def plotCrossCorrelateValues(fileh5, A="2DPhi",B="2DTp",frame=-1, Z=0, species=1):
import scipy.signal
D, T, A = gkcData.getData(A, fileh5, Z, frame)
D, T, B = gkcData.getData(B, fileh5, Z, frame)
# first correlate then average
C = []
for nky in np.arange(1,len(A[:,0])): C.append(scipy.signal.correlate(abs(A[nky,:]), abs(B[nky,:])))
Corr = np.array(C)
X = np.linspace(-np.pi, np.pi, len(Corr[0,:]))
Y = (D['ky'])[1:]
ax = pylab.subplot(111)
ax.contourf(X,Y,Corr[:,:],100, cmap=pylab.cm.hot)
#pylab.colorbar()
ax.set_yscale("log")
ax.set_xticks([-np.pi, -np.pi/2., 0, np.pi/2., np.pi])
ax.set_xticklabels(['$\\pi$', '$-\\pi/2$', '$0$', '$\\pi/2$', '$\\pi$'])
ax.plot(np.linspace(0., 0., 101), np.linspace(Y.min(), Y.max(), 101), 'r-')
ax.set_xlim((-np.pi, np.pi))
pylab.ylim((Y.min(), Y.max()))
pylab.xlabel("Phase")
pylab.ylabel("$k_y$")
def plotCrossCorrelateValues(fileh5,
A="2DPhi",
B="2DTp",
frame=-1,
Z=0,
species=1):
import scipy.signal
D, T, A = gkcData.getData(A, fileh5, Z, frame)
D, T, B = gkcData.getData(B, fileh5, Z, frame)
# first correlate then average
C = []
for nky in np.arange(1, len(A[:, 0])):
C.append(scipy.signal.correlate(abs(A[nky, :]), abs(B[nky, :])))
Corr = np.array(C)
X = np.linspace(-np.pi, np.pi, len(Corr[0, :]))
Y = (D['ky'])[1:]
ax = pylab.subplot(111)
ax.contourf(X, Y, Corr[:, :], 100, cmap=pylab.cm.hot)
#pylab.colorbar()
ax.set_yscale("log")
ax.set_xticks([-np.pi, -np.pi / 2., 0, np.pi / 2., np.pi])
ax.set_xticklabels(['$\\pi$', '$-\\pi/2$', '$0$', '$\\pi/2$', '$\\pi$'])
ax.plot(np.linspace(0., 0., 101), np.linspace(Y.min(), Y.max(), 101), 'r-')
ax.set_xlim((-np.pi, np.pi))
pylab.ylim((Y.min(), Y.max()))
pylab.xlabel("Phase")
pylab.ylabel("$k_y$")
def plotContour(fileh5, var="2DPhi", **kwargs):
"""
Plots Scalar Data (2D) in XY coordinates
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)
#norm = kwargs.pop('Normalize', True)
Z = kwargs.pop('Z', 0)
modes = kwargs.pop('modes' , range(D['Nky']))
doCFL = kwargs.pop('doCFL' , True)
#interpolation = kwargs.pop('interpolation' , 'bilinear')
printTitle = kwargs.pop('printTitle' , True)
#orientation = kwargs.pop('orientation' , 'horizontal')
frame = kwargs.pop('frame' , -1)
D, T, data = gkcData.getData(var, fileh5, Z, frame, species=0)
X, Y, data = gkcData.getRealFromXky(fileh5, data, modes)
gkcStyle.plotContourWithColorbar(X,Y, data, **kwargs)
pylab.xlabel(kwargs.pop('xlabel' , 'X'))
pylab.ylabel(kwargs.pop('ylabel' , 'Y'))
if printTitle == True : pylab.title("TimeStep : %i Time : %.3f " % (T[0], T[1]))
def plotContour(fileh5, var="2DPhi", **kwargs):
"""
Plots Scalar Data (2D) in XY coordinates
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)
#norm = kwargs.pop('Normalize', True)
Z = kwargs.pop('Z', 0)
modes = kwargs.pop('modes', range(D['Nky']))
doCFL = kwargs.pop('doCFL', True)
#interpolation = kwargs.pop('interpolation' , 'bilinear')
printTitle = kwargs.pop('printTitle', True)
#orientation = kwargs.pop('orientation' , 'horizontal')
frame = kwargs.pop('frame', -1)
D, T, data = gkcData.getData(var, fileh5, Z, frame, species=0)
X, Y, data = gkcData.getRealFromXky(fileh5, data, modes)
gkcStyle.plotContourWithColorbar(X, Y, data, **kwargs)
pylab.xlabel(kwargs.pop('xlabel', 'X'))
pylab.ylabel(kwargs.pop('ylabel', 'Y'))
if printTitle == True:
pylab.title("TimeStep : %i Time : %.3f " % (T[0], T[1]))
