statistics.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import yaml\n",
    "import requests\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from pathlib import Path\n",
    "from matplotlib import rc\n",
    "from tqdm import tqdm\n",
    "\n",
    "PTS_PER_INCH = 72.26999\n",
    "# Latex text width in points\n",
    "TEXT_WIDTH_PTS = 505.12177\n",
    "# Latex column width in points\n",
    "COLUMN_WIDTH_PTS = TEXT_WIDTH_PTS / 2\n",
    "# Latex column width in inches\n",
    "COLUMN_WIDTH_INCHES = COLUMN_WIDTH_PTS / PTS_PER_INCH\n",
    "# Latex text width in inches\n",
    "TEXT_WIDTH_INCHES = TEXT_WIDTH_PTS / PTS_PER_INCH\n",
    "# DPI for figures\n",
    "DPI = 600\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"sans\"\n",
    "plt.rcParams['font.stretch'] = 'condensed'\n",
    "plt.rcParams['font.weight'] = 'bold'\n",
    "plt.rcParams[\"axes.labelweight\"] = \"bold\"\n",
    "\n",
    "palette = [\"#66c2a5\", \"#fc8d62\", \"#8da0cb\", \"#e78ac3\", \"#a6d854\", \"#ffd92f\", \"#e5c494\", \"#b3b3b3\"]\n",
    "\n",
    "color = '#de2d26'\n",
    "edgecolor = 'black'\n",
    "width = .5\n",
    "bar_params = dict(color=palette[1], edgecolor=edgecolor, width=width)\n",
    "grid_params = dict(color='gray', alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('config.yml') as file_handle:\n",
    "    config = yaml.load(file_handle, yaml.FullLoader)\n",
    "\n",
    "ENDPOINT_URL = config['rest_api']\n",
    "PLOT_PATH = Path('./summary')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 349.469x349.469 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "url=\"http://mastapp.site/json/shots/aggregate?data=shot_id$count&groupby=campaign&sort=-campaign\"\n",
    "df = pd.read_json(url)\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(COLUMN_WIDTH_INCHES, COLUMN_WIDTH_INCHES))\n",
    "\n",
    "sns.barplot(df, x='campaign', y='count_shot_id', ax=ax, **bar_params)\n",
    "\n",
    "ax.set_xlabel('Campaign')\n",
    "ax.set_ylabel('Shot Count')\n",
    "ax.set_axisbelow(True)\n",
    "ax.grid(**grid_params)\n",
    "\n",
    "plt.savefig(PLOT_PATH / 'campaign_shots_summary.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uuid</th>\n",
       "      <th>name</th>\n",
       "      <th>units</th>\n",
       "      <th>rank</th>\n",
       "      <th>url</th>\n",
       "      <th>csd3_path</th>\n",
       "      <th>description</th>\n",
       "      <th>signal_type</th>\n",
       "      <th>quality</th>\n",
       "      <th>doi</th>\n",
       "      <th>dimensions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2f78475e-c766-545f-9b95-4d95c634ea98</td>\n",
       "      <td>ABM_CALIB_SHOT</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>1</td>\n",
       "      <td>s3://mast/ABM_CALIB_SHOT.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Shot used for calibration (obsolete)</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0496f46d-cc02-55c9-9cb8-b19c3ada2002</td>\n",
       "      <td>ABM_CHANNEL_STATUS</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>2</td>\n",
       "      <td>s3://mast/ABM_CHANNEL_STATUS.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Failed = 0, OK = 1</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time, dim_0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>fda31845-7f97-53d9-b0bd-c4eb94741017</td>\n",
       "      <td>ABM_CHANNEL_TYPE</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>2</td>\n",
       "      <td>s3://mast/ABM_CHANNEL_TYPE.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Channel type (0 = poloidal, 1 = co-tangential,...</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time, dim_0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4eca20e8-632b-54d8-9c33-e240ab6ddab8</td>\n",
       "      <td>ABM_GAIN</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>2</td>\n",
       "      <td>s3://mast/ABM_GAIN.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Gain of pre-amplifiers</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time, dim_0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>cc94cf82-d8ec-5104-bd7b-cbadf240d2dd</td>\n",
       "      <td>ABM_I-BOL</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>2</td>\n",
       "      <td>s3://mast/ABM_I-BOL.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Incident powers (x - channel)</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time, chord_number]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>10ed3a41-f062-5d3d-9e7c-9bfa878b31d6</td>\n",
       "      <td>AMB_OBV17</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>1</td>\n",
       "      <td>s3://mast/AMB_OBV17.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Outer discrete Br magnetic coil array r=1.590,...</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>e8c8c81f-a63b-5a35-a351-13bac038d771</td>\n",
       "      <td>AMB_OBV18</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>1</td>\n",
