searchAndRank_dev.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import midi2nmat as m2n\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#path=\"/Users/aaroncarter-enyi/Downloads/atavizm-SAR_dev/Data/a-exsultate.mid\"\n",
    "path=\"/Users/aaroncarter-enyi/Google Drive/atavizm-SAR_dev/Data/Fugue-BWV-847.mid\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import mido\n",
    "\n",
    "def midi2nmat(path):\n",
    "    \"\"\"Returns a Note Matrix from a given MIDI files\"\"\"\n",
    "    \n",
    "    assert (type(path) is str), \"Filepath must be a string: %r\" % path\n",
    "    mid = mido.MidiFile(path)\n",
    "    #print(\"mid : \", mid.time)\n",
    "    tpb = mid.ticks_per_beat\n",
    "\n",
    "    output=pd.DataFrame(columns=[\"Type\", \"Voice\", \"Pitch\", \"Velocity\", \"Ticks\"])\n",
    "\n",
    "    for track in mid.tracks:\n",
    "        midiframe = pd.DataFrame(columns=[\"Type\", \"Voice\", \"Pitch\", \"Velocity\", \"Ticks\"])\n",
    "        for msg in track:\n",
    "            if msg.type == \"note_on\":\n",
    "                df = pd.DataFrame({\"Type\":msg.type, \"Voice\":msg.channel, \"Pitch\":msg.note, \"Velocity\":msg.velocity, \"Ticks\":msg.time},\\\n",
    "                              index=[0])\n",
    "            else:\n",
    "                df = pd.DataFrame({\"Type\":msg.type, \"Ticks\":msg.time},\\\n",
    "                              index=[0])\n",
    "            midiframe = midiframe.append(df, ignore_index=True)\n",
    "        \n",
    "\n",
    "           \n",
    "            \n",
    "        midiframe[\"Time\"] = pd.Series(midiframe[\"Ticks\"].cumsum() / tpb, index=midiframe.index)\n",
    "\n",
    "        note_on = midiframe.loc[(midiframe[\"Velocity\"] != 0) & (midiframe[\"Type\"] == \"note_on\")]\n",
    "        note_off = midiframe.loc[(midiframe[\"Velocity\"] == 0) & (midiframe[\"Type\"] == \"note_on\")]\n",
    "        newdex = range(0,len(note_off))\n",
    "\n",
    "        \n",
    "\n",
    "        note_off = note_off.reset_index(drop=True)\n",
    "        note_on = note_on.reset_index(drop=True)\n",
    "\n",
    "\n",
    "        note_on[\"Duration\"] = pd.Series(note_off[\"Time\"] - note_on[\"Time\"], index = note_on.index)\n",
    "        print(\"noteon : \", note_on)\n",
    "        output=output.append(note_on[[\"Pitch\", \"Time\", \"Velocity\", \"Voice\", \"Duration\"]])\n",
    "        \n",
    "    \n",
    "    output.reset_index(drop=True, inplace=True)\n",
    "    print(\"output : \", output)\n",
    "\n",
    "    return output\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/aaroncarter-enyi/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py:6201: FutureWarning: Sorting because non-concatenation axis is not aligned. A future version\n",
      "of pandas will change to not sort by default.\n",
      "\n",
      "To accept the future behavior, pass 'sort=True'.\n",
      "\n",
      "To retain the current behavior and silence the warning, pass sort=False\n",
      "\n",
      "  sort=sort)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "noteon :      Pitch Ticks     Type Velocity Voice    Time  Duration\n",
      "0      79  4080  note_on       64     0     8.5  0.235417\n",
      "1      78     7  note_on       64     0    8.75  0.235417\n",
      "2      79     7  note_on       64     0       9  0.472917\n",
      "3      72    13  note_on       64     0     9.5  0.472917\n",
      "4      75    13  note_on       64     0      10  0.472917\n",
      "5      79    13  note_on       64     0    10.5  0.235417\n",
      "6      78     7  note_on       64     0   10.75  0.235417\n",
      "7      79     7  note_on       64     0      11  0.472917\n",
      "8      81    13  note_on       64     0    11.5  0.472917\n",
      "9      74    13  note_on       64     0      12  0.472917\n",
      "10     79    13  note_on       64     0    12.5  0.235417\n",
      "11     78     7  note_on       64     0   12.75  0.235417\n",
      "12     79     7  note_on       64     0      13  0.472917\n",
      "13     81    13  note_on       64     0    13.5  0.472917\n",
      "14     72    13  note_on       64     0      14  0.235417\n",
      "15     74     7  note_on       64     0   14.25  0.235417\n",
      "16     75     7  note_on       64     0    14.5  0.947917\n",
      "17     74    25  note_on       64     0    15.5  0.235417\n",
      "18     72     7  note_on       64     0   15.75  0.235417\n",
      "19     70     7  note_on       64     0      16  0.472917\n",
      "20     75    13  note_on       64     0    16.5  0.235417\n",
      "21     74     7  note_on       64     0   16.75  0.235417\n",
      "22     75     7  note_on       64     0      17  0.472917\n",
      "23     67    13  note_on       64     0    17.5  0.472917\n",
      "24     68    13  note_on       64     0      18  0.472917\n",
      "25     77    13  note_on       64     0    18.5  0.235417\n",
      "26     75     7  note_on       64     0   18.75  0.235417\n",
      "27     77     7  note_on       64     0      19  0.472917\n",
      "28     69    13  note_on       64     0    19.5  0.472917\n",
      "29     70    13  note_on       64     0      20  0.472917\n",
      "..    ...   ...      ...      ...   ...     ...       ...\n",
      "233    68    13  note_on       64     0     110  0.472917\n",
      "234    67    13  note_on       64     0   110.5  0.472917\n",
      "235    69   253  note_on       64     0   111.5  0.472917\n",
      "236    71    13  note_on       64     0     112  0.472917\n",
      "237    72    13  note_on       64     0   112.5  0.472917\n",
      "238    65    13  note_on       64     0     113  0.235417\n",
      "239    63     7  note_on       64     0  113.25  0.235417\n",
      "240    62     7  note_on       64     0   113.5  0.235417\n",
      "241    60     7  note_on       64     0  113.75  0.235417\n",
      "242    60     7  note_on       64     0     114  0.472917\n",
      "243    72    13  note_on       64     0   114.5  0.235417\n",
      "244    71     7  note_on       64     0  114.75  0.235417\n",
      "245    72     7  note_on       64     0     115  0.472917\n",
      "246    67    13  note_on       64     0   115.5  0.472917\n",
      "247    68    13  note_on       64     0     116  0.472917\n",
      "248    72    13  note_on       64     0   116.5  0.235417\n",
      "249    71     7  note_on       64     0  116.75  0.235417\n",
      "250    72     7  note_on       64     0     117  0.472917\n",
      "251    74    13  note_on       64     0   117.5  0.472917\n",
      "252    67    13  note_on       64     0     118  0.472917\n",
      "253    72    13  note_on       64     0   118.5  0.235417\n",
      "254    71     7  note_on       64     0  118.75  0.235417\n",
      "255    72     7  note_on       64     0     119  0.472917\n",
      "256    74    13  note_on       64     0   119.5  0.472917\n",
      "257    65    13  note_on       64     0     120  0.235417\n",
      "258    67     7  note_on       64     0  120.25  0.235417\n",
      "259    68     7  note_on       64     0   120.5  0.947917\n",
      "260    67    25  note_on       64     0   121.5  0.235417\n",
      "261    65     7  note_on       64     0  121.75  0.235417\n",
      "262    64     7  note_on       64     0     122   1.89792\n",
      "\n",
      "[263 rows x 7 columns]\n",
      "noteon :      Pitch Ticks     Type Velocity Voice    Time  Duration\n",
      "0      72   240  note_on       64     1     0.5  0.235417\n",
      "1      71     7  note_on       64     1    0.75  0.235417\n",
      "2      72     7  note_on       64     1       1  0.472917\n",
      "3      67    13  note_on       64     1     1.5  0.472917\n",
      "4      68    13  note_on       64     1       2  0.472917\n",
      "5      72    13  note_on       64     1     2.5  0.235417\n",
      "6      71     7  note_on       64     1    2.75  0.235417\n",
      "7      72     7  note_on       64     1       3  0.472917\n",
      "8      74    13  note_on       64     1     3.5  0.472917\n",
      "9      67    13  note_on       64     1       4  0.472917\n",
      "10     72    13  note_on       64     1     4.5  0.235417\n",
      "11     71     7  note_on       64     1    4.75  0.235417\n",
      "12     72     7  note_on       64     1       5  0.472917\n",
      "13     74    13  note_on       64     1     5.5  0.472917\n",
      "14     65    13  note_on       64     1       6  0.235417\n",
      "15     67     7  note_on       64     1    6.25  0.235417\n",
      "16     68     7  note_on       64     1     6.5  0.947917\n",
      "17     67    25  note_on       64     1     7.5  0.235417\n",
      "18     65     7  note_on       64     1    7.75  0.235417\n",
      "19     63     7  note_on       64     1       8  0.235417\n",
      "20     72     7  note_on       64     1    8.25  0.235417\n",
      "21     71     7  note_on       64     1     8.5  0.235417\n",
      "22     69     7  note_on       64     1    8.75  0.235417\n",
