def main(distance=150):
thickness = 0.32
from parallax import (
derive_absorption_coefficient_Si,
compute_offset,
compute_offset_dectris,
)
t0_cm = 0.032
pixel_cm = 0.0172
for energy_ev in range(8000, 16001, 4000):
mu_cm = derive_absorption_coefficient_Si(energy_ev * 0.001)
wavelength = 12.3985 / (energy_ev * 0.001)
theta_o = run_xds_xycorr(distance, wavelength, thickness)
fout = open("p%d.dat" % energy_ev, "w")
for theta in sorted(theta_o):
model = compute_offset(t0_cm, theta, mu_cm) / pixel_cm
model_d = compute_offset_dectris(t0_cm, theta, mu_cm) / pixel_cm
fout.write("%.3f %.3f %.3f %.3f\n" %
(theta, theta_o[theta], model, model_d))
fout.close()
def main_plot(distance, energy_ev):
thickness = 0.32
from parallax import (
derive_absorption_coefficient_Si,
compute_offset,
compute_offset_dectris,
)
t0_cm = 0.032
pixel_cm = 0.0172
mu_cm = derive_absorption_coefficient_Si(energy_ev * 0.001)
wavelength = 12.3985 / (energy_ev * 0.001)
theta_o = run_xds_xycorr(distance, wavelength, thickness)
import math
displacement = []
xds = []
m_gw = []
m_dec = []
for theta in sorted(theta_o):
model = compute_offset(t0_cm, theta, mu_cm) / pixel_cm
model_d = compute_offset_dectris(t0_cm, theta, mu_cm) / pixel_cm
displacement.append(distance * math.tan(theta))
xds.append(theta_o[theta])
m_gw.append(model)
m_dec.append(model_d)
import matplotlib
matplotlib.use("Agg")
from matplotlib import pyplot
p1, p2, p3 = pyplot.plot(displacement, xds, displacement, m_gw,
displacement, m_dec)
pyplot.xlabel("Displacement, pixels")
pyplot.ylabel("Offset, pixels")
pyplot.title("Parallax correction offsets at %deV" % energy_ev)
pyplot.legend([p1, p2, p3],
["Calculated by XDS", "GW model", "Dectris model"],
loc=2)
pyplot.savefig("%d.png" % energy_ev)
def main_plot(distance, energy_ev):
thickness = 0.32
from parallax import derive_absorption_coefficient_Si, compute_offset, \
compute_offset_dectris
t0_cm = 0.032
pixel_cm = 0.0172
mu_cm = derive_absorption_coefficient_Si(energy_ev * 0.001)
wavelength = 12.3985 / (energy_ev * 0.001)
theta_o = run_xds_xycorr(distance, wavelength, thickness)
import math
displacement = []
xds = []
m_gw = []
m_dec = []
for theta in sorted(theta_o):
model = compute_offset(t0_cm, theta, mu_cm) / pixel_cm
model_d = compute_offset_dectris(t0_cm, theta, mu_cm) / pixel_cm
displacement.append(distance * math.tan(theta))
xds.append(theta_o[theta])
m_gw.append(model)
m_dec.append(model_d)
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot
p1, p2, p3 = pyplot.plot(displacement, xds, displacement, m_gw,
displacement, m_dec)
pyplot.xlabel('Displacement, pixels')
pyplot.ylabel('Offset, pixels')
pyplot.title('Parallax correction offsets at %deV' % energy_ev)
pyplot.legend([p1, p2, p3], ['Calculated by XDS', 'GW model', 'Dectris model'],
loc=2)
pyplot.savefig('%d.png' % energy_ev)
def main(distance=150):
thickness = 0.32
from parallax import derive_absorption_coefficient_Si, compute_offset, \
compute_offset_dectris
t0_cm = 0.032
pixel_cm = 0.0172
for energy_ev in range(8000, 16001, 4000):
mu_cm = derive_absorption_coefficient_Si(energy_ev * 0.001)
wavelength = 12.3985 / (energy_ev * 0.001)
theta_o = run_xds_xycorr(distance, wavelength, thickness)
fout = open('p%d.dat' % energy_ev, 'w')
for theta in sorted(theta_o):
model = compute_offset(t0_cm, theta, mu_cm) / pixel_cm
model_d = compute_offset_dectris(t0_cm, theta, mu_cm) / pixel_cm
fout.write('%.3f %.3f %.3f %.3f\n' % (theta, theta_o[theta], model, model_d))
fout.close()