       "      <td>s3://mast/AMB_OBV18.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Outer discrete Br magnetic coil array r=1.440,...</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>15ee2882-cf3b-54ba-9d1b-bd8786b6c86a</td>\n",
       "      <td>AMB_OBV19</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>1</td>\n",
       "      <td>s3://mast/AMB_OBV19.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td>Outer discrete Br magnetic coil array r=1.440,...</td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>1b3cccaa-2f07-5a63-b7aa-cd76ee2265c9</td>\n",
       "      <td>AMB_STATUS</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>1</td>\n",
       "      <td>s3://mast/AMB_STATUS.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td></td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>aa015324-1ac5-584a-b83c-3d9035dc7c67</td>\n",
       "      <td>AMB_VERSION</td>\n",
       "      <td>dimensionless</td>\n",
       "      <td>1</td>\n",
       "      <td>s3://mast/AMB_VERSION.zarr</td>\n",
       "      <td>/rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...</td>\n",
       "      <td></td>\n",
       "      <td>Analysed</td>\n",
       "      <td>Not Checked</td>\n",
       "      <td></td>\n",
       "      <td>[time]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3773 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    uuid                name          units  \\\n",
       "0   2f78475e-c766-545f-9b95-4d95c634ea98      ABM_CALIB_SHOT  dimensionless   \n",
       "1   0496f46d-cc02-55c9-9cb8-b19c3ada2002  ABM_CHANNEL_STATUS  dimensionless   \n",
       "2   fda31845-7f97-53d9-b0bd-c4eb94741017    ABM_CHANNEL_TYPE  dimensionless   \n",
       "3   4eca20e8-632b-54d8-9c33-e240ab6ddab8            ABM_GAIN  dimensionless   \n",
       "4   cc94cf82-d8ec-5104-bd7b-cbadf240d2dd           ABM_I-BOL  dimensionless   \n",
       "..                                   ...                 ...            ...   \n",
       "68  10ed3a41-f062-5d3d-9e7c-9bfa878b31d6           AMB_OBV17  dimensionless   \n",
       "69  e8c8c81f-a63b-5a35-a351-13bac038d771           AMB_OBV18  dimensionless   \n",
       "70  15ee2882-cf3b-54ba-9d1b-bd8786b6c86a           AMB_OBV19  dimensionless   \n",
       "71  1b3cccaa-2f07-5a63-b7aa-cd76ee2265c9          AMB_STATUS  dimensionless   \n",
       "72  aa015324-1ac5-584a-b83c-3d9035dc7c67         AMB_VERSION  dimensionless   \n",
       "\n",
       "    rank                                url  \\\n",
       "0      1      s3://mast/ABM_CALIB_SHOT.zarr   \n",
       "1      2  s3://mast/ABM_CHANNEL_STATUS.zarr   \n",
       "2      2    s3://mast/ABM_CHANNEL_TYPE.zarr   \n",
       "3      2            s3://mast/ABM_GAIN.zarr   \n",
       "4      2           s3://mast/ABM_I-BOL.zarr   \n",
       "..   ...                                ...   \n",
       "68     1           s3://mast/AMB_OBV17.zarr   \n",
       "69     1           s3://mast/AMB_OBV18.zarr   \n",
       "70     1           s3://mast/AMB_OBV19.zarr   \n",
       "71     1          s3://mast/AMB_STATUS.zarr   \n",
       "72     1         s3://mast/AMB_VERSION.zarr   \n",
       "\n",
       "                                            csd3_path  \\\n",
       "0   /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "1   /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "2   /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "3   /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "4   /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "..                                                ...   \n",
       "68  /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "69  /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "70  /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "71  /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "72  /rds/project/rds-sPGbyCAPsJI/archive/zarr/M7/A...   \n",
       "\n",
       "                                          description signal_type  \\\n",
       "0                Shot used for calibration (obsolete)    Analysed   \n",
       "1                                  Failed = 0, OK = 1    Analysed   \n",
       "2   Channel type (0 = poloidal, 1 = co-tangential,...    Analysed   \n",
       "3                              Gain of pre-amplifiers    Analysed   \n",
       "4                       Incident powers (x - channel)    Analysed   \n",
       "..                                                ...         ...   \n",
       "68  Outer discrete Br magnetic coil array r=1.590,...    Analysed   \n",
       "69  Outer discrete Br magnetic coil array r=1.440,...    Analysed   \n",
       "70  Outer discrete Br magnetic coil array r=1.440,...    Analysed   \n",
       "71                                                       Analysed   \n",
       "72                                                       Analysed   \n",
       "\n",
