def get_fwhm(self):
sig_x, sig_y = calculate_fwhm(self)['fwhm_x'], calculate_fwhm(
self)['fwhm_y']
self.custom_fields['fwhm'] = sig_x, sig_y
return sig_x, sig_y
def simpleProp(wfr):
print(calculate_fwhm(wfr))
bl = Beamline()
#bl.append(Aperture('c','a', 500e-06),propagation_parameters(1,1,1,1,mode = 'normal'))
bl.append(Drift(100), propagation_parameters(1,1,1,1,mode = 'quadratic'))
#bl.append(Drift(100), propagation_parameters(1,1,1,1,mode = 'quadratic'))
bl.propagate(wfr)
plotIntensity(wfr)
print(calculate_fwhm(wfr))
def storeWavefrontInfo(wfr):
sz0 = get_axial_power_density(wfr, spectrum = False)
sz1 = get_axial_power_density(wfr, spectrum = True)
fwhm = calculate_fwhm(wfr)
srwlib.srwl.SetRepresElecField(wfr._srwl_wf, 't')
pulseEn, photons_per_pulse = calc_pulse_energy(wfr)
srwlib.srwl.SetRepresElecField(wfr._srwl_wf, 'f')
divergence = wfr.get_divergence()
wfr.custom_fields['/source/t_spectrum'] = sz0
wfr.custom_fields['/source/f_spectrum'] = sz1
wfr.custom_fields['/source/xFWHM'] = fwhm['fwhm_x']
wfr.custom_fields['/source/yFWHM'] = fwhm['fwhm_y']
wfr.custom_fields['/source/divX'] = divergence[0]
wfr.custom_fields['/source/divX'] = divergence[1]
wfr.custom_fields['/source/pulseEn'] = pulseEn
wfr.custom_fields['/source/nPhotons'] = photons_per_pulse
def get_divergence(self):
"""
calculate the full-angle divergence of the beam
:param wfr: WPG wavefront structure
"""
self.set_electric_field_representation('a')
sig_x, sig_y = calculate_fwhm(self)['fwhm_x'], calculate_fwhm(
self)['fwhm_y']
self.set_electric_field_representation('c')
self.custom_fields['divergence'] = sig_x, sig_y
return sig_x, sig_y
def get_divergence(self):
"""
calculate the full-angle divergence of the beam
:param wfr: WPG wavefront structure
"""
wDomain = self.params.wDomain
self.set_electric_field_representation('a')
sig_x, sig_y = calculate_fwhm(self)['fwhm_x'], calculate_fwhm(
self)['fwhm_y']
self.set_electric_field_representation(wDomain)
return sig_x, sig_y
def comparePulses(wfr, cwfr, savedir):
print("Intial Incoherent Integrated Intensity: {} W/mm^2".format(wfr.initial_intensity))
print("Coherent Integrated Intensity: {} W/mm^2".format(cwfr.initial_intensity))
print("Final Incoherent Integrated Intensity: {} W/mm^2".format(wfr.final_intensity))
print("Final Coherent Integrated Intensity: {} W/mm^2".format(cwfr.final_intensity))
print("Incoherent System Efficiency: {}".format((wfr.final_intensity)/wfr.initial_intensity))
print("Coherent System Efficiency: {}".format((cwfr.final_intensity)/cwfr.initial_intensity))
fwhm_x, fwhm_y = calculate_fwhm(wfr)['fwhm_x'], calculate_fwhm(wfr)['fwhm_y']
