def plotTurbulenceTime(fileh5, dir='Y', pos=(-2,-1), doFit='False', posT=(1,-1)):
"""
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)
data = fileh5.root.Analysis.PowerSpectrum.Y[1:,:]
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:,1]
timeEvolution = []
for step in range(len(data[0,:])):
timeEvolution.append(data[:,step]/sum(data[:,step]))
contourf(np.log10(D['ky']), T,timeEvolution, 250, locator=ticker.LogLocator(), cmap=cm.jet)
colorbar()
def getFrequencyGrowthrates(fileh5, start=1, stop=-1, q=0):
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:,1]
power = fileh5.root.Analysis.PowerSpectrum.Y[q, :,:]
phase = fileh5.root.Analysis.PhaseShift.Y [q, :,:]
frequency = getFrequency (T,phase, start,stop)
growthrates = getGrowthrate(T,power, start, stop)
return np.array(frequency) + 1.j * np.array(growthrates)
def getFrequencyGrowthrates(fileh5, start=1, stop=-1, q=0):
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:, 1]
power = fileh5.root.Analysis.PowerSpectrum.Y[q, :, :]
phase = fileh5.root.Analysis.PhaseShift.Y[q, :, :]
frequency = getFrequency(T, phase, start, stop)
growthrates = getGrowthrate(T, power, start, stop)
return np.array(frequency) + 1.j * np.array(growthrates)
def plotTurbulenceTime(fileh5,
dir='Y',
pos=(-2, -1),
doFit='False',
posT=(1, -1)):
"""
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)
data = fileh5.root.Analysis.PowerSpectrum.Y[1:, :]
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:, 1]
timeEvolution = []
for step in range(len(data[0, :])):
timeEvolution.append(data[:, step] / sum(data[:, step]))
contourf(np.log10(D['ky']),
T,
timeEvolution,
250,
locator=ticker.LogLocator(),
cmap=cm.jet)
colorbar()
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 plotTimeEvolutionModePhase(fileh5, **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)
leg_loc = kwargs.pop('loc', 'best')
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')
ncol = kwargs.pop('ncol', 2)
if doCFL == True : pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PhaseShift.Time)[2:,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 = plot(T, fileh5.root.Analysis.PhaseShift.X[n_field,:numModes,2:].T)
legend_list = []
for i in range(len(fileh5.root.Analysis.PhaseShift.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 = []
for m in modes:
data = fileh5.root.Analysis.PhaseShift.Y[n_field, m,n_offset:]
# set jump value to nan so it is not plotted, (can we speed up using ma ?)
data_m = []
for n in range(len(data[:-1])):
if abs(data[n] - data[n+1]) < 1.: data_m.append(data[n])
else : data_m.append(float('nan'))
data_m.append(data[-1])
data_m = np.array(data_m)
pl = pylab.plot(T, data_m)
if (label == 'm' ) : legend_list.append("m = %i" % m)
elif(label == 'ky') : legend_list.append("ky = %.1f" % (m / scale))
else : print "Name Error"
leg = pylab.legend(legend_list, loc=leg_loc, ncol=ncol, mode="expand").draw_frame(0)
else : raise TypeError("Wrong argument for dir : " + str(dir))
pylab.xlabel("Time")
pylab.xlim((0.,max(T)))
ax = pylab.gca()
ax.set_yticks([-np.pi, -np.pi/2.,0.,np.pi/2., np.pi])
ax.set_yticklabels(['$-\\pi$','$-\\pi/2$','$0$', '$\\pi/2.$', '$\\pi$'])
pylab.ylim((-3.5,3.5))
if field == "phi" : pylab.ylabel("Mode Phase $|\\phi|^2$")
elif field == "A" : pylab.ylabel("Mode Phase $|A_\\parallel|^2$")
elif field == "B" : pylab.ylabel("Mode Phase $|B_\\parallel|^2$")
else : raise TypeError("Wrong argument for field : " + str(field))
return pl, leg
def plotTimeEvolutionModePower(fileh5, **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)
doLog = kwargs.pop('doLog', True)
