def construct_gaussian(nx, ny, ekev, extent, sigX, sigY, divergence, xoff = 0, yoff = 0, tau = 1, mx = 0, my = 0, tiltX = 0, tiltY = 0):
gsnBm = build_gaussian(nx, ny, ekev, xMin = extent[0], xMax = extent[1], yMin = extent[2], yMax = extent[3],
sigX = sigX, sigY = sigY, d2waist = 1, xoff = xoff, yoff = yoff, pulseTau = tau, _mx = mx, _my = my, tiltX= tiltX, tiltY = tiltY)
wfr = Wavefront(gsnBm)
wfr.params.wavelength = ekev2wav(ekev)
modify_beam_divergence(wfr,sigX, divergence)
return wfr
def generator(self, outdir, N=1):
"""
this is the emission process, and generates N wavefronts according to the rules given by the source paramters file.
currently, it will only support cases where the input dictionary has values in the form of a single value or list.
:param
"""
for n in range(N):
self.set_empirical_values()
self.build_properties()
for itr in range(self._control):
pulse_properties = {
item: self.source_properties[item][itr]
for item in self.source_properties
}
tp = self.get_temporal_profile(pulse_properties)
pulse_properties['nz'] = len(tp)
tilt = wavefront_tilt(
np.meshgrid(
np.linspace(pulse_properties['xMin'],
pulse_properties['xMax'],
pulse_properties['nx']),
np.linspace(pulse_properties['yMin'],
pulse_properties['yMax'],
pulse_properties['ny'])),
2 * np.pi * np.sin(pulse_properties['theta_x']) /
ekev2wav(pulse_properties['ekev']),
2 * np.pi * np.sin(pulse_properties['theta_y']) /
ekev2wav(pulse_properties['ekev']))
efield = self.generate_beam_envelope(
pulse_properties)[:, :, np.newaxis] * tp * tilt[:, :,
np.newaxis]
self.generate(efield,
pulse_properties,
outdir=outdir + "_{:02}_{:04}.h5".format(n, itr))
for r in dr:
theta_r = phase_gradient(x, r, k, delta, offset=r)
ax1.plot(x * M * 1e3, theta_r, label="{} mm".format(r * 1e3))
ax1.set_xlim([0, 15])
ax1.set_xlabel("x (mm)")
ax1.set_ylabel("Phase Gradient ($\mu rad$)")
plt.legend()
if __name__ == '__main__':
delta = 4e-07 ### perspex
ekev = 25
wav = ekev2wav(ekev)
k = (np.pi * 2) / wav
N = 5000
x = np.linspace(-5e-02, 5e-02, N)
z1 = .1
z2 = 2
print("Angular Sensitivity: {}".format(angular_sensitivity(6.5e-06, z2)))
M = fresnel_magnification(z1, z2)
# =============================================================================
# plot_fullfield_image(r = 15e-03)
def define_speckle_mask(sample_directory,
rx,
ry,
sample_thickness,
sample_delta,
ekev=None,
xc=0,
yc=0,
plot=False):
arr = load_tif(sample_directory)
sample_thicc = arr / 255 * sample_thickness
if plot:
plt.style.use(['science', 'ieee'])
### plot sample thickness
fig, ax1 = plt.subplots()
img = ax1.imshow(sample_thicc * 1e6,
cmap="bone",
norm=colors.Normalize())
ax1.set_xlabel("x (mm)")
ax1.set_ylabel("y (mm)")
divider = make_axes_locatable(ax1)
cax = divider.append_axes('right', size='7.5%', pad=0.05)
cbar = fig.colorbar(img, cax)
cbar.set_label("Thickness ($\mu$m)")
if plot and ekev is not None:
plt.style.use(['science', 'ieee'])
### plot sample phase-shift
fig, ax1 = plt.subplots()
img = ax1.imshow(wrap_phase(
get_phase_shift(sample_thicc, ekev2wav(ekev))),
cmap="hsv")
ax1.set_xlabel("x (mm)")
ax1.set_ylabel("y (mm)")
divider = make_axes_locatable(ax1)
cax = divider.append_axes('right', size='7.5%', pad=0.05)
cbar = fig.colorbar(img, cax)
cbar.set_label("Phase Shift (rad)")
cax.set_xlim([-np.pi, np.pi])
s = Sample(sample_directory,
rx=rx,
ry=ry,
thickness=sample_thicc,
delta=sample_delta,
atten_len=1,
xc=xc,
yc=yc,
invert=True)
return s
from wpg.wpg_uti_wf import plot_intensity_map
from .examples.NFS.cylinder_phase_mask import phase, cylinder_thickness
import numpy as np
from felpy.utils.opt_utils import ekev2wav
from felpy.model.tools import propagation_parameters
from wpg.optical_elements import Drift
from wpg.beamline import Beamline
from .examples.NFS.speckle import define_speckle_mask
from felpy.analysis.statistics.correlation import norm
from PIL import Image
ekev = 25
wav = ekev2wav(25)
k = np.pi * 2 / wav
delta = 4e-07
d2waist = (wav) / (np.arctan(.27 / 8) * np.pi)
r = 75e-03
wfr = Wavefront(
construct_gaussian(1024, 1024, 25, -15e-02, 15e-02, -15e-02, 15e-02, 3e-2,
3e-02, d2waist))
### PLOT 1
plot_intensity_map(wfr)
bl = Beamline()
# images = [load_tif(fdir + a)[700:800,700:800] for a in os.listdir(fdir)]
# #images = [load_tif(fdir + a) for a in os.listdir(fdir)]
#
# reference = images[0]
# images = images[1:]
# =============================================================================
### using thibault speckle
reference, images = get_measurements()
images = list(images)
plot_images(reference, images, cmap='bone', clabel="Projected Thickness")
reference_map = paganin_method(I=reference,
n_ratio=100,
wav=ekev2wav(6.2),
z=.15)
distorted_maps = [
paganin_method(I=a, n_ratio=100, wav=ekev2wav(6.2), z=.15)
for a in images
]
reference_thickness = determine_thickness(reference_map,
ekev2wav(6.2),
delta=4e-07)
distorted_thickness = []
for item in distorted_maps:
distorted_thickness.append(
determine_thickness(item, ekev2wav(6.2), delta=4e-07))