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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Usual Tips & Tricks\n",
    "We loosely group here a few code lines that are relevant and useful throughout the analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initializaion of the notebooks\n",
    "We detail here the header we start almost all our notebooks with.\n",
    "\n",
    "#### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#useful to make plots editable in the notebook; should not be used in a regular script\n",
    "%matplotlib notebook \n",
    "\n",
    "#To avoid typing the main path each time\n",
    "from sitelle.constants import FITS_DIR\n",
    "\n",
    "#We prefer our implementation of the SpectralCube\n",
    "from sitelle.process import SpectralCubePatch as SpectralCube"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loading\n",
    "The datacubes are not calibrated by default. Calibration should be performed by the suer and respecified each time we launch a new instance of the cube."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "SN2_ORCS = SpectralCube(FITS_DIR/'orig/M31_SN2.merged.cm1.1.0.hdf5')\n",
    "#Astrometric calibration level 1 and 2:\n",
    "SN2_ORCS.set_wcs(FITS_DIR/'M31_SN2.1.0.ORCS/M31_SN2.1.0.wcs.deep_frame.fits')\n",
    "#Astrometric calibration level 3:\n",
    "SN2_ORCS.set_dxdymaps(FITS_DIR/'M31_SN2.1.0.ORCS/M31_SN2.1.0.wcs.dxmap.fits',\n",
    "                      FITS_DIR/'M31_SN2.1.0.ORCS/M31_SN2.1.0.wcs.dymap.fits')\n",
    "#Wavelength calibration\n",
    "SN2_ORCS.correct_wavelength(FITS_DIR/'M31_SN2.1.0.ORCS/M31_SN2.1.0.skymap.fits')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usage of the plot methods"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Usage of the parallelization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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