def test_run_without_set_up():
"""
Check that we raise a KeyError if we try to run a model without
setting it up first.
"""
test_m = model.Model()
pytest.raises(KeyError, test_m.run)
def test_set_up_bad_source_or_term(test_layers):
"""
Ensure that we raise an IndexError in the event we try to build a
model with fewer than three layers.
"""
test_m = model.Model()
pytest.raises(TypeError, test_m.set_up, test_layers)
def test_set_up_perpendicular_incidence():
"""
Ensure that we raise an IndexError in the event we try to build a
model with fewer than three layers.
"""
layers = [layer.Source(), layer.Layer(), layer.Terminator()]
test_m = model.Model()
pytest.raises(ValueError, test_m.set_up, layers, 500e6, 500e9, np.pi/2, 's')
def test_set_up_lt3_layers():
"""
Ensure that we raise an IndexError in the event we try to build a
model with fewer than three layers.
"""
layers = [layer.Source(), layer.Terminator()]
test_m = model.Model()
pytest.raises(IndexError, test_m.set_up, layers)
def test_set_angle_range():
"""
Check that we can properly set the angle sweep.
This test should raise a NotImplementedError for now.
"""
test_m = model.Model()
pytest.raises(NotImplementedError, test_m.set_angle_range, 0, 0)
def test_set_freq_range(f1, f2, nsample, expected):
"""Check that we can properly set the frequency sweep"""
test_m = model.Model()
if nsample == 0:
pytest.raises(ValueError, test_m.set_freq_range, f1, f2, nsample)
return
test_m.set_freq_range(f1, f2, nsample)
npt.assert_equal(test_m.freq_range, expected)
def test_run_halpern():
"""
Check that we can run the most basic model available, but with Halpern
coefficients.
"""
layers = [layer.Source(), layer.Layer(halperna=0., halpernb=0.), layer.Terminator()]
test_m = model.Model()
test_m.set_up(layers)
results = test_m.run()
npt.assert_allclose(results['transmittance'], np.ones(results['transmittance'].size))
npt.assert_allclose(results['reflectance'], np.zeros(results['reflectance'].size))
def test_run():
"""
Check that we can run the most basic model available---i.e., all
default values.
"""
layers = [layer.Source(), layer.Layer(), layer.Terminator()]
test_m = model.Model()
test_m.set_up(layers)
results = test_m.run()
npt.assert_allclose(results['transmittance'], np.ones(results['transmittance'].size))
npt.assert_allclose(results['reflectance'], np.zeros(results['reflectance'].size))
def test_set_up_halpern_layer():
"""
Check that we can set up a layer with Halpern coefficients, even if
other layers aren't created with Halpern coefficients.
"""
layers = [layer.Source(), layer.Layer(),
layer.Layer(halperna=999., halpernb=111.),
layer.Layer(), layer.Terminator()]
test_m = model.Model()
test_m.set_up(layers)
assert list(test_m.halpern_layers.keys()) == [2]
assert test_m.halpern_layers[2] == {'a' : 999., 'b' : 111., 'n' : 1.}
def test_set_up_basic(test_layers, expected_rind):
"""
Check that we can run through `set_up` with the most basic default
values.
"""
test_m = model.Model()
test_m.set_up(test_layers)
assert test_m.rinds == expected_rind
assert test_m.tands == [0., 0., 0.]
assert test_m.thicks == [np.inf, 1., np.inf]
assert test_m.low_freq == 500e6
assert test_m.high_freq == 500e9
assert test_m.pol == 's'
assert test_m.incident_angle == 0.
def test_save():
"""
Check that we can save the output of a model to a file
"""
layers = [layer.Source(), layer.Layer(), layer.Terminator()]
test_m = model.Model()
test_m.set_up(layers)
results = test_m.run()
test_m.save(OUTPUT_LOC)
dat = np.genfromtxt(OUTPUT_LOC, unpack=True)
expected_fs = np.linspace(500e6, 500e9, num=1000)
expected_ts = np.ones(1000)
expected_rs = np.zeros(1000)
assert dat.shape == (3, 1000)
npt.assert_allclose(dat[0], expected_fs)
npt.assert_allclose(dat[1], expected_ts)
npt.assert_allclose(dat[2], expected_rs)
os.remove(OUTPUT_LOC)
def test_reset_model():
"""
Check that we can create a basic model, then return all of the model's
attributes to their defaults.
"""
layers = [layer.Source(), layer.Layer(), layer.Terminator()]
test_m = model.Model()
expected_attrs = [None] * len(test_m.__dict__.keys())
test_m.set_up(layers)
assert test_m.rinds == [1., 1., 1]
assert test_m.tands == [0., 0., 0.]
assert test_m.thicks == [np.inf, 1., np.inf]
assert test_m.low_freq == 500e6
assert test_m.high_freq == 500e9
assert test_m.pol == 's'
assert test_m.incident_angle == 0.
test_m.reset_model()
reset_attrs = [test_m.__dict__[key] for key in test_m.__dict__.keys()]
assert reset_attrs == expected_attrs
def test_check_freq_bounds(f1, f2, expected_low, expected_high):
"""Check that we can properly set the high and low frequency bounds"""
test_m = model.Model()
test_m.set_freq_range(f1, f2)
assert test_m.low_freq == expected_low
assert test_m.high_freq == expected_high
def test_default_attr():
"""Check that we create `Model` class with expected attributes"""
test_m = model.Model()
model_attrs = [test_m.__dict__[key] for key in test_m.__dict__.keys()]
expected = [None] * len(model_attrs)
assert model_attrs == expected