gammapy__gammapy-5674

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  "stdout": "gammapy/estimators/points/core.py:31:def squash_fluxpoints(flux_point, axis):\ngammapy/estimators/points/core.py:869:            fp_new = squash_fluxpoints(fp, axis_new)\n",
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  "filepath": "gammapy/estimators/points/core.py",
  "content": "# Licensed under a 3-clause BSD style license - see LICENSE.rst\nimport logging\nfrom copy import deepcopy\nimport numpy as np\nfrom scipy import stats\nfrom scipy.interpolate import interp1d\nfrom scipy.optimize import minimize\nfrom astropy.io import fits\nfrom astropy.io.registry import IORegistryError\nfrom astropy.table import Table, vstack\nfrom astropy.time import Time\nfrom astropy.visualization import quantity_support\nimport matplotlib.pyplot as plt\nfrom gammapy.data import GTI\nfrom gammapy.maps import Map, MapAxis, Maps, RegionNDMap, TimeMapAxis\nfrom gammapy.maps.axes import UNIT_STRING_FORMAT, flat_if_equal\nfrom gammapy.modeling.models import TemplateSpectralModel\nfrom gammapy.modeling.models.spectral import scale_plot_flux\nfrom gammapy.modeling.scipy import stat_profile_ul_scipy\nfrom gammapy.utils.interpolation import interpolate_profile\nfrom gammapy.utils.scripts import make_path\nfrom gammapy.utils.table import table_standardise_units_copy\nfrom gammapy.utils.time import time_ref_to_dict\nfrom ..map.core import DEFAULT_UNIT, FluxMaps\n\n__all__ = [\"FluxPoints\"]\n\nlog = logging.getLogger(__name__)\n\n\ndef squash_fluxpoints(flux_point, axis):\n    \"\"\"Squash a `~FluxPoints` object into one point.\n\n    The log-likelihoods profiles in each bin are summed\n    to compute the resultant quantities. Stat profiles\n    must be present on the `~FluxPoints` object for\n    this method to work.\n    \"\"\"\n    value_scan = flux_point.stat_scan.geom.axes[\"norm\"].center\n    stat_scan = np.sum(flux_point.stat_scan.data, axis=0).ravel()\n    f = interp1d(value_scan, stat_scan, kind=\"quadratic\", bounds_error=False)\n    f = interpolate_profile(value_scan, stat_scan)\n    minimizer = minimize(\n        f,\n        x0=value_scan[int(len(value_scan) / 2)],\n        bounds=[(value_scan[0], value_scan[-1])],\n        method=\"L-BFGS-B\",\n    )\n\n    maps = Maps()\n    geom = flux_point.geom.to_image()\n    if axis.name != \"energy\":\n        geom = geom.to_cube([flux_point.geom.axes[\"energy\"]])\n\n    maps[\"norm\"] = Map.from_geom(geom, data=minimizer.x)\n    maps[\"norm_err\"] = Map.from_geom(\n        geom, data=np.sqrt(minimizer.hess_inv.todense()).reshape(geom.data_shape)\n    )\n    maps[\"n_dof\"] = Map.from_geom(geom, data=flux_point.geom.axes[axis.name].nbin)\n\n    if \"norm_ul\" in flux_point.available_quantities:\n        delta_ts = flux_point.meta.get(\"n_sigma_ul\", 2) ** 2\n        ul = stat_profile_ul_scipy(value_scan, stat_scan, delta_ts=delta_ts)\n        maps[\"norm_ul\"] = Map.from_geom(geom, data=ul.value)\n\n    maps[\"stat\"] = Map.from_geom(geom, data=f(minimizer.x))\n\n    geom_scan = geom.to_cube([MapAxis.from_nodes(value_scan, name=\"norm\")])\n    maps[\"stat_scan\"] = Map.from_geom(\n        geom=geom_scan, data=stat_scan.reshape(geom_scan.data_shape)\n    )\n    try:\n        maps[\"stat_null\"] = Map.from_geom(geom, data=np.sum(flux_point.stat_null.data))\n        maps[\"ts\"] = maps[\"stat_null\"] - maps[\"stat\"]\n    except AttributeError:\n        log.info(\n            \"Stat null info not present on original FluxPoints object. TS not computed\"\n        )\n\n    maps[\"success\"] = Map.from_geom(geom=geom, data=minimizer.success, dtype=bool)\n\n    combined_fp = FluxPoints.from_maps(\n        maps=maps,\n        sed_type=flux_point.sed_type_init,\n        reference_model=flux_point.reference_model,\n        gti=flux_point.gti,\n        meta=flux_point.meta,\n    )\n    return combined_fp\n\n\nclass FluxPoints(FluxMaps):\n    \"\"\"Flux points container.\n\n    The supported formats are described here: :ref:`gadf:flux-points`.\n\n    In summary, the following formats and minimum required columns are:\n\n    * Format ``dnde``: columns ``e_ref`` and ``dnde``\n    * Format ``e2dnde``: columns ``e_ref``, ``e2dnde``",
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  "filepath": "gammapy/estimators/points/core.py",