cfwhm_x, cfwhm_y = calculate_fwhm(cwfr)['fwhm_x'], calculate_fwhm(cwfr)['fwhm_y']
print("Incoherent Focal FWHM-x: {} um".format(fwhm_x*1e6))
print("Incoherent Focal FWHM-y: {} um".format(fwhm_y*1e6))
print("Coherent Focal FWHM-x: {} um".format(cfwhm_x*1e6))
print("coherent Focal FWHM-y: {} um".format(cfwhm_y*1e6))
### store pulses
wfr.store_hdf5(savedir + "pulse.hdf5")
cwfr.store_hdf5(savedir + "gaussian.hdf5")
def test_coherent_pulse_fwhm(E, sdir=None):
"""
Test that the FWHM of the source matches the analytical prediction
:param E: list/array of energies [keV]
:param sdir: output directory [str]
"""
print("Testing Source Size vs. Energy and Resolution")
sns.set()
fig = plt.figure(figsize=[12, 8])
ax = fig.add_subplot(111)
ax.set_title("Source Size Radiation Dependence", fontsize=22)
ax.set_ylabel("FWHM [$\mu$m]", fontsize=22)
ax.set_xlabel("Radiation Energy [keV]", fontsize=22)
ax.set_xlim([2.5, 17.5])
ax.set_ylim([0, 55])
E
analytical_data = np.array([analytical_pulse_width(a) * 1e6 for a in E])
fwhms = []
for energy in E:
wfr = construct_SA1_wavefront(nx=1024, ny=1024, ekev=energy, q=0.25)
fwhms.append(calculate_fwhm(wfr)['fwhm_x'] * 1e6)
simulation, = ax.plot(E, fwhms, 'r')
analytical, = ax.plot(E, analytical_data, '--b')
leg1 = ax.legend([simulation, analytical],
["Simulated Data", "Analytical Model"],
loc='lower left',
fontsize=22)
ax.add_artist(leg1)
ax.tick_params(axis='both', which='major', labelsize=18)
ax.tick_params(axis='both', which='minor', labelsize=14)
if sdir is not None:
fig.savefig(sdir + "coherent_source_test_fwhm.eps")
plt.show()
return wfr
def main(wpg_out):
# Backup
backup = wpg_out + ".backup"
shutil.copy2(wpg_out, backup)
print("Processing %s." % (wpg_out))
# Load wavefront.
wavefront = Wavefront()
wavefront.load_hdf5(wpg_out)
# Get width from intensity profile.
fwhm = wpg_uti_wf.calculate_fwhm(wavefront)
# Carefully insert new datasets.
try:
with h5py.File(wpg_out, 'a') as h5_handle:
if not 'misc' in h5_handle.keys():
misc = h5_handle.create_group("misc")
else:
misc = h5_handle['misc']
if not "xFWHM" in misc.keys():
misc.create_dataset("xFWHM", data=fwhm["fwhm_x"])
if not "yFWHM" in misc.keys():
misc.create_dataset("yFWHM", data=fwhm["fwhm_y"])
# If anything went wrong, restore the original file and raise.
except:
shutil.move(backup, wpg_out)
raise
# We only reach this point if everything went well, so can safely remove the backup."
os.remove(backup)
def propToBeamParameters(prop_output_path):
""" Utility to setup a PhotonBeamParameters instance from propagation output. """
# Check prop out exists.
if not os.path.isfile(prop_output_path):
raise IOError("File not found: %s." % (prop_output_path))