      "23     67     7  note_on       64     1       9  0.235417\n",
      "24     65     7  note_on       64     1    9.25  0.235417\n",
      "25     63     7  note_on       64     1     9.5  0.235417\n",
      "26     62     7  note_on       64     1    9.75  0.235417\n",
      "27     60     7  note_on       64     1      10  0.472917\n",
      "28     75    13  note_on       64     1    10.5  0.472917\n",
      "29     74    13  note_on       64     1      11  0.472917\n",
      "..    ...   ...      ...      ...   ...     ...       ...\n",
      "223    63    13  note_on       64     1     107  0.472917\n",
      "224    65    13  note_on       64     1   107.5  0.472917\n",
      "225    59    13  note_on       64     1     108  0.472917\n",
      "226    60    13  note_on       64     1   108.5  0.472917\n",
      "227    62    13  note_on       64     1     109  0.472917\n",
      "228    59    13  note_on       64     1   109.5  0.472917\n",
      "229    59    13  note_on       64     1     110  0.472917\n",
      "230    60    13  note_on       64     1   110.5  0.472917\n",
      "231    60   253  note_on       64     1   111.5  0.472917\n",
      "232    65    13  note_on       64     1     112  0.235417\n",
      "233    62     7  note_on       64     1  112.25  0.235417\n",
      "234    63     7  note_on       64     1   112.5  0.235417\n",
      "235    60     7  note_on       64     1  112.75  0.710417\n",
      "236    59    19  note_on       64     1   113.5  0.472917\n",
      "237    60    13  note_on       64     1     114  0.947917\n",
      "238    64   265  note_on       64     1   115.5  0.472917\n",
      "239    65    13  note_on       64     1     116  0.947917\n",
      "240    65   265  note_on       64     1   117.5  0.472917\n",
      "241    65    13  note_on       64     1     118  0.472917\n",
      "242    63    13  note_on       64     1   118.5  0.235417\n",
      "243    62     7  note_on       64     1  118.75  0.235417\n",
      "244    63     7  note_on       64     1     119  0.472917\n",
      "245    65    13  note_on       64     1   119.5  0.472917\n",
      "246    68     0  note_on       64     1   119.5  0.472917\n",
      "247    59    13  note_on       64     1     120  0.497917\n",
      "248    62     0  note_on       64     1     120  0.497917\n",
      "249    59   241  note_on       64     1     121  0.497917\n",
      "250    62     0  note_on       64     1     121  0.497917\n",
      "251    55   241  note_on       64     1     122   1.89792\n",
      "252    60     0  note_on       64     1     122   1.89792\n",
      "\n",
      "[253 rows x 7 columns]\n",
      "noteon :      Pitch  Ticks     Type Velocity Voice    Time  Duration\n",
      "0      60  11760  note_on       64     2    24.5  0.235417\n",
      "1      59      7  note_on       64     2   24.75  0.235417\n",
      "2      60      7  note_on       64     2      25  0.472917\n",
      "3      55     13  note_on       64     2    25.5  0.472917\n",
      "4      56     13  note_on       64     2      26  0.472917\n",
      "5      60     13  note_on       64     2    26.5  0.235417\n",
      "6      59      7  note_on       64     2   26.75  0.235417\n",
      "7      60      7  note_on       64     2      27  0.472917\n",
      "8      62     13  note_on       64     2    27.5  0.472917\n",
      "9      55     13  note_on       64     2      28  0.472917\n",
      "10     60     13  note_on       64     2    28.5  0.235417\n",
      "11     59      7  note_on       64     2   28.75  0.235417\n",
      "12     60      7  note_on       64     2      29  0.472917\n",
      "13     62     13  note_on       64     2    29.5  0.472917\n",
      "14     53     13  note_on       64     2      30  0.235417\n",
      "15     55      7  note_on       64     2   30.25  0.235417\n",
      "16     56      7  note_on       64     2    30.5  0.947917\n",
      "17     55     25  note_on       64     2    31.5  0.235417\n",
      "18     53      7  note_on       64     2   31.75  0.235417\n",
      "19     51      7  note_on       64     2      32  0.235417\n",
      "20     60      7  note_on       64     2   32.25  0.235417\n",
      "21     59      7  note_on       64     2    32.5  0.235417\n",
      "22     57      7  note_on       64     2   32.75  0.235417\n",
      "23     55      7  note_on       64     2      33  0.235417\n",
      "24     53      7  note_on       64     2   33.25  0.235417\n",
      "25     51      7  note_on       64     2    33.5  0.235417\n",
      "26     50      7  note_on       64     2   33.75  0.235417\n",
      "27     48      7  note_on       64     2      34  0.235417\n",
      "28     50      7  note_on       64     2   34.25  0.235417\n",
      "29     51      7  note_on       64     2    34.5  0.235417\n",
      "..    ...    ...      ...      ...   ...     ...       ...\n",
      "205    51      7  note_on       64     2  101.25  0.235417\n",
      "206    50      7  note_on       64     2   101.5  0.235417\n",
      "207    48      7  note_on       64     2  101.75  0.235417\n",
      "208    47      7  note_on       64     2     102  0.472917\n",
      "209    48     13  note_on       64     2   102.5  0.235417\n",
      "210    47      7  note_on       64     2  102.75  0.235417\n",
      "211    48      7  note_on       64     2     103  0.472917\n",
      "212    43     13  note_on       64     2   103.5  0.472917\n",
      "213    44     13  note_on       64     2     104  0.472917\n",
      "214    48     13  note_on       64     2   104.5  0.235417\n",
      "215    47      7  note_on       64     2  104.75  0.235417\n",
      "216    48      7  note_on       64     2     105  0.472917\n",
      "217    50     13  note_on       64     2   105.5  0.472917\n",
      "218    43     13  note_on       64     2     106  0.472917\n",
      "219    48     13  note_on       64     2   106.5  0.235417\n",
      "220    47      7  note_on       64     2  106.75  0.235417\n",
      "221    48      7  note_on       64     2     107  0.472917\n",
      "222    50     13  note_on       64     2   107.5  0.472917\n",
      "223    41     13  note_on       64     2     108  0.235417\n",
      "224    43      7  note_on       64     2  108.25  0.235417\n",
      "225    44      7  note_on       64     2   108.5  0.947917\n",
      "226    43     25  note_on       64     2   109.5  0.235417\n",
      "227    41      7  note_on       64     2  109.75  0.235417\n",
      "228    39      7  note_on       64     2     110  0.947917\n",
      "229    51    265  note_on       64     2   111.5  0.472917\n",
      "230    50     13  note_on       64     2     112  0.472917\n",
      "231    48     13  note_on       64     2   112.5  0.472917\n",
      "232    55     13  note_on       64     2     113  0.472917\n",
      "233    43     13  note_on       64     2   113.5  0.472917\n",
      "234    48     13  note_on       64     2     114   9.49792\n",
      "\n",
      "[235 rows x 7 columns]\n",
      "output :       Duration Pitch Ticks    Time Type Velocity Voice\n",
      "0    0.235417    79   NaN     8.5  NaN       64     0\n",
      "1    0.235417    78   NaN    8.75  NaN       64     0\n",
      "2    0.472917    79   NaN       9  NaN       64     0\n",
      "3    0.472917    72   NaN     9.5  NaN       64     0\n",
      "4    0.472917    75   NaN      10  NaN       64     0\n",
      "5    0.235417    79   NaN    10.5  NaN       64     0\n",
      "6    0.235417    78   NaN   10.75  NaN       64     0\n",
      "7    0.472917    79   NaN      11  NaN       64     0\n",
      "8    0.472917    81   NaN    11.5  NaN       64     0\n",
      "9    0.472917    74   NaN      12  NaN       64     0\n",
      "10   0.235417    79   NaN    12.5  NaN       64     0\n",
      "11   0.235417    78   NaN   12.75  NaN       64     0\n",
      "12   0.472917    79   NaN      13  NaN       64     0\n",
      "13   0.472917    81   NaN    13.5  NaN       64     0\n",
      "14   0.235417    72   NaN      14  NaN       64     0\n",
      "15   0.235417    74   NaN   14.25  NaN       64     0\n",
      "16   0.947917    75   NaN    14.5  NaN       64     0\n",
      "17   0.235417    74   NaN    15.5  NaN       64     0\n",
      "18   0.235417    72   NaN   15.75  NaN       64     0\n",
      "19   0.472917    70   NaN      16  NaN       64     0\n",
      "20   0.235417    75   NaN    16.5  NaN       64     0\n",
      "21   0.235417    74   NaN   16.75  NaN       64     0\n",
      "22   0.472917    75   NaN      17  NaN       64     0\n",
      "23   0.472917    67   NaN    17.5  NaN       64     0\n",
      "24   0.472917    68   NaN      18  NaN       64     0\n",
      "25   0.235417    77   NaN    18.5  NaN       64     0\n",
      "26   0.235417    75   NaN   18.75  NaN       64     0\n",
      "27   0.472917    77   NaN      19  NaN       64     0\n",
      "28   0.472917    69   NaN    19.5  NaN       64     0\n",
      "29   0.472917    70   NaN      20  NaN       64     0\n",
