols.Eigenvalue[:]
except:
print "Problems openning eigenvalues. Not included ?"
return
eigv_r = np.real(eigv)
eigv_i = np.imag(eigv)
pylab.plot(eigv_r, eigv_i, '.')
gkcStyle.plotZeroLine(1.1 * min(eigv_r),
1.1 * max(eigv_r),
direction='horizontal',
color="#666666",
lw=0.8)
gkcStyle.plotZeroLine(1.1 * min(eigv_i),
1.1 * max(eigv_i),
direction='vertical',
color="#666666",
lw=0.8)
pylab.xlim((1.1 * min(eigv_r), 1.1 * max(eigv_r)))
pylab.ylim((1.1 * min(eigv_i), 1.1 * max(eigv_i)))
pylab.xlabel("$\\omega_r$")
pylab.ylabel("$\\omega_i$")
def plotEigenvalues(fileh5, **kwargs):
"""
Plot the eigenvalues of the phase space function
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*offset* Offset due to zeroset to 2 .
"""
import gkcStyle
D = gkcData.getDomain(fileh5)
try:
eigv = fileh5.root.Eigenvalue.EigenValues.cols.Eigenvalue[:]
except:
print "Problems openning eigenvalues. Not included ?"
return
eigv_r = np.real(eigv)
eigv_i = np.imag(eigv)
pylab.plot(eigv_r, eigv_i, '.')
gkcStyle.plotZeroLine(1.1*min(eigv_r), 1.1*max(eigv_r), direction='horizontal', color="#666666", lw=0.8)
gkcStyle.plotZeroLine(1.1*min(eigv_i), 1.1*max(eigv_i), direction='vertical' , color="#666666", lw=0.8)
pylab.xlim((1.1*min(eigv_r), 1.1*max(eigv_r)))
pylab.ylim((1.1*min(eigv_i), 1.1*max(eigv_i)))
pylab.xlabel("$\\omega_r$")
pylab.ylabel("$\\omega_i$")
def plotFrequencySpectra(fileh5, which='b', markline="-", **kwargs):
"""
Plots time evolution of mode power.
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*modes* List of modes (default plot modes).
e.g. modes = [1,4,5] - to plot all modes
modes = range(Nky)[::2] - to plot every second mode
*field* 'phi' electric potential
'A' parallel magnetic vector potential
'B' parallel magnetic field
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*doCFL* clear previous figure
*label* 'ky' or 'm'
*offset* Offset due to zeroset to 2 .
"""
import gkcData
import gkcStyle
import pylab
import numpy as np
D = gkcData.getDomain(fileh5)
doCFL = kwargs.pop('doCFL', True)
dir = kwargs.pop('dir', 'Y')
modes = kwargs.pop('modes' , range(D['Nky']))
field = kwargs.pop('field', 'phi')
n_offset = kwargs.pop('offset', 2)
label = kwargs.pop('label', 'ky')
leg_loc = kwargs.pop('loc', 'best')
start = kwargs.pop('start', 1)
stop = kwargs.pop('stop', -1)
if doCFL == True : pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:,1]
if field == 'phi' : n_field = 0
elif field == 'A' : n_field = 1
elif field == 'B' : n_field = 2
else : raise TypeError("Wrong argument for field : " + str(field))
if(dir == 'X'):
raise TypeError("Not implemented for X-direction")
elif(dir == 'Y'):
shift = fileh5.root.Analysis.PhaseShift.Y [n_field, :,start:stop]
print "Using data from T=", T[start], " to T = ", T[stop]
freq = []
for nky in np.arange(1,len(D['ky'])):
time_series = np.sin(shift[nky,:])
FS = np.fft.rfft(time_series)
# Not only if we have constant time step !
freq.append(abs(FS))
fftfreq = np.fft.fftfreq(len(abs(np.fft.fftshift(FS))), d = (T[-10]-T[-11]))
freq = np.array(freq)
print np.shape(fftfreq), " 2 : ", np.shape(D['ky'][1:]), np.shape(freq)
pylab.contourf(D['ky'][1:], np.fft.fftshift(fftfreq), freq.T, 100, cmap=pylab.cm.jet)
pylab.xlim((D['ky'][1], D['ky'][-1]))
pylab.ylim((min(fftfreq), max(fftfreq)))
pylab.colorbar()
else : raise TypeError("Wrong argument for dir : " + str(dir))
pylab.gca().set_xscale("log")
pylab.xlabel("$k_y$")
gkcStyle.plotZeroLine(D['ky'][1], D['ky'][-1], color='r')
pylab.ylabel("Frequency $\\omega_r(k_y)$")
def plotFrequencyGrowthrates(fileh5, which='b', markline="-", **kwargs):
"""
Plots time evolution of mode power.