# Construct the wavefront.
wavefront = Wavefront()
wavefront.load_hdf5(prop_output_path)
pulse_energy = wpg_uti_wf.calc_pulse_energy(wavefront)
mesh = wavefront.params.Mesh
dx = (mesh.xMax - mesh.xMin) / (mesh.nx - 1)
dy = (mesh.yMax - mesh.yMin) / (mesh.ny - 1)
int0 = wavefront.get_intensity().sum(axis=0).sum(axis=0) # I(slice_num)
total_intensity = int0 * dx * dy # [J]
times = numpy.linspace(mesh.sliceMin, mesh.sliceMax, mesh.nSlices)
t = times[:-1]
dt = times[1:] - times[:-1]
It = total_intensity[:-1]
m0 = numpy.sum(It * dt)
m1 = numpy.sum(It * t * dt) / m0
m2 = numpy.sum(It * t**2 * dt) / m0
rms = math.sqrt(m2 - m1**2)
spike_fwhm_J = constants.hbar / rms
spike_fwhm_eV = spike_fwhm_J / constants.e
# Switch to energy domain
srwl.SetRepresElecField(wavefront._srwl_wf, 'f')
mesh = wavefront.params.Mesh
spectrum = wavefront.get_intensity().sum(axis=0).sum(
axis=0) # I(slice_num)
energies = numpy.linspace(mesh.sliceMin, mesh.sliceMax, mesh.nSlices)
w = energies[:-1]
dw = energies[1:] - energies[:-1]
Iw = spectrum[:-1]
m0 = numpy.sum(Iw * dw)
m1 = numpy.sum(Iw * w * dw) / m0
m2 = numpy.sum(Iw * w**2 * dw) / m0
rms = math.sqrt(m2 - m1**2)
photon_energy = m1
#spec_fwhm_eV = rms
# Extract beam diameter fwhm
xy_fwhm = wpg_uti_wf.calculate_fwhm(wavefront)
# Extract divergence
# Switch to reciprocal space
srwl.SetRepresElecField(wavefront._srwl_wf, 'a')
qxqy_fwhm = wpg_uti_wf.calculate_fwhm(wavefront)
del wavefront
beam_parameters = PhotonBeamParameters(
photon_energy=photon_energy * electronvolt,
photon_energy_relative_bandwidth=spike_fwhm_eV / photon_energy,
pulse_energy=pulse_energy * joule,
divergence=max([qxqy_fwhm['fwhm_x'], qxqy_fwhm['fwhm_y']]) / 2. *
radian,
beam_diameter_fwhm=max([xy_fwhm['fwhm_x'], xy_fwhm['fwhm_y']]) * meter,
photon_energy_spectrum_type="SASE",
)
return beam_parameters
spb = Instrument(overwrite_mirrors = True)
spb.setupHOMs(ekev, 2.2e-03)
spb.setupKBs(ekev, 3.5e-03)
spb.build_elements(focus = focus)
<<<<<<< HEAD
spb.build_beamline(focus = focus)
=======
spb.buildBeamline(focus = focus)
>>>>>>> 108cfb9b6fc97d3841ee1db54862523eee5b184e
bl = spb.get_beamline()
bl.propagate(wfr)
meas = calculate_fwhm(wfr)
fwhm_x = meas['fwhm_x']
fwhm_y = meas['fwhm_y']
return fwhm_x, fwhm_y
def plot(energyrange, data, estr, qstr, focus, outdir = "../../tmp/"):
fig = plt.figure()
ax = fig.add_subplot(111)
if focus == "micron":
focstr = "Micron-KB "
elif focus == "nano":
def testGaussianReference(self, debug=False):
""" Check that propagation of a Gaussian pulse (in t,x,y) through vacuum reproduces reference data. """
# Central photon energy.
ekev = 8.4 # Energy [keV]
# Pulse parameters.
qnC = 0.5 # e-bunch charge, [nC]
pulse_duration = 9.0e-15 # [s]
pulseEnergy = 1.5e-3 # total pulse energy, J
# Coherence time
coh_time = 0.25e-15 # [s]
# Distance in free space.
z0 = 10. # (m), position where to build the wavefront.
z1 = 10. # (m), distance to travel in free space.
# Beam divergence.
theta_fwhm = 2.5e-6 # rad
wlambda = 12.4*1e-10/ekev # wavelength, m
w0 = wlambda/(numpy.pi*theta_fwhm) # beam waist, m
zR = (math.pi*w0**2)/wlambda #Rayleigh range, m
fwhm_at_zR = theta_fwhm*zR #FWHM at Rayleigh range, m
sigmaAmp = w0/(2.0*math.sqrt(math.log(2.0))) #sigma of amplitude, m
if debug:
print (" *** Pulse properties ***")
print (" lambda = %4.3e m" % (wlambda) )
print (" w0 = %4.3e m" % (w0) )
print (" zR = %4.3e m" % (zR) )
print (" fwhm at zR = %4.3e m" % (fwhm_at_zR) )
print (" sigma = %4.3e m" % (sigmaAmp) )
