rays_dict = fi1.get_rays_dict()
#rays_dict = {"startz":[0], "starty": [0], "radius": [16],
# "anglex": [0., 0.1832595],
# "rasterobj":raster.RectGrid()}
#wavelength = [0.5875618e-3, 0.4861327e-3, 0.6562725e-3]
#numrays = 50
sample_param = 'bundle'
(initialbundle, meritfunctionrms) = get_bundle_merit(osa,
s,
sysseq,
rays_dict,
fi1.numrays,
fi1.wavelengths,
whichmeritfunc='sgd2',
error='error2',
sample_param=sample_param,
penalty=True,
penaltyVerz=True)
# ----- plot the original system
# --- set the plot setting
pn = np.array([1, 0, 0])
up = np.array([0, 1, 0])
fig = plt.figure(1)
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
# II---------------------- optical system analysis
# --- 1. elem
sysseq=fi1.get_sysseq(elem1);
# ----------- define optical system analysis object
osa = OpticalSystemAnalysis(s, sysseq)
# III ----------- defining raybundles for optimization and plotting
rays_dict=fi1.get_rays_dict()
(initialbundle, meritfunctionrms) = get_bundle_merit(osa, s, sysseq, rays_dict,
fi1.numrays, fi1.wavelengths,
whichmeritfunc='standard',
error='error2')
# ----- plot the original system
# --- set the plot setting
pn = np.array([1, 0, 0])
up = np.array([0, 1, 0])
fig = plt.figure(1)
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.axis('equal')
ax2.axis('equal')
# --- plot the bundles and draw the original system
rays_dict = fi1.get_rays_dict()
#rays_dict = {"startz":[0], "starty": [0], "radius": [16],
# "anglex": [0., 0.1832595],
# "rasterobj":raster.RectGrid()}
#wavelength = [0.5875618e-3, 0.4861327e-3, 0.6562725e-3]
#numrays = 50
sample_param = 'wave'
(initialbundle,
meritfunctionrms) = get_bundle_merit(osa,
s,
sysseq,
rays_dict,
fi1.numrays,
fi1.wavelengths,
whichmeritfunc='sgd',
error='error2',
sample_param=sample_param,
penalty=False)
# ----- plot the original system
# --- set the plot setting
pn = np.array([1, 0, 0])
up = np.array([0, 1, 0])
fig = plt.figure(1)
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.axis('equal')
# ----------- define optical system analysis object
osa = OpticalSystemAnalysis(s, sysseq)
# III ----------- defining raybundles for optimization and plotting
rays_dict = fi1.get_rays_dict()
#TODO In Landos code noch wavelength and numrays einpflegen
wavelength = [0.58749e-3] #, 0.6562725e-3]
numrays = 10
(initialbundle,
meritfunctionrms) = get_bundle_merit(osa,
s,
sysseq,
rays_dict,
fi1.numrays,
fi1.wavelengths,
whichmeritfunc='standard2',
error='error2',
penaltyVerz=True)
# ----- plot the original system
# --- set the plot setting
pn = np.array([1, 0, 0])
up = np.array([0, 1, 0])
fig = plt.figure(1)
#ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(111)
#ax1.axis('equal')
ax2.axis('equal')
"startz": [-7],
"starty": [0],
"radius": [5],
"anglex": [0.03, -0.05],
"raster": raster.RectGrid()
}
# rastertype = raster.RectGrid()
# define wavelengths
wavelength = [0.5875618e-3, 0.4861327e-3] #, 0.6562725e-3]
numrays = 10
(initialbundle,
meritfunctionrms) = get_bundle_merit(osa,
s,
sysseq,
rays_dict,
numrays,
wavelength,
whichmeritfunc='standard_error2')
# ----- plot the original system
# --- set the plot setting
pn = np.array([1, 0, 0])
up = np.array([0, 1, 0])
fig = plt.figure(1)
ax1 = fig.add_subplot(211)
ax2 = fig.add_subplot(212)
ax1.axis('equal')
ax2.axis('equal')
