Upload Los_Angeles_MIDI_Dataset_Search_and_Explore.ipynb

Los_Angeles_MIDI_Dataset_Search_and_Explore.ipynb

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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "gradient": {
+          "editing": false,
+          "id": "ac5a4cf0-d9d2-47b5-9633-b53f8d99a4d2",
+          "kernelId": ""
+        },
+        "id": "SiTIpPjArIyr"
+      },
+      "source": [
+        "# Los Angeles MIDI Dataset: Search and Explore (ver. 2.0)\n",
+        "\n",
+        "***\n",
+        "\n",
+        "Powered by tegridy-tools: https://github.com/asigalov61/tegridy-tools\n",
+        "\n",
+        "***\n",
+        "\n",
+        "#### Project Los Angeles\n",
+        "\n",
+        "#### Tegridy Code 2023\n",
+        "\n",
+        "***"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "gradient": {
+          "editing": false,
+          "id": "fa0a611c-1803-42ae-bdf6-a49b5a4e781b",
+          "kernelId": ""
+        },
+        "id": "gOd93yV0sGd2"
+      },
+      "source": [
+        "# (SETUP ENVIRONMENT)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "gradient": {
+          "editing": false,
+          "id": "a1a45a91-d909-4fd4-b67a-5e16b971d179",
+          "kernelId": ""
+        },
+        "id": "fX12Yquyuihc",
+        "cellView": "form"
+      },
+      "outputs": [],
+      "source": [
+        "#@title Install all dependencies (run only once per session)\n",
+        "!git clone --depth 1 https://github.com/asigalov61/Los-Angeles-MIDI-Dataset\n",
+        "!pip install huggingface_hub\n",
+        "!pip install matplotlib\n",
+        "!pip install sklearn\n",
+        "!pip install tqdm\n",
+        "!apt install fluidsynth #Pip does not work for some reason. Only apt works\n",
+        "!pip install midi2audio"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "gradient": {
+          "editing": false,
+          "id": "b8207b76-9514-4c07-95db-95a4742e52c5",
+          "kernelId": ""
+        },
+        "id": "z7n9vnKmug1J",
+        "cellView": "form"
+      },
+      "outputs": [],
+      "source": [
+        "#@title Import all needed modules\n",
+        "\n",
+        "print('Loading core modules...')\n",
+        "import os\n",
+        "import copy\n",
+        "from collections import Counter\n",
+        "import random\n",
+        "import pickle\n",
+        "from tqdm import tqdm\n",
+        "\n",
+        "from joblib import Parallel, delayed\n",
+        "import multiprocessing\n",
+        "\n",
+        "if not os.path.exists('/content/LAMD'):\n",
+        "    os.makedirs('/content/LAMD')\n",
+        "\n",
+        "print('Loading MIDI.py module...')\n",
+        "os.chdir('/content/Los-Angeles-MIDI-Dataset')\n",
+        "import MIDI\n",
+        "\n",
+        "print('Loading aux modules...')\n",
+        "from sklearn.metrics import pairwise_distances, pairwise\n",
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "from midi2audio import FluidSynth\n",
+        "from IPython.display import Audio, display\n",
+        "\n",
+        "from huggingface_hub import hf_hub_download\n",
+        "\n",
+        "os.chdir('/content/')\n",
+        "print('Done!')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# (PREP DATA)"
+      ],
+      "metadata": {
+        "id": "Erj-5wMNA1Jd"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Unzip LAMDa data\n",
+        "%cd /content/Los-Angeles-MIDI-Dataset/META-DATA\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Unzipping META-DATA...Please wait...')\n",
+        "\n",
+        "!cat LAMDa_META_DATA.zip* > LAMDa_META_DATA.zip\n",
+        "print('=' * 70)\n",
+        "\n",
+        "!unzip -j LAMDa_META_DATA.zip\n",
+        "print('=' * 70)\n",
+        "\n",
+        "print('Done! Enjoy! :)')\n",
+        "print('=' * 70)\n",
+        "%cd /content/\n",
+        "\n",
