def back_propagate(params):
"""
Propagate pulse from file params[0] at the distance params[1] and save result to HDF5 file.
If output files exists - skip calculations.
"""
(input_path, distance, propagation_parameters) = params
input_dir, input_file_name = os.path.split(input_path)
out_file_name = "{}_{:0.4f}.h5".format(
".".join(input_file_name.split(".")[:-1]), distance
)
out_path = os.path.join(input_dir, out_file_name)
if os.path.exists(out_path):
return
wf_L1 = Wavefront()
wf_L1.load_hdf5(input_path)
drift1 = optical_elements.Drift(distance)
srwl_bl1 = SRWLOptC([drift1,], [propagation_parameters,])
bl1 = Beamline(srwl_bl1)
wpg.srwlib.srwl.SetRepresElecField(wf_L1._srwl_wf, "f")
bl1.propagate(wf_L1)
wpg.srwlib.srwl.SetRepresElecField(wf_L1._srwl_wf, "t")
fit_gaussian_pulse(wf_L1)
wf_L1.store_hdf5(out_path)
del wf_L1
gc.collect()
return out_path
def back_propagate(params):
'''
Propagate pulse from file params[0] at the distance params[1] and save result to HDF5 file.
If output files exists - skip calculations.
'''
(input_path, distance, propagation_parameters) = params
input_dir, input_file_name = os.path.split(input_path)
out_file_name = '{}_{:0.4f}.h5'.format(
'.'.join(input_file_name.split('.')[:-1]), distance)
out_path = os.path.join(input_dir, out_file_name)
if os.path.exists(out_path):
return
wf_L1 = Wavefront()
wf_L1.load_hdf5(input_path)
drift1 = optical_elements.Drift(distance)
srwl_bl1 = SRWLOptC([drift1, ], [propagation_parameters, ])
bl1 = Beamline(srwl_bl1)
wpg.srwlib.srwl.SetRepresElecField(wf_L1._srwl_wf, 'f')
bl1.propagate(wf_L1)
wpg.srwlib.srwl.SetRepresElecField(wf_L1._srwl_wf, 't')
fit_gaussian_pulse(wf_L1)
wf_L1.store_hdf5(out_path)
del wf_L1
gc.collect()
return out_path
def propagate_run(ifname, ofname, optBL, bSaved=False):
"""
Propagate wavefront through a beamline and save the result (optionally).
:param ifname: input hdf5 file name with wavefront to be propagated
:param ofname: output hdf5 file name
:param optBL: beamline
:param bSaved: if True, save propagated wavefront in h5 file
:return: propagated wavefront
"""
print_beamline(optBL)
startTime = time.time()
print('*****reading wavefront from h5 file...')
w2 = Wavefront()
w2.load_hdf5(ifname + '.h5')
wfr = w2._srwl_wf
print('*****propagating wavefront (with resizing)...')
srwl.PropagElecField(wfr, optBL)
mwf = Wavefront(wfr)
print('[nx, ny, xmin, xmax, ymin, ymax]', get_mesh(mwf))
if bSaved:
print('save hdf5:', ofname + '.h5')
mwf.store_hdf5(ofname + '.h5')
print('done')
print('propagation lasted:',
round((time.time() - startTime) / 6.) / 10., 'min')
return wfr
def propagate_wavefront(wavefront, beamline, output_file = None):
"""
Propagate wavefront and store it in output file.
:param wavefront: 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
if isinstance(wavefront, Wavefront):
wfr = Wavefront(srwl_wavefront=wavefront._srw_wf)
else:
print '*****reading wavefront from h5 file...'
wfr = Wavefront()
wfr.load_hdf5(wavefront)
print '*****propagating wavefront (with resizing)...'
bl.propagate(wfr)
print '[nx, ny, xmin, xmax, ymin, ymax]', get_mesh(wfr)
if not output_file is None:
print 'save hdf5:', output_file
wfr.store_hdf5(output_file)
print 'done'
return wfr
def propagate_run(ifname, ofname, optBL, bSaved=False):
"""
Propagate wavefront through a beamline and save the result (optionally).
:param ifname: input hdf5 file name with wavefront to be propagated
:param ofname: output hdf5 file name
:param optBL: beamline
:param bSaved: if True, save propagated wavefront in h5 file
:return: propagated wavefront
"""
print_beamline(optBL)
startTime = time.time()
print '*****reading wavefront from h5 file...'
w2 = Wavefront()
w2.load_hdf5(ifname + '.h5')
wfr = w2._srwl_wf
print '*****propagating wavefront (with resizing)...'
