lotus/composer/chain-state.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "import json\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import hvplot.pandas\n",
    "import panel as pn\n",
    "\n",
    "STATE_FILE = './chain-state.ndjson'\n",
    "\n",
    "MINER_STATE_COL_RENAMES = {\n",
    "    'Info.MinerAddr': 'Miner',\n",
    "    'Info.MinerPower.MinerPower.RawBytePower': 'Info.MinerPowerRaw',\n",
    "    'Info.MinerPower.MinerPower.QualityAdjPower': 'Info.MinerPowerQualityAdj',\n",
    "    'Info.MinerPower.TotalPower.RawBytePower': 'Info.TotalPowerRaw',\n",
    "    'Info.MinerPower.TotalPower.QualityAdjPower': 'Info.TotalPowerQualityAdj',\n",
    "}\n",
    "\n",
    "MINER_NUMERIC_COLS = [\n",
    "    'Info.MinerPowerRaw',\n",
    "    'Info.MinerPowerQualityAdj',\n",
    "    'Info.TotalPowerRaw',\n",
    "    'Info.TotalPowerQualityAdj',\n",
    "    'Info.Balance',\n",
    "    'Info.CommittedBytes',\n",
    "    'Info.ProvingBytes',\n",
    "    'Info.FaultyBytes',\n",
    "    'Info.FaultyPercentage',\n",
    "    'Info.PreCommitDeposits',\n",
    "    'Info.LockedFunds',\n",
    "    'Info.AvailableFunds',\n",
    "    'Info.WorkerBalance',\n",
    "    'Info.MarketEscrow',\n",
    "    'Info.MarketLocked',\n",
    "]\n",
    "\n",
    "DERIVED_COLS = [\n",
    "    'CommittedSectors',\n",
    "    'ProvingSectors',\n",
    "]\n",
    "\n",
    "ATTO_FIL_COLS = [\n",
    "    'Info.Balance',\n",
    "    'Info.PreCommitDeposits',\n",
    "    'Info.LockedFunds',\n",
    "    'Info.AvailableFunds',\n",
    "    'Info.WorkerBalance',\n",
    "    'Info.MarketEscrow',\n",
    "    'Info.MarketLocked',\n",
    "]\n",
    "\n",
    "def atto_to_fil(x):\n",
    "    return float(x) * pow(10, -18)\n",
    "\n",
    "def chain_state_to_pandas(statefile):\n",
    "    chain = None\n",
    "    \n",
    "    with open(statefile, 'rt') as f:\n",
    "        for line in f.readlines():\n",
    "            j = json.loads(line)\n",
    "            chain_height = j['Height']\n",
    "            \n",
    "            miners = j['MinerStates']\n",
    "            for m in miners.values():\n",
    "                df = pd.json_normalize(m)\n",
    "                df['Height'] = chain_height\n",
    "                df.rename(columns=MINER_STATE_COL_RENAMES, inplace=True)\n",
    "                if chain is None:\n",
    "                    chain = df\n",
    "                else:\n",
    "                    chain = chain.append(df, ignore_index=True)\n",
    "    chain.fillna(0, inplace=True)\n",
    "    chain.set_index('Height', inplace=True)\n",
    "    \n",
    "    for c in ATTO_FIL_COLS:\n",
    "        chain[c] = chain[c].apply(atto_to_fil)\n",
    "    \n",
    "    for c in MINER_NUMERIC_COLS:\n",
    "        chain[c] = chain[c].apply(pd.to_numeric)\n",
    "            \n",
    "    # the Sectors.* fields are lists of sector ids, but we want to plot counts, so\n",
    "    # we pull the length of each list into a new column\n",
    "    chain['CommittedSectors'] = chain['Sectors.Committed'].apply(lambda x: len(x))\n",
    "    chain['ProvingSectors'] = chain['Sectors.Proving'].apply(lambda x: len(x))\n",
    "    return chain\n",
    "        \n",
    "cs = chain_state_to_pandas(STATE_FILE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# choose which col to plot using a widget\n",
    "\n",
    "cols_to_plot = MINER_NUMERIC_COLS + DERIVED_COLS\n",
    "\n",
    "col_selector = pn.widgets.Select(name='Field', options=cols_to_plot)\n",
    "cols = ['Miner'] + cols_to_plot\n",
    "plot = cs[cols].hvplot(by='Miner', y=col_selector)\n",
    "pn.Column(pn.WidgetBox(col_selector), plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# plot all line charts in a vertical stack\n",
    "\n",
    "plots = []\n",
    "for c in cols_to_plot:\n",
    "    title = c.split('.')[-1]\n",
    "    p = cs[['Miner', c]].hvplot(by='Miner', y=c, title=title)\n",
    "    plots.append(p)\n",
    "pn.Column(*plots)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# miner power area chart\n",
    "\n",
    "mp = cs[['Miner', 'Info.MinerPowerRaw']].rename(columns={'Info.MinerPowerRaw': 'Power'})\n",
    "mp = mp.pivot_table(values=['Power'], index=cs.index, columns='Miner', aggfunc='sum')\n",
    "mp = mp.div(mp.sum(1), axis=0)\n",
    "mp.columns = mp.columns.get_level_values(1)\n",
    "mp.hvplot.area(title='Miner Power Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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