+        "#================================================\n",
+        "\n",
+        "%cd /content/Los-Angeles-MIDI-Dataset/MIDI-MATRIXES\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Unzipping MIDI-MATRIXES...Please wait...')\n",
+        "\n",
+        "!cat LAMDa_MIDI_MATRIXES.zip* > LAMDa_MIDI_MATRIXES.zip\n",
+        "print('=' * 70)\n",
+        "\n",
+        "!unzip -j LAMDa_MIDI_MATRIXES.zip\n",
+        "print('=' * 70)\n",
+        "\n",
+        "print('Done! Enjoy! :)')\n",
+        "print('=' * 70)\n",
+        "%cd /content/\n",
+        "\n",
+        "#==================================================\n",
+        "\n",
+        "%cd /content/Los-Angeles-MIDI-Dataset/TOTALS\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Unzipping TOTALS...Please wait...')\n",
+        "\n",
+        "!unzip -j LAMDa_TOTALS.zip\n",
+        "print('=' * 70)\n",
+        "\n",
+        "print('Done! Enjoy! :)')\n",
+        "print('=' * 70)\n",
+        "%cd /content/"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "Shs-6PR6ie7-"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Load LAMDa data\n",
+        "print('=' * 70)\n",
+        "print('Loading LAMDa data...Please wait...')\n",
+        "print('=' * 70)\n",
+        "print('Loading LAMDa META-DATA...')\n",
+        "meta_data = pickle.load(open('/content/Los-Angeles-MIDI-Dataset/META-DATA/LAMDa_META_DATA.pickle', 'rb'))\n",
+        "print('Done!')\n",
+        "print('=' * 70)\n",
+        "print('Loading LAMDa MIDI-MATRIXES...')\n",
+        "midi_matrixes = pickle.load(open('/content/Los-Angeles-MIDI-Dataset/MIDI-MATRIXES/LAMDa_MIDI_MATRIXES.pickle', 'rb'))\n",
+        "print('Done!')\n",
+        "print('=' * 70)\n",
+        "print('Loading LAMDa TOTALS...')\n",
+        "totals = pickle.load(open('/content/Los-Angeles-MIDI-Dataset/TOTALS/LAMDa_TOTALS.pickle', 'rb'))\n",
+        "print('Done!')\n",
+        "print('=' * 70)\n",
+        "print('Enjoy!')\n",
+        "print('=' * 70)"
+      ],
+      "metadata": {
+        "id": "ML1CecXtjiGE",
+        "cellView": "form"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# (PREP MIDI DATASET)"
+      ],
+      "metadata": {
+        "id": "GDKQys8pFgtj"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Download the dataset\n",
+        "print('=' * 70)\n",
+        "print('Downloading Los Angeles MIDI Dataset...Please wait...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "hf_hub_download(repo_id='projectlosangeles/Los-Angeles-MIDI-Dataset', \n",
+        "                filename='Los-Angeles-MIDI-Dataset-Ver-2-0-CC-BY-NC-SA.zip',\n",
+        "                repo_type=\"dataset\",\n",
+        "                local_dir='/content/LAMD', \n",
+        "                local_dir_use_symlinks=False)\n",
+        "print('=' * 70)\n",
+        "print('Done! Enjoy! :)')\n",
+        "print('=' * 70)"
+      ],
+      "metadata": {
+        "id": "U_KPkpWMCkNO",
+        "cellView": "form"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Unzip the dataset\n",
+        "%cd /content/LAMD\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Unzipping Los Angeles MIDI Dataset...Please wait...')\n",
+        "!unzip 'Los-Angeles-MIDI-Dataset-Ver-2-0-CC-BY-NC-SA.zip'\n",
+        "print('=' * 70)\n",
+        "\n",
+        "print('Done! Enjoy! :)')\n",
+        "print('=' * 70)\n",
+        "%cd /content/"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "mKFlrD98FMAP"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Create dataset files list\n",
+        "print('=' * 70)\n",
+        "print('Creating dataset files list...')\n",
+        "dataset_addr = \"/content/LAMD/MIDIs\"\n",
+        "\n",
+        "# os.chdir(dataset_addr)\n",
+        "filez = list()\n",
+        "for (dirpath, dirnames, filenames) in os.walk(dataset_addr):\n",
