def test_analysis_1d_stacked():
cfg = """
datasets:
geom:
axes:
energy_true: {min: 0.03 TeV, max: 100 TeV, nbins: 50}
background:
method: reflected
"""
config = get_example_config("1d")
analysis = Analysis(config)
analysis.update_config(cfg)
analysis.config.datasets.stack = True
analysis.get_observations()
analysis.get_datasets()
analysis.read_models(MODEL_FILE_1D)
analysis.run_fit()
assert len(analysis.datasets) == 1
assert_allclose(analysis.datasets["stacked"].counts.data.sum(), 184)
pars = analysis.fit_result.parameters
assert_allclose(pars["index"].value, 2.76913, rtol=1e-2)
assert_allclose(pars["amplitude"].value, 5.496388e-11, rtol=1e-2)
def test_analysis_1d():
cfg = """
observations:
datastore: $GAMMAPY_DATA/hess-dl3-dr1
obs_ids: [23523, 23526]
obs_time: {
start: [J2004.92654346, J2004.92658453, J2004.92663655],
stop: [J2004.92658453, J2004.92663655, J2004.92670773]
}
datasets:
type: 1d
background:
method: reflected
geom:
axes:
energy_true: {min: 0.01 TeV, max: 300 TeV, nbins: 109}
on_region: {frame: icrs, lon: 83.633 deg, lat: 22.014 deg, radius: 0.11 deg}
safe_mask:
methods: [aeff-default, edisp-bias]
parameters: {bias_percent: 10.0}
containment_correction: false
flux_points:
energy: {min: 1 TeV, max: 50 TeV, nbins: 4}
light_curve:
energy_edges: {min: 1 TeV, max: 50 TeV, nbins: 1}
time_intervals: {
start: [J2004.92654346, J2004.92658453, J2004.92663655],
stop: [J2004.92658453, J2004.92663655, J2004.92670773]
}
"""
config = get_example_config("1d")
analysis = Analysis(config)
analysis.update_config(cfg)
analysis.get_observations()
analysis.get_datasets()
analysis.read_models(MODEL_FILE_1D)
analysis.run_fit()
analysis.get_flux_points()
analysis.get_light_curve()
assert len(analysis.datasets) == 3
table = analysis.flux_points.data.to_table(sed_type="dnde")
assert len(table) == 4
dnde = table["dnde"].quantity
assert dnde.unit == "cm-2 s-1 TeV-1"
assert_allclose(dnde[0].value, 8.116854e-12, rtol=1e-2)
assert_allclose(dnde[2].value, 3.444475e-14, rtol=1e-2)
axis = analysis.light_curve.geom.axes["time"]
assert axis.nbin == 3
assert_allclose(axis.time_min.mjd, [53343.92, 53343.935, 53343.954])
flux = analysis.light_curve.flux.data[:, :, 0, 0]
assert_allclose(flux, [[1.688954e-11], [2.347870e-11], [1.604152e-11]],
rtol=1e-4)
def main(config_path, models_path, output, reference):
config = AnalysisConfig.read(config_path)
analysis = Analysis(config)
log.info(config)
analysis.get_observations()
log.info(analysis)
log.info(dir(analysis))
log.info(analysis.datasets)
log.info(analysis.datasets[0].counts)
analysis.get_datasets()
analysis.read_models(models_path)
# stacked fit and flux estimation
analysis.run_fit()
analysis.get_flux_points()
# Plot flux points
ax_sed, ax_residuals = analysis.flux_points.plot_fit()
if reference:
plot_kwargs = {
"energy_range": [
analysis.config.flux_points.energy.min,
analysis.config.flux_points.energy.max,
],
"energy_power": 2,
"flux_unit": "erg-1 cm-2 s-1",
}
create_crab_spectral_model(reference).plot(
**plot_kwargs, ax=ax_sed, label="Crab reference"
)
ax_sed.legend()
ax_sed.set_ylim(1e-12, 1e-9)
base_out = Path(output)
ax_sed.get_figure().savefig(base_out.with_suffix(".pdf").as_posix())
plt.clf()
analysis.models.write(base_out.with_suffix(".yaml").as_posix(), overwrite=True)
analysis.flux_points.write(
base_out.with_suffix(".fits").as_posix(), overwrite=True
)
ax_excess = analysis.datasets["stacked"].plot_excess()
ax_excess.get_figure().savefig(base_out.with_suffix(".excess.pdf").as_posix())
plt.clf()
config.datasets.stack = False
analysis.get_observations()
analysis.get_datasets()
analysis.read_models(models_path)
lc_maker_low = LightCurveEstimator(
energy_edges=[.2, 5] * u.TeV, source=config.flux_points.source, reoptimize=False
)
lc_low = lc_maker_low.run(analysis.datasets)
ax_lc = lc_low.plot(marker="o", label="1D")
ax_lc.get_figure().savefig(base_out.with_suffix(".lc.pdf").as_posix())
plt.clf()
def test_usage_errors():
config = get_example_config("1d")
analysis = Analysis(config)
with pytest.raises(RuntimeError):
analysis.get_datasets()
with pytest.raises(RuntimeError):
analysis.read_models(MODEL_FILE)
with pytest.raises(RuntimeError):
analysis.run_fit()
with pytest.raises(RuntimeError):
analysis.get_flux_points()
def analysis_3d_data_reduction(target):
log.info(f"analysis_3d_data_reduction: {target}")
opts = yaml.safe_load(open("targets.yaml"))[target]
txt = Path("config_template.yaml").read_text()
txt = txt.format_map(opts)
config = AnalysisConfig.from_yaml(txt)
analysis = Analysis(config)
analysis.get_observations()
log.info("Running data reduction")
analysis.get_datasets()
# TODO: write datasets and separate fitting to next function
# Not implemented in Gammapy yet, coming very soon.
log.info("Running fit ...")
