dqa.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Quality Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from glob import glob\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from IPython.display import Audio\n",
    "from tqdm import tqdm\n",
    "\n",
    "from melody_gen.data import Composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_LOC = './data'\n",
    "SIZE = 'large'\n",
    "SIZE_PATH = f'{DATA_LOC}/raw/PPDD-Jul2018_aud_mono_{SIZE}'\n",
    "DESCRIPTOR_PATH = f'{DATA_LOC}/raw/PPDD-Jul2018_aud_mono_{SIZE}/descriptor'\n",
    "COLNAMES = ['onset', 'pitch', 'morph', 'dur', 'ch']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_fn(path):\n",
    "    return path.split('/')[-1].split('.')[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [00:00<00:00, 614.61it/s]\n",
      "100%|██████████| 100/100 [00:00<00:00, 599.35it/s]\n",
      "100%|██████████| 100/100 [00:00<00:00, 652.65it/s]\n",
      "100%|██████████| 1000/1000 [00:01<00:00, 677.28it/s]\n",
      "100%|██████████| 1000/1000 [00:01<00:00, 697.62it/s]\n",
      "100%|██████████| 1000/1000 [00:01<00:00, 662.47it/s]\n",
      "100%|██████████| 10000/10000 [00:17<00:00, 567.99it/s]\n",
      "100%|██████████| 10000/10000 [00:18<00:00, 540.12it/s]\n",
      "100%|██████████| 10000/10000 [00:17<00:00, 556.57it/s]\n"
     ]
    }
   ],
   "source": [
    "sizes = ['small', 'medium', 'large']\n",
    "parts = ['prime', 'cont_foil', 'cont_true']\n",
    "data = {size: {} for size in sizes}\n",
    "for size in sizes:\n",
    "    for part in parts:\n",
    "        size_path = f'{DATA_LOC}/raw/PPDD-Jul2018_aud_mono_{size}'\n",
    "        data[size][part] = {get_fn(path): pd.read_csv(path, names=COLNAMES) \n",
    "                            for path in tqdm(glob(f'{size_path}/{part}_csv/*'))}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "prime = data[SIZE]['prime']\n",
    "cont_foil = data[SIZE]['cont_foil']\n",
    "cont_true = data[SIZE]['cont_true']\n",
    "fn_list = list(prime.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary of issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. There are some pieces with an extremely large (>500) / very small (<10) number of notes. I think this is because these pieces have an extreme estimated tempo - the tempo was used to get 35 seconds of primer input. There are some pieces with a very high tempo (>300bpm, some 600), and others are very low (<30pbm some 20)\n",
    "    * [Plot of time signatures](#Distribution-of-time-signatures)\n",
    "    * [Piece length plot](#Total-length-of-excerpt-\\(from-start-onset-to-end-<strong>onset<%2Fstrong>\\))\n",
    "2. There are some very long notes\n",
    "    * [Analysis](#Note-durations)\n",
    "3. (Minor) sometimes the final note of the prime is quite long\n",
    "    * [Plots](#Final-note-length)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## General summary statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of notes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some of the primes have a *very* large number of notes and others - this is related to [issue 1](#Summary-of-issues) about tempo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/james/anaconda2/envs/mg/lib/python3.7/site-packages/scipy/stats/stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "sns.distplot([df.shape[0] for df in prime.values()], rug=True)\n",
    "plt.title('Nr notes in prime')\n",
    "plt.show()\n",
    "sns.distplot([df.shape[0] for df in cont_foil.values()], rug=True)\n",
    "plt.title('Nr notes in cont_foil')\n",
    "plt.show()\n",
    "sns.distplot([df.shape[0] for df in cont_true.values()], rug=True)\n",
    "plt.title('Nr notes in cont_true')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Total length of excerpt (from start onset to end **onset**)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some primes are very long, and others extremely short - this is related to [issue 1](#Summary-of-issues) about tempo. Below are some primes shorter than 10 quarters. '98d60602-2a03-43b1-9a24-49ab0ab9f31d' is an example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": [
    "max_len = 20\n",
    "prime_lengths = [df.onset.iloc[-1] - df.onset.iloc[0]\n",
    "                 for df in prime.values()]\n",
    "sns.distplot([ll for ll in prime_lengths if ll <= max_len],\n",
    "             rug=True)\n",
    "plt.title('prime total duration up to but not including final note onset')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initially, I thought there was an issue with the length of the cont_true examples: they should be 10 quarter notes long at most. This seems to all be fine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "sns.distplot([df.onset.iloc[-1] - df.onset.iloc[0]\n",
    "              for df in prime.values()],\n",
    "             rug=True)\n",
    "plt.title('prime total duration up to but not including final note onset')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[-1] - df.onset.iloc[0]\n",
    "              for df in cont_foil.values()],\n",
    "             rug=True)\n",
    "plt.title('cont_foil total duration up to but not including final note onset')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[-1] - df.onset.iloc[0]\n",
    "              for df in cont_true.values()],\n",
    "             rug=True)\n",
    "plt.title('cont_true total duration up to but not including final note onset')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's also true that the maximum time between the primer final note onset and the cont_true final note onset is no greater than 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ONmNM7WhpyhKSEpKISIMIJSRjanurOjWIiEh68oVECakJB1hVQhIRaRB5d7JmTO1oVZWdiIikp1BwMhljanuLquxERCQ9xU4N+3e0sLWnv+lG/FZCEhFpEPkCZMyY0tEaRvze1VwjfishiYg0iHyhQDYDU9tbgOYbYFUJSUSkQeQLkMtk2H9iSEjNNsCqEpKISIMouJPJwJT2VqD5BlhVQhIRaRD5QrHbd6yyUwlJRETSkPfQ7Xv/DpWQREQkRYVYQtpvQhj3utlGa1BCEhFpEMWhg3LZDJMn5Jquyi7V20+Y2TJgO5AHBtx9bprxiIikqeBhcFWASW05unub6zqkRrgf0h+4+4a0gxARSVuxhASQzdiQG/Y1A1XZiYg0iLxDJpmQNHRQXTnwKzNbYGYXVprAzC40s/lmNr+rq6vO4YmI1E/o1BAeZzPGgBJSXZ3k7icAZwIfMrOTyydw9yvcfa67z+3s7Kx/hCIidZKssstlTIOr1pO7r47/1wO3ACemGY+ISJqSCSljKiHVjZlNNLPJxcfAacCTacUjIpK24u0nAHLZ5mtDSrOX3YHALRa6OOaA69399hTjERFJVb4w2O07m8koIdWLuy8FXpPW8kVEGk3Bh7YhNVtCSrtTg4iIRMXBVQGyZgwUCilHVF9KSCIiDSJfcF2HJCIi6Sv4YAlJnRpERKSurp/3Yunx5u5+VuZ6uH7eiyohiYhIesLgquFxVtchiYhIWhwS3b5VQhIRkZQU3IkFpKZsQ1JCEhFpEIXEhbEZU0ISEZGUuEMmnpVzGu1bRETSUnDHmnjoICUkEZEGUXBKvew0dJCIiKTGGSwhZVRlJyIiaSn44Ek5lzEKroQkIiIpcPch1yEN5DW4qoiIpKDgJDo1qA1JRERS4omhg9TtW0REUlNeQlIbkoiI1F0x+aiEJCIiqSoWhpLdvt3DcELNQglJRKQBFEtI2UQJCWiqUpISkohIAygmpOTQQcnXm4ESkohIAyjmndIN+uLZWSUkERGpq2olpHxeCUlEROqoUFZCKrYh5VVlJyIi9eS7lZCKnRqaZ/ig1BOSmWXN7DEz+0XasYiIpGWwhDQ0ITXT8EGpJyTgY8CitIMQEUmTl10YWyohqQ2pPsxsJnA2cGWacYiIpK1QdmFssQ1J3b7r53LgU0DVSlIzu9DM5pvZ/K6urvpFJiJSR1VLSKqy2/vM7B3AendfUGs6d7/C3ee6+9zOzs46RSciUl/lJSS1IdXXScAfmdky4IfAqWZ2XYrxiIikptLgqqCEVBfu/hl3n+nus4FzgLvd/dy04hERSdNgQiq7MFYJSURE6klDB0Eu7QAA3P0e4J6UwxARSU3VoYN0YayIiNRTeQlpsA0ppYBSoIQkItIAdi8haeggERFJgYYOUkISEWkIg4Orhue6MFZERFJRXkIqDR2khCQiIvVUPnRQMTGphCQiInW12+CqWbUhiYhICspLSBo6SEREUrF7LzsNHSQiIikolPeyUxuSiIikYbfBVUttSLowVkRE6shLnRrCfw0dJCIiqdj99hMqIYmISAq8vFOD2pBERCQNu3Vq0HVIIiKShvISkq5DEhGRVBQYWkLS0EEiIpKKaoOrqoQkIiJ1VRo6KD7X/ZBERCQVpRJSTERmRjZjSkgiIlJf5Tfog9D1W21IIiJSV8Ub8WUSGSmbsVJ38GaghCQi0gCK4zEkS0i5jDGQV0ISEZE6Kh86CEJ7koYOEhGRuioNrpp4LZdRG1JdmNkEM3vYzB43s6fM7AtpxSIikraCO8bgLcyh+dqQcikuuxc41d13mFkL8ICZ/dLdH0oxJhGRVLgPra6D5mtDSi0heejjuCM+bYl/zbPmRUQSCu6U5aPYhtQ8p8VU25DMLGtmC4H1wB3uPq/CNBea2Xwzm9/V1VX/IEVE6qBqCUkJqT7cPe/uxwEzgRPN7JgK01zh7nPdfW5nZ2f9gxQRqYNKJaRsxsg3URtSQ/Syc/ctwD3AGSmHIiKSikLFElKGfBO1IaXZy67TzKbGx+3A24Bn0opHRCRN7k6mQhtSM1XZpdnL7mDgGjPLEhLjje7+ixTjERFJTeUSkrp914W7/w44Pq3li4g0kmptSM1UQmqINiQRkWYXquyGZqSshg4SEZF6KziVS0jq1CAiIvVUqFBCarY2JCUkEZEG4D50HDtQG5KIiKSgUKHbt25hLiIidVdt6CAlJBERqauqQwcpIYmISD1VKiGpDUlEROquchtSRiUkERGpr0q97NSGJCIidadedkpIIiINIXRqKGtDMmNAQweJiEg9hdG+h76WzRr55slHSkgiIo2g0uCqOQ2uKiIi9VZpcNWMqdu3iIjUWfUSkhKSiIjUUaHS4KpZJSQREamzSt2+VUISEZG6q3j7idiG5E1yTyQlJBGRBlBt6KDwXgoBpUAJSUSkATgVbj+RDc+bpdpOCUlEpAFUGzoIlJBERKSOqrUhAU0zfJASkohIAygUqpeQmiQfKSGJiDSCSoOrFtuQVELay8zsMDP7tZktMrOnzOxjacUiIpK2SoOrFjs5NEsbUi7FZQ8AH3f3R81sMrDAzO5w96dTjElEJBVOhRJSplhCao6ElFoJyd3XuPuj8fF2YBFwaFrxiIikqeC7n5DVyy4FZjYbOB6Yl24kIiLpqDi4qq5Dqi8zmwT8GPhbd99W4f0LzWy+mc3v6uqqf4AiInVQaXDVjKnKrm7MrIWQjH7g7j+pNI27X+Huc919bmdnZ30DFBGpE684uGpx6CAlpL3Kwk+Bq4BF7v7vacUhItIICg6ZsoxUbEMayCsh7W0nAecBp5rZwvh3VorxiIikolgCKr9jbLN1akit27e7PwDYsBOKiOzjijVyle4YC7owVkRE6qRYQqrW7VttSCIiUheDVXZVSkhqQxIRkXoYrLIb+nqmydqQlJBERFI2bAlJCUlEROqhUKWEVOplpzYkERGpB69aQgqn6LzakEREpB4KVbp9x3ykKjsREamPYglJQweJiEiqigWg8iq7rDo1iIhIPVUrIQ0OHaSRGkREpA6qtSHpwlgREamr4QZXVRuSiIjUxfCDqyohiYhIHRSqtCFp6CAREamr4YYOUkISEZG6qDa4arPdoE8JSUQkZdVKSLoOSURE6qpat2+VkEREpK68Srfv0uCqSkgiIlIPVQdXjU9VZSciInVRbeggMyObMQ0dJCIi9VGthATEhFTngFKihCQikrJqbUgQrkVSCUlEROpiuBKS2pBERKQuqg2uCsUqOyUkEREZxs6+AZ5YuXVM8xgcy273jJRTQtr7zOx7ZrbezJ5MKwYRkbG64eEV/Mm3fkN378Aez8NLd4zd/T2VkOrjauCMFJcvIjJm67fvoj/vbNjRu8fzqFVCyprakPY6d78P2JTW8kVExsO2nn4ANnb37fE8qt0PCSCbVQmpYZjZhWY238zmd3V1pR2OiMgQW4sJaceeJ6RanRpymYwSUqNw9yvcfa67z+3s7Ew7HBGRIYoJaVP3nlfZ1SwhqQ1JRERGYus4VNkVqDx0EBTbkHRhrIiIDGN8quzC//L7IYGGDqoLM7sB+C0wx8xWmtkFacUiIrKntu4sVtmNpVND9RJSLts8Qwfl0lqwu78nrWWLiIyHQsHZHq8/Glu37/C/UhtSRt2+RURkONt7B0odEsajhFR9cFUlJBERqaF4DVIuY2