def initialize_wavefront_from_range(cls, x_min=0.0, x_max=0.0, number_of_points=1000, wavelength=1e-10):
return Wavefront1D(
wavelength,
ScaledArray.initialize_from_range(
np_array=numpy.full(number_of_points, (1.0 + 0.0j), dtype=complex),
min_scale_value=x_min,
max_scale_value=x_max,
),
)
def initialize_wavefront_from_range(cls,
x_min=0.0,
x_max=0.0,
number_of_points=1000,
wavelength=1e-10):
return Wavefront1D(
wavelength,
ScaledArray.initialize_from_range(np_array=numpy.full(
number_of_points, (1.0 + 0.0j), dtype=complex),
min_scale_value=x_min,
max_scale_value=x_max))
def initialize_wavefront_from_range(cls,
x_min=0.0,
x_max=0.0,
number_of_points=1000,
wavelength=1e-10,
polarization=Polarization.SIGMA):
sA = ScaledArray.initialize_from_range(np_array=numpy.full(
number_of_points, (1.0 + 0.0j), dtype=complex),
min_scale_value=x_min,
max_scale_value=x_max)
if ((polarization == Polarization.PI)
or (polarization == Polarization.TOTAL)):
sA_pi = ScaledArray.initialize_from_range(np_array=numpy.full(
number_of_points, (0.0 + 0.0j), dtype=complex),
min_scale_value=x_min,
max_scale_value=x_max)
else:
sA_pi = None
return GenericWavefront1D(wavelength, sA, sA_pi)
def calculate_function_average_value(function, x_min, x_max, sampling=100):
sampled_function = ScaledArray.initialize_from_range(np.zeros(sampling), x_min, x_max)
sampled_function.np_array = function(sampled_function.scale)
return np.average(sampled_function.np_array)
def test_ScaledArray(self,do_plot=do_plot):
#
# ScaledArray.initialize + set_scale_from_steps
#
test_array = numpy.arange(15.0, 18.8, 0.2)
print("\nTesting ScaledArray.initialize + set_scale_from_steps...")
scaled_array = ScaledArray.initialize(test_array)
scaled_array.set_scale_from_steps(test_array[0],0.2)
print("Using array: ",test_array)
print("Stored array: ",scaled_array.get_values())
print("Using array: ",test_array)
print("Stored abscissas: ",scaled_array.get_abscissas())
numpy.testing.assert_almost_equal(test_array,scaled_array.get_values(),11)
numpy.testing.assert_almost_equal(test_array,scaled_array.get_abscissas(),11)
self.assertAlmostEqual(0.2,scaled_array.delta(),11)
self.assertAlmostEqual(15.0,scaled_array.offset(),11)
x_in = (18.80,16.22,22.35)
x_good = (18.80,16.22,18.8)
for i,x in enumerate(x_in):
print("interpolated at %3.2f is: %3.2f (must give %3.2f)"%( x,scaled_array.interpolate_value(x), x_good[i] ))
self.assertAlmostEqual(scaled_array.interpolate_value(x), x_good[i], 2)
#
# ScaledArray.initialize + set_scale_from_range ; interpolate vectorized
#
print("\nTesting ScaledArray.initialize + set_scale_from_range ; interpolate vectorized...")
scaled_array = ScaledArray.initialize(test_array)
scaled_array.set_scale_from_range(test_array[0],test_array[-1])
x_in = (18.80,16.22,22.35)
x_good = (18.80,16.22,18.8)
for i,x in enumerate(x_in):
print("interpolated at %3.2f is: %3.2f (must give %3.2f)"%( x,scaled_array.interpolate_value(x), x_good[i] ))
self.assertAlmostEqual(scaled_array.interpolate_value(x), x_good[i], 2)
#
# ScaledArray.initialize_from_steps
#
print("\nTesting ScaledArray.initialize_from_steps...")
scaled_array = ScaledArray.initialize_from_steps(test_array, test_array[0], 0.2)
x_in = (18.80,16.22,22.35)
x_good = (18.80,16.22,18.8)
for i,x in enumerate(x_in):
print("interpolated at %3.2f is: %3.2f (must give %3.2f)"%( x,scaled_array.interpolate_value(x), x_good[i] ))
self.assertAlmostEqual(scaled_array.interpolate_value(x), x_good[i], 2)
#
# ScaledArray.initialize_from_steps
#
print("\nTesting ScaledArray.initialize_from_range...")
