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{"receipt_id":"agent1-3","seq":3,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-c825aca0059c4439a7cd8f3ad1ab5d2c/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-c825aca0059c4439a7cd8f3ad1ab5d2c/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-3.xml","path":null,"exit_code":1,"stdout_tail":"15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd5e92380>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd5fb4eb0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-2/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d783d0>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d78850>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n------------ generated xml file: /opt/receipts/reports/agent1-3.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - ValueE...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.37s =========================\n","stderr_tail":"","stdout_sha256":"8b73f79b65bf011d00c41e5314c3997beae099c1ee55113af48e69cc1be36c95","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-3.log","tree_digest":"dc9c1539a6f71da0ffb683f95c6bbf71a3eb92cd3c4f353ec0db03529ab66fe4","tree_download_s":3.745631666854024,"started_at":"2026-10-03T19:29:00.846379Z","duration_s":6.06208,"timed_out":false,"image_before":"2c00c50a-b753-4f1a-8f20-fd7534a55ef3","image_after":"3d2b57c7-0d58-4b06-bbfd-2b14fc01449b","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...] total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d783d0>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d78850>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-4","seq":4,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-ee74f66e75ea4e3bae96180977302ce7/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-ee74f66e75ea4e3bae96180977302ce7/incoming/97c5d19f4cb753fc9ed9c8f07468f3e2cfa50c2f799f6d5e73c924917177e78d /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"97c5d19f4cb753fc9ed9c8f07468f3e2cfa50c2f799f6d5e73c924917177e78d","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-4.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:29:26.480669Z","duration_s":0.004822,"timed_out":false,"image_before":"3d2b57c7-0d58-4b06-bbfd-2b14fc01449b","image_after":"25312ca0-1beb-4e06-8b79-89c5585c5a13","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-5","seq":5,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-268f24c0be394cd196707748e04ebdcf/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-268f24c0be394cd196707748e04ebdcf/incoming/ea4d31e05bfe9a6449d74b876789c1dcd5c42926300d5c3198fda6f681cd98f2 /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"ea4d31e05bfe9a6449d74b876789c1dcd5c42926300d5c3198fda6f681cd98f2","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-5.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:29:31.354400Z","duration_s":0.005131,"timed_out":false,"image_before":"25312ca0-1beb-4e06-8b79-89c5585c5a13","image_after":"04d55761-c41a-45fc-ab37-b3e757a59e0c","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-6","seq":6,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-60234242ddae4b7c8189b4bf10edabe0/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-60234242ddae4b7c8189b4bf10edabe0/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-6.xml","path":null,"exit_code":1,"stdout_tail":"e versions: \nNumpy: 2.2.6\nScipy: 1.15.3\nMatplotlib: 3.10.8\nh5py: not available\nPandas: not available\ncython: not available\niminuit: 2.32.0\nmatplotlib: 3.10.8\nastropy: 6.1.7\nregions: 0.10\nhealpy: not available\nsherpa: not available\ngammapy: 1.3.dev554+gc9521d576\nnaima: not available\nray: not available\n\nUsing Astropy options: remote_data: none.\n\nrootdir: /gammapy\nconfigfile: pyproject.toml (WARNING: ignoring pytest config in setup.cfg!)\nplugins: hypothesis-6.151.9, arraydiff-0.6.1, astropy-0.11.0, astropy-header-0.2.2, cov-7.0.0, doctestplus-1.7.1, filter-subpackage-0.2.0, mock-3.15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd675ef80>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd686afe0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-3/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:439: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:415: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:398: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.datasets.evaluator.MapEvaluator object at 0x7fffd5ffbe80>\n\n    @lazyproperty\n    def _edisp_diagonal(self):\n        if self.edisp is None:\n            # Use energy axis from exposure (or geom) assuming same binning\n>           energy_axis = self.exposure.axes[\"energy\"]\nE           AttributeError: 'RegionNDMap' object has no attribute 'axes'\n\ngammapy/datasets/evaluator.py:246: AttributeError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n------------ generated xml file: /opt/receipts/reports/agent1-6.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - Attrib...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.39s =========================\n","stderr_tail":"","stdout_sha256":"e19e947e03c1c0a3476e0ab151252912efd50ff76f46d195f99fa2c23b0f7eb4","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-6.log","tree_digest":"d75eb9193eb5f998ed159e379f83524905a955772e4060a3dad212d33b3ead33","tree_download_s":4.069231041939929,"started_at":"2026-10-03T19:29:34.538160Z","duration_s":6.095521,"timed_out":false,"image_before":"04d55761-c41a-45fc-ab37-b3e757a59e0c","image_after":"a0382a1a-804d-46bc-8eba-b35a240f9c96","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...]ate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:439: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:415: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:398: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.datasets.evaluator.MapEvaluator object at 0x7fffd5ffbe80>\n\n    @lazyproperty\n    def _edisp_diagonal(self):\n        if self.edisp is None:\n            # Use energy axis from exposure (or geom) assuming same binning\n>           energy_axis = self.exposure.axes[\"energy\"]\nE           AttributeError: 'RegionNDMap' object has no attribute 'axes'\n\ngammapy/datasets/evaluator.py:246: AttributeError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-7","seq":7,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-ec0167af94484d42a2d46050f5b0ed68/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-ec0167af94484d42a2d46050f5b0ed68/incoming/2a0ad0eb34ca69980124bdb6484f9153ee2a58e5ff0351b705d15be7eae6cdee /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"2a0ad0eb34ca69980124bdb6484f9153ee2a58e5ff0351b705d15be7eae6cdee","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-7.