# expected beam radius after free space drift.
expected_beam_radius = w0*math.sqrt(1.0+(z0/zR)**2)
# Number of points in each x and y dimension.
np=400
# Sampling window = 6 sigma of initial beam.
range_xy = 6.*expected_beam_radius
dx = range_xy / (np-1)
nslices = 20
if debug:
print (" Expected beam waist at z=%4.3f m : %4.3e m." % (z0, expected_beam_radius) )
print ("Setting up mesh of %d points per dimension on a %4.3e x %4.3e m^2 grid with grid spacing %4.3e m." % (np, range_xy, range_xy, dx) )
# Construct srw wavefront.
srwl_wf = build_gauss_wavefront(np, np, nslices, ekev, -range_xy/2., range_xy/2.,
-range_xy/2., range_xy/2., coh_time/math.sqrt(2.),
sigmaAmp, sigmaAmp, z0,
pulseEn=pulseEnergy, pulseRange=8.)
# Convert to wpg.
wf = Wavefront(srwl_wf)
if debug:
print('*** z=%4.3e m ***' % (z0))
fwhm = calculate_fwhm(wf)
print('fwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
look_at_q_space(wf)
# Construct the beamline.
beamline = Beamline()
# Add free space drift.
drift = Drift(z1)
beamline.append( drift, Use_PP(semi_analytical_treatment=1))
# Propagate
srwl.SetRepresElecField(wf._srwl_wf, 'f') # <---- switch to frequency domain
beamline.propagate(wf)
srwl.SetRepresElecField(wf._srwl_wf, 't')
if debug:
print('*** z=%4.3e m ***' % (z0+z1))
fwhm = calculate_fwhm(wf)
print('fwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
look_at_q_space(wf)
# Get propagated wavefront data.
wf_intensity = wf.get_intensity()
# Project on t axis.
wf_onaxis = wf_intensity.sum(axis=(0,1))
# Get hash of the data.
wf_hash = hash( wf_intensity.tostring() )
# Load reference hash.
with open(TestUtilities.generateTestFilePath("reference_wf_gauss_10m.hash.txt"), 'r') as hashfile:
ref_hash = hashfile.readline()
hashfile.close()
ref_onaxis = numpy.loadtxt(TestUtilities.generateTestFilePath("reference_wf_gauss_onaxis_10m.txt"))
# Weak test.
for x,y in zip(wf_onaxis, ref_onaxis):
self.assertAlmostEqual( x, y, 14 )
# Strong test.
self.assertEqual( str(wf_hash), ref_hash)
def testGaussianVsAnalytic(self, debug=False):
""" Check that propagation of a Gaussian pulse (in t,x,y) through vacuum gives the correct result, compare
to analytic solution. """
# Central photon energy.
ekev = 8.4 # Energy [keV]
# Pulse parameters.
qnC = 0.5 # e-bunch charge, [nC]
pulse_duration = 9.0e-15 # [s]
pulseEnergy = 1.5e-3 # total pulse energy, J
# Coherence time
coh_time = 0.25e-15 # [s]
# Distance in free space.
z0 = 10. # (m), position where to build the wavefront.
z1 = 20. # (m), distance to travel in free space.
z2 = z0 + z1 # distance where to build the reference wavefront.
# Beam divergence.
theta_fwhm = 2.5e-6 # rad
wlambda = 12.4*1e-10/ekev # wavelength, m
w0 = wlambda/(numpy.pi*theta_fwhm) # beam waist, m
zR = (math.pi*w0**2)/wlambda #Rayleigh range, m
fwhm_at_zR = theta_fwhm*zR #FWHM at Rayleigh range, m
sigmaAmp = w0/(2.0*math.sqrt(math.log(2.0))) #sigma of amplitude, m
if debug:
print (" *** Pulse properties ***")
print (" lambda = %4.3e m" % (wlambda) )
print (" w0 = %4.3e m" % (w0) )
print (" zR = %4.3e m" % (zR) )
print (" fwhm at zR = %4.3e m" % (fwhm_at_zR) )
print (" sigma = %4.3e m" % (sigmaAmp) )