      "..        ...   ...   ...     ...  ...      ...   ...\n",
      "721  0.235417    51   NaN  101.25  NaN       64     2\n",
      "722  0.235417    50   NaN   101.5  NaN       64     2\n",
      "723  0.235417    48   NaN  101.75  NaN       64     2\n",
      "724  0.472917    47   NaN     102  NaN       64     2\n",
      "725  0.235417    48   NaN   102.5  NaN       64     2\n",
      "726  0.235417    47   NaN  102.75  NaN       64     2\n",
      "727  0.472917    48   NaN     103  NaN       64     2\n",
      "728  0.472917    43   NaN   103.5  NaN       64     2\n",
      "729  0.472917    44   NaN     104  NaN       64     2\n",
      "730  0.235417    48   NaN   104.5  NaN       64     2\n",
      "731  0.235417    47   NaN  104.75  NaN       64     2\n",
      "732  0.472917    48   NaN     105  NaN       64     2\n",
      "733  0.472917    50   NaN   105.5  NaN       64     2\n",
      "734  0.472917    43   NaN     106  NaN       64     2\n",
      "735  0.235417    48   NaN   106.5  NaN       64     2\n",
      "736  0.235417    47   NaN  106.75  NaN       64     2\n",
      "737  0.472917    48   NaN     107  NaN       64     2\n",
      "738  0.472917    50   NaN   107.5  NaN       64     2\n",
      "739  0.235417    41   NaN     108  NaN       64     2\n",
      "740  0.235417    43   NaN  108.25  NaN       64     2\n",
      "741  0.947917    44   NaN   108.5  NaN       64     2\n",
      "742  0.235417    43   NaN   109.5  NaN       64     2\n",
      "743  0.235417    41   NaN  109.75  NaN       64     2\n",
      "744  0.947917    39   NaN     110  NaN       64     2\n",
      "745  0.472917    51   NaN   111.5  NaN       64     2\n",
      "746  0.472917    50   NaN     112  NaN       64     2\n",
      "747  0.472917    48   NaN   112.5  NaN       64     2\n",
      "748  0.472917    55   NaN     113  NaN       64     2\n",
      "749  0.472917    43   NaN   113.5  NaN       64     2\n",
      "750   9.49792    48   NaN     114  NaN       64     2\n",
      "\n",
      "[751 rows x 7 columns]\n"
     ]
    }
   ],
   "source": [
    "test = midi2nmat(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test :       Duration Pitch Ticks    Time Type Velocity Voice\n",
      "0    0.235417    79   NaN     8.5  NaN       64     0\n",
      "1    0.235417    78   NaN    8.75  NaN       64     0\n",
      "2    0.472917    79   NaN       9  NaN       64     0\n",
      "3    0.472917    72   NaN     9.5  NaN       64     0\n",
      "4    0.472917    75   NaN      10  NaN       64     0\n",
      "5    0.235417    79   NaN    10.5  NaN       64     0\n",
      "6    0.235417    78   NaN   10.75  NaN       64     0\n",
      "7    0.472917    79   NaN      11  NaN       64     0\n",
      "8    0.472917    81   NaN    11.5  NaN       64     0\n",
      "9    0.472917    74   NaN      12  NaN       64     0\n",
      "10   0.235417    79   NaN    12.5  NaN       64     0\n",
      "11   0.235417    78   NaN   12.75  NaN       64     0\n",
      "12   0.472917    79   NaN      13  NaN       64     0\n",
      "13   0.472917    81   NaN    13.5  NaN       64     0\n",
      "14   0.235417    72   NaN      14  NaN       64     0\n",
      "15   0.235417    74   NaN   14.25  NaN       64     0\n",
      "16   0.947917    75   NaN    14.5  NaN       64     0\n",
      "17   0.235417    74   NaN    15.5  NaN       64     0\n",
      "18   0.235417    72   NaN   15.75  NaN       64     0\n",
      "19   0.472917    70   NaN      16  NaN       64     0\n",
      "20   0.235417    75   NaN    16.5  NaN       64     0\n",
      "21   0.235417    74   NaN   16.75  NaN       64     0\n",
      "22   0.472917    75   NaN      17  NaN       64     0\n",
      "23   0.472917    67   NaN    17.5  NaN       64     0\n",
      "24   0.472917    68   NaN      18  NaN       64     0\n",
      "25   0.235417    77   NaN    18.5  NaN       64     0\n",
      "26   0.235417    75   NaN   18.75  NaN       64     0\n",
      "27   0.472917    77   NaN      19  NaN       64     0\n",
      "28   0.472917    69   NaN    19.5  NaN       64     0\n",
      "29   0.472917    70   NaN      20  NaN       64     0\n",
      "..        ...   ...   ...     ...  ...      ...   ...\n",
      "721  0.235417    51   NaN  101.25  NaN       64     2\n",
      "722  0.235417    50   NaN   101.5  NaN       64     2\n",
      "723  0.235417    48   NaN  101.75  NaN       64     2\n",
      "724  0.472917    47   NaN     102  NaN       64     2\n",
      "725  0.235417    48   NaN   102.5  NaN       64     2\n",
      "726  0.235417    47   NaN  102.75  NaN       64     2\n",
      "727  0.472917    48   NaN     103  NaN       64     2\n",
      "728  0.472917    43   NaN   103.5  NaN       64     2\n",
      "729  0.472917    44   NaN     104  NaN       64     2\n",
      "730  0.235417    48   NaN   104.5  NaN       64     2\n",
      "731  0.235417    47   NaN  104.75  NaN       64     2\n",
      "732  0.472917    48   NaN     105  NaN       64     2\n",
      "733  0.472917    50   NaN   105.5  NaN       64     2\n",
      "734  0.472917    43   NaN     106  NaN       64     2\n",
      "735  0.235417    48   NaN   106.5  NaN       64     2\n",
      "736  0.235417    47   NaN  106.75  NaN       64     2\n",
      "737  0.472917    48   NaN     107  NaN       64     2\n",
      "738  0.472917    50   NaN   107.5  NaN       64     2\n",
      "739  0.235417    41   NaN     108  NaN       64     2\n",
      "740  0.235417    43   NaN  108.25  NaN       64     2\n",
      "741  0.947917    44   NaN   108.5  NaN       64     2\n",
      "742  0.235417    43   NaN   109.5  NaN       64     2\n",
      "743  0.235417    41   NaN  109.75  NaN       64     2\n",
      "744  0.947917    39   NaN     110  NaN       64     2\n",
      "745  0.472917    51   NaN   111.5  NaN       64     2\n",
      "746  0.472917    50   NaN     112  NaN       64     2\n",
      "747  0.472917    48   NaN   112.5  NaN       64     2\n",
      "748  0.472917    55   NaN     113  NaN       64     2\n",
      "749  0.472917    43   NaN   113.5  NaN       64     2\n",
      "750   9.49792    48   NaN     114  NaN       64     2\n",
      "\n",
      "[751 rows x 7 columns]\n",
      "voices :  [0 1 2]\n",
      "voice:  114.0\n",
      "voice:  8.5\n",
      "voice:  122.0\n",
      "voice:  0.5\n",
      "voice:  122.0\n",
      "voice:  24.5\n"
     ]
    }
   ],
   "source": [
    "print(\"test : \", test)\n",
    "voice=test[\"Voice\"]\n",
    "voices=voice.unique();\n",
    "print(\"voices : \", voices)\n",
    "ind=[];\n",
    "for i in range(0, len(voices)):\n",
    "    temp=voice[voice==i].index[0]\n",
    "    ind.append(temp)\n",
    "    print(\"voice: \", test[\"Time\"].iloc[temp-1])\n",
    "    print(\"voice: \", test[\"Time\"].iloc[temp])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _make_ContCM(arr, deg1, deg2 = None):\n",
    "    \"\"\"\n",
    "    Creates Continous Contour Matrix for searching\n",
    "    Adapted for asynchrony\n",
    "    \"\"\"\n",
    "    \n",
    "    if deg2 is None:\n",
    "        deg2 = deg1\n",
    "    \n",
    "    degrees = deg1 + deg2\n",
    "    ContCM = np.zeros((degrees,len(arr))) #creates and initializes  contour matrix w/ zeroes\n",
    "    ContCM.fill(np.nan)            #fills matrix with Null values\n",
    "    #print(arr)\n",
    "    for n in range(0,len(arr)):    \n",
    "            for i in [1,2]:\n",
    "                try:\n",
    "                    if arr[n] > arr[n-i] and n-i >= 0 :\n",
    "                        ContCM[deg1-i, n] = 1\n",
    "                    elif n-i >= 0:\n",
    "                        ContCM[deg1-i, n] = 0\n",
    "                except:\n",
    "                    continue\n",
    "\n",
    "            for i in [1,2]:\n",
    "                try:\n",
    "                    if arr[n] > arr[n+i]:\n",
    "                        ContCM[deg1+i-1, n] = 1\n",
    "                    else:\n",
    "                        ContCM[deg1+i-1, n] = 0\n",
    "                except:\n",
    "                    continue\n",
    "    \n",
    "    return ContCM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def _get_segments(cmin,cmax,pitches,CL_list):    \n",
    "    p = []\n",
    "    for n in range(cmin,cmax): #this should be a range of cardinalities to look over\n",
    "        segments = [CL_list[0][i:i+n] for i in range(0, len(pitches)-n)] #get list of all possible segments of n cardinality\n",
    "        segmentu = [list(x) for x in set(tuple(x) for x in segments)] #get the unique segments from the list\n",
    "\n",
    "        segind = [[] for i in range(0,len(segmentu))] #get the index of these occurences of these segments, this also happens to be the index of the notes they start on\n",
    "        for i in range(0,len(segmentu)):\n",
    "            for j in range(0,len(segments)):\n",
    "                if (segments[j] == segmentu[i]).all():\n",
    "                    segind[i].append(j)\n",
    "\n",
    "        if len(segments) == len(segmentu):\n",
