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]))