'freq_chirp':
0, #dw/dt=[1/fs**2] - requency chirp of the beam around power_center[2]
'en_pulse': None, #total energy or max power of the pulse, use only one
'power': 1e6,
}
dfl = generate_dfl(**kwargs)
#Gaussian beam defenition
#plot_dfl(dfl, fig_name='before', phase=0)
###
#RectApp = RectMask(dfl.shape())
#RectApp.lx = 0.0005
#RectApp.ly = 0.0005
#RectApp.apply(dfl)
###
#EllipsApp = EllipsMask(shape = dfl.shape())
#EllipsApp.ax = 0.0005
#EllipsApp.ay = 0.0005
#dfl=EllipsApp.apply(dfl)
###
RectApp = ApertureRect(lx=0.0005, ly=0.0005, cx=0, cy=0)
EllipsApp = ApertureEllips(ax=0.0006, ay=0.0006, cx=0, cy=0)
line = (RectApp, EllipsApp)
lat = OpticsLine(line)
#
dfl = propagate(lat, dfl)
plot_dfl(dfl, fig_name='after', phase=0)
'dgrid': (400e-5, 400e-5, 35e-6), #(x,y,z) [m] - size of field matrix
'power_rms':
(25e-5, 25e-5,
4e-6), #(x,y,z) [m] - rms size of the radiation distribution (gaussian)
'power_center':
(0, 0, None), #(x,y,z) [m] - position of the radiation distribution
'power_angle': (0,
0), #(x,y) [rad] - angle of further radiation propagation
'power_waistpos':
(0, 0), #(Z_x,Z_y) [m] downstrean location of the waist of the beam
'wavelength':
None, #central frequency of the radiation, if different from xlamds
'zsep': None, #distance between slices in z as zsep*xlamds
'freq_chirp':
0, #dw/dt=[1/fs**2] - requency chirp of the beam around power_center[2]
'en_pulse': None, #total energy or max power of the pulse, use only one
'power': 1e6,
}
#dfl = RadiationField()
dfl = generate_gaussian_dfl(**kwargs)
#Gaussian beam defenition
appRect = ApertureRectMask(lx=9e-4, ly=9e-4, cx=0, cy=0)
prop = PropMask(z0=30)
appRect.apply(dfl)
prop.apply(dfl)
plot_dfl(dfl, phase=True, fig_name='after', domain='sf')
'zsep': None, #distance between slices in z as zsep*xlamds
'freq_chirp':
0, #dw/dt=[1/fs**2] - requency chirp of the beam around power_center[2]
'en_pulse': None, #total energy or max power of the pulse, use only one
'power': 1e6,
}
dfl1 = generate_dfl(**kwargs)
#Gaussian beam defenition
dfl2 = generate_dfl(**kwargs)
#Gaussian beam defenition
#plot_dfl(dfl, fig_name='before', phase=0)
#QuadCurvMask(r = 0, plane='x').apply(dfl1)
#H1 = QuadCurvMask(r = 25, plane='x').get_mask(dfl1)
#H2 = QuadCurvMask(r = 25, plane='y').get_mask(dfl1)
#print(H1)
#print('aaaaaaaaaaaaaa')
#print(H2)
l = ThinLens(fx=15, fy=10)
##
line = (l)
lat = OpticsLine(line)
###
dfl2 = propagate(lat, dfl2)
#plot_dfl(dfl1, fig_name='after_dfl1', phase=0)
plot_dfl(dfl2, fig_name='after_dfl2', phase=0)
##generating RadiationField() objects
#help(generate_dfl)
dfl = generate_gaussian_dfl(**kwargs)
#Gaussian
#dfl = imitate_sase_dfl(**kwargs); help(imitate_sase_dfl) #SASE-like (same as Gaussian, but modulated in time by amplitude and phase to model Gaussian random process)
#help(plot_dfl)
plot_dfl(
dfl,
domains=None,
z_lim=[],
xy_lim=[],
figsize=4,
cmap='viridis', #jet
phase=False,
fig_name='default_dfl_plot',
auto_zoom=False,
column_3d=True,
savefig=False,