srwl.PropagElecField(wfr, optBL)
mwf = Wavefront(wfr)
print '[nx, ny, xmin, xmax, ymin, ymax]', get_mesh(mwf)
if bSaved:
print 'save hdf5:', ofname + '.h5'
mwf.store_hdf5(ofname + '.h5')
print 'done'
print 'propagation lasted:', round((time.time() - startTime) / 6.) / 10., 'min'
return wfr
def setupTestWavefront():
""" Utility to setup a Gaussian wavefront. Geometry corresponds to SPB-SFX Day1 configuration. """
### Geometry ###
src_to_hom1 = 257.8 # Distance source to HOM 1 [m]
src_to_hom2 = 267.8 # Distance source to HOM 2 [m]
src_to_crl = 887.8 # Distance source to CRL [m]
src_to_exp = 920.42 # Distance source to experiment [m]
# Central photon energy.
ekev = 8.4 # Energy [keV]
# Pulse parameters.
qnC = 0.5 # e-bunch charge, [nC]
pulse_duration = 9.e-15 # [s]
pulseEnergy = 1.5e-3 # total pulse energy, J
# Coherence time
coh_time = 0.24e-15 # [s]
# Distance to first HOM.
z1 = src_to_hom1
# Angular distribution
theta_fwhm = 2.124e-6 # Beam divergence # From Patrick's raytrace.
wlambda = 12.4 * 1e-10 / ekev # wavelength [AKM]
w0 = wlambda / (numpy.pi * theta_fwhm) # beam waist
zR = (numpy.pi * w0**2) / wlambda #Rayleigh range
fwhm_at_zR = theta_fwhm * zR #FWHM at Rayleigh range
sigmaAmp = w0 / (2 * numpy.sqrt(numpy.log(2))) #sigma of amplitude
# Number of points in each x and y dimension.
np = 100
bSaved = False
dx = 10.e-6
range_xy = dx * (np - 1)
#print ('range_xy = ', range_xy)
nslices = 10
srwl_wf = build_gauss_wavefront(np,
np,
nslices,
ekev,
-range_xy / 2,
range_xy / 2,
-range_xy / 2,
range_xy / 2,
coh_time / numpy.sqrt(2),
sigmaAmp,
sigmaAmp,
src_to_hom1,
pulseEn=pulseEnergy,
pulseRange=8.)
wf = Wavefront(srwl_wf)
wf.store_hdf5("source.h5")
def propagate(in_fname, out_fname, get_beamline):
"""
Propagate wavefront
:param in_file: input wavefront file
:param out_file: output file
:param get_beamline: function to build beamline
"""
print('Start propagating:' + in_fname)
wf = Wavefront()
wf.load_hdf5(in_fname)
bl0 = get_beamline()
if isIpynb:
print bl0
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, 'f')
sz0 = get_intensity_on_axis(wf)
wf.custom_fields['/misc/spectrum0'] = sz0
bl0.propagate(wf)
sz1 = get_intensity_on_axis(wf)
wf.custom_fields['/misc/spectrum1'] = sz1
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, 't')
#Resizing: decreasing Range of Horizontal and Vertical Position:
wpg.srwlib.srwl.ResizeElecField(wf._srwl_wf, 'c', [0, 0.5, 1, 0.5, 1])
fwhm = calculate_fwhm(wf)
wf.custom_fields['/misc/xFWHM'] = fwhm['fwhm_x']
wf.custom_fields['/misc/yFWHM'] = fwhm['fwhm_y']
wf.custom_fields['/params/beamline/printout'] = str(bl0)
wf.custom_fields['/info/contact'] = [
'Name: Liubov Samoylova', 'Email: [email protected]',
'Name: Alexey Buzmakov', 'Email: [email protected]'
]
wf.custom_fields[
'/info/data_description'] = 'This dataset contains infromation about wavefront propagated through beamline (WPG and SRW frameworks).'
wf.custom_fields[
'/info/method_description'] = """WPG, WaveProperGator (http://github.com/samoylv/WPG)is an interactive simulation framework for coherent X-ray wavefront propagation.\nSRW, Synchrotron Radiation Workshop (http://github.com/ochubar/SRW), is a physical optics computer code for simulation of the radiation wavefront propagation through optical systems of beamlines as well as detailed characteristics of Synchrotron Radiation (SR) generated by relativistic electrons in magnetic fields of arbitrary configuration."""
wf.custom_fields['/info/package_version'] = '2014.1'
print('Saving the wavefront data after propagation:' + out_fname)
mkdir_p(os.path.dirname(out_fname))
wf.store_hdf5(out_fname)
add_history(out_fname, in_fname)
def propagate(in_fname, out_fname, get_beamline):
"""
Propagate wavefront
:param in_file: input wavefront file
:param out_file: output file
:param get_beamline: function to build beamline
"""
print("#" * 80)
print("Setup initial wavefront.")
