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
