def test_gauss():
n = 64
sigma = 2
mean = n // 2
x = np.arange(n)
gt = np.exp(-((x - float(mean))**2) / (2 * sigma**2))
g = get_gauss(x, mean, sigma, normalized=False)
g_norm = get_gauss(n, mean, sigma, normalized=True)
np.testing.assert_almost_equal(gt, g)
assert np.abs(np.sum(g_norm) - 1) < 1e-7
# Extremely broad peak, sum must be 1 anyway
g = get_gauss(x, mean, n, normalized=True)
assert np.abs(np.sum(g_norm) - 1) < 1e-7
def __init__(self, energies, center, sigma, peak_transmission=1):
"""Create a Gussian beam filter for *energies* [keV], center it at *center* [keV] and use
std *sigma* [keV]. *peak_transmission* specifies the transmitted intensity for energy
*center*, i.e. this is the highest transmitted intensity.
"""
if len(energies) < 4:
raise ValueError('Number of energy points too low for interpolation')
energies = energies.rescale(q.keV).magnitude
center = center.rescale(q.keV).magnitude
sigma = sigma.rescale(q.keV).magnitude
profile = get_gauss(energies, center, sigma) * peak_transmission * q.keV
self._tck = interp.splrep(energies, profile)
def __init__(self, energies, center, sigma, peak_transmission=1):
"""Create a Gussian beam filter for *energies* [keV], center it at *center* [keV] and use
std *sigma* [keV]. *peak_transmission* specifies the transmitted intensity for energy
*center*, i.e. this is the highest transmitted intensity.
"""
if len(energies) < 4:
raise ValueError("Number of energy points too low for interpolation")
energies = energies.rescale(q.keV).magnitude
center = center.rescale(q.keV).magnitude
sigma = sigma.rescale(q.keV).magnitude
profile = get_gauss(energies, center, sigma) * peak_transmission * q.keV
self._tck = interp.splrep(energies, profile)
def main():
args = parse_args()
syris.init()
n = 1024
shape = (n, n)
ps = 1 * q.um
tr = Trajectory([(n / 2, n / 2, 0)] * ps, pixel_size=ps)
energy_center = args.energy_center * q.keV
fwhm = args.energy_resolution * energy_center
sigma = smath.fwnm_to_sigma(fwhm, n=2)
# Make sure we resolve the curve nicely
energies = np.arange(max(1 * q.keV, energy_center - 2 * fwhm),
energy_center + 2 * fwhm, fwhm / 25) * q.keV
dE = energies[1] - energies[0]
print 'Energy from, to, step, number:', energies[0], energies[-1], dE, len(
energies)
bm = make_topotomo(dE=dE, pixel_size=ps, trajectory=tr)
spectrum_energies = np.arange(1, 50, 1) * q.keV
native_spectrum = get_spectrum(bm, spectrum_energies, ps)
fltr = GaussianFilter(energies, energy_center, sigma)
gauss = get_gauss(energies.magnitude, energy_center.magnitude,
sigma.magnitude)
filtered_spectrum = get_spectrum(bm, energies, ps) * gauss
intensity = propagate([bm, fltr], shape, energies, 0 * q.m, ps).get()
show(intensity,
title='Intensity for energy range {} - {}'.format(
energies[0], energies[-1]))
plt.figure()
plt.plot(spectrum_energies.magnitude, native_spectrum)
plt.title('Source Spectrum')
plt.xlabel('Energy [keV]')
plt.ylabel('Intensity')
plt.figure()
plt.plot(energies.magnitude, gauss)
plt.title('Gaussian Filter')
plt.xlabel('Energy [keV]')
plt.ylabel('Transmitted intensity')
plt.figure()
plt.plot(energies.magnitude, filtered_spectrum)
plt.title('Filtered Spectrum')
plt.xlabel('Energy [keV]')
plt.ylabel('Intensity')
plt.show()
def main():
args = parse_args()
syris.init()
n = 1024
shape = (n, n)
ps = 1 * q.um
tr = Trajectory([(n / 2, n / 2, 0)] * ps, pixel_size=ps)
energy_center = args.energy_center * q.keV
fwhm = args.energy_resolution * energy_center
sigma = smath.fwnm_to_sigma(fwhm, n=2)
# Make sure we resolve the curve nicely
energies = np.arange(max(1 * q.keV, energy_center - 2 * fwhm),
energy_center + 2 * fwhm,
fwhm / 25) * q.keV
dE = energies[1] - energies[0]
print 'Energy from, to, step, number:', energies[0], energies[-1], dE, len(energies)
bm = make_topotomo(dE=dE, pixel_size=ps, trajectory=tr)
spectrum_energies = np.arange(1, 50, 1) * q.keV
native_spectrum = get_spectrum(bm, spectrum_energies, ps)
fltr = GaussianFilter(energies, energy_center, sigma)
gauss = get_gauss(energies.magnitude, energy_center.magnitude, sigma.magnitude)
filtered_spectrum = get_spectrum(bm, energies, ps) * gauss
intensity = propagate([bm, fltr], shape, energies, 0 * q.m, ps).get()
show(intensity, title='Intensity for energy range {} - {}'.format(energies[0], energies[-1]))
plt.figure()
plt.plot(spectrum_energies.magnitude, native_spectrum)
plt.title('Source Spectrum')
plt.xlabel('Energy [keV]')
plt.ylabel('Intensity')
plt.figure()
plt.plot(energies.magnitude, gauss)
plt.title('Gaussian Filter')
plt.xlabel('Energy [keV]')
plt.ylabel('Transmitted intensity')
plt.figure()
plt.plot(energies.magnitude, filtered_spectrum)
plt.title('Filtered Spectrum')
plt.xlabel('Energy [keV]')
plt.ylabel('Intensity')
plt.show()