wf = Wavefront()
# Load wavefront data.
print("Load " + in_fname)
wf.load_hdf5(in_fname)
# Get beamline.
bl0 = get_beamline()
# Switch to frequency domain.
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, "f")
# Save spectrum for later reference.
sz0 = get_intensity_on_axis(wf)
wf.custom_fields["/misc/spectrum0"] = sz0
# Propagate.
bl0.propagate(wf)
# Save spectrum after propagation for later reference.
sz1 = get_intensity_on_axis(wf)
wf.custom_fields["/misc/spectrum1"] = sz1
# Switch back to time domain.
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, "t")
# Resizing: decreasing Range of Horizontal and Vertical Position:
wpg.srwlib.srwl.ResizeElecField(wf._srwl_wf, "c", [0, 0.5, 1, 0.5, 1])
add_custom_data(wf, bl0)
print("Saving propagated wavefront to " + out_fname)
mkdir_p(os.path.dirname(out_fname))
wf.store_hdf5(out_fname)
print("Saving history.")
add_history(out_fname, in_fname)
print("ALL DONE.")
print("#" * 80)
def forward_propagate(root_dir, distance, propagation_parameters):
"""
Forward_propagate_wavefront
the result will saved in root_dir\distance\distance.h5 file
:param root_dir: directory, where '0.h' file located
:param distance: distance to forward propagate initial wvefront
:param propagation_parameters: SRW propagation parameters
"""
out_dir = os.path.join(root_dir, '{:0.4f}'.format(distance))
mkdir_p(out_dir)
out_file_name = '{:0.4f}.h5'.format(distance)
out_path = os.path.join(out_dir, out_file_name)
if os.path.exists(out_path):
print('File exists: {}. Skiping.'.format(out_path))
return out_path
ppDrift0 = propagation_parameters
drift0 = optical_elements.Drift(distance)
srwl_bl0 = SRWLOptC([
drift0,
], [
ppDrift0,
])
bl0 = Beamline(srwl_bl0)
# forward propagate to L0 meters
wf_L0 = Wavefront()
wf_L0.load_hdf5(os.path.join(root_dir, '0.h5'))
tmin = wf_L0.params.Mesh.sliceMin
tmax = wf_L0.params.Mesh.sliceMax
wf_L0.params.Mesh.sliceMin = -(tmax - tmin) / 2
wf_L0.params.Mesh.sliceMax = (tmax - tmin) / 2
# wpg.srwlib.srwl.ResizeElecField(wf_L0._srwl_wf, 't',[0,3.,1.])
wpg.srwlib.srwl.SetRepresElecField(wf_L0._srwl_wf, 'f')
bl0.propagate(wf_L0)
wpg.srwlib.srwl.SetRepresElecField(wf_L0._srwl_wf, 't')
fit_gaussian_pulse(wf_L0)
wf_L0.store_hdf5(out_path)
print('Save file : {}'.format(out_path))
del wf_L0
return out_path
def propagate(in_fname, out_fname, get_beamline):
"""
Propagate wavefront
:param in_file: input wavefront file
:param out_file: output file
:param get_beamline: function to build beamline
"""
print('Start propagating:' + in_fname)
wf=Wavefront()
wf.load_hdf5(in_fname)
bl0 = get_beamline()
if isIpynb:
print bl0
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, 'f')
sz0 = get_intensity_on_axis(wf);
wf.custom_fields['/misc/spectrum0'] = sz0
bl0.propagate(wf)
sz1 = get_intensity_on_axis(wf);
wf.custom_fields['/misc/spectrum1'] = sz1
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, 't')
#Resizing: decreasing Range of Horizontal and Vertical Position:
wpg.srwlib.srwl.ResizeElecField(wf._srwl_wf, 'c', [0, 0.5, 1, 0.5, 1]);
fwhm = calculate_fwhm(wf)
wf.custom_fields['/misc/xFWHM'] = fwhm['fwhm_x']
wf.custom_fields['/misc/yFWHM'] = fwhm['fwhm_y']
wf.custom_fields['/params/beamline/printout'] = str(bl0)
wf.custom_fields['/info/contact'] = [
'Name: Liubov Samoylova', 'Email: [email protected]',
'Name: Alexey Buzmakov', 'Email: [email protected]']
wf.custom_fields['/info/data_description'] = 'This dataset contains infromation about wavefront propagated through beamline (WPG and SRW frameworks).'
wf.custom_fields['/info/method_description'] = """WPG, WaveProperGator (http://github.com/samoylv/WPG)is an interactive simulation framework for coherent X-ray wavefront propagation.\nSRW, Synchrotron Radiation Workshop (http://github.com/ochubar/SRW), is a physical optics computer code for simulation of the radiation wavefront propagation through optical systems of beamlines as well as detailed characteristics of Synchrotron Radiation (SR) generated by relativistic electrons in magnetic fields of arbitrary configuration."""
