TB3 Power Usage.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TB3 Power Usage Measurements\n",
    "\n",
    "Current readings taken with a 34465A Digital Multimeter. The unit was indoors at the Auckland Sensium office."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define units\n",
    "A = 1\n",
    "mA = 1e-3\n",
    "uA = 1e-6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sleep current readings\n",
    "\n",
    "The below readings were taken with the unit sleeping with VWAKE off (`peripheralsOff`), on (`peripheralsNone`), and with VWAKE on in various accelerometer states. Temperature chip is off in all readings.\n",
    "\n",
    "There are traces taken for most of the accelerometer states to confirm that the readings are sensible. (Also because I couldn't find a way to get a good average current draw from the ammeter)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "peripheralsOff = 17.3 * uA\n",
    "peripheralsNone = 21 * uA\n",
    "peripheralsAcc_LOW_1Hz = 38 * uA\n",
    "peripheralsAcc_LOW_2Hz = 52 * uA\n",
    "peripheralsAcc_LOW_5Hz = 87 * uA\n",
    "peripheralsAcc_LOW_10Hz = 145 * uA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "code_folding": [
     0
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   "source": [
    "# Define graph display\n",
    "\n",
    "import pandas as pd\n",
    "import plotly.offline as py\n",
    "import plotly.graph_objs as go\n",
    "import numpy as np\n",
    "\n",
    "py.init_notebook_mode(connected=True)\n",
    "\n",
    "def plot(graphs, **kws):\n",
    "    layout = go.Layout(**kws)\n",
    "    fig = go.Figure(data=graphs, layout=layout)\n",
    "    py.iplot(fig)\n",
    "\n",
    "def load(csvname):\n",
    "    with open(csvname) as csv:\n",
    "        csv.readline() # drop Start date line\n",
    "        csv.readline() # drop Sample interval line\n",
    "        return pd.read_csv(csv)\n",
    "\n",
    "def series(frame, **kws):\n",
    "    kws.update({\n",
    "        'xaxis': { 'title': 'Time (S)' },\n",
    "        'yaxis': { 'title': 'Current Draw (A)'},\n",
    "    })\n",
    "    time = frame['Reading #'] * 0.010\n",
    "    plot([go.Scatter(x=time, y=frame['Reading'])], **kws)\n",
    "\n",
    "def stats(frame):\n",
    "    # Average here is calculated by simply summing all the readings and dividing by the\n",
    "    # number of readings. This naive is appropriate since each reading represents the same\n",
    "    # time period, and we want the average current draw over time\n",
    "    print(\"Average Current Draw: %d uA\" % (np.average(frame['Reading']) * 1000 * 1000))\n",
    "\n"
   ]
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       "}\n",
       "});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){if (document.getElementById(\"3f0c44c8-4c6f-4e20-a927-0fcb5e8b14a3\")) {window._Plotly.Plots.resize(document.getElementById(\"3f0c44c8-4c6f-4e20-a927-0fcb5e8b14a3\"));};})</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Current Draw: 38 uA\n"
     ]
    }
   ],
   "source": [
    "data = load('Standby_Acc1HzTmpOff_2.csv')\n",
    "series(data, title='Standby with Accelerometer 1Hz; Temp Off')\n",
    "stats(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Current Draw: 52 uA\n"
     ]
    }
   ],
   "source": [
    "data = load('Standby_Acc2HzTmpOff.csv')\n",
    "series(data, title='Standby with Accelerometer 2Hz; Temp Off')\n",
    "stats(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       "}\n",
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     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Current Draw: 87 uA\n"
     ]
    }
   ],
   "source": [
    "data = load('Standby_Acc5HzTmpOff.csv')\n",
    "series(data, title='Standby with Accelerometer 5Hz; Temp Off')\n",
    "stats(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When downloading data from the Ammeter we consistently get a single sample that is silly large (9e37 A):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Reading #</th>\n",