# expected beam radius after free space drift.
expected_beam_radius = w0*math.sqrt(1.0+(z0/zR)**2)
# Number of points in each x and y dimension.
np=600
# Sampling window = 6 sigma of initial beam.
range_xy = 6.*expected_beam_radius
dx = range_xy / (np-1)
nslices = 20
#if debug:
#print (" Expected beam waist at z=%4.3f m : %4.3e m." % (z0, expected_beam_radius) )
#print ("Setting up mesh of %d points per dimension on a %4.3e x %4.3e m^2 grid with grid spacing %4.3e m." % (np, range_xy, range_xy, dx) )
# Construct srw wavefront.
srwl_wf = build_gauss_wavefront(np, np, nslices, ekev, -range_xy/2., range_xy/2.,
-range_xy/2., range_xy/2., coh_time/math.sqrt(2.),
sigmaAmp, sigmaAmp, z0,
pulseEn=pulseEnergy, pulseRange=8.)
# Convert to wpg.
wf = Wavefront(srwl_wf)
# Construct reference srw wavefront.
reference_srwl_wf = build_gauss_wavefront(np, np, nslices, ekev, -1.5*range_xy/2., 1.5*range_xy/2.,
-1.5*range_xy/2., 1.5*range_xy/2., coh_time/math.sqrt(2.),
sigmaAmp, sigmaAmp, z2,
pulseEn=pulseEnergy, pulseRange=8.)
reference_wf = Wavefront(reference_srwl_wf)
if debug:
print('*** z=%4.3e m ***' % (z0))
fwhm = calculate_fwhm(wf)
print('wf:\nfwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
#look_at_q_space(wf)
# Construct the beamline.
beamline = Beamline()
# Add free space drift.
drift = Drift(z1)
beamline.append( drift, Use_PP(semi_analytical_treatment=0, zoom=2.0, sampling=0.5))
# Propagate
srwl.SetRepresElecField(wf._srwl_wf, 'f')
beamline.propagate(wf)
srwl.SetRepresElecField(wf._srwl_wf, 't')
fwhm = calculate_fwhm(wf)
reference_fwhm = calculate_fwhm(reference_wf)
if debug:
print('*** z=%4.3e m ***' % (z0+z1))
print('wf :\nfwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
print('ref:\nfwhm_x = %4.3e\nfwhm_y = %4.3e' % (reference_fwhm['fwhm_x'], reference_fwhm['fwhm_y']) )
plot_t_wf(reference_wf)
#look_at_q_space(wf)
# Calculate difference
reference_norm = numpy.linalg.norm(numpy.array([reference_fwhm['fwhm_x'], reference_fwhm['fwhm_y']]))
difference_norm = numpy.linalg.norm(numpy.array([fwhm['fwhm_x'], fwhm['fwhm_y']]) - numpy.array([reference_fwhm['fwhm_x'], reference_fwhm['fwhm_y']]))
if debug:
print ("|ref_fwhm_xy| = %4.3e" % (reference_norm) )
print ("|ref_fwhm_xy - fhwm_xy| = %4.3e" % (difference_norm) )
self.assertLess(difference_norm / reference_norm, 0.01)
def testGaussianReference(self, debug=False):
""" Check that propagation of a Gaussian pulse (in t,x,y) through vacuum reproduces reference data. """
# Central photon energy.
ekev = 8.4 # Energy [keV]
# Pulse parameters.
qnC = 0.5 # e-bunch charge, [nC]
pulse_duration = 9.0e-15 # [s]
pulseEnergy = 1.5e-3 # total pulse energy, J
# Coherence time
coh_time = 0.25e-15 # [s]
# Distance in free space.
z0 = 10. # (m), position where to build the wavefront.
z1 = 10. # (m), distance to travel in free space.