wf.custom_fields['/info/package_version'] = '2014.1'
print('Saving the wavefront data after propagation:' + out_fname)
mkdir_p(os.path.dirname(out_fname))
wf.store_hdf5(out_fname)
add_history(out_fname, in_fname)
def forward_propagate(root_dir, distance, propagation_parameters):
"""
Forward_propagate_wavefront
the result will saved in root_dir\distance\distance.h5 file
:param root_dir: directory, where '0.h' file located
:param distance: distance to forward propagate initial wvefront
:param propagation_parameters: SRW propagation parameters
"""
out_dir = os.path.join(root_dir, '{:0.4f}'.format(distance))
mkdir_p(out_dir)
out_file_name = '{:0.4f}.h5'.format(distance)
out_path = os.path.join(out_dir, out_file_name)
if os.path.exists(out_path):
print 'File exists: {}. Skiping.'.format(out_path)
return out_path
ppDrift0 = propagation_parameters
drift0 = optical_elements.Drift(distance)
srwl_bl0 = SRWLOptC([drift0, ], [ppDrift0, ])
bl0 = Beamline(srwl_bl0)
# forward propagate to L0 meters
wf_L0 = Wavefront()
wf_L0.load_hdf5(os.path.join(root_dir, '0.h5'))
tmin = wf_L0.params.Mesh.sliceMin
tmax = wf_L0.params.Mesh.sliceMax
wf_L0.params.Mesh.sliceMin = -(tmax-tmin)/2
wf_L0.params.Mesh.sliceMax = (tmax-tmin)/2
# wpg.srwlib.srwl.ResizeElecField(wf_L0._srwl_wf, 't',[0,3.,1.])
wpg.srwlib.srwl.SetRepresElecField(wf_L0._srwl_wf, 'f')
bl0.propagate(wf_L0)
wpg.srwlib.srwl.SetRepresElecField(wf_L0._srwl_wf, 't')
fit_gaussian_pulse(wf_L0)
wf_L0.store_hdf5(out_path)
print 'Save file : {}'.format(out_path)
del wf_L0
return out_path
def add_wf_attributes(fname0):
# use srwlib glossary to add attributes to wavefront datasets
in_fname = fname0+'.h5'
bare_fname = fname0+'_bare.h5'
if doPrint: print('Loading wavefront data from the file: '+in_fname)
wf_struct=Wavefront()
wf_struct.load_hdf5(in_fname)
wfr = wf_struct._srwl_wf
wf_struct = Wavefront(wfr)
if doPrint: print('Saving the wavefront data with attributes:'+bare_fname)
wf_struct.store_hdf5(bare_fname)
if doPrint: print('Replacing data with attributes from '+bare_fname)
with h5py.File(bare_fname) as h2:
with h5py.File(in_fname) as h1:
try:
del h1['params'] # delete group
except KeyError:
pass
h2.copy('params',h1) #copy h2['params'] to h1
class WavePropagator(AbstractPhotonPropagator):
"""
Class representing a photon propagator that uses wave optics.
"""
def __init__(self, parameters=None, input_path=None, output_path=None):
"""
:param parameters: Parameters steering the propagation of photons.
:type parameters: WavePropagatorParameters
:param input_path: Location of input data for the photon propagation.
:type input_path: str
:param output_path: Location of output data for the photon propagation.
:type output_path: str
"""
# DCheck (and set) parameters.
parameters = checkAndSetInstance(WavePropagatorParameters, parameters, WavePropagatorParameters() )
# Initialize base class.
super(WavePropagator, self).__init__(parameters,input_path,output_path)
def backengine(self):
""" This method drives the backengine code, in this case the WPG interface to SRW.
:return: 0 if WPG run was successful, 1 if not.
"""
# Switch to frequency representation.
srwl.SetRepresElecField(self.__wavefront._srwl_wf, 'f') # <---- switch to frequency domain
# Propagate through beamline.
self.parameters.beamline.propagate(self.__wavefront)
# Switch back to time representation.
srwl.SetRepresElecField(self.__wavefront._srwl_wf, 't')
return 0
@property
def data(self):
""" Query for the field data.
:return: The WPG wavefront data.
"""
return self.__data
def _readH5(self):
""" """
""" Private method for reading the hdf5 input and extracting the parameters and data relevant to initialize the object. """
# Check input.
try:
self.__h5 = h5py.File( self.input_path, 'r' )
except:
raise IOError( 'The input_path argument (%s) is not a path to a valid hdf5 file.' % (self.input_path) )
# Construct wpg wavefront based on input data.
self.__wavefront = Wavefront()
self.__wavefront.load_hdf5(self.input_path)
def saveH5(self):
"""
Method to save the object to a file.
:param output_path: The file where to save the wavefront data.
:type output_path: str, default 'prop_out.h5'
"""
# Write data to hdf file using wpg interface function.
self.__wavefront.store_hdf5(self.output_path)
# Write openPMD file if requested.
if self.parameters.use_opmd:
wpg_to_opmd.convertToOPMD( self.output_path )
class WavePropagator(AbstractPhotonPropagator):
"""
Class representing a photon propagator using wave optics through WPG.
"""
def __init__(self, parameters=None, input_path=None, output_path=None):
"""
Constructor for the xfel photon propagator.
@param parameters : Parameters steering the propagation of photons.