NKSMPffkIJSUREaih2aDh8egcbd/SVSjqjVfM6JF0YKyIiwykmpCNmTKQvX2DHHo5nV2voILUhiYjIsIoJ6WUzJgJ73vW7NLhqhfdyGSslrH2dEpKIyB4aTEiTgD2/OLbgjlHtOqQMA3klJBGRfdK8pRu5af6KMc+nVGXXGUpIe9qxwb1ydR1ANoPakERE9lVXPvACl922aMzz2dbTTy5jzNy/HYCNNa5FuuDqR/jmrxdXfK/gXrFDA4TBVTV0kIjIPmrV5h427+ynpy8/pvls7elnSnsLMya1AdWr7HoH8tzzXBe/enpdxffdIVNpmAZCt+8mKSApIYlI81m9tQeANfH/nrh+3ov8Lt66/CePrqI1l+HBxRsqTvvChm7yBeeZNdsYqDAwXcG94rBBEDo1qIQkIrIP6u4dYEscf271ll1jmteu/jztrVkAJrZm6a5S4npu3Q4AegcKLOnq3u39goNV7GMXSk55dWoQEdn3rNoyWCpavWXPS0gAPf152ltiQmrL0V3lOqTF67aXHj+1eutu7/swJaS8un2LiOx7Vm1OJKQxVNkB9PQNlpAmteWqXhj73LodzJrewYSWDE+u2rbb+4WaveyaZ6SG1Eb7FhFJw8pYKmrNZsa3hNSaqzq/59ZvZ86Bk5k2sbVqCal6L7vmGalBCUlEmsrqLT20ZI2jD548pjYkdw9tSEOq7PIxuQxml96BPMs37uTwaR20ZjMsXLGF6x5aPqREFDo1qA1JVXYi0lRWbe7h4CntHLp/+5iq7PoGChQcJpQSUpa8D94fqajYw+6AyRM4ZGo7vQMFNpd1Dy945YFVQW1IIiL7rFVbejhk6gQOmdLO6i09ezxCd09/6FGXbEMC2FQ2nt3zsYfdgfu1cciUcAHt6q1DS2a1SkjZTKZpquyaNiH9xx3Pjdu83v2d345oupO+cteIYhhpbMnpan3mFf9424jmd+znbx/RdNW+b3kMyelqxTf707cOu8zy71BtfrXmlYynfH7VvlOt+SVjSE5Xazsnpyv/DsnnyW1RaztXi6/WdLW2S7X5JV8vX3dHfKbydy+fV3K5yffKp6u2Lmtti2rzK//MsZ+/nVWbezh0agdXPvACu/oLbNnZXzOGao+/+r/PApSq7G5asBKAjd29Q6b7yA2PkTGYMamNA/cLF9Cu3tLDpu4+PnvLE8x7YSPuu19UW5yHhg5qAl+76/lxm9e8FzaNaLpVZfXV1WIYaWzJ6Wp9pm+E9c/be0d21Xq171seQ3K6sa7v8u+wJ/NLxlM+v5Fuw5HEsKfbOfk8uS1Gup1HskwY+3YpX3fJc2X5d6+23JGqNb89sb03z7rtuzg0DvUTljG2jg3FElJRpRG/Z02fSEs2Qy4bTrnPrt3OFfctAeBnC1fz9Jrde94VZTMZ8gXf45LcS0nTJiQRaU7usHLTztLzHz5ceZDV3oE851wxfO1HsYRUtG777uPZHXnApCHP127bVUrkZx5zENTINVPaWzhkyoSmGD5ICUlEms7UjtbS4609lcefe2jpJh5aOnypbkIiIU2b2Mp37l1Set43EIb8OaosIc2a1sGFJx8BwJuP6uRDpx5Zdf4XvOllPPiZt5KtduXsPkQJSUTGVU9fnl8+sWavzLvaSAijNbWjBQg92LbEW0iUu2vR4ECo67dXrzpMlpD+7PdnDrkWaf7ykNBeceDkIZ+56C0vLw3ICnDQfhNGEf2+SwlJRMbV5Xc+x1//4FEAbnxkxbg0yBdv6/CXVz8y5nlBqAYr/i+Oa1furkXrmRMTya2/G0ywDzy/ofSdDGhrGTyNzpo+kQ+fehQA5101j/ddOQ+AE182bVzi3tcpIYnIuLruoeW84YjpAHzqx7/jS7eO7b5D7s4nb/4dEDpGLFi+eUzzm9yWoyV2LpjS3lK6yV65VVt6OP+k2QD8dOHq0uvnXjWPax5cBoTquvLu2h+N1W8Pv7CJD745VMsdMrUdGZ4SkoiMi+vnvQhAd1+e184OJYLXzp7GNb9dxjNrq/ciG87VDy7j7mfWA7DfhBxX3r+06rS/ibd/+HWcvpJidV3xcTEhfe3O5/n2vUtK3wMG7wj7+IotXPvbZQC05TJ8I95or7yHHcCN80P370+ePofZ08OdZJPzlOpSTUhmdoaZPWtmi83s02nGIvJS0t07wFdvfwYIt0AYqwee31DzRD8SvTGOow+azEFTQpvI6a8+kP0m5Pj8z54a1byun/diqRRy6a2LeOVBoers3NfP4van1rJ8Yxj94O5n1rGkK1x4+szabVx87QIAPvbDx1i2IdzmYd7SjVx22yLmLd0IDO3QMKW9lW0x6Xz97uf55t2LS+1FM/dvZ/KEkLzM4J/id7j2gteVblVe3sMuqaNVI7ONVmprzMyywDeBtwMrgUfM7Ofu/vR4L+ujNzzGpAk53nG3Fq8gAAAIvUlEQVTswbzuiOmlni9bd/YzeUJuyJ0aCwWnpz9PNmO05TKYGb0DeXbsGqCtJcvE+ItoR+8A3b15Jk0Iq9Dd6e7L0zdQYFJbjtZcuHZgR+8AhYLT0RY+19OXZ0fvAK3Zwd8C+UIYE6s1lylVJQzkC/TlC7TlsqXeNQP5AgMFL8UFlRt53Z3+vDNQKNA/EOq6127dxcS2LJPacqXP5gtOf74Q/8J067ftYr/2llLPoUKsK88kYgDY2TdAe0sWM2MgX2DXQGHI8nfG+8Ls6s+X5tWfL5CP8ecLzrPrtpducLakawcvmz4Rs3DPmFzGyGUz9A0UWLE5dNFdvH47M/fvKM2vu3cgVplA1/be0j1nlm/s5rD9O0rzgvCrFsIN2bpit9ztu/rpaM2xs2+gtG0mtGRYtGY7tz+1lufWhlsG3PLYSg6f1sHBU9qZPql1yLZ7ctXWUnvC8o3dpdh29edpy2VKoz//bOGq0onvR4+8yCsP2q+0DbIZK11jsn1X/+D+2dNPR9zfkuv4tifW8KVbF5Wun/njb/6Gb7z3eI48YGjD+daefp5YuZVn460Plm3o5sDYeN7dO1Dqafx3P1rILY+tKn3u63c9z5uOmsGs6RPJF7x0wv/N4g2lzz+5aiu7+vOl7fzTx1Zxa+zIcMqcA0rz6mjN8YnT5/CPtzwJhLaY4vxuf3Jt6QZ5b//3e3nTUTM47VUHAXDnonWlqrmjDpjEn54wk0tvW8QH3jib796/lEtvXcT6bbt4fOXW0l2E3v2dh0rD7/TnnYuvC8npnO8+hDtccV9IuFPbEyWk9pbSepgxqY0dvQN89/4XAErbCGD29Ims2LSTgYKzeP0Ojj10Ck+s2sqEFlUyjSdL62IrM3sDcIm7nx6ffwbA3b9c7TNz5871+fPnj2o5hYLz9zcu5FdPr2NnX363odwzFuqBjXCBX0/i12bGKJ0Uk6+Z7T4cfMaGXiDYms3QV+HOkOVac0Pn35K1UnIoastlKMQkA+HXWlsuw67+ofOf0JKJSab6Ns1mrLSMWo3NrbkMhYKXhixpyRoZs9IJvvidy9dPazZD3ofOu9K6KF9fxWUMFJziLtmSDes5OZ0ZZG3o6MeV5l8c/2u0u3dx/zBCF95Kt6TOWJiu1nouxjqS5e/JaM6dk9t413GHcsX9S5ke4yz+rqq0f9bSkjXedGQnRx88mf+6Z8nwHxjGZe86FoDP3vIEl73rWN792sN45zcfqHjbhaKjDpjECxu6S+vBgMOndbB8084h81v2lbP55E2Pc9OClcyY1ManzpjDLx5fw33Pd9Gay3Dhm4/gG79ezPlvnM3VDy7Dgbmz9ue0Vx/Ec2u3c/OjK7no5COYNX0in73lCT4QpwP43FlHs6NvgKvuf4HtvQN85NQjOXhKO5+95Qk+cdocdvYN8F/3LOGydx3Lxh29/Nsdz3HMoVN474mHD/m+tR6PdrplXzl7jFsDzGyBu88d84zqIM2E9KfAGe7+V/H5ecDr3P3DZdNdCFwYn84Bnq1roCMzA6h87+LGoPj2XCPHBo0dXyPHBs0T3yx37xyH+ex1aVZyVrrKa7fs6O5XAFfs/XD2nJnNb+RfIIpvzzVybNDY8TVybKD4GlGaFaArgcMSz2cCq6tMKyIi+7g0E9IjwFFm9jIzawXOAX6eYjwiIpKi1Krs3H3AzD4M/C+QBb7n7qPrG9o4GrpKEcU3Fo0cGzR2fI0cGyi+hpNapwYREZEkdaIXEZGGoIQkIiINQQlpDMxsgpk9bGaPm9lTZvaFtGMqZ2ZZM3vMzH6RdizlzGyZmT1hZgvNbHRXPNeBmU01s5vN7BkzWxQv5k6dmc2J66z4t83M/jbtuJLM7O/iMfGkmd1gZg1zfwUz+1iM66lGWG9m9j0zW29mTyZem2Zmd5jZ8/H//mnGWC9KSGPTC5zq7q8BjgPOMLPXpxxTuY8BYxtuee/6A3c/rkGvt/gacLu7vxJ4DQ2yHt392bjOjgN+H9gJ3JJyWCVmdijwUWCuux9D6LR0TrpRBWZ2DPBB4ETCNn2HmR2VblRcDZxR9tqngbvc/Sjgrvh8n6eENAYe7IhPW+Jfw/QSMbOZwNnAlWnH8lJjZvsBJwNXAbh7n7tvSTeqit4KLHH35WkHUiYHtJtZDuigca4xPBp4yN13uvsAcC/wrjQDcvf7gPJb074TuCY+vgb447oGlRIlpDGKVWILgfXAHe4+L+2YEi4HPgUMP6heOhz4lZktiENENZIjgC7g+7HK80ozm5h2UBWcA9yQdhBJ7r4K+FfgRWANsNXdf5VuVCVPAieb2XQz6wDOYugF+o3iQHdfAxD/HzDM9PsEJaQxcvd8rDqZCZwYqwRSZ2bvANa7+4K0Y6nhJHc/ATgT+JCZnZx2QAk54ATgW+5+PNBNg1WbxAvK/wi4Ke1YkmJ7xzuBlwGHABPN7Nx0owrcfRHwL8AdwO3A48D43BddxkwJaZzE6px72L0uOC0nAX9kZsuAHwKnmtl16YY0lLuvjv/XE9pATkw3oiFWAisTJd6bCQmqkZwJPOru69IOpMzbgBfcvcvd+4GfAG9MOaYSd7/K3U9w95MJVWXPpx1TBevM7GCA+L/6HQf3IUpIY2BmnWY2NT5uJxyIz6QbVeDun3H3me4+m1Ctc7e7N8SvVAAzm2hmk4uPgdMI1SkNwd3XAivMbE586a3AuN+ra4zeQ4NV10UvAq83sw4LN996Kw3SIQTAzA6I/w8H/oTGXIc/B94fH78f+FmKsdSNbmk4NgcD18SbDWaAG9294bpXN6gDgVvizQJzwPXufnu6Ie3mI8APYtXYUuD8lOMpie0fbwcuSjuWcu4+z8xuBh4lVIc9RmMNg/NjM5sO9AMfcvfNaQZjZjcApwAzzGwl8HngK8CNZnYBIcH/WXoR1o+GDhIRkYagKjsREWkISkgiItIQlJBERKQhKCGJiEhDUEISEZGGoIQkIiINQQlJREQawv8BJbRk1XuJQKoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot([cont_true[fn].onset.iloc[-1] - prime[fn].onset.iloc[-1] \n",
    "              for fn in fn_list],\n",
    "             rug=True)\n",
    "plt.title('time between final prime note onset and cont_true final note onset')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Total length of excerpt (from start onset to end **offset**)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "...but there are some very long final notes, especially in the HMM cont_foil data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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id0AT3InI6NRDKECdfYP8+IW9XPbW+SMXlwFcsmIO71w2a9SL0ZLFp6840j3A3Gmp770sIgLqIRSktS/uo6t/iKsuWHTc+hKzMYUBHJu+olXXIohIBgqEArTmN2/w5rm1vH1R5iGhTOpGeggKBBEZnQKhwLzcdIRNe9u56oJFjMdtpmeEU2DrnggikomOIRSYv/uv1yiLGYNDfsI9EE5GXbVmPBWR7KiHUEAGh4bZvO8oK+ZNpbJsfA4AT9eMpyKSJQVCAXluVxvd/UOcOX/auG2zLFZCbUWprkUQkYwUCAXk4c0HKC0xzphTO67bnT6lXD0EEclIxxAKhLvz8OYDLJ9TO+o9DrKRfOxh2J1X97ef0jZFZOJTD6FAvNx0lP1Hezlz/tRx33Z1eYyuPl2pLCKjUyAUiJ9tPkCsxHjz3PEdLgKoLi+lu39w3LcrIhOLAqEAuDsPbzrAO5bOpLp8/EfxppTH6O5XD0FERqdAKAA7WrrY0dLFB86ck5PtV5WX0jc4TP/gcE62LyITgwKhADyxpRmA975pdk62P6UiuKZB01eIyGgUCAXgl1ubWVo/hYUzqnOy/fgwlKavEJHRKBAi1jswxPodh3nPGbnpHUBwlhGgO6eJyKgUCBF7Zsdh+gaHefeb6nP2HiOBoB6CiIxCgRCxX25pprKshAuWzMjZe8Tvvdzc0Zez9xCR4qdAiNgvtzbzjqUzx20yu1RqKkopLTH2HunJ2XuISPHLKhDM7FIz22JmjWZ2Y4rnK8zs/vD59Wa2OFw/08weN7NOM/t60mueCLf5YviVu0H0AvXG4S52tnTx7jNyN1wEYGbUVZfR1Nad0/cRkeKW8SooM4sBdwKXAE3Ac2a21t1fTWh2LdDm7svMbDVwB/BxoBe4GTgr/Ep2tbtvOMXPULR+ta0FgPfk6HTTRNOry9nbph6CiKSXzWWx5wON7r4DwMzuA1YBiYGwCrg1XH4Q+LqZmbt3AU+a2bLxK3liWLN+Nw89v5eailKe3n6Yp7cfzun71VWXsbOlK6fvISLFLZshowZgT8LjpnBdyjbuPggcBWZmse3vhMNFN9t43C+yyOw/2sP8usq8vFdddTktnf30aAoLEUkjm0BI9YvaT6JNsqvd/Wzgd8KvT6Z8c7PrzGyDmW1obm7OWGyxGBwe5lB7H/OmVeXl/aaHt9LUgWURSSebQGgCFiY8XgDsS9fGzEqBaUDraBt1973h9w5gDcHQVKp2d7n7SndfWV+f24Ov+XSovY8hd+ZNy1MPoSq4laYCQUTSySYQngOWm9kSMysHVgNrk9qsBa4Jl68EHnP3tD0EMys1s1nhchlwGbBprMUXs/1HewGYn6ceQl3YQ9CZRiKSTsaDyu4+aGY3AA8DMeDb7r7ZzG4DNrj7WuBu4F4zayToGayOv97MdgFTgXIz+yjwAeAN4OEwDGLAL4BvjusnK3D7j/ZQHithRk15Xt5valVZcC2CzjQSkTSymnzf3dcB65LW3ZKw3At8LM1rF6fZ7HnZlTgx7T/ay9xplZTk6Vh6iRnz6io1ZCQiaelK5Qi4O/uP9uTt+EFcQ12VeggikpYCIQJNbT30Dgzn7QyjuIa6apoUCCKShgIhApv3tQPkvYewYHoVBzt6dec0EUlJgRCBV/e3Y8DcfA8ZTa/CHQ6EZziJiCRSIETg1X3t1NdWUBbL7+5fUBcMUenUUxFJRYEQgdf2t+e9dwCwYHpwi84mnWkkIikoEPKss2+QvUd6mDs1/4Ewd1olZuhMIxFJSYGQZ9sPdQIwu7Yi7+9dXlrCnNpKnWkkIikpEPJs20gg5L+HAMGZRnuP6BiCiJxIgZBn2w51UB4rYfqU/ExZkaxhepWuVhaRlBQIebb9UCdLZk0hVhLN7R8a6qrYf6SXoeFMs5OLyGSjQMizbYc6WTanJrL3b5hexeCwc7Bd1yKIyPEUCHnUOzDE7tZuls+OLhDip55q2EhEkikQ8mh7cyfusCzCQGgIL07TqacikkyBkEeN4RlGy2fXRlZDg65WFpE0FAh5tO1gJ7ESY/Gs6shqqCqPMaumXENGInICBUIeNR7q5LSZ1VSUxiKto6GuShenicgJFAh5tO1QR6QHlOMaputGOSJyoqxuoSmnrn9wmF2Hu7n0rLmR1bBm/W4AOnoG2d3azQ+efQMz46oLFkVWk4gUDvUQ8mTX4S6Ghj3SA8pxddVlDA47nX2DUZciIgVEgZAnWw92ANGechpXVx1Mm3GkeyDiSkSkkGjIKA/WrN/Nz189QInBxjfaeLnpaKT11FWXAdDW3c/CGdGd8SQihUU9hDw5cLSXWTX5v0taKtPVQxCRFKL/7TRJHGjvjeQuaalUlsWoLCvhSE9/1KWISAFRIORB78AQR7oHIrlLWjrTq8tp61IPQUSOUSDkQXxm0ULpIUBwYFk9BBFJpEDIg/1Hw0AooB5CXXUZR7oHcNd9EUQkoEDIgwPtvVSWlTCtqizqUkZMryqjb3CYnoGhqEsRkQKRVSCY2aVmtsXMGs3sxhTPV5jZ/eHz681scbh+ppk9bmadZvb1pNecZ2avhK/5mplFcwuxPDhwtJe5UysppI+oaxFEJFnGQDCzGHAn8CFgBfAJM1uR1OxaoM3dlwFfAe4I1/cCNwOfTbHpbwDXAcvDr0tP5gMUOvfg7mSFdPwAEk891XEEEQlk00M4H2h09x3u3g/cB6xKarMKuCdcfhC42MzM3bvc/UmCYBhhZvOAqe7+jAeD2N8DPnoqH6RQNbX10Dc4zNypVVGXcpxjF6ephyAigWwCoQHYk/C4KVyXso27DwJHgZkZttmUYZsAmNl1ZrbBzDY0NzdnUW5hef1AMGVFofUQqstjlMVMPQQRGZFNIKQa+E4+NSWbNifV3t3vcveV7r6yvr5+lE0Wptf3twMwp7Yi4kqOZ2bBtQjqIYhIKJtAaAIWJjxeAOxL18bMSoFpQGuGbS7IsM0J4bUD7UyvLqOiLNqb4qRSV12maxFEZEQ2gfAcsNzMlphZObAaWJvUZi1wTbh8JfCYj3KCu7vvBzrM7MLw7KJPAT8ec/VFYPO+dubXFdbxg7g6Xa0sIgkyBkJ4TOAG4GHgNeABd99sZreZ2RVhs7uBmWbWCHwGGDk11cx2AV8G/ruZNSWcofQHwLeARmA78NPx+UiFo713gDcOd4/c2L7QTK8up2dgiC7dF0FEyHL6a3dfB6xLWndLwnIv8LE0r12cZv0G4KxsCy1Gr+4Ljh8Ubg8hONNo75EezpgT/Y17RCRaulI5hzbtDe57MK/AzjCKmx5eOd3U1h1xJSJSCBQIObR5Xztzp1ZSW1k4U1YkqpsSXJy2t60n4kpEpBAoEHJo096jnNUwNeoy0qqpKCVWYjQdUSCIiAIhZ7r7B9ne3MmK+dOiLiWtEjPqqsrUQxARQIGQM6/t72DY4az5hdtDgODAcpMCQURQIOTM5n3BAeWzGgq3hwDBqad7NWQkIigQcmbT3qPMmFJesGcYxdVVl9Hc0Uev7osgMukpEHJk0952zpw/taDugZBK/L4I+9RLEJn0FAg50D84zLZDHQU/XATH7ougYSMRUSDkwO7WbgaGnOWza6IuJaORq5V1YFlk0lMg5MCe1uDK39NmVkdcSWZTK8uCaxEUCCKTngIhB3aHgbBwRuEHQqzEWDC9ip2Hu6IuRUQipkDIgd2t3VSWlVBfU1g3xUlnWX0NjQc7oy5DRCKmQMiB3a3dLJpRXfBnGMUtm13DzpYuBoeGoy5FRCKkQMiBPa3dLJoxJeoysnb67Br6h4bZo+MIIpOaAmGcuftID6FYxM+GajykYSORySyrG+RIdtas301n3yDd/UMc6uhlzfrdUZeUldMTAuGSFXMirkZEoqIewjhr7QpuWj8jvNdAMZhaWcacqRVsO9QRdSkiEiEFwjgbCYTq4gkECA4sb9eQkcikpkAYZ/FAmF5EPQSA5bNr2d7chbtHXYqIRESBMM7auvqZWllKWay4du3ps2vo7BvkQHtv1KWISESK67dWEWjt7i+63gEEF6eBzjQSmcwUCOOstau/6I4fQHAMAWCbrlgWmbQUCONoYGiY9p6BojrDKG5WTTl11WU0NisQRCYrBcI4OtI9gFNcp5zGmVkwp5GGjEQmLQXCOCrGaxASLZtdw7aDHTrTSGSSUiCMo9bu4g6Ety2qo617gK06jiAyKWUVCGZ2qZltMbNGM7sxxfMVZnZ/+Px6M1uc8NxN4fotZvbBhPW7zOwVM3vRzDaMx4eJWmtnH2Uxo6aiOGcEedcZ9QD8cuuhiCsRkShkDAQziwF3Ah8CVgCfMLMVSc2uBdrcfRnwFeCO8LUrgNXAmcClwD+H24t7r7uf6+4rT/mTFICWzn5m1VQUzbTXyeZNq+KMOTX8amtL1KWISASy6SGcDzS6+w537wfuA1YltVkF3BMuPwhcbMFvxVXAfe7e5+47gcZwexNSS2cfs4rkpjiJ1qzfPfI1u7aSZ3Yc5rtP7Yq6LBHJs2wCoQHYk/C4KVyXso27DwJHgZkZXuvAz81so5ldl+7Nzew6M9tgZhuam5uzKDca/YPDtHX3M6umOI8fxJ0xp5ahYWdHi44jiEw22QRCqvGP5NNQ0rUZ7bUXufvbCYairjezd6V6c3e/y91XuvvK+vr6LMqNxp62boadouwhJDptZjVlMdMFaiKTUDaB0AQsTHi8ANiXro2ZlQLTgNbRXuvu8e+HgIco8qGknc3BTeqLPRDKYiUsnVXD1oOaCltksskmEJ4DlpvZEjMrJzhIvDapzVrgmnD5SuAxD05mXwusDs9CWgIsB35jZlPMrBbAzKYAHwA2nfrHic7OliAQZhb5kBHA8jk1HO7qZ/fh7qhLEZE8yhgI4TGBG4CHgdeAB9x9s5ndZmZXhM3uBmaaWSPwGeDG8LWbgQeAV4GfAde7+xAwB3jSzF4CfgP8xN1/Nr4fLb92tHRRXR6jurw4TzlN9KY5tQD8aOOeDC1FZCLJ6reXu68D1iWtuyVhuRf4WJrXfh74fNK6HcA5Yy22kO1s6Sz64aK4mTUVnN0wjW/9eieffMdpzK6tjLokEckDXak8Tna2dE2YQAD4wIo5DAwN87VHt0VdiojkiQJhHHT1DXKwva/oTzlNNLOmgqsuWMQPf7OHHZoBVWRSUCCMg/gB5YnUQwD4v+9bTkVpCV/62ZaoSxGRPFAgjIOJGgj1tRX84XtO52ebD/D4Fs1vJDLRKRDGwUQ65TTRmvW7mVpZxqyaCv7sgZe45+ldrFm/O+qyRCRHFAjjYGdLFw11VZTFJt7uLI2VsOrc+bR29fOEegkiE9rE+w0WgR0tXSyZNSXqMnLm9Poazl1Yx6+2tnCwvTfqckQkRxQIp6h3YIjX97fzprm1UZeSUx8+ex4VZSX82/NNDA4NR12OiOSAAuEUPf9GG32Dw1y0bGbUpeRUTUUpV5wzn6a2Hr715M6oyxGRHFAgnKInG1soLTHOXzKxAwHg7IZprJg3lS8/spXGQ5r8TmSiUSCcoqcaW3jborqivW3mWJgZq86dz5TyGNfdu5Ej4T2kRWRiUCCcgqPdA7y89ygXLZsVdSl5U1tZxr/8/nk0tfbw6Xs30jc4FHVJIjJOFAin4JkdLbjDOydRIABsb+7id9/WwPqdrXz8X5/lB8++EXVJIjIOFAin4MnGFqaUxzhnYV3UpeTdOQvruGTFHF7cc4RndhyOuhwRGQcKhFPw5LYWLlw6c0JekJaN95xRz1vm1rLulf1sfKMt6nJE5BRNzt9k42BPaze7DnfzzuWTa7gokZlx5XkLqasu5/ofPM/hzr6oSxKRU6BAOEnffXoXJQbve/PsqEuJVFV5jKvOX8Thrj4+v+61qMsRkVMw8c+VzIF/fryR7z69i7ctms5TjYd5qnFyj6HPr6viunct5c7Ht7P6txZx/pIZUZckIidBPYST8OjrwSRvF0/y3kGi69+7jIa6Km758SZNbSFSpBQIY9R4qIPn32jjwiUzqKueWNNdn4rq8lJuvmwFrx/o4J+f2I67R12SiIyRFdN/3JUrV/qGDRvGfbtfeWQrf3rJGVz0xUd56saLueiLj9LeM8CK+dNYv7OVC5bM4LldrQwXz66zk0h6AAAH7klEQVQqKOUxo3/o+J3XUFcJwJXnLeSrj26jxGDHFz7C2X/zMwA6+oYojxn1tRUsmF7NhUtn8mx4euuFS2fyT49tY0p5jI6+If744uU8uHEPV563kG880Uj/kPPHFy/n20/u4H++c+nIz/bK8xYC8KeXnMFXHtk6shz38X99hvs//Y6UnyH+byT+fbQ2Mn4m0z7N5Wc1s43uvjJTO/UQgK+GN5Lfe6R35HtH3xDrd7YCsH6nwuBUJIcBBPt475HekX0f378dfUN09A2NvG7vkV7W72zlq49uY/3O1pHlYWek3Vcf3Tayrfh7ffXRbXT0DR33s/3qo9tGHicux8V/3qkkvi5TGxk/k2mfFsJnVSCIiAigQBARkZACQUREAAWCiIiEFAhSMIZ05F4kUgoEKRhn3/pw1CWITGpZBYKZXWpmW8ys0cxuTPF8hZndHz6/3swWJzx3U7h+i5l9MNtt5lv8eozP3P9ixJVMXufmaBrx1Xc9k5Ptikw0GecyMrMYcCdwCdAEPGdma9391YRm1wJt7r7MzFYDdwAfN7MVwGrgTGA+8Aszi195kWmb487d6Rscpm9wmJ7+Ifa0dbP9UCcA5972CAD/9cr+XJYgo7jsrfN5evv4zwv13M7jp+a+61fbR5Yfe/0gVWWlVJXHgOBK9LJYCWWxEkpjBn7sGol9R3oAaO7ooyxmxEqMslgJJWYj2xsYGsaAEjPMghlhRYpFxiuVzewdwK3u/sHw8U0A7v6FhDYPh22eMbNS4ABQD9yY2DbeLnzZqNtM5WSvVL7i60/y+oEO+gfTz7Fz5vypbN7Xzi2XreC2/8ppLkkaf/+7Z/O5h14Z9+1+7sNv4e8jmom1xIJwiAdErEQBMRbd/UNUh2E90WX6rM/ffAmVZSe3L7K9Ujmb2U4bgD0Jj5uAC9K1cfdBMzsKzAzXP5v02oZwOdM2ATCz64DrwoedZrYli5qTzQJaRmsQvwnktXecxNbHV8ZaC8S413l1jvb9p+8omn0Kk/jnn0MTotaqvzul7Z6WTaNsAiHVnzTJ3Yp0bdKtT3XsImVXxd3vAu4arcBMzGxDNulYCIql1mKpE1RrLhRLnaBaxyKbg8pNwMKExwuAfenahENG04DWUV6bzTZFRCSPsgmE54DlZrbEzMoJDhKvTWqzFrgmXL4SeMyDgxNrgdXhWUhLgOXAb7LcpoiI5FHGIaPwmMANwMNADPi2u282s9uADe6+FrgbuNfMGgl6BqvD1242sweAV4FB4Hp3HwJItc3x/3gjTmnIKc+KpdZiqRNUay4US52gWrNWVPdDEBGR3NGVyiIiAigQREQkNKEDodCmx0hmZrvM7BUze9HMNoTrZpjZI2a2Lfw+PaLavm1mh8xsU8K6lLVZ4Gvhfn7ZzN4ecZ23mtnecL++aGYfTngu5VQqeap1oZk9bmavmdlmM/vjcH1B7ddR6iy4/WpmlWb2GzN7Kaz1b8P1SyyYRmebBdPqlIfr006zE2Gt3zWznQn79dxwff5//u4+Ib8IDlZvB5YC5cBLwIqo60qqcRcwK2ndl4Abw+UbgTsiqu1dwNuBTZlqAz4M/JTgupMLgfUR13kr8NkUbVeE/w4qgCXhv49YHmudB7w9XK4FtoY1FdR+HaXOgtuv4b6pCZfLgPXhvnoAWB2u/xfgD8LlPwT+JVxeDdyfx59/ulq/C1yZon3ef/4TuYdwPtDo7jvcvR+4D1gVcU3ZWAXcEy7fA3w0iiLc/VcEZ4wlSlfbKuB7HngWqDOzeRHWmc4q4D5373P3nUAjwb+TvHD3/e7+fLjcAbxGcOV+Qe3XUepMJ7L9Gu6bzvBhWfjlwPuAB8P1yfs0vq8fBC42y8+EU6PUmk7ef/4TORBSTbkx2j/qKDjwczPbaMEUHQBz3H0/BP8xgdmRVXeidLUV4r6+Iexmfzth2K1g6gyHKt5G8Fdiwe7XpDqhAPermcXM7EXgEPAIQQ/liLsPpqjnuGl2gPg0O5HU6u7x/fr5cL9+xcwqkmsN5Xy/TuRAyGbKjahd5O5vBz4EXG9m74q6oJNUaPv6G8DpwLnAfuD/hesLok4zqwH+DfgTd28frWmKdXmrN0WdBblf3X3I3c8lmPHgfOAto9RTULWa2VnATcCbgd8CZgB/GTbPe60TORAKfnoMd98Xfj8EPETwj/lgvFsYfj8UXYUnSFdbQe1rdz8Y/scbBr7JseGLyOs0szKCX7I/cPd/D1cX3H5NVWch79ewviPAEwTj7XUWTKOTXE+6aXbyKqHWS8MhOnf3PuA7RLhfJ3IgFPT0GGY2xcxq48vAB4BNHD8NyDXAj6OpMKV0ta0FPhWeFXEhcDQ+BBKFpHHW3yXYr5B+KpV81WUEV/W/5u5fTniqoPZrujoLcb+aWb2Z1YXLVcD7CY55PE4wjQ6cuE9TTbMTVa2vJ/wxYATHOhL3a35//rk+ah3lF8FR+q0EY4p/FXU9SbUtJTgz4yVgc7w+gvHMR4Ft4fcZEdX3Q4JhgQGCv1SuTVcbQdf2znA/vwKsjLjOe8M6Xib4TzUvof1fhXVuAT6U5336ToIu/8vAi+HXhwttv45SZ8HtV+CtwAthTZuAW8L1SwlCqRH4EVARrq8MHzeGzy8tgFofC/frJuD7HDsTKe8/f01dISIiwMQeMhIRkTFQIIiICKBAEBGRkAJBREQABYKIiIQUCCIiAigQREQk9P8BEBA9WAL/x8AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "sns.distplot([df.onset.iloc[-1] - df.onset.iloc[0] + df.dur.iloc[-1]\n",
    "              for df in prime.values()],\n",
    "             rug=True)\n",
    "plt.title('prime total duration')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[-1] - df.onset.iloc[0] + df.dur.iloc[-1]\n",
    "              for df in cont_foil.values()],\n",
    "             rug=True)\n",
    "plt.title('cont_foil total duration')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[-1] - df.onset.iloc[0] + df.dur.iloc[-1]\n",
    "              for df in cont_true.values()],\n",
    "             rug=True)\n",
    "plt.title('cont_true total duration')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Final note length"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just focussing on the final notes, we see there are a few example where the final note is longer than 8 beats long at the end of the true continuation. However, there are only a few cases where the final note of the primer is longer than 4 beats."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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"
    },
    {
     "data": {
      "image/png": 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9d3e/BbilZtuHq7534O/jrxlTjJfwzVSFe9qMYmm4LDOYLzGnMwsMaiqkiAQrqDtUyyFe3XNPp0aG+0ChRHdHGoChggZURSRMbRfug/ki3R3RLyxaz11EQtUe4R6Xa4olp1ByunNxuKvmLiKBCjPcrX7PfTAuw8zKlcsyCncRCVOY4T7GgOpgPgrzzmyaXCbFoMoyIhKooMK9MEHNfSDuuXdkUuTSKfIFzZYRkTAFFe71eu6p1Oiee0c2RS6T0vIDIhKs4MO9ekC1XHPvzKTJpVOquYtIsIIK95KPDvfMiLJM3HPPxD13hbuIBCqocK9Xc09VDagOVcoy6bgso3AXkTAFFe7lEM/UTIUs1QyodsYDquq5i0ioggr38uqPmfTwZaVTwz36wUIJI1rjPZsZuRSwiEhIggr3fLnnnh45z71cix/MF8llUqTM6EintLaMiAQrqHAv99yzqeqee2rEgGpHJtqnAVURCVlQ4V5ewndEzz1F1Tz3Ih3ZaOkBDaiKSMiCCvdybT0zouduOFHADxZKdJZ77hpQFZGAhRXulQHV4Z77/FnRR+pt3nmAwUJpZM9d4S4igQor3Cs99+FwP+mouXRmU6x9fCcD+aJq7iLSFsIK92KJTMqwqnnuuUyKFy6Zx4NP7mHfQIGOTNRzz6Y1FVJEwhVUuOdLPqIkU3bqMQsolJz+fJGObHTJHRlNhRSRcAUV7oWij5gGWXbk3C6WzO8CGB5Q1WwZEQlYYOFeqttzBzhl+QKASllGs2VEJGRhhXvJR0yDrHbykrkc29PN0QtnAVHPveTDM2xEREKSmekGNNN4PfeOTJp3vvLYyuNcXJ4ZKpZGrEUjIhKCoFIt6rnXD/da2TjQ9VF7IhKioMI9X/TEvfByz31QH7UnIgEKKtwLpRLZMcoytTriHwIaVBWREIUV7sWxB1RrVWruCncRCVBQ4Z4fZ0C1VvWAqohIaIIK9/GmQtbKqSwjIgELK9wn03NXuItIgBKFu5mtMrMNZrbRzC4Z57g3mZmb2crmNTG5QsnJNjgVUmUZEQnRhOFuZmngauBM4ETgfDM7sc5xc4D/BaxpdiOTKkxiKqR67iISoiRJeCqw0d03ufsQcANwdp3jPgp8ChhoYvsSK7lT9OQ3MXUo3EUkYEnCfTGwpepxb7ytwsxeDCx19++PdyIzu9DM1pnZuu3btzfc2PEUKp+f2mDPXWUZEQlQkiSs1xWu3LNvZingc8B7JzqRu1/j7ivdfWVPT0/yViZQKEUhnfQmJs2WEZGQJQn3XmBp1eMlwNaqx3OAFwB3mtnjwMuB1dM9qFrpuesmJhGRROG+FlhhZseYWQ44D1hd3unue9x9kbsvd/flwN3AG9x93ZS0eAyVz09N2HOvLBymsoyIBGjCcHf3AnARcCvwMHCTuz9kZleY2RumuoFJlUM66YBqZeEw9dxFJECJ1nN391uAW2q2fXiMY08/+GY1rtxzzyYcUO3QgKqIBCyYO1QLjfbcNaAqIgELJ9xLjU2FTKWMTMoU7iISpGDCvdGaO0R1d4W7iIQomHAfvokpebhn0ynV3EUkSOGEe/kmpoTz3CHquWsqpIiEKJxwn0TPPZdOaSqkiAQpmHDPNzigCtF0yCQ19/+6bytfv/uJSbdNRGS6BRPujU6FhOQDqjes3czXfqVwF5HWEU64N7j8AMThnqDmvqc/T99gYdJtExGZbuGEe7GEAWlrrOaepOe+pz/PgSGFu4i0jkTLD7SC6FOYDGsg3LPpZLNl9hzIM5DXwKuItI5geu75kide7rcsSc29VHL2DRYYKpZ0w5OItIxgwr1QLCX+oI6yXGbiqZD7Bgt4/NEk/UPFyTZPRGRahRPupeQfjl2WZEB1b3++8n2f6u4i0iLCCfdiqaFpkAAdCQZU91SF+wHNmBGRFhFOuJe8oWmQkKzmXh3umg4pIq0imHDPF0sND6gmmS0zoueumruItIhgwr08FbIRjfbc96vnLiItIpxwL3lDK0JCsgHVEeGuAVURaRHBhHu+WGq8555OkS86pZKz+8AQA/nRZZeRPXeVZUSkNQQT7oWSNzxbJhd/SPZAocjrvvBzPnHLw6OO2dufpzMbHaeyjIi0inDCvVhqeJ57Rxzud27YzpO7+7l707OjjtnTn+fIuV0A7NeAqoi0iHDC/SB67t9atwWAR7f1jZruuKc/z9yuLLNyafXcRaRlhBPuRSfbYM+9fPxPH9nO4nlduMODT+4ZcczeONy7OzJaGVJEWkY44V5q/A7VXBzuJYf3r3oeAPdt2T3imD39eQ7rytKdS2tAVURaRhDhXiiWKHljH9QBw2WZRbM7eP3JR7F0QRf39Y4O97ldGbo7MirLiEjLCCLcyys7TmbJX4A/feGRpFPGyUvmcd+W4bKMu7N3oBCVZXIZzXMXkZYRVLg3uuTv4nldZNPGn79kCQAvWjKPJ3f3s6NvEIhmxxRLHtfcVZYRkdYRxCcxDRai0G10KuQLFs/lgcv+hM5sGoAXLp0HwBdue5TnP+cwdh8YAuB3T+1jVkeG/TsPNLHVIiJTJ4yee