scaled_array = ScaledArray.initialize_from_range(test_array,test_array[0], test_array[-1])
x_in = (18.80,16.22,22.35)
x_good = (18.80,16.22,18.8)
for i,x in enumerate(x_in):
print("interpolated at %3.2f is: %3.2f (must give %3.2f)"%( x,scaled_array.interpolate_value(x), x_good[i] ))
self.assertAlmostEqual(scaled_array.interpolate_value(x), x_good[i], 2)
#
# interpolator
#
print("\nTesting interpolator...")
x = numpy.arange(-5.0, 18.8, 3)
y = x**2
scaled_array = ScaledArray.initialize_from_range(y,x[0],x[-1])
print("for interpolation; x=",x)
print("for interpolation; offset, delta:=",scaled_array.offset(),scaled_array.delta())
print("for interpolation; abscissas:=",scaled_array.get_abscissas())
x1 = numpy.concatenate( ( numpy.arange(-6, -4, 0.1) , [0], numpy.arange(11, 20.0, 0.1) ) )
y1 = scaled_array.interpolate_values(x1)
if do_plot:
from srxraylib.plot.gol import plot
plot(x,y,x1,y1,legend=["Data",'Interpolated'],legend_position=[0.4,0.8],
marker=['','o'],linestyle=['-',''],xrange=[-6,21],yrange=[-5,375])
for i in range(len(x1)):
y2 = x1[i]**2
if x1[i] <= x[0]:
y2 = y[0]
if x1[i] >= x[-1]:
y2 = y[-1]
print(" interpolated at x=%g is: %g (expected: %g)"%(x1[i],y1[i],y2))
self.assertAlmostEqual(1e-3*y1[i], 1e-3*y2, 2)
# interpolate on same grid
print("\nTesting interpolation on the same grid...")
y1 = scaled_array.interpolate_values(scaled_array.get_abscissas())
if do_plot:
from srxraylib.plot.gol import plot
plot(scaled_array.get_abscissas(),scaled_array.get_values(),
scaled_array.get_abscissas(),y1,legend=["Data",'Interpolated on same grid'],legend_position=[0.4,0.8],
marker=['','o'],linestyle=['-',''])
numpy.testing.assert_almost_equal(scaled_array.get_values(),y1,5)
def propagate_1D_x_direction(calculation_parameters, input_parameters):
scale_factor = 1.0
shadow_oe = calculation_parameters.shadow_oe_end
global_phase_shift_profile = None
if shadow_oe._oe.F_MOVE == 1 and shadow_oe._oe.Y_ROT != 0.0:
if input_parameters.ghy_calcType == 3 or input_parameters.ghy_calcType == 4:
global_phase_shift_profile = calculation_parameters.w_mirror_lx
elif input_parameters.ghy_calcType == 2:
global_phase_shift_profile = ScaledArray.initialize_from_range(numpy.zeros(3), shadow_oe._oe.RWIDX2, shadow_oe._oe.RWIDX1)
global_phase_shift_profile.set_values(global_phase_shift_profile.get_values() +
global_phase_shift_profile.get_abscissas()*numpy.sin(numpy.radians(-shadow_oe._oe.Y_ROT)))
elif input_parameters.ghy_calcType == 3 or input_parameters.ghy_calcType == 4:
global_phase_shift_profile = calculation_parameters.w_mirror_lx
if input_parameters.ghy_calcType == 3 or input_parameters.ghy_calcType == 4:
rms_slope = hy_findrmsslopefromheight(global_phase_shift_profile)
print("Using RMS slope = " + str(rms_slope))
average_incident_angle = numpy.radians(90-calculation_parameters.shadow_oe_end._oe.T_INCIDENCE)*1e3
average_reflection_angle = numpy.radians(90-calculation_parameters.shadow_oe_end._oe.T_REFLECTION)*1e3
if calculation_parameters.beam_not_cut_in_x:
dp_image = numpy.std(calculation_parameters.xx_focal_ray)/input_parameters.ghy_focallength
dp_se = 2 * rms_slope * numpy.sin(average_incident_angle/1e3) # different in x and z
dp_error = calculation_parameters.gwavelength/2/(calculation_parameters.ghy_x_max-calculation_parameters.ghy_x_min)
scale_factor = max(1, 5*min(dp_error/dp_image, dp_error/dp_se))
# ------------------------------------------
# far field calculation
# ------------------------------------------
if calculation_parameters.do_ff_x:
focallength_ff = calculate_focal_length_ff(calculation_parameters.ghy_x_min,
