Run black on tutorials/analysis_3d.ipynb
"metadata": {},
"outputs": [],
"source": [
- "counts = maps['counts'].sum_over_axes()\n",
+ "counts = maps[\"counts\"].sum_over_axes()\n",
"counts.smooth(width=0.1 * u.deg).plot(stretch=\"sqrt\", add_cbar=True, vmax=6);"
]
},
"metadata": {},
"outputs": [],
"source": [
- "background = maps['background'].sum_over_axes()\n",
- "background.smooth(width=0.1 * u.deg).plot(stretch=\"sqrt\", add_cbar=True, vmax=6);"
+ "background = maps[\"background\"].sum_over_axes()\n",
+ "background.smooth(width=0.1 * u.deg).plot(\n",
+ " stretch=\"sqrt\", add_cbar=True, vmax=6\n",
+ ");"
]
},
{
"table_psf = obs_list.make_mean_psf(src_pos)\n",
"\n",
"# PSF kernel used for the model convolution\n",
- "psf_kernel = PSFKernel.from_table_psf(\n",
- " table_psf, geom, max_radius=\"0.3 deg\"\n",
- ")"
+ "psf_kernel = PSFKernel.from_table_psf(table_psf, geom, max_radius=\"0.3 deg\")"
]
},
{
"metadata": {},
"outputs": [],
"source": [
- "residual.sum_over_axes().smooth(width=0.05 * u.deg).plot(cmap=\"coolwarm\", vmin=-3, vmax=3, add_cbar=True);"
+ "residual.sum_over_axes().smooth(width=0.05 * u.deg).plot(\n",
+ " cmap=\"coolwarm\", vmin=-3, vmax=3, add_cbar=True\n",
+ ");"
]
},
{