<br/><b>type</b> : dict
@param input_path : Location of input data for the photon propagation.
<br/><b>type</b> : string
@param output_path : Location of output data for the photon propagation.
<br/><b>type</b> : string
"""
# Check if beamline was given.
if isinstance(parameters, Beamline):
parameters = {'beamline': parameters}
# Raise if no beamline in parameters.
if parameters is None or not 'beamline' in parameters.keys():
raise RuntimeError(
'The parameters argument must be an instance of wpg.Beamline or a dict containing the key "beamline" and an instance of wpg.Beamline as the corresponding value.'
)
# Initialize base class.
super(WavePropagator, self).__init__(parameters, input_path,
output_path)
# Take reference to beamline.
self.__beamline = parameters['beamline']
def backengine(self):
""" This method drives the backengine code, in this case the WPG interface to SRW."""
# Switch to frequency representation.
srwl.SetRepresElecField(self.__wavefront._srwl_wf,
'f') # <---- switch to frequency domain
# Propagate through beamline.
self.__beamline.propagate(self.__wavefront)
# Switch back to time representation.
srwl.SetRepresElecField(self.__wavefront._srwl_wf, 't')
return 0
@property
def data(self):
""" Query for the field data. """
return self.__data
def _readH5(self):
""" """
""" Private method for reading the hdf5 input and extracting the parameters and data relevant to initialize the object. """
# Check input.
try:
self.__h5 = h5py.File(self.input_path, 'r')
except:
raise IOError(
'The input_path argument (%s) is not a path to a valid hdf5 file.'
% (self.input_path))
# Construct wpg wavefront based on input data.
self.__wavefront = Wavefront()
self.__wavefront.load_hdf5(self.input_path)
def saveH5(self):
""" """
"""
Private method to save the object to a file.
@param output_path : The file where to save the object's data.
<br/><b>type</b> : string
<br/><b>default</b> : None
"""
# Write data to hdf file using wpg interface function.
self.__wavefront.store_hdf5(self.output_path)
def backengine(self):
# check for WPG first
if not WPG_AVAILABLE:
raise ModuleNotFoundError(
'Cannot find the "WPG" module, which is required to run '
"GaussianSourceCalculator.backengine(). Is it included in PYTHONPATH?"
)
# The rms of the amplitude distribution (Gaussian)
theta = self.parameters["divergence"].value_no_conversion.to(
"radian").magnitude
E_joule = (self.parameters["photon_energy"].value_no_conversion.to(
"joule").magnitude)
E_eV = self.parameters["photon_energy"].value_no_conversion.to(
"eV").magnitude
relative_bandwidth = self.parameters[
"photon_energy_relative_bandwidth"].value
coherence_time = 2.0 * np.pi * hbar / relative_bandwidth / E_joule
pulse_energy = self.parameters["pulse_energy"].value_no_conversion
beam_waist = 2.0 * hbar * c / theta / E_joule
wavelength = 1239.8e-9 / E_eV
rayleigh_length = np.pi * beam_waist**2 / wavelength
logger.info(f"rayleigh_length = {rayleigh_length}")
beam_diameter_fwhm = (self.parameters["beam_diameter_fwhm"].
value_no_conversion.to("meter").magnitude)
beam_waist_radius = beam_diameter_fwhm / np.sqrt(2.0 * np.log(2.0))
# x-y range at beam waist.
range_xy = 30.0 * beam_waist_radius
# Set number of sampling points in x and y and number of temporal slices.
npoints = self.parameters["number_of_transverse_grid_points"].value
nslices = self.parameters["number_of_time_slices"].value
# Distance from source position.
z = self.parameters["z"].value_no_conversion.to("meter").magnitude
# Build wavefront
srwl_wf = build_gauss_wavefront(
npoints,
npoints,
nslices,
E_eV / 1.0e3,
-range_xy / 2,
range_xy / 2,
-range_xy / 2,
range_xy / 2,
coherence_time / np.sqrt(2),
beam_waist_radius / 2,
beam_waist_radius /
2, # Scaled such that fwhm comes out as demanded by parameters.
d2waist=z,
pulseEn=pulse_energy.to("joule").magnitude,
pulseRange=8.0,
)