+        "    filez += [os.path.join(dirpath, file) for file in filenames]\n",
+        "\n",
+        "if filez == []:\n",
+        "    print('Could not find any MIDI files. Please check Dataset dir...')\n",
+        "    print('=' * 70)\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Randomizing file list...')\n",
+        "random.shuffle(filez)\n",
+        "print('=' * 70)\n",
+        "\n",
+        "LAMD_files_list = []\n",
+        "\n",
+        "for f in tqdm(filez):\n",
+        "  LAMD_files_list.append([f.split('/')[-1].split('.mid')[0], f])\n",
+        "print('Done!')\n",
+        "print('=' * 70)"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "nMRMnn7rHBg5"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# (PLOT TOTALS)"
+      ],
+      "metadata": {
+        "id": "ta6K3AOOqhpM"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Plot Totals\n",
+        "\n",
+        "cos_sim = pairwise.cosine_similarity(\n",
+        "      totals[0][0][4] \n",
+        "  )\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.imshow(cos_sim, cmap=\"inferno\", interpolation=\"none\")\n",
+        "im_ratio = 1\n",
+        "plt.colorbar(fraction=0.046 * im_ratio, pad=0.04)\n",
+        "plt.title('Times')\n",
+        "plt.xlabel(\"Position\")\n",
+        "plt.ylabel(\"Position\")\n",
+        "plt.tight_layout()\n",
+        "plt.plot()\n",
+        "\n",
+        "cos_sim = pairwise.cosine_similarity(\n",
+        "      totals[0][0][5] \n",
+        "  )\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.imshow(cos_sim, cmap=\"inferno\", interpolation=\"none\")\n",
+        "im_ratio = 1\n",
+        "plt.colorbar(fraction=0.046 * im_ratio, pad=0.04)\n",
+        "plt.title('Durations')\n",
+        "plt.xlabel(\"Position\")\n",
+        "plt.ylabel(\"Position\")\n",
+        "plt.tight_layout()\n",
+        "plt.plot()\n",
+        "\n",
+        "cos_sim = pairwise.cosine_similarity(\n",
+        "      totals[0][0][6] \n",
+        "  )\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.imshow(cos_sim, cmap=\"inferno\", interpolation=\"none\")\n",
+        "im_ratio = 1\n",
+        "plt.colorbar(fraction=0.046 * im_ratio, pad=0.04)\n",
+        "plt.title('Channels')\n",
+        "plt.xlabel(\"Position\")\n",
+        "plt.ylabel(\"Position\")\n",
+        "plt.tight_layout()\n",
+        "plt.plot()\n",
+        "\n",
+        "cos_sim = pairwise.cosine_similarity(\n",
+        "      totals[0][0][7] \n",
+        "  )\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.imshow(cos_sim, cmap=\"inferno\", interpolation=\"none\")\n",
+        "im_ratio = 1\n",
+        "plt.colorbar(fraction=0.046 * im_ratio, pad=0.04)\n",
+        "plt.title('Instruments')\n",
+        "plt.xlabel(\"Position\")\n",
+        "plt.ylabel(\"Position\")\n",
+        "plt.tight_layout()\n",
+        "plt.plot()\n",
+        "\n",
+        "cos_sim = pairwise.cosine_similarity(\n",
+        "      totals[0][0][8] \n",
+        "  )\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.imshow(cos_sim, cmap=\"inferno\", interpolation=\"none\")\n",
+        "im_ratio = 1\n",
+        "plt.colorbar(fraction=0.046 * im_ratio, pad=0.04)\n",
+        "plt.title('Pitches')\n",
+        "plt.xlabel(\"Position\")\n",
+        "plt.ylabel(\"Position\")\n",
+        "plt.tight_layout()\n",
+        "plt.plot()\n",
+        "\n",
+        "cos_sim = pairwise.cosine_similarity(\n",
+        "      totals[0][0][9] \n",
+        "  )\n",
+        "plt.figure(figsize=(8, 8))\n",
+        "plt.imshow(cos_sim, cmap=\"inferno\", interpolation=\"none\")\n",
+        "im_ratio = 1\n",
+        "plt.colorbar(fraction=0.046 * im_ratio, pad=0.04)\n",
+        "plt.title('Velocities')\n",
+        "plt.xlabel(\"Position\")\n",
+        "plt.ylabel(\"Position\")\n",
+        "plt.tight_layout()\n",