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:29:49.985279Z","duration_s":0.004871,"timed_out":false,"image_before":"a0382a1a-804d-46bc-8eba-b35a240f9c96","image_after":"fb701103-ce29-44ae-8ac8-055a8a2d6506","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-8","seq":8,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-a7ad59353dc04aec91b7d96ca99f8a22/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-a7ad59353dc04aec91b7d96ca99f8a22/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-8.xml","path":null,"exit_code":1,"stdout_tail":"32.0\nmatplotlib: 3.10.8\nastropy: 6.1.7\nregions: 0.10\nhealpy: not available\nsherpa: not available\ngammapy: 1.3.dev554+gc9521d576\nnaima: not available\nray: not available\n\nUsing Astropy options: remote_data: none.\n\nrootdir: /gammapy\nconfigfile: pyproject.toml (WARNING: ignoring pytest config in setup.cfg!)\nplugins: hypothesis-6.151.9, arraydiff-0.6.1, astropy-0.11.0, astropy-header-0.2.2, cov-7.0.0, doctestplus-1.7.1, filter-subpackage-0.2.0, mock-3.15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd7169180>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd6775ea0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-4/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:439: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:415: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:398: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:246: in _edisp_diagonal\n    energy_axis = self.exposure.geom.axes[\"energy\"]\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd67987c0>, idx = 'energy'\n\n    def __getitem__(self, idx):\n        if isinstance(idx, int):\n            return self._axes[idx]\n        elif isinstance(idx, str):\n            for ax in self._axes:\n                if ax.name == idx:\n                    return ax\n>           raise KeyError(f\"No axes: {idx!r}\")\nE           KeyError: \"No axes: 'energy'\"\n\ngammapy/maps/axes.py:1815: KeyError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n------------ generated xml file: /opt/receipts/reports/agent1-8.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - KeyErr...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.41s =========================\n","stderr_tail":"","stdout_sha256":"ec61524a994cd0d48a16ea1b47ee0395c12a847f1c190659cda1118b8c5c2284","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-8.log","tree_digest":"27bf14b295d97f863beccb013d520d5037cc721c1ab97a16775e8c47ec27e82c","tree_download_s":3.9250447920057923,"started_at":"2026-10-03T19:29:52.719578Z","duration_s":6.099367,"timed_out":false,"image_before":"fb701103-ce29-44ae-8ac8-055a8a2d6506","image_after":"5ef040bd-076b-4a04-95dc-201c930a9f51","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...]sets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:439: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:415: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:398: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:246: in _edisp_diagonal\n    energy_axis = self.exposure.geom.axes[\"energy\"]\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd67987c0>, idx = 'energy'\n\n    def __getitem__(self, idx):\n        if isinstance(idx, int):\n            return self._axes[idx]\n        elif isinstance(idx, str):\n            for ax in self._axes:\n                if ax.name == idx:\n                    return ax\n>           raise KeyError(f\"No axes: {idx!r}\")\nE           KeyError: \"No axes: 'energy'\"\n\ngammapy/maps/axes.py:1815: KeyError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-9","seq":9,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-8c10f0582b374acea442ff54d4168c9e/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-8c10f0582b374acea442ff54d4168c9e/incoming/83e1d85f8c782d786ab083f449fa3854f1ff43d00f23ebef72c2ab148d5eb312 /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"83e1d85f8c782d786ab083f449fa3854f1ff43d00f23ebef72c2ab148d5eb312","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-9.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:30:08.193466Z","duration_s":0.005037,"timed_out":false,"image_before":"5ef040bd-076b-4a04-95dc-201c930a9f51","image_after":"34356368-d4f4-46bb-90d0-284a9bc1b349","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-10","seq":10,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-c1c11539c3ed4c23b3c5aa8631a450dd/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-c1c11539c3ed4c23b3c5aa8631a450dd/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-10.xml","path":null,"exit_code":1,"stdout_tail":"inuit: 2.32.0\nmatplotlib: 3.10.8\nastropy: 6.1.7\nregions: 0.10\nhealpy: not available\nsherpa: not available\ngammapy: 1.3.dev554+gc9521d576\nnaima: not available\nray: not available\n\nUsing Astropy options: remote_data: none.\n\nrootdir: /gammapy\nconfigfile: pyproject.toml (WARNING: ignoring pytest config in setup.cfg!)