       "      <th>Reading</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>430</td>\n",
       "      <td>9.900000e+37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Reading #       Reading\n",
       "429        430  9.900000e+37"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = load('FullCycle.csv')\n",
    "data[data['Reading'] > 1.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We discard this sample, which shouldn't affect the results much."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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\"type\": \"scatter\", \"uid\": \"57b31d14-f551-4124-9a9d-455cca1c583f\"}], {\"title\": {\"text\": \"Full Cycle\"}, \"xaxis\": {\"title\": {\"text\": \"Time (S)\"}}, \"yaxis\": {\"title\": {\"text\": \"Current Draw (A)\"}}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"}); \n",
       "}\n",
       "});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){if (document.getElementById(\"3acdd466-94c2-4f30-8891-237d2b0f2991\")) {window._Plotly.Plots.resize(document.getElementById(\"3acdd466-94c2-4f30-8891-237d2b0f2991\"));};})</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average Current Draw: 92026 uA\n"
     ]
    }
   ],
   "source": [
    "data = load('FullCycle.csv')\n",
    "data = data[data['Reading'] < 1.0]\n",
    "series(data, title='Full Cycle')\n",
    "stats(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remove the sleeping part of the trace (by trimming values below 30mA)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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     "text": [
      "Average Current Draw: 148319 uA\n"
     ]
    }
   ],
   "source": [
    "data = load('FullCycle.csv')\n",
    "data = data[data['Reading'] < 1.0] # cut bad points\n",
    "data = data[data['Reading'] > 0.03]\n",
    "series(data, title='Full Cycle (Trimmed)')\n",
    "stats(data)"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculation of TB3 Longevity\n",
    "\n",
    "We have a reading of a \"full cycle\", i.e. unit waking up, getting a GPS fix, then sending it's data. This was with a unit that had recently had a GPS fix (i.e. ephemerides were intact), but hadn't been primed with Assistance data (Online or Offline). The device was also indoors. This \"full cycle\" is therefore hopefully somewhere within the range of \"normal\" for the purpose of rough estimation.\n",
    "\n",
    "Using this \"full cycle\" we can calculate how many coulombs capturing a single point will consume. If we combine this usage with the sleep cost, and the battery vampiric drain then we should be able to estimate the longevity of a TB3 on batteries.\n",
    "\n",
    "Note the full cycle data was read at 10mS intervals, and the data is in the units of Amps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load the full cycle data, remove the bad sample, and trim out the sleeping part of the trace\n",
    "data = load('FullCycle.csv')\n",
    "data = data[data['Reading'] < 1.0]\n",
    "data = data[data['Reading'] > 0.03]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Amps are 1 coulomb per second.\n",
    "The area under the full cycle trace is the Amp.Seconds (i.e. Coulombs) of the wake cycle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.679816880766"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "CwakeCycle = np.sum(data['Reading']) * 0.01\n",
    "CwakeCycle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The battery is rated at 7600mAh."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27360.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Cbattery = 7.6 * 3600 # Amp.Seconds\n",
    "Cbattery"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.4523128684861306"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "def longevity(numPointsPerDay, sleepCurrent, vampiric=0.02, wakeCycle=CwakeCycle):\n",
    "    # charge for sleeping all day despite minor double charge when awake\n",
