def plotContours(): ky = 0.5 R = linspace(-1.5, 0.5, 16) I = linspace(0., 10., 16) V = zeros((len(R),len(I)), dtype=complex) for r in range(len(R)): for i in range(len(I)): A = zeros((Nx,Nx), dtype=complex) iCode.setupMatrixPy(species, R[r]+1.j*I[i], ky, X, kx_list, Ls, Ln, Nx, A, dk*dx, lambda_D2) val = det(A) #(sign, logdet) = np.linalg.slogdet(A) #val = sign * logdet V[r,i] = val print "x, y", R[r], I[i] , " r : ", val subplot(131) contourf(R,I,real(V), 100) colorbar() subplot(132) contourf(R,I,imag(V), 100) colorbar() subplot(133) contourf(R,I,abs(V), 100) colorbar() #pcolor(R,I,imag(V)) savefig("Contour.png")
def plotContours(): ky = 0.5 R = linspace(-0.5, 0.5, 8) I = linspace(-.3, 0.3, 8) V = zeros((len(R),len(I)), dtype=complex) fig = figure(figsize=(30,10)) n = 0 for r in range(len(R)): for i in range(len(I)): A = zeros((Nx,Nx), dtype=complex) iCode.setupMatrixPy(species, R[r]+1.j*I[i], ky, X, kx_list, Ls, Ln, Nx, A, dk*dx, lambda_D2) #val = getMinEigenvalue(A) (sign, logdet) = np.linalg.slogdet(A) val = sign * logdet V[r,i] = val #print "x, y", R[r], I[i] , " r : ", val print n, "/", len(R) * len(I) n = n+1 """ #subplot(131) #norm = mpl.colors.Normalize(vmin = -1., vmax = 1.) #contourf(R,I,real(V), 100, vmin=-1., vmax=1., norm = norm) xlabel("Real") ylabel("Imag") cb = colorbar() cb.set_clim(vmin=-1, vmax=1) #subplot(132) #contourf(R,I,imag(V), 100, vmin=-1., vmax=1.) #norm = mpl.colors.Normalize(vmin = -1., vmax = 1.) contourf(R,I,imag(V), 100, vmin=-1., vmax=1., norm = norm) xlabel("Real") ylabel("Imag") cb = colorbar() cb.set_clim(vmin=-1, vmax=1) subplot(133) """ pcolor(R,I,log10(abs(V))) xlabel("Real") ylabel("Imag") cb = colorbar() #cb.set_clim(vmin=0., vmax=1) #pcolor(R,I,imag(V)) savefig("Contour.png")
def plotContours(): ky = 0.5 R = linspace(-0.5, 0.5, 8) I = linspace(-.3, 0.3, 8) V = zeros((len(R), len(I)), dtype=complex) fig = figure(figsize=(30, 10)) n = 0 for r in range(len(R)): for i in range(len(I)): A = zeros((Nx, Nx), dtype=complex) iCode.setupMatrixPy(species, R[r] + 1.j * I[i], ky, X, kx_list, Ls, Ln, Nx, A, dk * dx, lambda_D2) #val = getMinEigenvalue(A) (sign, logdet) = np.linalg.slogdet(A) val = sign * logdet V[r, i] = val #print "x, y", R[r], I[i] , " r : ", val print n, "/", len(R) * len(I) n = n + 1 """ #subplot(131) #norm = mpl.colors.Normalize(vmin = -1., vmax = 1.) #contourf(R,I,real(V), 100, vmin=-1., vmax=1., norm = norm) xlabel("Real") ylabel("Imag") cb = colorbar() cb.set_clim(vmin=-1, vmax=1) #subplot(132) #contourf(R,I,imag(V), 100, vmin=-1., vmax=1.) #norm = mpl.colors.Normalize(vmin = -1., vmax = 1.) contourf(R,I,imag(V), 100, vmin=-1., vmax=1., norm = norm) xlabel("Real") ylabel("Imag") cb = colorbar() cb.set_clim(vmin=-1, vmax=1) subplot(133) """ pcolor(R, I, log10(abs(V))) xlabel("Real") ylabel("Imag") cb = colorbar() #cb.set_clim(vmin=0., vmax=1) #pcolor(R,I,imag(V)) savefig("Contour.png")
def setup_L(w): L[:,:] = 0. iCode.setupMatrixPy(species, w, ky, X, kx_list, Ls, Ln, Nx, L, dk*dx, lambda_D2) return L
def setupA(w): A[:,:] = 0. iCode.setupMatrixPy(species, w, ky, X, kx_list, Ls, Ln, Nx, A, dk*dx, lambda_D2) return A
def setup_L(w): L[:, :] = 0. iCode.setupMatrixPy(species, w, ky, X, kx_list, Ls, Ln, Nx, L, dk * dx, lambda_D2) return L