analysis.read_models(f"{target}/model_3d.yaml")
logging.info(analysis.models)
analysis.run_fit()
logging.info(analysis.fit_result.parameters.to_table())
path = f"{target}/{target}_3d_bestfit.rst"
log.info(f"Writing {path}")
analysis.fit_result.parameters.to_table().write(path,
format="ascii.rst",
overwrite=True)
# analysis.get_flux_points(source=f"{target}")
# path = f"{target}/{target}_3d_fluxpoints.fits"
# log.info(f"Writing {path}")
# analysis.flux_points.write(path, overwrite=True)
analysis.get_flux_points(source=f"{target}")
path = f"{target}/{target}_3d_fluxpoints.ecsv"
log.info(f"Writing {path}")
keys = [
"e_ref", "e_min", "e_max", "dnde", "dnde_errp", "dnde_errn", "is_ul"
]
analysis.flux_points.data.table_formatted[keys].write(path,
format="ascii.ecsv",
overwrite=True)
return analysis # will write to disk when possible
def test_usage_errors():
config = get_example_config("1d")
analysis = Analysis(config)
with pytest.raises(RuntimeError):
analysis.get_datasets()
with pytest.raises(RuntimeError):
analysis.read_datasets()
with pytest.raises(RuntimeError):
analysis.write_datasets()
with pytest.raises(TypeError):
analysis.read_models()
with pytest.raises(RuntimeError):
analysis.write_models()
with pytest.raises(RuntimeError):
analysis.run_fit()
with pytest.raises(RuntimeError):
analysis.get_flux_points()
with pytest.raises(ValidationError):
analysis.config.datasets.type = "None"
def test_analysis_3d():
config = get_example_config("3d")
analysis = Analysis(config)
analysis.get_observations()
analysis.get_datasets()
analysis.read_models(MODEL_FILE)
analysis.datasets["stacked"].background_model.spectral_model.tilt.frozen = False
analysis.run_fit()
analysis.get_flux_points()
assert len(analysis.datasets) == 1
assert len(analysis.fit_result.parameters) == 8
res = analysis.fit_result.parameters
assert res["amplitude"].unit == "cm-2 s-1 TeV-1"
assert len(analysis.flux_points.data.table) == 2
dnde = analysis.flux_points.data.table["dnde"].quantity
assert_allclose(dnde[0].value, 1.376879e-11, rtol=1e-2)
assert_allclose(dnde[-1].value, 2.691466e-13, rtol=1e-2)
assert_allclose(res["index"].value, 3.097613, rtol=1e-2)
assert_allclose(res["tilt"].value, -0.207792, rtol=1e-2)
def test_analysis_1d_stacked_no_fit_range():
cfg = """
observations:
datastore: $GAMMAPY_DATA/hess-dl3-dr1
obs_cone: {frame: icrs, lon: 83.633 deg, lat: 22.014 deg, radius: 5 deg}
obs_ids: [23592, 23559]
datasets:
type: 1d
stack: false
geom:
axes:
energy: {min: 0.01 TeV, max: 100 TeV, nbins: 73}
energy_true: {min: 0.03 TeV, max: 100 TeV, nbins: 50}
on_region: {frame: icrs, lon: 83.633 deg, lat: 22.014 deg, radius: 0.1 deg}
containment_correction: true
background:
method: reflected
"""
config = AnalysisConfig.from_yaml(cfg)
analysis = Analysis(config)
analysis.update_config(cfg)
analysis.config.datasets.stack = True
analysis.get_observations()
analysis.get_datasets()
analysis.read_models(MODEL_FILE_1D)
analysis.run_fit()
with pytest.raises(ValueError):
analysis.get_excess_map()
assert len(analysis.datasets) == 1
assert_allclose(analysis.datasets["stacked"].counts.data.sum(), 184)
pars = analysis.models.parameters
assert_allclose(analysis.datasets[0].mask_fit.data, True)
assert_allclose(pars["index"].value, 2.76913, rtol=1e-2)
assert_allclose(pars["amplitude"].value, 5.479729e-11, rtol=1e-2)
def test_analysis_1d():
cfg = """
observations:
datastore: $GAMMAPY_DATA/hess-dl3-dr1
obs_ids: [23523, 23526]
datasets:
type: 1d
background:
method: reflected
geom:
axes:
energy_true: {min: 0.01 TeV, max: 300 TeV, nbins: 109}
on_region: {frame: icrs, lon: 83.633 deg, lat: 22.014 deg, radius: 0.11 deg}
safe_mask:
methods: [aeff-default, edisp-bias]
parameters: {bias_percent: 10.0}
containment_correction: false
flux_points:
energy: {min: 1 TeV, max: 50 TeV, nbins: 4}
"""
config = get_example_config("1d")
analysis = Analysis(config)
analysis.update_config(cfg)
analysis.get_observations()
analysis.get_datasets()
analysis.read_models(MODEL_FILE_1D)
analysis.run_fit()
analysis.get_flux_points()
assert len(analysis.datasets) == 2
assert len(analysis.flux_points.data.table) == 4
dnde = analysis.flux_points.data.table["dnde"].quantity
assert dnde.unit == "cm-2 s-1 TeV-1"
assert_allclose(dnde[0].value, 8.116854e-12, rtol=1e-2)
assert_allclose(dnde[2].value, 3.547128e-14, rtol=1e-2)