    "    CdaySleep = 86400 * sleepCurrent\n",
    "    CsendPoints = wakeCycle * numPointsPerDay\n",
    "    Cyearly = (CdaySleep + CsendPoints) * 365 + Cbattery * vampiric\n",
    "    return Cbattery / Cyearly\n",
    "\n",
    "longevity(5, peripheralsNone)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 25,
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       "    Plotly.newPlot(\"7b01c391-2bed-4de7-95c9-10d2b8ae4fdd\", [{\"name\": \"No peripherals\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], \"y\": [25.037226402414113, 11.231960688409048, 7.239935631726334, 5.341483745699077, 4.231818624636329, 3.5039015321293956, 2.989650378205553, 2.6070289904824366, 2.3112328271213003, 2.0757195713567973, 1.8837650307806932, 1.7243077043800212, 1.5897391414107813, 1.4746540679644127, 1.3751067537951973, 1.2881495286333653, 1.2115359807889101, 1.1435241247904318, 1.0827423424529292, 1.0280959199808186, 0.9787005279058602, 0.9338339978847103, 0.8929007822478972, 0.8554053682095121, 0.8209321205976918], \"type\": \"scatter\", \"uid\": \"10aed483-993c-4ba5-8547-f75532304668\"}, {\"name\": \"Acc 1Hz\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], \"y\": [15.673981191222573, 8.858092307931031, 6.173515976953636, 4.737689012747564, 3.843721992844916, 3.2335709688199614, 2.790593221046308, 2.4543619358651196, 2.190441378010928, 1.9777694015819605, 1.8027397356787445, 1.6561710482373768, 1.5316433881506233, 1.4245326420585753, 1.3314236448422938, 1.2497393280489397, 1.1774984901561987, 1.11315298805426, 1.0554755435611067, 1.003480711188007, 0.9563681088993488, 0.9134809233650845, 0.8742751007283626, 0.8382961447087588, 0.8051614172134098], \"type\": \"scatter\", \"uid\": \"84681683-e29b-49d1-8397-bc7b7b6ca089\"}, {\"name\": \"Acc 2Hz\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], \"y\": [12.509876218066895, 7.750257774971015, 5.614221337989624, 4.401210569128846, 3.619236888899001, 3.0732119255791774, 2.6703439935079873, 2.3608585942541094, 2.115659568296628, 1.9166011662948181, 1.7517795464115706, 1.6130613847602, 1.4947005377883082, 1.3925220983645614, 1.3034197074480096, 1.225034250713476, 1.1555419143503898, 1.0935105059611445, 1.0377996953624213, 0.9874902715511579, 0.9418330247681386, 0.9002111827009271, 0.8621123853518583, 0.8271074874396641, 0.7948343234951514], \"type\": \"scatter\", \"uid\": \"9439b04e-58b9-4573-9c02-40c1071524d3\"}, {\"name\": \"Acc 5Hz\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], \"y\": [8.314006913753117, 5.904230836138648, 4.577471964097529, 3.7375867222452523, 3.1581263306157075, 2.734223354326061, 2.4106510665435197, 2.155558845891055, 1.9492875611103666, 1.7790458301680607, 1.636151913726742, 1.5145059801027412, 1.4096967187838716, 1.3184548975498165, 1.2383062286603042, 1.1673435925808109, 1.1040733348278295, 1.0473089773863762, 0.9960961148648406, 0.9496583186048364, 0.9073574984152968, 0.8686644062434303, 0.8331363781743016, 0.8004003238722182, 0.7701395747330535], \"type\": \"scatter\", \"uid\": \"b306f042-f8cc-4386-aadc-fd2657158f76\"}, {\"name\": \"Acc 10Hz\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], \"y\": [5.343833497398397, 4.233293354767403, 3.504912497352271, 2.9903863392828383, 2.60758860900299, 2.3116726493502635, 2.076074318347067, 1.8840571956248908, 1.7245524970059696, 1.5899472144049103, 1.4748331038849432, 1.3752624324742844, 1.2882861396604475, 1.211656824232465, 1.1436317809021719, 1.0828388577376533, 1.0281829383964678, 0.9787793851834181, 0.9339057905195501, 0.8929664187568015, 0.8554656077525731, 0.8209876024549703, 0.7891810761856335, 0.7597471157660063, 0.7324297986701492], \"type\": \"scatter\", \"uid\": \"2fab9bfa-3382-4da7-98ac-fda8bf21eb2a\"}], {\"xaxis\": {\"title\": {\"text\": \"# Points Per Day\"}}, \"yaxis\": {\"title\": {\"text\": \"Longevity (years)\"}}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"}); \n",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph of longevity by points per day\n",
    "parms = {\n",
