praca-magisterska/docs/images/plots.ipynb

{
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 "nbformat_minor": 2,
 "metadata": {
  "language_info": {
   "name": "python",
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "version": "3.8.2-final"
  },
  "orig_nbformat": 2,
  "file_extension": ".py",
  "mimetype": "text/x-python",
  "name": "python",
  "npconvert_exporter": "python",
  "pygments_lexer": "ipython3",
  "version": 3,
  "kernelspec": {
   "name": "python38264bit90963b6dfcff4977b23d3abddad7c054",
   "display_name": "Python 3.8.2 64-bit"
  }
 },
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import music21\n",
    "from music21.midi import MidiFile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "mf = MidiFile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "filepath = '/home/altarin/praca-magisterska/docs/images/seq2seq_generated_midi_7.mid'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mido"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "<meta message set_tempo tempo=500000 time=0>\n<meta message time_signature numerator=4 denominator=4 clocks_per_click=24 notated_32nd_notes_per_beat=8 time=0>\n<meta message end_of_track time=1>\n<meta message track_name name='Guitar' time=0>\nprogram_change channel=0 program=30 time=0\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=60 velocity=100 time=0\nnote_on channel=0 note=48 velocity=0 time=220\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=55 velocity=100 time=0\nnote_on channel=0 note=60 velocity=0 time=0\nnote_on channel=0 note=60 velocity=100 time=0\nnote_on channel=0 note=48 velocity=0 time=220\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=55 velocity=0 time=0\nnote_on channel=0 note=55 velocity=100 time=0\nnote_on channel=0 note=60 velocity=0 time=0\nnote_on channel=0 note=60 velocity=100 time=0\nnote_on channel=0 note=48 velocity=0 time=440\nnote_on channel=0 note=55 velocity=0 time=0\nnote_on channel=0 note=60 velocity=0 time=0\nnote_on channel=0 note=48 velocity=0 time=110\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=45 velocity=100 time=770\nnote_on channel=0 note=50 velocity=100 time=0\nnote_on channel=0 note=57 velocity=100 time=0\nnote_on channel=0 note=45 velocity=0 time=220\nnote_on channel=0 note=46 velocity=100 time=0\nnote_on channel=0 note=50 velocity=0 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=57 velocity=0 time=0\nnote_on channel=0 note=58 velocity=100 time=0\nnote_on channel=0 note=46 velocity=0 time=220\nnote_on channel=0 note=46 velocity=100 time=0\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=58 velocity=0 time=0\nnote_on channel=0 note=58 velocity=100 time=0\nnote_on channel=0 note=46 velocity=0 time=220\nnote_on channel=0 note=46 velocity=100 time=0\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=58 velocity=0 time=0\nnote_on channel=0 note=58 velocity=100 time=0\nnote_on channel=0 note=46 velocity=0 time=440\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=58 velocity=0 time=0\nnote_on channel=0 note=60 velocity=100 time=0\nnote_on channel=0 note=48 velocity=0 time=440\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=60 velocity=0 time=0\nnote_on channel=0 note=60 velocity=100 time=0\nnote_on channel=0 note=48 velocity=0 time=220\nnote_on channel=0 note=48 velocity=100 time=0\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=60 velocity=0 time=0\nnote_on channel=0 note=48 velocity=0 time=220\nnote_on channel=0 note=51 velocity=100 time=0\nnote_on channel=0 note=48 velocity=100 time=220\nnote_on channel=0 note=51 velocity=0 time=0\nnote_on channel=0 note=48 velocity=0 time=220\nnote_on channel=0 note=60 velocity=100 time=0\nnote_on channel=0 note=51 velocity=100 time=220\nnote_on channel=0 note=60 velocity=0 time=0\nnote_on channel=0 note=51 velocity=0 time=220\nnote_on channel=0 note=51 velocity=100 time=0\nnote_on channel=0 note=51 velocity=0 time=220\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=46 velocity=100 time=440\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=58 velocity=100 time=0\nnote_on channel=0 note=46 velocity=0 time=990\nnote_on channel=0 note=53 velocity=0 time=0\nnote_on channel=0 note=58 velocity=0 time=0\nnote_on channel=0 note=46 velocity=100 time=110\nnote_on channel=0 note=53 velocity=100 time=0\nnote_on channel=0 note=58 velocity=100 time=0\nnote_on channel=0 note=46 velocity=0 time=220\nnote_on channel=0 note=46 velocity=100 time=0\nnote_on channel=0 note
    }
   ],
   "source": [
    "mid = mido.MidiFile(filepath)\n",
    "for i, track in enumerate(mid.tracks):\n",
    "    for msg in track:\n",
    "        print(msg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {
      "image/png": {
       "width": 362,
       "height": 248
      },
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "x = np.arange(0,10)\n",
    "y = np.arange(0,10) + np.random.random(10)-0.5\n",
    "y_hat = np.arange(0,10)\n",
    "plt.scatter(x, y, c='k')\n",
    "plt.plot(x,y_hat, c='r')\n",
    "plt.labels\n",
    "# plt.savefig('linear_reg.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}