コード例 #1
0
def propagate_single_mode(af, i, beamline):

    from wofry.propagator.propagator import PropagationManager, PropagationElements, PropagationParameters
    from syned.beamline.beamline_element import BeamlineElement
    from syned.beamline.element_coordinates import ElementCoordinates
    from wofry.propagator.propagators2D.fresnel_zoom_xy import FresnelZoomXY2D

    from wofry.propagator.wavefront2D.generic_wavefront import GenericWavefront2D
    from wofry.beamline.optical_elements.ideal_elements.screen import WOScreen

    mi = af.coherentMode(i)
    evi = af.eigenvalue(i)

    print("propagating mode index", i, evi, mi.shape)

    input_wavefront = GenericWavefront2D.initialize_wavefront_from_arrays(
        x_array=af.xCoordinates(),
        y_array=af.yCoordinates(),
        z_array=mi * numpy.sqrt(evi),
    )
    i0 = input_wavefront.get_integrated_intensity()

    input_wavefront.set_photon_energy(17226.0)

    propagator = PropagationManager.Instance()
    try:
        propagator.add_propagator(FresnelZoomXY2D())
    except:
        pass

    wfp = beamline.propagate(input_wavefront, propagator)

    i1 = wfp[-1].get_integrated_intensity()

    return wfp, i1 / i0
コード例 #2
0
    def propagate_numpy_wavefront(cls, filename_in, filename_out, beamline, mypropagator, return_wavefront_list=True):

        file_content = numpy.load(filename_in)
        e_field = file_content["e_field"]
        coordinates = file_content["coordinates"]
        energies = file_content["energies"]

        x = numpy.linspace(coordinates[0], coordinates[1], e_field.shape[1])
        y = numpy.linspace(coordinates[2], coordinates[3], e_field.shape[2])
        wofry_wf_in = GenericWavefront2D.initialize_wavefront_from_arrays(x, y, e_field[0, :, :, 0].copy())
        wofry_wf_in.set_photon_energy(energies[0])

        # wofry_wf_out_list = cls.propagate_classmethod(wofry_wf_in,beamline,mypropagator)
        wofry_wf_out = beamline.propagate(wofry_wf_in, mypropagator, return_wavefront_list=return_wavefront_list)

        if return_wavefront_list:
            wofry_wf_out_list = wofry_wf_out
            wofry_wf_out = wofry_wf_out_list[-1]

        e_field[0, :, :, 0] = wofry_wf_out.get_complex_amplitude()

        coordinates[0] = wofry_wf_out.get_coordinate_x()[0]
        coordinates[1] = wofry_wf_out.get_coordinate_x()[-1]
        coordinates[2] = wofry_wf_out.get_coordinate_y()[0]
        coordinates[3] = wofry_wf_out.get_coordinate_y()[-1]

        numpy.savez(filename_out,
                    e_field=e_field,
                    coordinates=coordinates,
                    energies=energies)

        if return_wavefront_list:
            return wofry_wf_out_list
        else:
            return wofry_wf_out
コード例 #3
0
def load_h5_file(filename, filepath):
    try:
        f = h5py.File(filename, 'r')
        mesh_X = f[filepath + "/wfr_mesh_X"].value
        mesh_Y = f[filepath + "/wfr_mesh_Y"].value
        complex_amplitude_s = f[filepath + "/wfr_complex_amplitude_s"].value.T
        wfr = GenericWavefront2D.initialize_wavefront_from_arrays(
            x_array=numpy.linspace(mesh_X[0], mesh_X[1], int(mesh_X[2])),
            y_array=numpy.linspace(mesh_Y[0], mesh_Y[1], int(mesh_Y[2])),
            z_array=complex_amplitude_s)
        wfr.set_photon_energy(f[filepath + "/wfr_photon_energy"].value)
        f.close()
        return wfr
    except:
        raise Exception("Failed to load 2D wavefront to h5 file: " + filename)
コード例 #4
0
    def propagate_numpy_wavefront(cls,
                                  filename_in,
                                  filename_out,
                                  beamline,
                                  mypropagator,
                                  return_wavefront_list=True):

        file_content = numpy.load(filename_in)
        e_field = file_content["e_field"]
        coordinates = file_content["coordinates"]
        energies = file_content["energies"]

        x = numpy.linspace(coordinates[0], coordinates[1], e_field.shape[1])
        y = numpy.linspace(coordinates[2], coordinates[3], e_field.shape[2])
        wofry_wf_in = GenericWavefront2D.initialize_wavefront_from_arrays(
            x, y, e_field[0, :, :, 0].copy())
        wofry_wf_in.set_photon_energy(energies[0])