# Correct radius of curvature.
Rx = Ry = z * np.sqrt(1.0 + (rayleigh_length / z)**2)
# Store on class.
srwl_wf.Rx = Rx
srwl_wf.Ry = Ry
key = self.output_keys[0]
filename = self.output_file_paths[0]
output_data = self.output[key]
wavefront = Wavefront(srwl_wf)
wavefront.store_hdf5(filename)
output_data.set_file(filename, WPGFormat)
return self.output
def constructWavefield(
ekeV,
qnC,
z1,
range_xy,
strOutputDataFolder=None,
dimension=2,
beta=0.7, # 'tunable' parameter — sets global degree of coherence
threshold=0.8, # ignore modes with eigenvalue < this value
npoints=512,
nslices=10,
display=True,
):
"""
Define Transverse Optical Modes
"""
k = 2 * np.sqrt(2 * np.log(2))
wlambda = 12.4 * 1e-10 / ekeV # wavelength
theta_fwhm = calculate_theta_fwhm_cdr(ekeV, qnC)
sigX = 12.4e-10 * k / (ekeV * 4 * np.pi * theta_fwhm)
# coherence width:
widthCoherence = beta * sigX
# get first n eigenvalues for transverse modes
n = 99
e0 = eigenvaluePartCoh(sigX, widthCoherence, range(0, n))
# keep only modes for which eigenvalue > threshold
e = e0[e0 > threshold]
if display:
plotEigenValues(e0, threshold)
# generate mode indices
modes = modes2D(9, N=len(e))
dimension = 2 # value should be 3 for 3D wavefront, 2 for 2D wavefront
wf = []
for mx, my in modes:
# define unique filename for storing results
ip = np.floor(ekeV)
frac = np.floor((ekeV - ip) * 1e3)
# build initial gaussian wavefront
if dimension == 2:
wfr0 = build_gauss_wavefront_xy(
nx=npoints,
ny=npoints,
ekev=ekeV,
xMin=-range_xy / 2,
xMax=range_xy / 2,
yMin=-range_xy / 2,
yMax=range_xy / 2,
sigX=sigX,
sigY=sigX,
d2waist=z1,
_mx=mx,
_my=my,
)
else:
# build initial 3d gaussian beam
tau = 1
# not sure if this parameter is even used - check meaning.
wfr0 = build_gauss_wavefront(
nx=npoints,
ny=npoints,
nz=nslices,
ekev=ekev,
xMin=-range_xy / 2,
xMax=range_xy / 2,
yMin=-range_xy / 2,
yMax=range_xy / 2,
tau=tau,
sigX=sigX,
sigY=sigX,
d2waist=z1,
_mx=mx,
_my=my,
)
if display == True:
print(
"dy {:.1f} um".format(
(mwf.params.Mesh.yMax - mwf.params.Mesh.yMin)
* 1e6
/ (mwf.params.Mesh.ny - 1.0)
)
)
print(
"dx {:.1f} um".format(
(mwf.params.Mesh.xMax - mwf.params.Mesh.xMin)
* 1e6
/ (mwf.params.Mesh.nx - 1.0)
)
)
plot_t_wf(mwf)
look_at_q_space(mwf)
# init WPG Wavefront helper class
mwf = Wavefront(wfr0)
# store wavefront to HDF5 file
if strOutputDataFolder:
fname0 = (
"g"
+ str(int(ip))
+ "_"
+ str(int(frac))
+ "kev"
+ "_tm"
+ str(mx)
+ str(my)
)
ifname = os.path.join(strOutputDataFolder, fname0 + ".h5")
mwf.store_hdf5(ifname)
print("Saved wavefront to HDF5 file: {}".format(ifname))
else:
ifname = None
wf.append([mx, my, ifname, mwf])
# plotWavefront(mwf, 'at '+str(z1)+' m')
# look_at_q_space(mwf)
fwhm_x = calculate_fwhm_x(mwf)
print(
"FWHMx [mm], theta_fwhm [urad]: {}, {}".format(
fwhm_x * 1e3, fwhm_x / z1 * 1e6
)
)
# show_slices_hsv(mwf, slice_numbers=None, pretitle='SLICETYSLICE')
return wf, modes, e
def propagate(in_fname, out_fname):
"""
Propagate wavefront
:param in_file: input wavefront file
:param out_file: output file
"""
print('Start propagating:' + in_fname)
wf=Wavefront()
wf.load_hdf5(in_fname)
distance0 = 300.
distance1 = 630.