  "content": "        Parameters\n        ----------\n        axis_new : `MapAxis` or `TimeMapAxis`\n            The new axis to resample along\n\n        Returns\n        -------\n        flux_points : `~gammapy.estimators.FluxPoints`\n            A new FluxPoints object with modified axis.\n        \"\"\"\n        if not self.has_stat_profiles:\n            raise ValueError(\"Stat profiles not present, rebinning is not possible\")\n\n        fluxpoints = []\n        for edge_min, edge_max in zip(axis_new.edges_min, axis_new.edges_max):\n            if isinstance(axis_new, TimeMapAxis):\n                edge_min = edge_min + axis_new.reference_time\n                edge_max = edge_max + axis_new.reference_time\n            fp = self.slice_by_coord({axis_new.name: slice(edge_min, edge_max)})\n            fp_new = squash_fluxpoints(fp, axis_new)\n            fluxpoints.append(fp_new)\n\n        return self.__class__.from_stack(fluxpoints, axis=axis_new)",
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{
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  "filepath": "gammapy/maps/core.py",
  "content": "        from .hpx import HpxGeom\n        from .region import RegionGeom\n        from .wcs import WcsGeom\n\n        if isinstance(geom, HpxGeom):\n            map_type = \"hpx\"\n        elif isinstance(geom, WcsGeom):\n            map_type = \"wcs\"\n        elif isinstance(geom, RegionGeom):\n            map_type = \"region\"\n        else:\n            raise ValueError(\"Unrecognized geom type.\")\n\n        cls_out = Map._get_map_cls(map_type)\n        return cls_out(geom, data=data, meta=meta, unit=unit, dtype=dtype)\n\n    @staticmethod\n    def from_hdulist(\n        hdulist, hdu=None, hdu_bands=None, map_type=\"auto\", format=None, colname=None\n    ):\n        \"\"\"Create from a `astropy.io.fits.HDUList` object.",
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  "filepath": "gammapy/maps/region/ndmap.py",
  "content": "            data = np.zeros(geom.data_shape, dtype=dtype)\n\n        if meta is None:\n            meta = {}\n\n        self._geom = geom\n        self.data = data\n        self.meta = meta\n        self._unit = u.Unit(unit)\n\n    @property\n    def data(self):\n        return self._data\n\n    @data.setter\n    def data(self, value):\n        \"\"\"Set data.\n        Parameters\n        ----------\n        value : array-like\n            Data array.\n        \"\"\"\n        if np.isscalar(value):\n            value = value * np.ones(self.geom.data_shape, dtype=type(value))\n\n        if isinstance(value, u.Quantity):\n            raise TypeError(\"Map data must be a Numpy array. Set unit separately\")\n\n        input_shape = value.shape\n        if len(self.geom.data_shape) == 2 + len(value.shape):\n            if self.geom.data_shape[: len(value.shape)] == value.shape:\n                value = np.expand_dims(value, (-2, -1))\n\n        if self.geom.data_shape != value.shape:\n            raise ValueError(\n                f\"Input shape {input_shape} is not compatible with shape from geometry {self.geom.data_shape}\"\n            )\n\n        self._data = value\n\n    def plot(self, ax=None, axis_name=None, **kwargs):",
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{
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  "stdout": "gammapy/estimators/tests:\n__init__.py\ntest_core.py\ntest_energydependentmorphology.py\ntest_flux.py\ntest_metadata.py\ntest_parameter_estimator.py\ntest_profile.py\ntest_utils.py\n",
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{
  "status": "ok",
  "stdout": "gammapy/datasets/tests/test_flux_points.py:9:from gammapy.datasets import Datasets, FluxPointsDataset\ngammapy/datasets/tests/test_flux_points.py:10:from gammapy.estimators import FluxPoints\ngammapy/datasets/tests/test_flux_points.py:37:    data = FluxPoints.from_table(table, format=\"gadf-sed\")\ngammapy/datasets/tests/test_flux_points.py:48:    dataset = FluxPointsDataset(model, data, meta_table=obs_table)\ngammapy/datasets/tests/test_flux_points.py:57:    data = FluxPoints.from_table(table, format=\"gadf-sed\")\ngammapy/datasets/tests/test_flux_points.py:63:    dataset = FluxPointsDataset(model, data, name=\"test_dataset\")\ngammapy/datasets/tests/test_flux_points.py:65:    dataset2 = FluxPointsDataset.read(path, name=\"test_dataset2\")\ngammapy/datasets/tests/test_flux_points.py:90:    assert \"FluxPointsDataset\" in str(dataset)\ngammapy/datasets/tests/test_flux_points.py:93:    assert \"FluxPointsDataset\" in str(dataset)\ngammapy/datasets/tests/test_flux_points.py:134:    flux_points = FluxPoints.from_table(table=table)\ngammapy/datasets/tests/test_flux_points.py:135:    flux_points_dataset = FluxPointsDataset(data=flux_points)\n",
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  "exit_code": 0
}

