def test_extract_regularizer_mutliple_raises():
callbacks = [SplineRegularizer(), SplineRegularizer()]
with pytest.raises(NotImplementedError) as excinfo:
extract_regularizer(callbacks)
err_msg = 'Multiple regularizer callbacks where provided.'
assert err_msg == str(excinfo.value)
def test_SplineRegularizer(example_dataset):
degree = 3
smooth = 20
spline_reg = SplineRegularizer(degree=degree, smooth=smooth)
unfolded_with_reg = iterative_unfold(
data=example_dataset.data,
data_err=example_dataset.data_err,
response=example_dataset.response,
response_err=example_dataset.response_err,
efficiencies=example_dataset.efficiencies,
efficiencies_err=example_dataset.efficiencies_err,
return_iterations=True,
callbacks=[spline_reg])
unfolded_no_reg = iterative_unfold(
data=example_dataset.data,
data_err=example_dataset.data_err,
response=example_dataset.response,
response_err=example_dataset.response_err,
efficiencies=example_dataset.efficiencies,
efficiencies_err=example_dataset.efficiencies_err,
return_iterations=True)
no_reg = unfolded_no_reg.iloc[0]['unfolded']
x = np.arange(len(no_reg), dtype=float)
spline = UnivariateSpline(x, no_reg, k=degree, s=smooth)
fitted_unfolded = spline(x)
np.testing.assert_allclose(unfolded_with_reg.iloc[0]['unfolded'],
fitted_unfolded)
def test_callbacklist_callbacks():
logger = Logger()
reg = SplineRegularizer()
callbacks = [logger, reg]
c = CallbackList(callbacks=callbacks)
assert len(c) == len(callbacks)
assert all(i is j for i, j in zip(c.callbacks, callbacks))
def test_setup_callbacks_regularizer():
callbacks = [Logger(), SplineRegularizer()]
c, r = setup_callbacks_regularizer(callbacks)
assert isinstance(c, CallbackList)
assert len(c) == 1
assert c.callbacks[0] is callbacks[0]
assert r is callbacks[1]
def test_validate_callbacks_raises():
callbacks = [Logger(), SplineRegularizer(), 'not a callback']
with pytest.raises(TypeError) as excinfo:
validate_callbacks(callbacks)
err_msg = 'Found non-callback object in callbacks: {}'.format(
['not a callback'])
assert err_msg == str(excinfo.value)
def test_SplineRegularizer_groups(example_dataset):
degree = 3
smooth = 20
groups = np.empty_like(example_dataset.data)
groups[:len(groups) // 2] = 0
groups[len(groups) // 2:] = 1
spline_reg = SplineRegularizer(degree=degree, smooth=smooth, groups=groups)
unfolded_with_reg = iterative_unfold(
data=example_dataset.data,
data_err=example_dataset.data_err,
response=example_dataset.response,
response_err=example_dataset.response_err,
efficiencies=example_dataset.efficiencies,
efficiencies_err=example_dataset.efficiencies_err,
return_iterations=True,
callbacks=[spline_reg])
unfolded_no_reg = iterative_unfold(
data=example_dataset.data,
data_err=example_dataset.data_err,
response=example_dataset.response,
response_err=example_dataset.response_err,
efficiencies=example_dataset.efficiencies,
efficiencies_err=example_dataset.efficiencies_err,
return_iterations=True)
# Manually regularize each group independently
y_no_reg = unfolded_no_reg.iloc[0]['unfolded']
x = np.arange(len(y_no_reg), dtype=float)
fitted_unfolded_no_reg = np.empty(len(y_no_reg))
group_ids = np.unique(groups)
for group in group_ids:
group_mask = groups == group
x_group = x[group_mask]
y_group = y_no_reg[group_mask]
spline_group = UnivariateSpline(x_group, y_group, k=degree, s=smooth)
fitted_unfolded_group = spline_group(x_group)
fitted_unfolded_no_reg[group_mask] = fitted_unfolded_group
np.testing.assert_allclose(unfolded_with_reg.iloc[0]['unfolded'],
fitted_unfolded_no_reg)
def test_SplineRegularizer_groups_raises(example_dataset):
degree = 3
smooth = 20
groups = np.empty(len(example_dataset.data) - 1)
groups[:len(groups) // 2] = 0
groups[len(groups) // 2:] = 1
spline_reg = SplineRegularizer(degree=degree, smooth=smooth, groups=groups)
with pytest.raises(ValueError) as excinfo:
iterative_unfold(data=example_dataset.data,
data_err=example_dataset.data_err,
response=example_dataset.response,
response_err=example_dataset.response_err,
efficiencies=example_dataset.efficiencies,
efficiencies_err=example_dataset.efficiencies_err,
return_iterations=True,
callbacks=[spline_reg])
err_msg = ('Invalid groups array. There should be an entry '
'for each cause bin. However, got len(groups)={} '
'while there are {} cause bins.'.format(
len(groups), len(example_dataset.data)))
assert err_msg == str(excinfo.value)
def test_SplineRegularizer_isinstance_Regularizer():
spline_reg = SplineRegularizer()
assert isinstance(spline_reg, Regularizer)
def test_validate_callbacks():
callbacks = [Logger(), SplineRegularizer()]
assert validate_callbacks(callbacks) == callbacks
'for each cause bin. However, got len(groups)={} '
'while there are {} cause bins.'.format(
len(groups), len(example_dataset.data)))
assert err_msg == str(excinfo.value)
def test_validate_callbacks():
callbacks = [Logger(), SplineRegularizer()]
assert validate_callbacks(callbacks) == callbacks
def test_validate_empty_callbacks():
assert validate_callbacks(None) == []
@pytest.mark.parametrize('callback', [Logger(), SplineRegularizer()])
def test_validate_callbacks_single_callback(callback):
validate_callbacks(callback) == [callback]
def test_validate_callbacks_raises():
callbacks = [Logger(), SplineRegularizer(), 'not a callback']
with pytest.raises(TypeError) as excinfo:
validate_callbacks(callbacks)
err_msg = 'Found non-callback object in callbacks: {}'.format(
['not a callback'])
assert err_msg == str(excinfo.value)
def test_extract_regularizer_mutliple_raises():