       "        quality doi            dimensions  \n",
       "0   Not Checked                    [time]  \n",
       "1   Not Checked             [time, dim_0]  \n",
       "2   Not Checked             [time, dim_0]  \n",
       "3   Not Checked             [time, dim_0]  \n",
       "4   Not Checked      [time, chord_number]  \n",
       "..          ...  ..                   ...  \n",
       "68  Not Checked                    [time]  \n",
       "69  Not Checked                    [time]  \n",
       "70  Not Checked                    [time]  \n",
       "71  Not Checked                    [time]  \n",
       "72  Not Checked                    [time]  \n",
       "\n",
       "[3773 rows x 11 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url=\"http://mastapp.site/json/signal_datasets?per_page=100\"\n",
    "response = requests.get(url)\n",
    "total_pages = int(response.headers['x-total-pages'])\n",
    "dfs = [pd.read_json(url + f'&page={i}') for i in range(total_pages)]\n",
    "df = pd.concat(dfs)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Server': 'nginx/1.23.4', 'Date': 'Thu, 29 Feb 2024 16:45:39 GMT', 'Content-Type': 'application/json', 'Content-Length': '36001', 'Connection': 'keep-alive', 'x-total-count': '7468655.0', 'x-total-pages': '74687', 'link': '<http://mastapp.site/json/signals?per_page=100>; rel=\"next\"', 'Strict-Transport-Security': 'max-age=31536000'}\n"
     ]
    }
   ],
   "source": [
    "url=\"http://mastapp.site/json/signals?per_page=100\"\n",
    "response = requests.get(url)\n",
    "print(response.headers)\n",
    "original = 7468739\n",
    "total_pages = int(response.headers['x-total-pages'])\n",
    "# dfs = [pd.read_json(url + f'&page={i}') for i in tqdm(range(total_pages))]\n",
    "# df_signals = pd.concat(dfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_455793/2938176294.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_m9['rank'] = df_m9['rank'].astype(str)\n"
     ]
    },
    {
     "data": {
      "image/png": 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Aq666ivj4eDZu3GhUTSIiXYrXzwxrDVwREfGM12cdlJWVcccdd9CvXz8CAwPbvPzleewiIp3J66C955572LhxI0ePHqW5ubndyxvfPsD27deOHTvcbWpra5k7dy42m42QkBCmTp1KYWFhm/Xk5+czZcoUQkJCsNlszJs3j5MnT3rbNRERQ3i9Cbp37166devGCy+8wNChQ32yFTtixAjCw8Pd09/+ftasWdjtdnr16kVERASZmZkkJyeTn5+PzWbD4XCQnJyMw+EgJiaGuro61q9fT1lZGZmZmZdcm4jIpfI6JceOHcs///lP0tLSfFbEmjVrSEpKajd/+/bt2O12wsLCKCgoIDIykoSEBHJzc1mzZg1PPPEEa9asweFwMH78eHbu3ElNTQ1Dhw4lKyuLnJwcJk6c6LM6RUS+D693Hdx7772UlpaSkpLC+++/z8cff9zm9X3cfvvthIaGct111/HOO++459vtdgDGjRtH//79CQoKYvr06W2WtX6dNm0agYGBREVFMXbs2DbLRETM5PUW7QMPPIDFYuHNN9/kzTffbLPMYrHgdDq9Wl/37t2Jjo6murqavLw87rrrLkJDQ5k+fTpVVVUA2Gw2d/vIyEgAKisrATxq812NjY00Nja6p+vq6gBwOp1e138hvlxXZ/P1WPgrp9OJy+XSWBjMH8fZm1q9DtrWCxd84fHHH2fdunUEBwdz9uxZpk2bRnZ2Nq+88op7y/W7PDngdrE2K1euJD09vd38Xbt2ERoa6lnxHigqKvLZujpbXl4eDQ0NZpdhOpfLRVlZGQABAbrZnVH8cZzr6+s9bmvqebRXX321+/vg4GCmT59OdnY2hw8fBiAqKgqAY8eOuds5HA4AoqOj3W2Kioou2Oa7Fi9ezIIFC9zTdXV1xMTEkJCQ0OZA3KUKCQnx2bo625gxY4iPjze7DNO1brVMmDBBpy8ayB/HufWTsCe87lHr/zrnExsb6/G6nn76aR555BHCw8NpbGxk69atwL8CsvUAWW5uLtXV1URERLBly5Y2y5KSkrDb7WzdupWlS5dSU1NDbm5umzbfZbVasVqt7eYHBQX59JfsL38wHfH1WPizgIAAjUcn8Ldx9qZOr3s0YMCA8y7zdh/tE088wVNPPcWQIUM4evSoe6v00UcfBSAxMZHExEQ+/vhjRowYQY8ePSgvLycyMtJ91kNaWhovvfQSu3fvZsCAAZw6dYqGhgaSk5N1xoGIXBa83hnS0UUK3/eChfT0dEaPHk1lZSVOp5N/+7d/44MPPmDGjBlAS3Bv2rSJlJQUoGUXwuTJk8nOziYiIgKAPn36kJ2dzeTJk91BnZqaqnsxiMhlw+stWpfL1Wb69OnTbNmyhf/8z/9sc49aT/z2t7/lt7/97QXb9O7dm4yMjAu2GTVqFFlZWV79bBGRznLJh/fCwsK48847iY+PZ9GiRb6oSUSkS/F6i/a795xtamqipKSEnJwcevTo4bPCRES6Cq+D9sknn2x3Hm3rvtmZM2f6pCgRka7E66BNTExsE7QWi4WIiAgmTpzIAw884NPiRES6Aq+DVvcPEBHxzvc6M/j48eO8/PLLHDhwAGg56v/ggw+2ud+AiIi08Dpo9+3bx80330xtba173+zGjRtZvXo1WVlZehKuiMh3eB20jz/+OF9//TVDhgxh6tSpAGzbto0vv/ySRYsW8eGHH/q8SBERf+Z10O7atYv+/fuTl5dH9+7dAThz5gyDBg3iH//4h88LFBHxd15fsNB6xkFgYOC/VvL/b2vmq9snioh0JV5v0U6YMIGsrCxGjx7dZtdBTU0NU6ZM8XmBIiL+zuugXbVqFZMmTaKoqIgvv/wSaLlg4Uc/+hGrVq3yeYEiIv7O66C99tprKSoq4uWXX+aLL74AWk7veuihh3R6l4hIB77XebQ2m41ly5b5uhYRkS7J44NhK1asIDAwkD/+8Y/tlq1evZrAwEBWrFjh0+JERLoCj4P23XffJTg4mLlz57ZblpaWRnBwMG+//bZPixMR6Qo8DtqvvvqKQYMGdficnCuuuIJBgwZRUlLi0+JERLoCj4M2MDCQioqKdk9YgJanLlRUVLQ5t1ZERFp4HLRjxozh5MmT/OpXv6Kpqck9v6mpiYULF1JbW8t1111nSJEiIv7M47MOHn74YT7++GNWr17Nxo0biY+Px2KxsHfvXsrLy7FYLDz88MNG1ioi4pc8DtrZs2ezePFiVq5cSXl5uTtcW+/gtWTJEm6//XbDChUR8Vde3etgxYoVfPrppzz66KPcdttt3HrrrTz66KN8+umnLF++/HsXUVJSQlhYGBaLhX79+rnn19bWMnfuXGw2GyEhIUydOpXCwsI2783Pz2fKlCmEhIRgs9mYN28eJ0+e/N61iIj4mtcXLIwdO5axY8f6tIhf/OIX1NfXt5s/a9Ys7HY7vXr1IiIigszMTJKTk8nPz8dms+FwOEhOTsbhcBATE0NdXR3r16+nrKyMzMxMn9YoIvJ9XfLjxi/V66+/TmZmJj/5yU/azN++fTt2u52wsDAKCgo4fPgwY8eOpaamhjVr1gCwZs0aHA4H48ePp6SkhIKCAkJDQ8nKyiInJ8eM7oiItGNq0B49epQFCxYwe/bsdvt3W59NNm7cOPr3709QUBDTp09vs6z167Rp0wgMDCQqKsq9ta1nm4nI5eJ73evAVx555BFcLhcvv/wyH3zwQZtlVVVVAG1uVBMZGQlAZWWlx2060tjYSGNjo3u6rq4OAKfTidPp/N79+S5frquz+Xos/JXT6cTlcmksDOaP4+xNraYFbWZmJm+//TavvvpqmwNgF9J6hsOltlm5ciXp6ent5u/atYvQ0FCPavFEUVGRz9bV2fLy8mhoaDC7DNO5XC7KysqAf93gXnzPH8e5o+NK