\nplugins: hypothesis-6.151.9, arraydiff-0.6.1, astropy-0.11.0, astropy-header-0.2.2, cov-7.0.0, doctestplus-1.7.1, filter-subpackage-0.2.0, mock-3.15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd5eb8af0>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd5ebabf0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-5/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:439: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:415: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:398: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:246: in _edisp_diagonal\n    energy_axis = self.geom.axes[\"energy\"]\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd64941f0>, idx = 'energy'\n\n    def __getitem__(self, idx):\n        if isinstance(idx, int):\n            return self._axes[idx]\n        elif isinstance(idx, str):\n            for ax in self._axes:\n                if ax.name == idx:\n                    return ax\n>           raise KeyError(f\"No axes: {idx!r}\")\nE           KeyError: \"No axes: 'energy'\"\n\ngammapy/maps/axes.py:1815: KeyError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n----------- generated xml file: /opt/receipts/reports/agent1-10.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - KeyErr...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.42s =========================\n","stderr_tail":"","stdout_sha256":"179877226ee6af23e97be51a9611fe3e41863d072b5eb3fc4babb5013d4ba29f","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-10.log","tree_digest":"03e279c5d373196002790f4710f122779b520974665bd545bbdd67f923f082bf","tree_download_s":4.026094792177901,"started_at":"2026-10-03T19:30:11.861715Z","duration_s":6.1496580000000005,"timed_out":false,"image_before":"34356368-d4f4-46bb-90d0-284a9bc1b349","image_after":"df121951-f53a-4d0a-a026-959d83fedefb","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...]mize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:439: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:415: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:398: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:246: in _edisp_diagonal\n    energy_axis = self.geom.axes[\"energy\"]\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd64941f0>, idx = 'energy'\n\n    def __getitem__(self, idx):\n        if isinstance(idx, int):\n            return self._axes[idx]\n        elif isinstance(idx, str):\n            for ax in self._axes:\n                if ax.name == idx:\n                    return ax\n>           raise KeyError(f\"No axes: {idx!r}\")\nE           KeyError: \"No axes: 'energy'\"\n\ngammapy/maps/axes.py:1815: KeyError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-11","seq":11,"branch_id":"agent1","kind":"command","cmd":"grep -n \"def energy_axis\" gammapy/datasets/evaluator.py","path":null,"exit_code":1,"stdout_tail":"","stderr_tail":"","stdout_sha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-11.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:30:28.356591Z","duration_s":0.003096,"timed_out":false,"image_before":"df121951-f53a-4d0a-a026-959d83fedefb","image_after":"c401a469-a26b-42be-b043-dca2135db072","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-12","seq":12,"branch_id":"agent1","kind":"command","cmd":"grep -n \"energy_axis\" gammapy/datasets/evaluator.py","path":null,"exit_code":0,"stdout_tail":"120:            energy_axis = self.edisp.axes[\"energy\"].copy(name=\"energy\")\n122:            energy_axis = self.geom.axes[\"energy_true\"].copy(name=\"energy\")\n123:        geom = self.geom.to_image().to_cube(axes=[energy_axis])\n196:            energy_axis = geom.axes[\"energy\"]\n198:                position=self.position, energy_axis=energy_axis\n246:            energy_axis = self.geom.axes[\"energy\"]\n248:                energy_axis_true=energy_axis,\n249:                energy_axis=energy_axis,\n252:            energy_axis_true=self.edisp.axes[\"energy_true\"],\n253:            energy_axis=self.edisp.axes[\"energy\"],\n","stderr_tail":"","stdout_sha256":"1901faebe52942c1816c0cc3101e701e32ec4a04241b4de582541d4078542c12","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-12.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:30:32.162376Z","duration_s":0.0031720000000000003,"timed_out":false,"image_before":"c401a469-a26b-42be-b043-dca2135db072","image_after":"872570e7-6913-4235-ae9e-50d2ae3847ae","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-13","seq":13,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-278a447b43a44adc9342afd84b0577d0/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-278a447b43a44adc9342afd84b0577d0/incoming/44a81146437e9c64e673b3b7d586a68f659484f70934fc1e744244c6e3ab585a /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"44a81146437e9c64e673b3b7d586a68f659484f70934fc1e744244c6e3ab585a","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-13.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:30:37.082745Z","duration_s":0.004717,"timed_out":false,"image_before":"872570e7-6913-4235-ae9e-50d2ae3847ae","image_after":"269ab002-f3f2-45d3-9de5-a1ea1f065bd6","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-14","seq":14,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-954929b926f84940bbd03832ff2f6c17/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-954929b926f84940bbd03832ff2f6c17/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-14.xml","path":null,"exit_code":1,"stdout_tail":"1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd65ab190>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd6596020>)\ntmpdir = local('/tmp/pytest-of-root/pytest-6/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:442: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:418: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:401: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:250: in _edisp_diagonal\n    return EDispKernel.from_diagonal_response(\ngammapy/irf/edisp/kernel.py:205: in from_diagonal_response\n    return cls(axes=[energy_axis_true, energy_axis], data=data.value)\ngammapy/irf/core.py:76: in __init__\n    axes = MapAxes(axes)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd5d859f0>\naxes = [MapAxis\n\n\tname       : energy_true\n\tunit       : 'TeV'     \n\tnbins      : 20        \n\tnode type  : edges     \n\tedges ...   : 20        \n\tnode type  : edges     \n\tedges min  : 3.2e-01 TeV\n\tedges max  : 3.2e+01 TeV\n\tinterp     : log       \n]\nn_spatial_axes = None\n\n    def __init__(self, axes, n_spatial_axes=None):\n        unique_names = []\n    \n        for ax in axes:\n            if ax.name in unique_names:\n>               raise (\n                    ValueError(f\"Axis names must be unique, got: '{ax.name}' twice.\")\n                )\nE               ValueError: Axis names must be unique, got: 'energy_true' twice.\n\ngammapy/maps/axes.py:1487: ValueError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n----------- generated xml file: /opt/receipts/reports/agent1-14.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - ValueE...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.39s =========================\n","stderr_tail":"","stdout_sha256":"57abc9e2d98c58c515bb8cf2e6efca05680aae6485118b26a08c670b6a939d6d","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-14.log","tree_digest":"76c909f408e34c6ccb90dd6665c6e2d6012846703fbb8cfc98dea96275256729","tree_download_s":3.917787041980773,"started_at":"2026-10-03T19:30:40.069012Z","duration_s":6.062577999999999,"timed_out":false,"image_before":"269ab002-f3f2-45d3-9de5-a1ea1f065bd6","image_after":"2b0ca53a-a8ea-4be5-8dbd-bd3f2be77b19","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...]nction()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:442: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:418: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:401: in apply_edisp\n    return apply_edisp(npred, self._edisp_diagonal)\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:250: in _edisp_diagonal\n    return EDispKernel.from_diagonal_response(\ngammapy/irf/edisp/kernel.py:205: in from_diagonal_response\n    return cls(axes=[energy_axis_true, energy_axis], data=data.value)\ngammapy/irf/core.py:76: in __init__\n    axes = MapAxes(axes)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd5d859f0>\naxes = [MapAxis\n\n\tname       : energy_true\n\tunit       : 'TeV'     \n\tnbins      : 20        \n\tnode type  : edges     \n\tedges ...   : 20        \n\tnode type  : edges     \n\tedges min  : 3.2e-01 TeV\n\tedges max  : 3.2e+01 TeV\n\tinterp     : log       \n]\nn_spatial_axes = None\n\n    def __init__(self, axes, n_spatial_axes=None):\n        unique_names = []\n    \n        for ax in axes:\n            if ax.name in unique_names:\n>               raise (\n                    ValueError(f\"Axis names must be unique, got: '{ax.name}' twice.\")\n                )\nE               ValueError: Axis names must be unique, got: 'energy_true' twice.\n\ngammapy/maps/axes.py:1487: ValueError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-15","seq":15,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-a713650cecb3499fab2b51f4305e09bc/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-a713650cecb3499fab2b51f4305e09bc/incoming/05f16410eeaff30be7d20ce8780b54098f18b147b8c8797a244cb160e01e5081 /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"05f16410eeaff30be7d20ce8780b54098f18b147b8c8797a244cb160e01e5081","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-15.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:30:56.676834Z","duration_s":0.005153,"timed_out":false,"image_before":"2b0ca53a-a8ea-4be5-8dbd-bd3f2be77b19","image_after":"c51ab1cc-3bae-4043-8011-4e043024d78d","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-16","seq":16,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-1077caa38817433aa7b6095a00e14939/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-1077caa38817433aa7b6095a00e14939/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-16.xml","path":null,"exit_code":1,"stdout_tail":"15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd76511b0>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd61263e0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-7/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d91390>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d905e0>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n----------- generated xml file: /opt/receipts/reports/agent1-16.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - ValueE...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.39s =========================\n","stderr_tail":"","stdout_sha256":"f2c1c7085766115790333f8505d71ed615fc28916c3cab3c855d3fae5f476836","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-16.log","tree_digest":"f5352fda6d809f07865d194eec8d01b605845f93990ac0164cc4fb344a835187","tree_download_s":3.511550333118066,"started_at":"2026-10-03T19:30:59.977521Z","duration_s":6.158757,"timed_out":false,"image_before":"c51ab1cc-3bae-4043-8011-4e043024d78d","image_after":"c9858832-27c6-4cb0-a0ae-1309ed37dee5","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...] total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d91390>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5d905e0>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-17","seq":17,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-1932d9816d1b4362ac25bb0e07a680bc/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-1932d9816d1b4362ac25bb0e07a680bc/incoming/442495d05c9f2c0abd2e44badcbfce188a061b1ac9ba4199d3c4d340d7b565dc /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"442495d05c9f2c0abd2e44badcbfce188a061b1ac9ba4199d3c4d340d7b565dc","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-17.