calculation_parameters.ghy_x_max,
input_parameters.ghy_npeak,
calculation_parameters.gwavelength)
if input_parameters.ghy_calcType == 3:
if not (rms_slope == 0.0 or average_incident_angle == 0.0):
focallength_ff = min(focallength_ff,(calculation_parameters.ghy_x_max-calculation_parameters.ghy_x_min) / 16 / rms_slope / numpy.sin(average_incident_angle / 1e3))#xshi changed
elif input_parameters.ghy_calcType == 4:
if not (rms_slope == 0.0 or average_incident_angle == 0.0):
focallength_ff = min(focallength_ff,(calculation_parameters.ghy_x_max-calculation_parameters.ghy_x_min) / 8 / rms_slope / (numpy.sin(average_incident_angle / 1e3) + numpy.sin(average_reflection_angle / 1e3)))#xshi changed
elif input_parameters.ghy_calcType == 2 and not global_phase_shift_profile is None:
focallength_ff = min(focallength_ff, input_parameters.ghy_distance*4) #TODO: PATCH to be found with a formula
fftsize = int(scale_factor * calculate_fft_size(calculation_parameters.ghy_x_min,
calculation_parameters.ghy_x_max,
calculation_parameters.gwavelength,
focallength_ff,
input_parameters.ghy_fftnpts))
print("FF: creating plane wave begin, fftsize = " + str(fftsize))
wavefront = Wavefront1D.initialize_wavefront_from_range(wavelength=calculation_parameters.gwavelength,
number_of_points=fftsize,
x_min=scale_factor * calculation_parameters.ghy_x_min,
x_max=scale_factor * calculation_parameters.ghy_x_max)
if scale_factor == 1.0:
try:
wavefront.set_plane_wave_from_complex_amplitude(numpy.sqrt(calculation_parameters.wIray_x.interpolate_values(wavefront.get_abscissas())))
except IndexError:
raise Exception("Unexpected Error during interpolation: try reduce Number of bins for I(Sagittal) histogram")
wavefront.apply_ideal_lens(focallength_ff)
if input_parameters.ghy_calcType == 3 or \
(input_parameters.ghy_calcType == 2 and not global_phase_shift_profile is None):
wavefront.add_phase_shifts(get_mirror_phase_shift(wavefront.get_abscissas(),
calculation_parameters.gwavelength,
calculation_parameters.wangle_x,
calculation_parameters.wl_x,
global_phase_shift_profile))
elif input_parameters.ghy_calcType == 4:
wavefront.add_phase_shifts(get_grating_phase_shift(wavefront.get_abscissas(),
calculation_parameters.gwavelength,
calculation_parameters.wangle_x,
calculation_parameters.wangle_ref_x,
calculation_parameters.wl_x,
global_phase_shift_profile))
print("calculated plane wave: begin FF propagation (distance = " + str(focallength_ff) + ")")
propagated_wavefront = propagator.propagate_1D_fresnel(wavefront, focallength_ff)
print("dif_xp: begin calculation")
shadow_oe = calculation_parameters.shadow_oe_end
imagesize = min(abs(calculation_parameters.ghy_x_max), abs(calculation_parameters.ghy_x_min)) * 2
# 2017-01 Luca Rebuffi
imagesize = min(imagesize,
input_parameters.ghy_npeak*2*0.88*calculation_parameters.gwavelength*focallength_ff/abs(calculation_parameters.ghy_x_max-calculation_parameters.ghy_x_min))
# TODO: this is a patch: to be rewritten
if shadow_oe._oe.F_MOVE==1 and not shadow_oe._oe.Y_ROT==0:
imagesize = max(imagesize, 8*(focallength_ff*numpy.tan(numpy.radians(numpy.abs(shadow_oe._oe.Y_ROT))) + numpy.abs(shadow_oe._oe.OFFX)))
imagenpts = int(round(imagesize / propagated_wavefront.delta() / 2) * 2 + 1)
dif_xp = ScaledArray.initialize_from_range(numpy.ones(propagated_wavefront.size()),
-(imagenpts - 1) / 2 * propagated_wavefront.delta(),
(imagenpts - 1) / 2 * propagated_wavefront.delta())
dif_xp.np_array = numpy.absolute(propagated_wavefront.get_interpolated_complex_amplitudes(dif_xp.scale))**2