        # wofry_wf_out_list = cls.propagate_classmethod(wofry_wf_in,beamline,mypropagator)
        wofry_wf_out = beamline.propagate(
            wofry_wf_in,
            mypropagator,
            return_wavefront_list=return_wavefront_list)

        if return_wavefront_list:
            wofry_wf_out_list = wofry_wf_out
            wofry_wf_out = wofry_wf_out_list[-1]

        e_field[0, :, :, 0] = wofry_wf_out.get_complex_amplitude()

        coordinates[0] = wofry_wf_out.get_coordinate_x()[0]
        coordinates[1] = wofry_wf_out.get_coordinate_x()[-1]
        coordinates[2] = wofry_wf_out.get_coordinate_y()[0]
        coordinates[3] = wofry_wf_out.get_coordinate_y()[-1]

        numpy.savez(filename_out,
                    e_field=e_field,
                    coordinates=coordinates,
                    energies=energies)

        if return_wavefront_list:
            return wofry_wf_out_list
        else:
            return wofry_wf_out
コード例 #5
0
def fresnel(wavefront, propagation_distance, shift_half_pixel=False):
    wavelength = wavefront.get_wavelength()

    #
    # convolving with the Fresnel kernel via FFT multiplication
    #
    fft = numpy.fft.fft2(wavefront.get_complex_amplitude())

    # frequency for axis 1
    shape = wavefront.size()
    delta = wavefront.delta()

    pixelsize = delta[0]  # p_x[1] - p_x[0]
    npixels = shape[0]
    freq_nyquist = 0.5 / pixelsize
    freq_n = numpy.linspace(-1.0, 1.0, npixels)
    freq_x = freq_n * freq_nyquist

    # frequency for axis 2
    pixelsize = delta[1]
    npixels = shape[1]
    freq_nyquist = 0.5 / pixelsize
    freq_n = numpy.linspace(-1.0, 1.0, npixels)
    freq_y = freq_n * freq_nyquist

    if shift_half_pixel:
        freq_x = freq_x - 0.5 * numpy.abs(freq_x[1] - freq_x[0])
        freq_y = freq_y - 0.5 * numpy.abs(freq_y[1] - freq_y[0])

    freq_xy = numpy.array(numpy.meshgrid(freq_y, freq_x))
    # fft *= numpy.exp((-1.0j) * numpy.pi * wavelength * propagation_distance *
    #               numpy.fft.fftshift(freq_xy[0]*freq_xy[0] + freq_xy[1]*freq_xy[1]) )
    fft *= numpy.exp(
        (-1.0j) * numpy.pi * wavelength * propagation_distance *
        numpy.fft.fftshift(freq_xy[0] * freq_xy[0] + freq_xy[1] * freq_xy[1]))

    wf_propagated = GenericWavefront2D.initialize_wavefront_from_arrays(
        x_array=wavefront.get_coordinate_x(),
        y_array=wavefront.get_coordinate_y(),
        z_array=numpy.fft.ifft2(fft),
        wavelength=wavelength)

    return wf_propagated
コード例 #6
0
    def send_mode(self):

        wf = GenericWavefront2D.initialize_wavefront_from_arrays(
            self.af.x_coordinates(), self.af.y_coordinates(),
            self.af.mode(self.MODE_INDEX))
        wf.set_photon_energy(self.af.photon_energy())
        ampl = wf.get_complex_amplitude()

        if self.TYPE_PRESENTATION == 5:
            eigen = self.af.eigenvalues_old()
            wf.set_complex_amplitude(ampl * numpy.sqrt(eigen[self.MODE_INDEX]))
        else:
            wf.set_complex_amplitude(ampl)

        beamline = WOBeamline(light_source=self.get_light_source())
        print(">>> sending mode: ", int(self.MODE_INDEX))
        self.send("WofryData", WofryData(wavefront=wf, beamline=beamline))

        # script
        self.wofry_python_script.set_code(beamline.to_python_code())
コード例 #7
0
    def propagate_wavefront(cls,
                            wavefront,
                            propagation_distance,
                            shift_half_pixel=False):

        from scipy.signal import fftconvolve

        wavelength = wavefront.get_wavelength()