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:31:17.277504Z","duration_s":0.004866,"timed_out":false,"image_before":"c9858832-27c6-4cb0-a0ae-1309ed37dee5","image_after":"fa427383-1ac2-4c93-82ea-1288bddc70ae","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-18","seq":18,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-17e02a2565864fcc8cfbbe1a347a1c2f/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-17e02a2565864fcc8cfbbe1a347a1c2f/incoming/e65cdaab57bc574437c825e37f5c1f93e3b8d75d3d1cbd65ee0bba068d63e1d9 /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"e65cdaab57bc574437c825e37f5c1f93e3b8d75d3d1cbd65ee0bba068d63e1d9","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-18.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:31:21.925582Z","duration_s":0.004912,"timed_out":false,"image_before":"fa427383-1ac2-4c93-82ea-1288bddc70ae","image_after":"ced9646b-bbe3-472f-8c66-e3f0a8f111a4","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-19","seq":19,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-9ff978091a8e4c2190c6d73f195fa0b9/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-9ff978091a8e4c2190c6d73f195fa0b9/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-19.xml","path":null,"exit_code":1,"stdout_tail":"15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd7c79de0>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd612b580>)\ntmpdir = local('/tmp/pytest-of-root/pytest-8/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd6104370>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd61061a0>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n----------- generated xml file: /opt/receipts/reports/agent1-19.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - ValueE...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.42s =========================\n","stderr_tail":"","stdout_sha256":"74ce68303b5e64c38a5f85c3636d72a99ead525cfae8f970d3c33cb6077d70fe","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-19.log","tree_digest":"dc9c1539a6f71da0ffb683f95c6bbf71a3eb92cd3c4f353ec0db03529ab66fe4","tree_download_s":3.908596291905269,"started_at":"2026-10-03T19:31:25.107554Z","duration_s":6.149025,"timed_out":false,"image_before":"ced9646b-bbe3-472f-8c66-e3f0a8f111a4","image_after":"cf4d034d-5386-4d6f-b4b2-f71c29a0bcb5","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...] total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd6104370>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd61061a0>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-20","seq":20,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-217d0814ebfd4e9eacf85312fc77e51f/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-217d0814ebfd4e9eacf85312fc77e51f/incoming/d3343c39bebbde90f39dba52bc0ae99974fe6bdf8d61fb8eb2ba4112797103a3 /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"d3343c39bebbde90f39dba52bc0ae99974fe6bdf8d61fb8eb2ba4112797103a3","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-20.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:31:45.355189Z","duration_s":0.004744,"timed_out":false,"image_before":"cf4d034d-5386-4d6f-b4b2-f71c29a0bcb5","image_after":"bf75302b-22f5-4b51-8a8c-cb1129cf4fde","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-21","seq":21,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-6107b75b45df4eb2a3268300fe3374ad/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-6107b75b45df4eb2a3268300fe3374ad/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-21.xml","path":null,"exit_code":1,"stdout_tail":"\nGammapy test data availability:\ngammapy-data ... no\nGammapy environment variables:\nGAMMAPY_DATA = not set\nSetting matplotlib backend to \"agg\" for the tests.\n============================= test session starts ==============================\nplatform linux -- Python 3.10.19, pytest-9.0.2, pluggy-1.6.0 -- /usr/local/bin/python\nhypothesis profile 'default'\n\nRunning tests with gammapy version 1.3.dev554+gc9521d576.\nRunning tests in gammapy/estimators/points/tests/test_sed.py::test_run_no_edip.\n\nDate: 2026-10-03T19:31:54\n\nPlatform: Linux-7.0.6-x86_64-with-glibc2.41\n\nExecutable: /usr/local/bin/python\n\nFull Python Version: \n3.10.19 (main, Dec 30 2025, 00:42:16) [GCC 14.2.0]\n\nencodings: sys: utf-8, locale: UTF-8, filesystem: utf-8\nbyteorder: little\nfloat info: dig: 15, mant_dig: 15\n\nPackage versions: \nNumpy: 2.2.6\nScipy: 1.15.3\nMatplotlib: 3.10.8\nh5py: not available\nPandas: not available\ncython: not available\niminuit: 2.32.0\nmatplotlib: 3.10.8\nastropy: 6.1.7\nregions: 0.10\nhealpy: not available\nsherpa: not available\ngammapy: 1.3.dev554+gc9521d576\nnaima: not available\nray: not available\n\nUsing Astropy options: remote_data: none.\n\nrootdir: /gammapy\nconfigfile: pyproject.toml (WARNING: ignoring pytest config in setup.cfg!)\nplugins: hypothesis-6.151.9, arraydiff-0.6.1, astropy-0.11.0, astropy-header-0.2.2, cov-7.0.0, doctestplus-1.7.1, filter-subpackage-0.2.0, mock-3.15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd67ac250>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd5ecfe80>)\ntmpdir = local('/tmp/pytest-of-root/pytest-9/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:439: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5ff4c40>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5ff5d20>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError\n----------- generated xml file: /opt/receipts/reports/agent1-21.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - ValueE...