5+N10AYGBnLjjTeyc+fONvNTUlI4cOAAe/bs8Wg9+fn5QMtW7SOPPOL+3+Ho0aOEhYXx61//GoBjx4653+NwOACIjo4GICoqiqKiogu26cjixYtZsGCBe7quro6YmBgSEhIIDw/3qH5PhISE+GxdnW3MmDHEx8ebXYbpWv8uJ0yY0OHl5+Ib/jjOrZ+EPeF1j5qbmzvcavz888/d96f1xnf/V2hubqa+vp6kpCQAcnNzqa6uJiIigi1btgC4lyUlJWG329m6dStLly6lpqaG3NzcNm06YrVasVqt7eYHBQX59JfsL38wHfH1WPizgIAAjUcn8Ldx9qZOj1tOmjTJ/X1BQUGb6fr6evbv30/Pnj09/sGPPfYYjz32mHs6IyOD+++/n759+1JdXU1zczOJiYl8/PHHjBgxgh49elBeXk5kZCRpaWlAy13DXnrpJXbv3s2AAQM4deoUDQ0NJCcnM3HiRI9rERExksc7Q+x2O3a7HYvFwqlTp9zTdrudzz77DMB9VoAvWCwWNm3aREpKCtCyC2Hy5MlkZ2cTEREBQJ8+fcjOzmby5Mnu3Qepqals3LjRZ3WIiFwqj7doW5+okJ6ezpVXXsm8efPcy7p3786QIUOYMWPG9y4kNTWV1NTUNvN69+5NRkbGBd83atQosrKyvvfPFRExmtdBC7QLWhEROT+v9zovW7aMgwcPcv/993PgwAGgZaty0aJFDBs2zOcFioj4O6+D9qOPPuK2227D6XS6zz7Ys2cP//u//8sHH3xAcnKyz4sUEfFnXgft0qVL+eabb0hMTHTfn+C9994jJyeHpUuXtju/VkTkh87roN23bx9xcXFkZ2djsViAllO1Bg8ezL59+3xeoIiIv/P6Wrfg4GBOnTpFbW2te97Jkyc5depUhxcBiIj80HkdtJMmTeLEiRMMHjyYGTNmMGPGDIYMGcLXX3/NzTffbESNIiJ+zetdBy+88AL79++nuLiY//u//3PPHzx4MM8995xPixMR6Qq8Dtq4uDjy8/P585//3Ob0rrvvvptu3br5vEAREX/3ve7e0K1bt3ZXcYmISMe8Dtqvv/6aZ555hpycHBwOR5s7eVksFoqLi31aoIiIv/M6aO+77z62bNnS4a0SW0/3EhGRf/E6aO12OwEBASxYsIChQ4f6zb0jRUTM4nVKDhs2jPr6ep599lkj6hER6XI8CtrWZ/lAyyW499xzD8uWLWPOnDntbvYdGxvr2wpFRPycR0E7YMCAdvOefvppnn766TbzLBaLXz3FUkSkM3gUtJ48WdabdiIiPyQeBa3L5TK6DhGRLss/HqAuIuLHPA7aHTt2sGbNGvLz84GWO3bNnDmT0NBQ+vTpwwMPPNDu0eEiIuLF6V1PP/00mZmZ7qD9r//6L9577z0Azpw5w6uvvkqvXr1YtWqVMZWKiPgpj7do8/Pz6devH8OHD6e5uZl33nkHi8XCvHnzWL9+PRaLxevHfC9ZsoQhQ4YQEhJCr169uPHGG9m0aZN7eUVFBbNnzyY8PJzw8HDmzJlDZWVlm3Xs2LGDhIQEgoOD6devHwsXLuTcuXNe1SEiYiSPg/bYsWP0798fgAMHDnD8+HEsFgvPPPMMqampXHPNNVRVVXn1wzMzM3E6nYwYMQKr1cru3bu54447yM/Pp7GxkZtvvpmNGzfSvXt3unfvzoYNG5g6dao7SAsLC5k6dSqffPIJ0dHRnDp1iueff55f/vKXXtUhImIkj4PWZrPx5ZdfUllZydtvvw3ANddcQ2RkJABnz55td/HCxeTk5FBSUsKePXs4fPgwoaGhNDU1sXfvXt566y0OHTpEXFwcxcXFfPXVV8TExFBQUOD++atWreLMmTPMnj2b4uJi9/PK1q9f3+YiCxERM3kctFOmTOHUqVPExsaycuVKLBYL99xzDwA1NTV8+eWXDB061KsfbrVaWb58OTfccAMDBw6kvr6ewMBArr/+eux2O9DyRIewsDB69OjBpEmTANzLWr/OmDEDgDFjxhAXF0dzczPbt2/3qhYREaN4fDBs1apVlJeXk52dTXNzM7NmzWL+/PkArFu3jubmZm677TavCyguLuazzz4DWu5z+8Ybb3D11Ve7d0PYbDZ329at59b9tOdrU1pa2m5f7rc1NjbS2Njonq6rqwPA6XT69Mo2f75Kztdj4a+cTicul0tjYTB/HGdvavU4aCMjI8nKyqK+vp7m5mbCwsLcyxYtWsTChQvp3r27d5UCGRkZ/OEPf2Dnzp3MmjWLtLQ0Ro8e3WFbT64886TNypUrSU9Pbzd/165dhIaGXrxoDxUVFflsXZ0tLy+PhoYGs8swncvlcu+GCgjQaedG8cdx9uZ0Vq/v3tVREAUHB3u7mjasViuTJk1iypQpbNiwgXXr1hEVFQW0HIRr5XA4AIiOjgYgKiqKI0eOXLBNRxYvXsyCBQvc03V1dcTExJCQkEB4ePgl9eXbQkJCfLauzjZmzBji4+PNLsN0rVstEyZM0C1BDeSP49z6SdgTpvWooqKCvXv38pOf/ASLxcLXX3/Nnj17AGhoaCApKYmMjAyys7PdW9HZ2dkAJCUlub9mZGTw/vvvk5KSQl5eHmVlZVgsFhITE8/7s61Wa4ePRg8KCvLpL9lf/mA64uux8GcBAQEaj07gb+PsTZ2mbaMfO3aMn/70p/Tu3ZsxY8YQGxvLkSNHAJgzZw533XUXQ4YMobS0lIEDBzJo0CDKy8sZPnw4d955JwALFy4kODiYDRs2MGjQIG666SYAUlNTiYuLM6trIiJtmBa0ffv2ZebMmXTv3p2CggJCQ0O5+eab2bx5M7fccgvBwcFkZWUxc+ZMGhoaaGhoYNasWWzbts29NTpy5Eg+/PBDxo8fT0VFBWFhYcyfP5+1a9ea1S0RkXZM20bv379/m6vAOhIbG3vRNomJiXzyySe+LE1ExKf84/CeiIgfU9CKiBhMQSsiYjAFrYiIwRS0IiIGU9CKiBhMQSsiYjD/uNZN5CLKysra3PPCV5xOJ0VFRYSEhBhyaWhERASxsbE+X69cXhS04vfKysoYMXw4DWfOmF2K10K6d6fw4EGFbRenoBW/d+zYMRrOnOGV1OkM7We7+BsuE0XVx3kwYzPHjh1T0HZxClrpMob2szE6tq/ZZYi0o4NhIiIGU9CKiBhMQSsiYjAFrYiIwRS0IiIGU9CKiBhMQSsiYjAFrYiIwRS0IiIGU9CKiBhMQSsiYjBTg/bXv/418fHx9OrVi549e5KYmEhOTk6bNrW1tcydOxebzUZISAhTp06lsLCwTZv8/HymTJlCSEgINpuNefPmcfLkyc7siojIeZkatM899xyHDh3iqquu4ptvviEnJ4dbb72Vw4cPu9vMmjWL1157DZfLRUREBJmZmSQnJ3P8+HEAHA4HycnJZGVlERERQVNTE+vXr2fOnDlmdUtEpA1Tg3b58uXU1NSQl5fHnj17CAwMpKGhgQ8++ACA7du3Y7fbCQsLo6CggMOHDzN27FhqampYs2YNAGvWrMHhcDB+/HhKSkooKCggNDSUrKysdlvHIiJmMPU2iUuXLnV/P3z4cHr06EFtbS0ulwsAu90OwLhx4+jfvz8A06dPJzc3F7vdzhNPPOFuM23aNAIDA4mKimLs2LHukJ44cWK7n9vY2EhjY6N7uq6uDmi5m77T6fRZ/3y5rs7m67Ewkr/UeT7+NNZGcTqduFwuvxoHb2q9bO5H+84771BbW0tYWBizZs0CoKqqCgCb7V83c46MjASgsrLS4zbftXLlStLT09vN37VrF6GhoZfaFbeioiKfrauz5eXl0dDQYHYZHvHncQb/GmujuFwuysrKAAgI8I9j9PX19R63vSyC9qOPPmLevHkEBgby2muvER0dfd62zc3NF13fxdosXryYBQsWuKfr6uqIiYkhISGB8PBwzwu/iJCQEJ+tq7ONGTOG+Ph4s8vwiD+PM/jXWBuldetwwoQJhjybzQitn4Q9YXqPtm3bxsyZMzl37hwZGRltDmJFRUUBtHnonsPhAHCHcVRUFEVFRRds811WqxWr1dpuflBQkE9/yf7yB9MRX4+FkfylzvPxp7E2UkBAgF+NhTd1mrqNvnnzZmbMmIHT6eQvf/kLP//5z9ssT0pKAiA3N5fq6mqcTidbtmxps6z169atW2lqaqKqqorc3Nw2y0REzGRq0N5+++00NjbSo0cPnn/+eW688UZuvPFGli9fDkBiYiKJiYmcPn2aESNGMHDgQHJzc4mMjCQtLQ2AtLQ0bDYbu3fvZsCAAYwcOZKGhgaSk5M7PBAmItLZTA3ac+fOAXDixAl2797tfhUXFwNgsVjYtGkTKSkpQMsuhMmTJ5OdnU1ERAQAffr0ITs7m8mTJ7t3H6SmprJx40YTeiQi0p6pO0M8ObDVu3dvMjIyLthm1KhRZGVl+agqERHf8o/zKERE/JiCVkTEYApaERGDKWhFRAymoBURMZiCVkTEYApaERGDKWhFRAymoBURMZiCVkTEYApaERGDKWhFRAymoBURMZiCVkTEYApaERGDKWhFRAymoBURMZh/PG5SRC4bZWVlbZ467QtOp5OioiJCQkIMeQpuREQEsbGxPl+vpxS0IuKxsrIyRgwfTsOZM2aX4pWQ7t0pPHjQtLBV0IqIx44dO0bDmTO8kjqdof1sZpfjkaLq4zyYsZljx44paEXEfwztZ2N0bF+zy/Abph4M27BhAzfddBNWqxWLxUJSUlKb5bW1tcydOxebzUZISAhTp06lsLCwTZv8/HymTJlCSEgINpuNefPmcfLkyU7shYjIhZkatDk5Oezfvx+breOPILNmzeK1117D5XIRERFBZmYmycnJHD9+HACHw0FycjJZWVlERETQ1NTE+vXrmTNnTmd2Q0TkgkwN2iVLllBbW8t9993Xbtn27dux2+2EhYVRUFDA4cOHGTt2LDU1NaxZswaANWvW4HA4GD9+PCUlJRQUFBAaGkpWVhY5OTmd3R0RkQ6Zuo82MjLyvMvsdjsA48aNo3///gBMnz6d3Nxc7HY7TzzxhLvNtGnTCAwMJCoqirFjx7pDeuLEiR2uu7GxkcbGRvd0XV0d0HKKidPp9EHPcK/PX/l6LIzkL3Wej8a6c5j57/uyPRhWVVUF0Ga3QmswV1ZWetymIytXriQ9Pb3d/F27dhEaGnqJlf9LUVGRz9bV2fLy8mhoaDC7DI/48ziDxrqz+Hqc6+vrPW572QZtR5qbm33SZvHixSxYsMA9XVdXR0xMDAkJCYSHh19Sjd8WEhLis3V1tjFjxhAfH292GR7x53EGjXVn8fU4t34S9sRlG7RRUVEAba5AcTgcAERHR7vbFBUVXbBNR6xWK1artd38oKAgn16VYsQVLp3F12NhJH+p83w01p3DzH/fl+29DlpP9crNzaW6uhqn08mWLVvaLGv9unXrVpqamqiqqiI3N7fNMhERs5katKtXr2bw4MH84Q9/AGD37t0MHjyYpKQkEhMTSUxM5PTp04wYMYKBAweSm5tLZGQkaWlpAKSlpWGz2di9ezcDBgxg5MiRNDQ0kJycfN4DYSIinc3UoD1x4gTFxcXU1tYCcPbsWYqLizly5AgWi4VNmzaRkpICtOxCmDx5MtnZ2URERADQp08fsrOzmTx5snv3QWpqKhs3bjSlPyIiHTF1h8uTTz7Jk08+ed7lvXv3JiMj44LrGDVqFFlZWb4tTETEhy7bfbQiIl2FglZExGAKWhERgyloRUQMpqAVETGYglZExGAKWhERgyloRUQMpqAVETGYglZExGAKWhERgyloRUQMpqAVETGYglZExGAKWhERgyloRUQMpqAVETGYglZExGAKWhERgyloRUQMpqAVETFYlwja5uZmVqxYQVxcHFarlWuvvZb33nvP7LJERIAuErTp6eksXbqU6upq4uLi2L9/P7fffjvbt283uzQREf8P2oaGBp577jkANmzYQFFREY899hhNTU089dRTJlcnIgJBZhdwqT777DPq6+u54ooruO222wD46U9/yu9//3t27tyJ0+kkKKhtNxsbG2lsbHRPnzx5EoATJ07gdDp9VlttbS0An5dVU994zmfrNdJXNSeAltpPnDhhcjWe8cdxBo11ZzFqnOvq6oCWXZcX1ezn/vznPzcDzREREe55Bw4caAaageZ//vOf7d6zbNky93K99NJLr0t5lZeXXzSn/H6LtiPNF/kfZvHixSxYsMA97XK5OHHiBDabDYvFYnR5PlFXV0dMTAzl5eWEh4ebXU6XpXHuHP44zs3NzZw6dYqoqKiLtvX7oG3tZG1trXs3gcPhAMBqtRIREdHuPVarFavV2mZer169DK/VCOHh4X7zh+nPNM6dw9/GuWfPnh618/uDYePGjSM0NBSn08kHH3wA4D6166abbmq3f1ZEpLP5fdCGhIS4dwPMnj2bYcOG8fvf/56AgACWLl1qcnUiIl0gaAGefPJJnnrqKfr06UNJSQmjRo1iw4YNJCcnm12aYaxWK8uWLWu3C0R8S+PcObr6OFuaL3bkSERELkmX2KIVEbmcKWhFRAymoBURMZiCVkTEYApaP7NhwwZuuukmrFYrFouFpKQks0vqkn79618THx9Pr1696NmzJ4mJieTk5JhdVpe0ZMkShgwZQkhICL169eLGG29k06ZNZpflUwpaP5OTk8P+/fux2Wxml9KlPffccxw6dIirrrqKb775hpycHG699VYOHz5sdmldTmZmJk6nkxEjRmC1Wtm9ezd33HEH+fn5ZpfmMwpaP7NkyRJqa2u57777zC6lS1u+fDk1NTXk5eWxZ88eAgMDaWhocF99KL6Tk5NDSUkJe/bs4fDhw4SGhtLU1MTevXvNLs1nFLR+JjIyksDAQLPL6PKWLl1KWFgYAMOHD6dHjx5Ayw2IxLesVivLly/nhhtuYODAgdTX1xMYGMj1119vdmk+oxsBiFzEO++8Q21tLWFhYcyaNcvscrqk4uJiPvvsMwC6devGG2+8wdVXX21yVb6jLVqRC/joo4+YN28egYGBvPbaa0RHR5tdUpeUkZHB2bNn+fvf/05wcDBpaWkUFhaaXZbPKGhFzmPbtm38+Mc/5uzZs2RkZDBnzhyzS+rSrFYrkyZNYsqUKXz99desW7fO7JJ8RkEr0oHNmzczY8YMnE4nf/nLX/j5z39udkldUkVFBe+99577Zv1ff/01e/bsAVqeB9hV6KYyfmb16tWsXr2a48ePU1tbS3BwMNHR0Vx55ZXY7Xazy+syrFYr586do3fv3gwZMsQ9f/r06TzxxBMmVta15OXlcd1119GrVy/i4uIoLi7m9OnTAHzwwQfccsstJlfoGzoY5mdOnDhBcXGxe/rs2bMUFxf79KGSAufOtTx48MSJE+zevds9f/jw4WaV1CX17duXmTNnsnv3bgoKCujduzc33ngj8+fP7zIhC9qiFRExnPbRiogYTEErImIwBa2IiMEUtCIiBlPQiogYTEErImIwBa2IiMEUtCI+YLfbsVgsXHXVVWaXIpchBa10eVdddRUWiwWLxUJAQAB9+vRh2rRp7N+/3+zS5AdCl+DKD8aAAQPo3bs3BQUFbN26lQMHDlBaWorFYjG7NOnitEUrPxiPP/44ubm5bN68GYDy8nIqKyvZuXMnEyZMwGazccUVVxATE8NvfvMbvvnmGwCOHDni3iLesmULw4YNIzw8nHvvvZezZ892+LOOHDlC3759sVgsPPvss53WR7k8KWjlBys4OJgf/ehHfPnll+zdu5c+ffowaNAgKioqePbZZ3nuuefavWf27NkAnDp1ijfffJP//u//btfm5MmTTJ8+naNHj/LYY4+xaNEiw/silzcFrfxgrFq1irFjxzJ9+nS6devG888/T2hoKFOmTOHo0aMUFhZy8OBBfvOb3wDw3nvvtVvHSy+9xKFDh7jjjjsA2j2C3Ol0MmfOHAoKCvjZz37GCy+8YHzH5LKnfbTyg1FSUkJJSQkAsbGxJCYmAi23mnzooYf4xz/+gcPhcN+E+ujRo+3W0RqwQ4cOBcDhcLRZXllZSWVlJaNHjyYjI0P7fwXQFq38gKxdu5bq6mpuuOEGysrKSElJASAlJYW//e1vnD59muuvv54BAwYA0NTU1G4dPXv2BCAoqGUb5bt3GbVarQQEBHDgwAEyMzON7I74EQWt/KD07duXF198EYC9e/fy0UcfsW/fPgDWrVvHZ599dkk3nO7Xrx/PPPMMLpeLu+++m4KCAp/ULf5NQSs/OBMmTOD6668H4OWXX2bEiBEApKWlMXz4cN56661LWv+iRYu44447qKurY8aMGRw/fvySaxb/pqCVH6SHH34YaDng9eKLL3Lttdficrm4+uqrWbx48SWv/7XXXuOaa66huLiYOXPmuE8Vkx8mPcpGRMRg2qIVETGYglZExGAKWhERgyloRUQMpqAVETGYglZExGAKWhERgyloRUQMpqAVETGYglZExGAKWhERgyloRUQM9v8Agnjo7wjyJbQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 349.469x349.469 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_m9 = df.loc[df.csd3_path.str.contains('M9')]\n",
    "df_m9['rank'] = df_m9['rank'].astype(str)\n",
    "df_m9 = df_m9.groupby('rank').name.count()\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(COLUMN_WIDTH_INCHES, COLUMN_WIDTH_INCHES))\n",
    "\n",
    "sns.barplot(df_m9, ax=ax, **bar_params)\n",
    "\n",
    "ax.set_xlabel('Rank')\n",
    "ax.set_ylabel('Shot Count')\n",
    "ax.grid(**grid_params)\n",
    "ax.set_axisbelow(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 30000)\n",
       "Coordinates:\n",
       "  * time     (time) float32 -2.0 -2.0 -2.0 -1.999 -1.999 ... 3.999 3.999 4.0 4.0\n",
       "Data variables:\n",
       "    data     (time) float32 dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;\n",
       "    error    (time) float32 dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;\n",
       "Attributes: (12/19)\n",
       "    created:       2024-03-01T15:16:24.196838\n",
       "    dataset_uuid:  29ea843c-bdc6-5311-9632-4c593275db84\n",
       "    description:   Plasma Current\n",
       "    file_name:     None\n",
       "    format:        None\n",
       "    identifier:    81ee8587-4cd8-5a32-bc9b-b1dcf7277005\n",
       "    ...            ...\n",
       "    shot_id:       30110\n",
       "    source:        AMC\n",