    "            break\n",
    "        \n",
    "        segmentucount = np.array([len(x) for x in segind]) #get a count of all the occurences for a given segment\n",
    "#         segmentpitch = [pitches[ind[i][0]-2:ind[i][0]+n-1+2] for i in range(len(ind))] #get the pitches of the original occurence\n",
    "\n",
    "        max_ind = np.argsort(segmentucount)[::-1][:5] #the indexes of the 5 most frequent segments so that the largest is in front\n",
    "        max_segmentu = np.array(segmentu)[max_ind]\n",
    "        max_segmentucount = segmentucount[max_ind]\n",
    "#         max_segmentpitch = np.array(segmentpitch)[max_ind]\n",
    "        max_segmentucov = [i*n for i in max_segmentucount]\n",
    "        max_segind = np.array(segind)[max_ind]\n",
    "\n",
    "        p.append({\"segments\":segments,\n",
    "                  \"seg\":max_segmentu,\n",
    "                  \"segcount\":max_segmentucount,\n",
    "                  \"segind\":max_segind,\n",
    "                  \"segcov\":max_segmentucov}) #storing the results in a data structure for later (will have index n-1)\n",
    "    return p\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def SAR_Contour(nmat, s_type=3, cmin=5, cmax=10, degrees=2):\n",
    "    print(\"nmat : \", nmat)\n",
    "    pitches=list(nmat['Pitch']) #Get the list of pitches for the piece\n",
    "    contcom = _make_ContCM(pitches,degrees) #convert to continuous contour matrix\n",
    "    CL = np.nansum(contcom, axis=0) #get the sums of the columns of the matrix\n",
    "    \n",
    "    if s_type > 1:\n",
    "        durs=list(nmat['Time']) #extract beat onsets as a list\n",
    "        durs=[x-y for x,y in zip(durs[1:len(durs)-1],durs[0:len(durs)-2])] #convert to interonset durations by subtracting adjacent onsets\n",
    "        durs.append(nmat['Duration'].iloc[-1]) #add the duration of the last note back to list\n",
    "        contcom=_make_ContCM(durs,degrees) #create continuous contour matrix\n",
    "        DCL = np.nansum(contcom, axis=0) #get the sums of the columns of the matrix\n",
    "        \n",
    "    if s_type == 1:\n",
    "        CL_list = [CL, CL]\n",
    "    elif s_type == 2:\n",
    "        CL_list = [DCL, DCL]\n",
    "    elif s_type == 3:\n",
    "        CL_list = [CL,DCL]\n",
    "    \n",
    "    p = _get_segments(cmin,cmax,pitches,CL_list) #makes a dataframe of all the important segments needed\n",
    "    \n",
    "    #initialize storage variables\n",
    "#     allcov = []\n",
    "    r = pd.DataFrame(columns=['card','seg','segcount','segind','cov','invind'])\n",
    "    \n",
    "    for i in range(0,len(p)):\n",
    "        for j in range(0,len(p[i][\"seg\"])):\n",
    "            r = r.append({\"card\":len(p[i][\"seg\"][j]),\n",
    "                  \"seg\":p[i][\"seg\"][j],\n",
    "                  \"segcount\":p[i][\"segcount\"][j],\n",
    "                  \"segind\":p[i][\"segind\"][j],\n",
    "                  \"cov\":p[i][\"segcov\"][j],\n",
    "                  \"invind\":[]}, ignore_index=True)\n",
    "#             allcov.append(p[i][\"segcov\"][j])\n",
    "\n",
    "    r = r.sort_values(by=[\"cov\"], ascending=False).reset_index(drop=True)\n",
    "\n",
    "    s = []\n",
    "\n",
    "    for i in range(0,len(r)):\n",
    "        inds=[];\n",
    "        for j in range(0,len(r[\"segind\"].iloc[i])):\n",
    "            a=r[\"segind\"].iloc[i][j]\n",
    "            b=r[\"segind\"].iloc[i][j]+r[\"card\"].iloc[i]-1\n",
    "            temp=list(range(a,b))\n",
    "            inds=inds+temp\n",
    "        #print(\"inds : \", inds)\n",
    "        s.append(inds)\n",
    "        \n",
    "    r[\"inds\"] = pd.Series(s, index=r.index) \n",
    "    \n",
    "    for i in range(len(r)-1,1,-1):\n",
    "        print(\"lenr : \", len(r))\n",
    "        print(\"i : \", i)\n",
    "        b=r[\"inds\"].iloc[i]\n",
    "        print(\"b : \", b)\n",
    "        for j in range(0,i-1):\n",
    "            a=r[\"inds\"].iloc[j]\n",
    "            print(\"a : \", a)\n",
    "            if set(b).issubset(set(a)):\n",
    "                print(\"yes\")\n",
    "                print(\"rtest : \", r[\"inds\"].iloc[i])\n",
    "                r.drop(r.index[i], inplace=True)\n",
    "                break\n",
    "                \n",
    "    r = r.sort_values(by=[\"cov\"], ascending=False).reset_index(drop=True)\n",
    "    \n",
    "    return {\"r\":r, \"p\":p, \"CL\":CL_list, \"nmat\":nmat}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "nmat :       Duration Pitch Ticks    Time Type Velocity Voice\n",
      "0    0.235417    79   NaN     8.5  NaN       64     0\n",
      "1    0.235417    78   NaN    8.75  NaN       64     0\n",
      "2    0.472917    79   NaN       9  NaN       64     0\n",
      "3    0.472917    72   NaN     9.5  NaN       64     0\n",
      "4    0.472917    75   NaN      10  NaN       64     0\n",
      "5    0.235417    79   NaN    10.5  NaN       64     0\n",
      "6    0.235417    78   NaN   10.75  NaN       64     0\n",
      "7    0.472917    79   NaN      11  NaN       64     0\n",
      "8    0.472917    81   NaN    11.5  NaN       64     0\n",
      "9    0.472917    74   NaN      12  NaN       64     0\n",
      "10   0.235417    79   NaN    12.5  NaN       64     0\n",
      "11   0.235417    78   NaN   12.75  NaN       64     0\n",
      "12   0.472917    79   NaN      13  NaN       64     0\n",
      "13   0.472917    81   NaN    13.5  NaN       64     0\n",
      "14   0.235417    72   NaN      14  NaN       64     0\n",
      "15   0.235417    74   NaN   14.25  NaN       64     0\n",
      "16   0.947917    75   NaN    14.5  NaN       64     0\n",
      "17   0.235417    74   NaN    15.5  NaN       64     0\n",
      "18   0.235417    72   NaN   15.75  NaN       64     0\n",
      "19   0.472917    70   NaN      16  NaN       64     0\n",
      "20   0.235417    75   NaN    16.5  NaN       64     0\n",
      "21   0.235417    74   NaN   16.75  NaN       64     0\n",
      "22   0.472917    75   NaN      17  NaN       64     0\n",
      "23   0.472917    67   NaN    17.5  NaN       64     0\n",
      "24   0.472917    68   NaN      18  NaN       64     0\n",
      "25   0.235417    77   NaN    18.5  NaN       64     0\n",
      "26   0.235417    75   NaN   18.75  NaN       64     0\n",
      "27   0.472917    77   NaN      19  NaN       64     0\n",
      "28   0.472917    69   NaN    19.5  NaN       64     0\n",
      "29   0.472917    70   NaN      20  NaN       64     0\n",
      "..        ...   ...   ...     ...  ...      ...   ...\n",
      "721  0.235417    51   NaN  101.25  NaN       64     2\n",
      "722  0.235417    50   NaN   101.5  NaN       64     2\n",
      "723  0.235417    48   NaN  101.75  NaN       64     2\n",
      "724  0.472917    47   NaN     102  NaN       64     2\n",
      "725  0.235417    48   NaN   102.5  NaN       64     2\n",
      "726  0.235417    47   NaN  102.75  NaN       64     2\n",
      "727  0.472917    48   NaN     103  NaN       64     2\n",
      "728  0.472917    43   NaN   103.5  NaN       64     2\n",
      "729  0.472917    44   NaN     104  NaN       64     2\n",
      "730  0.235417    48   NaN   104.5  NaN       64     2\n",
      "731  0.235417    47   NaN  104.75  NaN       64     2\n",
      "732  0.472917    48   NaN     105  NaN       64     2\n",
      "733  0.472917    50   NaN   105.5  NaN       64     2\n",
      "734  0.472917    43   NaN     106  NaN       64     2\n",
      "735  0.235417    48   NaN   106.5  NaN       64     2\n",
      "736  0.235417    47   NaN  106.75  NaN       64     2\n",
      "737  0.472917    48   NaN     107  NaN       64     2\n",
      "738  0.472917    50   NaN   107.5  NaN       64     2\n",
      "739  0.235417    41   NaN     108  NaN       64     2\n",
      "740  0.235417    43   NaN  108.25  NaN       64     2\n",
      "741  0.947917    44   NaN   108.5  NaN       64     2\n",
      "742  0.235417    43   NaN   109.5  NaN       64     2\n",
      "743  0.235417    41   NaN  109.75  NaN       64     2\n",
      "744  0.947917    39   NaN     110  NaN       64     2\n",
      "745  0.472917    51   NaN   111.5  NaN       64     2\n",
      "746  0.472917    50   NaN     112  NaN       64     2\n",
      "747  0.472917    48   NaN   112.5  NaN       64     2\n",
      "748  0.472917    55   NaN     113  NaN       64     2\n",
      "749  0.472917    43   NaN   113.5  NaN       64     2\n",
      "750   9.49792    48   NaN     114  NaN       64     2\n",
      "\n",
      "[751 rows x 7 columns]\n",
      "lenr :  25\n",
      "i :  24\n",