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n============================== 1 failed in 1.00s ===============================\n","stderr_tail":"","stdout_sha256":"a60e136eb9941a08c4af8f2fb0157cf37f0c00e284f33cb6a264adbcd2e54c26","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-21.log","tree_digest":"598e585e54e834e430d89a7788630678c4aa24a356ba161106e7fee668e62d94","tree_download_s":3.8269389998167753,"started_at":"2026-10-03T19:31:49.024410Z","duration_s":5.744238,"timed_out":false,"image_before":"bf75302b-22f5-4b51-8a8c-cb1129cf4fde","image_after":"e1adec44-c0e2-4594-96b9-1ed3528fdf8f","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...] total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5ff4c40>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5ff5d20>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-22","seq":22,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-f73d8f067a4c4ba48d9c04b7c7078e0b/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-f73d8f067a4c4ba48d9c04b7c7078e0b/incoming/e65cdaab57bc574437c825e37f5c1f93e3b8d75d3d1cbd65ee0bba068d63e1d9 /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"e65cdaab57bc574437c825e37f5c1f93e3b8d75d3d1cbd65ee0bba068d63e1d9","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-22.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:32:05.241057Z","duration_s":0.005884,"timed_out":false,"image_before":"e1adec44-c0e2-4594-96b9-1ed3528fdf8f","image_after":"b44901e8-8138-42f2-be75-fbfdb936cbb4","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-23","seq":23,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-0e732837788445b28bb28a52d0c95634/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-0e732837788445b28bb28a52d0c95634/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-23.xml","path":null,"exit_code":1,"stdout_tail":"5.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd5f967d0>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd6023af0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-10/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5fb8d90>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5fb88e0>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n----------- generated xml file: /opt/receipts/reports/agent1-23.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - ValueE...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.37s =========================\n","stderr_tail":"","stdout_sha256":"1378438290a0bfcd85112c2578caf36ddd4ab3db3211a4ca5547d5ec20ec836d","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-23.log","tree_digest":"dc9c1539a6f71da0ffb683f95c6bbf71a3eb92cd3c4f353ec0db03529ab66fe4","tree_download_s":3.8467955000232905,"started_at":"2026-10-03T19:32:08.822557Z","duration_s":6.085125,"timed_out":false,"image_before":"b44901e8-8138-42f2-be75-fbfdb936cbb4","image_after":"429eee05-ef75-4787-a265-d9fdd23f0d91","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...] total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:731: in npred_signal\n    npred_total.stack(npred)\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5fb8d90>\nother = <gammapy.maps.region.ndmap.RegionNDMap object at 0x7fffd5fb88e0>\nweights = None, nan_to_num = True\n\n    def stack(self, other, weights=None, nan_to_num=True):\n        \"\"\"Stack other region map into map.\n    \n        Parameters\n        ----------\n        other : `RegionNDMap`\n            Other map to stack.\n        weights : `RegionNDMap`, optional\n            Array to be used as weights. The spatial geometry must be equivalent\n            to `other` and additional axes must be broadcastable.\n            Default is None.\n        nan_to_num: bool, optional\n            Non-finite values are replaced by zero if True.\n            Default is True.\n        \"\"\"\n        data = other.quantity.to_value(self.unit).astype(self.data.dtype)\n    \n        # TODO: re-think stacking of regions. Is making the union reasonable?\n        # self.geom.union(other.geom)\n        if nan_to_num:\n            not_finite = ~np.isfinite(data)\n            if np.any(not_finite):\n                data = data.copy()\n                data[not_finite] = 0\n        if weights is not None:\n            if not other.geom.to_image() == weights.geom.to_image():\n                raise ValueError(\"Incompatible geoms between map and weights\")\n            data = data * weights.data\n    \n>       self.data += data\nE       ValueError: operands could not be broadcast together with shapes (5,1,1) (20,1,1) (5,1,1)\n\ngammapy/maps/region/ndmap.py:708: ValueError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-24","seq":24,"branch_id":"agent1","kind":"diff","cmd":"compute patch in executor staging agent1-5ba3ab0be12c4a7f932d9f240406313f: /opt/homebrew/Cellar/git/2.53.0/bin/git -c core.hooksPath=/dev/null -c core.attributesFile=/dev/null -c diff.external= -c core.quotePath=false add -A && /opt/homebrew/Cellar/git/2.53.0/bin/git -c core.hooksPath=/dev/null -c core.attributesFile=/dev/null -c diff.external= -c core.quotePath=false diff --cached --binary --no-ext-diff --no-textconv --no-renames 4517b03c54bd02dbf548c19cfdbf5a8ece447a4d","path":null,"exit_code":0,"stdout_tail":"diff --git a/gammapy/datasets/evaluator.py b/gammapy/datasets/evaluator.py\nindex 160ad4c43..c274ed418 100644\n--- a/gammapy/datasets/evaluator.py\n+++ b/gammapy/datasets/evaluator.py\n@@ -384,6 +384,9 @@ class MapEvaluator:\n         npred_reco : `~gammapy.maps.Map`\n             Predicted counts in reconstructed energy bins.\n         \"\"\"\n+        # No energy dispersion -> return unchanged\n+        if self.edisp is None:\n+            return npred\n         if self.model.apply_irf[\"edisp\"]:\n             return apply_edisp(npred, self.edisp)\n         else:\n","stderr_tail":"","stdout_sha256":"bd06a7e712c954e081ed3e173adff53a4eeb7c654b5e5633abfd8704538ccd4e","log_path":null,"tree_digest":"dc9c1539a6f71da0ffb683f95c6bbf71a3eb92cd3c4f353ec0db03529ab66fe4","tree_download_s":2.952033167006448,"started_at":"2026-10-03T19:32:37.796613Z","duration_s":0.07556349993683398,"timed_out":false,"image_before":"429eee05-ef75-4787-a265-d9fdd23f0d91","image_after":"429eee05-ef75-4787-a265-d9fdd23f0d91","junit":null,"diff":{"files":[{"path":"gammapy/datasets/evaluator.py","added":3,"deleted":0,"category":"source","status":"modified"}],"patch_sha256":"bd06a7e712c954e081ed3e173adff53a4eeb7c654b5e5633abfd8704538ccd4e","patch_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/artifacts/agent1/agent1-24.patch"},"patch_sha256":"bd06a7e712c954e081ed3e173adff53a4eeb7c654b5e5633abfd8704538ccd4e","dropped_paths":[],"snapshot_sha":"4517b03c54bd02dbf548c19cfdbf5a8ece447a4d"}