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*modes* List of modes (default plot modes).
e.g. modes = [1,4,5] - to plot all modes
modes = range(Nky)[::2] - to plot every second mode
*field* 'phi' electric potential
'A' parallel magnetic vector potential
'B' parallel magnetic field
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*doCFL* clear previous figure
*label* 'ky' or 'm'
*offset* Offset due to zeroset to 2 .
"""
D = gkcData.getDomain(fileh5)
doCFL = kwargs.pop('doCFL', True)
dir = kwargs.pop('dir', 'Y')
modes = kwargs.pop('modes' , range(D['Nky']))
field = kwargs.pop('field', 'phi')
n_offset = kwargs.pop('offset', 2)
label = kwargs.pop('label', 'ky')
leg_loc = kwargs.pop('loc', 'best')
start = kwargs.pop('start', 1)
stop = kwargs.pop('stop', -1)
if doCFL == True : pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:,1]
print "Fitting from T : ", T[start], " - ", T[stop]
if field == 'phi' : n_field = 0
elif field == 'A' : n_field = 1
elif field == 'B' : n_field = 2
else : raise TypeError("Wrong argument for field : " + str(field))
if(dir == 'X'):
pl = semilogy(T, fileh5.root.Analysis.PowerSpectrum.X[n_field,:numModes,2:].T)
legend_list = []
for i in range(len(fileh5.root.Analysis.PowerSpectrum.X[n_field, :numModes,0])):
legend_list.append("kx = %i" % i)
leg = pylab.legend(legend_list, loc='lower right', ncol=2)
leg.draw_frame(0)
elif(dir == 'Y'):
scale = fileh5.root.Grid._v_attrs.Ly/(2. * np.pi)
legend_list = []
if which=='i' or which=='b':
power = fileh5.root.Analysis.PowerSpectrum.Y[n_field, :,:]
growthrates = getGrowthrate(T,power, start,stop, dir='Y')
pl = pylab.semilogx(D['ky'], growthrates, "s" + markline, label='$\\gamma$')
if which=='r' or which=='b':
shift = fileh5.root.Analysis.PhaseShift.Y [n_field, :,:]
frequency = getFrequency(T,shift, start,stop, dir='Y')
pl = pylab.semilogx(D['ky'], frequency, "v" + markline, label='$\\omega_r$')
#if which !='r' or which != 'i' or which !='b':
# raise TypeError("Wrong argument for which (r/i/b) : " + str(dir))
#pylab.twinx()
pylab.xlim((0.8*min(D['ky']), 1.2*max(D['ky'])))
else : raise TypeError("Wrong argument for dir : " + str(dir))
pylab.xlabel("$k_y$")
leg = pylab.legend(loc=leg_loc, ncol=1, mode="expand").draw_frame(0)
gkcStyle.plotZeroLine(0.8*min(D['ky']), 1.2*max(D['ky']))
pylab.ylabel("Growthrate $\\gamma(k_y)$ / Frequency $\\omega_r(k_y)$")
def plotScalarDataTimeEvolution(fileh5, var = "KinPhi", **kwargs):
"""
Plots time evolution of mode power.
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*modes* List of modes (default plot modes).
e.g. modes = [1,4,5] - to plot all modes
modes = range(Nky)[::2] - to plot every second mode
*field* 'phi' electric potential
'A' parallel magnetic vector potential
'B' parallel magnetic field
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*doCFL* clear previous figure
*label* 'ky' or 'm'
*offset* Offset due to zeroset to 2 .