      "b :  [20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 180, 181, 182, 183, 184, 243, 244, 245, 246, 247, 263, 264, 265, 266, 267, 381, 382, 383, 384, 385, 422, 423, 424, 425, 426, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 78, 79, 80, 162, 163, 164, 165, 166, 167, 168, 169, 245, 246, 247, 248, 249, 250, 251, 252, 265, 266, 267, 268, 269, 270, 271, 272, 383, 384, 385, 386, 387, 388, 389, 390, 518, 519, 520, 521, 522, 523, 524, 525, 727, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [39, 40, 41, 42, 43, 44, 124, 125, 126, 127, 128, 129, 285, 286, 287, 288, 289, 290, 434, 435, 436, 437, 438, 439, 546, 547, 548, 549, 550, 551, 562, 563, 564, 565, 566, 567, 570, 571, 572, 573, 574, 575, 663, 664, 665, 666, 667, 668, 679, 680, 681, 682, 683, 684, 695, 696, 697, 698, 699, 700]\n",
      "a :  [43, 44, 45, 46, 128, 129, 130, 131, 212, 213, 214, 215, 281, 282, 283, 284, 289, 290, 291, 292, 438, 439, 440, 441, 479, 480, 481, 482, 534, 535, 536, 537, 550, 551, 552, 553, 566, 567, 568, 569, 574, 575, 576, 577, 667, 668, 669, 670, 683, 684, 685, 686, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 44, 45, 125, 126, 127, 128, 129, 130, 286, 287, 288, 289, 290, 291, 435, 436, 437, 438, 439, 440, 547, 548, 549, 550, 551, 552, 563, 564, 565, 566, 567, 568, 571, 572, 573, 574, 575, 576, 664, 665, 666, 667, 668, 669, 680, 681, 682, 683, 684, 685, 696, 697, 698, 699, 700, 701]\n",
      "a :  [41, 42, 43, 44, 45, 126, 127, 128, 129, 130, 287, 288, 289, 290, 291, 436, 437, 438, 439, 440, 477, 478, 479, 480, 481, 548, 549, 550, 551, 552, 564, 565, 566, 567, 568, 572, 573, 574, 575, 576, 665, 666, 667, 668, 669, 681, 682, 683, 684, 685, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 127, 128, 129, 130, 280, 281, 282, 283, 288, 289, 290, 291, 437, 438, 439, 440, 478, 479, 480, 481, 533, 534, 535, 536, 549, 550, 551, 552, 565, 566, 567, 568, 573, 574, 575, 576, 666, 667, 668, 669, 682, 683, 684, 685, 698, 699, 700, 701]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 74, 75, 76, 77, 78, 79, 80, 163, 164, 165, 166, 167, 168, 169, 246, 247, 248, 249, 250, 251, 252, 266, 267, 268, 269, 270, 271, 272, 384, 385, 386, 387, 388, 389, 390, 519, 520, 521, 522, 523, 524, 525, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [10, 11, 12, 13, 14, 15, 16, 81, 82, 83, 84, 85, 86, 87, 170, 171, 172, 173, 174, 175, 176, 253, 254, 255, 256, 257, 258, 259, 273, 274, 275, 276, 277, 278, 279, 391, 392, 393, 394, 395, 396, 397, 526, 527, 528, 529, 530, 531, 532, 735, 736, 737, 738, 739, 740, 741]\n",
      "a :  [7, 8, 9, 10, 11, 12, 13, 78, 79, 80, 81, 82, 83, 84, 167, 168, 169, 170, 171, 172, 173, 250, 251, 252, 253, 254, 255, 256, 270, 271, 272, 273, 274, 275, 276, 388, 389, 390, 391, 392, 393, 394, 523, 524, 525, 526, 527, 528, 529, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [40, 41, 42, 43, 44, 125, 126, 127, 128, 129, 286, 287, 288, 289, 290, 435, 436, 437, 438, 439, 547, 548, 549, 550, 551, 563, 564, 565, 566, 567, 571, 572, 573, 574, 575, 664, 665, 666, 667, 668, 680, 681, 682, 683, 684, 696, 697, 698, 699, 700]\n",
      "a :  [20, 21, 22, 23, 25, 26, 27, 28, 30, 31, 32, 33, 57, 58, 59, 60, 180, 181, 182, 183, 243, 244, 245, 246, 263, 264, 265, 266, 381, 382, 383, 384, 422, 423, 424, 425, 427, 428, 429, 430, 616, 617, 618, 619, 621, 622, 623, 624]\n",
      "a :  [7, 8, 9, 10, 11, 12, 78, 79, 80, 81, 82, 83, 167, 168, 169, 170, 171, 172, 250, 251, 252, 253, 254, 255, 270, 271, 272, 273, 274, 275, 388, 389, 390, 391, 392, 393, 523, 524, 525, 526, 527, 528, 732, 733, 734, 735, 736, 737]\n",
      "lenr :  25\n",
      "i :  23\n",
      "b :  [8, 9, 10, 11, 12, 13, 79, 80, 81, 82, 83, 84, 168, 169, 170, 171, 172, 173, 251, 252, 253, 254, 255, 256, 271, 272, 273, 274, 275, 276, 389, 390, 391, 392, 393, 394, 524, 525, 526, 527, 528, 529, 733, 734, 735, 736, 737, 738]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "yes\n",
      "rtest :  [8, 9, 10, 11, 12, 13, 79, 80, 81, 82, 83, 84, 168, 169, 170, 171, 172, 173, 251, 252, 253, 254, 255, 256, 271, 272, 273, 274, 275, 276, 389, 390, 391, 392, 393, 394, 524, 525, 526, 527, 528, 529, 733, 734, 735, 736, 737, 738]\n",
      "lenr :  24\n",
      "i :  22\n",
      "b :  [7, 8, 9, 10, 11, 12, 78, 79, 80, 81, 82, 83, 167, 168, 169, 170, 171, 172, 250, 251, 252, 253, 254, 255, 270, 271, 272, 273, 274, 275, 388, 389, 390, 391, 392, 393, 523, 524, 525, 526, 527, 528, 732, 733, 734, 735, 736, 737]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "yes\n",
      "rtest :  [7, 8, 9, 10, 11, 12, 78, 79, 80, 81, 82, 83, 167, 168, 169, 170, 171, 172, 250, 251, 252, 253, 254, 255, 270, 271, 272, 273, 274, 275, 388, 389, 390, 391, 392, 393, 523, 524, 525, 526, 527, 528, 732, 733, 734, 735, 736, 737]\n",
      "lenr :  23\n",
      "i :  21\n",
      "b :  [20, 21, 22, 23, 25, 26, 27, 28, 30, 31, 32, 33, 57, 58, 59, 60, 180, 181, 182, 183, 243, 244, 245, 246, 263, 264, 265, 266, 381, 382, 383, 384, 422, 423, 424, 425, 427, 428, 429, 430, 616, 617, 618, 619, 621, 622, 623, 624]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 78, 79, 80, 162, 163, 164, 165, 166, 167, 168, 169, 245, 246, 247, 248, 249, 250, 251, 252, 265, 266, 267, 268, 269, 270, 271, 272, 383, 384, 385, 386, 387, 388, 389, 390, 518, 519, 520, 521, 522, 523, 524, 525, 727, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [39, 40, 41, 42, 43, 44, 124, 125, 126, 127, 128, 129, 285, 286, 287, 288, 289, 290, 434, 435, 436, 437, 438, 439, 546, 547, 548, 549, 550, 551, 562, 563, 564, 565, 566, 567, 570, 571, 572, 573, 574, 575, 663, 664, 665, 666, 667, 668, 679, 680, 681, 682, 683, 684, 695, 696, 697, 698, 699, 700]\n",
      "a :  [43, 44, 45, 46, 128, 129, 130, 131, 212, 213, 214, 215, 281, 282, 283, 284, 289, 290, 291, 292, 438, 439, 440, 441, 479, 480, 481, 482, 534, 535, 536, 537, 550, 551, 552, 553, 566, 567, 568, 569, 574, 575, 576, 577, 667, 668, 669, 670, 683, 684, 685, 686, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 44, 45, 125, 126, 127, 128, 129, 130, 286, 287, 288, 289, 290, 291, 435, 436, 437, 438, 439, 440, 547, 548, 549, 550, 551, 552, 563, 564, 565, 566, 567, 568, 571, 572, 573, 574, 575, 576, 664, 665, 666, 667, 668, 669, 680, 681, 682, 683, 684, 685, 696, 697, 698, 699, 700, 701]\n",
      "a :  [41, 42, 43, 44, 45, 126, 127, 128, 129, 130, 287, 288, 289, 290, 291, 436, 437, 438, 439, 440, 477, 478, 479, 480, 481, 548, 549, 550, 551, 552, 564, 565, 566, 567, 568, 572, 573, 574, 575, 576, 665, 666, 667, 668, 669, 681, 682, 683, 684, 685, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 127, 128, 129, 130, 280, 281, 282, 283, 288, 289, 290, 291, 437, 438, 439, 440, 478, 479, 480, 481, 533, 534, 535, 536, 549, 550, 551, 552, 565, 566, 567, 568, 573, 574, 575, 576, 666, 667, 668, 669, 682, 683, 684, 685, 698, 699, 700, 701]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 74, 75, 76, 77, 78, 79, 80, 163, 164, 165, 166, 167, 168, 169, 246, 247, 248, 249, 250, 251, 252, 266, 267, 268, 269, 270, 271, 272, 384, 385, 386, 387, 388, 389, 390, 519, 520, 521, 522, 523, 524, 525, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [10, 11, 12, 13, 14, 15, 16, 81, 82, 83, 84, 85, 86, 87, 170, 171, 172, 173, 174, 175, 176, 253, 254, 255, 256, 257, 258, 259, 273, 274, 275, 276, 277, 278, 279, 391, 392, 393, 394, 395, 396, 397, 526, 527, 528, 529, 530, 531, 532, 735, 736, 737, 738, 739, 740, 741]\n",
      "a :  [7, 8, 9, 10, 11, 12, 13, 78, 79, 80, 81, 82, 83, 84, 167, 168, 169, 170, 171, 172, 173, 250, 251, 252, 253, 254, 255, 256, 270, 271, 272, 273, 274, 275, 276, 388, 389, 390, 391, 392, 393, 394, 523, 524, 525, 526, 527, 528, 529, 732, 733, 734, 735, 736, 737, 738]\n",
      "lenr :  23\n",
      "i :  20\n",
      "b :  [40, 41, 42, 43, 44, 125, 126, 127, 128, 129, 286, 287, 288, 289, 290, 435, 436, 437, 438, 439, 547, 548, 549, 550, 551, 563, 564, 565, 566, 567, 571, 572, 573, 574, 575, 664, 665, 666, 667, 668, 680, 681, 682, 683, 684, 696, 697, 698, 699, 700]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [40, 41, 42, 43, 44, 125, 126, 127, 128, 129, 286, 287, 288, 289, 290, 435, 436, 437, 438, 439, 547, 548, 549, 550, 551, 563, 564, 565, 566, 567, 571, 572, 573, 574, 575, 664, 665, 666, 667, 668, 680, 681, 682, 683, 684, 696, 697, 698, 699, 700]\n",
      "lenr :  22\n",
      "i :  19\n",
      "b :  [7, 8, 9, 10, 11, 12, 13, 78, 79, 80, 81, 82, 83, 84, 167, 168, 169, 170, 171, 172, 173, 250, 251, 252, 253, 254, 255, 256, 270, 271, 272, 273, 274, 275, 276, 388, 389, 390, 391, 392, 393, 394, 523, 524, 525, 526, 527, 528, 529, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "yes\n",
      "rtest :  [7, 8, 9, 10, 11, 12, 13, 78, 79, 80, 81, 82, 83, 84, 167, 168, 169, 170, 171, 172, 173, 250, 251, 252, 253, 254, 255, 256, 270, 271, 272, 273, 274, 275, 276, 388, 389, 390, 391, 392, 393, 394, 523, 524, 525, 526, 527, 528, 529, 732, 733, 734, 735, 736, 737, 738]\n",
      "lenr :  21\n",
      "i :  18\n",
      "b :  [10, 11, 12, 13, 14, 15, 16, 81, 82, 83, 84, 85, 86, 87, 170, 171, 172, 173, 174, 175, 176, 253, 254, 255, 256, 257, 258, 259, 273, 274, 275, 276, 277, 278, 279, 391, 392, 393, 394, 395, 396, 397, 526, 527, 528, 529, 530, 531, 532, 735, 736, 737, 738, 739, 740, 741]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 78, 79, 80, 162, 163, 164, 165, 166, 167, 168, 169, 245, 246, 247, 248, 249, 250, 251, 252, 265, 266, 267, 268, 269, 270, 271, 272, 383, 384, 385, 386, 387, 388, 389, 390, 518, 519, 520, 521, 522, 523, 524, 525, 727, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [39, 40, 41, 42, 43, 44, 124, 125, 126, 127, 128, 129, 285, 286, 287, 288, 289, 290, 434, 435, 436, 437, 438, 439, 546, 547, 548, 549, 550, 551, 562, 563, 564, 565, 566, 567, 570, 571, 572, 573, 574, 575, 663, 664, 665, 666, 667, 668, 679, 680, 681, 682, 683, 684, 695, 696, 697, 698, 699, 700]\n",
