def test_dnde_from_flux():
"""Tests y-value normalization adjustment method.
"""
e_min = np.array([10, 20, 30, 40])
e_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()
e_ref = FluxPoints._e_ref_lafferty(model, e_min, e_max)
dnde = FluxPoints._dnde_from_flux(flux,
model,
e_ref,
e_min,
e_max,
pwl_approx=False)
# Set up test case comparison
dnde_model = model(e_ref)
# Test comparison result
desired = model.integral(e_min, e_max)
# Test output result
actual = 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 gammapy.spectrum.powerlaw.
"""
model = ExpTestModel()
e_min = [1.0, 10.0] * u.TeV
e_max = [10.0, 100.0] * u.TeV
table = Table()
table.meta["SED_TYPE"] = "flux"
table["e_min"] = e_min
table["e_max"] = e_max
flux = model.integral(e_min, e_max)
table["flux"] = flux
if method == "log_center":
e_ref = np.sqrt(e_min * e_max)
elif method == "table":
e_ref = [2.0, 20.0] * u.TeV
table["e_ref"] = e_ref
elif method == "lafferty":
e_ref = FluxPoints._e_ref_lafferty(model, e_min, e_max)
result = FluxPoints(table).to_sed_type("dnde", model=model, method=method)
# Test energy
actual = result.e_ref
assert_quantity_allclose(actual, e_ref, rtol=1e-8)
# Test flux
actual = result.table["dnde"].quantity
desired = model(e_ref)
assert_quantity_allclose(actual, desired, rtol=1e-8)
def test_e_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()
e_min = np.array([0.0, 0.1, 0.3, 0.6])
e_max = np.array([0.1, 0.3, 0.6, 1.0])
actual = FluxPoints._e_ref_lafferty(model, e_min, e_max)
assert_allclose(actual, desired, atol=1e-3)
