def test_plot_offset(self):
with mpl_plot_check():
self.table_summary.plot_offset_distribution()
def test_plot_allsky():
m = WcsNDMap.create(binsz=10 * u.deg)
with mpl_plot_check():
m.plot()
def test_plot_background_rate(self):
with mpl_plot_check():
self.obs_summary.plot_background_rate()
def test_plot_bias(self):
with mpl_plot_check():
self.edisp.plot_bias()
def test_plot_correlation(covariance_diagonal):
with mpl_plot_check():
covariance_diagonal.plot_correlation()
def test_plot(self, flux_points):
with mpl_plot_check():
flux_points.plot()
def test_plot_migration(self):
with mpl_plot_check():
self.edisp.plot_migration()
def test_map_fit(sky_model, geom, geom_etrue):
dataset_1 = get_map_dataset(geom, geom_etrue, name="test-1")
dataset_2 = get_map_dataset(geom, geom_etrue, name="test-2")
datasets = Datasets([dataset_1, dataset_2])
models = Models(datasets.models)
models.insert(0, sky_model)
models["test-1-bkg"].spectral_model.norm.value = 0.5
models["test-model"].spatial_model.sigma.frozen = True
datasets.models = models
dataset_2.counts = dataset_2.npred()
dataset_1.counts = dataset_1.npred()
models["test-1-bkg"].spectral_model.norm.value = 0.49
models["test-2-bkg"].spectral_model.norm.value = 0.99
fit = Fit(datasets)
result = fit.run()
assert result.success
assert "minuit" in repr(result)
npred = dataset_1.npred().data.sum()
assert_allclose(npred, 7525.790688, rtol=1e-3)
assert_allclose(result.total_stat, 21625.845714, rtol=1e-3)
pars = result.parameters
assert_allclose(pars["lon_0"].value, 0.2, rtol=1e-2)
assert_allclose(pars["lon_0"].error, 0.002244, rtol=1e-2)
assert_allclose(pars["index"].value, 3, rtol=1e-2)
assert_allclose(pars["index"].error, 0.024277, rtol=1e-2)
assert_allclose(pars["amplitude"].value, 1e-11, rtol=1e-2)
assert_allclose(pars["amplitude"].error, 4.216154e-13, rtol=1e-2)
# background norm 1
assert_allclose(pars[8].value, 0.5, rtol=1e-2)
assert_allclose(pars[8].error, 0.015811, rtol=1e-2)
# background norm 2
assert_allclose(pars[11].value, 1, rtol=1e-2)
assert_allclose(pars[11].error, 0.02147, rtol=1e-2)
# test mask_safe evaluation
dataset_1.mask_safe = geom.energy_mask(energy_min=1 * u.TeV)
dataset_2.mask_safe = geom.energy_mask(energy_min=1 * u.TeV)
stat = fit.datasets.stat_sum()
assert_allclose(stat, 14823.772744, rtol=1e-5)
region = sky_model.spatial_model.to_region()
initial_counts = dataset_1.counts.copy()
with mpl_plot_check():
dataset_1.plot_residuals(kwargs_spectral=dict(region=region))
# check dataset has not changed
assert initial_counts == dataset_1.counts
# test model evaluation outside image
dataset_1.models[0].spatial_model.lon_0.value = 150
dataset_1.npred()
assert not dataset_1._evaluators["test-model"].contributes
def test_plot_constant_model():
time_range = [Time.now(), Time.now() + 1 * u.d]
constant_model = ConstantTemporalModel(const=1)
with mpl_plot_check():
constant_model.plot(time_range)
def test_plot_gamma_rate(self):
with mpl_plot_check():
self.obs_summary.plot_gamma_rate()
def test_lightcurve_plot(lc):
with mpl_plot_check():
lc.plot()
def test_plot_background(self):
with mpl_plot_check():
self.obs_summary.plot_background_vs_livetime()
def test_plot_excess(self):
with mpl_plot_check():
self.obs_summary.plot_excess_vs_livetime()
def test_plot_significance(self):
with mpl_plot_check():
self.obs_summary.plot_significance_vs_livetime()
def test_plot_fit(self):
dataset = self.dataset.copy()
dataset.models = SkyModel(spectral_model=PowerLawSpectralModel())
with mpl_plot_check():
dataset.plot_fit()
def test_peek(self, psf):
with mpl_plot_check():
psf.peek()
def test_plot_off_regions(self):
from gammapy.visualization import plot_spectrum_datasets_off_regions
with mpl_plot_check():
plot_spectrum_datasets_off_regions([self.dataset])
def test_psf_3d_plot_vs_rad(psf_3d):
with mpl_plot_check():
psf_3d.plot_psf_vs_rad()
def test_plot_likelihood(self, flux_points_likelihood):
with mpl_plot_check():
flux_points_likelihood.plot_ts_profiles()
def test_psf_3d_plot_containment(psf_3d):
with mpl_plot_check():
psf_3d.plot_containment_radius()
def test_plot_matrix(self):
with mpl_plot_check():
self.edisp.plot_matrix()
def test_psf_3d_peek(psf_3d):
with mpl_plot_check():
psf_3d.peek()
def test_peek(self):
with mpl_plot_check():
self.edisp.peek()
def test_plot_allsky():
axis = MapAxis([0, 1], node_type="edges")
m = WcsNDMap.create(binsz=10 * u.deg, axes=[axis])
with mpl_plot_check():
m.plot()
def test_plot_grid():
axis = MapAxis([0, 1, 2], node_type="edges")
m = WcsNDMap.create(binsz=0.1 * u.deg, width=1 * u.deg, axes=[axis])
with mpl_plot_check():
m.plot_grid()
def test_plot_grid(geom_true):
spatial_model = MyCustomGaussianModel(frame="galactic")
with mpl_plot_check():
spatial_model.plot_grid(geom=geom_true)
def test_plot_nan():
m = Map.create(width=10, binsz=1)
m.data += np.nan
with mpl_plot_check():
m.plot(add_cbar=False)
def test_fp_dataset_plot_fit(fit):
fp_dataset = fit.datasets[0]
with mpl_plot_check():
fp_dataset.plot_fit(kwargs_residuals=dict(method="diff/model"))
def test_plot_zenith(self):
with mpl_plot_check():
self.table_summary.plot_zenith_distribution()
def test_fp_dataset_plot_fit(dataset):
with mpl_plot_check():
dataset.plot_fit(kwargs_residuals=dict(method="diff/model"))