       "    status:        1\n",
       "    time_index:    0\n",
       "    type:          Analysed\n",
       "    units:         kA</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-15900bf8-2bc4-456b-80cc-30e3fd84b246' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-15900bf8-2bc4-456b-80cc-30e3fd84b246' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 30000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-075621e7-b945-4bba-b559-2d4a703f1d8e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-075621e7-b945-4bba-b559-2d4a703f1d8e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-2.0 -2.0 -2.0 ... 3.999 4.0 4.0</div><input id='attrs-995934aa-ba1b-4c95-9d16-682fc3df0d26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-995934aa-ba1b-4c95-9d16-682fc3df0d26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af993f59-7970-4b78-a341-d0a48b67de1f' class='xr-var-data-in' type='checkbox'><label for='data-af993f59-7970-4b78-a341-d0a48b67de1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([-2.      , -1.9998  , -1.9996  , ...,  3.999399,  3.9996  ,  3.999799],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d496bb17-5ad8-44d7-9aff-659a39a76f87' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d496bb17-5ad8-44d7-9aff-659a39a76f87' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;</div><input id='attrs-199e229b-a09d-49fb-8047-cb6b98309ddc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-199e229b-a09d-49fb-8047-cb6b98309ddc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e46773b3-cc6d-468b-aa78-7df98922fec1' class='xr-var-data-in' type='checkbox'><label for='data-e46773b3-cc6d-468b-aa78-7df98922fec1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (30000,) </td>\n",
       "                        <td> (30000,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >30000</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(30000,), meta=np.ndarray&gt;</div><input id='attrs-c94abe08-b3f8-47f0-a904-6dcd1cb7f106' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c94abe08-b3f8-47f0-a904-6dcd1cb7f106' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-825f026b-8663-40a6-85ee-4d52c7caaa81' class='xr-var-data-in' type='checkbox'><label for='data-825f026b-8663-40a6-85ee-4d52c7caaa81' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                        <td> 117.19 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (30000,) </td>\n",
       "                        <td> (30000,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >30000</text>\n",
       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5f29d3cb-eb55-484b-a9a3-c2950a455782' class='xr-section-summary-in' type='checkbox'  ><label for='section-5f29d3cb-eb55-484b-a9a3-c2950a455782' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f5ae6762-aa6d-42f8-ba14-4cbec76f4e20' class='xr-index-data-in' type='checkbox'/><label for='index-f5ae6762-aa6d-42f8-ba14-4cbec76f4e20' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ -2.000000238418579,  -1.999800205230713, -1.9996002912521362,\n",
       "         -1.99940025806427, -1.9992002248764038, -1.9990001916885376,\n",
       "        -1.998800277709961, -1.9986002445220947, -1.9984002113342285,\n",
       "       -1.9982002973556519,\n",
       "       ...\n",
       "         3.997999429702759,   3.998199701309204,   3.998399496078491,\n",
       "        3.9985997676849365,  3.9987995624542236,   3.998999834060669,\n",
       "         3.999199628829956,   3.999399423599243,  3.9995996952056885,\n",
       "        3.9997994899749756],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;time&#x27;, length=30000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4ea74a61-3e25-4d31-86fc-2bdd08cd1c2c' class='xr-section-summary-in' type='checkbox'  ><label for='section-4ea74a61-3e25-4d31-86fc-2bdd08cd1c2c' class='xr-section-summary' >Attributes: <span>(19)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created :</span></dt><dd>2024-03-01T15:16:24.196838</dd><dt><span>dataset_uuid :</span></dt><dd>29ea843c-bdc6-5311-9632-4c593275db84</dd><dt><span>description :</span></dt><dd>Plasma Current</dd><dt><span>file_name :</span></dt><dd>None</dd><dt><span>format :</span></dt><dd>None</dd><dt><span>identifier :</span></dt><dd>81ee8587-4cd8-5a32-bc9b-b1dcf7277005</dd><dt><span>label :</span></dt><dd>Plasma Current</dd><dt><span>mds_name :</span></dt><dd>\\TOP.ANALYSED.AMC.PLASMA:CURRENT</dd><dt><span>name :</span></dt><dd>AMC_PLASMA CURRENT</dd><dt><span>pass_ :</span></dt><dd>0</dd><dt><span>rank :</span></dt><dd>1</dd><dt><span>shape :</span></dt><dd>[30000]</dd><dt><span>shot :</span></dt><dd>30110</dd><dt><span>shot_id :</span></dt><dd>30110</dd><dt><span>source :</span></dt><dd>AMC</dd><dt><span>status :</span></dt><dd>1</dd><dt><span>time_index :</span></dt><dd>0</dd><dt><span>type :</span></dt><dd>Analysed</dd><dt><span>units :</span></dt><dd>kA</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 30000)\n",