+        "plt.plot()"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "Tk-3Q3UnqkpL"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# (LOAD SOURCE MIDI)"
+      ],
+      "metadata": {
+        "id": "jiVsfC0u7aAQ"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Load source MIDI\n",
+        "\n",
+        "full_path_to_source_MIDI = \"/content/Los-Angeles-MIDI-Dataset/Come-To-My-Window-Modified-Sample-MIDI.mid\" #@param {type:\"string\"}\n",
+        "render_MIDI_to_audio = False #@param {type:\"boolean\"}\n",
+        "\n",
+        "#=================================================================================\n",
+        "\n",
+        "f = full_path_to_source_MIDI\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Loading MIDI file...')\n",
+        "\n",
+        "score = MIDI.midi2ms_score(open(f, 'rb').read())\n",
+        "\n",
+        "events_matrix = []\n",
+        "\n",
+        "itrack = 1\n",
+        "\n",
+        "while itrack < len(score):\n",
+        "    for event in score[itrack]:         \n",
+        "      events_matrix.append(event)\n",
+        "    itrack += 1\n",
+        "\n",
+        "# Sorting...\n",
+        "events_matrix.sort(key=lambda x: x[1])\n",
+        "\n",
+        "# recalculating timings\n",
+        "for e in events_matrix:\n",
+        "    e[1] = int(e[1] / 10)\n",
+        "    if e[0] == 'note':\n",
+        "      e[2] = int(e[2] / 20)\n",
+        "\n",
+        "# final processing...\n",
+        "\n",
+        "melody_chords = []\n",
+        "\n",
+        "patches = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
+        "\n",
+        "pe = events_matrix[0]\n",
+        "for e in events_matrix:\n",
+        "\n",
+        "  if e[0] == 'note':\n",
+        "    # ['note', start_time, duration, channel, note, velocity]\n",
+        "    time = max(0, min(255, e[1]-pe[1]))\n",
+        "    duration = max(1, min(255, e[2]))\n",
+        "    channel = max(0, min(15, e[3]))\n",
+        "\n",
+        "    if e[3] != 9:\n",
+        "      instrument = max(0, min(127, patches[e[3]]))\n",
+        "    else:\n",
+        "      instrument = max(128, min(255, patches[e[3]]+128))\n",
+        "\n",
+        "    if e[3] != 9:\n",
+        "\n",
+        "      pitch = max(1, min(127, e[4]))\n",
+        "    else:\n",
+        "      pitch = max(129, min(255, e[4]+128))\n",
+        "\n",
+        "    if e[3] != 9:\n",
+        "      velocity = max(1, min(127, e[5]))\n",
+        "    else:\n",
+        "      velocity = max(129, min(255, e[5]+128))\n",
+        "\n",
+        "    melody_chords.append([time, duration, channel, instrument, pitch, velocity])\n",
+        "\n",
+        "  if e[0] == 'patch_change':\n",
+        "    # ['patch_change', dtime, channel, patch]\n",
+        "    time = max(0, min(127, e[1]-pe[1]))\n",
+        "    channel = max(0, min(15, e[2]))\n",
+        "    patch = max(0, min(127, e[3]))\n",
+        "\n",
+        "    patches[channel] = patch\n",
+        "\n",
+        "  pe = e # Previous event\n",
+        "\n",
+        "MATRIX = [[0]*256 for i in range(38)]\n",
+        "\n",
+        "for m in melody_chords:\n",
+        "\n",
+        "  MATRIX[0][m[0]] += 1\n",
+        "  MATRIX[1][m[1]] += 1\n",
+        "  MATRIX[2][m[2]] += 1 \n",
+        "  MATRIX[3][m[3]] += 1\n",
+        "  MATRIX[4][m[4]] += 1\n",
+        "  MATRIX[5][m[5]] += 1\n",
+        "  MATRIX[m[2]+6][m[3]] += 1\n",
+        "  MATRIX[m[2]+22][m[4]] += 1\n",
+        "\n",
+        "#==================================================\n",
+        "\n",
+        "score = MIDI.midi2score(open(f, 'rb').read())\n",
+        "\n",
+        "events_matrix = []\n",
+        "\n",
+        "track_count = 0\n",
+        "\n",
+        "for s in score:\n",
+        "    \n",
+        "    if track_count > 0:\n",
+        "        track = s\n",
+        "        track.sort(key=lambda x: x[1])\n",