"""
D = gkcData.getDomain(fileh5)
log = kwargs.pop('log', True)
leg_loc = kwargs.pop('leg_loc' , 'best')
leg_ncol = kwargs.pop('leg_ncol', 1)
if(log == 1) :
plotf = pylab.semilogy
af = abs
else :
plotf = pylab.plot
af = lambda x : x
T = fileh5.root.Analysis.scalarValues.cols.Time[5:]
n_sp = len(fileh5.root.Species.cols.Name[1:])
# Plot Field Energy"
if var == "phi":
plotf(T, af(fileh5.root.Analysis.scalarValues.cols.phiEnergy[3:]), label="Field Energy")
pylab.ylabel("Field Energy")
if var == "kinEnergy":
for s in range(n_sp):
plotf(T, af(fileh5.root.Analysis.scalarValues.cols.KineticEnergy[3:][:,s]) , label="Kinetic Energy (" + fileh5.root.Species.cols.Name[s]+ ")" )
#plotf(T, af(fileh5.root.Analysis.scalarValues.cols.phiEnergy[3:]+1.*(np.sum(fileh5.root.Analysis.scalarValues.cols.KineticEnergy[3:], axis=1))) , label="Total Energy")
pylab.ylabel("Energy")
if var == "KinPhi":
pylab.plot(T, fileh5.root.Analysis.scalarValues.cols.phiEnergy[5:], label="Field Energy")
E_kin_total = fileh5.root.Analysis.scalarValues.cols.phiEnergy[5:]
for s in range(n_sp):
E_kin = fileh5.root.Analysis.scalarValues.cols.KineticEnergy[5:][:,s]-fileh5.root.Analysis.scalarValues.cols.KineticEnergy[5][s]
E_kin = -abs(E_kin)
E_kin_total = E_kin_total + E_kin
pylab.plot(T, E_kin , label="Kinetic Energy (" + fileh5.root.Species.cols.Name[s]+ ")" )
gkcStyle.plotZeroLine(min(T), max(T))
pylab.plot(T, -abs(E_kin_total)/100. , label="Total Energy")
pylab.yscale('symlog', linthreshy=1.e-7)
# Plot Toal nergy
pylab.ylabel("Energy")
if var == "heatFlux":
for s in sp:
for s in range(n_sp):
plot(T, fileh5.root.Analysis.scalarValues.cols.HeatFlux[3:][:,s], label=fileh5.root.Species.cols.Name[s])
pylab.ylabel("Heat Flux")
if var == "Charge":
charge = np.zeros(len(fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3:][:,1]))
for s in range(n_sp):
dn = (fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3:][:,s] - fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3][s])
n = fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3:][:,s]
q = fileh5.root.Species.cols.Charge[s]
charge = charge + q * n
pylab.plot(fileh5.root.Analysis.scalarValues.cols.Time[3:], q*n , label=fileh5.root.Species.cols.Name[s])
pylab.plot(fileh5.root.Analysis.scalarValues.cols.Time[3:], q*dn , label=fileh5.root.Species.cols.Name[s])
if D['Ns'] > 1:
plotf(fileh5.root.Analysis.scalarValues.cols.Time[3:], charge , label="Charge")
gkcStyle.plotZeroLine(min(T), max(T))
pylab.yscale('symlog', linthreshy=1.e-7)
pylab.ylabel("Charge")
if var == "particleFlux":
for s in range(n_sp):
plotf(T, fileh5.root.Analysis.scalarValues.cols.ParticleFlux[3:][:,s], label=fileh5.root.Species.cols.Name[s])
pylab.ylabel("Particle Flux")
pylab.xlim((min(T), max(T)))
leg = pylab.legend(loc=leg_loc, ncol=leg_ncol).draw_frame(0)
pylab.xlabel("Time")
def plotFrequencyGrowthrates(fileh5, which='b', markline="-", **kwargs):
"""
Plots time evolution of mode power.
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*modes* List of modes (default plot modes).
e.g. modes = [1,4,5] - to plot all modes
modes = range(Nky)[::2] - to plot every second mode
*field* 'phi' electric potential
'A' parallel magnetic vector potential
'B' parallel magnetic field
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*doCFL* clear previous figure
*label* 'ky' or 'm'
*offset* Offset due to zeroset to 2 .