       "Coordinates:\n",
       "  * time     (time) float32 -2.0 -2.0 -2.0 -1.999 -1.999 ... 3.999 3.999 4.0 4.0\n",
       "Data variables:\n",
       "    data     (time) float32 dask.array<chunksize=(30000,), meta=np.ndarray>\n",
       "    error    (time) float32 dask.array<chunksize=(30000,), meta=np.ndarray>\n",
       "Attributes: (12/19)\n",
       "    created:       2024-03-01T15:16:24.196838\n",
       "    dataset_uuid:  29ea843c-bdc6-5311-9632-4c593275db84\n",
       "    description:   Plasma Current\n",
       "    file_name:     None\n",
       "    format:        None\n",
       "    identifier:    81ee8587-4cd8-5a32-bc9b-b1dcf7277005\n",
       "    ...            ...\n",
       "    shot_id:       30110\n",
       "    source:        AMC\n",
       "    status:        1\n",
       "    time_index:    0\n",
       "    type:          Analysed\n",
       "    units:         kA"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import zarr\n",
    "import s3fs\n",
    "import xarray as xr\n",
    "\n",
    "access_key = \"PZACJ5JF2XUPKC07F59V\"\n",
    "secret_key = \"SoWr0W6OtA2MB7Si8AXpFtRe4sBYxZCQgsZ44K5B\"\n",
    "ENDPOINT_URL = 'https://s3.echo.stfc.ac.uk'\n",
    "s3 = s3fs.S3FileSystem(anon=False, key=access_key, secret=secret_key, client_kwargs={'endpoint_url': ENDPOINT_URL})\n",
    "store = zarr.storage.FSStore('s3://mast/AMC/AMC_PLASMA-CURRENT.zarr', fs=s3)\n",
    "ds = xr.open_zarr(store, '30110')\n",
    "plt.plot(ds.time, ds.data)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['mast/AMC_PLASMA-CURRENT.zarr']"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "s3 = s3fs.S3FileSystem(anon=False, key=access_key, secret=secret_key, client_kwargs={'endpoint_url': ENDPOINT_URL})\n",
    "s3.ls('s3://mast')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "ename": "PermissionError",
     "evalue": "An error occurred (AccessDenied) when calling the ListObjectsV2 operation: Unknown",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mClientError\u001b[0m                               Traceback (most recent call last)",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/s3fs/core.py:706\u001b[0m, in \u001b[0;36mS3FileSystem._lsdir\u001b[0;34m(self, path, refresh, max_items, delimiter, prefix, versions)\u001b[0m\n\u001b[1;32m    705\u001b[0m files \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m--> 706\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iterdir(\n\u001b[1;32m    707\u001b[0m     bucket,\n\u001b[1;32m    708\u001b[0m     max_items\u001b[38;5;241m=\u001b[39mmax_items,\n\u001b[1;32m    709\u001b[0m     delimiter\u001b[38;5;241m=\u001b[39mdelimiter,\n\u001b[1;32m    710\u001b[0m     prefix\u001b[38;5;241m=\u001b[39mprefix,\n\u001b[1;32m    711\u001b[0m     versions\u001b[38;5;241m=\u001b[39mversions,\n\u001b[1;32m    712\u001b[0m ):\n\u001b[1;32m    713\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m c[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtype\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdirectory\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/s3fs/core.py:756\u001b[0m, in \u001b[0;36mS3FileSystem._iterdir\u001b[0;34m(self, bucket, max_items, delimiter, prefix, versions)\u001b[0m\n\u001b[1;32m    749\u001b[0m it \u001b[38;5;241m=\u001b[39m pag\u001b[38;5;241m.\u001b[39mpaginate(\n\u001b[1;32m    750\u001b[0m     Bucket\u001b[38;5;241m=\u001b[39mbucket,\n\u001b[1;32m    751\u001b[0m     Prefix\u001b[38;5;241m=\u001b[39mprefix,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    754\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mreq_kw,\n\u001b[1;32m    755\u001b[0m )\n\u001b[0;32m--> 756\u001b[0m \u001b[38;5;28;01masync\u001b[39;00m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m it:\n\u001b[1;32m    757\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m l \u001b[38;5;129;01min\u001b[39;00m i\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCommonPrefixes\u001b[39m\u001b[38;5;124m\"\u001b[39m, []):\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/aiobotocore/paginate.py:30\u001b[0m, in \u001b[0;36mAioPageIterator.__anext__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m---> 30\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_request(current_kwargs)\n\u001b[1;32m     31\u001b[0m     parsed \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_extract_parsed_response(response)\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/aiobotocore/client.py:383\u001b[0m, in \u001b[0;36mAioBaseClient._make_api_call\u001b[0;34m(self, operation_name, api_params)\u001b[0m\n\u001b[1;32m    382\u001b[0m     error_class \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexceptions\u001b[38;5;241m.\u001b[39mfrom_code(error_code)\n\u001b[0;32m--> 383\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m error_class(parsed_response, operation_name)\n\u001b[1;32m    384\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n",
