def test_sqe_normalization():
# We need some lines
L1 = LorentzianLine("Lorentzian1", (-5.0, 5.0),
x0=0.0,
width=0.4,
c=0.0,
weight=2)
L2 = LorentzianLine(name="Lorentzian2",
domain=(-5.0, 5.0),
x0=-1.0,
width=0.4,
c=0.02,
weight=1)
# Contruct a SqE model
sqe = SqE(lines=(L1, L2), lam=6.0, dlam=0.12, l_SD=3.43, T=20)
new_domain = (-1 * energy_from_lambda(6.0), UPPER_INTEGRATION_LIMIT)
sqe.update_domain(new_domain)
# integrate over domain
from scipy.integrate import quad
to_integrate = lambda x: sqe(x)
valdom, errdom = quad(to_integrate, *new_domain)
valover, errover = quad(to_integrate, -15, 20)
print(
f"Integration value over domain from {new_domain[0]:.5f} to {UPPER_INTEGRATION_LIMIT}: {valdom:.5f} +- {errdom:.5f}"
) # | normalization factor: {n:.5f}")
print(
f"Integration value beyond domain from -15.0 to 20.0: {valover:.5f} +- {errover:.5f}"
)
def test_DetectorEfficiency_cancel():
# We need some lines
L1 = LorentzianLine("Lorentzian1", (-5.0, 5.0),
x0=0.0,
width=0.4,
c=0.0,
weight=2)
L2 = LorentzianLine(name="Lorentzian2",
domain=(-5.0, 5.0),
x0=-1.0,
width=0.4,
c=0.02,
weight=1)
# Contruct a SqE model
sqe = SqE(lines=(L1, L2), lam=6.0, dlam=0.12, lSD=3.43, T=20)
new_domain = (-1 * energy_from_lambda(6.0), UPPER_INTEGRATION_LIMIT)
sqe.update_domain(new_domain)
# init energycutoff
decf = DetectorEfficiencyCorrectionFactor(sqe, ne=10, nlam=5)
ee, ll = energy_lambda_nrange(15.0, 6.0, 0.12, 10000, 20)
# print(detector_efficiency(ee, ll, 1) * decf(ee, ll))
print(
trapz(trapz(decf(ee, ll) * decf.legacy_calc(ee, ll, 0), ee, axis=0),
ll[0]))
# print(trapz(trapz(ones(ll.shape), ee, axis=0), ll[0]))
print(trapz(trapz(decf.legacy_calc(ee, ll, 1), ee, axis=0), ll[0]))
print(trapz(trapz(decf.legacy_calc(ee, ll, 0), ee, axis=0), ll[0]))
print(
trapz(
trapz(decf.legacy_calc(ee, ll, 0), ee, axis=0) /
trapz(trapz(decf.legacy_calc(ee, ll, 1), ee, axis=0), ll[0]),
ll[0]))
def test_export_load():
# We need some lines
L1 = LorentzianLine("Lorentzian1", (-5.0, 5.0),
x0=0.0,
width=0.4,
c=0.0,
weight=2)
L2 = LorentzianLine(name="Lorentzian2",
domain=(-5.0, 5.0),
x0=-1.0,
width=0.4,
c=0.02,
weight=1)
# Contruct a SqE model
sqe = SqE(lines=(L1, L2), lam=6.0, dlam=0.12, lSD=3.43, T=20)
new_domain = (-1 * energy_from_lambda(6.0), UPPER_INTEGRATION_LIMIT)
sqe.update_domain(new_domain)
# init energycutoff
decf = DetectorEfficiencyCorrectionFactor(sqe, ne=10000, nlam=20)
# exports
corrdict = decf.export_to_dict()
decf.export_to_jsonfile(
f"{testdir}/resources/test_correction_export_load_file.json")
# loading
decf_from_dict = decf.load_from_dict(**corrdict)
print(decf_from_dict.export_to_dict())
print("", "Loading successful: ", decf, decf_from_dict, sep='\n')
decf_from_jsonfile = decf.load_from_jsonfile(
f"{testdir}/resources/test_correction_export_load_file.json")
print("Loading successful: ", decf, decf_from_jsonfile, sep='\n')
def test_EnergyCutoffCorrectionFactor():
# We need some lines
L1 = LorentzianLine("Lorentzian1", (-5.0, 5.0),
x0=0.0,
width=0.4,
c=0.0,
weight=2)
L2 = LorentzianLine(name="Lorentzian2",
domain=(-5.0, 5.0),
x0=-1.0,
width=0.4,
c=0.02,
weight=1)
# Contruct a SqE model
sqe = SqE(lines=(L1, L2), lam=6.0, dlam=0.12, lSD=3.43, T=20)
new_domain = (-1 * energy_from_lambda(6.0), UPPER_INTEGRATION_LIMIT)
sqe.update_domain(new_domain)
# init energycutoff
eccf = EnergyCutOffCorrectionFactor(sqe, ne=10000, nlam=20)
ne = 10000
nlam = 5
lam = 6.0 * linspace(1 - 0.12 * 1.01, 1 + 0.12 * 1.01, nlam)
lams = tile(lam, (ne, 1))
a = -0.99999 * energy_from_lambda(lam)
b = 15.0 + a
es = linspace(a, b, ne)
### Calculate the trapz integral over the S(q,E)
# Only over domain (interval length: 15 meV)
I_over_dom_only = trapz(sqe(es[:, 2]), es[:, 2])
print("Trapz integration over the domain.")
print(f"Interval {a[2]:.4f} - {b[2]:.4f} -> length {b[2]-a[2]:.4f} meV.")
print(f"#Steps = {ne}")
print(f"Integral value: {I_over_dom_only:.4f}")
# plt.plot(es[:,2], sqe(es[:,2]), label="Over domain only")
# plt.show()
# Beyond domain same array length
es_same_length = linspace(-UPPER_INTEGRATION_LIMIT,
UPPER_INTEGRATION_LIMIT, ne)
I_beyond_dom_same_length = trapz(sqe(es_same_length), es_same_length)
print("\nTrapz integration beyond the domain with varrying stepsize.")
print(
f"Interval {-UPPER_INTEGRATION_LIMIT} - {UPPER_INTEGRATION_LIMIT} -> length {30.0} meV."
)
print(f"#Steps = {ne}")
print(f"Integral value: {I_beyond_dom_same_length:.4f}")
# plt.plot(es_same_length, sqe(es_same_length), ls="--", label="Beyond domain ne=10000")
# plt.show()
# Beyond domain same step size
es_same_stepsize = arange(-UPPER_INTEGRATION_LIMIT,
UPPER_INTEGRATION_LIMIT + 0.001, 15e-3)
I_beyond_dom_same_stepsize = trapz(sqe(es_same_stepsize), es_same_stepsize)
print("\nTrapz integration beyond the domain with varrying stepsize.")
print(
f"Interval {-UPPER_INTEGRATION_LIMIT} - {UPPER_INTEGRATION_LIMIT} -> length {30.0} meV."
)
print(f"#Steps = {30.0 / 0.015}")
print(f"Integral value: {I_beyond_dom_same_stepsize:.4f}")