showfig=True,
return_proj=False,
line_off_xy=True,
log_scale=0,
debug=1,
cmap_cutoff=0)
plot_dfl(dfl, fig_name='dfl_xy', column_3d=0, phase=1)
plot_dfl(dfl, fig_name='dfl', domains='kt')
plot_dfl(dfl, fig_name='dfl', domains='sf')
plot_dfl(dfl, fig_name='dfl', domains='kf')
plot_dfl(dfl, fig_name='dfl', log_scale=1)
hprofile = generate_1d_profile(hrms=1e-9, # [m] height errors root mean square
length=0.03, # [m] length of the mirror surface
points_number=1111, # number of points (pixels) at the mirror surface
wavevector_cutoff=0, # [1/m] point on k axis for cut off large wave lengths in the PSD (with default value 0 effects on nothing)
k=None, # [1/m] one dimension numpy.ndarray of wave vectors; if specified, psd will be calculated using this values as arguments
psd=None, # [m^3] 1d array; power spectral density of surface (if not specified, will be generated)
seed=666) # seed for np.random.seed() to allow reproducibility
# plotting 1d height profile
plot_1d_hprofile(hprofile, fig_name='mirror1 height profile and PSD')
# generating gaussian RadiationField
dfl = generate_gaussian_dfl(1e-9, (1000, 1000, 1))
# plotting generated RadiationField
plot_dfl(dfl, phase=1, fig_name='radiation before mirror1')
# reflecting generated RadiationField from the imperfect mirror
dfl_reflect_surface(dfl, # ocelot.optics.wave.RadiationField, which will be reflected from imperfect mirror surface (hprofile2)
angle=np.pi * 2 / 180, # [radians] angle of incidence with respect to the surface
hrms=None, # [m] height errors root mean square
height_profile=hprofile, # HeightProfile object of the reflecting surface (if not specified, will be generated using hrms)
axis='x') # direction along which reflection takes place
# plotting RadiationField after reflection
plot_dfl(dfl, phase=1, fig_name='radiation after reflection from mirror1')
# propagating RadiationField for 10 meters
dfl.prop(z=10)
# plotting RadiationField after propagation
dfl_SERVAL.xlamds = xlamds # SVEA carrieer frequency
dfl_SERVAL.fld = np.random.randn(dfl_SERVAL.Nz(), dfl_SERVAL.Ny(), dfl_SERVAL.Nx()) + 1j * np.random.randn(dfl_SERVAL.Nz(), dfl_SERVAL.Ny(), dfl_SERVAL.Nx()) # Gaussian noise
# dfl_SERVAL.fld = np.random.randn(dfl_SERVAL.Nz(), dfl_SERVAL.Ny(), dfl_SERVAL.Nx()) + 1j * np.random.randn(dfl_SERVAL.Nz(), dfl_SERVAL.Ny(), dfl_SERVAL.Nx()) # Gaussian noise
dfl_SERVAL.filePath = filePath+'.dfl'
# dfl_omega_0 = 2*np.pi * speed_of_light / dfl.xlamds # set undulator resonance to SVEA carrier frequency (to the middle of the photon energy domain mesh)
# radiation_omega_resonance = dfl_omega_0 * 1.01 # shift undulator resonance to the right
fieldname_SERVAL = '0-source_SERVAL'
dfl_SERVAL = undulator_field_dfl_SERVAL(dfl_SERVAL, L_w=L_w,
sig_x=ebeam_sigma_x, sig_y=ebeam_sigma_y,
sig_xp=ebeam_sigma_xp, sig_yp=ebeam_sigma_yp,
k_support = 'intensity', s_support='conv_intensities', showfig=False)
plot_dfl(dfl_SERVAL, domains='sf', phase=True, fig_name = fieldname_SERVAL)