"""
D = gkcData.getDomain(fileh5)
doCLF = kwargs.pop('doCLF', True)
dir = kwargs.pop('dir', 'Y')
modes = kwargs.pop('modes', range(D['Nky']))
field = kwargs.pop('field', 'phi')
n_offset = kwargs.pop('offset', 2)
label = kwargs.pop('label', 'ky')
leg_loc = kwargs.pop('loc', 'best')
start = kwargs.pop('start', 1)
stop = kwargs.pop('stop', -1)
m = kwargs.pop('m', 0)
useLog = kwargs.pop('useLog', True)
if useLog == True: pf = pylab.semilogx
else: pf = pylab.plot
if doCLF == True: pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:, 1]
if field == 'phi': n_field = 0
elif field == 'A': n_field = 1
elif field == 'B': n_field = 2
else: raise TypeError("Wrong argument for field : " + str(field))
if (dir == 'X'):
pl = pf(T, fileh5.root.Analysis.PowerSpectrum.X[n_field, :numModes,
2:].T)
legend_list = []
for i in range(
len(fileh5.root.Analysis.PowerSpectrum.X[n_field, :numModes,
0])):
legend_list.append("kx = %i" % i)
leg = pylab.legend(legend_list, loc='lower right', ncol=2)
leg.draw_frame(0)
elif (dir == 'Y'):
scale = fileh5.root.Grid._v_attrs.Ly / (2. * np.pi)
legend_list = []
if which == 'i' or which == 'b':
power = fileh5.root.Analysis.PowerSpectrum.Y[n_field, :, :]
growthrates = getGrowthrate(T, power, start, stop)
pl = pf(D['ky'], growthrates, "s" + markline, label='$\\gamma$')
if which == 'r' or which == 'b':
shift = fileh5.root.Analysis.PhaseShift.Y[n_field, :, :]
frequency = getFrequency(T, shift, start, stop)
pl = pf(D['ky'], frequency, "v" + markline, label='$\\omega_r$')
#if which !='r' or which != 'i' or which !='b':
# raise TypeError("Wrong argument for which (r/i/b) : " + str(dir))
#pylab.twinx()
pylab.xlim((0.8 * min(D['ky']), 1.2 * max(D['ky'])))
else:
raise TypeError("Wrong argument for dir : " + str(dir))
pylab.xlabel("$k_y$")
leg = pylab.legend(loc=leg_loc, ncol=1, mode="expand").draw_frame(0)
gkcStyle.plotZeroLine(0.8 * min(D['ky']), 1.2 * max(D['ky']))
pylab.ylabel("Growthrate $\\gamma(k_y)$ / Frequency $\\omega_r(k_y)$")
# sw-ITG (2)
w_2, kx, phi_k, x, phi_2 = disp.solveEquation((w0, w0+0.0005, w0+0.0002j), 9., stdSetup_swITG)
"""
# sw-ITG (2)
w_2, kx, phi_k, x, phi_2 = disp.solveEquation((w0, w0+0.0005, w0+0.0002j), 0.5, stdSetup_swITG)
########### Plotting #######333
gkcStyle.newFigure(ratio="2.33:1", basesize=10.)
subplot(121)
plot(x, real(phi_0), label="%.3f %.3f" % (real(w_0), imag(w_0)))
plot(x, real(phi_1), label="%.3f %.3f" % (real(w_1), imag(w_1)))
plot(x, real(phi_2), label="%.3f %.3f" % (real(w_2), imag(w_2)))
gkcStyle.plotZeroLine(min(kx), max(kx))
xlim((-5, 5.))
xlabel("$X$")
ylabel("$\phi(x)$")
####
subplot(122)
plot(x, imag(phi_0), label="%.3f %.3f" % (real(w_0), imag(w_0)))
plot(x, imag(phi_1), label="%.3f %.3f" % (real(w_1), imag(w_1)))
plot(x, imag(phi_2), label="%.3f %.3f" % (real(w_2), imag(w_2)))
gkcStyle.plotZeroLine(min(kx), max(kx))
xlim((-5, 5.))
xlabel("$X$")
title="Benchmark of Smolykov et al. (PRL, 2002) using gkc++ (rev. 173)")
pylab.semilogx(D['ky'][1:-1],
2. * np.imag(omega_sim[1:-1]),
'^',
label='gkc++')
pylab.semilogx(ky_list,
np.imag(omega_th),
'-',
color='#FF4444',
alpha=0.8,
linewidth=5.,
label='Theory')
gkcStyle.plotZeroLine(D['ky'][1],
D['ky'][-1],
direction='horizontal',
color="#666666",
lw=1.5)
pylab.xlim((D['ky'][1], D['ky'][-1]))
if (isKinetic): pylab.ylim((-0.005, 0.015))
else: pylab.ylim((-0.002, 0.005))
pylab.legend(loc='best').draw_frame(0)
pylab.xlabel("$k_y$")
pylab.ylabel("Growthrate $\\omega_i [L_n / v_{te}]$")
# Plot Frequency
pylab.subplot(212)
omega_th = np.array(omega_th) * param['kp']#/sqrt(1837.)