75clmms5w5Ugh3gBYsPw4DeXf0A9Md3rHZm03Tn0hxQz11EWkQgPfc43BvsudealctwxGGd9O6KeujlT17qyqUpeUoDqiLSMhKloZmtMrMNZrbRzC6ps//vzWy9md1vZreZ2dHNb+rYymvCZCfRc6+1ZH4Xvbv6cfdKz70rm64MqHr5M/dERA5hE4a7maWBq4EzgROB883sxJrDfgOsdPeTgf8APtXsho6nWT13gMXzuzgwVGTXgfxwzz2bprsjQ8lhIK8PyRaRQ1+SNDwV2Ojum9x9CLgBOLv6AHe/w93Lo413A0ua28zxVQZUm9BzXzp/FgBbdh0Y7rnn0nR3RLV5TYcUkVaQpOa+GNhS9bgXeNk4x78D+EG9HWZ2IXAhwLJlyxI2cWKVAdUGp0LWc8RhnWRSxpO7+smkDSOaD//bzdHNTTf8egsLunMAvPllzbsGEZFmStJzr5eYdQvPZvZWYCXw6Xr73f0ad1/p7it7enqSt3ICzSzLpFPGUfO62LLrAAP5Ip3ZNCmzyg1P5d8SREQOZUnSsBdYWvV4CbC19iAzOwP4IPAGdx9sTvOSKQduMwZUIRpU3bq7n/2DRbpyUTmmvDzwRB/LJyJyKEgS7muBFWZ2jJnlgPOA1dUHmNmLgX8lCvZtzW/m+JrZcwdYMn8W+aLzxLP76cqODPdBhbuItIAJ09DdC8BFwK3Aw8BN7v6QmV1hZm+ID/s0MBv4lpn91sxWj3G6KTGYb96AKkQ9d4C9A4VKuOcy0Z8KdxFpBYluYnL3W4BbarZ9uOr7M5rcroYM99ybE+4Lu3N0ZlMM5Et0jirLqOYuIoe+MJYfmOSqkGMxs8qUyOGeu8oyItI6Agn3IimLZro0y+K4NFMb7hpQFZFWEEa45xv/cOyJVHrucVkmkzJSpp67iLSGMMK90PhH7E1k6YJZZNPGwviGJYvnuqvnLiKtIJBVIYsNfzj2RGZ3ZLj0zBMqA6kAHZm0eu4i0hKCCPeBfPN77jByrXcg7rlrtoyIHPqCKMv0DRYqA55TqSOTYqionruIHPqCCPcdfYPM6Zz6X0JymVRlkTIRkUNZEOG+fd8gszuyU/46HWn13EWkNbR8uJdKPm09946sBlRFpDW0fLjv6c+TLzqzO6ahLJNOKdxFpCW0fLhv74tWF549TTV3zZYRkVbQ+uG+Lwr3OdPQc+/IpMgXnZI+JFtEDnEtH+47prnnDlpfRkQOfS0f7sM992mYLaM13UWkRQQR7rlMis7s1F+Keu4i0iqCCPee2R2YNX/5gVqHdUWln1/+fofq7iJySGv9cO8bZNGcjml5rWMWdvNHKxax5rGdfPc3T1Is1Q/4j3zvQd5z42+npU0iIvW0/MJh2/cNsiRee32qmRmrTnoO2XSK23+3jZM+8kPmdGY54cjD+MoFp5BOGfsHC9y4bgv5ovN/Xn8iC+Ilg0VEplPL99x39A3SM009d4gC/owTjuC8U5byl69YzkuXzeeuR7Zz16PbAbj9d9sYyJcolpyfPPzMtLVLRKRaS/fcC8USz+4fmtZwLzt5yTwAlszv4mcbd/DpH27gqd0DfGPNE/TM6SCXTnHrg09zzsql0942EZGWDved+4dwZ1Lh/s01m5vShkwqxUuXzePnG3ewo2+QDU/v480vW0YmleLrdz9B32BhWpZGEBGp1tJlmW3xHPee2dPfc6+2cvkCSg43rt1CoeTkMinSKWOoWOJj31/PN9dsHveHSb5YGnNwVkRkMlq6S1m+O7VnTo6b1m3h9t9tm/A5aYNinKOf+LM/4APfeWDcYwDmdmXY01/gj59/+IjXKG9fvjAa0H1ydz8Av9/Wxx0bohr8Q1v3csPaLQB84DsP8PiVr2P5JTdz8atXcNVtj1bOtbA7x7P7h7j41Sv4v7c/SskhZbDpk9Hxj1/5Oo7/4C0APPLxswAq28tOu/I2AH5xyas59tKbefcfrwDg2p9v4oHLV416zrn/+isAbnzXKzj20pvZ9Mnhc5X9wUd+WHkuwOd+/Ajvec3xI/adduVtLJk/i5cfu5D3vOb4yrmqjy2/3o3vesWo89R7PNH26nONtX2s5x6sgzlv0uuejra0ghCub6auoaV77tsrPffORMEOI0M76TF7+gsAo16jvP3xZw+M2F4OdoANT+8bse/hp/YCjAh2gGf3D1W2lzvxtZ35oaIzNM4FPLl7gCd3D1See9Vtj3LVbY+yb7D+YmdrHtvJmsd21n2tstrnVre7vO/J3QOseWxnZV/5XLXXWH6tevtqH0+0vfpcSV+jWQ7mvEmvezra0gpCuL6ZuobWDve4575ozqE73TBf8+Ee53zxVzPUEhFpJ60d7vsGmd2RYVbu0K0u/flLl4x4vGD2ofuDSETC0fLhPhPTIBvxkmXzRzw+75RlM9QSEWknrR/uMzxTplFzu6Z+9UoRkZYO9x19g4d0vV1EZKa0dLi3Ys+9Ua/6pzsBWPd4/dkhIiL1JAp3M1tlZhvMbKOZXVJnf4eZ3RjvX2Nmy5vd0Gruzk/WP8PegQKLAg/34w6fDcC519xd2ZYvlijEs3A2buujpBugRKTGhNNMzCwNXA28BugF1prZandfX3XYO4Bd7n6cmZ0H/CNw7lQ0+P7e3Xzs5of59WM7OWZRN2940VFT8TKHjFc973B+vP4ZTjrqMO7v3QPA8z70g8r69Wd89qcs7M7xyhWLKs+5bPVDo85zwVd+zUNbozn2Z1/9C1553MLKvh888BQAd296lkWzc/TM6aRQLPHUnmjO/Pqte1k0O1eZv/5A7x72D0Vz/Ffft3XE6/zHPb0A3PPELgD2HMjTkU1xYCiaE7+jb5CubPSJVkOFEtXL8BeKJcyM8qZpWKK/whtcn7/R46PnRH/W/jA+2B/O1c+f6h/zk7nuhl+j5nHtdOJmyaSs8v+oWHIKpRK5dAozw90ZLJRwh85stK1QLLF/sEgqBd25DGawf6jI3v48Xdk0c7uylNx5Zt8gu/YPsXB2jsPndAJwzxM72dOfZ/nCbpYtmEUmPfVFE5vozTKzVwCXufufxI8vBXD3T1Ydc2t8zK/MLAM8DfT4OCdfuXKlr1u3ruEGf/3uJ/j8Tx7h4jOO57xTlpKN/5KWX3Jzw+ca6w7VZqp9jUZfs3z8x9/4Aj743QeBKPAd584N2/kfL17Mph37+f22PvYNRoHbkUmN+ijA5xzWyVHzOrl3826WLZhF764DY964JNIOzCCXTuEOQ/EPkPK2fLFU+f9R3lb9f8os+uGQr7qp0AyMkTcEpmz0DYK5dIrLzz6J80+d3Mw5M7vH3VdOeFyCcH8TsMrd3xk/fhvwMne/qOqYB+NjeuPHv4+P2VFzrguBC+OHzwM2JL+kcS0Cdkx4VHja9bpB196O196u1w0jr/1od++Z6AlJ7v6p98tx7U+EJMfg7tcA1yR4zYaY2bokP8lC067XDbr2drz2dr1umNy1Jyn89ALVi5IvAbaOdUxclpkLaHqHiMgMSRLua4EVZnaMmeWA84DVNcesBt4ef/8m4Pbx6u0iIjK1JizLuHvBzC4CbgXSwLXu/pBDp6G1AAACxUlEQVSZXQGsc/fVwL8BXzOzjUQ99vOmstF1NL3U0yLa9bpB196O2vW6YRLXPuGAqoiItJ6WvkNVRETqU7iLiASopcN9omURQmZmj5vZA2b2WzNr/G6wFmJm15rZtvh+ivK2BWb2YzN7NP5z/njnaEVjXPdlZvZk/L7/1szOmsk2ThUzW2pmd5jZw2b2kJldHG8P+n0f57obft9btuYeL4vwCFXLIgDn1yyLECwzexxYWXujWIjM7L8BfcBX3f0F8bZPATvd/cr4B/t8d/+HmWxns41x3ZcBfe7+TzPZtqlmZkcCR7r7vWY2B7gHeCNwAQG/7+Nc9zk0+L63cs/9VGCju29y9yHgBuDsGW6TTAF3v4vR902cDfx7/P2/E/0HCMoY190W3P0pd783/n4f8DCwmMDf93Guu2GtHO6LgS1Vj3uZ5F9Ci3LgR2Z2T7ysQ7s5wt2fgug/BHD4DLdnOl1kZvfHZZugyhL1xKvMvhhYQxu97zXXDQ2+760c7omWPAjYae7+EuBM4O/iX+ElfP8CPBd4EfAU8JmZbc7UMrPZwH8C/9vd9850e6ZLnetu+H1v5XBPsixCsNx9a/znNuA7RGWqdvJMXJ8s1ym3zXB7poW7P+PuRXcvAV8i4PfdzLJEAfcNd/92vDn4973edU/mfW/lcE+yLEKQzKw7HmzBzLqB1wIPjv+s4FQvefF24Hsz2JZpUw622J8R6Ptu0ULr/wY87O6frdoV9Ps+1nVP5n1v2dkyAPF0oM8zvCzCx2e4SdPCzI4l6q1DtITEN0O+djO7HjidaNnTZ4CPAN8FbgKWAZuBv3D3oAYfx7ju04l+NXfgceBd5Rp0SMzslcDPgAeA8kLqHyCqPwf7vo9z3efT4Pve0uEuIiL1tXJZRkRExqBwFxEJkMJdRCRACncRkQAp3EVEAqRwFxEJkMJdRCRA/x+rYcoU7Hp+kgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "sns.distplot([df.dur.iloc[-1]\n",
    "              for df in prime.values()],\n",
    "             rug=True)\n",
    "plt.title('prime final note length')\n",
    "plt.show()\n",
    "sns.distplot([df.dur.iloc[-1]\n",
    "              for df in cont_foil.values()],\n",
    "             rug=True)\n",
    "plt.title('cont_foil final note length')\n",
    "plt.show()\n",
    "sns.distplot([df.dur.iloc[-1]\n",
    "              for df in cont_true.values()],\n",
    "             rug=True)\n",
    "plt.title('cont_true final note length')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Onset times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Where within the piece does the exerpt start? Some...appear to be very long pieces, having an onset time of over 4000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qKv/KVMbzqczeyVdz/IpNup4ge0XqYQcKM+sALQNFel3pncDVwGrgo5JW12S7HjgYEZcAdwC3p31Xk70W9TJgPfDpVN4wcHlE/CSwBlgv6T2prNuBOyJiFXAwlT3jssHsxoFioL+bo+56MrMOkKdFsQ4YjIidETECbAY21OTZANyblh8ErpCklL45IoYjYhcwCKyLzLGUvyd9Iu1zeSqDVOaHJ1i3SSmVo2mLYmBeD0fcojCzDpAnUFwM7K5a35PS6uaJiCJwGFjcbF9JBUlPAfuARyNia9rnUCqj0bFI+98gaZukbfv3789RjfEZLTV+4A6yO5+Gi+Wxd2ubmbWrPIGi3p/VkTNPw30johQRa4BlwDpJP57zWKT974qItRGxdsmSJQ1PfqKK5eZdTwv7uwHYd2Royo9tZnYmyRMo9gDLq9aXAS83yiOpG1gEHMizb0QcAr5ONobxGnB2KqPRsWZEsRwUGtz1BFnXE8ArDhRm1ubyBIongFXpbqRessHpLTV5tgDXpeVrgMciIlL6xnRX1EpgFfC4pCWSzgaQNA94H/D9tM/XUhmkMr808epNXLFUpqfZGEV66G7fkeGZOiUzs1nR3SpDRBQl3QQ8AhSAeyJiu6TbgG0RsQW4G7hP0iBZS2Jj2ne7pAeAZ4EicGNElCRdCNyb7oDqAh6IiIfSIT8BbJb0e8B3Utkzrlhq/MAdZHc9AbzqFoWZtbmWgQIgIh4GHq5Ju7VqeQi4tsG+m4BNNWlPA29vkH8n2Z1Ws6pYLjd8cRFAX0+Bvu4udz2ZWdvzk9kNFJtM4VGxsL/HXU9m1vYcKBrIphlv/vUMzOt215OZtT0HigayrqfmLYqB/h53PZlZ23OgaKDVYDZkA9r7jgyT3axlZtaeHCgaaPbO7IqBeT2MlMocPOGpPMysfTlQNFBsMYUHZIPZ4Ftkzay9OVA00OzFRRV+lsLMOoEDRQOlnF1P4EBhZu3NgaKOiEiBokXXU1+lReFnKcysfeV6MruTfH7rSxTLZQCe3XuEz299qWHe7kIX587vdYvCzNqaWxR1pDhBl5p3PQEsHeh3oDCztuZAUUc5PRfRYiwbgKUDfe56MrO25kBRR6mcBYquFoPZAEsX9vvpbDNraw4UdVRaFLm6nhb189qxYYql8nSflpnZrHCgqKPSoijkaVEM9BEBrx0bme7TMjObFbkChaT1knZIGpR0c53tfZLuT9u3SlpRte2WlL5D0lUpbbmkr0l6TtJ2Sb9alf+Tkn4k6an0+cDkqzk+KU5QyNGiuGCgH/ArUc2sfbW8PTa9he5O4Eqyd2A/IWlLRDxble164GBEXCJpI3A78BFJq8nedncZcBHwFUmXkr3t7uMR8W1JC4EnJT1aVeYdEfFfpqqS41UeG6NonXdpChS+88nM2lWeFsU6YDAidkbECLAZ2FCTZwNwb1p+ELhCklL65ogYjohdwCCwLiL2RsS3ASLiKPAccPHkqzM1SuMYozh/oA+AfQ4UZtam8gSKi4HdVet7eONFfSxPRBSBw8DiPPumbqq3A1urkm+S9LSkeySdU++kJN0gaZukbfv3789RjfzGM5h93vw+Cl1y15OZta08gaLe1bL2BQyN8jTdV9IC4IvAr0XEkZT8Z8CPAWuAvcB/rXdSEXFXRKyNiLVLlixpXoNxGs9gdleXOH+hn6Uws/aVJ1DsAZZXrS8DXm6UR1I3sAg40GxfST1kQeJzEfG3lQwR8WpElCKiDPw5WdfXjCqPI1AAnO+ns82sjeUJFE8AqyStlNRLNji9pSbPFuC6tHwN8Fhkr33bAmxMd0WtBFYBj6fxi7uB5yLij6oLknRh1eq/Ap4Zb6Umq5TaPHm6ngAuGOhzoDCzttXyrqeIKEq6CXgEKAD3RMR2SbcB2yJiC9lF/z5Jg2QtiY1p3+2SHgCeJbvT6caIKEl6L/Ax4HuSnkqH+p2IeBj4Q0lryLqoXgB+aQrrm8vYGEXOp0yWDvTzrZ0HpvGMzMxmT67ZY9MF/OGatFurloeAaxvsuwnYVJP2TeqPXxARH8tzTtNpbIwiZ4ti6UA/h0+OMjRaor+nMJ2nZmY24/xkdh3juesJ/CyFmbU3B4o6xjuYvTQ9S+E7n8ysHTlQ1DE2mJ07UHgaDzNrXw4UdYxN4ZEvTowFCj+dbWbtyIGijlKMbzB7oL+b/p4uj1GYWVvyO7PrGM8YReWd2vN7u9m668DY+s+9+03Td4JmZjPILYo6xjMpYMXC/h6OnCxO1ymZmc0aB4o6yuN4FWrFwLxujg6NTtcpmZnNGgeKOsbz4qKKgf4ejgyNElE7X6KZ2dzmQFFHaRwvLqoY6O9mtBQMjfrd2WbWXhwo6iiP864ngIXzegA44u4nM2szDhR1jA1mj2eMot+BwszakwNFHeVyIMZ319NAf3an8VHf+WRmbcaBoo5SeXytCYABdz2ZWZtyoKijHJF7+o6KnkIX83oKDhRm1nYcKOooReSeObbawv5uP3RnZm0nV6CQtF7SDkmDkm6us71P0v1p+1ZJK6q23ZLSd0i6KqUtl/Q1Sc9J2i7pV6vynyvpUUnPp5/nTL6a41Mux7jGJyoG5vW4RWFmbadloJBUAO4ErgZWAx+VtLom2/XAwYi4BLgDuD3tu5rstaiXAeuBT6fyisDHI+JtwHuAG6vKvBn4akSsAr6a1mdUOWJct8ZWDPT3cHTILQozay95WhTrgMGI2BkRI8BmYENNng3AvWn5QeAKSUrpmyNiOCJ2AYPAuojYGxHfBoiIo8BzwMV1yroX+PDEqjZxExnMhuzOp6NDo2PPYZiZtYM8geJiYHfV+h5OXdTfkCciisBhYHGefVM31duBrSlpaUTsTWXtBc6vd1KSbpC0TdK2/fv356hGfhMZzIbsobtywPFhtyrMrH3kCRT1Lpm1fzI3ytN0X0kLgC8CvxYRR3Kcy6lCIu6KiLURsXbJkiXj2bWlUnlig9mL0rMUR9z9ZGZtJE+g2AMsr1pfBrzcKI+kbmARcKDZvpJ6yILE5yLib6vyvCrpwpTnQmBf3spMlaxFMZG7ntKzFCc9oG1m7SNPoHgCWCVppaRessHpLTV5tgDXpeVrgMcim0Z1C7Ax3RW1ElgFPJ7GL+4GnouIP2pS1nXAl8ZbqckqT7BF4YfuzKwdtXzDXUQUJd0EPAIUgHsiYruk24BtEbGF7KJ/n6RBspbExrTvdkkPAM+S3el0Y0SUJL0X+BjwPUlPpUP9TkQ8DPwB8ICk64GXgGunssJ5lCbYoljQ143Adz6ZWVvJ9SrUdAF/uCbt1qrlIRpc0CNiE7CpJu2b1B+/ICJeB67Ic17TpVzO9xrUWoUusaCv211PZtZW/GR2HaUJ3vUEfujOzNqPA0Ud5XJM6DkKyKbxcNeTmbUTB4o6ShN8Mhuyp7MPu+vJzNqIA0UdE709FmBgXjcnRkoMF0tTfFZmZrPDgaKOiQ5mw6k33e07MjyVp2RmNmscKOooxWTGKFKgODo0ladkZjZrHCjqyKYZn9i+A/OyO45fdYvCzNqEA0Udkx3MBnjlsFsUZtYeHCjqmMztsWf1Fih0iVfd9WRmbcKBoo5SMOEWhSQG+rs9mG1mbcOBoo7JtCggG9B215OZtQsHijqyV6FOfP+BeT3uejKztuFAUUdpki2Kgf5uXnWLwszahANFHeVJ3PUE2Z1Px0dKHPMrUc2sDThQ1IgIysHkWhRjz1K4VWFmc1+uQCFpvaQdkgYl3Vxne5+k+9P2rZJWVG27JaXvkHRVVfo9kvZJeqamrE9K+pGkp9LnAxOv3viV0xu9JzrXE5x6OtvdT2bWDloGCkkF4E7gamA18FFJq2uyXQ8cjIhLgDuA29O+q8nedncZsB74dCoP4C9TWj13RMSa9Hm4QZ5pUUqRYqJzPcGph+48oG1m7SBPi2IdMBgROyNiBNgMbKjJswG4Ny0/CFyR3ou