# Beam divergence.
theta_fwhm = 2.5e-6 # rad
wlambda = 12.4*1e-10/ekev # wavelength, m
w0 = wlambda/(numpy.pi*theta_fwhm) # beam waist, m
zR = (math.pi*w0**2)/wlambda #Rayleigh range, m
fwhm_at_zR = theta_fwhm*zR #FWHM at Rayleigh range, m
sigmaAmp = w0/(2.0*math.sqrt(math.log(2.0))) #sigma of amplitude, m
if debug:
print (" *** Pulse properties ***")
print (" lambda = %4.3e m" % (wlambda) )
print (" w0 = %4.3e m" % (w0) )
print (" zR = %4.3e m" % (zR) )
print (" fwhm at zR = %4.3e m" % (fwhm_at_zR) )
print (" sigma = %4.3e m" % (sigmaAmp) )
# expected beam radius after free space drift.
expected_beam_radius = w0*math.sqrt(1.0+(z0/zR)**2)
# Number of points in each x and y dimension.
np=400
# Sampling window = 6 sigma of initial beam.
range_xy = 6.*expected_beam_radius
dx = range_xy / (np-1)
nslices = 20
if debug:
print (" Expected beam waist at z=%4.3f m : %4.3e m." % (z0, expected_beam_radius) )
print ("Setting up mesh of %d points per dimension on a %4.3e x %4.3e m^2 grid with grid spacing %4.3e m." % (np, range_xy, range_xy, dx) )
# Construct srw wavefront.
srwl_wf = build_gauss_wavefront(np, np, nslices, ekev, -range_xy/2., range_xy/2.,
-range_xy/2., range_xy/2., coh_time/math.sqrt(2.),
sigmaAmp, sigmaAmp, z0,
pulseEn=pulseEnergy, pulseRange=8.)
# Convert to wpg.
wf = Wavefront(srwl_wf)
if debug:
print('*** z=%4.3e m ***' % (z0))
fwhm = calculate_fwhm(wf)
print('fwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
look_at_q_space(wf)
# Construct the beamline.
beamline = Beamline()
# Add free space drift.
drift = Drift(z1)
beamline.append( drift, Use_PP(semi_analytical_treatment=1))
# Propagate
srwl.SetRepresElecField(wf._srwl_wf, 'f') # <---- switch to frequency domain
beamline.propagate(wf)
srwl.SetRepresElecField(wf._srwl_wf, 't')
if debug:
print('*** z=%4.3e m ***' % (z0+z1))
fwhm = calculate_fwhm(wf)
print('fwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
look_at_q_space(wf)
# Get propagated wavefront data.
wf_intensity = wf.get_intensity()
# Project on t axis.
wf_onaxis = wf_intensity.sum(axis=(0,1))
# Get hash of the data.
wf_hash = hash( wf_intensity.tostring() )
# Load reference hash.
with open(TestUtilities.generateTestFilePath("reference_wf_gauss_10m.hash.txt"), 'r') as hashfile:
ref_hash = hashfile.readline()
hashfile.close()
ref_onaxis = numpy.loadtxt(TestUtilities.generateTestFilePath("reference_wf_gauss_onaxis_10m.txt"))
# Weak test.
for x,y in zip(wf_onaxis, ref_onaxis):
self.assertAlmostEqual( x, y, 14 )
# Strong test.
self.assertEqual( str(wf_hash), ref_hash)
def testGaussianVsAnalytic(self, debug=False):
""" Check that propagation of a Gaussian pulse (in t,x,y) through vacuum gives the correct result, compare
to analytic solution. """
# Central photon energy.
ekev = 8.4 # Energy [keV]
# Pulse parameters.
qnC = 0.5 # e-bunch charge, [nC]
pulse_duration = 9.0e-15 # [s]
pulseEnergy = 1.5e-3 # total pulse energy, J
# Coherence time
coh_time = 0.25e-15 # [s]
# Distance in free space.
z0 = 10. # (m), position where to build the wavefront.
z1 = 20. # (m), distance to travel in free space.
z2 = z0 + z1 # distance where to build the reference wavefront.