fileh5.close()
############################## Plot Figure ###################
gkcStyle.newFigure(ratio="1:1.33", basesize=12)
# Plot Growthrates
pylab.subplot(211, title="Benchmark of Smolykov et al. (PRL, 2002) using gkc++ (rev. 173)")
pylab.semilogx(D['ky'][1:-1], 2. * np.imag(omega_sim[1:-1]), '^', label='gkc++')
pylab.semilogx(ky_list, np.imag(omega_th), '-', color='#FF4444', alpha=0.8, linewidth=5., label='Theory')
gkcStyle.plotZeroLine(D['ky'][1], D['ky'][-1], direction='horizontal', color="#666666", lw=1.5)
pylab.xlim((D['ky'][1], D['ky'][-1]))
if (isKinetic) : pylab.ylim((-0.005, 0.015))
else : pylab.ylim((-0.002, 0.005))
pylab.legend(loc='best').draw_frame(0)
pylab.xlabel("$k_y$")
pylab.ylabel("Growthrate $\\omega_i [L_n / v_{te}]$")
# Plot Frequency
pylab.subplot(212)
pylab.semilogx(D['ky'][1:-1], np.real(omega_sim[1:-1]), '^')
def plotFrequencySpectra(fileh5, which='b', markline="-", **kwargs):
"""
Plots time evolution of mode power.
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*modes* List of modes (default plot modes).
e.g. modes = [1,4,5] - to plot all modes
modes = range(Nky)[::2] - to plot every second mode
*field* 'phi' electric potential
'A' parallel magnetic vector potential
'B' parallel magnetic field
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*doCFL* clear previous figure
*label* 'ky' or 'm'
*offset* Offset due to zeroset to 2 .
"""
import gkcData
import gkcStyle
import pylab
import numpy as np
D = gkcData.getDomain(fileh5)
doCFL = kwargs.pop('doCFL', True)
dir = kwargs.pop('dir', 'Y')
modes = kwargs.pop('modes', range(D['Nky']))
field = kwargs.pop('field', 'phi')
n_offset = kwargs.pop('offset', 2)
label = kwargs.pop('label', 'ky')
leg_loc = kwargs.pop('loc', 'best')
start = kwargs.pop('start', 1)
stop = kwargs.pop('stop', -1)
if doCFL == True: pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:, 1]
if field == 'phi': n_field = 0
elif field == 'A': n_field = 1
elif field == 'B': n_field = 2
else: raise TypeError("Wrong argument for field : " + str(field))
if (dir == 'X'):
raise TypeError("Not implemented for X-direction")
elif (dir == 'Y'):
shift = fileh5.root.Analysis.PhaseShift.Y[n_field, :, start:stop]
print "Using data from T=", T[start], " to T = ", T[stop]
freq = []
for nky in np.arange(1, len(D['ky'])):
time_series = np.sin(shift[nky, :])
FS = np.fft.rfft(time_series)
# Not only if we have constant time step !
freq.append(abs(FS))
fftfreq = np.fft.fftfreq(len(abs(np.fft.fftshift(FS))),
d=(T[-10] - T[-11]))
freq = np.array(freq)
print np.shape(fftfreq), " 2 : ", np.shape(D['ky'][1:]), np.shape(freq)
pylab.contourf(D['ky'][1:],
np.fft.fftshift(fftfreq),
freq.T,
100,
cmap=pylab.cm.jet)
pylab.xlim((D['ky'][1], D['ky'][-1]))
pylab.ylim((min(fftfreq), max(fftfreq)))
pylab.colorbar()
else:
raise TypeError("Wrong argument for dir : " + str(dir))
pylab.gca().set_xscale("log")
pylab.xlabel("$k_y$")
gkcStyle.plotZeroLine(D['ky'][1], D['ky'][-1], color='r')
pylab.ylabel("Frequency $\\omega_r(k_y)$")
def plotScalarDataTimeEvolution(fileh5, var="KinPhi", **kwargs):
"""
Plots time evolution of mode power.