        X = wavefront.get_mesh_x()
        Y = wavefront.get_mesh_y()

        if shift_half_pixel:
            x = wavefront.get_coordinate_x()
            y = wavefront.get_coordinate_y()
            X += 0.5 * numpy.abs(x[0] - x[1])
            Y += 0.5 * numpy.abs(y[0] - y[1])

        kernel = numpy.exp(1j * 2 * numpy.pi / wavefront.get_wavelength() *
                           (X**2 + Y**2) / 2 / propagation_distance)
        kernel *= numpy.exp(1j * 2 * numpy.pi / wavefront.get_wavelength() *
                            propagation_distance)
        kernel /= 1j * wavefront.get_wavelength() * propagation_distance

        wavefront_out = GenericWavefront2D.initialize_wavefront_from_arrays(
            x_array=wavefront.get_coordinate_x(),
            y_array=wavefront.get_coordinate_y(),
            z_array=fftconvolve(wavefront.get_complex_amplitude(),
                                kernel,
                                mode='same'),
            wavelength=wavelength)
        # added [email protected] 2018-03-23 to conserve energy - TODO: review method!
        wavefront_out.rescale_amplitude(
            numpy.sqrt(wavefront.get_intensity().sum() /
                       wavefront_out.get_intensity().sum()))

        return wavefront_out
コード例 #8
0
    def propagate_wavefront(cls,
                            wavefront1,
                            propagation_distance,
                            magnification_x=1.0,
                            magnification_y=1.0,
                            shift_half_pixel=False):

        wavefront = wavefront1.duplicate()
        wavelength = wavefront.get_wavelength()
        wavenumber = wavefront.get_wavenumber()

        shape = wavefront.size()
        delta = wavefront.delta()

        # frequency for axis 1
        pixelsize = delta[0]
        npixels = shape[0]
        freq_nyquist = 0.5 / pixelsize
        freq_n = numpy.linspace(-1.0, 1.0, npixels)
        freq_x0 = freq_n * freq_nyquist

        freq_x1 = numpy.fft.fftfreq(npixels, pixelsize)
        freq_x1 = numpy.fft.ifftshift(freq_x1)

        # frequency for axis 2
        pixelsize = delta[1]
        npixels = shape[1]
        freq_nyquist = 0.5 / pixelsize
        freq_n = numpy.linspace(-1.0, 1.0, npixels)
        freq_y0 = freq_n * freq_nyquist

        freq_y1 = numpy.fft.fftfreq(npixels, pixelsize)
        freq_y1 = numpy.fft.ifftshift(freq_y1)

        print(freq_x0[0:10], freq_x1[0:10])

        # It happens that with method=0 (old) the propagation of a centro-symmetric beam
        # is not longer center but shifted.
        # This is due to "shifted" storage of the frequencies that is dependent on the
        # even or odd number of pixels.
        # It seems that with the new method (method=1) the beam is center.
        # Note: The new method ignores the shift_half_pixel keyword
        # See also doscussion with V. Favre-Nicolin email to srio on 2018-05-02
        method = 1  # 0-old, 1-new

        if method == 0:
            freq_x = freq_x0
            freq_y = freq_y0
            if shift_half_pixel:
                freq_x = freq_x - 0.5 * numpy.abs(freq_x[1] - freq_x[0])
                freq_y = freq_y - 0.5 * numpy.abs(freq_y[1] - freq_y[0])
        else:
            freq_x = freq_x1
            freq_y = freq_y1

        f_x, f_y = numpy.meshgrid(freq_x, freq_y, indexing='ij')
        fsq = numpy.fft.fftshift(f_x**2 / magnification_x +
                                 f_y**2 / magnification_y)

        x = wavefront.get_mesh_x()
        y = wavefront.get_mesh_y()

        x_rescaling = wavefront.get_mesh_x() * magnification_x
        y_rescaling = wavefront.get_mesh_y() * magnification_y

        r1sq = x**2 * (1 - magnification_x) + y**2 * (1 - magnification_y)
        r2sq = x_rescaling**2 * (
            (magnification_x - 1) / magnification_x) + y_rescaling**2 * (
                (magnification_y - 1) / magnification_y)

