def test_random_radius(self):
""" Tests the random gaussian smearing method for radius.
Creates a delta function and fits the mean and sigma after smearing.
Mean and sigma are checked against set values within 1 %.
Integral of smeared spectrum is checked against original number of
entries.
"""
num_entries = 100000
test_spectra = spectra.Spectra("Test", num_entries)
radius = 1000. # mm
for i in range(num_entries):
test_spectra.fill(0, radius, 0)
smearing = smear.Smear()
smearing._position_resolution = 100. # mm
smeared_spectra = smearing.random_gaussian_radius_spectra(test_spectra)
mean, sigma, integral = self.fit_gaussian_radius(smeared_spectra)
self.assertTrue(radius < 1.01*mean and radius > 0.99*mean)
self.assertTrue(smearing._position_resolution < 1.01*sigma and smearing._position_resolution > 0.99*sigma)
self.assertAlmostEqual(integral/float(num_entries), 1.0)
def test_random_energy(self):
""" Tests the random gaussian smearing method for energy.
Creates a delta function and fits the mean and sigma after smearing.
Mean and sigma are checked against set values within 1 %.
Integral of smeared spectrum is checked against original number of
entries.
"""
num_entries = 100000
test_spectra = spectra.Spectra("Test",num_entries)
energy = 2.5 # MeV
for i in range(num_entries):
test_spectra.fill(energy, 0, 0)
smearing = smear.Smear()
smearing._light_yield = 200. # NHit per MeV
smeared_spectra = smearing.random_gaussian_energy_spectra(test_spectra)
expected_sigma = numpy.sqrt(energy/200.)
mean, sigma, integral = self.fit_gaussian_energy(smeared_spectra)
self.assertTrue(energy < 1.01*mean and energy > 0.99*mean)
self.assertTrue(expected_sigma < 1.01*sigma and expected_sigma > 0.99*sigma)
self.assertAlmostEqual(integral/float(num_entries), 1.0)
parser = argparse.ArgumentParser()
parser.add_argument("-m",
"--smear_method",
nargs='?',
const="weight",
type=str,
default="weight",
help="specify the smearing method to use")
parser.add_argument("path", type=str, help="specify path to hdf5 file")
args = parser.parse_args()
directory = args.path[:args.path.rfind("/") + 1] # strip filename
# strip directory and extension
filename = args.path[args.path.rfind("/") + 1:args.path.rfind(".")]
smearer = smear.Smear()
spectrum = store.load(args.path)
if args.smear_method == "weight": # Use default smear method
smeared_spectrum = smearer.weight_gaussian_energy_spectra(spectrum)
smeared_spectrum = smearer.weight_gaussian_radius_spectra(
smeared_spectrum)
elif args.smear_method == "random":
smeared_spectrum = smearer.random_gaussian_energy_spectra(spectrum)
smeared_spectrum = smearer.random_gaussian_radius_spectra(
smeared_spectrum)
else: # Not a valid smear method
parser.error(args.smear_method + " is not a valid smear method")
filename = directory + filename + "_smeared" + ".hdf5"
store.dump(filename, smeared_spectrum)