ADapted exclusion mask notebook
"\n",
"We can rely on known sources positions and properties to build a list of regions (here `~regions.SkyRegions`) enclosing most of the signal that our detector would see from these objects. We show below how to build this list manually or from an existing catalog. \n",
"\n",
- "Finally, we show how to build the mask from a `MapDataset`, finding pixels which contain statistically significant signal. To do so, we use the `LiMaMapEstimator`\n",
+ "Finally, we show how to build the mask from a `MapDataset`, finding pixels which contain statistically significant signal. To do so, we use the `CorrelatedExcessMapEstimator`\n",
" "
]
},
"from gammapy.utils.regions import make_region\n",
"from gammapy.catalog import SOURCE_CATALOGS\n",
"from gammapy.datasets import Datasets\n",
- "from gammapy.estimators import LiMaMapEstimator"
+ "from gammapy.estimators import CorrelatedExcessMapEstimator"
]
},
{
"metadata": {},
"outputs": [],
"source": [
- "estimator = LiMaMapEstimator(\"0.4 deg\")\n",
- "result = estimator.run(dataset)"
+ "estimator = CorrelatedExcessMapEstimator(dataset, \"0.4 deg\")\n",
+ "result = estimator.run(steps=\"ts\")"
]
},
{