+        "        events_matrix.extend(track)\n",
+        "    else:\n",
+        "        midi_ticks = s\n",
+        "\n",
+        "    track_count += 1\n",
+        "    \n",
+        "events_matrix.sort(key=lambda x: x[1])\n",
+        "\n",
+        "for e in events_matrix:\n",
+        "    if e[0] == 'note':\n",
+        "        if e[3] == 9:\n",
+        "            e[4] = ((e[4] % 128) + 128)\n",
+        "\n",
+        "pitches_counts = [[y[0],y[1]] for y in Counter([y[4] for y in events_matrix if y[0] == 'note']).most_common()]\n",
+        "pitches_counts.sort(key=lambda x: x[0], reverse=True)\n",
+        "\n",
+        "patches_list = sorted(list(set([y[3] for y in events_matrix if y[0] == 'patch_change'])))\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Done!')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "#============================================\n",
+        "# MIDI rendering code\n",
+        "#============================================\n",
+        "\n",
+        "print('Rendering source MIDI...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "ms_score = MIDI.midi2ms_score(open(f, 'rb').read())\n",
+        "\n",
+        "itrack = 1\n",
+        "song_f = []\n",
+        "\n",
+        "while itrack < len(ms_score):\n",
+        "    for event in ms_score[itrack]:         \n",
+        "        if event[0] == 'note':\n",
+        "            song_f.append(event)\n",
+        "    itrack += 1\n",
+        "\n",
+        "song_f.sort(key=lambda x: x[1])\n",
+        "\n",
+        "fname = f.split('.mid')[0]\n",
+        "\n",
+        "x = []\n",
+        "y =[]\n",
+        "c = []\n",
+        "\n",
+        "colors = ['red', 'yellow', 'green', 'cyan', 'blue', 'pink', 'orange', 'purple', 'gray', 'white', 'gold', 'silver', 'aqua', 'azure', 'bisque', 'coral']\n",
+        "\n",
+        "for s in song_f:\n",
+        "  x.append(s[1] / 1000)\n",
+        "  y.append(s[4])\n",
+        "  c.append(colors[s[3]])\n",
+        "\n",
+        "if render_MIDI_to_audio:\n",
+        "  FluidSynth(\"/usr/share/sounds/sf2/FluidR3_GM.sf2\", 16000).midi_to_audio(str(fname + '.mid'), str(fname + '.wav'))\n",
+        "  display(Audio(str(fname + '.wav'), rate=16000))\n",
+        "\n",
+        "plt.figure(figsize=(14,5))\n",
+        "ax=plt.axes(title=fname)\n",
+        "ax.set_facecolor('black')\n",
+        "\n",
+        "plt.scatter(x,y, c=c)\n",
+        "plt.xlabel(\"Time\")\n",
+        "plt.ylabel(\"Pitch\")\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "z7mm6WsDmuRi"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# (SEARCH AND EXPLORE)"
+      ],
+      "metadata": {
+        "id": "LRnuphuiqc5F"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Legacy MIDI Matrixes Search (Slow)\n",
+        "matching_type = \"minkowski\" #@param {type:\"string\"}\n",
+        "stop_search_on_exact_match = True #@param {type:\"boolean\"}\n",
+        "\n",
+        "#=================================================================================\n",
+        "\n",
+        "def compress_matrix(midi_matrix):\n",
+        "\n",
+        "  MX = 38\n",
+        "  MY = 256\n",
+        "\n",
+        "  if len(midi_matrix) == MX:\n",
+        "\n",
+        "    compressed_matrix = []\n",
+        "    zeros = 0\n",
+        "    zeros_shift = 0\n",
+        "    zeros_count = 0\n",
+        "\n",
+        "    for m in midi_matrix:\n",
+        "      for mm in m:\n",
+        "        zeros_shift = max(zeros_shift, mm) + 1\n",
+        "\n",
+        "    compressed_matrix.append(zeros_shift)\n",
+        "\n",
+        "    for m in midi_matrix:\n",
+        "      if len(m) == MY:\n",
+        "        for mm in m:\n",
+        "          if mm != 0:\n",
+        "            if zeros > 0:\n",
+        "              compressed_matrix.append(zeros+zeros_shift)\n",
