Merged changes

tests/python/field-Ag-flow.py

@@ -36,54 +36,6 @@ from fieldplot import fieldplot
 
 import numpy as np
 import cmath
-
-<<<<<<< HEAD
-
-def get_index(array,value):
-    idx = (np.abs(array-value)).argmin()
-    return idx
-
-#Ec = np.resize(Ec, (npts, npts)).T
-
-
-def GetFlow(scale_x, scale_z, Ec, Hc, a, b, nmax):
-    # Initial position
-    flow_x = [a]
-    flow_z = [b]
-    x_pos = flow_x[-1]
-    z_pos = flow_z[-1]
-    x_idx = get_index(scale_x, x_pos)
-    z_idx = get_index(scale_z, z_pos)
-    S=np.cross(Ec[npts*z_idx+x_idx], Hc[npts*z_idx+x_idx].conjugate()).real
-    #if (np.linalg.norm(S)> 1e-4):
-    Snorm_prev=S/np.linalg.norm(S)
-    Snorm_prev=Snorm_prev.real
-    for n in range(0, nmax):
-        #Get the next position
-        #1. Find Poynting vector and normalize it
-        x_pos = flow_x[-1]
-        z_pos = flow_z[-1]
-        x_idx = get_index(scale_x, x_pos)
-        z_idx = get_index(scale_z, z_pos)
-        Epoint = Ec[npts*z_idx+x_idx]
-        Hpoint = Hc[npts*z_idx+x_idx]
-        S=np.cross(Epoint, Hpoint.conjugate())
-        #if (np.linalg.norm(S)> 1e-4):
-        Snorm=S.real/np.linalg.norm(S)
-        #Snorm=Snorm.real
-        #2. Evaluate displacement = half of the discrete and new position
-        dpos = abs(scale_z[0]-scale_z[1])/2.0
-        dx = dpos*Snorm[0];
-        dz = dpos*Snorm[2];
-        x_pos = x_pos+dx
-        z_pos = z_pos+dz
-        #3. Save result
-        flow_x.append(x_pos)
-        flow_z.append(z_pos)
-    return flow_x, flow_z
-
-=======
->>>>>>> feb3ad9a4b3aa424f2e1087b4bc7b9bc52598810
 # # a)
 #WL=400 #nm
 #core_r = WL/20.0
@@ -120,137 +72,6 @@ m[1] = index_Ag/nm
 print "x =", x
 print "m =", m
 