      "a :  [43, 44, 45, 46, 128, 129, 130, 131, 212, 213, 214, 215, 281, 282, 283, 284, 289, 290, 291, 292, 438, 439, 440, 441, 479, 480, 481, 482, 534, 535, 536, 537, 550, 551, 552, 553, 566, 567, 568, 569, 574, 575, 576, 577, 667, 668, 669, 670, 683, 684, 685, 686, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 44, 45, 125, 126, 127, 128, 129, 130, 286, 287, 288, 289, 290, 291, 435, 436, 437, 438, 439, 440, 547, 548, 549, 550, 551, 552, 563, 564, 565, 566, 567, 568, 571, 572, 573, 574, 575, 576, 664, 665, 666, 667, 668, 669, 680, 681, 682, 683, 684, 685, 696, 697, 698, 699, 700, 701]\n",
      "a :  [41, 42, 43, 44, 45, 126, 127, 128, 129, 130, 287, 288, 289, 290, 291, 436, 437, 438, 439, 440, 477, 478, 479, 480, 481, 548, 549, 550, 551, 552, 564, 565, 566, 567, 568, 572, 573, 574, 575, 576, 665, 666, 667, 668, 669, 681, 682, 683, 684, 685, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 127, 128, 129, 130, 280, 281, 282, 283, 288, 289, 290, 291, 437, 438, 439, 440, 478, 479, 480, 481, 533, 534, 535, 536, 549, 550, 551, 552, 565, 566, 567, 568, 573, 574, 575, 576, 666, 667, 668, 669, 682, 683, 684, 685, 698, 699, 700, 701]\n",
      "lenr :  21\n",
      "i :  17\n",
      "b :  [3, 4, 5, 6, 7, 8, 9, 74, 75, 76, 77, 78, 79, 80, 163, 164, 165, 166, 167, 168, 169, 246, 247, 248, 249, 250, 251, 252, 266, 267, 268, 269, 270, 271, 272, 384, 385, 386, 387, 388, 389, 390, 519, 520, 521, 522, 523, 524, 525, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "yes\n",
      "rtest :  [3, 4, 5, 6, 7, 8, 9, 74, 75, 76, 77, 78, 79, 80, 163, 164, 165, 166, 167, 168, 169, 246, 247, 248, 249, 250, 251, 252, 266, 267, 268, 269, 270, 271, 272, 384, 385, 386, 387, 388, 389, 390, 519, 520, 521, 522, 523, 524, 525, 728, 729, 730, 731, 732, 733, 734]\n",
      "lenr :  20\n",
      "i :  16\n",
      "b :  [42, 43, 44, 45, 127, 128, 129, 130, 280, 281, 282, 283, 288, 289, 290, 291, 437, 438, 439, 440, 478, 479, 480, 481, 533, 534, 535, 536, 549, 550, 551, 552, 565, 566, 567, 568, 573, 574, 575, 576, 666, 667, 668, 669, 682, 683, 684, 685, 698, 699, 700, 701]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [42, 43, 44, 45, 127, 128, 129, 130, 280, 281, 282, 283, 288, 289, 290, 291, 437, 438, 439, 440, 478, 479, 480, 481, 533, 534, 535, 536, 549, 550, 551, 552, 565, 566, 567, 568, 573, 574, 575, 576, 666, 667, 668, 669, 682, 683, 684, 685, 698, 699, 700, 701]\n",
      "lenr :  19\n",
      "i :  15\n",
      "b :  [41, 42, 43, 44, 45, 126, 127, 128, 129, 130, 287, 288, 289, 290, 291, 436, 437, 438, 439, 440, 477, 478, 479, 480, 481, 548, 549, 550, 551, 552, 564, 565, 566, 567, 568, 572, 573, 574, 575, 576, 665, 666, 667, 668, 669, 681, 682, 683, 684, 685, 697, 698, 699, 700, 701]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [41, 42, 43, 44, 45, 126, 127, 128, 129, 130, 287, 288, 289, 290, 291, 436, 437, 438, 439, 440, 477, 478, 479, 480, 481, 548, 549, 550, 551, 552, 564, 565, 566, 567, 568, 572, 573, 574, 575, 576, 665, 666, 667, 668, 669, 681, 682, 683, 684, 685, 697, 698, 699, 700, 701]\n",
      "lenr :  18\n",
      "i :  14\n",
      "b :  [40, 41, 42, 43, 44, 45, 125, 126, 127, 128, 129, 130, 286, 287, 288, 289, 290, 291, 435, 436, 437, 438, 439, 440, 547, 548, 549, 550, 551, 552, 563, 564, 565, 566, 567, 568, 571, 572, 573, 574, 575, 576, 664, 665, 666, 667, 668, 669, 680, 681, 682, 683, 684, 685, 696, 697, 698, 699, 700, 701]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [40, 41, 42, 43, 44, 45, 125, 126, 127, 128, 129, 130, 286, 287, 288, 289, 290, 291, 435, 436, 437, 438, 439, 440, 547, 548, 549, 550, 551, 552, 563, 564, 565, 566, 567, 568, 571, 572, 573, 574, 575, 576, 664, 665, 666, 667, 668, 669, 680, 681, 682, 683, 684, 685, 696, 697, 698, 699, 700, 701]\n",
      "lenr :  17\n",
      "i :  13\n",
      "b :  [43, 44, 45, 46, 128, 129, 130, 131, 212, 213, 214, 215, 281, 282, 283, 284, 289, 290, 291, 292, 438, 439, 440, 441, 479, 480, 481, 482, 534, 535, 536, 537, 550, 551, 552, 553, 566, 567, 568, 569, 574, 575, 576, 577, 667, 668, 669, 670, 683, 684, 685, 686, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 78, 79, 80, 162, 163, 164, 165, 166, 167, 168, 169, 245, 246, 247, 248, 249, 250, 251, 252, 265, 266, 267, 268, 269, 270, 271, 272, 383, 384, 385, 386, 387, 388, 389, 390, 518, 519, 520, 521, 522, 523, 524, 525, 727, 728, 729, 730, 731, 732, 733, 734]\n",
      "lenr :  17\n",
      "i :  12\n",
      "b :  [39, 40, 41, 42, 43, 44, 124, 125, 126, 127, 128, 129, 285, 286, 287, 288, 289, 290, 434, 435, 436, 437, 438, 439, 546, 547, 548, 549, 550, 551, 562, 563, 564, 565, 566, 567, 570, 571, 572, 573, 574, 575, 663, 664, 665, 666, 667, 668, 679, 680, 681, 682, 683, 684, 695, 696, 697, 698, 699, 700]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [39, 40, 41, 42, 43, 44, 124, 125, 126, 127, 128, 129, 285, 286, 287, 288, 289, 290, 434, 435, 436, 437, 438, 439, 546, 547, 548, 549, 550, 551, 562, 563, 564, 565, 566, 567, 570, 571, 572, 573, 574, 575, 663, 664, 665, 666, 667, 668, 679, 680, 681, 682, 683, 684, 695, 696, 697, 698, 699, 700]\n",
      "lenr :  16\n",
      "i :  11\n",
      "b :  [2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 78, 79, 80, 162, 163, 164, 165, 166, 167, 168, 169, 245, 246, 247, 248, 249, 250, 251, 252, 265, 266, 267, 268, 269, 270, 271, 272, 383, 384, 385, 386, 387, 388, 389, 390, 518, 519, 520, 521, 522, 523, 524, 525, 727, 728, 729, 730, 731, 732, 733, 734]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "lenr :  16\n",
      "i :  10\n",
      "b :  [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 81, 82, 83, 84, 166, 167, 168, 169, 170, 171, 172, 173, 249, 250, 251, 252, 253, 254, 255, 256, 269, 270, 271, 272, 273, 274, 275, 276, 387, 388, 389, 390, 391, 392, 393, 394, 522, 523, 524, 525, 526, 527, 528, 529, 731, 732, 733, 734, 735, 736, 737, 738]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "lenr :  16\n",
      "i :  9\n",
      "b :  [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, 79, 80, 81, 163, 164, 165, 166, 167, 168, 169, 170, 246, 247, 248, 249, 250, 251, 252, 253, 266, 267, 268, 269, 270, 271, 272, 273, 384, 385, 386, 387, 388, 389, 390, 391, 519, 520, 521, 522, 523, 524, 525, 526, 728, 729, 730, 731, 732, 733, 734, 735]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "lenr :  16\n",
      "i :  8\n",
      "b :  [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79, 80, 81, 82, 164, 165, 166, 167, 168, 169, 170, 171, 247, 248, 249, 250, 251, 252, 253, 254, 267, 268, 269, 270, 271, 272, 273, 274, 385, 386, 387, 388, 389, 390, 391, 392, 520, 521, 522, 523, 524, 525, 526, 527, 729, 730, 731, 732, 733, 734, 735, 736]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "lenr :  16\n",
      "i :  7\n",
      "b :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "yes\n",
      "rtest :  [39, 40, 41, 42, 124, 125, 126, 127, 285, 286, 287, 288, 434, 435, 436, 437, 501, 502, 503, 504, 538, 539, 540, 541, 546, 547, 548, 549, 554, 555, 556, 557, 562, 563, 564, 565, 570, 571, 572, 573, 663, 664, 665, 666, 671, 672, 673, 674, 679, 680, 681, 682, 687, 688, 689, 690, 695, 696, 697, 698]\n",
      "lenr :  15\n",
      "i :  6\n",
      "b :  [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 130, 131, 287, 288, 289, 290, 291, 292, 436, 437, 438, 439, 440, 441, 477, 478, 479, 480, 481, 482, 548, 549, 550, 551, 552, 553, 564, 565, 566, 567, 568, 569, 572, 573, 574, 575, 576, 577, 665, 666, 667, 668, 669, 670, 681, 682, 683, 684, 685, 686, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "lenr :  15\n",
      "i :  5\n",
      "b :  [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, 280, 281, 282, 283, 284, 288, 289, 290, 291, 292, 437, 438, 439, 440, 441, 478, 479, 480, 481, 482, 533, 534, 535, 536, 537, 549, 550, 551, 552, 553, 565, 566, 567, 568, 569, 573, 574, 575, 576, 577, 666, 667, 668, 669, 670, 682, 683, 684, 685, 686, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "lenr :  15\n",
      "i :  4\n",
      "b :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [39, 40, 41, 42, 43, 44, 45, 124, 125, 126, 127, 128, 129, 130, 285, 286, 287, 288, 289, 290, 291, 434, 435, 436, 437, 438, 439, 440, 546, 547, 548, 549, 550, 551, 552, 562, 563, 564, 565, 566, 567, 568, 570, 571, 572, 573, 574, 575, 576, 663, 664, 665, 666, 667, 668, 669, 679, 680, 681, 682, 683, 684, 685, 695, 696, 697, 698, 699, 700, 701]\n",
      "lenr :  14\n",
      "i :  3\n",
      "b :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n",
      "a :  [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126, 127, 128, 129, 130, 131, 285, 286, 287, 288, 289, 290, 291, 292, 434, 435, 436, 437, 438, 439, 440, 441, 546, 547, 548, 549, 550, 551, 552, 553, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 663, 664, 665, 666, 667, 668, 669, 670, 679, 680, 681, 682, 683, 684, 685, 686, 695, 696, 697, 698, 699, 700, 701, 702]\n",