dif_xp.set_scale_from_range(-(imagenpts - 1) / 2 * propagated_wavefront.delta() / focallength_ff,
(imagenpts - 1) / 2 * propagated_wavefront.delta() / focallength_ff)
calculation_parameters.dif_xp = dif_xp
# ------------------------------------------
# near field calculation
# ------------------------------------------
if input_parameters.ghy_nf >= 1 and input_parameters.ghy_calcType > 1: # near field calculation
focallength_nf = input_parameters.ghy_focallength
fftsize = int(scale_factor * calculate_fft_size(calculation_parameters.ghy_x_min,
calculation_parameters.ghy_x_max,
calculation_parameters.gwavelength,
numpy.abs(focallength_nf),
input_parameters.ghy_fftnpts))
print("NF: creating plane wave begin, fftsize = " + str(fftsize))
wavefront = Wavefront1D.initialize_wavefront_from_range(wavelength=calculation_parameters.gwavelength,
number_of_points=fftsize,
x_min=scale_factor*calculation_parameters.ghy_x_min,
x_max=scale_factor*calculation_parameters.ghy_x_max)
if scale_factor == 1.0:
try:
wavefront.set_plane_wave_from_complex_amplitude(numpy.sqrt(calculation_parameters.wIray_x.interpolate_values(wavefront.get_abscissas())))
except IndexError:
raise Exception("Unexpected Error during interpolation: try reduce Number of bins for I(Sagittal) histogram")
wavefront.apply_ideal_lens(focallength_nf)
if input_parameters.ghy_calcType == 3 or \
(input_parameters.ghy_calcType == 2 and not global_phase_shift_profile is None):
wavefront.add_phase_shifts(get_mirror_phase_shift(wavefront.get_abscissas(),
calculation_parameters.gwavelength,
calculation_parameters.wangle_x,
calculation_parameters.wl_x,
global_phase_shift_profile))
elif input_parameters.ghy_calcType == 4:
wavefront.add_phase_shifts(get_grating_phase_shift(wavefront.get_abscissas(),
calculation_parameters.gwavelength,
calculation_parameters.wangle_x,
calculation_parameters.wangle_ref_x,
calculation_parameters.wl_x,
global_phase_shift_profile))
print("calculated plane wave: begin NF propagation (distance = " + str(input_parameters.ghy_distance) + ")")
propagated_wavefront = propagator.propagate_1D_fresnel(wavefront, input_parameters.ghy_distance)
# ghy_npeak in the wavefront propagation image
imagesize = (input_parameters.ghy_npeak * 2 * 0.88 * calculation_parameters.gwavelength * numpy.abs(focallength_nf) / abs(calculation_parameters.ghy_x_max - calculation_parameters.ghy_x_min))
imagesize = max(imagesize,
2 * abs((calculation_parameters.ghy_x_max - calculation_parameters.ghy_x_min) * (input_parameters.ghy_distance - numpy.abs(focallength_nf))) / numpy.abs(focallength_nf))
if input_parameters.ghy_calcType == 3:
imagesize = max(imagesize,
16 * rms_slope * numpy.abs(focallength_nf) * numpy.sin(average_incident_angle / 1e3))
elif input_parameters.ghy_calcType == 4:
imagesize = max(imagesize,
8 * rms_slope * numpy.abs(focallength_nf) * (numpy.sin(average_incident_angle / 1e3) + numpy.sin(average_reflection_angle / 1e3)))
# TODO: this is a patch: to be rewritten
if shadow_oe._oe.F_MOVE==1 and not shadow_oe._oe.Y_ROT==0:
imagesize = max(imagesize, 8*(input_parameters.ghy_distance*numpy.tan(numpy.radians(numpy.abs(shadow_oe._oe.Y_ROT))) + numpy.abs(shadow_oe._oe.OFFX)))
imagenpts = int(round(imagesize / propagated_wavefront.delta() / 2) * 2 + 1)
print("dif_x: begin calculation")
dif_x = ScaledArray.initialize_from_range(numpy.ones(imagenpts),
-(imagenpts - 1) / 2 * propagated_wavefront.delta(),
(imagenpts - 1) / 2 * propagated_wavefront.delta())
dif_x.np_array *= numpy.absolute(propagated_wavefront.get_interpolated_complex_amplitudes(dif_x.scale))**2
calculation_parameters.dif_x = dif_x