+        "              zeros = 0\n",
+        "            compressed_matrix.append(mm)\n",
+        "          \n",
+        "          else:\n",
+        "            zeros += 1\n",
+        "            zeros_count += 1\n",
+        "      \n",
+        "      else:\n",
+        "        print('Wrong matrix format!')\n",
+        "        return [1]\n",
+        "\n",
+        "    if zeros > 0:\n",
+        "      compressed_matrix.append(zeros+zeros_shift)\n",
+        "\n",
+        "    compressed_matrix.append(zeros_count+zeros_shift)\n",
+        "    compressed_matrix.append(zeros_shift)\n",
+        "\n",
+        "    return compressed_matrix\n",
+        "\n",
+        "  else:\n",
+        "    print('Wrong matrix format!')\n",
+        "    return [0]\n",
+        "\n",
+        "#=================================================================================\n",
+        "\n",
+        "def decompress_matrix(compressed_midi_matrix):\n",
+        "\n",
+        "  MX = 38\n",
+        "  MY = 256\n",
+        "\n",
+        "  zeros_count = 0\n",
+        "\n",
+        "  temp_matrix = []\n",
+        "  decompressed_matrix = [[0]*MY for i in range(MX)]\n",
+        "\n",
+        "  if compressed_midi_matrix[0] == compressed_midi_matrix[-1]:\n",
+        "    zeros_shift = compressed_midi_matrix[0]\n",
+        "    mcount = 0\n",
+        "\n",
+        "    for c in compressed_midi_matrix[1:-2]:\n",
+        "      if c > zeros_shift:\n",
+        "        temp_matrix.extend([0] * (c-zeros_shift))\n",
+        "        zeros_count += (c-zeros_shift)\n",
+        "\n",
+        "      else:\n",
+        "        temp_matrix.extend([c])\n",
+        "\n",
+        "    if len(temp_matrix) == (MX * MY):\n",
+        "\n",
+        "      for i in range(MX):\n",
+        "        for j in range(MY):\n",
+        "          decompressed_matrix[i][j] = copy.deepcopy(temp_matrix[(i*MY) + j])\n",
+        "      \n",
+        "      if len(decompressed_matrix) == MX and zeros_count == (compressed_midi_matrix[-2]-zeros_shift):\n",
+        "        return decompressed_matrix\n",
+        "\n",
+        "      else:\n",
+        "        print('Matrix is corrupted!')\n",
+        "        return [len(decompressed_matrix), (MX * MY), zeros_count, (compressed_midi_matrix[-2]-zeros_shift)]\n",
+        "    \n",
+        "    else:\n",
+        "      print('Matrix is corrupted!')\n",
+        "      return [len(temp_matrix), zeros_count]\n",
+        "\n",
+        "  else:\n",
+        "    print('Matrix is corrupted!')\n",
+        "    return [0]\n",
+        "\n",
+        "#=================================================================================\n",
+        "\n",
+        "def batched_scores(matbatch, matrix):\n",
+        "\n",
+        "  sco= []\n",
+        "  for D in matbatch:\n",
+        "\n",
+        "    dist = pairwise_distances(matrix, decompress_matrix(D[1]), metric=matching_type)[0][0]                         \n",
+        "    sco.append(dist)\n",
+        "\n",
+        "  return sco\n",
+        "\n",
+        "#=================================================================================\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Searching...Please wait...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "scores = []\n",
+        "\n",
+        "c_count = multiprocessing.cpu_count()\n",
+        "\n",
+        "par = Parallel(n_jobs=c_count)\n",
+        "\n",
+        "num_jobs = c_count\n",
+        "scores_per_job = 100\n",
+        "\n",
+        "MATRIX_X = [MATRIX] * num_jobs\n",
+        "\n",
+        "for i in tqdm(range(0, len(midi_matrixes), (num_jobs*scores_per_job))):\n",
+        "  \n",
+        "  try:\n",
+        "\n",
+        "    MAT_BATCHES = []\n",
+        "\n",
+        "    for j in range(num_jobs):\n",