{"receipt_id":"agent1-25","seq":25,"branch_id":"agent1","kind":"write","cmd":"/opt/receipts-87b8d3c44f3846fba08b0868fc7a7714/bin/busybox sh -c 'mkdir -p /gammapy/gammapy/datasets && cp /opt/receipts-87b8d3c44f3846fba08b0868fc7a7714/incoming/0ff47cb99e22f9dea30dd563b240b525f7236c6dd6239f539b4b7e605e72b6ae /gammapy/gammapy/datasets/evaluator.py'","path":"gammapy/datasets/evaluator.py","exit_code":0,"stdout_tail":"","stderr_tail":"","stdout_sha256":"0ff47cb99e22f9dea30dd563b240b525f7236c6dd6239f539b4b7e605e72b6ae","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-25.log","tree_digest":null,"tree_download_s":null,"started_at":"2026-10-03T19:33:10.577665Z","duration_s":0.00475,"timed_out":false,"image_before":"429eee05-ef75-4787-a265-d9fdd23f0d91","image_after":"17698b03-7155-4531-9b4b-f5f4d62e1efc","junit":null,"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-26","seq":26,"branch_id":"agent1","kind":"command","cmd":"/opt/receipts-030b5b29128847589a79130b9c8f8aa1/bin/busybox mkdir -p /opt/receipts/reports && python -I /opt/receipts-030b5b29128847589a79130b9c8f8aa1/receipts_pytest.py gammapy/estimators/points/tests/test_sed.py::test_run_no_edip -xvs -o junit_family=xunit1 -p no:cacheprovider -rA --continue-on-collection-errors --junitxml=/opt/receipts/reports/agent1-26.xml","path":null,"exit_code":1,"stdout_tail":"F-8, filesystem: utf-8\nbyteorder: little\nfloat info: dig: 15, mant_dig: 15\n\nPackage versions: \nNumpy: 2.2.6\nScipy: 1.15.3\nMatplotlib: 3.10.8\nh5py: not available\nPandas: not available\ncython: not available\niminuit: 2.32.0\nmatplotlib: 3.10.8\nastropy: 6.1.7\nregions: 0.10\nhealpy: not available\nsherpa: not available\ngammapy: 1.3.dev554+gc9521d576\nnaima: not available\nray: not available\n\nUsing Astropy options: remote_data: none.\n\nrootdir: /gammapy\nconfigfile: pyproject.toml (WARNING: ignoring pytest config in setup.cfg!)\nplugins: hypothesis-6.151.9, arraydiff-0.6.1, astropy-0.11.0, astropy-header-0.2.2, cov-7.0.0, doctestplus-1.7.1, filter-subpackage-0.2.0, mock-3.15.1, remotedata-0.4.1, xdist-3.8.0\ncollecting ... collected 1 item\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip FAILED\n\n=================================== FAILURES ===================================\n_______________________________ test_run_no_edip _______________________________\n\nfpe_pwl = ([<gammapy.datasets.spectrum.SpectrumDatasetOnOff object at 0x7fffd677d2d0>], <gammapy.estimators.points.sed.FluxPointsEstimator object at 0x7fffd5d30dc0>)\ntmpdir = local('/tmp/pytest-of-root/pytest-11/test_run_no_edip0')\n\n    def test_run_no_edip(fpe_pwl, tmpdir):\n        datasets, fpe = fpe_pwl\n    \n        datasets = datasets.copy()\n    \n        datasets[0].models[\"source\"].apply_irf[\"edisp\"] = False\n        fp = fpe.run(datasets)\n        table = fp.to_table()\n        actual = table[\"norm\"].data\n        assert_allclose(actual, [1.081434, 0.91077, 0.922176], rtol=1e-3)\n    \n        datasets[0].edisp = None\n    \n>       fp = fpe.run(datasets)\n\ngammapy/estimators/points/tests/test_sed.py:446: \n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \ngammapy/estimators/points/sed.py:155: in run\n    rows = parallel.run_multiprocessing(\ngammapy/utils/parallel.py:271: in run_multiprocessing\n    return run_loop(\ngammapy/utils/parallel.py:301: in run_loop\n    result = func(*arguments)\ngammapy/estimators/points/sed.py:208: in estimate_flux_point\n    return super().run(datasets=datasets_sliced)\ngammapy/estimators/flux.py:224: in run\n    result.update(super().run(datasets, model.norm))\ngammapy/estimators/parameter.py:336: in run\n    result = self.estimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:446: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:422: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:395: in apply_edisp\n    energy_axis = self.geom.axes[\"energy\"].copy()\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd6223460>, idx = 'energy'\n\n    def __getitem__(self, idx):\n        if isinstance(idx, int):\n            return self._axes[idx]\n        elif isinstance(idx, str):\n            for ax in self._axes:\n                if ax.name == idx:\n                    return ax\n>           raise KeyError(f\"No axes: {idx!r}\")\nE           KeyError: \"No axes: 'energy'\"\n\ngammapy/maps/axes.py:1815: KeyError\n------------------------------ Captured log call -------------------------------\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\nWARNING  gammapy.modeling.iminuit:iminuit.py:117 Reoptimize = False ignored for iminuit backend\n=============================== warnings summary ===============================\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: divide by zero encountered in divide\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\ngammapy/estimators/points/tests/test_sed.py::test_run_no_edip\n  /usr/local/lib/python3.10/site-packages/astropy/units/quantity.py:671: RuntimeWarning: invalid value encountered in multiply\n    result = super().__array_ufunc__(function, method, *arrays, **kwargs)\n\n-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html\n----------- generated xml file: /opt/receipts/reports/agent1-26.xml ------------\n=========================== short test summary info ============================\nFAILED gammapy/estimators/points/tests/test_sed.py::test_run_no_edip - KeyErr...