        Q1 = wavenumber / 2 / propagation_distance * r1sq
        Q2 = numpy.exp(-1.0j * numpy.pi * wavelength * propagation_distance *
                       fsq)
        Q3 = numpy.exp(1.0j * wavenumber / 2 / propagation_distance * r2sq)

        wavefront.add_phase_shift(Q1)

        fft = numpy.fft.fft2(wavefront.get_complex_amplitude())

        ifft = numpy.fft.ifft2(fft * Q2) * Q3 / numpy.sqrt(
            magnification_x * magnification_y)

        wf_propagated = GenericWavefront2D.initialize_wavefront_from_arrays(
            x_array=wavefront.get_coordinate_x() * magnification_x,
            y_array=wavefront.get_coordinate_y() * magnification_y,
            z_array=ifft,
            wavelength=wavelength)
        return wf_propagated
コード例 #9
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    def test_initializers(self, do_plot=do_plot):

        print("#                                                             ")
        print("# Tests for initializars (2D)                                 ")
        print("#                                                             ")

        x = numpy.linspace(-100, 100, 50)
        y = numpy.linspace(-50, 50, 200)
        XY = numpy.meshgrid(x, y)
        X = XY[0].T
        Y = XY[1].T
        sigma = 10
        Z = numpy.exp(-(X**2 + Y**2) / 2 / sigma**2) * 1j
        print("Shapes x,y,z: ", x.shape, y.shape, Z.shape)

        wf0 = GenericWavefront2D.initialize_wavefront_from_steps(
            x[0],
            numpy.abs(x[1] - x[0]),
            y[0],
            numpy.abs(y[1] - y[0]),
            number_of_points=Z.shape)
        wf0.set_complex_amplitude(Z)

        wf1 = GenericWavefront2D.initialize_wavefront_from_range(
            x[0], x[-1], y[0], y[-1], number_of_points=Z.shape)
        wf1.set_complex_amplitude(Z)

        wf2 = GenericWavefront2D.initialize_wavefront_from_arrays(x, y, Z)

        if do_plot:
            from srxraylib.plot.gol import plot_image
            plot_image(wf0.get_intensity(),
                       wf0.get_coordinate_x(),
                       wf0.get_coordinate_y(),
                       title="initialize_wavefront_from_steps",
                       show=0)
            plot_image(wf1.get_intensity(),
                       wf1.get_coordinate_x(),
                       wf1.get_coordinate_y(),
                       title="initialize_wavefront_from_range",
                       show=0)
            plot_image(wf2.get_intensity(),
                       wf2.get_coordinate_x(),
                       wf2.get_coordinate_y(),
                       title="initialize_wavefront_from_arrays",
                       show=1)

        numpy.testing.assert_almost_equal(
            numpy.abs(Z)**2, wf0.get_intensity(), 11)
        numpy.testing.assert_almost_equal(
            numpy.abs(Z)**2, wf1.get_intensity(), 11)
        numpy.testing.assert_almost_equal(
            numpy.abs(Z)**2, wf2.get_intensity(), 11)

        numpy.testing.assert_almost_equal(x, wf0.get_coordinate_x(), 11)
        numpy.testing.assert_almost_equal(x, wf1.get_coordinate_x(), 11)
        numpy.testing.assert_almost_equal(x, wf2.get_coordinate_x(), 11)

        numpy.testing.assert_almost_equal(y, wf0.get_coordinate_y(), 11)
        numpy.testing.assert_almost_equal(y, wf1.get_coordinate_y(), 11)
        numpy.testing.assert_almost_equal(y, wf2.get_coordinate_y(), 11)
コード例 #10
0
ファイル: fresnel_zoom_xy.py プロジェクト: tschoonj/wofry
    def propagate_wavefront(cls,
                            wavefront1,
                            propagation_distance,
                            magnification_x=1.0,
                            magnification_y=1.0,
                            shift_half_pixel=False):

        wavefront = wavefront1.duplicate()
        wavelength = wavefront.get_wavelength()
        wavenumber = wavefront.get_wavenumber()

        shape = wavefront.size()
        delta = wavefront.delta()

        pixelsize = delta[0]
        npixels = shape[0]
        freq_nyquist = 0.5 / pixelsize
        freq_n = numpy.linspace(-1.0, 1.0, npixels)
        freq_x = freq_n * freq_nyquist

        # frequency for axis 2
        pixelsize = delta[1]
        npixels = shape[1]
        freq_nyquist = 0.5 / pixelsize
        freq_n = numpy.linspace(-1.0, 1.0, npixels)
        freq_y = freq_n * freq_nyquist

        if shift_half_pixel:
            freq_x = freq_x - 0.5 * numpy.abs(freq_x[1] - freq_x[0])
            freq_y = freq_y - 0.5 * numpy.abs(freq_y[1] - freq_y[0])

        f_x, f_y = numpy.meshgrid(freq_x, freq_y, indexing='ij')
        fsq = numpy.fft.fftshift(f_x**2 / magnification_x +
                                 f_y**2 / magnification_y)

        x = wavefront.get_mesh_x()
        y = wavefront.get_mesh_y()

        x_rescaling = wavefront.get_mesh_x() * magnification_x
        y_rescaling = wavefront.get_mesh_y() * magnification_y

        r1sq = x**2 * (1 - magnification_x) + y**2 * (1 - magnification_y)
        r2sq = x_rescaling**2 * (
            (magnification_x - 1) / magnification_x) + y_rescaling**2 * (
                (magnification_y - 1) / magnification_y)

