ii = np.arange(nlayers)
phi = 2 * np.pi / pitch * ii * step
eps_angles = np.zeros(
shape=(nlayers, 3), dtype="float32"
) #in case we compiled for float32, this has to be float not duouble
eps_angles[..., 1] = np.pi / 2 #theta angle - in plane director
eps_angles[..., 2] = phi
d = np.ones((nlayers, ), "float32") * (thickness / nlayers)
n = [no, no, ne]
#: layer thickness time wavenumber
kd = 2 * np.pi / wavelengths * step
#: input epsilon -air
eps_in = dtmm.refind2eps(nin)
#: layer epsilon
eps_layer = dtmm.refind2eps(n)
eps_layers = np.array([eps_layer] * nlayers, dtype="complex64")
#: substrate epsilon
eps_out = dtmm.refind2eps(nout)
#: ray beta parameters; beta is nin*np.sin(theta)
beta = 0.
phi = 0.
#stack = d,eps_layers, eps_angles
#cmat = dtmm.tmm.stack_mat(stack,kd, beta = beta, phi = phi)
#build field matrices
a, f, fi = dtmm.tmm.alphaffi(beta, phi, eps_layers, eps_angles)
def beam_waist(z, w0, k):
z0 = w0**2 * k / 2.
return w0 * (1 + (z / z0)**2)**0.5
window = dtmm.window.gaussian_beam(shape, w0, dtmm.k0(600, 50), n=n, z=0)
field, w, p = dtmm.illumination_data(shape, [w],
pixelsize=50,
n=n,
window=window,
jones=(1, 0))
ks = dtmm.k0(w, p)
epsv = dtmm.refind2eps([n] * 3)
power = dtmm.field2intensity(field)
plt.subplot(121)
plt.imshow(power[0])
plt.title("z=0")
waist = []
z = np.linspace(-512, 512, 13)
for d in z:
dmat = dtmm.diffract.field_diffraction_matrix(shape,
ks,
d=d,
epsv=epsv,
betamax=1.)
import dtmm
import numpy as np
dtmm.conf.set_verbose(1)
THICKNESS = 100
#: pixel size in nm
PIXELSIZE = 200
#: compute box dimensions
NLAYERS, HEIGHT, WIDTH = 1,96,96
#: illumination wavelengths in nm
WAVELENGTHS = np.linspace(400,700,9)
#: some experimental data
BETA = 0.4
epsv = dtmm.refind2eps([4,4,4]) #high reflective index medium, to increase reflections.
epsa = (0.,0.,0.)
optical_data = [(THICKNESS, epsv, epsa)]
window = dtmm.aperture((HEIGHT, WIDTH),0.2,1)
#illumination data is focused at the top (exit) surface (actual focus = focus * ref_ind = 25*4=100)
field_data_in = dtmm.illumination_data((HEIGHT, WIDTH), WAVELENGTHS, window = window,
beta = BETA, pixelsize = PIXELSIZE,focus = 25.,n=1)
#illumination filed is defined in vacuum, so we make input and output medium with n = 1.
field_data_out = dtmm.transfer_field(field_data_in, optical_data, beta = BETA, phi = 0.,
reflection = 2, diffraction =1, npass = 3, method = "2x2",nin = 1, nout = 1)
#we are viewing computed data in vacuum, so set n = 1.
wavelength = 550
#: thickness of layer in microns
thickness = 2.
#: refractive indices of the anisotropic layer
n = [1.5, 1.5, 1.5]
#n = [np.sqrt(-10+0.32j)]*3#silver
#: euler angles of the optical axes (will make effect for anisotropic)
eps_angles = np.array(
[0, 0.2, 0.4], dtype="float32"
) #in case we compiled for float32, this has to be float not duouble
#: refractive indices if the substrate
nout = [1.] * 3
#: phase retardation - layer thickness times wavenumber
kd = 2 * np.pi / wavelength * thickness * 1000.
#: input epsilon -air
eps_in = dtmm.refind2eps([1., 1., 1.])
#: layer epsilon
eps_layer = dtmm.refind2eps(n)
#: substrate epsilon
eps_out = dtmm.refind2eps(nout)
#: ray beta parameters; beta is nin*np.sin(theta)
betas = np.array(
np.linspace(0.0, 0.9999, 1000), dtype="float32"
) #in case we compiled for float32, this has to be float not duouble
#: phi angle of the input light - will make a diffference for anisotropic layer
phi = 0.0
_phi = 0
pol1 = (-np.sin(_phi), np.cos(_phi))
pol2 = (np.cos(_phi), np.sin(_phi))
_phi = np.linspace(0, np.pi/2, nlayers) eps_angles = np.zeros(shape = (nlayers+2,3), dtype = "float32") #in case we compiled for float32, this has to be float not duouble eps_angles[1:-1,1] = np.pi/2 #theta angle - in plane director eps_angles[1:-1,2] = _phi d = np.ones((nlayers+2,),"float32") d[0] = 0 #first layer is zero thickness d[-1] = 0 #last too... n = [no,no,ne] #: layer thickness times wavenumber kd = 2*np.pi/wavelengths[:,None]* step * d #: input epsilon -air eps_in = dtmm.refind2eps([nin]*3) #: layer epsilon eps_layer = dtmm.refind2eps(n) eps_values = np.array([eps_layer]*(nlayers+2), dtype = "complex64") eps_values[0] = dtmm.refind2eps([nin]*3) eps_values[-1] = dtmm.refind2eps([nout]*3) #stack = d,eps_values, eps_angles #cmat = tmm.stack_mat(stack,kd, beta = beta, phi = phi) #build field matrices a,f,fi = tmm.alphaffi(beta,phi,eps_values, eps_angles) fout = f[-1]
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Plot material example"""
import dtmm
data = dtmm.nematic_droplet_data((60, 128, 128),
radius=30,
profile="r",
no=1.5,
ne=1.6,
nhost=1.5)
thickness, material_eps, angles = data
fig, ax = dtmm.plot_material(material_eps,
eps=dtmm.refind2eps([1.5, 1.5, 1.6]))
fig.show() #you may call matplotlib.pyplot.show() as well
