|
@@ 139-151 (lines=13) @@
|
| 136 |
|
# def test_covariance(): |
| 137 |
|
|
| 138 |
|
|
| 139 |
|
@pytest.mark.parametrize("backend", ["minuit"]) |
| 140 |
|
def test_confidence(backend): |
| 141 |
|
dataset = MyDataset() |
| 142 |
|
fit = Fit(backend=backend) |
| 143 |
|
fit.optimize([dataset]) |
| 144 |
|
result = fit.confidence(datasets=[dataset], parameter="x") |
| 145 |
|
|
| 146 |
|
assert result["success"] is True |
| 147 |
|
assert_allclose(result["errp"], 1) |
| 148 |
|
assert_allclose(result["errn"], 1) |
| 149 |
|
|
| 150 |
|
# Check that original value state wasn't changed |
| 151 |
|
assert_allclose(dataset.models.parameters["x"].value, 2) |
| 152 |
|
|
| 153 |
|
|
| 154 |
|
@pytest.mark.parametrize("backend", ["minuit"]) |
|
@@ 154-164 (lines=11) @@
|
| 151 |
|
assert_allclose(dataset.models.parameters["x"].value, 2) |
| 152 |
|
|
| 153 |
|
|
| 154 |
|
@pytest.mark.parametrize("backend", ["minuit"]) |
| 155 |
|
def test_confidence_frozen(backend): |
| 156 |
|
dataset = MyDataset() |
| 157 |
|
dataset.models.parameters["x"].frozen = True |
| 158 |
|
fit = Fit(backend=backend) |
| 159 |
|
fit.optimize([dataset]) |
| 160 |
|
result = fit.confidence(datasets=[dataset], parameter="y") |
| 161 |
|
|
| 162 |
|
assert result["success"] is True |
| 163 |
|
assert_allclose(result["errp"], 1) |
| 164 |
|
assert_allclose(result["errn"], 1) |
| 165 |
|
|
| 166 |
|
|
| 167 |
|
def test_stat_profile(): |
gammapy /
gammapy