        Q1 = wavenumber / 2 / propagation_distance * r1sq
        Q2 = numpy.exp(-1.0j * numpy.pi * wavelength * propagation_distance *
                       fsq)
        Q3 = numpy.exp(1.0j * wavenumber / 2 / propagation_distance * r2sq)

        wavefront.add_phase_shift(Q1)

        fft = numpy.fft.fft2(wavefront.get_complex_amplitude())

        ifft = numpy.fft.ifft2(fft * Q2) * Q3 / numpy.sqrt(
            magnification_x * magnification_y)

        wf_propagated = GenericWavefront2D.initialize_wavefront_from_arrays(
            x_array=wavefront.get_coordinate_x() * magnification_x,
            y_array=wavefront.get_coordinate_y() * magnification_y,
            z_array=ifft,
            wavelength=wavelength)
        return wf_propagated
コード例 #11
0
ファイル: integral.py プロジェクト: oasys-kit/wofryimpl
    def propagate_wavefront(cls,wavefront,propagation_distance,shuffle_interval=False,calculate_grid_only=True):
        #
        # Fresnel-Kirchhoff integral (neglecting inclination factor)
        #

        if not calculate_grid_only:
            #
            # calculation over the whole detector area
            #
            p_x = wavefront.get_coordinate_x()
            p_y = wavefront.get_coordinate_y()
            wavelength = wavefront.get_wavelength()
            amplitude = wavefront.get_complex_amplitude()

            det_x = p_x.copy()
            det_y = p_y.copy()

            p_X = wavefront.get_mesh_x()
            p_Y = wavefront.get_mesh_y()

            det_X = p_X
            det_Y = p_Y


            amplitude_propagated = numpy.zeros_like(amplitude,dtype='complex')

            wavenumber = 2 * numpy.pi / wavelength

            for i in range(det_x.size):
                for j in range(det_y.size):
                    if not shuffle_interval:
                        rd_x = 0.0
                        rd_y = 0.0
                    else:
                        rd_x = (numpy.random.rand(p_x.size,p_y.size)-0.5)*shuffle_interval
                        rd_y = (numpy.random.rand(p_x.size,p_y.size)-0.5)*shuffle_interval

                    r = numpy.sqrt( numpy.power(p_X + rd_x - det_X[i,j],2) +
                                    numpy.power(p_Y + rd_y - det_Y[i,j],2) +
                                    numpy.power(propagation_distance,2) )

                    amplitude_propagated[i,j] = (amplitude / r * numpy.exp(1.j * wavenumber *  r)).sum()

            output_wavefront = GenericWavefront2D.initialize_wavefront_from_arrays(det_x,det_y,amplitude_propagated)

        else:
            x = wavefront.get_coordinate_x()
            y = wavefront.get_coordinate_y()
            X = wavefront.get_mesh_x()
            Y = wavefront.get_mesh_y()
            wavenumber = 2 * numpy.pi / wavefront.get_wavelength()
            amplitude = wavefront.get_complex_amplitude()

            used_indices = wavefront.get_mask_grid(width_in_pixels=(1,1),number_of_lines=(1,1))
            indices_x = wavefront.get_mesh_indices_x()
            indices_y = wavefront.get_mesh_indices_y()

            indices_x_flatten = indices_x[numpy.where(used_indices == 1)].flatten()
            indices_y_flatten = indices_y[numpy.where(used_indices == 1)].flatten()
            X_flatten         =         X[numpy.where(used_indices == 1)].flatten()
            Y_flatten         =         Y[numpy.where(used_indices == 1)].flatten()
            complex_amplitude_propagated = amplitude*0

            print("propagate_2D_integral: Calculating %d points from a total of %d x %d = %d"%(
                X_flatten.size,amplitude.shape[0],amplitude.shape[1],amplitude.shape[0]*amplitude.shape[1]))

            for i in range(X_flatten.size):
                r = numpy.sqrt( numpy.power(wavefront.get_mesh_x() - X_flatten[i],2) +
                                numpy.power(wavefront.get_mesh_y() - Y_flatten[i],2) +
                                numpy.power(propagation_distance,2) )

                complex_amplitude_propagated[int(indices_x_flatten[i]),int(indices_y_flatten[i])] = (amplitude / r * numpy.exp(1.j * wavenumber *  r)).sum()

            output_wavefront = GenericWavefront2D.initialize_wavefront_from_arrays(x_array=x,
                                                                                   y_array=y,
                                                                                   z_array=complex_amplitude_propagated,
                                                                                   wavelength=wavefront.get_wavelength())

