notebooks/ds3231_example.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from meerkat import ds3231, parser\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "from importlib import reload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "rtc = ds3231.DS3231(bus_n=1, bus_addr=0x68)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "rtc.save_time(YY=2020, MM=10, DD=14, hh=22, mm=6, ss=0, micro=0, tz=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2020, 12, 13, 21, 42, 25)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtc.get_time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtc.get_temp()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'{\"description\": \"test_1\", \"sample_n\": 0, \"rtc_time\": \"2020-12-13 21:42:25\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:23.914827\"}'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtc.publish(description=\"test_1\", n=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['{\"description\": \"test_1\", \"sample_n\": 0, \"rtc_time\": \"2020-12-13 21:42:25\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:23.932123\"}',\n",
       " '{\"description\": \"test_1\", \"sample_n\": 0, \"rtc_time\": \"2020-12-13 21:42:28\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:26.937450\"}']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtc.publish(description=\"test_1\", n=2, delay=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# default writer format is CSV, switch to JSON\n",
    "rtc.writer_output = 'json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': 'DS3231', 'urls': 'https://datasheets.maximintegrated.com/en/ds/DS3231.pdf', 'manufacturer': 'Adafruit Industries', 'header': ['description', 'sample_n', 'rtc_time', 'temp_C'], 'dtype': ['str', 'int', 'str', 'float'], 'units': [None, 'count', 'datetime', 'degrees Celcius'], 'accuracy': [None, 1, '+/- 3.5 ppm', '+/- 3.0'], 'precision': [None, 1, '1 second', 0.25], 'bus_n': 1, 'bus_addr': '0x68', 'description': 'Adafruit DS3221 Precision RTC', 'rtc_time_source': '%Y-%m-%d %H:%M:%S'}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtc.json_writer.metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# writer method with description and sample number\n",
    "rtc.write(description='test_2', n=6, delay=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2020_12_13_20_43_30_ds3231.jsontxt'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rtc.json_writer.path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"description\": \"test_2\", \"sample_n\": 0, \"rtc_time\": \"2020-12-13 21:42:31\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:30.041333\"}\n",
      "{\"description\": \"test_2\", \"sample_n\": 1, \"rtc_time\": \"2020-12-13 21:42:32\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:31.045605\"}\n",
      "{\"description\": \"test_2\", \"sample_n\": 2, \"rtc_time\": \"2020-12-13 21:42:33\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:32.049301\"}\n",
      "{\"description\": \"test_2\", \"sample_n\": 3, \"rtc_time\": \"2020-12-13 21:42:34\", \"temp_C\": 20.0, \"std_time_ms\": \"2020-12-13 20:43:33.052928\"}\n"
     ]
    }
   ],
   "source": [
    "with open(rtc.json_writer.path, 'r') as f:\n",
    "    for _ in range(4):\n",
    "        print(f.readline().strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# switch back to CSV format\n",
    "rtc.writer_output = 'csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "rtc.write(description='test_3', n=6, delay=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "m, df = parser.csv_resource(rtc.csv_writer.path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"rtc_datetime64_ns\"] = pd.to_datetime(df.rtc_time)\n",
    "df.temp_C = df.temp_C.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "std_time_ms                  object\n",
       "description                  object\n",
       "sample_n                      int64\n",
       "rtc_time                     object\n",
       "temp_C                      float64\n",
       "datetime64_ns        datetime64[ns]\n",
       "rtc_datetime64_ns    datetime64[ns]\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>std_time_ms</th>\n",
       "      <th>description</th>\n",
       "      <th>sample_n</th>\n",
       "      <th>rtc_time</th>\n",
       "      <th>temp_C</th>\n",
       "      <th>datetime64_ns</th>\n",
       "      <th>rtc_datetime64_ns</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-12-13 20:43:36.159805</td>\n",
       "      <td>test_3</td>\n",
       "      <td>0</td>\n",
       "      <td>2020-12-13 21:42:37</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-13 20:43:36.159805</td>\n",
       "      <td>2020-12-13 21:42:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-12-13 20:43:37.163392</td>\n",
       "      <td>test_3</td>\n",
       "      <td>1</td>\n",
       "      <td>2020-12-13 21:42:38</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-13 20:43:37.163392</td>\n",
       "      <td>2020-12-13 21:42:38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-12-13 20:43:38.166982</td>\n",
       "      <td>test_3</td>\n",
       "      <td>2</td>\n",
       "      <td>2020-12-13 21:42:39</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-13 20:43:38.166982</td>\n",
       "      <td>2020-12-13 21:42:39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-12-13 20:43:39.170642</td>\n",
       "      <td>test_3</td>\n",
       "      <td>3</td>\n",
       "      <td>2020-12-13 21:42:40</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-13 20:43:39.170642</td>\n",
       "      <td>2020-12-13 21:42:40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-12-13 20:43:40.174216</td>\n",
       "      <td>test_3</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-12-13 21:42:41</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-13 20:43:40.174216</td>\n",
       "      <td>2020-12-13 21:42:41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-12-13 20:43:41.177811</td>\n",
       "      <td>test_3</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-12-13 21:42:42</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2020-12-13 20:43:41.177811</td>\n",
       "      <td>2020-12-13 21:42:42</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  std_time_ms description  sample_n             rtc_time  \\\n",
       "0  2020-12-13 20:43:36.159805      test_3         0  2020-12-13 21:42:37   \n",
       "1  2020-12-13 20:43:37.163392      test_3         1  2020-12-13 21:42:38   \n",
       "2  2020-12-13 20:43:38.166982      test_3         2  2020-12-13 21:42:39   \n",
       "3  2020-12-13 20:43:39.170642      test_3         3  2020-12-13 21:42:40   \n",
       "4  2020-12-13 20:43:40.174216      test_3         4  2020-12-13 21:42:41   \n",
       "5  2020-12-13 20:43:41.177811      test_3         5  2020-12-13 21:42:42   \n",
       "\n",
       "   temp_C              datetime64_ns   rtc_datetime64_ns  \n",
       "0    20.0 2020-12-13 20:43:36.159805 2020-12-13 21:42:37  \n",
       "1    20.0 2020-12-13 20:43:37.163392 2020-12-13 21:42:38  \n",
       "2    20.0 2020-12-13 20:43:38.166982 2020-12-13 21:42:39  \n",
       "3    20.0 2020-12-13 20:43:39.170642 2020-12-13 21:42:40  \n",
       "4    20.0 2020-12-13 20:43:40.174216 2020-12-13 21:42:41  \n",
       "5    20.0 2020-12-13 20:43:41.177811 2020-12-13 21:42:42  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[[\"rtc_datetime64_ns\", \"temp_C\"]].plot(x=\"rtc_datetime64_ns\", marker=\"x\");"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}