dir = kwargs.pop('dir', 'Y')
modes = kwargs.pop('modes' , range(D['Nky']))
field = kwargs.pop('field', 'phi')
n_offset = kwargs.pop('offset', 3)
label = kwargs.pop('label', 'k')
leg_loc = kwargs.pop('loc', 'best')
ncol = kwargs.pop('ncol', 3)
showLegend = kwargs.pop('showLegend', True)
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))
legend_list = []
if(dir == 'X'):
for n in modes:
pl = pylab.semilogy(T[n_offset:], fileh5.root.Analysis.PowerSpectrum.X[n_field, n,n_offset:].T)
if (label == 'm' ) : legend_list.append("n = %i" % n)
elif(label == 'k') : legend_list.append("kx = %.1f" % (D['kx'][n]))
else : print "Name Error"
elif(dir == 'Y'):
legend_list = []
for m in modes:
if(doLog) : pylab.semilogy(T[n_offset:], fileh5.root.Analysis.PowerSpectrum.Y[n_field, m,n_offset:].T, label='$k_y^{(%i)} = %.2f$' % (m, D['ky'][m]))
else : pylab.plot(T[n_offset:], fileh5.root.Analysis.PowerSpectrum.Y[n_field, m,n_offset:].T, label='$k_y^{(%i)} = %.2f$' % (m, D['ky'][m]))
else : raise TypeError("Wrong argument for dir : " + str(dir))
#if showLegend == True:
leg = pylab.legend(loc=leg_loc, ncol=ncol, mode="expand").draw_frame(0)
pylab.xlabel("Time")
pylab.xlim((0.,max(T)))
if field == "phi" : pylab.ylabel("Mode Power $|\\phi|^2$")
elif field == "A" : pylab.ylabel("Mode Power $|A_\\parallel|^2$")
elif field == "B" : pylab.ylabel("Mode Power $|B_\\parallel|^2$")
else : raise TypeError("Wrong argument for field : " + str(field))
def plotModeStructure(fileh5, mode, part = "b", phaseCorrect=True, **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)
field = kwargs.pop('field', 'phi')
Z = kwargs.pop('Z', 0)
frame = kwargs.pop('frame', -1)
label = kwargs.pop('label', "")
norm = kwargs.pop('norm', 'max')
m = kwargs.pop('m', 0)
phase = kwargs.pop('phase', 0.)
color = kwargs.pop('color', '')
phase = np.exp(1.j * phase)
if field == 'phi' :
data_X = fileh5.root.Visualization.Phi[Z,mode,:,frame]
y_label = '$\\phi(x)$'
elif field == 'A' :
data_X = fileh5.root.Visualization.Ap[Z,mode,:,frame]
n_field = 2
y_label = '$A_\parallel(x)$'
elif field == 'B' :
n_field = 2
data_X = fileh5.root.Visualization.Bp[Z,mode,:,frame]
y_label = '$B_\\parallel(x)$'
else : raise TypeError("Wrong argument for field : " + str(field))
print "Mode Structure at T = ", gkcData.getTime(fileh5.root.Visualization.Time)[frame,:]
# Normalization
def Normalize_data(data):
print norm
if norm == 'sum2' : return np.sum(abs(data))
elif norm == 'max' : return abs(data).max()
else : raise TypeError("No such normalization")
if(phaseCorrect == True):
# Calculate phase
phase_shift = np.arctan2(np.sum(np.imag(np.sum(data_X))), np.real(np.sum(data_X)))
print "phaseCorrect = True : Correcting for phase ", phase_shift
data_X = data_X * np.exp(- 1.j * phase_shift)
# Normalization is to real part
if part == "a" :
if color=='' : color='g'
data_X = abs(data_X) / Normalize_data(data_X)
pylab.plot(D['X'], data_X, color=color, label=label)
if part in [ 'r' , 'b' ]:
if color=='' : color='r'
data_X = np.real(data_X * phase) / Normalize_data(np.real(data_X))
pylab.plot(D['X'], data_X, 'o-', color=color, label=label, markersize=8., markeredgecolor='None')
if part in [ 'i', 'b' ] :
if color=='' : color=gkcStyle.color_indigo
data_X = np.imag(data_X * phase) / Normalize_data(np.real(data_X))
pylab.plot(D['X'], data_X, 's-', color=color, label=label, markersize=8., markeredgecolor='None')
#else : raise TypeError("Wrong argument for part : " + str(part))
if field == "phi" : pylab.ylabel("Mode Power $|\\phi|^2$")
elif field == "A" : pylab.ylabel("Mode Power $|A_\\parallel|^2$")