        # added [email protected] 2018-03-23 to conserve energy - TODO: review method!
        output_wavefront.rescale_amplitude( numpy.sqrt(wavefront.get_intensity().sum() /
                                                    output_wavefront.get_intensity().sum()))

        return output_wavefront
コード例 #12
0
    def write_file(self):
        self.setStatusMessage("")

        try:
            if not self.af is None:
                congruence.checkDir(self.file_name)

                if self.TYPE_OF_OUTPUT == 0:  # ['COMSYL hdf5 with multi-mode','WOFRY hdf5 with multi-mode','WOFRY multiple files'
                    if self.ALL_MODES:
                        self.af.write_h5(self.file_name,
                                         maximum_number_of_modes=None)
                    else:
                        self.af.write_h5(self.file_name,
                                         maximum_number_of_modes=self.MODE_TO)
                        path, file_name = os.path.split(self.file_name)
                        self.setStatusMessage("File Out: " + file_name)
                else:  # WOFRY
                    if self.ALL_MODES == 0 and (self.MODE_TO <
                                                self.af.number_of_modes()):
                        nmax = self.MODE_TO
                    else:
                        nmax = self.af.number_of_modes()

                    for i in range(nmax + 1):
                        eigenvalue = numpy.real(self.af.eigenvalue(i), )
                        eigenfunction = self.af.mode(i)
                        w = GenericWavefront2D.initialize_wavefront_from_arrays(
                            self.af.x_coordinates(), self.af.y_coordinates(),
                            eigenfunction * numpy.sqrt(eigenvalue))
                        w.set_photon_energy(self.af.photon_energy())

                        if self.TYPE_OF_OUTPUT == 1:  #
                            file_name = self.file_name
                            subgroupname = "mode" + self.index_format % (i)
                            overwrite = False
                        elif self.TYPE_OF_OUTPUT == 2:
                            subgroupname = "mode" + self.index_format % (i)
                            file_name = self.file_name.split(".")[0] + "_" + (
                                self.index_format % i) + ".h5"
                            overwrite = True

                        if i == 0:
                            w.save_h5_file(file_name,
                                           subgroupname=subgroupname,
                                           intensity=True,
                                           phase=True,
                                           overwrite=True)
                        else:
                            w.save_h5_file(file_name,
                                           subgroupname=subgroupname,
                                           intensity=True,
                                           phase=True,
                                           overwrite=overwrite)
                        path, file_name = os.path.split(file_name)
                        self.setStatusMessage("File Out: " + file_name)

                # path, file_name = os.path.split(self.file_name)

                # self.setStatusMessage("File Out: " + file_name)

            else:
                QMessageBox.critical(self, "Error", "COMSYL modes not present",
                                     QMessageBox.Ok)
        except Exception as exception:
            QMessageBox.critical(self, "Error", str(exception), QMessageBox.Ok)
コード例 #13
0
    X2 = numpy.outer(numpy.ones_like(x), x)

    # plot_image(X2,x,x)
    z = csd(X1, X2, sigmaI, sigmaMu)
    zi = get_intensity_from_csd(z)
    if do_plot:
        plot_image(z,
                   1e6 * x,
                   1e6 * x,
                   xtitle="X1",
                   ytitle="X2",
                   title="CDS before propagation",
                   show=0)
        plot(1e6 * x, zi, show=0)

    wf = GenericWavefront2D.initialize_wavefront_from_arrays(x, x, z)
    wf.set_photon_energy(23000)

    # wfp = fresnel(wf,propagation_distance=propagation_distance)
    magnification = 5
    wfp = fresnel_zoom(wf,
                       propagation_distance=propagation_distance,
                       magnification_x=magnification,
                       magnification_y=magnification)

    zp = wfp.get_intensity()
    zpi = get_intensity_from_csd(zp)

    fwhm_z, tmp, tmp = get_fwhm(zi / zi.max(), 1e6 * x)
    fwhm_zp, tmp, tmp = get_fwhm(zpi / zpi.max(), 1e6 * x)