-<<<<<<< HEAD
-npts = 281
-
-factor=3
-scan = np.linspace(-factor*x[0, 0], factor*x[0, 0], npts)
-
-coordX, coordZ = np.meshgrid(scan, scan)
-coordX.resize(npts*npts)
-coordZ.resize(npts*npts)
-coordY = np.zeros(npts*npts, dtype = np.float64)
-
-coord = np.vstack((coordX, coordY, coordZ)).transpose()
-#coord = np.vstack((coordY, coordX, coordZ)).transpose()
-
-terms, Qext, Qsca, Qabs, Qbk, Qpr, g, Albedo, S1, S2 = scattnlay(x, m)
-terms, E, H = fieldnlay(x, m, coord)
-
-P = np.array(map(lambda n: np.linalg.norm(np.cross(E[0][n], H[0][n].conjugate())).real, range(0, len(E[0]))))
-
-Ec = E[0, :, :]
-Hc = H[0, :, :]
-
-
-try:
-    import matplotlib.pyplot as plt
-    from matplotlib import cm
-    from matplotlib.colors import LogNorm
-
-    # min_tick = 0.0
-    # max_tick = 1.0
-
-    Eabs_data = np.resize(P, (npts, npts)).T
-
-    #Eabs_data = np.resize(Eabs, (npts, npts)).T
-    #Eabs_data = np.resize(Eangle, (npts, npts)).T
-    #Eabs_data = np.resize(Habs, (npts, npts)).T
-    #Eabs_data = np.resize(Hangle, (npts, npts)).T
-
-    fig, ax = plt.subplots(1, 1)#, sharey=True, sharex=True)
-
-    #idxs = np.where(np.abs(coordX) < 1e-10)
-    #print H[0, idxs][0, :, 1]
-    #axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, P[idxs], fmt = 'r', label = 'Poynting vector')
-    #axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, np.linalg.norm(E[0, idxs][0], axis = 1), fmt = 'g', label = 'E')
-    # axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, np.linalg.norm(H[0, idxs][0], axis = 1), fmt = 'b', label = 'H')
-    # axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, H[0, idxs][0, :, 1].real, fmt = 'k', label = 'H.r')
-    # axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, H[0, idxs][0, :, 1].imag, fmt = 'b', label = 'H.i')
-    #axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, H[0, idxs][0, :, 0].real, fmt = 'b', label = 'Px')
-    #axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, H[0, idxs][0, :, 1].real, fmt = 'k', label = 'Py')
-    #axs[0].errorbar(coordZ[idxs]*WL/2.0/np.pi/nm, H[0, idxs][0, :, 2].real, fmt = 'b', label = 'Pz')
-
-    #axs[0].legend()
-
-    #fig.tight_layout()
-    # Rescale to better show the axes
-    scale_x = np.linspace(min(coordX)*WL/2.0/np.pi/nm, max(coordX)*WL/2.0/np.pi/nm, npts)
-    scale_z = np.linspace(min(coordZ)*WL/2.0/np.pi/nm, max(coordZ)*WL/2.0/np.pi/nm, npts)
-
-    # Define scale ticks
-    min_tick = np.amin(Eabs_data)
-    max_tick = np.amax(Eabs_data)
-    # scale_ticks = np.power(10.0, np.linspace(np.log10(min_tick), np.log10(max_tick), 6))
-    scale_ticks = np.linspace(min_tick, max_tick, 11)
-
-    # Interpolation can be 'nearest', 'bilinear' or 'bicubic'
-    ax.set_title(r'$Re(E \times H^*)$')
-    cax = ax.imshow(Eabs_data, interpolation = 'nearest', cmap = cm.jet,
-                        origin = 'lower'
-                        #, vmin = min_tick, vmax = max_tick
-                        , extent = (min(scale_x), max(scale_x), min(scale_z), max(scale_z))
-                        #,norm = LogNorm()
-                       )
-    ax.axis("image")
-
-    # # Add colorbar
-    cbar = fig.colorbar(cax, ticks = [a for a in scale_ticks])
-    cbar.ax.set_yticklabels(['%5.3g' % (a) for a in scale_ticks]) # vertically oriented colorbar
-    # pos = list(cbar.ax.get_position().bounds)
-    # fig.text(pos[0] - 0.02, 0.925, '|E|/|E$_0$|', fontsize = 14)
-
-    plt.xlabel('Z, nm')
-    plt.ylabel('X, nm')
-
-    # This part draws the nanoshell
-    from matplotlib import patches
-    s1 = patches.Arc((0, 0), 2.0*core_r, 2.0*core_r,  angle=0.0, zorder=2,
-                     theta1=0.0, theta2=360.0, linewidth=1, color='black')
-    ax.add_patch(s1)
-
-    from matplotlib.path import Path
-    #import matplotlib.patches as patches
-    flow_total = 39
-    for flow in range(0,flow_total):
-        flow_x, flow_z = GetFlow(scale_x, scale_z, Ec, Hc,
-                                 min(scale_x)+flow*(scale_x[-1]-scale_x[0])/(flow_total-1),
-                                 min(scale_z),
-                                 #0.0,
-                                 npts*16)
-        verts = np.vstack((flow_z, flow_x)).transpose().tolist()
-        #codes = [Path.CURVE4]*len(verts)
-        codes = [Path.LINETO]*len(verts)
-        codes[0] = Path.MOVETO
-        path = Path(verts, codes)
-        patch = patches.PathPatch(path, facecolor='none', lw=1, edgecolor='white')
-        ax.add_patch(patch)
-    # # Start powerflow lines in the middle of the image
-    # flow_total = 131
-    # for flow in range(0,flow_total):
-    #     flow_x, flow_z = GetFlow(scale_x, scale_z, Ec, Hc,
-    #                              min(scale_x)+flow*(scale_x[-1]-scale_x[0])/(flow_total-1),
-    #                              15.0, #min(scale_z),
-    #                              npts*6)
-    #     verts = np.vstack((flow_z, flow_x)).transpose().tolist()
-    #     #codes = [Path.CURVE4]*len(verts)
-    #     codes = [Path.LINETO]*len(verts)
-    #     codes[0] = Path.MOVETO
-    #     path = Path(verts, codes)
-    #     patch = patches.PathPatch(path, facecolor='none', lw=1, edgecolor='white')
-    #     ax.add_patch(patch)
- 
-    plt.savefig("Ag-flow.png")
-    plt.draw()
-
-    plt.show()
-
-    plt.clf()
-    plt.close()
-finally:
-    print("Qabs = "+str(Qabs));
-#
-=======
 comment='bulk-Ag-flow'
 WL_units='nm'
 npts = 501
@@ -268,6 +89,3 @@ field_to_plot='Pabs'
 
 fieldplot(x,m, WL, comment, WL_units, crossplane, field_to_plot, npts, factor, flow_total, is_flow_extend=False)
 
->>>>>>> feb3ad9a4b3aa424f2e1087b4bc7b9bc52598810
-
-