      "yes\n",
      "rtest :  [40, 41, 42, 43, 44, 45, 46, 125, 126, 127, 128, 129, 130, 131, 286, 287, 288, 289, 290, 291, 292, 435, 436, 437, 438, 439, 440, 441, 547, 548, 549, 550, 551, 552, 553, 563, 564, 565, 566, 567, 568, 569, 571, 572, 573, 574, 575, 576, 577, 664, 665, 666, 667, 668, 669, 670, 680, 681, 682, 683, 684, 685, 686, 696, 697, 698, 699, 700, 701, 702]\n",
      "lenr :  13\n",
      "i :  2\n",
      "b :  [40, 41, 42, 43, 125, 126, 127, 128, 216, 217, 218, 219, 286, 287, 288, 289, 435, 436, 437, 438, 502, 503, 504, 505, 539, 540, 541, 542, 547, 548, 549, 550, 555, 556, 557, 558, 563, 564, 565, 566, 571, 572, 573, 574, 664, 665, 666, 667, 672, 673, 674, 675, 680, 681, 682, 683, 688, 689, 690, 691, 696, 697, 698, 699, 720, 721, 722, 723]\n",
      "a :  [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, 285, 286, 287, 288, 289, 434, 435, 436, 437, 438, 501, 502, 503, 504, 505, 538, 539, 540, 541, 542, 546, 547, 548, 549, 550, 554, 555, 556, 557, 558, 562, 563, 564, 565, 566, 570, 571, 572, 573, 574, 663, 664, 665, 666, 667, 671, 672, 673, 674, 675, 679, 680, 681, 682, 683, 687, 688, 689, 690, 691, 695, 696, 697, 698, 699]\n"
     ]
    }
   ],
   "source": [
    "tuh = SAR_Contour(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        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>card</th>\n",
       "      <th>seg</th>\n",
       "      <th>segcount</th>\n",
       "      <th>segind</th>\n",
       "      <th>cov</th>\n",
       "      <th>invind</th>\n",
       "      <th>inds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>[2.0, 2.0, 2.0, 2.0, 1.0, 0.0]</td>\n",
       "      <td>15</td>\n",
       "      <td>[39, 124, 285, 434, 501, 538, 546, 554, 562, 5...</td>\n",
       "      <td>90</td>\n",
       "      <td>[]</td>\n",
       "      <td>[39, 40, 41, 42, 43, 124, 125, 126, 127, 128, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9</td>\n",
       "      <td>[2.0, 2.0, 2.0, 2.0, 1.0, 0.0, 4.0, 3.0, 2.0]</td>\n",
       "      <td>10</td>\n",
       "      <td>[39, 124, 285, 434, 546, 562, 570, 663, 679, 695]</td>\n",
       "      <td>90</td>\n",
       "      <td>[]</td>\n",
       "      <td>[39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>[2.0, 2.0, 2.0, 1.0, 0.0]</td>\n",
       "      <td>17</td>\n",
       "      <td>[40, 125, 216, 286, 435, 502, 539, 547, 555, 5...</td>\n",
       "      <td>85</td>\n",
       "      <td>[]</td>\n",
       "      <td>[40, 41, 42, 43, 125, 126, 127, 128, 216, 217,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>[2.0, 1.0, 0.0, 4.0, 3.0, 2.0]</td>\n",
       "      <td>13</td>\n",
       "      <td>[42, 127, 280, 288, 437, 478, 533, 549, 565, 5...</td>\n",
       "      <td>78</td>\n",
       "      <td>[]</td>\n",
       "      <td>[42, 43, 44, 45, 46, 127, 128, 129, 130, 131, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>[2.0, 2.0, 1.0, 0.0, 4.0, 3.0, 2.0]</td>\n",
       "      <td>11</td>\n",
       "      <td>[41, 126, 287, 436, 477, 548, 564, 572, 665, 6...</td>\n",
       "      <td>77</td>\n",
       "      <td>[]</td>\n",
       "      <td>[41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9</td>\n",
       "      <td>[1.0, 3.0, 1.0, 2.0, 4.0, 0.0, 2.0, 1.0, 2.0]</td>\n",
       "      <td>8</td>\n",
       "      <td>[4, 75, 164, 247, 267, 385, 520, 729]</td>\n",
       "      <td>72</td>\n",
       "      <td>[]</td>\n",
       "      <td>[4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>9</td>\n",
       "      <td>[0.0, 1.0, 3.0, 1.0, 2.0, 4.0, 0.0, 2.0, 1.0]</td>\n",
       "      <td>8</td>\n",
       "      <td>[3, 74, 163, 246, 266, 384, 519, 728]</td>\n",
       "      <td>72</td>\n",
       "      <td>[]</td>\n",
       "      <td>[3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9</td>\n",
       "      <td>[1.0, 2.0, 4.0, 0.0, 2.0, 1.0, 2.0, 4.0, 0.0]</td>\n",
       "      <td>8</td>\n",
       "      <td>[6, 77, 166, 249, 269, 387, 522, 731]</td>\n",
       "      <td>72</td>\n",
       "      <td>[]</td>\n",
       "      <td>[6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>[3.0, 0.0, 1.0, 3.0, 1.0, 2.0, 4.0, 0.0, 2.0]</td>\n",
       "      <td>8</td>\n",
       "      <td>[2, 73, 162, 245, 265, 383, 518, 727]</td>\n",
       "      <td>72</td>\n",
       "      <td>[]</td>\n",
       "      <td>[2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5</td>\n",
       "      <td>[1.0, 0.0, 4.0, 3.0, 2.0]</td>\n",
       "      <td>14</td>\n",
       "      <td>[43, 128, 212, 281, 289, 438, 479, 534, 550, 5...</td>\n",
       "      <td>70</td>\n",
       "      <td>[]</td>\n",
       "      <td>[43, 44, 45, 46, 128, 129, 130, 131, 212, 213,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8</td>\n",
       "      <td>[2.0, 1.0, 2.0, 4.0, 0.0, 1.0, 4.0, 2.0]</td>\n",
       "      <td>8</td>\n",
       "      <td>[10, 81, 170, 253, 273, 391, 526, 735]</td>\n",
       "      <td>64</td>\n",
       "      <td>[]</td>\n",
       "      <td>[10, 11, 12, 13, 14, 15, 16, 81, 82, 83, 84, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5</td>\n",
       "      <td>[3.0, 2.0, 3.0, 0.0, 1.0]</td>\n",
       "      <td>12</td>\n",
       "      <td>[20, 25, 30, 57, 180, 243, 263, 381, 422, 427,...</td>\n",
       "      <td>60</td>\n",
       "      <td>[]</td>\n",
       "      <td>[20, 21, 22, 23, 25, 26, 27, 28, 30, 31, 32, 3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6</td>\n",
       "      <td>[3.0, 2.0, 3.0, 0.0, 1.0, 3.0]</td>\n",
       "      <td>9</td>\n",
       "      <td>[20, 25, 180, 243, 263, 381, 422, 616, 621]</td>\n",
       "      <td>54</td>\n",
       "      <td>[]</td>\n",
       "      <td>[20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 180, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   card                                            seg segcount  \\\n",
       "0     6                 [2.0, 2.0, 2.0, 2.0, 1.0, 0.0]       15   \n",
       "1     9  [2.0, 2.0, 2.0, 2.0, 1.0, 0.0, 4.0, 3.0, 2.0]       10   \n",
       "2     5                      [2.0, 2.0, 2.0, 1.0, 0.0]       17   \n",
       "3     6                 [2.0, 1.0, 0.0, 4.0, 3.0, 2.0]       13   \n",
       "4     7            [2.0, 2.0, 1.0, 0.0, 4.0, 3.0, 2.0]       11   \n",
       "5     9  [1.0, 3.0, 1.0, 2.0, 4.0, 0.0, 2.0, 1.0, 2.0]        8   \n",
       "6     9  [0.0, 1.0, 3.0, 1.0, 2.0, 4.0, 0.0, 2.0, 1.0]        8   \n",
       "7     9  [1.0, 2.0, 4.0, 0.0, 2.0, 1.0, 2.0, 4.0, 0.0]        8   \n",
       "8     9  [3.0, 0.0, 1.0, 3.0, 1.0, 2.0, 4.0, 0.0, 2.0]        8   \n",
       "9     5                      [1.0, 0.0, 4.0, 3.0, 2.0]       14   \n",
       "10    8       [2.0, 1.0, 2.0, 4.0, 0.0, 1.0, 4.0, 2.0]        8   \n",
       "11    5                      [3.0, 2.0, 3.0, 0.0, 1.0]       12   \n",
       "12    6                 [3.0, 2.0, 3.0, 0.0, 1.0, 3.0]        9   \n",
       "\n",
       "                                               segind cov invind  \\\n",
       "0   [39, 124, 285, 434, 501, 538, 546, 554, 562, 5...  90     []   \n",
       "1   [39, 124, 285, 434, 546, 562, 570, 663, 679, 695]  90     []   \n",
       "2   [40, 125, 216, 286, 435, 502, 539, 547, 555, 5...  85     []   \n",
       "3   [42, 127, 280, 288, 437, 478, 533, 549, 565, 5...  78     []   \n",
       "4   [41, 126, 287, 436, 477, 548, 564, 572, 665, 6...  77     []   \n",
       "5               [4, 75, 164, 247, 267, 385, 520, 729]  72     []   \n",
       "6               [3, 74, 163, 246, 266, 384, 519, 728]  72     []   \n",
       "7               [6, 77, 166, 249, 269, 387, 522, 731]  72     []   \n",
       "8               [2, 73, 162, 245, 265, 383, 518, 727]  72     []   \n",
       "9   [43, 128, 212, 281, 289, 438, 479, 534, 550, 5...  70     []   \n",
       "10             [10, 81, 170, 253, 273, 391, 526, 735]  64     []   \n",
       "11  [20, 25, 30, 57, 180, 243, 263, 381, 422, 427,...  60     []   \n",
       "12        [20, 25, 180, 243, 263, 381, 422, 616, 621]  54     []   \n",
       "\n",
       "                                                 inds  \n",
       "0   [39, 40, 41, 42, 43, 124, 125, 126, 127, 128, ...  \n",
       "1   [39, 40, 41, 42, 43, 44, 45, 46, 124, 125, 126...  \n",
       "2   [40, 41, 42, 43, 125, 126, 127, 128, 216, 217,...  \n",
       "3   [42, 43, 44, 45, 46, 127, 128, 129, 130, 131, ...  \n",
       "4   [41, 42, 43, 44, 45, 46, 126, 127, 128, 129, 1...  \n",
       "5   [4, 5, 6, 7, 8, 9, 10, 11, 75, 76, 77, 78, 79,...  \n",
       "6   [3, 4, 5, 6, 7, 8, 9, 10, 74, 75, 76, 77, 78, ...  \n",
       "7   [6, 7, 8, 9, 10, 11, 12, 13, 77, 78, 79, 80, 8...  \n",
       "8   [2, 3, 4, 5, 6, 7, 8, 9, 73, 74, 75, 76, 77, 7...  \n",
       "9   [43, 44, 45, 46, 128, 129, 130, 131, 212, 213,...  \n",
       "10  [10, 11, 12, 13, 14, 15, 16, 81, 82, 83, 84, 8...  \n",
       "11  [20, 21, 22, 23, 25, 26, 27, 28, 30, 31, 32, 3...  \n",
