def test_dnde_from_flux():
"""Tests y-value normalization adjustment method.
"""
energy_min = np.array([10, 20, 30, 40])
energy_max = np.array([20, 30, 40, 50])
flux = np.array([42, 52, 62, 72]) # 'True' integral flux in this test bin
# Get values
model = XSqrTestModel()
energy_ref = FluxPoints._energy_ref_lafferty(model, energy_min, energy_max)
dnde = FluxPoints._dnde_from_flux(flux,
model,
energy_ref,
energy_min,
energy_max,
pwl_approx=False)
# Set up test case comparison
dnde_model = model(energy_ref)
# Test comparison result
desired = model.integral(energy_min, energy_max)
# Test output result
actual = flux * (dnde_model / dnde)
# Compare
assert_allclose(actual, desired, rtol=1e-6)
def test_energy_ref_lafferty():
"""
Tests Lafferty & Wyatt x-point method.
Using input function g(x) = 10^4 exp(-6x) against
check values from paper Lafferty & Wyatt. Nucl. Instr. and Meth. in Phys.
Res. A 355 (1995) 541-547, p. 542 Table 1
"""
# These are the results from the paper
desired = np.array([0.048, 0.190, 0.428, 0.762])
model = LWTestModel()
energy_min = np.array([0.0, 0.1, 0.3, 0.6])
energy_max = np.array([0.1, 0.3, 0.6, 1.0])
actual = FluxPoints._energy_ref_lafferty(model, energy_min, energy_max)
assert_allclose(actual, desired, atol=1e-3)
def test_dnde_from_flux():
"""Tests y-value normalization adjustment method.
"""
table = Table()
table["e_min"] = np.array([10, 20, 30, 40])
table["e_max"] = np.array([20, 30, 40, 50])
table["flux"] = np.array([42, 52, 62, 72]) # 'True' integral flux in this test bin
# Get values
model = XSqrTestModel()
table["e_ref"] = FluxPoints._energy_ref_lafferty(model, table["e_min"], table["e_max"])
dnde = FluxPoints.from_table(table, reference_model=model)
# Set up test case comparison
dnde_model = model(table["e_ref"])
# Test comparison result
desired = model.integral(table["e_min"], table["e_max"])
# Test output result
actual = table["flux"] * (dnde_model / dnde)
# Compare
assert_allclose(actual, desired, rtol=1e-6)
def test_compute_flux_points_dnde_exp(method):
"""
Tests against analytical result or result from a powerlaw.
"""
model = ExpTestModel()
energy_min = [1.0, 10.0] * u.TeV
energy_max = [10.0, 100.0] * u.TeV
table = Table()
table.meta["SED_TYPE"] = "flux"
table["e_min"] = energy_min
table["e_max"] = energy_max
flux = model.integral(energy_min, energy_max)
table["flux"] = flux
if method == "log_center":
energy_ref = np.sqrt(energy_min * energy_max)
elif method == "table":
energy_ref = [2.0, 20.0] * u.TeV
elif method == "lafferty":
energy_ref = FluxPoints._energy_ref_lafferty(model, energy_min,
energy_max)
table["e_ref"] = energy_ref
result = FluxPoints.from_table(table, reference_model=model)
# Test energy
actual = result.energy_ref
assert_quantity_allclose(actual, energy_ref, rtol=1e-8)
# Test flux
actual = result.dnde
desired = model(energy_ref)
assert_quantity_allclose(actual, desired, rtol=1e-8)
