improve docs in 2d fit tutorial
" - To understand how a generel modelling and fiiting works in gammapy, please refer to the [analysis_3d tutorial](analysis_3d.ipynb)\n",
"\n",
"## Context:\n",
- "Classically, images analysis in IACTs has been done using a ring background analysis. To understand how this works in gammapy, please refer to the [ring_background tutorial](ring_background.ipynb). Recently, with the availabilty of background IRFs with DL3 data, we can directly do spatial modelling in 2D. Of course, you can also extract maps using the ring background method and then use the same for modelling as described here.\n",
+ "We often want the determine the position and morphology of an object. To do so, we don't necessarily have to resort to a full 3D fitting but can perform a simple image fitting, in particular, in an energy range where the PSF does not vary strongly, or if we want to explore a possible energy dependance of the morphology.\n",
+ "\n",
+ "\n",
+ "## Objective: \n",
+ "To localize a source and/or constrain its morphology.\n",
"\n",
"## Proposed approach:\n",
"\n",
"# To see the best fit values along with the errors\n",
"analysis.fit_result.parameters.to_table()"
]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
}
],
"metadata": {
