def propagate_wavefront(wavefront, beamline, output_file=None):
"""
Propagate wavefront and store it in output file.
:param wavefront: wpg.Wavefront object or path to HDF5 file
:param beamline: SRWLOptC container of beamline
:param output_file: if parameter present - store propagaed wavefront to file
:return: propagated wavefront object
"""
if not isinstance(beamline, Beamline):
bl = Beamline(beamline)
else:
bl = beamline
print(bl)
if isinstance(wavefront, Wavefront):
wfr = Wavefront(srwl_wavefront=wavefront._srwl_wf)
else:
print('*****reading wavefront from h5 file...')
wfr = Wavefront()
wfr.load_hdf5(wavefront)
print_mesh(wfr)
print('*****propagating wavefront (with resizing)...')
bl.propagate(wfr)
if output_file is not None:
print('save hdf5:', output_file)
wfr.store_hdf5(output_file)
print('done')
return wfr
def do_wpg_calculation(self):
aperture = Aperture(shape='r',
ap_or_ob='a',
Dx=self.horApM1,
Dy=self.range_xy)
wavefront = self.input_data.get_wavefront()
beamline_for_propagation = Beamline()
beamline_for_propagation.append(aperture, Use_PP())
beamline_for_propagation.propagate(wavefront)
return wavefront
def do_wpg_calculation(self):
rMinCRL = 2 * self.delta * self.input_data.get_distance_to_previous(
) / self.nCRL #CRL radius at the tip of parabola [m]
opCRL = create_CRL_from_file(self.working_directory, self.file_name, 3,
self.delta, self.attenLen, 1,
self.diamCRL, self.diamCRL, rMinCRL,
self.nCRL, self.wallThickCRL, 0, 0, None)
wavefront = self.input_data.get_wavefront()
beamline_for_propagation = Beamline()
beamline_for_propagation.append(opCRL, Use_PP())
beamline_for_propagation.append(Drift(self.distance),
Use_PP(semi_analytical_treatment=1))
beamline_for_propagation.propagate(wavefront)
return wavefront
def main():
d2waist = 270.
# beam parameters:
qnC = 0.1 # [nC] e-bunch charge
thetaOM = 3.6e-3
ekev = 5.0
# calculate angular divergence:
theta_fwhm = (17.2 - 6.4 * np.sqrt(qnC)) * 1e-6 / ekev**0.85
theta_rms = theta_fwhm / 2.35
sigX = 12.4e-10 / (ekev * 4 * np.pi * theta_rms)
# define limits
xmax = theta_rms * d2waist * 3.5
xmin = -xmax
ymin = xmin
ymax = xmax
nx = 600
ny = nx
nz = 5
tau = 0.12e-15
srw_wf = build_gauss_wavefront(nx, ny, nz, ekev, xmin, xmax, ymin, ymax,
tau, sigX, sigX, d2waist)
wf = wpg.Wavefront(srw_wf)
b = Beamline()
b.append(Drift(5), Use_PP())
b.propagate(wf)
# srwl.ResizeElecField(srw_wf, 'c', [0, 0.25, 1, 0.25, 1])
if not os.path.exists('tests_data'):
os.mkdir('tests_data')
wf_hdf5_out_file_path = os.path.join('tests_data', 'my_gauss.h5')
wf.store_hdf5(wf_hdf5_out_file_path)
wf_out = wpg.Wavefront()
wf_out.load_hdf5(wf_hdf5_out_file_path)
return wf
def scale(self, wfr, iscx=1024, iscy=1024, ifov=800e-06):
"""
DEPR.
narrow functionality for scaling a wavefront (ie the number of pixels)
in the source plane
:param wfr: wpg wfr strucutre
:param isc: ideal scale
:param ifov: ideal field of view
:returns wfr: scaled wpg wfr structure
"""
nx, ny = wfr.params.Mesh.nx, wfr.params.Mesh.ny
dx, dy = wfr.params.Mesh.xMax - wfr.params.Mesh.xMin, wfr.params.Mesh.yMax - wfr.params.Mesh.yMin
scbl = Beamline()
scbl.append(
Aperture('r', 'a', 800e-06, 800e-06),
propagation_parameters(dx / ifov, iscx / nx, dy / ifov, iscy / ny))
scbl.propagate(wfr)
return wfr
ekev = 25
wav = ekev2wav(25)
k = np.pi * 2 / wav
delta = 4e-07
d2waist = (wav) / (np.arctan(.27 / 8) * np.pi)
r = 75e-03
wfr = Wavefront(
construct_gaussian(1024, 1024, 25, -15e-02, 15e-02, -15e-02, 15e-02, 3e-2,
3e-02, d2waist))
### PLOT 1
plot_intensity_map(wfr)
bl = Beamline()
bl.append(Drift(1), propagation_parameters(1, 1, 1, 1))
bl.propagate(wfr)
x = np.linspace(wfr.params.Mesh.xMin, wfr.params.Mesh.xMax, wfr.params.Mesh.nx)
y = np.ones([wfr.params.Mesh.nx, wfr.params.Mesh.ny])
thickness = norm(cylinder_thickness(x, r, offset=0), lim=(0, 255))
sdir = "../../data/samples/cylinder_thickness.png"
im = Image.fromarray(thickness * y)
im = im.convert("L")
im.save(sdir)
def build_beamline(self, focus="nano", screens="false"):
"""
Construct the beamline object
:param focus: what beamline configuration (micron or nano)
"""
self.bl = Beamline()
if focus == "micron":
self.bl.append(
self.d1, propagation_parameters(1, 1, 1, 1, mode="fraunhofer"))
self.bl.append(self.HOM1,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d2, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.HOM2,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d3, propagation_parameters(1, 1, 1, 1, mode='fraunhofer'))
self.bl.append(
self.MKB_pslit,
propagation_parameters(1 / 5, 1, 1 / 5, 1, mode='fresnel'))
self.bl.append(
self.d4, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.MHP,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d5, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.MHE,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(self.MHE_error,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d6, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.MVE,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(self.MVE_error,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d8, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.MVP,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(self.df,
propagation_parameters(5, 1, 5, 1, mode='converge'))
elif focus == "nano":
self.bl.append(
self.d1, propagation_parameters(1, 1, 1, 1, mode="fraunhofer"))
self.bl.append(self.HOM1,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d2, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.HOM2,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d3, propagation_parameters(1, 1, 1, 1, mode='fraunhofer'))
self.bl.append(
self.NKB_pslit,
propagation_parameters(1 / 10, 1, 1 / 10, 1, mode='fresnel'))
self.bl.append(
self.d4, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.NHE_error,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(self.NHE,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(
self.d5, propagation_parameters(1, 1, 1, 1, mode='quadratic'))
self.bl.append(self.NVE_error,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(self.NVE,
propagation_parameters(1, 1, 1, 1, mode='fresnel'))
self.bl.append(self.df,
propagation_parameters(1, 1, 1, 1, mode='converge'))
self.bl.params = self.params