    "    'xaxis': { 'title': '# Points Per Day' },\n",
    "    'yaxis': { 'title': 'Longevity (years)'},\n",
    "}\n",
    "pointsPerDay = list(range(0, 25))\n",
    "plot([\n",
    "    go.Scatter(x=pointsPerDay, y=[longevity(p, peripheralsOff) for p in pointsPerDay], name='No peripherals'),\n",
    "    go.Scatter(x=pointsPerDay, y=[longevity(p, peripheralsAcc_LOW_1Hz) for p in pointsPerDay], name='Acc 1Hz'),\n",
    "    go.Scatter(x=pointsPerDay, y=[longevity(p, peripheralsAcc_LOW_2Hz) for p in pointsPerDay], name='Acc 2Hz'),\n",
    "    go.Scatter(x=pointsPerDay, y=[longevity(p, peripheralsAcc_LOW_5Hz) for p in pointsPerDay], name='Acc 5Hz'),\n",
    "    go.Scatter(x=pointsPerDay, y=[longevity(p, peripheralsAcc_LOW_10Hz) for p in pointsPerDay], name='Acc 10Hz'),\n",
    "], **parms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Projected longevity (for improved wake time)\n",
    "\n",
    "If we improve the battery usage (by reducing the amount of time spent awake), then here are the projected longevities:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
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2.530587917249995, 2.4543619358651187, 2.382593810287387, 2.3149035933870885, 2.250953322887427, 2.1904413780109278, 2.1330977225513643, 2.078679876074868, 2.0269694864567978, 1.9777694015819596, 1.9309011574056048, 1.886202814906991, 1.8435270906791554], \"type\": \"scatter\", \"uid\": \"5f49d5f0-6c64-4be7-a48b-4011178ac023\"}, {\"name\": \"Acc 2Hz\", \"x\": [0.1, 0.15000000000000002, 0.20000000000000004, 0.25000000000000006, 0.30000000000000004, 0.3500000000000001, 0.40000000000000013, 0.45000000000000007, 0.5000000000000001, 0.5500000000000002, 0.6000000000000002, 0.6500000000000001, 0.7000000000000002, 0.7500000000000002, 0.8000000000000002, 0.8500000000000002, 0.9000000000000002, 0.9500000000000003, 1.0000000000000004, 1.0500000000000003, 1.1000000000000005, 1.1500000000000004, 1.2000000000000004, 1.2500000000000004, 1.3000000000000005, 1.3500000000000005, 1.4000000000000006, 1.4500000000000006, 1.5000000000000004, 1.5500000000000005, 1.6000000000000005, 1.6500000000000006, 1.7000000000000006, 1.7500000000000007, 1.8000000000000007, 1.8500000000000008, 1.9000000000000008, 1.9500000000000006], \"y\": [9.570989555776384, 8.564930088741084, 7.750257774971015, 7.07710339561697, 6.511538864685779, 6.029678935791871, 5.614221337989624, 5.2523250618667365, 4.934259554523343, 4.6525166948308305, 4.401210569128845, 4.1756618050309156, 3.9721034844906478, 3.787469076735316, 3.619236888899001, 3.465314208849673, 3.3239498057566372, 3.1936670079919374, 3.073211925579176, 2.961512964083671, 2.857648857905348, 2.7608232023351915, 2.6703439935079865, 2.5856070638567457, 2.5060825743820243, 2.4313039252530153, 2.3608585942541085, 2.2943805230812164, 2.2315437547484405, 2.172057088647554, 2.1156595682966275, 2.0621166542624634, 2.0112169638707416, 1.9627694821318564, 1.9166011662948172, 1.8725548807061851, 1.830487610031521, 1.7902689080269092], \"type\": \"scatter\", \"uid\": \"3918df07-0dcb-4278-ba47-029ad4fb8daf\"}, {\"name\": \"Acc 5Hz\", \"x\": [0.1, 0.15000000000000002, 0.20000000000000004, 0.25000000000000006, 0.30000000000000004, 0.3500000000000001, 0.40000000000000013, 0.45000000000000007, 0.5000000000000001, 0.5500000000000002, 0.6000000000000002, 0.6500000000000001, 0.7000000000000002, 0.7500000000000002, 0.8000000000000002, 0.8500000000000002, 0.9000000000000002, 0.9500000000000003, 1.0000000000000004, 1.0500000000000003, 1.1000000000000005, 1.1500000000000004, 1.2000000000000004, 1.2500000000000004, 1.3000000000000005, 1.3500000000000005, 1.4000000000000006, 1.4500000000000006, 1.5000000000000004, 1.5500000000000005, 1.6000000000000005, 1.6500000000000006, 1.7000000000000006, 1.7500000000000007, 1.8000000000000007, 1.8500000000000008, 1.9000000000000008, 1.9500000000000006], \"y\": [6.9049085907182475, 6.365482155117897, 5.904230836138646, 5.505308822988415, 5.156881784775619, 4.849933010644532, 4.577471964097527, 