distance = distance0 + distance1
f_hfm = 3.0 # nominal focal length for HFM KB
f_vfm = 1.9 # nominal focal length for VFM KB
distance_hfm_vfm = f_hfm - f_vfm
distance_foc = 1. /(1./f_vfm + 1. / (distance + distance_hfm_vfm))
theta_om = 3.5e-3 # offset mirrors incidence angle
theta_kb = 3.5e-3 # KB mirrors incidence angle
drift0 = wpg.optical_elements.Drift(distance0)
drift1 = wpg.optical_elements.Drift(distance1)
drift_in_kb = wpg.optical_elements.Drift(distance_hfm_vfm)
drift_to_foc = wpg.optical_elements.Drift(distance_foc)
om_mirror_length = 0.8; om_clear_ap = om_mirror_length*theta_om
kb_mirror_length = 0.9; kb_clear_ap = kb_mirror_length*theta_kb
ap0 = wpg.optical_elements.Aperture('r','a', 120.e-6, 120.e-6)
ap1 = wpg.optical_elements.Aperture('r','a', om_clear_ap, 2*om_clear_ap)
ap_kb = wpg.optical_elements.Aperture('r','a', kb_clear_ap, kb_clear_ap)
hfm = wpg.optical_elements.Mirror_elliptical(
orient='x',p=distance, q=(distance_hfm_vfm+distance_foc),
thetaE=theta_kb, theta0=theta_kb, length=0.9)
vfm = wpg.optical_elements.Mirror_elliptical(
orient='y',p=(distance+distance_hfm_vfm), q=distance_foc,
thetaE=theta_kb, theta0=theta_kb, length=0.9)
wf_dist_om = wpg.optical_elements.WF_dist(1500, 100, om_clear_ap, 2*om_clear_ap)
defineOPD(wf_dist_om, os.path.join(mirror_data_dir,'mirror2.dat'), 2, '\t', 'x',
theta_kb, scale=2)
if isIpynb:
meshT = wf_dist_om.mesh
opdTmp=np.array(wf_dist_om.arTr)[1::2].reshape(meshT.ny,meshT.nx)
figure(); pylab.imshow(opdTmp,extent=[meshT.xStart,meshT.xFin,meshT.yStart,meshT.yFin])
pylab.title('OPD [m]');pylab.xlabel('x (m)'); pylab.ylabel('y (m)')
wf_dist_hfm = wpg.optical_elements.WF_dist(1500, 100, kb_clear_ap, kb_clear_ap)
defineOPD(wf_dist_hfm, os.path.join(mirror_data_dir,'mirror1.dat'), 2, '\t', 'x',
theta_kb, scale=2, stretching=kb_mirror_length/0.8)
if isIpynb:
meshT = wf_dist_hfm.mesh
opdTmp=np.array(wf_dist_hfm.arTr)[1::2].reshape(meshT.ny,meshT.nx)
figure(); pylab.imshow(opdTmp,extent=[meshT.xStart,meshT.xFin,meshT.yStart,meshT.yFin])
pylab.title('OPD [m]');pylab.xlabel('x (m)'); pylab.ylabel('y (m)')
wf_dist_vfm = wpg.optical_elements.WF_dist(1100, 1500, kb_clear_ap, kb_clear_ap)
defineOPD(wf_dist_vfm, os.path.join(mirror_data_dir,'mirror2.dat'), 2, ' ', 'y',
theta_kb, scale=2, stretching=kb_mirror_length/0.8)
if isIpynb:
meshT = wf_dist_vfm.mesh
opdTmp=np.array(wf_dist_vfm.arTr)[1::2].reshape(meshT.ny,meshT.nx)
figure(); pylab.imshow(opdTmp,extent=[meshT.xStart,meshT.xFin,meshT.yStart,meshT.yFin])
pylab.title('OPD [m]');pylab.xlabel('x (m)'); pylab.ylabel('y (m)')
bl0 = wpg.Beamline()
bl0.append(ap0, Use_PP(semi_analytical_treatment=0, zoom=14.4, sampling=1/1.6))
bl0.append(drift0,Use_PP(semi_analytical_treatment=0))
bl0.append(ap1, Use_PP(zoom=0.8)) #bl0.append(ap1, Use_PP(zoom=1.6, sampling=1/1.5))
bl0.append(wf_dist_om, Use_PP())
bl0.append(drift1, Use_PP(semi_analytical_treatment=1))
bl0.append(ap_kb, Use_PP(zoom = 6.4, sampling = 1/16.))#bl0.append(ap_kb, Use_PP(zoom=5.4, sampling=1/6.4))
bl0.append(hfm, Use_PP())
bl0.append(wf_dist_hfm, Use_PP())
bl0.append(drift_in_kb, Use_PP(semi_analytical_treatment=1))
bl0.append(vfm, Use_PP())
bl0.append(wf_dist_vfm, Use_PP())
bl0.append(drift_to_foc, Use_PP(semi_analytical_treatment=1))
if isIpynb:
print bl0
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, 'f')
sz0 = get_intensity_on_axis(wf);
wf.custom_fields['/misc/spectrum0'] = sz0
bl0.propagate(wf)
sz1 = get_intensity_on_axis(wf);
wf.custom_fields['/misc/spectrum1'] = sz1
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, 't')
#Resizing: decreasing Range of Horizontal and Vertical Position:
wpg.srwlib.srwl.ResizeElecField(wf._srwl_wf, 'c', [0, 0.25, 1, 0.25, 1]);
fwhm = calculate_fwhm(wf)
wf.custom_fields['/misc/xFWHM'] = fwhm['fwhm_x']
wf.custom_fields['/misc/yFWHM'] = fwhm['fwhm_y']
wf.custom_fields['/params/beamline/printout'] = str(bl0)
wf.custom_fields['/info/contact'] = [
'Name: Liubov Samoylova', 'Email: [email protected]',
'Name: Alexey Buzmakov', 'Email: [email protected]']
wf.custom_fields['/info/data_description'] = 'This dataset contains infromation about wavefront propagated through beamline (WPG and SRW frameworks).'