9AdgcEcMRsQsYTOUREd8ge23qGaUcWaCYRJxgoN/TeJhZ+8gTKC4Gdlet70lpdfNERBE4DCzOuW89N0l6OnVPnVMvg6QbJG2TtG3//v05isynPAUtir6eAgv6uv0shZm1hTyBot4VM3LmybNvrT8DfgxYA+wF/mu9TBFxV0SsjYi1S5YsaVFkfqWxFsUkmhTA+QN9nkHWzNpCnkCxB1hetb4MeLlRHkndwCKybqU8+54mIl6NiFJElIE/J3VVzZTKYPZkbo8FuGCg311PZtYW8gSKJ4BVklZK6iUbnN5Sk2cLcF1avgZ4LCIipW9Md0WtBFYBjzc7mKQLq1b/FfBMo7zToTKYPZnbYwGWDvS768nM2kJ3qwwRUZR0E/AIUADuiYjtkm4DtkXEFuBu4D5Jg2QtiY1p3+2SHgCeBYrAjRFRApD0BeBfAudJ2gP8PxFxN/CHktaQdVG9APzSVFa4lakYzIZTXU8RgSbZOjEzm00tAwVAukX14Zq0W6uWh4BrG+y7CdhUJ/2jDfJ/LM85TZepuD0Wsq6n0VJw4PgIixf0TcWpmZnNCj+ZXaM8RYPZSwf6Ad8ia2ZznwNFjXI5+znZFsVYoPCdT2Y2xzlQ1Jiq22OXDmTdTZ7Gw8zmOgeKGlM1RnH+Qnc9mVl7cKCoMVV3PfV2d7F4fq+7nsxsznOgqDEVU3hUnD/Q764nM5vzHChqTNUYBWTjFG5RmNlc50BRo3LX02SfzAa4cNE89hw8SUSr6a3MzM5cDhQ1Ki2Kyc71BHDp0gUcOjHKvqMe0DazucuBosZUDWYD/JMLFgLw/VeOTr4wM7NZ4kBRYyoHs996wQAAO145MumyzMxmS665njrJVM0e+/mtLwGwsK+bL3/vFRb0Za9H/bl3v2lyJ2hmNsPcoqhReR/FVNz1BLB0UT+vHvGdT2Y2dzlQ1BgbzJ6KQQqyWWT3HR0ea6mYmc01DhQ1xsYopqpFMdBPsRy8ftx3PpnZ3ORAUWMq73oCuGCR53wys7ktV6CQtF7SDkmDkm6us71P0v1p+1ZJK6q23ZLSd0i6qir9Hkn7JD1TU9a5kh6V9Hz6ec7Eqzd+UzWYXXH+wj4Efi2qmc1ZLQOFpAJwJ3A1sBr4qKTVNdmuBw5GxCXAHcDtad/VZK9FvQxYD3w6lQfwlymt1s3AVyNiFfDVtD5jpnqMoqfQxeIFfR7QNrM5K0+LYh0wGBE7I2IE2AxsqMmzAbg3LT8IXKHsRdEbgM0RMRwRu4DBVB4R8Q2y92vXqi7rXuDD46jPpFWm8JjKt1xfMNDHKw4UZjZH5QkUFwO7q9b3pLS6eSKiCBwGFufct9bSiNibytoLnF8vk6QbJG2TtG3//v05qpFPOYKChKZoMBuyW2QPHh9hpFiesjLNzGZKnkBR74pZe69nozx59p2QiLgrItZGxNolS5ZMRZFANkbRNcVD/BcM9BPg7iczm5PyXBL3AMur1pcBLzfKI6kbWETWrZRn31qvSrowlXUhsC/HOU6ZcsSUPWxXcUHl/dkOFGY2B+UJFE8AqyStlNRLNji9pSbPFuC6tHwN8Fhkc2tvATamu6JWAquAx1scr7qs64Av5TjHKVMqx5QNZFecM7+XnoI8TmFmc1LLQJHGHG4CHgGeAx6IiO2SbpP0oZTtbmCxpEHgN0h3KkXEduAB4FngfwI3RkQJQNIXgH8E/omkPZKuT2X9AXClpOeBK9P6jCnH1E3fUdElsXSg34HCzOakXJMCRsTDwMM1abdWLQ8B1zbYdxOwqU76Rxvkfx24Is95TYfyNLQoIHtC+/t7PYusmc09fjK7Riliyp7KrnbBQD/HR0rs90uMzGyOcaCoMR2D2ZC1KAB2+CVGZjbHOFDUmI7BbDg159P3/RIjM5tjHChqTNcYxYK+bub3dbtFYWZzjgNFjem466nigoE+drzqQGFmc4sDRY3pGsyGbED7B68e9UuMzGxOcaCoMV1jFJANaA+NlnnpwIlpKd/MbDo4UNSYrrue4NSA9g4PaJvZHOJAUWO6BrMBzl/YjwTf94C2mc0hDhQ1RktBd2F6vpbe7i5WLJ7Pd3cfmpbyzcymgwNFjeMjReb3FlpnnKD3r17K3z//Gq8d8xPaZjY3OFBUiQhODJeY35drCqwJ+dfvXEaxHHzpqVazrZvC7BUMAAAMqUlEQVSZnRkcKKocHS5SiuCsaWxRXLp0IT+xbBFffHLPtB3DzGwqOVBUOXh8BID5vdPXogC45p3LeHbvEba/fHhaj2NmNhUcKKocSIHirL7pa1EA/OxPXERPQXzxyR9N63HMzKZCrkAhab2kHZIGJd1cZ3ufpPvT9q2SVlRtuyWl75B0VasyJf2lpF2SnkqfNZOrYn4HT0x/i+LzW1/iy8+8wqVLF3L/Ey9x3z++yOe3vjRtxzMzm6yWgUJSAbgTuBpYDXxU0uqabNcDByPiEuAO4Pa072qyV6deBqwHPi2pkKPM34qINenz1KRqOA6vH0uBYhoHsyv+6cWLOD5SYu/hk9N+LDOzycjTolgHDEbEzogYATYDG2rybADuTcsPAldIUkrfHBHDEbELGEzl5SlzxlVaFNM5mF2xYvF8AF547fi0H8vMbDLyBIqLgd1V63tSWt086R3bh4HFTfZtVeYmSU9LukNSX72TknSDpG2Stu3fvz9HNVo7cHyUgkRf9/QP3QzM6+Hc+b288LrnfTKzM1ueK2K9+Sxqpz9tlGe86QC3AG8F3gWcC3yi3klFxF0RsTYi1i5ZsqRelnE7eHyEs/oKaJrmeqq1YvFZvPj6cSI8m6yZnbnyBIo9wPKq9WVA7dNiY3kkdQOLgANN9m1YZkTsjcww8FmybqoZceDEyLTfGlvtzYvnc3ykxGtpbMTM7EyUJ1A8AayStFJSL9ng9JaaPFuA69LyNcBjkf2ZvAXYmO6KWgmsAh5vVqakC9NPAR8GnplMBcfjQGpRzJSxcYrXPU5hZmeuln8+R0RR0k3AI0ABuCcitku6DdgWEVuAu4H7JA2StSQ2pn23S3oAeBYoAjdGRAmgXpnpkJ+TtISse+op4JenrrrNHTw+MiN3PFWct6CX+b0FD2ib2Rkt11UxIh4GHq5Ju7VqeQi4tsG+m4BNecpM6ZfnOafpcODECEsW1h07nxaSePPi+bzoFxmZ2RnMT2YnxVKZwydHZ7RFAbDivPkcOD7Cq0eGZvS4ZmZ5OVAkh06OEsG0TjFez4rFZwHw+K4DM3pcM7O8HCiSg2PzPM1si+LCRfOY31vgS0953iczOzM5UCQHZmjm2FqFLvHutyzmK8/tY+f+YzN6bDOzPBwokrEJAWfw9tiKd688l95CF5/93y/M+LHNzFpxoEher3Q9zXCLAmBhfw8b1lzEg0/u4dAJP3xnZmcWB4pkbIxihgezK67/6ZWcHC3x+cc95biZnVkcKJIDx0eZ31ugpzA7X8lbLxjgvZecxz3ffIEjQ6Ozcg5mZvXMfD/LGergiRHOmd/L7/y3783K8auP+xOf/F+59lnYV+DocGlsvUun3967+qJFPPHCAX7l8lU8+ORurnnncr618/Wx7c++fJiBeT3sPTzEr1y+im/tfJ33vGXx2M9Wfv3KSwG449Ef8OtXXsodj/7gtG311iv7VO9XrVFa9fHqqbffeNOr69HsWOM9hzOZz3numY36u0WRvH58hMXze2f7NMalOkgAlCNLq3y27jpAOeBPvvo8Pzo0xJ989Xm27jow9jk6XOJHh4bG8mzddeC0n60+FZXl2m311qvVrjdLq5fear/xpjc6z7wmut9s8jnPPbNRfweK5ODxrEVhZmanc6BIDhwf4dyzHCjMzGo5UCSVMQozMzudAwUwNFrixEiJcx0ozMzewIGCU9N3OFCYmb2RAwXwzedfA+CCgf5ZPhMzszNPrkAhab2kHZIGJd1cZ3ufpPvT9q2SVlRtuyWl75B0Vasy0+tRt0p6PpU5rX/m73rtOJ/679tZt/Jc/sWlS6bzUGZmc1LLB+4kFYA7gSuBPcATkrZExLNV2a4HDkbEJZI2ArcDH5G0muy1qJcBFwFfkVR5UqRRmbcDd0TEZkmfSWX/2VRUttZIscy//8J36C508ccfWUOhS9NxmLb1yuEhutKfGi/WvPd7cN/pM+HuO5q9mOnI0ChRht7uU3+jRATlgFI5ADg2XKRUDsrloBQxlu/ESJG+7kLDf6fK/gKk7A2CeQ2NlsbqVDmnPPtHBMPFMsPFcu5jzYSIIAICKI8tp59VywCjpTLdXRrX9zUbIoLjI9m/04mRIvN6CpM+59p/58rvYvXvWOX3sPIdRQQjpTJC9BSytHI5ODFaortL9HV3IYmh0RLHh4vM6y0wr6dABBw+OcqJ0RKL5vUwv7fAcLHM/qPDDBfLLFnYx0B/N/uPDfPS6ycodIkVi+czr7fAd146xFO7D7F0IHsD5+4DJ3jo6b089PTL/PFH1rBq6cJJfQ+tKKr+I9bNIP0z4JMRcVVavwUgIn6/Ks8jKc8/SuoGXgGWADdX563kS7u9oUzgD4D9wAXpXd2nHbuRtWvXxrZt23JXuuI/Pfwcd31jJ5/5hXey/scvAGDFzf9j3OXYxBW6NHaBz6u7S/QUuihHUEr/iVv8GmeBgyx4CCiWI/tPjgiC0VK8IX9XypvtmxVQvS5lf2wUq86/t7uLQrrwBKfSq8+v2alWLk+Va5c4dcGqpDW66JcjO2Kr76KRnoLo7upCOlVGpQ6n1ptUQqf9eEMdWp1/VBVTCfTV3/do6fTvunK+QXZxrwTHcrrYQzZbgaSxnyL7d638m5fKQZegp9BFkAXNiGy/3u4uSuVTvxuVtJFieaz8Qpfo7tJpfygUukRBYqR0Kq27S6edVyWtWPO7X+//Q/W/R601y8/mP35wNe988zn1M7Qg6cmIWNsqX54pPC4Gdlet7wHe3ShPusAfBhan9G/V7HtxWq5X5mLgUEQU6+Q/jaQbgBvS6jFJO3LUpa6rbx9bPA94baLltIFOrn8n1x06u/5ztu4vAl+6aVJFvDlPpjyBol7brja+NcrTKL3e2Eiz/G9MjLgLuKvetomStC1PdG1XnVz/Tq47dHb9O7nueeUZzN4DLK9aXwa83ChP6npaBBxosm+j9NeAs1MZjY5lZmYzKE+geAJYle5G6iUbnN5Sk2cLcF1avgZ4LLLBjy3AxnRX1EpgFfB4ozLTPl9LZZDK/NLEq2dmZpPVsuspjTncBDwCFIB7ImK7pNuAbRGxBbgbuE/SIFlLYmPad7ukB4BngSJwY0SUAOqVmQ75CWCzpN8DvpPKnilT2pU1B3Vy/Tu57tDZ9e/kuufS8q4nMzPrbH4y28zMmnKgMDOzphwoaD1FyVwl6R5J+yQ9U5V2rqRH0xQpj0o6J6VL0p+m7+BpSe+o2ue6lP95SdfVO9aZRtJySV+T9Jyk7ZJ+NaV3Sv37JT0u6bup/p9K6XWnyJnINDxnOkkFSd+R9FBa75i6T7nsacbO/ZANpv8QeAvQC3wXWD3b5zVFdfsXwDuAZ6rS/hC4OS3fDNyelj8AfJnsWZb3AFtT+rnAzvTznLR8zmzXLUfdLwTekZYXAj8AVndQ/QUsSMs9wNZUrweAjSn9M8D/lZb/b+AzaXkjcH9aXp3+T/QBK9P/lcJs1y/nd/AbwOeBh9J6x9R9qj9uUcA6YDAidkbECLAZ2DDL5zQlIuIbZHehVdsA3JuW7wU+XJX+V5H5FtnzLBcCVwGPRsSBiDgIPAqsn/6zn5yI2BsR307LR4HnyJ7y75T6R0RUJtzqSZ8ALgceTOm19a98Lw8CVyibBGkDsDkihiNiFzBI9n/mjCZpGfAzwF+kddEhdZ8ODhT1pyipO21Im1gaEXshu5gC56f0Rt/DnP9+UlfC28n+qu6Y+qeul6eAfWQB7oc0niLntGl4gOppeOZi/f8Y+G2gMuFSs+mB2q3uU86BYhzThrS58U7DMidIWgB8Efi1iDjSLGudtDld/4goRcQashkO1gFvq5ct/Wyb+kv6ILAvIp6sTq6Tte3qPl0cKPJNUdJOXk1dKqSf+1L6eKdbOeNJ6iELEp+LiL9NyR1T/4qIOAR8nWyMotEUOeOdhudM9lPAhyS9QNaVfDlZC6MT6j4tHCjyTVHSTqqnW6meImUL8H+mu3/eAxxOXTOPAO+XdE66Q+j9Ke2MlvqY7waei4g/qtrUKfVfIunstDwPeB/ZOE2jKXLGOw3PGSsibomIZRGxguz/82MR8fN0QN2nzWyPpp8JH7I7Xn5A1of7u7N9PlNYry8Ae4FRsr+Orifre/0q8Hz6eW7KK7KXSf0Q+B6wtqqcXyQbyBsE/s1s1ytn3d9L1k3wNPBU+nygg+r/E2RT4DwNPAPcmtLfQnaxGwT+BuhL6f1pfTBtf0tVWb+bvpcdwNWzXbdxfg//klN3PXVU3afy4yk8zMysKXc9mZlZUw4UZmbWlAOFmZk15UBhZmZNOVCYmVlTDhRmZtaUA4WZmTX1/wMz5huxaQ4RDAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot([df.onset.iloc[0] for df in prime.values()], rug=True)\n",
    "plt.title('prime onset times')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[0] for df in cont_foil.values()], rug=True)\n",
    "plt.title('cont_foil onset times')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[0] for df in cont_true.values()], rug=True)\n",
    "plt.title('cont_true onset times')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "max_onset = 400\n",
    "sns.distplot([df.onset.iloc[0] for df in prime.values()\n",
    "              if df.onset.iloc[0] <= max_onset],\n",
    "             rug=True)\n",
    "plt.title('prime onset times')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[0] for df in cont_foil.values()\n",
    "              if df.onset.iloc[0] <= max_onset],\n",
    "              rug=True)\n",
    "plt.title('cont_foil onset times')\n",
    "plt.show()\n",
    "sns.distplot([df.onset.iloc[0] for df in cont_true.values()\n",
    "              if df.onset.iloc[0] <= max_onset],\n",
    "              rug=True)\n",
    "plt.title('cont_true onset times')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Time between prime final note **offset**, and continuation first note **onset**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The HMM appears to be good at getting the location of the first note in the continuation correct. The distributions match pretty well. A large chunk of the data start immediately after the final note of the prime finishes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 1, figsize=(6,6), sharex=True, sharey=True)\n",
    "cont = cont_true\n",
    "plt.sca(ax[0])\n",
    "sns.distplot(\n",
    "    [cont[fn].onset.iloc[0] - (prime[fn].onset.iloc[-1] + prime[fn].dur.iloc[-1])\n",
    "     for fn in prime.keys()],\n",
    "    rug=True\n",
    ")\n",
    "plt.title('Time between prime last note end and *cont_true* first note start')\n",
    "plt.sca(ax[1])\n",
    "cont = cont_foil\n",
    "sns.distplot(\n",
    "    [cont[fn].onset.iloc[0] - (prime[fn].onset.iloc[-1] + prime[fn].dur.iloc[-1])\n",
    "     for fn in prime.keys()],\n",
    "    rug=True\n",
    ")\n",
    "plt.title('Time between prime last note end and *cont_foil* first note start')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.5833299999999895"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max([cont_true[fn].onset.iloc[0] - (prime[fn].onset.iloc[-1] + prime[fn].dur.iloc[-1])\n",
    "     for fn in prime.keys()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "90.99995999999987"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "7.5833299999999895 * 12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Note durations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Are note durations of standard lengths? Some are very long."