elif field == "B" : pylab.ylabel("Mode Power $|B_\\parallel|^2$")
else : raise TypeError("Wrong argument for field : " + str(field))
pylab.xlim((min(D['X']), max(D['X'])))
pylab.xlabel("X")
pylab.ylabel(y_label)
def plotInstantGrowthrates(fileh5, **kwargs):
"""
Plots instant growthrates 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 scipy.ndimage
import scipy.interpolate
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')
off = kwargs.pop('off', 2)
sigma = kwargs.pop('sigma', 10)
#filterType = kwargs.pop('filterType', 'hanning')
if doCFL == True : pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:,1]
# TimeStep is irregular thus needs to cast into regular
def cast2Equidistant(T, Var):
f = scipy.interpolate.interp1d(T, Var)
Tnew = np.linspace(min(T), max(T), 1000)
return Tnew, f(Tnew)
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'):
plot(T, grad)
legend_list = []
for i in range(len(fileh5.root.Analysis.PowerSpectrum.X[n_field,:numModes,0])):
legend_list.append("kx = %i" % i)
leg = legend(legend_list, loc='best', ncol=3)
leg.draw_frame(0)
if(dir == 'Y'):
for m in modes:
Var = fileh5.root.Analysis.PowerSpectrum.Y[n_field,m,off:]
Tn, V = cast2Equidistant(T[off:], np.log(Var))
# Use NdImage for line-smoothening (convolution with gaussian kernel)
V = scipy.ndimage.gaussian_filter(V, sigma=sigma, mode='nearest')
gamma = np.gradient(V, Tn[1]-Tn[0])
pylab.plot(Tn, gamma, "-", label='$k_y^{(%i)} = %.2f$' % (m, D['ky'][m]))#, color=gkcStyle.markers_C[m])
leg = pylab.legend(loc='best', ncol=3).draw_frame(0)
pylab.xlabel("Time")
pylab.xlim((0.,max(T)))
pylab.ylabel("Instant Mode Growth $\gamma$")
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 $\\omega_r(k_y)$")
def plotAveragedFluxes(fileh5, var='H', **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)
start = kwargs.pop('start', 1)
stop = kwargs.pop('stop', -1)
scale = kwargs.pop('scale', 'ky')
field = kwargs.pop('field', 'phi')
if doCFL == True: pylab.clf()
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))
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:, 1]
# Averaged over Z and start stop
if var == 'P':
data = np.mean(fileh5.root.Analysis.Flux.Density[n_field, :, :,
start:stop],
axis=2)
ylabel = "Particle Flux $k_y \\Gamma/\\Gamma_{gB}\,(ky)$"
elif var == 'H':
data = np.mean(fileh5.root.Analysis.Flux.Heat[n_field, :, :,
start:stop],
axis=2)
#ylabel = "Heat Flux $Q/Q_\\textrm{gB}(k_y)$"
ylabel = "Heat Flux $k_y Q/Q_{gB}\,(k_y)$"
else:
raise TypeError("No such variable")
if scale == 'ky': gor_ky = D['ky'][1:]
else: gor_ky = 1.
for s in range(D['Ns']):
species_name = fileh5.root.Species.cols.Name[s + 1]
pylab.semilogx(D['ky'][1:],
gor_ky * data[1:, s],
gkcStyle.markers_D[s] + '-',
label=species_name,
color=gkcStyle.markers_C[s],
markersize=7.)
pylab.xlabel("$k_y \\rho_i$")
pylab.ylabel(ylabel)
pylab.legend(ncol=2).draw_frame(0)
pylab.xlim((0.8 * D['ky'][1], 1.2 * D['ky'][-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 plotTimeEvolutionModePhase(fileh5, **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)
leg_loc = kwargs.pop('loc', 'best')
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')
ncol = kwargs.pop('ncol', 2)
if doCFL == True: pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PhaseShift.Time)[2:, 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 = plot(T, fileh5.root.Analysis.PhaseShift.X[n_field, :numModes,
2:].T)
legend_list = []
for i in range(
len(fileh5.root.Analysis.PhaseShift.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 = []
for m in modes:
data = fileh5.root.Analysis.PhaseShift.Y[n_field, m, n_offset:]