      "\u001b[0;31mClientError\u001b[0m: An error occurred (AccessDenied) when calling the ListObjectsV2 operation: Unknown",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mPermissionError\u001b[0m                           Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[73], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m s3 \u001b[38;5;241m=\u001b[39m s3fs\u001b[38;5;241m.\u001b[39mS3FileSystem(anon\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, client_kwargs\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mendpoint_url\u001b[39m\u001b[38;5;124m'\u001b[39m: ENDPOINT_URL})\n\u001b[0;32m----> 2\u001b[0m \u001b[43ms3\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mls\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43ms3://mast\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/fsspec/asyn.py:118\u001b[0m, in \u001b[0;36msync_wrapper.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    115\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m    116\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m    117\u001b[0m     \u001b[38;5;28mself\u001b[39m \u001b[38;5;241m=\u001b[39m obj \u001b[38;5;129;01mor\u001b[39;00m args[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 118\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msync\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/fsspec/asyn.py:103\u001b[0m, in \u001b[0;36msync\u001b[0;34m(loop, func, timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m    101\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m FSTimeoutError \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mreturn_result\u001b[39;00m\n\u001b[1;32m    102\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(return_result, \u001b[38;5;167;01mBaseException\u001b[39;00m):\n\u001b[0;32m--> 103\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m return_result\n\u001b[1;32m    104\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    105\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m return_result\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/fsspec/asyn.py:56\u001b[0m, in \u001b[0;36m_runner\u001b[0;34m(event, coro, result, timeout)\u001b[0m\n\u001b[1;32m     54\u001b[0m     coro \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mwait_for(coro, timeout\u001b[38;5;241m=\u001b[39mtimeout)\n\u001b[1;32m     55\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 56\u001b[0m     result[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m coro\n\u001b[1;32m     57\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m ex:\n\u001b[1;32m     58\u001b[0m     result[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m ex\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/s3fs/core.py:985\u001b[0m, in \u001b[0;36mS3FileSystem._ls\u001b[0;34m(self, path, detail, refresh, versions)\u001b[0m\n\u001b[1;32m    983\u001b[0m     files \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lsbuckets(refresh)\n\u001b[1;32m    984\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 985\u001b[0m     files \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lsdir(path, refresh, versions\u001b[38;5;241m=\u001b[39mversions)\n\u001b[1;32m    986\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m files \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m path:\n\u001b[1;32m    987\u001b[0m         files \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lsdir(\n\u001b[1;32m    988\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_parent(path), refresh\u001b[38;5;241m=\u001b[39mrefresh, versions\u001b[38;5;241m=\u001b[39mversions\n\u001b[1;32m    989\u001b[0m         )\n",
      "File \u001b[0;32m~/miniconda3/envs/mast-book/lib/python3.11/site-packages/s3fs/core.py:719\u001b[0m, in \u001b[0;36mS3FileSystem._lsdir\u001b[0;34m(self, path, refresh, max_items, delimiter, prefix, versions)\u001b[0m\n\u001b[1;32m    717\u001b[0m     files \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m dirs\n\u001b[1;32m    718\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ClientError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m--> 719\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m translate_boto_error(e)\n\u001b[1;32m    721\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m delimiter \u001b[38;5;129;01mand\u001b[39;00m files \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m versions:\n\u001b[1;32m    722\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdircache[path] \u001b[38;5;241m=\u001b[39m files\n",
      "\u001b[0;31mPermissionError\u001b[0m: An error occurred (AccessDenied) when calling the ListObjectsV2 operation: Unknown"
     ]
    }
   ],
   "source": [
    "\n",
    "s3 = s3fs.S3FileSystem(anon=True, client_kwargs={'endpoint_url': ENDPOINT_URL})\n",
    "s3.ls('s3://mast')"
   ]
  }
 ],
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    "name": "ipython",
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