   ]
  },
  {
   "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": [
    "part = prime\n",
    "part_note_lengths = np.hstack([part[fn].dur for fn in prime.keys()])\n",
    "sns.distplot(\n",
    "    part_note_lengths\n",
    ")\n",
    "plt.title('')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": [
    "max_note_len = 4\n",
    "sns.distplot(\n",
    "    [ll for ll in part_note_lengths if ll <= max_note_len]\n",
    ")\n",
    "plt.title('')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Durations are regular - they've been quantised breaking each quarter note into 12."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8md2K0hILRnLU0WI+CkcUAqHInGtQFQ4bRFjFR2RWGQUopdR2AG0GjcVwHUMevPf0Bafc7iq1YSLLGVQ4ojAVDM+aQQHRdSiuQWVPfJNugj58AGCxCCocNk7xEZlU0XaSGPMGMeoNvq2CT+Ny2LI+xecNzN5FQlPjtOesJ+B8FG9zNMcUHxDrx8cARWRKRRugToz7AABNVaWn3Ody2DCZ5Wmd+CbdBFNMNeUlzKCyaCqgdfGYO0CxHx+ReRVtgBry+AEAdS77Kfe5SrOfQSXqw6eJZlB8Y8wWb5I+fJrKUnY0JzKrog1QWnZSV+445T6XwwZvIJzVdkfJAlRtuR3DnOLLmmSdzDWVZTy0kMisijZADU1G3/xry2fJoBzZb3fkTTLFV+20Y2wqmJOegPORViThTJJBcYqPyLyKN0B5AhABapwlp9xXkYO9UIk6mWtqnSVQintwskXLoEqTZVCc4iMyraINUMMeP6rLSmCznvpPzEU3CU8ghLISK6yW2Ttpa90kWCiRHd5gGKUlllP6IM5UVVYCbyCMYJid5YnMpogDVGDW6T1gWoDKYiVfoj58mpp4NwkGqGyYCszdRUJTyXZHRKZVtAFqcDIwa4EEcLLdUTY36ybqw6epZT++rIr24Uu+D72K7Y6ITKtoA9RcGVQu2h0l6sOniTeMZQaVFd5AKGkFH8BDC4nMrKgD1Gx7oDTZ3gvlTTrFF/3kzoax2eFN0slcwwyKyLyKMkCFIwoj3gDqEmRQQHbbHSmlohnUHFNMZSVWOGwWTvFlSbKzoDTxQwsZoIhMpygD1Ig3AKVm3wOlcTlsWTu00BeMIKIA5xxTfCIS3azLAGW4SERxDYqoCBRlgNLe9GtdsxdJANmd4ot3kUgyxVTttHOKLwsmfCEoJO/DB0yr4uNeKCLTKcoApXWRqE+SQU1lqd2RJ0knc01teQmLJLJAe05TCVClJVbYbRZmUEQmVJQB6mQGNXeAUjgZTIyUrA+fptpp5xpUFozGgk0qVXxArJsE+/ERmU5RBiitk3myNSggO5t1kx21oal12plBZcHJDCq18zirynhoIZEZFWeAik3xad0aZpPNfnypZlA15XaM5qBhrFIKk/4Q+sZ92HZ0uOgPShyLreslaxSrqSxjPz4iM8royHezGvYEUFVWgpJZ+vBpsppB+UOw2yxzXh+I7oVSKlriXDNHtpepX+/rw0sHBgAA//XiQVy1sRn3Xr8pa9fLNy2DSnWKr6qMh0cSmVHGGZSIWEXkTRH5uREDMkKyTbrAyXZHWcmgAuGk03vAySnIbJ8LdXTQA7fLgevOasXZS2uxp3ssq9fLN+0gyPTWoJhBEZmNEVN8nwGwz4DvY5jBSf+cm3SBaLujEqtgIgtTOx5/KJ6hzSXeMDaLn96VUugb92NJvRMbWqqxeWktjg154Iudl1SMRr2BlDqZayrLbKziIzKhjAKUiLQAeC+A7xkzHGPM1YdvuorSkqxkUJP+ufvwaU52NM/em+OkP4SpYBgNFaUAgJWNFYgo4PDAZNaumW+jU8GUCySA6P/D2FQQER4eSWQqmWZQ/wngdgAJD9MRkdtEpF1E2gcGBjK8XGqiASrxJl1NttodpZxBlcf68WUxg+qfiFY0NlZGA9TqpgoAwMG+4g1QI95gSnugNLXldkTUyfJ0IjIH3QFKRN4HoF8p9fpcj1NK3aeUalNKtbndbr2XS1kk1oevPskaFJCdAKVVzKWSQeViDap/3AcAaKiIBuwldeWwWQQH+iayds18G/MG0g5QQPSQSyIyj0wyqPMBXC0ixwA8BuAiEXnIkFFlYHQqiEiSPnyabPTjG58KIaKQUgZVFutikM29UH0TfpSWWOJl9XabBUvry3GwiAPUiDeYUqNYzckAxQyKyEx0Byil1BeVUi1KqSUArgPwG6XUjYaNTKehyeSbdDWu0mi7o5CBx30Pxj6Fp5JBiUh0s242p/jGfWisKIVMKxhY1VSBt4p4im/UG0hrDYoZFJE5Fd1G3aHYm32i03Sn09odGbkHRtsknEoGBUQ362brk7tWwdcQW3/SrGqoQOewF94stHnKt1A4gnFfaocVarTXyhD3QhGZiiEBSin1W6XU+4z4XpnSgk2yfVDAySAyMGncJ2ctg5vrsMLpapwlWevscLKC7+3BenWTCwBwqL/4sijtZNx01qByUaxCROkr4gwqlTLzaIAanDTujWnQoyODylKAmlnBp1nZGK3kK8ZpvnQ6mWscNitcDhszKCKTKb4AFctgUmkdFM+gJozLoAYn/BCk3qg0m2tQ8Qq+yrdnUItrnbBbLXirCAsltC4S6axBAeDhkUQmVHQBatgTQGWpLWkfPOBku6NBI6f4PH6U2a2wWlLrYlDnijaMDRpYqKGJV/DNyOZsVguWN7iKNEDF+vClUcUHMEARmVHRBaghTwB1c5ykO53W7mjQwAxqaDKQ8vQeALgrHFDqZHGFkfrH/adU8GlWNbqKcrPuyQyKAYqo0BVdgBqeDKS0/qRxOWzGZlCTgZRKzDVaCyIjpxmBaAVf/4TvlAo+zarGCnSPTmWlF2E+pXsWlIYBish8ii5ADXn8Ke2B0rgcNkOr+AY9/rQzKADon/AZNgYgWsHnDZxawadZFSuUOFhklXxjU0FYBHCUpPfSriu3Y8gTgFLsx0dkFsUXoCZTn+IDog1jByeM3QeVXgYVHavRGVSiCj7NqsZoqXmxdZQY8UbPAku1k7mmptyOQCgSPw2ZiPKvqAKUPxTGkCeAxsrUA5SRU3yBUARjU0G4UtwDBQD1Li2DMjZAaQHPnSCDaqlxosQqODroNfS6+TbqDc55knIiWtbNvVBE5lFUAap/PPqm3JQga5iNq9SGYW/AkHZH2vpHOhmU3WZBjbPE8Cm+YU8ANougsnT2sVgtgpYaJ44PF1+AqnKWpP33tHVL7oUiMo+iClB9sX0/jVVpBCiHDUoZ0+5Iy8TSWYMColmO0VN82plYs1XwaVprnegstgA1Fcgog2I/PiLzKKoAdSIWoNLKoAxsd5RuHz5NQ0Wp4VN8qRzauKi2rOgC1IgniOqy9DMo7bnKRrk/EelTXAFqLP0AZWS7I70ZVIPBGZRSCsPe5AFqcW05xqaCGMviib65NjYVRHUma1BZPPqEiNKT3jupyfWN+2C3WVCdxhqEFkyM2KyrffpOZw0KiE7x9U/4oZSac0ouVZ5AGIFQJGmAaq11AgA6h7043VmV8XXzLRCKYNIfSuv/X+Ny2GC3WrgGRUXlka2ds95+wzmLcjwSfYorgxr3o6ly9s4JiRg5xTfo8cNus8BhS+9pdVc4EAhF4p24M6Wtp9UmySQWTQtQxWAsdmR7jY4AJSKoKS/BMKf4iEyjqAJU35gvrek9IFpFV1ZiNSyDqk9SmDAbd3wvlDGVfPEAlWwNqq64ApTWh69KxxQfANSWOzjFR2QixRWgJnxpVfAB0U/O9RV2Q/ZCDU3609okrNHaHWll8pnSKtGSdXR3OWyoK7cXT4DKIIMCTnaTICJzKJoApZTCiTEfmtLYpKupdzkMKZKINqpN/9N7PIMyaMPwsCeYckf3aKm5x5Dr5pu2yba6TG8GxX58RGZSNAFqbCoIfyiSsLXPXKIBypgpvlSOmp9JO6/JuAwqeQWfZlER7YXSMig9RRJALEBxDYrINIomQMX3QKU5xQcYs1FWKYXBST/qdWRQFQ4bHDaLgRlU6g1zF9U60TPqy8p5VLnWF9tmkKi9UzK15XZM+EMIhAr/uSAqBroDlIi0ishLIrJPRPaIyGeMHFi69OyB0tS7HBm3O/IEwvCHIrqm+EQEDZWO+Am4mfAFwxj3hVIPUHVOhCMKvaPGtlrKh66RKbgrHChN87BCDfdCEZlLJhlUCMDnlFKnAdgM4K9EZK0xw0pfvM2RjgDldtmj7Y4yeGPSjprXM8UHRAsljMigukai03XpZFAA0FEE61DHR7xoqSnT/ffZTYLIXHRv1FVK9QLojf15QkT2AVgIYK9BY0vLibHom3uDziIJABicCMQr6tKlFVnUuezo0ZGNuF0OHB7I/GwmbT0p2R4oTTHtheoamcI7Wqt1//2T/fiKO0AV+ubNVM2Xf2cxM2QNSkSWANgEYOss990mIu0i0j4wMGDE5WZ1YtyH2nI7HLb0p3eMqKLTiizqdZSZA9HAakQ/vs6hWIBKcRyNlaWwWy0FH6DCEYWe0amMMiito3kmmTQRGSfjACUiLgA/AfC3Sqnxmfcrpe5TSrUppdrcbneml0uob9yna3oPmJ5B6Q8QWpGF3gDldjlilYiZHZjXMeyF3WpBuT21QG21CFpqywr+2I0T4z6EIirevkmPeAZl4AnLRKRfRgFKREoQDU4PK6WeNGZI+ujdAwVMP3Zd/xvTsUEPSkssCY9YT0abmsy0mvD4sDfpMRszLap1omOosAOUFmAzyaCqnXaIFP8UH1GhyKSKTwDcD2CfUuo/jBuSPn3jPl0l5kC0uWu9y4EjGawBHRn0YEldOSwWfc1e3QYd/d4x5E25QEKzqNaJziEvlFIZXTufukamAACtNfozKKtFUF1Wwm4SRCaRSQZ1PoCbAFwkIttjv640aFxpCYQisaPe9QUoAFjRUI5DmQSogUksd7t0//14u6MMApRSCp3D+gLUhD8Ub7ZaiI4PeyECLKjW/xoAotN8LDMnMgfdAUop9QellCilNiil3hH79ZyRg0uVdly6nj1QmhUNLhzqn9SVRQRCERwfmcIyd7nu6xuRQfVP+OFP4ZiNmbRKvqODhVtq3jUyhabKUl1FMtM1VZWiO5aNEVF+FUUnCT1Hvc+0wu3ChC+kK0B0DnsQjqiMAlRdeXT9I5MM6sCJCQDpd1I4bUElAGBv7yk1LgUj0z1QmpUNFbo/qBCRsYoiQGl7oDLLoCoAAIf605/mOzwQzTyW1euf4rNZLagrd2R05MbunjEAQHNVem/ULTVlqCy1YU9P4Qao7pGpjNafNCsaXPAEwugZK/zOGkSzGZ8K4s6nduGtvol8DyWp4ghQ48ZM8QHQtQ51RAtQGWRQQDTz6cugYezu7jEsqnWiLMUSc42IYF1zVcEGqGA4gt6xzPZAaVbGXgcHC+CHlyhdRwYn8c2XDuHhrZ349CNvmr7vZFEc+a7nqPeZGisdcDlsujKoIwOTcFc4UFGq//oAsNxdju3HR3X//d3d41i/sFLX313XXIkfbelAKByBLYVjOsykd9SHiAJaMtgDpVnVGM2kD/ZN4sLVDRl/v/mMnRzMZevRIfxsRw9qy+347KVr8a8/34t7f3MQn7tsdb6HllBhvRMl0DM6lfZR7zOJCJbHCiXSdXhgEsszzJ4AYP3CKnSNTMVPhk3HmDeIzmEv1jVX6b62PxSJT1cWEq3/oBEZVE25HfUuOw72M4Oi4jHhC+LnO3qx3O3CX164Are+cyk+dMZCfPu3h7Grayzfw0uoKALU7u4xrGmqyPj7rHDrC1BHBj1YlkGJuWZ9LLjomWrb0xt9ka1fqC9ArWuOZl67u837Yk3keCxAGbEGBUSnew/qeB0QmdW2Y8MIK4WrNjTHu/3f9b51qCu34/M/3mHaqb6CD1AjngCODXnxjkX6m4RqVjS40D/hx7gv9f1Aw54ARr1BLKvPPIPSgsQuHUFiT3c0qK1v1jfFt8ztQmmJpSDXobpGpmC1CBZkUMU53arGChzqK75KvkP9k7j7mT3xzvvzjVIKE74ghj0BTKTxM17oQpEIth0dxsoGF+qnVfhWOUvwL1evw4G+Cfxq74k8jjCxgl+D2t4VXbPZ1FqT8feKF0r0T+KMRal9P637RCabdDU15Xa01JTpymJ294yhuaoUdTp7AVotgtMWVMYrAQvJ8WEvFlSVGrZ2trLBhQl/CCfGfViQZkWkWfWOTeGm+7eid8wHm0Vw0ZoGvGulG1adnU8KjVIKj7cfx46uMXzlF/sBANec2YKvX7sxzyPLvj0945jwhfDBTXWn3HfZuiY0V5Xi/147jvdtaM7D6OZW8BnUm52jsAiwoUXf1NZ0K6cFqFQZVcGnWa+zmm539xjW6Zzem37tfT3jiEQKK3PoGjGmgk+jbTk42Fcc03xj3iBufmAbJnwhfP9jZ2F1UwU3y6cNAAASHUlEQVR+tbcP//v7I4gUWZaYyM6uMezoGkPb4hrcfdVaXHNmC554vQvP7uzN99Cy7tXDQ6gtt8cLgKazWgTXtrXiD4cG42u5ZlLwAWr78VGsaqxAuSPzZLC11gm7zYLDaQSow4OTsFstaDFo/WP9wkocHfSkNQXh8YdwZNATX8PSa11zJSb8oYI7euP4iNew9ScAWNUYKzUvgnWoYDiCT/ywHccGvbjvpjPx7tUN+Og5i/GBdyxE57AXb3SM5HuIWTfuC+KZHT1orSnDBzYtxC3nL8VXP3Q6NrRU4Z+f3l3UU57do1PoHPZi87I6WBIUkV3b1gIA+HF7Vy6HlpKCDlBKKew4PprRIXXTWS2CZfXlaWdQi+uchk2VaFnQ3jSyqL2941AKukvMNVqBRSGtQ/lDYfSN+w37gAAAdS4HasvtRbEX6onXu7Dt2DC++uHTcd6K+vjtZy2pQWtNGX69r8+0C+RGUErhp292IxiO4JozW+Nv0jarBfdcsxHjviDuemZPnkeZPa8eHkKJVXDmHEsWLTVOvHNFPX7cfhxhk82eFHSAOjrowdhUEJsMKJDQLG9wpbVZ9/DApGHTe8DJSr50CiW0NSu9FXyalY0u2CxSUOtQ2jEbrbXGrhUVQyWfPxTGvS8exKZF1fjgpoVvu09E8J71CzDuC+GPhwdzMp6IUjhwYgJ3PrULr+Tomju7x7D/xAQuW9d0Sguw1U0V+MzFK/Hznb341R5zFglkYmjSj51dozhjUU3SzfvXnbUIPWM+/P5g9g6V1aOgA5S2qfUdBhRIaFa4XTg+7IUvmPzgwGA4gs4hryEFEhp3hQONlY60spjd3eOodzl0n0WlcdisWNVYUVAZ1G/29wMAzlxs3GsAiE7zHeybKOhKvse2HUfPmA+fu3T1rHsEl9SXY+2CSrz81gAm/aGsjuWNjhH8xwtv4QevHsOj2zpx4/e24lsvHcrqemcoEsELe/uwoKoU5y0/tUAAAD55wXKsaHDhq7/cj1C4uDLJx147jlBEYfOy2f/t012ytgE1zhI83n48ByNLXUEHqDc7R1Fut8ar74ywosGFiEqtUOLIgAehiDJkD9R065ur0qrk2909hvULKzPaqKxZ11yJ3d1jpkv1E3l21wmcvrAKi+uMy2KBaNPYcV8oo+a9+TQVCOObLx3COUtrcf6KxG9Ql69rQjAcwYv7+rI2lp1do3jijS447Vb8aVsr3vinS3Hl6Qtwz/MH8Ikftqf0YVCP146NYNgTwOXrmhKuv5RYLfjC5atxZMCDJ1433xqMXqFwBA9t6cByd3lKxxA5bFZcc2YLnt/TZ6rTtQs6QG0/PoqNrdWGlsqevbQWVovgmR09SR/75BtdsFoE71pZn/Sx6Vi3sAqHBybhDST/VLv/xDgO9E3g3BQ+JaXiwtUNGPYE8FIsMzGz48Ne7Dg+iitPX2D49z7Zk68wp/l+tOUYBib8+Nxls2dPGneFA2cvrcVrx4bj3fCN1D06hZ+80YXFtU7c9q5l2NhajWqnHfdevwl3X7UWL+7vx7/8bK/h1/X4Q3hpfz+W1pfH/y8TuWxtI85YVI3//PXBrAXLXPvV3j70jvlw7rLU35tufecyWEXw7d8eyuLI0lOwAcoXDGNf77hhBRKaxspSXL6uEY+3H5/zxeoLhvF4+3FctrYxo4MSZ7O+uRIRBezrTf6G8cAfjqK0xII/PavVkGtftq4RTZWlePCVY4Z8v2z6xe5oifB7sxGgYiW5e3sLZz1OMzjpx7d/exjvWlmPs5fWJn38JWsa4bBZ8aWf7zF0SnPCF8RDWzrgtNvw0c2L37ZPTURwy/lL8RcXLMej2zrx9PZuw64LAN//41FM+kO4fF1T0pkFEcHfX7EGJ8Z9BfG6T8WDrxxDS00Z1ixIvcNOU1Uprju7FU+83mWakvOCDVB7esYQiijDAxQA3LR5CUa9wTmzqF/uPoERbxAfPWex4dfXih3e7Jy7BHhw0o+fbu/Bh89oQbUzvUMKEymxWnDTuYvxh0ODpq9ie3ZnL05fWIVFdcZV8GnqXXasX1iJh7Z0IlhgaxN3P7MHXn8Yd121NqXHOx02XHxaA/54aAgv7DVmqs8fCuPhrZ3wBkK4afNiuBJsA/n8ZavQtrgG//DkLhzO4ETr6frHffju745g7YLK+GGcyZyzrA7vXu3Gt186VPBl53t7xrHt6DBu2rw44dRmIn9xwXIAwHd+dzgbQ0tbwQaop7f3QATYlGLHh3RsXlaLVY0u/OjVjoSfKB/a0oGl9eUJF18zsaCqFBtbqnDfy0fm3A/10JYOBEIRfPydSw29/vVnL4LDZsH3Tfxp8viwFzu6xvDeDcZnT0D0U/VnL1mFzmEvnnyjcNYmXtjbh5/v7MWnL1oR33CcinOW1mFlgwtffm4f/KHMprmUUviHJ3ejc9iLa89sRXN14gpLm9WCe2/YBEeJFZ966HWMeTNrQRQMR/DXj7yJUETh8nVNaf3dO95zGnzBCP72/7YXzBrsTP5QGHc8uROVpTZdsyrN1WX4SFsrHn+tC71j+T9ZuiAD1NYjQ/jhqx24+dwlaZ8emwoRwU2bF2NX99isx1/sPzGO9o4R3HD2Iliy0CpGRPCl96/HwKQf33jh4KyP8QXDeGhLB9692m1oFSEA1Jbb8YF3LMSTb3Rl/IaRLc/tyt70nuaiNQ3Y2FKF/37xUEHsFRr3BfGPP92FNU0V+GTsk3CqrBbBP1+1Fh1DXnzpZ3szmuq7/w9H8ZM3unDRmoaUtj4sqCrDvddvwrFBL27+/raMKgrvef4Ath0bxlc+dHra7w2rmyrwpfevw+8PDuIbL7ylewz59JXn9mNn1xjuuXaj7lmVT124HAoK//aL/XmvYi24AOUNhPCFJ3ZicZ0Tt1+RvXNMPnhGC1wOG370ascp9z28pRN2mwXXnNmStetvbK3GDWcvwoOvHJ110+7T27sxOBnAre9clpXr33L+EviCETy87dR/f775gmE89WY3Tl9YhVYDzoBKRETw2UtXoXt0Cj9+3VzltzNN+IL47GPbMTDhx799eAPstvR/tN+10o1PXrAMD2/txD/+dHfaJeBKKTyytRP/77l9eM/6Jly0JvXztM5fUY97b9iEXd1j+PMfvKarWOGXu0/gvpeP4KbNi/GBGfu+UnXd2Ytw3Vmt+OZLhwyb7syVX+zqxYOvHMPHz1+advY4XUuNE5+6cAV+ur0Hd+p4HRgpowAlIleIyAEROSQidxg1qLl87ZcH0Dnsxdc+vAFOe/Z63bocNlxzZgue2t6Nzzz2JjqGPOgencLtT+zAw1s78L4NC1BTbsy6TyK3X74GNU47/unp3fDEPlX6gmF87Zf7cedTu7GuuXLOEuJMnLagEn+yyo17nj+Ae57fb5p1mJ7RKfzpd1/F/hMTuOW8JVm/3gWr3DhjUTW++ZtDps0m9/aM46p7/4DfvjWAu65ah40ZrMveccUafOrC5Xh4aye++OSu+Osumb5xHz7+4Gv4h6d24dzldfj3j2xMe/3j8nVN+PdrN2Lr0WFc+51X8fuDAyl9gp/wBfGV5/bh04++gY2t1fjH952W1nVnuvvqdTh9YRX+6pE3cM/z+7O+RyxTwXAEj27rxO1P7MTG1mrc8Z41GX/Pz16yEn954XI8srUTdzy5M29Tnrrf4UXECuBbAC4F0AXgNRF5RillfM1oTPuxYTz4yjF87PwlOMegsuq53H7FapTZrfj+H4/i2Z298R+4W85bis9csjLr169yluCLV56Gz/94B06/+3msaarEZKxX3jVntuDOK08zZO9TIv/z0TPwpZ/txbdeOozfHxzEre9ciuVuF5bUl6OsxAqLICvXV0pBKUD7kZj0h3BkYBIHTkzg6786gKlAGN+58UxcsV7/p8RUiQi+cPka3PC9LTj3qy/imjNb8JG2VjRVlaKqrAQlOT59OBiOYNIXwuCkH+0dI9h6ZAjP7T6BGmcJHrttM85akrxqby4igtsvXw2bRXDvbw7hZzt78J71C/Ce9U1oqiqFu8IBm0Xg8Ycx7gtiR9coXjk0hJffGkAwEsHdV63Fn527RPfU9wc2LUSJ1YIvP7sXN92/DWcvrcWV65uwoqECS+qd8cxw0hfCW30T2Nc7gYe3dmJw0o9rz2zBHe9ZA4dt7q4JyZSWWPHALWfhy89GX/uPt3fhxnMWY21zJVY3VqC6vAQlFgtKrAKrRQz5GZj5mldKQQHQ4rOCOvlnBYx4A+gY8uLAiXE88Mdj6Bz24h2t1fjWR8/QlT3PFH3dr4bNasF/v3gQv9nfj/NX1OOdK+px8WmNqM3yh3NNJinI2QAOKaWOAICIPAbg/QCyFqDWL6zCFy5fjY+fb2xRQCJOuw1/f8UafOy8Jfjuy0cQDEfwyQuWY+Eci75Gu+bMFiysLsOrR4bwRscI7DYLvvKh03H+CmP3Xs2m3GHDv12zAReuduOLT+3CZx7bfspjrBaBVQQWC2ARif2QRX+S4j9ws/2Q4eQPofbYVCxzl+Ox2zanVQCQqXOX1+G5v3kX7v/DUTy27Th+OG3at8QqEMTeoKa9T01/y5K33S6n3AbglOcNmP25C834JFvvcuCqDc344pVrUK/zqJWZRASfu2w1Llztxo/box2/fzJHoUhTZSkuW9eEv3r3ckM2rb93wwJcsrYBj207ju/87jDunmOflAjQtrgG99/cllHmOJO7woH/vG4Tbj5vCb787D5849eJ16TsVgusFjnl9Y1Zfha0jHB68MnU2gWVuP/mNly0psHQD4wigr+7dBVOa6rAL/ecwB8PDeLp7T145BPn4Lzl2X//AQDRuwgmItcAuEIp9eexr28CcI5S6q9nPO42ALfFvlwN4ID+4eZFPYDcNA4rHnzO9OHzpg+ft/Tl+zlbrJRyJ3tQJhnUbKH6lGinlLoPwH0ZXCevRKRdKdWW73EUEj5n+vB504fPW/oK5TnLZLKyC8D0QvsWAMn7AxEREaUgkwD1GoCVIrJUROwArgPwjDHDIiKi+U73FJ9SKiQifw3geQBWAA8opYrx5K+CnZ7MIz5n+vB504fPW/oK4jnTXSRBRESUTQXXSYKIiOYHBigiIjIlBqiYZG2bROTvRGSviOwUkRdFxPhzNgpMqq2uROQaEVEiYvqy1lxI5XkTkY/EXm97ROSRXI/RbFL4+VwkIi+JyJuxn9Er8zFOMxGRB0SkX0R2J7hfROS/Y8/pThE5I9djTCraYmN+/0K0yOMwgGUA7AB2AFg74zHvBuCM/flTAP4v3+M2+3MWe1wFgJcBbAHQlu9x5/tXiq+1lQDeBFAT+7oh3+MugOfsPgCfiv15LYBj+R53vn8B+BMAZwDYneD+KwH8AtE9rZsBbM33mGf+YgYVFW/bpJQKANDaNsUppV5SSmnHTG5BdN/XfJb0OYv5VwBfA+DL5eBMLJXn7RMAvqWUGgEApVR/jsdoNqk8ZwpAZezPVeCeTCilXgYwPMdD3g/ghypqC4BqEcne+TU6MEBFLQQw/TyFrthtidyK6CeP+SzpcyYimwC0KqV+nsuBmVwqr7VVAFaJyB9FZIuIXJGz0ZlTKs/Z3QBuFJEuAM8B+HRuhlbQ0n3fy7nsnVdRWFJq2wQAInIjgDYAF2R1ROY353MmIhYA3wBwS64GVCBSea3ZEJ3muxDRTP33IrJeKXXq6ZnzQyrP2fUAHlRK/buInAvgR7HnzBznxJhTyu97+cIMKiqltk0icgmAOwFcrZTy52hsZpXsOasAsB7Ab0XkGKJz3M+wUCKl11oXgKeVUkGl1FFEGyxn/3wX80rlObsVwOMAoJR6FUApog1RKTHTt6tjgIpK2rYpNl31XUSD03xfEwCSPGdKqTGlVL1SaolSagmi63ZXK6Xa8zNc00ilRdhPES3KgYjUIzrldySnozSXVJ6zTgAXA4CInIZogBrI6SgLzzMA/ixWzbcZwJhSqjffg5qOU3xI3LZJRL4EoF0p9QyAewC4APw4duZKp1Lq6rwNOs9SfM5ohhSft+cBXCYiewGEAXxBKTWUv1HnV4rP2ecA/K+IfBbRaapbVKxUbb4SkUcRnSauj63N3QWgBACUUt9BdK3uSgCHAHgBfCw/I02MrY6IiMiUOMVHRESmxABFRESmxABFRESmxABFRESmxABFRESmxABFRESmxABFRESm9P8BBpEx/FCyVxgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([0.16667, 0.25   , 0.33333, 0.5    , 0.66667, 0.75   , 0.83333,\n",