# set jump value to nan so it is not plotted, (can we speed up using ma ?)
data_m = []
for n in range(len(data[:-1])):
if abs(data[n] - data[n + 1]) < 1.: data_m.append(data[n])
else: data_m.append(float('nan'))
data_m.append(data[-1])
data_m = np.array(data_m)
pl = pylab.plot(T, data_m)
if (label == 'm'): legend_list.append("m = %i" % m)
elif (label == 'ky'): legend_list.append("ky = %.1f" % (m / scale))
else: print "Name Error"
leg = pylab.legend(legend_list, loc=leg_loc, ncol=ncol,
mode="expand").draw_frame(0)
else:
raise TypeError("Wrong argument for dir : " + str(dir))
pylab.xlabel("Time")
pylab.xlim((0., max(T)))
ax = pylab.gca()
ax.set_yticks([-np.pi, -np.pi / 2., 0., np.pi / 2., np.pi])
ax.set_yticklabels(['$-\\pi$', '$-\\pi/2$', '$0$', '$\\pi/2.$', '$\\pi$'])
pylab.ylim((-3.5, 3.5))
if field == "phi": pylab.ylabel("Mode Phase $|\\phi|^2$")
elif field == "A": pylab.ylabel("Mode Phase $|A_\\parallel|^2$")
elif field == "B": pylab.ylabel("Mode Phase $|B_\\parallel|^2$")
else: raise TypeError("Wrong argument for field : " + str(field))
return pl, leg
def plotTimeEvolutionModePower(fileh5, **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)
doLog = kwargs.pop('doLog', True)
dir = kwargs.pop('dir', 'Y')
modes = kwargs.pop('modes', range(D['Nky']))
field = kwargs.pop('field', 'phi')
n_offset = kwargs.pop('offset', 3)
label = kwargs.pop('label', 'k')
leg_loc = kwargs.pop('loc', 'best')
ncol = kwargs.pop('ncol', 3)
showLegend = kwargs.pop('showLegend', True)
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))
legend_list = []
if (dir == 'X'):
for n in modes:
pl = pylab.semilogy(
T[n_offset:],
fileh5.root.Analysis.PowerSpectrum.X[n_field, n, n_offset:].T)
if (label == 'm'): legend_list.append("n = %i" % n)
elif (label == 'k'): legend_list.append("kx = %.1f" % (D['kx'][n]))
else: print "Name Error"
elif (dir == 'Y'):
legend_list = []
for m in modes:
if (doLog):
pylab.semilogy(
T[n_offset:],
fileh5.root.Analysis.PowerSpectrum.Y[n_field, m,
n_offset:].T,
label='$k_y^{(%i)} = %.2f$' % (m, D['ky'][m]))
else:
pylab.plot(T[n_offset:],
fileh5.root.Analysis.PowerSpectrum.Y[n_field, m,
n_offset:].T,
label='$k_y^{(%i)} = %.2f$' % (m, D['ky'][m]))
else:
raise TypeError("Wrong argument for dir : " + str(dir))
#if showLegend == True:
leg = pylab.legend(loc=leg_loc, ncol=ncol, mode="expand").draw_frame(0)
pylab.xlabel("Time")
pylab.xlim((0., max(T)))
if field == "phi": pylab.ylabel("Mode Power $|\\phi|^2$")
elif field == "A": pylab.ylabel("Mode Power $|A_\\parallel|^2$")
elif field == "B": pylab.ylabel("Mode Power $|B_\\parallel|^2$")
else: raise TypeError("Wrong argument for field : " + str(field))
def plotModeStructure(fileh5, mode, part="b", phaseCorrect=True, **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)
field = kwargs.pop('field', 'phi')
Z = kwargs.pop('Z', 0)
frame = kwargs.pop('frame', -1)
label = kwargs.pop('label', "")
norm = kwargs.pop('norm', 'max')
m = kwargs.pop('m', 0)
phase = kwargs.pop('phase', 0.)
color = kwargs.pop('color', '')
phase = np.exp(1.j * phase)
if field == 'phi':
data_X = fileh5.root.Visualization.Phi[Z, mode, :, frame]
y_label = '$\\phi(x)$'
elif field == 'A':
data_X = fileh5.root.Visualization.Ap[Z, mode, :, frame]
n_field = 2
y_label = '$A_\parallel(x)$'
elif field == 'B':
n_field = 2
data_X = fileh5.root.Visualization.Bp[Z, mode, :, frame]
y_label = '$B_\\parallel(x)$'
else:
raise TypeError("Wrong argument for field : " + str(field))
print "Mode Structure at T = ", gkcData.getTime(
fileh5.root.Visualization.Time)[frame, :]
# Normalization
def Normalize_data(data):
print norm
if norm == 'sum2': return np.sum(abs(data))
elif norm == 'max': return abs(data).max()
else: raise TypeError("No such normalization")
if (phaseCorrect == True):
# Calculate phase
phase_shift = np.arctan2(np.sum(np.imag(np.sum(data_X))),
np.real(np.sum(data_X)))