# Beam divergence.
theta_fwhm = 2.5e-6 # rad
wlambda = 12.4*1e-10/ekev # wavelength, m
w0 = wlambda/(numpy.pi*theta_fwhm) # beam waist, m
zR = (math.pi*w0**2)/wlambda #Rayleigh range, m
fwhm_at_zR = theta_fwhm*zR #FWHM at Rayleigh range, m
sigmaAmp = w0/(2.0*math.sqrt(math.log(2.0))) #sigma of amplitude, m
if debug:
print (" *** Pulse properties ***")
print (" lambda = %4.3e m" % (wlambda) )
print (" w0 = %4.3e m" % (w0) )
print (" zR = %4.3e m" % (zR) )
print (" fwhm at zR = %4.3e m" % (fwhm_at_zR) )
print (" sigma = %4.3e m" % (sigmaAmp) )
# expected beam radius after free space drift.
expected_beam_radius = w0*math.sqrt(1.0+(z0/zR)**2)
# Number of points in each x and y dimension.
np=600
# Sampling window = 6 sigma of initial beam.
range_xy = 6.*expected_beam_radius
dx = range_xy / (np-1)
nslices = 20
#if debug:
#print (" Expected beam waist at z=%4.3f m : %4.3e m." % (z0, expected_beam_radius) )
#print ("Setting up mesh of %d points per dimension on a %4.3e x %4.3e m^2 grid with grid spacing %4.3e m." % (np, range_xy, range_xy, dx) )
# Construct srw wavefront.
srwl_wf = build_gauss_wavefront(np, np, nslices, ekev, -range_xy/2., range_xy/2.,
-range_xy/2., range_xy/2., coh_time/math.sqrt(2.),
sigmaAmp, sigmaAmp, z0,
pulseEn=pulseEnergy, pulseRange=8.)
# Convert to wpg.
wf = Wavefront(srwl_wf)
# Construct reference srw wavefront.
reference_srwl_wf = build_gauss_wavefront(np, np, nslices, ekev, -1.5*range_xy/2., 1.5*range_xy/2.,
-1.5*range_xy/2., 1.5*range_xy/2., coh_time/math.sqrt(2.),
sigmaAmp, sigmaAmp, z2,
pulseEn=pulseEnergy, pulseRange=8.)
reference_wf = Wavefront(reference_srwl_wf)
if debug:
print('*** z=%4.3e m ***' % (z0))
fwhm = calculate_fwhm(wf)
print('wf:\nfwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
#look_at_q_space(wf)
# Construct the beamline.
beamline = Beamline()
# Add free space drift.
drift = Drift(z1)
beamline.append( drift, Use_PP(semi_analytical_treatment=0, zoom=2.0, sampling=0.5))
# Propagate
srwl.SetRepresElecField(wf._srwl_wf, 'f')
beamline.propagate(wf)
srwl.SetRepresElecField(wf._srwl_wf, 't')
fwhm = calculate_fwhm(wf)
reference_fwhm = calculate_fwhm(reference_wf)
if debug:
print('*** z=%4.3e m ***' % (z0+z1))
print('wf :\nfwhm_x = %4.3e\nfwhm_y = %4.3e' % (fwhm['fwhm_x'], fwhm['fwhm_y']) )
plot_t_wf(wf)
print('ref:\nfwhm_x = %4.3e\nfwhm_y = %4.3e' % (reference_fwhm['fwhm_x'], reference_fwhm['fwhm_y']) )
plot_t_wf(reference_wf)
#look_at_q_space(wf)
# Calculate difference
reference_norm = numpy.linalg.norm(numpy.array([reference_fwhm['fwhm_x'], reference_fwhm['fwhm_y']]))
difference_norm = numpy.linalg.norm(numpy.array([fwhm['fwhm_x'], fwhm['fwhm_y']]) - numpy.array([reference_fwhm['fwhm_x'], reference_fwhm['fwhm_y']]))
if debug:
print ("|ref_fwhm_xy| = %4.3e" % (reference_norm) )
print ("|ref_fwhm_xy - fhwm_xy| = %4.3e" % (difference_norm) )
self.assertLess(difference_norm / reference_norm, 0.01)