+        "      MAT_BATCHES.append(midi_matrixes[i+(j*scores_per_job):i+((j+1)*scores_per_job)])\n",
+        "\n",
+        "    output = par(delayed(batched_scores) (MB, MAT) for MB, MAT in zip(MAT_BATCHES, MATRIX_X))\n",
+        "\n",
+        "    output1 = []\n",
+        "\n",
+        "    for o in output:\n",
+        "      output1.extend(o)\n",
+        "\n",
+        "    scores.extend(output1)                            \n",
+        "\n",
+        "    if stop_search_on_exact_match:\n",
+        "      if 0 in output1:\n",
+        "        print('=' * 70)\n",
+        "        print('Found exact match!')\n",
+        "        print('Stoping further search...')\n",
+        "        print('=' * 70)\n",
+        "        break\n",
+        "\n",
+        "    else:\n",
+        "      if 0 in output1:\n",
+        "        print('=' * 70)\n",
+        "        print('Found exact match!')\n",
+        "        print('=' * 70)\n",
+        "        print('LAMDa Index:', scores.index(min(scores)))\n",
+        "        print('LAMDa File Name:', midi_matrixes[scores.index(min(scores))][0])\n",
+        "        print('=' * 70)\n",
+        "        print('Continuing search...')\n",
+        "        print('=' * 70)\n",
+        "  except KeyboardInterrupt:\n",
+        "    break\n",
+        "  \n",
+        "  except:\n",
+        "    continue\n",
+        "\n",
+        "print('Done!')\n",
+        "print('=' * 70)\n",
+        "print('Best match:')\n",
+        "print('=' * 70)   \n",
+        "print(matching_type.title(), 'distance ==', min(scores))\n",
+        "print('LAMDa Index:', scores.index(min(scores)))\n",
+        "print('LAMDa File Name:', midi_matrixes[scores.index(min(scores))][0])\n",
+        "print('=' * 70)\n",
+        "\n",
+        "print('Top 100 matches')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "top_matches = []\n",
+        "\n",
+        "for i in range(len(scores)):\n",
+        "  top_matches.append([midi_matrixes[i][0], scores[i]])\n",
+        "\n",
+        "top_matches.sort(key=lambda x: x[1])\n",
+        "\n",
+        "for t in top_matches[:100]:\n",
+        "  print(t)\n",
+        "  \n",
+        "print('=' * 70)"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "pNQG6Qgfrlfi"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title MIDI Pitches Search\n",
+        "\n",
+        "render_MIDI_to_audio = False #@param {type:\"boolean\"}\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('MIDI Pitches Search')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "ratios = []\n",
+        "\n",
+        "for d in tqdm(meta_data):\n",
+        "  p_counts = d[1][3][1]\n",
+        "\n",
+        "  num_same_pitches = len(set([T[0] for T in p_counts]) & set([m[0] for m in pitches_counts]))\n",
+        "  same_pitches_ratio = (num_same_pitches / len(set([m[0] for m in p_counts]+[T[0] for T in pitches_counts])))\n",
+        "\n",
+        "  ratios.append(same_pitches_ratio)\n",
+        "\n",
+        "max_ratio = max(ratios)\n",
+        "max_ratio_index = ratios.index(max(ratios))\n",
+        "\n",
+        "print('FOUND')\n",
+        "print('=' * 70)\n",
+        "print('Match ratio', max_ratio)\n",
+        "print('MIDI file name', meta_data[max_ratio_index][0])\n",
+        "print('=' * 70)\n",
+        "print('First metadata MIDI event', meta_data[max_ratio_index][1][0])\n",
+        "print('=' * 70)\n",
+        "\n",
+        "#============================================\n",
+        "# MIDI rendering code\n",
+        "#============================================\n",
+        "\n",
+        "print('Rendering source MIDI...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "fn = meta_data[max_ratio_index][0]\n",
+        "fn_idx = [y[0] for y in LAMD_files_list].index(fn)\n",
+        "\n",
+        "f = LAMD_files_list[fn_idx][1]\n",
+        "\n",
