{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "nervous-sight",
   "metadata": {},
   "source": [
    "# Using !-string and #-string commands\n",
    "\n",
    "## !-strings are for setting simulation parameters\n",
    "\n",
    "!-strings are a convenient way of accessing multiple layers of a nested dictionary structure with a single string using the format:\n",
    "\n",
    "    \"!<ALIAS>.<sub-dict>...<sub-dict>.<param>\"\n",
    "    \n",
    "Any level of the nested dictionary can be reached by truncating the keyword.\n",
    "\n",
    "**Note: !-strings only work on `UserCommands` objects**\n",
    "\n",
    "Below is an example of how to use !-strings, using the example optical train."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "loved-franchise",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scopesim as sim\n",
    "opt = sim.load_example_optical_train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "uniform-cursor",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt.cmds[\"!ATMO\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "domestic-chemical",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt.cmds[\"!ATMO.background\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "earned-indicator",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt.cmds[\"!ATMO.background.filter_name\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "selected-backup",
   "metadata": {},
   "source": [
    "## #-strings are for accessing Effect object parameters\n",
    "\n",
    "Similar to !-strings, #-strings allow us to get at the preset values inside the Effect-objects of the optical system. #-strings allow us to pring the contents of an effect's meta dictionary.\n",
    "\n",
    "**Note: !-strings only work on `OpticalTrain` objects**\n",
    "\n",
    "Here, we're again using the example optical train defined above. First let's list the effects:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "hydraulic-astrology",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt.effects"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "paperback-outreach",
   "metadata": {},
   "source": [
    "We list the meta dictionary contents by using the string format \n",
    "\n",
    "    \"#<effect-name>.\"\n",
    "    \n",
    "**Note: The `.` at the end is important, otherwise the optical train will look for a non-existant effect named `#<effect-name>`**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "exterior-romania",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt[\"#exposure_action.\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "invisible-contrary",
   "metadata": {},
   "source": [
    "We print a specific meta parameter by adding it after the `.`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "independent-benjamin",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt[\"#exposure_action.ndit\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dying-appeal",
   "metadata": {},
   "source": [
    "Notice that the value of this dictionary entry is itself a !-string. We can resolve this by adding a `!` to the end of the string, to force it to get the actual value from `opt.cmds`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "internal-capital",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt[\"#exposure_action.ndit!\"]"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}