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{
  "status": "ok",
  "stdout": "gammapy/estimators/map/excess.py:290:            reco_exposure = reco_exposure.resample_axis(\ngammapy/estimators/map/excess.py:299:            resampled_dataset.background = dataset.npred().resample_axis(\ngammapy/estimators/points/core.py:840:    def resample_axis(self, axis_new):\ngammapy/estimators/points/tests/test_core.py:419:def test_resample_axis():\ngammapy/estimators/points/tests/test_core.py:427:    l1 = lc_1d.resample_axis(axis_new=axis_new)\ngammapy/estimators/points/tests/test_core.py:436:    l1 = lc_1d.resample_axis(axis_new=axis_new)\ngammapy/estimators/points/tests/test_core.py:447:        fp.resample_axis(axis_new=MapAxis.from_nodes([0, 1, 2]))\ngammapy/visualization/utils.py:122:    >>> map_ = map_.resample_axis(axis_rgb)\ngammapy/visualization/tests/test_utils.py:101:    map_ = map_.resample_axis(axis_rgb)\ngammapy/maps/geom.py:541:    def resample_axis(self, axis):\ngammapy/maps/region/tests/test_ndmap.py:269:def test_region_nd_map_resample_axis():\ngammapy/maps/region/tests/test_ndmap.py:280:    m2 = m.resample_axis(axis=new_axis)\ngammapy/maps/region/tests/test_ndmap.py:286:    m3 = m.resample_axis(axis=new_axis)\ngammapy/maps/core.py:709:    def resample_axis(self, axis, weights=None, ufunc=np.add):\ngammapy/maps/core.py:733:        geom = self.geom.resample_axis(axis)\ngammapy/maps/hpx/tests/test_ndmap.py:339:def test_hpxndmap_resample_axis():\ngammapy/maps/hpx/tests/test_ndmap.py:348:    m2 = m.resample_axis(axis=new_axis)\ngammapy/maps/hpx/tests/test_ndmap.py:354:    m3 = m.resample_axis(axis=new_axis)\ngammapy/maps/wcs/tests/test_ndmap.py:510:def test_wcsndmap_resample_axis():\ngammapy/maps/wcs/tests/test_ndmap.py:519:    m2 = m.resample_axis(axis=new_axis)\n",
  "stderr": "",
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{
  "status": "ok",
  "stdout": "gammapy/estimators/tests:\n__init__.py\ntest_core.py\ntest_energydependentmorphology.py\ntest_flux.py\ntest_metadata.py\ntest_parameter_estimator.py\ntest_profile.py\ntest_utils.py\n",
  "stderr": "",
  "exit_code": 0
}