plot_dfl(dfl_SERVAL, domains='kf', phase=True, fig_name = fieldname_SERVAL)
#%%
dfl_prop_SERVAL = deepcopy(dfl_SERVAL)
fieldname_SERVAL = '1-far_zone_25_m_SERVAL'
dfl_prop_SERVAL.prop_m(25, m=[12, 12])
dfl_prop_SERVAL.to_domain(domains='sf')
plot_dfl(dfl_prop_SERVAL, domains='sf', phase=True, fig_name = fieldname_SERVAL)
plot_dfl(dfl_prop_SERVAL, domains='kf', phase=True, fig_name = fieldname_SERVAL)
corr_SERVAL = dfl_xy_corr(dfl_prop_SERVAL, norm=1)
plot_dfl(corr_SERVAL, domains='sf', phase=True, fig_name = 'corr')
#%%
power_center=power_center,
power=(1e6),
phase_chirp_lin=0)
dflL = generate_gaussian_dfl(xlamds=lamds,
wavelength=lamds + dlamds,
dgrid=(grid_xy, grid_xy, grid_z),
shape=(shape_xy, shape_xy, shape_z),
power_rms=(rms_xy, rms_xy, rms_z),
power_center=power_center,
power=(1e6),
phase_chirp_lin=0)
dflR.prop_m(5, m=1)
dflL.prop_m(-10, m=1)
plot_dfl(dflR, cmap='Greys')
S = calc_stokes_dfl(dflR, dflL, basis='rl')
#%% fix
#plot_stokes_values(S[25, np.newaxis, 125, np.newaxis, :], direction='x', fig=plt.figure('Stokes_x_vals'))
#plot_stokes_angles(S[25, np.newaxis, 125, np.newaxis, :], direction='x', fig=plt.figure('Stokes_x_ang'))
#%% fix
#plot_stokes_values(S[:, 125, np.newaxis, 125, np.newaxis], direction='z', fig=plt.figure('Stokes_z_vals'))
#plot_stokes_angles(S[:, 125, np.newaxis, 125, np.newaxis], direction='z', fig=plt.figure('Stokes_z_ang'))
#%%
#normalization = 's0' #normalize to s0 (degree of polarization is depicted, without hint of radiation intensity)
normalization = 's0_max' #normalize to the maximum value of s0 (shall be rewritten in terms of power)
plot_stokes_3d(S,
cmap_lin='brightwheel',
x_plane='max_slice',
screen_2d.ny = 200
screen_2d.nx = 200
screen_2d.start_energy = 7762 # [eV], starting photon energy
screen_2d.end_energy = 7762 # [eV], ending photon energy
screen_2d.num_energy = 1 # number of energy points[eV]
# calculate radiation
screen_2d = calculate_radiation(lat, screen_2d, beam)
# %%
# converting Screen to RadiationField (function generates new RadiationField() without changing Screen)
dfl_2d = screen2dfl(
screen_2d, # Screen object, electric field of which will be used to generate RadiationField
polarization='x'
) # polarization for conversion to RadiationField ('x' or 'y')
plot_dfl(dfl_2d, domains='fs', fig_name='dfl_2d generated from screen_2d')
# scanning for waist position
wfs = dfl_waistscan(dfl_2d, np.linspace(-80, -20, 200))
plot_dfl_waistscan(wfs, fig_name='waist scan of dfl_2d')
# half analytical propagation to waist point
dfl_2d.prop_m(-48.25, m=0.05)
plot_dfl(dfl_2d, domains='fs', fig_name='dfl_2d at waist position')
# %%
# generating 3D synchrotron radiation (it will take up to 5 minute)
# LOOK TUTORIAL ABOUT GENERATING SYNCHROTRON RADIATION IN demos/ipython_tutorials/9_synchrotron_radiation.ipynb
screen_3d = Screen()
screen_3d.z = 50.0 # distance from the begining of lattice to the screen
screen_3d.size_x = 0.0015 # half of screen size in [m] in horizontal plane