\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n======================== 1 failed, 2 warnings in 1.37s =========================\n","stderr_tail":"","stdout_sha256":"ef76c997b8e1cc7d13771d9ee0ce107541018eaf9f87303b8bb825cc4e310837","log_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/logs/agent1/agent1-26.log","tree_digest":"ed141caf561272cfaca984301d50e9163d8f666f88847602d9d5150a59663814","tree_download_s":3.525722124846652,"started_at":"2026-10-03T19:33:14.001265Z","duration_s":5.9728840000000005,"timed_out":false,"image_before":"17698b03-7155-4531-9b4b-f5f4d62e1efc","image_after":"49a46658-3600-4011-9185-b5a1bd09e397","junit":{"passed":[],"failed":["gammapy/estimators/points/tests/test_sed.py::test_run_no_edip"],"errors":[],"skipped":[],"collection_errors":[],"failure_text":{"gammapy/estimators/points/tests/test_sed.py::test_run_no_edip":"[...]stimate_best_fit(datasets, parameter)\ngammapy/estimators/parameter.py:108: in estimate_best_fit\n    result = self.fit.run(datasets=datasets)\ngammapy/modeling/fit.py:174: in run\n    optimize_result = self.optimize(datasets=datasets)\ngammapy/modeling/fit.py:223: in optimize\n    factors, info, optimizer = compute(\ngammapy/modeling/iminuit.py:79: in optimize_iminuit\n    minuit.migrad(**migrad_opts)\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:852: in migrad\n    fm = _robust_low_level_fit(\n/usr/local/lib/python3.10/site-packages/iminuit/minuit.py:2863: in _robust_low_level_fit\n    fm = migrad(ncall, tolerance)\ngammapy/modeling/iminuit.py:25: in fcn\n    total_stat = self.function()\ngammapy/datasets/core.py:240: in stat_sum\n    stat_sum += dataset.stat_sum()\ngammapy/datasets/map.py:2651: in stat_sum\n    return Dataset.stat_sum(self)\ngammapy/datasets/core.py:72: in stat_sum\n    stat = self.stat_array()\ngammapy/datasets/map.py:2412: in stat_array\n    mu_sig = self.npred_signal().data\ngammapy/datasets/map.py:729: in npred_signal\n    npred = evaluator.compute_npred()\ngammapy/datasets/evaluator.py:446: in compute_npred\n    return self._compute_npred\n/usr/local/lib/python3.10/site-packages/astropy/utils/decorators.py:836: in __get__\n    val = self.fget(obj)\ngammapy/datasets/evaluator.py:422: in _compute_npred\n    values = method(self._computation_cache)\ngammapy/datasets/evaluator.py:395: in apply_edisp\n    energy_axis = self.geom.axes[\"energy\"].copy()\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \n\nself = <gammapy.maps.axes.MapAxes object at 0x7fffd6223460>, idx = 'energy'\n\n    def __getitem__(self, idx):\n        if isinstance(idx, int):\n            return self._axes[idx]\n        elif isinstance(idx, str):\n            for ax in self._axes:\n                if ax.name == idx:\n                    return ax\n>           raise KeyError(f\"No axes: {idx!r}\")\nE           KeyError: \"No axes: 'energy'\"\n\ngammapy/maps/axes.py:1815: KeyError"}},"diff":null,"patch_sha256":null,"dropped_paths":[],"snapshot_sha":null}
{"receipt_id":"agent1-27","seq":27,"branch_id":"agent1","kind":"diff","cmd":"compute patch in executor staging agent1-561dadb26e44487b907db9e066bb0947: /opt/homebrew/Cellar/git/2.53.0/bin/git -c core.hooksPath=/dev/null -c core.attributesFile=/dev/null -c diff.external= -c core.quotePath=false add -A && /opt/homebrew/Cellar/git/2.53.0/bin/git -c core.hooksPath=/dev/null -c core.attributesFile=/dev/null -c diff.external= -c core.quotePath=false diff --cached --binary --no-ext-diff --no-textconv --no-renames 4517b03c54bd02dbf548c19cfdbf5a8ece447a4d","path":null,"exit_code":0,"stdout_tail":"diff --git a/gammapy/datasets/evaluator.py b/gammapy/datasets/evaluator.py\nindex 160ad4c43..eb4cef4ec 100644\n--- a/gammapy/datasets/evaluator.py\n+++ b/gammapy/datasets/evaluator.py\n@@ -387,8 +387,22 @@ class MapEvaluator:\n         if self.model.apply_irf[\"edisp\"]:\n             return apply_edisp(npred, self.edisp)\n         else:\n+            # No edisp application: map from true to reco using identity if needed\n             if \"energy_true\" in npred.geom.axes.names:\n-                return apply_edisp(npred, self._edisp_diagonal)\n+                if self.edisp is None:\n+                    # Create identity EDispKernel from geom energy axes\n+                    energy_axis_true = self.geom.axes[\"energy_true\"].copy()\n+                    energy_axis = self.geom.axes[\"energy\"].copy()\n+                    # If axes differ, we cannot map; assume same binning and rename\n+                    if energy_axis_true.nbin != energy_axis.nbin:\n+                        # Fallback: reuse one axis for both\n+                        energy_axis = energy_axis_true.copy(name=\"energy\")\n+                    return apply_edisp(npred,\n+                                     EDispKernel.from_diagonal_response(\n+                                         energy_axis_true=energy_axis_true,\n+                                         energy_axis=energy_axis))\n+                else:\n+                    return apply_edisp(npred, self._edisp_diagonal)\n             else:\n                 return npred\n \n","stderr_tail":"","stdout_sha256":"f4311494a9068da62a7237b066a4f2385b62b0188fe765a4f747fcf8a6653e90","log_path":null,"tree_digest":"ed141caf561272cfaca984301d50e9163d8f666f88847602d9d5150a59663814","tree_download_s":4.300797416130081,"started_at":"2026-10-03T19:33:34.262544Z","duration_s":0.07352524995803833,"timed_out":false,"image_before":"49a46658-3600-4011-9185-b5a1bd09e397","image_after":"49a46658-3600-4011-9185-b5a1bd09e397","junit":null,"diff":{"files":[{"path":"gammapy/datasets/evaluator.py","added":15,"deleted":1,"category":"source","status":"modified"}],"patch_sha256":"f4311494a9068da62a7237b066a4f2385b62b0188fe765a4f747fcf8a6653e90","patch_path":"~/dev/nebius-hackathon/pilot/v2-P/gammapy__gammapy-5342/runs/pilot-gammapy__gammapy-5342-56a1561ee1/artifacts/agent1/agent1-27.patch"},"patch_sha256":"f4311494a9068da62a7237b066a4f2385b62b0188fe765a4f747fcf8a6653e90","dropped_paths":[],"snapshot_sha":"4517b03c54bd02dbf548c19cfdbf5a8ece447a4d"}