wf.custom_fields['/info/method_description'] = """WPG, WaveProperGator (http://github.com/samoylv/WPG)is an interactive simulation framework for coherent X-ray wavefront propagation.\nSRW, Synchrotron Radiation Workshop (http://github.com/ochubar/SRW), is a physical optics computer code for simulation of the radiation wavefront propagation through optical systems of beamlines as well as detailed characteristics of Synchrotron Radiation (SR) generated by relativistic electrons in magnetic fields of arbitrary configuration."""
wf.custom_fields['/info/package_version'] = '2014.1'
print('Saving the wavefront data after propagation:' + out_fname)
mkdir_p(os.path.dirname(out_fname))
wf.store_hdf5(out_fname)
add_history(out_fname, in_fname)
print('...done')
def stepwise(in_fname, get_beamline):
"""
Propagate wavefront stepwise, dumping the wavefront at every step.
:param in_file: input wavefront file
:param get_beamline: function to build beamline
"""
print("#" * 80)
print("Setup initial wavefront.")
wf = Wavefront()
# Load wavefront data.
print("Load " + in_fname)
wf.load_hdf5(in_fname)
# Get beamline.
bl0 = get_beamline()
beamline = bl0.propagation_options
if len(beamline) > 1:
raise RuntimeError("Beamline configuration not supported.")
beamline = beamline[0]
elements = beamline["optical_elements"]
options = beamline["propagation_parameters"]
if len(elements) != len(options):
raise RuntimeError("Beamline configuration not supported.")
i = 0
for element, option in zip(elements, options):
print("\n")
print("#" * 80)
print("Propagation step %d." % (i))
print("Setting up incremental beamline.")
beamline_step = Beamline()
beamline_step.append(element, option) ### <== CHECKME
# Switch to frequency domain.
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, "f")
# Save spectrum for later reference.
sz0 = get_intensity_on_axis(wf)
wf.custom_fields["/misc/spectrum0"] = sz0
# Propagate.
beamline_step.propagate(wf)
# Save spectrum after propagation for later reference.
sz1 = get_intensity_on_axis(wf)
wf.custom_fields["/misc/spectrum1"] = sz1
# Switch back to time domain.
wpg.srwlib.srwl.SetRepresElecField(wf._srwl_wf, "t")
incremental_filename = "%04d.h5" % (i)
print("Saving propagated wavefront to " + incremental_filename)
mkdir_p(os.path.dirname(incremental_filename))
wf.store_hdf5(incremental_filename)
print("Done with propagation step %d." % (i))
print("#" * 80)
# Increment running index.
i += 1
class WavePropagator(AbstractPhotonPropagator):
"""
Class representing a photon propagator using wave optics through WPG.
"""
def __init__(self, parameters=None, input_path=None, output_path=None):
"""
Constructor for the xfel photon propagator.
@param parameters : Parameters steering the propagation of photons.
<br/><b>type</b> : dict
@param input_path : Location of input data for the photon propagation.
<br/><b>type</b> : string
@param output_path : Location of output data for the photon propagation.
<br/><b>type</b> : string
"""
# Check if beamline was given.
if isinstance(parameters, Beamline):
parameters = {'beamline' : parameters}
# Raise if no beamline in parameters.
if parameters is None or not 'beamline' in parameters.keys():
raise RuntimeError( 'The parameters argument must be an instance of wpg.Beamline or a dict containing the key "beamline" and an instance of wpg.Beamline as the corresponding value.')
# Initialize base class.
super(WavePropagator, self).__init__(parameters,input_path,output_path)
# Take reference to beamline.
self.__beamline = parameters['beamline']
def backengine(self):
""" This method drives the backengine code, in this case the WPG interface to SRW."""
# Switch to frequency representation.
srwl.SetRepresElecField(self.__wavefront._srwl_wf, 'f') # <---- switch to frequency domain
# Propagate through beamline.
self.__beamline.propagate(self.__wavefront)
# Switch back to time representation.
srwl.SetRepresElecField(self.__wavefront._srwl_wf, 't')
return 0
@property
def data(self):
""" Query for the field data. """
return self.__data
def _readH5(self):
""" """
""" Private method for reading the hdf5 input and extracting the parameters and data relevant to initialize the object. """
# Check input.
try:
self.__h5 = h5py.File( self.input_path, 'r' )
except:
raise IOError( 'The input_path argument (%s) is not a path to a valid hdf5 file.' % (self.input_path) )
# Construct wpg wavefront based on input data.
self.__wavefront = Wavefront()
self.__wavefront.load_hdf5(self.input_path)
def saveH5(self):
""" """
"""
Private method to save the object to a file.
@param output_path : The file where to save the object's data.
<br/><b>type</b> : string
<br/><b>default</b> : None
"""
# Write data to hdf file using wpg interface function.
self.__wavefront.store_hdf5(self.output_path)
