gistfile1.txt

_________________________________________________________________ test_map_dataset_fits_io __________________________________________________________________

tmp_path = PosixPath('/private/var/folders/t_/_mywtcj146lbk2c99bnxw7z40000gp/T/pytest-of-deil/pytest-78/test_map_dataset_fits_io0')
sky_model = SkyModel(spatial_model=<gammapy.modeling.models.spatial.GaussianSpatialModel object at 0x11329ad30>, spectral_model=<gammapy.modeling.models.spectral.PowerLawSpectralModel object at 0x11329ac50>)
geom = WcsGeom

	axes       : ['lon', 'lat', 'energy']
	shape      : (100, 100, 2)
	ndim       : 3
	coordsys   : CEL
	projection : CAR
	center     : 266.4 deg, -28.9 deg
	width      : 2.0 deg x 2.0 deg

geom_etrue = WcsGeom

	axes       : ['lon', 'lat', 'energy']
	shape      : (100, 100, 3)
	ndim       : 3
	coordsys   : CEL
	projection : CAR
	center     : 266.4 deg, -28.9 deg
	width      : 2.0 deg x 2.0 deg


    @requires_data()
    def test_map_dataset_fits_io(tmp_path, sky_model, geom, geom_etrue):
        dataset = get_map_dataset(sky_model, geom, geom_etrue)
        dataset.counts = dataset.npred()
        dataset.mask_safe = dataset.mask_fit
        gti = GTI.create([0 * u.s], [1 * u.h], reference_time="2010-01-01T00:00:00")
        dataset.gti = gti
    
        hdulist = dataset.to_hdulist()
        actual = [hdu.name for hdu in hdulist]
    
        desired = [
            "PRIMARY",
            "COUNTS",
            "COUNTS_BANDS",
            "EXPOSURE",
            "EXPOSURE_BANDS",
            "BACKGROUND",
            "BACKGROUND_BANDS",
            "EDISP",
            "EDISP_BANDS",
            "EDISP_EXPOSURE",
            "EDISP_EXPOSURE_BANDS",
            "PSF",
            "PSF_BANDS",
            "PSF_EXPOSURE",
            "PSF_EXPOSURE_BANDS",
            "MASK_SAFE",
            "MASK_SAFE_BANDS",
            "MASK_FIT",
            "MASK_FIT_BANDS",
            "GTI",
        ]
    
        assert actual == desired
    
        dataset.write(tmp_path / "test.fits")
    
        dataset_new = MapDataset.read(tmp_path / "test.fits")
>       assert len(dataset_new.models) == 0
E       TypeError: object of type 'NoneType' has no len()

gammapy/cube/tests/test_fit.py:257: TypeError
_________________________________________________________________ test_datasets_io_no_model _________________________________________________________________

tmpdir = local('/private/var/folders/t_/_mywtcj146lbk2c99bnxw7z40000gp/T/pytest-of-deil/pytest-78/test_datasets_io_no_model0')

    def test_datasets_io_no_model(tmpdir):
        axis = MapAxis.from_energy_bounds("1 TeV", "10 TeV", nbin=2)
        geom = WcsGeom.create(npix=(5, 5), axes=[axis])
        dataset_1 = MapDataset.create(geom, name="1")
        dataset_2 = MapDataset.create(geom, name="2")
    
        datasets = Datasets([dataset_1, dataset_2])
    
>       datasets.to_yaml(path=tmpdir, prefix="test")

gammapy/cube/tests/test_fit.py:677: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
gammapy/modeling/datasets.py:184: in to_yaml
    datasets_dict, components_dict = datasets_to_dict(self, path, prefix, overwrite)
gammapy/modeling/serialize.py:127: in datasets_to_dict
    datasets_dictlist.append(dataset.to_dict(filename=filename))
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <gammapy.cube.fit.MapDataset object at 0x1146a2128>
filename = PosixPath('/private/var/folders/t_/_mywtcj146lbk2c99bnxw7z40000gp/T/pytest-of-deil/pytest-78/test_datasets_io_no_model0/test_data_1.fits')

    def to_dict(self, filename=""):
        """Convert to dict for YAML serialization."""
        return {
            "name": self.name,
            "type": self.tag,
            "likelihood": self.likelihood_type,
>           "models": [_.name for _ in self.models],
            "background": self.background_model.name,
            "filename": str(filename),
        }
E       TypeError: 'NoneType' object is not iterable

gammapy/cube/fit.py:814: TypeError
======================================================== 2 failed, 1 passed, 50 deselected in 3.93s =========================================================