Optional keyword arguments:
Keyword Description
=============== ==============================================
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*modes* List of modes (default plot modes).
e.g. modes = [1,4,5] - to plot all modes
modes = range(Nky)[::2] - to plot every second mode
*field* 'phi' electric potential
'A' parallel magnetic vector potential
'B' parallel magnetic field
*dir* Direction 'X' (for radial) or 'Y' for poloidal
*doCFL* clear previous figure
*label* 'ky' or 'm'
*offset* Offset due to zeroset to 2 .
"""
D = gkcData.getDomain(fileh5)
log = kwargs.pop('log', True)
leg_loc = kwargs.pop('leg_loc', 'best')
leg_ncol = kwargs.pop('leg_ncol', 1)
if (log == 1):
plotf = pylab.semilogy
af = abs
else:
plotf = pylab.plot
af = lambda x: x
T = fileh5.root.Analysis.scalarValues.cols.Time[5:]
n_sp = len(fileh5.root.Species.cols.Name[1:])
# Plot Field Energy"
if var == "phi":
plotf(T,
af(fileh5.root.Analysis.scalarValues.cols.phiEnergy[3:]),
label="Field Energy")
pylab.ylabel("Field Energy")
if var == "kinEnergy":
for s in range(n_sp):
plotf(T,
af(fileh5.root.Analysis.scalarValues.cols.KineticEnergy[3:]
[:, s]),
label="Kinetic Energy (" + fileh5.root.Species.cols.Name[s] +
")")
#plotf(T, af(fileh5.root.Analysis.scalarValues.cols.phiEnergy[3:]+1.*(np.sum(fileh5.root.Analysis.scalarValues.cols.KineticEnergy[3:], axis=1))) , label="Total Energy")
pylab.ylabel("Energy")
if var == "KinPhi":
pylab.plot(T,
fileh5.root.Analysis.scalarValues.cols.phiEnergy[5:],
label="Field Energy")
E_kin_total = fileh5.root.Analysis.scalarValues.cols.phiEnergy[5:]
for s in range(n_sp):
E_kin = fileh5.root.Analysis.scalarValues.cols.KineticEnergy[
5:][:,
s] - fileh5.root.Analysis.scalarValues.cols.KineticEnergy[
5][s]
E_kin = -abs(E_kin)
E_kin_total = E_kin_total + E_kin
pylab.plot(T,
E_kin,
label="Kinetic Energy (" +
fileh5.root.Species.cols.Name[s] + ")")
gkcStyle.plotZeroLine(min(T), max(T))
pylab.plot(T, -abs(E_kin_total) / 100., label="Total Energy")
pylab.yscale('symlog', linthreshy=1.e-7)
# Plot Toal nergy
pylab.ylabel("Energy")
if var == "heatFlux":
for s in sp:
for s in range(n_sp):
plot(T,
fileh5.root.Analysis.scalarValues.cols.HeatFlux[3:][:, s],
label=fileh5.root.Species.cols.Name[s])
pylab.ylabel("Heat Flux")
if var == "Charge":
charge = np.zeros(
len(fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3:][:,
1]))
for s in range(n_sp):
dn = (
fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3:][:, s]
- fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3][s])
n = fileh5.root.Analysis.scalarValues.cols.ParticleNumber[3:][:, s]
q = fileh5.root.Species.cols.Charge[s]
charge = charge + q * n
pylab.plot(fileh5.root.Analysis.scalarValues.cols.Time[3:],
q * n,
label=fileh5.root.Species.cols.Name[s])
pylab.plot(fileh5.root.Analysis.scalarValues.cols.Time[3:],
q * dn,
label=fileh5.root.Species.cols.Name[s])
if D['Ns'] > 1:
plotf(fileh5.root.Analysis.scalarValues.cols.Time[3:],
charge,
label="Charge")
gkcStyle.plotZeroLine(min(T), max(T))
pylab.yscale('symlog', linthreshy=1.e-7)
pylab.ylabel("Charge")
if var == "particleFlux":
for s in range(n_sp):
plotf(T,
fileh5.root.Analysis.scalarValues.cols.ParticleFlux[3:][:,
s],
label=fileh5.root.Species.cols.Name[s])
pylab.ylabel("Particle Flux")
pylab.xlim((min(T), max(T)))
leg = pylab.legend(loc=leg_loc, ncol=leg_ncol).draw_frame(0)
pylab.xlabel("Time")
