Пример #1
0
def show_diagnostics(FELsource_out_number):

      FELsource_out_file = FELsource_out_number

      if not os.path.exists(FELsource_out_file):
            print('Input file {} not found.'.format(FELsource_out_file))
            return

      wf = Wavefront()
      wf.load_hdf5(FELsource_out_file)

      plot_t_wf(wf)
      look_at_q_space(wf)
      # show two figures window 1: image of I(x,y) integral intensity, with real
      # x and y axis and title with file name
      J2eV = 6.24150934e18;
      mesh = wf.params.Mesh
      tmin = mesh.sliceMin;
      tmax = mesh.sliceMax;
      dt = (tmax - tmin) / (mesh.nSlices - 1);
      dx = (mesh.xMax - mesh.xMin) / (mesh.nx - 1);
      dy = (mesh.yMax - mesh.yMin) / (mesh.ny - 1);

      wf_intensity = wf.get_intensity(polarization='horizontal');
      total_intensity = wf_intensity.sum(axis=-1);
      data = total_intensity * dt
      plt.figure()
      plt.imshow(data*dx*dy*1e6*J2eV/wf.params.photonEnergy,extent=[mesh.xMin*1e6,mesh.xMax*1e6,mesh.yMin*1e6,mesh.yMax * 1e6], cmap="YlGnBu_r")
      title = 'Number of photons per %.2f x %.2f $\mu m ^2$ pixel'  %  (dx*1e6, dx*1e6)
      plt.title(title)
      plt.colorbar(); plt.xlabel('[$\mu m$]');

      # window 2: plot of 2 curves:
      #(1) history/parent/temporal_struct - FAST post-processing
      temporal_struct = wf.custom_fields['history']['parent']['misc']['temporal_struct']
      t0 = (temporal_struct[:, 0].max() + temporal_struct[:, 0].min()) / 2

      plt.figure()
      plt.plot(temporal_struct[:, 0] - t0, temporal_struct[:, 1] * 1e-9, 'b',label = 'output FAST-pp')
      plt.hold(True)
      #(2) integral intensity I(t) calculated for wavefront written in h5

      t = np.linspace(tmin, tmax, wf.params.Mesh.nSlices)
      pulse_energy = wf.get_intensity().sum(axis=0).sum(axis=0) #check it
      plt.plot(t * 1e15, pulse_energy*dx*dy*1e6*1e-9,'ro', label = 'wavefront data')

      title = 'FEL pulse energy %.2f %s ' % (pulse_energy.sum(axis=0) * dx * dy * 1e6 * dt * 1e3, 'mJ')
      plt.title(title)
      plt.xlabel('time [fs]');
      plt.ylabel('Instantaneous power [GW]');
      plt.legend()
      plt.grid(True)
      plt.show()
Пример #2
0
    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)
Пример #3
0
    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)
Пример #4
0
    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)
Пример #5
0
    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)