{
  "status": "ok",
  "stdout": "gammapy/estimators/points/tests\n",
  "stderr": "",
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{
  "status": "ok",
  "filepath": "gammapy/estimators/points/tests/test_core.py",
  "content": "        model, table[\"e_min\"], table[\"e_max\"]\n    )\n    fp = FluxPoints.from_table(table, reference_model=model)\n\n    assert fp.available_quantities == [\"norm\", \"n_dof\"]\n    assert_allclose(fp.n_dof.data.ravel(), table[\"n_dof\"])\n\n\n@requires_data()\ndef test_resample_axis():\n    lc_1d = FluxPoints.read(\n        \"$GAMMAPY_DATA/estimators/pks2155_hess_lc/pks2155_hess_lc.fits\",\n        format=\"lightcurve\",\n    )\n    axis_new = get_rebinned_axis(\n        lc_1d, method=\"fixed-bins\", group_size=5, axis_name=\"time\"\n    )\n    l1 = lc_1d.resample_axis(axis_new=axis_new)\n    assert_allclose(l1.norm.data.ravel()[0:2], [1.56321943, 2.12845751], rtol=1e-3)\n    assert_allclose(l1.norm_err.data.ravel()[0:2], [0.03904136, 0.03977413], rtol=1e-3)\n    assert_allclose(l1.n_dof.data.ravel()[0], 5.0)\n    assert l1.success.data.ravel()[0]\n\n    axis_new = get_rebinned_axis(\n        lc_1d, method=\"min-ts\", ts_threshold=300, axis_name=\"time\"\n    )\n    l1 = lc_1d.resample_axis(axis_new=axis_new)\n    assert_allclose(l1.norm_err.data.ravel()[0:2], [0.072236, 0.092942], rtol=1e-3)\n    assert_allclose(l1.ts.data.ravel()[0:2], [312.742222, 454.99609], rtol=1e-3)\n    assert_allclose(l1.stat_null.data.ravel()[0:2], [319.8675, 462.329], rtol=1e-3)\n    assert l1.success.data.ravel()[0]\n    assert_allclose(l1.n_dof.data[0][0][0][0], 2)\n\n    path = make_path(\"$GAMMAPY_DATA/tests/spectrum/flux_points/flux_points.fits\")\n    table = Table.read(path)\n    fp = FluxPoints.from_table(table)\n    with pytest.raises(ValueError):\n        fp.resample_axis(axis_new=MapAxis.from_nodes([0, 1, 2]))",
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{
  "status": "error",
  "error_type": "CommandError",
  "error_message": "Traceback (most recent call last):\n  File \"<stdin>\", line 3, in <module>\n  File \"/workspace/gammapy/estimators/__init__.py\", line 4, in <module>\n    from .core import Estimator\n  File \"/workspace/gammapy/estimators/core.py\", line 9, in <module>\n    from gammapy.modeling.models import ModelBase\n  File \"/workspace/gammapy/modeling/__init__.py\", line 8, in <module>\n    from .selection import select_nested_models\n  File \"/workspace/gammapy/modeling/selection.py\", line 4, in <module>\n    from gammapy.stats.utils import sigma_to_ts\n  File \"/workspace/gammapy/stats/__init__.py\", line 4, in <module>\n    from .counts_statistic import CashCountsStatistic, WStatCountsStatistic\n  File \"/workspace/gammapy/stats/counts_statistic.py\", line 8, in <module>\n    from .fit_statistics import cash, wstat\n  File \"/workspace/gammapy/stats/fit_statistics.py\", line 8, in <module>\n    from gammapy.stats.fit_statistics_cython import TRUNCATION_VALUE\nModuleNotFoundError: No module named 'gammapy.stats.fit_statistics_cython'\n",
  "details": {
    "stdout": "",
    "stderr": "Traceback (most recent call last):\n  File \"<stdin>\", line 3, in <module>\n  File \"/workspace/gammapy/estimators/__init__.py\", line 4, in <module>\n    from .core import Estimator\n  File \"/workspace/gammapy/estimators/core.py\", line 9, in <module>\n    from gammapy.modeling.models import ModelBase\n  File \"/workspace/gammapy/modeling/__init__.py\", line 8, in <module>\n    from .selection import select_nested_models\n  File \"/workspace/gammapy/modeling/selection.py\", line 4, in <module>\n    from gammapy.stats.utils import sigma_to_ts\n  File \"/workspace/gammapy/stats/__init__.py\", line 4, in <module>\n    from .counts_statistic import CashCountsStatistic, WStatCountsStatistic\n  File \"/workspace/gammapy/stats/counts_statistic.py\", line 8, in <module>\n    from .fit_statistics import cash, wstat\n  File \"/workspace/gammapy/stats/fit_statistics.py\", line 8, in <module>\n    from gammapy.stats.fit_statistics_cython import TRUNCATION_VALUE\nModuleNotFoundError: No module named 'gammapy.stats.fit_statistics_cython'\n",
    "exit_code": 1
  }
}