print "phaseCorrect = True : Correcting for phase ", phase_shift
data_X = data_X * np.exp(-1.j * phase_shift)
# Normalization is to real part
if part == "a":
if color == '': color = 'g'
data_X = abs(data_X) / Normalize_data(data_X)
pylab.plot(D['X'], data_X, color=color, label=label)
if part in ['r', 'b']:
if color == '': color = 'r'
data_X = np.real(data_X * phase) / Normalize_data(np.real(data_X))
pylab.plot(D['X'],
data_X,
'o-',
color=color,
label=label,
markersize=8.,
markeredgecolor='None')
if part in ['i', 'b']:
if color == '': color = gkcStyle.color_indigo
data_X = np.imag(data_X * phase) / Normalize_data(np.real(data_X))
pylab.plot(D['X'],
data_X,
's-',
color=color,
label=label,
markersize=8.,
markeredgecolor='None')
#else : raise TypeError("Wrong argument for part : " + str(part))
if field == "phi": pylab.ylabel("Mode Power $|\\phi|^2$")
elif field == "A": pylab.ylabel("Mode Power $|A_\\parallel|^2$")
elif field == "B": pylab.ylabel("Mode Power $|B_\\parallel|^2$")
else: raise TypeError("Wrong argument for field : " + str(field))
pylab.xlim((min(D['X']), max(D['X'])))
pylab.xlabel("X")
pylab.ylabel(y_label)
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 plotAveragedFluxes(fileh5, var='H', **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)
start = kwargs.pop('start', 1)
stop = kwargs.pop('stop', -1)
scale = kwargs.pop('scale', 'ky')
field = kwargs.pop('field', 'phi')
if doCFL == True : pylab.clf()
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))
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:,1]
# Averaged over Z and start stop
if var == 'P' :
data = np.mean(fileh5.root.Analysis.Flux.Density[n_field,:,:,start:stop], axis=2)
ylabel = "Particle Flux $k_y \\Gamma/\\Gamma_{gB}\,(ky)$"
elif var == 'H' :
data = np.mean(fileh5.root.Analysis.Flux.Heat [n_field,:,:,start:stop], axis=2)
#ylabel = "Heat Flux $Q/Q_\\textrm{gB}(k_y)$"
ylabel = "Heat Flux $k_y Q/Q_{gB}\,(k_y)$"
else : raise TypeError("No such variable")
if scale == 'ky' : gor_ky = D['ky'][1:]
else : gor_ky = 1.
for s in range(D['Ns']):
species_name = fileh5.root.Species.cols.Name[s+1]
pylab.semilogx(D['ky'][1:], gor_ky * data[1:,s], gkcStyle.markers_D[s]+'-', label=species_name, color=gkcStyle.markers_C[s], markersize=7.)
pylab.xlabel("$k_y \\rho_i$")
pylab.ylabel(ylabel)
pylab.legend(ncol=2).draw_frame(0)
pylab.xlim((0.8*D['ky'][1], 1.2*D['ky'][-1]))
def plotInstantGrowthrates(fileh5, **kwargs):
"""
Plots instant growthrates 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 scipy.ndimage
import scipy.interpolate
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')
off = kwargs.pop('off', 2)
sigma = kwargs.pop('sigma', 10)
#filterType = kwargs.pop('filterType', 'hanning')
if doCFL == True: pylab.clf()
T = gkcData.getTime(fileh5.root.Analysis.PowerSpectrum.Time)[:, 1]
# TimeStep is irregular thus needs to cast into regular
def cast2Equidistant(T, Var):
f = scipy.interpolate.interp1d(T, Var)
Tnew = np.linspace(min(T), max(T), 1000)
return Tnew, f(Tnew)
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'):
plot(T, grad)
legend_list = []
for i in range(
len(fileh5.root.Analysis.PowerSpectrum.X[n_field, :numModes,
0])):
legend_list.append("kx = %i" % i)
leg = legend(legend_list, loc='best', ncol=3)
leg.draw_frame(0)
if (dir == 'Y'):
for m in modes:
Var = fileh5.root.Analysis.PowerSpectrum.Y[n_field, m, off:]
Tn, V = cast2Equidistant(T[off:], np.log(Var))
# Use NdImage for line-smoothening (convolution with gaussian kernel)
V = scipy.ndimage.gaussian_filter(V, sigma=sigma, mode='nearest')
gamma = np.gradient(V, Tn[1] - Tn[0])
pylab.plot(Tn,
gamma,
"-",
label='$k_y^{(%i)} = %.2f$' %
(m, D['ky'][m])) #, color=gkcStyle.markers_C[m])
leg = pylab.legend(loc='best', ncol=3).draw_frame(0)
pylab.xlabel("Time")
pylab.xlim((0., max(T)))
pylab.ylabel("Instant Mode Growth $\gamma$")