def test_proton_model():
"""
test import
"""
from ..sherpa_models import PionDecay
model = PionDecay()
model.ampl = 1e36
model.index = 2.1
# point calc
output = model.calc([p.val for p in model.pars], energies)
# integrated
output = model.calc([p.val for p in model.pars], elo, xhi=ehi)
# test as well ECPL
model.cutoff = 1000
# Perform a fit to fake data
ui.load_arrays(1, energies, test_spec_points, test_err_points)
ui.set_model(model)
ui.guess()
# Actual fit is too slow for tests
# ui.fit()
# test with integrated data
ui.load_arrays(1, elo, ehi, test_spec_int, test_err_int, ui.Data1DInt)
ui.set_model(model)
ui.guess()
def test_guess_warns_no_guess_names_model(caplog, clean_ui):
"""Do we warn when the named model has no guess"""
ui.load_arrays(1, [1, 2, 3], [-3, 4, 5])
cpt = DummyModel('dummy')
assert len(caplog.records) == 0
ui.guess(cpt)
assert len(caplog.records) == 1
lname, lvl, msg = caplog.record_tuples[0]
assert lname == "sherpa.ui.utils"
assert lvl == logging.INFO
assert msg == "WARNING: No guess found for dummy"
def test_guess_warns_no_guess_no_argument(caplog, clean_ui):
"""Do we warn when the (implied) model has no guess"""
ui.load_arrays(1, [1, 2, 3], [-3, 4, 5])
cpt = DummyModel('dummy')
ui.set_source(cpt + cpt)
assert len(caplog.records) == 0
ui.guess()
assert len(caplog.records) == 1
lname, lvl, msg = caplog.record_tuples[0]
assert lname == "sherpa.ui.utils"
assert lvl == logging.INFO
assert msg == "WARNING: No guess found for (dummy + dummy)"
def test_electron_models():
"""
test import
"""
from ..sherpa_models import InverseCompton, Synchrotron, Bremsstrahlung
for modelclass in [InverseCompton, Synchrotron, Bremsstrahlung]:
model = modelclass()
model.ampl = 1e-8
model.index = 2.1
print(model)
# point calc
output = model.calc([p.val for p in model.pars], energies)
# test as well ECPL
model.cutoff = 100
# integrated
output = model.calc([p.val for p in model.pars], elo, xhi=ehi)
if modelclass is InverseCompton:
# Perform a fit to fake data
ui.load_arrays(1, energies, test_spec_points, test_err_points)
ui.set_model(model)
ui.guess()
ui.fit()
# add FIR and NIR components and test verbose
model.uNIR.set(1.0)
model.uFIR.set(1.0)
model.verbose.set(1)
# test with integrated data
ui.load_arrays(1, elo, ehi, test_spec_int, test_err_int,
ui.Data1DInt)
ui.set_model(model)
ui.guess()
ui.fit()