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  "stderr": "",
  "exit_code": 0
}

{
  "status": "ok",
  "stdout": "/workspace/gammapy/stats/fit_statistics_cython.pyx\n",
  "stderr": "",
  "exit_code": 0
}

{
  "status": "error",
  "error_type": "CommandError",
  "error_message": "In /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nImportError while loading conftest '/workspace/gammapy/conftest.py'.\n/gammapy/gammapy/conftest.py:12: in <module>\n    from gammapy.data import GTI\n/gammapy/gammapy/data/__init__.py:4: in <module>\n    from .data_store import DataStore\n/gammapy/gammapy/data/data_store.py:17: in <module>\n    from .observations import Observation, ObservationChecker, Observations\n/gammapy/gammapy/data/observations.py:20: in <module>\n    from gammapy.utils.metadata import CreatorMetaData, TargetMetaData, TimeInfoMetaData\n/gammapy/gammapy/utils/metadata.py:16: in <module>\n    from gammapy.version import version\nE   ModuleNotFoundError: No module named 'gammapy.version'\n",
  "details": {
    "stdout": "",
    "stderr": "In /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'parseString' deprecated - use 'parse_string'\nIn /usr/local/lib/python3.10/site-packages/matplotlib/mpl-data/stylelib/classic.mplstyle: 'resetCache' deprecated - use 'reset_cache'\nImportError while loading conftest '/workspace/gammapy/conftest.py'.\n/gammapy/gammapy/conftest.py:12: in <module>\n    from gammapy.data import GTI\n/gammapy/gammapy/data/__init__.py:4: in <module>\n    from .data_store import DataStore\n/gammapy/gammapy/data/data_store.py:17: in <module>\n    from .observations import Observation, ObservationChecker, Observations\n/gammapy/gammapy/data/observations.py:20: in <module>\n    from gammapy.utils.metadata import CreatorMetaData, TargetMetaData, TimeInfoMetaData\n/gammapy/gammapy/utils/metadata.py:16: in <module>\n    from gammapy.version import version\nE   ModuleNotFoundError: No module named 'gammapy.version'\n",
    "exit_code": 4
  },
  "budget_warning": "Only 10 tool call(s) remaining (20/30 used). Finalize your edits and call submit_patch soon."
}

{
  "status": "ok",
  "stdout": "/gammapy\n",
  "stderr": "",
  "exit_code": 0,
  "budget_warning": "Only 9 tool call(s) remaining (21/30 used). Finalize your edits and call submit_patch soon."
}

{
  "status": "error",
  "error_type": "CommandError",
  "error_message": "ls: cannot access '/workspace/gammapy/version.py': No such file or directory\n",
  "details": {
    "stdout": "",
    "stderr": "ls: cannot access '/workspace/gammapy/version.py': No such file or directory\n",
    "exit_code": 2
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  "budget_warning": "Only 8 tool call(s) remaining (22/30 used). Finalize your edits and call submit_patch soon."
}

{
  "status": "ok",
  "stdout": "__init__.py\n__main__.py\n_astropy_init.py\nanalysis\nastro\ncatalog\nconftest.py\ndata\ndatasets\nestimators\nextern\nirf\nmakers\nmaps\nmodeling\nscripts\nstats\ntests\nutils\nvisualization\nworkflow\n",
  "stderr": "",
  "exit_code": 0,
  "budget_warning": "Only 7 tool call(s) remaining (23/30 used). Finalize your edits and call submit_patch soon."
}