       "       1.     ])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max_note_len = 1\n",
    "duration_list = [ll for ll in part_note_lengths if ll <= max_note_len]\n",
    "sns.distplot(\n",
    "    duration_list\n",
    ")\n",
    "plt.title('')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "np.unique(duration_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indeed, looking at all note lengths in primers, we see they are integers when multiplied by 12 (rounded to 4dp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  2.,   3.,   4.,   6.,   8.,   9.,  10.,  12.,  14.,  15.,  16.,\n",
       "        18.,  20.,  21.,  22.,  24.,  26.,  27.,  28.,  30.,  32.,  33.,\n",
       "        34.,  36.,  38.,  39.,  40.,  42.,  44.,  45.,  46.,  48.,  50.,\n",
       "        51.,  52.,  54.,  56.,  57.,  58.,  60.,  62.,  63.,  64.,  66.,\n",
       "        68.,  69.,  70.,  72.,  74.,  75.,  76.,  78.,  80.,  81.,  82.,\n",
       "        84.,  86.,  87.,  88.,  90.,  92.,  93.,  94.,  96.,  98., 102.,\n",
       "       126., 144., 153., 555.])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.around(np.unique(part_note_lengths) * 12, 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "...but there are some very long notes! Some are 46.25 beats long."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.16667,  0.25   ,  0.33333,  0.5    ,  0.66667,  0.75   ,\n",
       "        0.83333,  1.     ,  1.16667,  1.25   ,  1.33333,  1.5    ,\n",
       "        1.66667,  1.75   ,  1.83333,  2.     ,  2.16667,  2.25   ,\n",
       "        2.33333,  2.5    ,  2.66667,  2.75   ,  2.83333,  3.     ,\n",
       "        3.16667,  3.25   ,  3.33333,  3.5    ,  3.66667,  3.75   ,\n",
       "        3.83333,  4.     ,  4.16667,  4.25   ,  4.33333,  4.5    ,\n",
       "        4.66667,  4.75   ,  4.83333,  5.     ,  5.16667,  5.25   ,\n",
       "        5.33333,  5.5    ,  5.66667,  5.75   ,  5.83333,  6.     ,\n",
       "        6.16667,  6.25   ,  6.33333,  6.5    ,  6.66667,  6.75   ,\n",
       "        6.83333,  7.     ,  7.16667,  7.25   ,  7.33333,  7.5    ,\n",
       "        7.66667,  7.75   ,  7.83333,  8.     ,  8.16667,  8.5    ,\n",
       "       10.5    , 12.     , 12.75   , 46.25   ])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(part_note_lengths)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution over pitches"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These plots look like a mixture of two gaussians. This suggests to me that there may be two types of pieces - bass and melody. Indeed, the chimes true with randomly selecting different pieces. It's something to take into account when thinking about augmenting data by transposition, because bass and melody parts may have very different melodic structures: transposing a bass part up too high could make very unlikely data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "parts = {'prime': prime, 'cont_true': cont_true, 'cont_foil': cont_foil}\n",
    "bins = [ii - .5 for ii in range(130)]\n",
    "\n",
    "part_name = 'prime'\n",
    "part = parts[part_name]\n",
    "part_pitches = np.hstack([part[fn].pitch for fn in prime.keys()])\n",
    "sns.distplot(part_pitches, bins=bins)\n",
    "plt.title(f'{part_name}: min {min(part_pitches)}, max {max(part_pitches)}')\n",
    "plt.show()\n",
    "\n",
    "part_name = 'cont_true'\n",
    "part = parts[part_name]\n",
    "part_pitches = np.hstack([part[fn].pitch for fn in prime.keys()])\n",
    "sns.distplot(part_pitches, bins=bins)\n",
    "plt.title(f'{part_name}: min {min(part_pitches)}, max {max(part_pitches)}')\n",
    "plt.show()\n",
    "\n",
    "part_name = 'cont_foil'\n",
    "part = parts[part_name]\n",
    "part_pitches = np.hstack([part[fn].pitch for fn in prime.keys()])\n",
    "sns.distplot(part_pitches, bins=bins)\n",
    "plt.title(f'{part_name}: min {min(part_pitches)}, max {max(part_pitches)}')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing metadata..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* I find bpm of 20 and 600 quite unlikely...though meat of data seems fine\n",
    "* No big surprises re predicted key data, c and g major very popular\n",
    "* Twice as much major data as minor, expected a larger discrepancy https://www.music-ir.org/mirex/abstracts/2018/OM1.pdf\n",
    "* Some nan time signature information - most seems to be the logical candidates: [4,4], [2,4], [3,4], [6, 8], [3, 8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [00:00<00:00, 141.02it/s]\n",
      "100%|██████████| 1000/1000 [00:03<00:00, 278.17it/s]\n",
      "100%|██████████| 10000/10000 [00:32<00:00, 305.32it/s]\n"
     ]
    }
   ],
   "source": [
    "all_metadata = {}\n",
    "for size in sizes:\n",
    "    descriptor_path = f'{DATA_LOC}/raw/PPDD-Jul2018_aud_mono_{size}/descriptor'\n",
    "    all_metadata[size] = pd.concat(\n",
    "        [pd.read_json(ff, typ='series') \n",
    "         for ff in tqdm(glob(f'{descriptor_path}/*.json'))],\n",
    "        axis=1,\n",
    "        sort=False\n",
    "    ).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata = all_metadata[SIZE]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata.bpm = metadata.bpm.astype('float')\n",
    "metadata.keyEstimate = metadata.keyEstimate.astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>id</th>\n",
       "      <th>idLakh</th>\n",
       "      <th>bpm</th>\n",
       "      <th>timeSignature</th>\n",
       "      <th>keyEstimate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7f842f97-415b-4a29-bf86-55a9ffee1228</td>\n",
       "      <td>2fab0032939ca5f3233cfde5f6ae937c</td>\n",
       "      <td>100.0</td>\n",
       "      <td>[4, 4]</td>\n",
       "      <td>A minor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>faea1bda-c8a8-4f2f-8cc9-253ec3989e77</td>\n",
       "      <td>84f8375aec0544ac09417ae8ef0bac84</td>\n",
       "      <td>125.0</td>\n",
       "      <td>[4, 4]</td>\n",
       "      <td>Eb major</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>05522bb0-2f4f-4da4-8816-ddde7fb1bce9</td>\n",
       "      <td>a94c01f86a9632b4c9726458e841f4ef</td>\n",
       "      <td>160.0</td>\n",
       "      <td>[4, 4]</td>\n",
       "      <td>Ab major</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35643dd8-df2c-4a95-bb1c-d3c901e03e2e</td>\n",
       "      <td>a019912ac23907d55d883eb527f5b776</td>\n",
       "      <td>80.0</td>\n",
       "      <td>[4, 4]</td>\n",
       "      <td>Ab major</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1c7b6536-79d2-44bf-a32b-15bca092e26f</td>\n",
       "      <td>17520ad7d1469cc23779b9436ae75f0b</td>\n",
       "      <td>181.0</td>\n",
       "      <td>[4, 4]</td>\n",
       "      <td>Db major</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     id                            idLakh  \\\n",
       "0  7f842f97-415b-4a29-bf86-55a9ffee1228  2fab0032939ca5f3233cfde5f6ae937c   \n",
       "1  faea1bda-c8a8-4f2f-8cc9-253ec3989e77  84f8375aec0544ac09417ae8ef0bac84   \n",
       "2  05522bb0-2f4f-4da4-8816-ddde7fb1bce9  a94c01f86a9632b4c9726458e841f4ef   \n",
       "3  35643dd8-df2c-4a95-bb1c-d3c901e03e2e  a019912ac23907d55d883eb527f5b776   \n",
       "4  1c7b6536-79d2-44bf-a32b-15bca092e26f  17520ad7d1469cc23779b9436ae75f0b   \n",
       "\n",
       "     bpm timeSignature keyEstimate  \n",
       "0  100.0        [4, 4]     A minor  \n",
       "1  125.0        [4, 4]    Eb major  \n",
       "2  160.0        [4, 4]    Ab major  \n",
       "3   80.0        [4, 4]    Ab major  \n",
       "4  181.0        [4, 4]    Db major  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>id</th>\n",
       "      <th>idLakh</th>\n",
       "      <th>bpm</th>\n",
       "      <th>timeSignature</th>\n",
       "      <th>keyEstimate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>10000</td>\n",
       "      <td>10000</td>\n",
       "      <td>10000.00000</td>\n",
       "      <td>9781</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>10000</td>\n",
       "      <td>10000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>35ae3d81-a394-4efe-93a1-6d44d4df0cc9</td>\n",
       "      <td>5a4e3a38e5880b0ee21bd7ff5fc012fa</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[4, 4]</td>\n",
       "      <td>C major</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8012</td>\n",
       "      <td>1315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111.24228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>34.13967</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>111.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>128.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>600.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          id  \\\n",
       "count                                  10000   \n",
       "unique                                 10000   \n",
       "top     35ae3d81-a394-4efe-93a1-6d44d4df0cc9   \n",
       "freq                                       1   \n",
       "mean                                     NaN   \n",
       "std                                      NaN   \n",
       "min                                      NaN   \n",
       "25%                                      NaN   \n",
       "50%                                      NaN   \n",
       "75%                                      NaN   \n",
       "max                                      NaN   \n",
       "\n",
       "                                  idLakh          bpm timeSignature  \\\n",
       "count                              10000  10000.00000          9781   \n",
       "unique                             10000          NaN            35   \n",
       "top     5a4e3a38e5880b0ee21bd7ff5fc012fa          NaN        [4, 4]   \n",
       "freq                                   1          NaN          8012   \n",
       "mean                                 NaN    111.24228           NaN   \n",
       "std                                  NaN     34.13967           NaN   \n",
       "min                                  NaN     20.00000           NaN   \n",
       "25%                                  NaN     88.00000           NaN   \n",
       "50%                                  NaN    111.00000           NaN   \n",
       "75%                                  NaN    128.00000           NaN   \n",
       "max                                  NaN    600.00000           NaN   \n",
       "\n",
       "       keyEstimate  \n",
       "count        10000  \n",
       "unique          24  \n",
       "top        C major  \n",
       "freq          1315  \n",
       "mean           NaN  \n",
       "std            NaN  \n",
       "min            NaN  \n",
       "25%            NaN  \n",
       "50%            NaN  \n",
       "75%            NaN  \n",
       "max            NaN  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata.describe(include='all')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Total number of pieces"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ids of the pieces in small are not a direct subset of large. How much to parts overlap?\n",
    "\n",
    "Potential issue combining small, med, large datasets: Though their ids have no intersection, there is an overlap of lakh ids (i.e. there are songs with the same lakh id in different size parts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "for size in sizes:\n",
    "    assert list(data[size]['prime'].keys()) == list(data[size]['cont_true'].keys())\n",
    "    assert list(data[size]['prime'].keys()) == list(data[size]['cont_foil'].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_fn = set([fn for size in sizes \n",
