{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [],
   "source": [
    "!pip install aiohttp matplotlib pandas pyarrow requests \"xarray[io]\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 139
    },
    "id": "cpiv_WAPGfrY",
    "outputId": "11e0d328-c765-4382-fbe7-64cc5adba404"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "URL = 'https://mastapp.site'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Hu8S8IvjI4sj"
   },
   "source": [
    "# Quickstart\n",
    "This notebook shows some very simple example of getting started."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "l8ci7WglJJPb"
   },
   "source": [
    "#### List All Shots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 721
    },
    "id": "yNJv-2FfF2zb",
    "outputId": "2eaafdfa-6e1d-491d-bc62-3c98d42cae77"
   },
   "outputs": [],
   "source": [
    "shots_df = pd.read_parquet(f'{URL}/parquet/level2/shots')\n",
    "shots_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S4ZTGisaJQUm"
   },
   "source": [
    "#### List All Sources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 424
    },
    "id": "eI3YpqABGQ_K",
    "outputId": "046933be-b3ef-42fb-c8f2-f9c3dab2ce28"
   },
   "outputs": [],
   "source": [
    "sources_df = pd.read_parquet(f\"{URL}/parquet/level2/sources\")\n",
    "sources_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qW5VOYWyJR5t"
   },
   "source": [
    "#### List all signals Given a Shot Number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 424
    },
    "id": "oyuHeNgkGOab",
    "outputId": "06e3ecb7-b177-4817-a265-1b2d81e234e7"
   },
   "outputs": [],
   "source": [
    "signals_df = pd.read_parquet(f\"{URL}/parquet/level2/signals?shot_id=30421\")\n",
    "signals_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kLR6H5S-JVsD"
   },
   "source": [
    "#### Open and plot shot data. \n",
    "\n",
    "Here we are visualising some plasma current data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 447
    },
    "id": "AXaJ1a9GGbtW",
    "outputId": "76ac54b6-8210-484a-847b-6b7acea96399"
   },
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "dataset = xr.open_zarr(\n",
    "    \"https://s3.echo.stfc.ac.uk/mast/level2/shots/30421.zarr\",\n",
    "    group='summary'\n",
    ")\n",
    "\n",
    "dataset['ip'].plot()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.13.3"
  }
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