       "12  [20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 180, ...  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tuh[\"r\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patheffects as pe\n",
    "\n",
    "def plot(nmat,segind,segcard):\n",
    "    \"\"\"\n",
    "    plot(nmat,segind,segcard)\n",
    "    ######################################################\n",
    "    \n",
    "    Displays Arc Plot Diagram. This consists of a series of arcs overlayed on MIDI data presented horizontally.\n",
    "    \n",
    "    Parameters:\n",
    "        nmat (pandas.df): A Note Matrix that contains pitch, timing, and velocity information for a series of notes.\n",
    "        nmatRCE (pandas.df): A version of the Note Matrix which has each element reduced to a binary value.\n",
    "        onsets (list): A list of values that describes when each note would begin in the piece.\n",
    "        offsets (list): A list of values that describes when each note would end in the piece.\n",
    "        segind (list): A list of lists of values that describe the occurences of each pattern found in the piece.\n",
    "        segcard (list): A list that describes how many notes should be in each pattern.\n",
    "    \"\"\"\n",
    "    \n",
    "    onsets = nmat['Time']\n",
    "    offsets = onsets + nmat['Duration']\n",
    "    pitch = nmat['Pitch']\n",
    "    \n",
    "    _midiplot(onsets,offsets,pitch)\n",
    "\n",
    "    colornum=1\n",
    "    #cmap1=jet(len(segcard))\n",
    "    #cmap1 = plt.cm.get_cmap('jet')\n",
    "    pitchmax=nmat['Pitch'].max()\n",
    "    pitchmean=nmat['Pitch'].mean()\n",
    "    pitchmean=(pitchmax+pitchmean)/2\n",
    "\n",
    "    #segind=[1,72,161,244,264,382,517,726]\n",
    "    framelabels = [\"Onset in Beats\", \"Durations in Beats\", \"Pitch (C4=60)\"]\n",
    "    #segcard=20\n",
    "    rads = [1]\n",
    "    # for i in range(0,len(segind)-1):\n",
    "    #try:\n",
    "    temp=onsets[segind]\n",
    "    temp=temp.sort_values()\n",
    "    #SortInd = temp.head() \n",
    "    SortInd=list(temp.index.values) \n",
    "    #r = r.sort_values(by=[\"cov\"], ascending=False).reset_index(drop=True)\n",
    "    #print(\"onsets : \", temp)\n",
    "    #print(\"onsets : \", SortInd)\n",
    "    ind=SortInd\n",
    "    segind=ind\n",
    "    #print(\"onsets : \", ind)\n",
    "    #print(\"segind : \", segind)\n",
    "    #finally:\n",
    "    #    pass\n",
    "    #     try\n",
    "    #         try\n",
    "    #             simind=r(i).simind;\n",
    "    #         catch\n",
    "    #             simind=r(i).invind;\n",
    "    #         end\n",
    "    #     catch\n",
    "    #         simind=[];\n",
    "    #     end\n",
    "    #       ind\n",
    "    origxstart = onsets[segind[0]]\n",
    "    #print(\"origxstart: \", origxstart)\n",
    "    card=segcard\n",
    "    #print(\"card : \", card)\n",
    "    origxend=offsets[segind[0]+card-1]\n",
    "    origwidth=origxend - origxstart\n",
    "    origx=(origwidth) / 2 + origxstart\n",
    "    linewidthstart= origwidth #need to normalize to pixel length\n",
    "    print(\"linewidthstart : \", linewidthstart)\n",
    "    origpitchmin=min(pitch[segind[0]:(segind[0] + card - 1)]) - 2\n",
    "    colornoalpha=[colornum]\n",
    "    colornum=colornum + 1\n",
    "    \n",
    "    for j in range(1,len(ind)):\n",
    "        #noteInd = ind[j]\n",
    "        #compxstart=nmat.iloc[noteInd,0]\n",
    "        compxstart = onsets[ind[j]]\n",
    "        print(\"start : \", compxstart)\n",
    "        #compxend=nmat.iloc[noteInd + (card - 1),0] + nmat.iloc[noteInd + (card - 1),1]\n",
    "        compxend = offsets[ind[j]+card-1]\n",
    "        print(\"end : \", compxend)\n",
    "        compwidth=compxend - compxstart\n",
    "        compx=(compwidth) / 2 + compxstart\n",
    "        linewidthend= compwidth #need to normalize to pixel length\n",
    "        print(\"linewidthend : \", linewidthend)\n",
    "        comppitchmin=min(pitch[ind[j]:ind[j] + (card - 1)]) - 2\n",
    "        rad=(compx - origx) / 2\n",
    "        rads.append(rad)\n",
    "        x=rad + origx\n",
    "        nsegments=100\n",
    "        linewidth=np.dot(card,3)\n",
    "        \n",
    "        if segcard:\n",
    "            colornoalpha=[0,0,1]\n",
    "            \n",
    "        coloralpha=colornoalpha.append(0.5)\n",
    "        _arc(x=x,y=pitchmean,r=rad,linewidthstart=linewidthstart,linewidthend=linewidthend)\n",
    "\n",
    "def _arc(x,y,r,nsegments=100,coloralpha='r',linewidthstart=5,linewidthend=10):\n",
    "    \"\"\"\n",
    "    _arc(x,y,r,nsegments=100,coloralpha='r',linewidthstart=5,linewidthend=10)\n",
    "    #########################################################################\n",
    "    \n",
    "    Draws an arc from one point to another.\n",
    "    \n",
    "    Parameters:\n",
    "        x (float): The time value the arc will start at.\n",
    "        y (float): The pitch value the arc will start at.\n",
    "        r (float): The radius of the arc.\n",
    "        nsegments (int): The number of line segments that make up the arc.\n",
    "        coloralpha (str): The color of the line segments.\n",
    "        linewidthstart (int): the width of each line segment at the beginning.\n",
    "        linewidthend (int): the width of each line segment at the end.\n",
    "    \"\"\"\n",
    "    th=np.arange(0,np.pi,np.pi/200)\n",
    "    xunit=r * np.cos(th) + x;\n",
    "    yunit=r * np.sin(th) + y;\n",
    "    linewidthincrement=(linewidthstart-linewidthend)/len(xunit);\n",
    "\n",
    "    plt.figure(1)\n",
    "    for i in range(2,len(th)):\n",
    "        plt.plot([xunit[i-1],xunit[i]], [yunit[i-1],yunit[i]],'b',linewidth = 10*(linewidthend+i*linewidthincrement), zorder=0, alpha=0.05)\n",
    "        \n",
    "def _midiplot(onsets,offsets,pitch):\n",
    "    plt.figure(figsize=(20,10))\n",
    "    \n",
    "    for i in range(0,len(onsets)):\n",
    "        #try:\n",
    "            #print(\"onsets : \", i)\n",
    "        plt.plot([onsets[i],offsets[i]], [pitch[i],pitch[i]], 'k', lw=2, path_effects=[pe.Stroke(linewidth=2, foreground='k'), pe.Normal()], zorder=5)\n",
    "        #except:\n",
    "          #  print(\"An exception occurred\")\n",
    "    plt.xlabel(\"Beats\")\n",
    "    plt.ylabel(\"Pitch (C4=60)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "linewidthstart :  3.7354166666666666\n",
      "start :  9.0\n",
      "end :  12.735416666666667\n",
      "linewidthend :  3.7354166666666675\n",
      "start :  25.0\n",
      "end :  28.735416666666666\n",
      "linewidthend :  3.7354166666666657\n",
      "start :  41.0\n",
      "end :  44.735416666666666\n",
      "linewidthend :  3.7354166666666657\n",
      "start :  57.0\n",
      "end :  60.735416666666666\n",
      "linewidthend :  3.7354166666666657\n",
      "start :  77.0\n",
      "end :  80.73541666666667\n",
      "linewidthend :  3.7354166666666657\n",
      "start :  103.0\n",
      "end :  106.73541666666667\n",
      "linewidthend :  3.7354166666666657\n",
      "start :  115.0\n",
      "end :  118.73541666666667\n",
      "linewidthend :  3.7354166666666657\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "i=8\n",
    "plot(test,tuh[\"r\"]['segind'].iloc[i],tuh[\"r\"]['card'].iloc[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello\n"
     ]
    }
   ],
   "source": [
    "from tkinter import *\n",
    "\n",
    "class Window(Frame):\n",
    "\n",
    "    def __init__(self, master=None):\n",
    "        # parameters that you want to send through the Frame class. \n",
    "        Frame.__init__(self, master)   \n",
    "\n",
    "        #reference to the master widget, which is the tk window                 \n",
    "        self.master = master\n",
    "\n",
    "        #with that, we want to then run init_window, which doesn't yet exist\n",
    "        self.init_window()\n",
    "\n",
    "        \n",
    "            #Creation of init_window\n",
    "    def init_window(self):\n",
    "\n",
    "        # changing the title of our master widget      \n",
    "        self.master.title(\"GUI\")\n",
    "\n",
    "        # allowing the widget to take the full space of the root window\n",
    "        self.pack(fill=BOTH, expand=1)\n",
    "\n",
    "        # creating a button instance\n",
    "        quitButton = Button(self, text=\"Quit\", command=self.client_exit)\n",
    "\n",
    "        # placing the button on my window\n",
    "        quitButton.place(x=0, y=0)\n",
    "\n",
    " \n",
    "    def client_exit(self):\n",
    "        print(\"hello\")\n",
    "        self.destroy()\n",
    "\n",
    "# root window created. Here, that would be the only window, but\n",
    "# you can later have windows within windows.\n",
    "\n",
    "root = Tk()\n",
    "\n",
    "#size of the window\n",
    "root.geometry(\"400x300\")\n",
    "\n",
    "#creation of an instance\n",
    "app = Window(root)\n",
    "\n",
    "#mainloop \n",
    "root.mainloop()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}