    "                  for fn in list(data[size]['prime'].keys())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11100"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_idLakh = pd.concat([all_metadata[size].idLakh for size in sizes])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11100"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_idLakh)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10904"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_idLakh.unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_lakh_id = set([all_metadata[size].query(f'id == \"{fn}\"').idLakh.iloc[0]\n",
    "                   for size in sizes \n",
    "                       for fn in list(data[size]['prime'].keys())])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10904"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_lakh_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "172"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pd.merge(all_metadata['large'].idLakh.reset_index(drop=True), \n",
    "             all_metadata['medium'].idLakh.reset_index(drop=True),\n",
    "             how='inner'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(pd.merge(all_metadata['large'].idLakh.reset_index(drop=True), \n",
    "             all_metadata['small'].idLakh.reset_index(drop=True)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(\n",
    "    pd.merge(\n",
    "        all_metadata['medium'].idLakh.reset_index(drop=True), \n",
    "        all_metadata['small'].idLakh.reset_index(drop=True),\n",
    "        how='inner')\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mrg = pd.merge(pd.merge(all_metadata['large'].idLakh.reset_index(drop=True), \n",
    "                        all_metadata['small'].idLakh.reset_index(drop=True),\n",
    "                        how='inner'),\n",
    "               all_metadata['medium'].idLakh.reset_index(drop=True),\n",
    "               how=\"outer\", indicator=True)\n",
    "len(mrg[mrg['_merge']=='both'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10904"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "11100 - 172 - 23 - 2 + 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of keys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23]), <a list of 24 Text xticklabel objects>)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.countplot(metadata['keyEstimate'])\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc192e537b8>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAD8CAYAAABgmUMCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAE35JREFUeJzt3X+QXfV53/H3xwjiNk1AMgsliFakVp2QNMZ4K2jt8bjGFT/aII0dbLlJWRNmlD9oJpl2muJMJ3LAtE6T1jFpQkZjZAuPY0xJMaqHhqgCx5NkMCyGgAEzUrCDVGFpHck4Ng0Z7Kd/3O+aK7G72iPv2atl36+ZO+ec53zPuc+d2dFH58c9N1WFJEnz9apRNyBJWloMDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdGBySpE5WjLqBPpx++um1Zs2aUbchSUvKQw899LWqGjvWuN6CI8nrgE8NlX4Y+BXg1lZfA3wFeFdVHU4S4MPA5cDzwHur6gttXxPAf2z7+UBVbZ/rvdesWcPk5OTCfRhJWgaS/MV8xvV2qqqqnqqq86vqfOCNDMLgTuA6YFdVrQV2tWWAy4C17bUZuBkgySpgC3AhsA7YkmRlX31Lkua2WNc4Lgb+vKr+AtgATB8xbAc2tvkNwK01cD9wWpKzgEuAnVV1qKoOAzuBSxepb0nSURYrODYBn2zzZ1bVswBtekarnw3sHdpmX6vNVj9Cks1JJpNMTk1NLXD7kqRpvQdHklOAK4D/cayhM9RqjvqRhaqtVTVeVeNjY8e8tiNJOk6LccRxGfCFqjrQlg+0U1C06cFW3wecM7TdamD/HHVJ0ggsRnC8h5dOUwHsACba/ARw11D9qgxcBDzXTmXdA6xPsrJdFF/fapKkEej1exxJ/jbwz4GfGyp/ELg9yTXAM8CVrX43g1tx9zC4A+tqgKo6lOQG4ME27vqqOtRn35Kk2eWV+NOx4+Pj5fc4JKmbJA9V1fixxvnIEUlSJ6/IR45Ir2TPXP+PRt2CTkB/71ceW7T38ohDktSJwSFJ6sTgkCR1YnBIkjoxOCRJnRgckqRODA5JUicGhySpE4NDktSJwSFJ6sTgkCR1YnBIkjoxOCRJnRgckqRODA5JUicGhySpE4NDktSJwSFJ6sTgkCR10mtwJDktyR1JvpTkyST/JMmqJDuT7G7TlW1sktyUZE+SR5NcMLSfiTZ+d5KJPnuWJM2t7yOODwN/UFU/ArweeBK4DthVVWuBXW0Z4DJgbXttBm4GSLIK2AJcCKwDtkyHjSRp8fUWHEl+EHgLcAtAVf1NVX0d2ABsb8O2Axvb/Abg1hq4HzgtyVnAJcDOqjpUVYeBncClffUtSZpbn0ccPwxMAR9N8nCSjyT5fuDMqnoWoE3PaOPPBvYObb+v1WarS5JGoM/gWAFcANxcVW8AvsVLp6VmkhlqNUf9yI2TzUkmk0xOTU0dT7+SpHnoMzj2Afuq6vNt+Q4GQXKgnYKiTQ8OjT9naPvVwP456keoqq1VNV5V42NjYwv6QSRJL+ktOKrqq8DeJK9rpYuBJ4AdwPSdURPAXW1+B3BVu7vqIuC5dirrHmB9kpXtovj6VpMkjcCKnvf/88AnkpwCPA1czSCsbk9yDfAMcGUbezdwObAHeL6NpaoOJbkBeLCNu76qDvXctyRpFr0GR1U9AozPsOriGcYWcO0s+9kGbFvY7iRJx8NvjkuSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1EmvwZHkK0keS/JIkslWW5VkZ5Ldbbqy1ZPkpiR7kjya5IKh/Uy08buTTPTZsyRpbotxxPHPqur8qhpvy9cBu6pqLbCrLQNcBqxtr83AzTAIGmALcCGwDtgyHTaSpMU3ilNVG4DtbX47sHGofmsN3A+cluQs4BJgZ1UdqqrDwE7g0sVuWpI00HdwFPCHSR5KsrnVzqyqZwHa9IxWPxvYO7TtvlabrX6EJJuTTCaZnJqaWuCPIUmatqLn/b+pqvYnOQPYmeRLc4zNDLWao35koWorsBVgfHz8ZeslSQuj1yOOqtrfpgeBOxlcozjQTkHRpgfb8H3AOUObrwb2z1GXJI1Ab8GR5PuT/MD0PLAe+CKwA5i+M2oCuKvN7wCuandXXQQ8105l3QOsT7KyXRRf32qSpBHo81TVmcCdSabf5/eq6g+SPAjcnuQa4Bngyjb+buByYA/wPHA1QFUdSnID8GAbd31VHeqxb0nSHHoLjqp6Gnj9DPW/BC6eoV7AtbPsaxuwbaF7lCR15zfHJUmdGBySpE4MDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1EnvwZHkpCQPJ/lMWz43yeeT7E7yqSSntPr3teU9bf2aoX28r9WfSnJJ3z1Lkma3GEccvwA8ObT8a8CHqmotcBi4ptWvAQ5X1WuBD7VxJDkP2AT8GHAp8DtJTlqEviVJM+g1OJKsBv4F8JG2HOBtwB1tyHZgY5vf0JZp6y9u4zcAt1XVC1X1ZWAPsK7PviVJs+v7iOM3gV8CvtOWXwN8vapebMv7gLPb/NnAXoC2/rk2/rv1GbaRJC2y3oIjyb8EDlbVQ8PlGYbWMdbNtc3w+21OMplkcmpqqnO/kqT5mVdwJNk1n9pR3gRckeQrwG0MTlH9JnBakhVtzGpgf5vfB5zT9r0COBU4NFyfYZvvqqqtVTVeVeNjY2Pz+ViSpOMwZ3AkeXWSVcDpSVYmWdVea4AfmmvbqnpfVa2uqjUMLm7fW1U/DdwH/FQbNgHc1eZ3tGXa+nurqlp9U7vr6lxgLfBAx88pSVogK46x/ueAX2QQEg/x0mmjbwC/fZzv+R+A25J8AHgYuKXVbwE+nmQPgyONTQBV9XiS24EngBeBa6vq28f53pKk79GcwVFVHwY+nOTnq+q3jvdNquqzwGfb/NPMcFdUVf01cOUs298I3Hi87y9JWjjHOuIAoKp+K8k/BdYMb1NVt/bUlyTpBDWv4EjyceAfAI8A06eJCjA4JGmZmVdwAOPAee1itSRpGZvv9zi+CPzdPhuRJC0N8z3iOB14IskDwAvTxaq6opeuJEknrPkGx/v7bEKStHTM966qP+q7EUnS0jDfu6r+ipeeD3UKcDLwrar6wb4akySdmOZ7xPEDw8tJNuKjzSVpWTqup+NW1acZPLRQkrTMzPdU1TuGFl/F4HsdfqdDkpah+d5V9ZND8y8CX2Hwy3ySpGVmvtc4ru67EUnS0jDfH3JaneTOJAeTHEjy++33xCVJy8x8L45/lMEPKv0Qg9/7/l+tJklaZuYbHGNV9dGqerG9Pgb4+6yStAzNNzi+luRnkpzUXj8D/GWfjUmSTkzzDY6fBd4FfBV4lsFvgnvBXJKWofnejnsDMFFVhwGSrAJ+g0GgSJKWkfkGx09MhwZAVR1K8oaeejohvPHf++OGermHfv2qUbcgjdx8T1W9KsnK6YV2xDHf0JEkvYLM9x///wr8aZI7GDxq5F3Ajb11JUk6Yc3riKOqbgXeCRwApoB3VNXH59omyauTPJDkz5I8nuRXW/3cJJ9PsjvJp5Kc0urf15b3tPVrhvb1vlZ/Ksklx/dRJUkLYd6nm6rqCeCJDvt+AXhbVX0zycnAHyf538C/BT5UVbcl+V3gGuDmNj1cVa9Nsgn4NeDdSc4DNgE/xuALiP8nyT+sqm936EWStECO67Hq81ED32yLJ7dXMXgc+x2tvh3Y2OY3tGXa+ouTpNVvq6oXqurLwB78LRBJGpneggOgfVnwEeAgsBP4c+DrVfViG7KPwSNMaNO9AG39c8BrhuszbDP8XpuTTCaZnJqa6uPjSJLoOTiq6ttVdT6wmsFRwo/ONKxNM8u62epHv9fWqhqvqvGxMZ+GIkl96TU4plXV14HPAhcBpyWZvrayGtjf5vcB5wC09acCh4brM2wjSVpkvQVHkrEkp7X5vwW8HXgSuI/BI0sAJoC72vyOtkxbf29VVatvanddnQusBR7oq29J0tz6/BLfWcD2JCcxCKjbq+ozSZ4AbkvyAeBh4JY2/hbg40n2MDjS2ARQVY8nuZ3BHV0vAtd6R5UkjU5vwVFVjwIveyxJVT3NDHdFVdVfA1fOsq8b8QuHknRCWJRrHJKkVw6DQ5LUicEhSerE4JAkdWJwSJI6MTgkSZ0YHJKkTgwOSVInBockqRODQ5LUicEhSerE4JAkdWJwSJI6MTgkSZ0YHJKkTgwOSVInBockqRODQ5LUicEhSerE4JAkdWJwSJI66S04kpyT5L4kTyZ5PMkvtPqqJDuT7G7Tla2eJDcl2ZPk0SQXDO1roo3fnWSir54lScfW5xHHi8C/q6ofBS4Crk1yHnAdsKuq1gK72jLAZcDa9toM3AyDoAG2ABcC64At02EjSVp8vQVHVT1bVV9o838FPAmcDWwAtrdh24GNbX4DcGsN3A+cluQs4BJgZ1UdqqrDwE7g0r76liTNbVGucSRZA7wB+DxwZlU9C4NwAc5ow84G9g5ttq/VZqtLkkag9+BI8neA3wd+saq+MdfQGWo1R/3o99mcZDLJ5NTU1PE1K0k6pl6DI8nJDELjE1X1P1v5QDsFRZsebPV9wDlDm68G9s9RP0JVba2q8aoaHxsbW9gPIkn6rj7vqgpwC/BkVf23oVU7gOk7oyaAu4bqV7W7qy4Cnmunsu4B1idZ2S6Kr281SdIIrOhx328C/jXwWJJHWu2XgQ8Ctye5BngGuLKtuxu4HNgDPA9cDVBVh5LcADzYxl1fVYd67FuSNIfegqOq/piZr08AXDzD+AKunWVf24BtC9edJOl4+c1xSVInBockqRODQ5LUicEhSerE4JAkdWJwSJI6MTgkSZ0YHJKkTgwOSVInBockqRODQ5LUicEhSerE4JAkdWJwSJI6MTgkSZ0YHJKkTgwOSVInBockqRODQ5LUicEhSerE4JAkdWJwSJI66S04kmxLcjDJF4dqq5LsTLK7TVe2epLclGRPkkeTXDC0zUQbvzvJRF/9SpLmp88jjo8Blx5Vuw7YVVVrgV1tGeAyYG17bQZuhkHQAFuAC4F1wJbpsJEkjUZvwVFVnwMOHVXeAGxv89uBjUP1W2vgfuC0JGcBlwA7q+pQVR0GdvLyMJIkLaLFvsZxZlU9C9CmZ7T62cDeoXH7Wm22+ssk2ZxkMsnk1NTUgjcuSRo4US6OZ4ZazVF/ebFqa1WNV9X42NjYgjYnSXrJYgfHgXYKijY92Or7gHOGxq0G9s9RlySNyGIHxw5g+s6oCeCuofpV7e6qi4Dn2qmse4D1SVa2i+LrW02SNCIr+tpxkk8CbwVOT7KPwd1RHwRuT3IN8AxwZRt+N3A5sAd4HrgaoKoOJbkBeLCNu76qjr7gLklaRL0FR1W9Z5ZVF88wtoBrZ9nPNmDbArYmSfoenCgXxyVJS4TBIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJwaHJKkTg0OS1InBIUnqxOCQJHVicEiSOjE4JEmdLJngSHJpkqeS7Ely3aj7kaTlakkER5KTgN8GLgPOA96T5LzRdiVJy9OSCA5gHbCnqp6uqr8BbgM2jLgnSVqWlkpwnA3sHVre12qSpEW2YtQNzFNmqNURA5LNwOa2+M0kT/Xe1fJxOvC1UTdxIshvTIy6BR3Jv81pW2b6Z7Kzvz+fQUslOPYB5wwtrwb2Dw+oqq3A1sVsarlIMllV46PuQzqaf5ujsVROVT0IrE1ybpJTgE3AjhH3JEnL0pI44qiqF5P8G+Ae4CRgW1U9PuK2JGlZWhLBAVBVdwN3j7qPZcpTgDpR+bc5AqmqY4+SJKlZKtc4JEknCINDR0hyhY900VKTZDzJTaPuY7nwVJV6keSkqvr2qPuQZpJkRVW9OOo+liqPOJaRJGuSfCnJR5J8Mcknkrw9yZ8k2Z1kXZL3JvnvbfzHktyU5E+TPJ3kp1o9SX697eOxJO9u9bcmuS/J7wGPjfCjagma59/nuvb3+HCbvq5t+9Ykn2nzq5J8OsmjSe5P8hOt/v4kW5P8IXDrCD/qkrdk7qrSgnktcCWDb9k/CPwr4M3AFcAvA58+avxZbf2PMPjuzB3AO4Dzgdcz+Obug0k+18avA368qr7c78fQK9Sx/j6vAt7SbtF/O/CfgHcetY9fBR6uqo1J3sYgJM5v694IvLmq/l/vn+QVzOBYfr5cVY8BJHkc2FVVleQxYM0M4z9dVd8BnkhyZqu9GfhkOxV1IMkfAf8Y+AbwgKGh78Gx/j5PBbYnWcvgsUMnz7CPN9PCpKruTfKaJKe2dTsMje+dp6qWnxeG5r8ztPwdZv6PxPD4HDWdybeOvzXpmH+fNwD3VdWPAz8JvHqGfcz1bDv/PheAwaHj8Tng3UlOSjIGvAV4YMQ9aXk4Ffi/bf69s4z5HPDTMLj2AXytqr7Re2fLiMGh43En8CjwZ8C9wC9V1VdH25KWif8C/Ockf8Lg8UPDpo8q3g+MJ3kU+CDgI40XmLfjSlrykrwTuKKqDIlF4MVxSUtakiuAG4GfHXUvy4VHHJKkTrzGIUnqxOCQJHVicEiSOjE4JEmdGBySpE4MDklSJ/8fU3BwxqxxWXoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(['major' if 'major' in key else 'minor'\n",
    "               for key in metadata['keyEstimate']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of tempo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fc192df5d30>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.distplot(metadata['bpm'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20.0, 600.0)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(metadata['bpm']), max(metadata['bpm'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of time signatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata.timeSignature = metadata.timeSignature.apply(str).astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "        34, 35]), <a list of 36 Text xticklabel objects>)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.countplot(metadata.timeSignature)\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'timeSignature == \"[4, 4]\"')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.countplot(metadata.timeSignature == '[4, 4]')\n",
    "plt.xlabel('timeSignature == \"[4, 4]\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'timeSignature == \"nan\"')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.countplot(metadata.timeSignature == 'nan')\n",
    "plt.xlabel('timeSignature == \"nan\"')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,\n",
       "        34, 35]), <a list of 36 Text xticklabel objects>)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "sns.countplot(metadata.loc[metadata.timeSignature != '[4, 4]', 'timeSignature'])\n",
    "plt.xticks(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Validation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Checking all are sorted"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This class checks to see if dataframes are sorted by onset then pitch. Running takes a while...No need to run, they all are sorted!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# prime_comp = {fn: Composition(note_df=prime[fn], sort_note_df=False,\n",
    "#                               check_sorted=True)\n",
    "#               for fn in tqdm(fn_list)}\n",
    "\n",
    "# for fn in tqdm(fn_list):\n",
    "#     try:\n",
    "#         Composition(note_df=prime[fn], sort_note_df=False)\n",
    "#     except IndexError as e:\n",
    "#         print(fn)\n",
    "#         print(e)\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cont_foil_comp = {fn: Composition(note_df=cont_foil[fn], sort_note_df=False,\n",
    "#                                   check_sorted=True)\n",
    "#                   for fn in tqdm(fn_list)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# cont_true_comp = {fn: Composition(note_df=cont_true[fn], sort_note_df=False,\n",
    "#                                   check_sorted=True)\n",
    "#                   for fn in tqdm(fn_list)}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Manual inspection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_listen(fn):\n",
    "    print(f'{fn}')\n",
    "    parts = ['prime', 'cont_true', 'cont_foil']\n",
    "    comp = {part: Composition(csv_path=f'{SIZE_PATH}/{part}_csv/{fn}.csv') \n",
    "            for part in parts}\n",
    "    fig, ax = plt.subplots(3, 1, figsize=(12, 8), sharey=True)\n",
    "    for ii, part in enumerate(parts):\n",
    "        plt.sca(ax[ii])\n",
    "        comp[part].plot(quantized=False)\n",
    "        plt.title(part)\n",
    "        fs = 16000\n",
    "        display(Audio(comp[part].synthesize(fs=fs), rate=fs))\n",
    "    plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b9a15846-98b1-489c-94c2-060e841c47e7\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",