4.333995420131409, 4.115111890325275, 3.917274384429374, 3.737586722245252, 3.573660815026804, 3.4235099256588484, 3.2854677525030356, 3.1581263306157075, 3.0402878354375362, 2.9309267883909946, 2.8291601361848606, 2.73422335432606, 2.645451205721438, 2.562262129679064, 2.484145486539653, 2.410651066543519, 2.341380407489467, 2.2759795675157943, 2.2141330762173665, 2.155558845891054, 2.100003869692576, 2.047240568304847, 1.9970636738548786, 1.9492875611103662, 1.9037439528035456, 1.8602799392909168, 1.8187562634343624, 1.77904583016806, 1.7410324071446606, 1.7046094884786924, 1.6696792981923168], \"type\": \"scatter\", \"uid\": \"424da1d7-1367-4a0a-96b4-df9dea228432\"}, {\"name\": \"Acc 10Hz\", \"x\": [0.1, 0.15000000000000002, 0.20000000000000004, 0.25000000000000006, 0.30000000000000004, 0.3500000000000001, 0.40000000000000013, 0.45000000000000007, 0.5000000000000001, 0.5500000000000002, 0.6000000000000002, 0.6500000000000001, 0.7000000000000002, 0.7500000000000002, 0.8000000000000002, 0.8500000000000002, 0.9000000000000002, 0.9500000000000003, 1.0000000000000004, 1.0500000000000003, 1.1000000000000005, 1.1500000000000004, 1.2000000000000004, 1.2500000000000004, 1.3000000000000005, 1.3500000000000005, 1.4000000000000006, 1.4500000000000006, 1.5000000000000004, 1.5500000000000005, 1.6000000000000005, 1.6500000000000006, 1.7000000000000006, 1.7500000000000007, 1.8000000000000007, 1.8500000000000008, 1.9000000000000008, 1.9500000000000006], \"y\": [4.724175670369088, 4.465283980554443, 4.233293354767403, 4.024217995795039, 3.8348224556518624, 3.6624530002790054, 3.504912497352271, 3.3603662626312705, 3.227270281499053, 3.1043158384499616, 2.9903863392828374, 2.88452330455132, 2.785899339267259, 2.6937964643944587, 2.6075886090029896, 2.526727359930297, 2.450730283110589, 2.379171290940635, 2.311672649350263, 2.2478983079247548, 2.1875483044365276, 2.1303540471503197, 2.0760743183470662, 2.024491873629947, 1.9754105359045042, 1.9286527020705346, 1.8840571956248902, 1.841477410451978, 1.8007797007540427, 1.7618419798657834, 1.7245524970059694, 1.6888087661501203, 1.6545166254019743, 1.621589408683968, 1.5899472144049098, 1.5595162581121076, 1.5302282980872637, 1.50202012447364], \"type\": \"scatter\", \"uid\": \"124f84ed-e1a2-4930-b813-b6ee80b7e36c\"}], {\"title\": {\"text\": \"5 Points per day longevity projection\"}, \"xaxis\": {\"title\": {\"text\": \"Proportion of full cycle usage\"}}, \"yaxis\": {\"title\": {\"text\": \"Longevity (years)\"}}}, {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"}); \n",
       "}\n",
       "});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){if (document.getElementById(\"eaeb7320-f258-4a45-b403-a89a3ba02516\")) {window._Plotly.Plots.resize(document.getElementById(\"eaeb7320-f258-4a45-b403-a89a3ba02516\"));};})</script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph of longevity by points per day\n",
    "parms = {\n",
    "    'title': '5 Points per day longevity projection',\n",
    "    'xaxis': { 'title': 'Proportion of full cycle usage' },\n",
    "    'yaxis': { 'title': 'Longevity (years)'},\n",
    "}\n",
    "proportion = np.arange(0.1, 2.0, 0.05)\n",
    "plot([\n",
    "    go.Scatter(x=proportion, y=[longevity(5, peripheralsOff, wakeCycle=CwakeCycle*p) for p in proportion], name='No peripherals'),\n",
    "    go.Scatter(x=proportion, y=[longevity(5, peripheralsAcc_LOW_1Hz, wakeCycle=CwakeCycle*p) for p in proportion], name='Acc 1Hz'),\n",
    "    go.Scatter(x=proportion, y=[longevity(5, peripheralsAcc_LOW_2Hz, wakeCycle=CwakeCycle*p) for p in proportion], name='Acc 2Hz'),\n",
    "    go.Scatter(x=proportion, y=[longevity(5, peripheralsAcc_LOW_5Hz, wakeCycle=CwakeCycle*p) for p in proportion], name='Acc 5Hz'),\n",
    "    go.Scatter(x=proportion, y=[longevity(5, peripheralsAcc_LOW_10Hz, wakeCycle=CwakeCycle*p) for p in proportion], name='Acc 10Hz'),\n",
    "], **parms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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