+        "ms_score = MIDI.midi2ms_score(open(f, 'rb').read())\n",
+        "\n",
+        "itrack = 1\n",
+        "song_f = []\n",
+        "\n",
+        "while itrack < len(ms_score):\n",
+        "    for event in ms_score[itrack]:         \n",
+        "        if event[0] == 'note':\n",
+        "            song_f.append(event)\n",
+        "    itrack += 1\n",
+        "\n",
+        "song_f.sort(key=lambda x: x[1])\n",
+        "\n",
+        "fname = f.split('.mid')[0]\n",
+        "\n",
+        "x = []\n",
+        "y =[]\n",
+        "c = []\n",
+        "\n",
+        "colors = ['red', 'yellow', 'green', 'cyan', 'blue', 'pink', 'orange', 'purple', 'gray', 'white', 'gold', 'silver', 'aqua', 'azure', 'bisque', 'coral']\n",
+        "\n",
+        "for s in song_f:\n",
+        "  x.append(s[1] / 1000)\n",
+        "  y.append(s[4])\n",
+        "  c.append(colors[s[3]])\n",
+        "\n",
+        "if render_MIDI_to_audio:\n",
+        "  FluidSynth(\"/usr/share/sounds/sf2/FluidR3_GM.sf2\", 16000).midi_to_audio(str(fname + '.mid'), str(fname + '.wav'))\n",
+        "  display(Audio(str(fname + '.wav'), rate=16000))\n",
+        "\n",
+        "plt.figure(figsize=(14,5))\n",
+        "ax=plt.axes(title=fname)\n",
+        "ax.set_facecolor('black')\n",
+        "\n",
+        "plt.scatter(x,y, c=c)\n",
+        "plt.xlabel(\"Time\")\n",
+        "plt.ylabel(\"Pitch\")\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "C-P71_9ojh8G"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title MIDI Patches Search\n",
+        "\n",
+        "render_MIDI_to_audio = False #@param {type:\"boolean\"}\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('MIDI Patches Search')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "ratios = []\n",
+        "\n",
+        "for d in tqdm(meta_data):\n",
+        "  p_list= d[1][4][1]\n",
+        "\n",
+        "  num_same_patches = len(set(p_list) & set(patches_list))\n",
+        "  \n",
+        "  if len(set(p_list + patches_list)) > 0:\n",
+        "    same_patches_ratio = num_same_patches / len(set(p_list + patches_list))\n",
+        "  else:\n",
+        "    same_patches_ratio = 0\n",
+        "\n",
+        "  ratios.append(same_patches_ratio)\n",
+        "\n",
+        "max_ratio = max(ratios)\n",
+        "max_ratio_index = ratios.index(max(ratios))\n",
+        "\n",
+        "print('FOUND')\n",
+        "print('=' * 70)\n",
+        "print('Match ratio', max_ratio)\n",
+        "print('MIDI file name', meta_data[max_ratio_index][0])\n",
+        "print('=' * 70)\n",
+        "print('Found MIDI patches list', meta_data[max_ratio_index][1][4][1])\n",
+        "print('=' * 70)\n",
+        "\n",
+        "#============================================\n",
+        "# MIDI rendering code\n",
+        "#============================================\n",
+        "\n",
+        "print('Rendering source MIDI...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "fn = meta_data[max_ratio_index][0]\n",
+        "fn_idx = [y[0] for y in LAMD_files_list].index(fn)\n",
+        "\n",
+        "f = LAMD_files_list[fn_idx][1]\n",
+        "\n",
+        "ms_score = MIDI.midi2ms_score(open(f, 'rb').read())\n",
+        "\n",
+        "itrack = 1\n",
+        "song_f = []\n",
+        "\n",
+        "while itrack < len(ms_score):\n",
+        "    for event in ms_score[itrack]:         \n",
+        "        if event[0] == 'note':\n",
+        "            song_f.append(event)\n",
+        "    itrack += 1\n",
+        "\n",
+        "song_f.sort(key=lambda x: x[1])\n",
+        "\n",
+        "fname = f.split('.mid')[0]\n",
+        "\n",
+        "x = []\n",
+        "y =[]\n",
+        "c = []\n",
+        "\n",
+        "colors = ['red', 'yellow', 'green', 'cyan', 'blue', 'pink', 'orange', 'purple', 'gray', 'white', 'gold', 'silver', 'aqua', 'azure', 'bisque', 'coral']\n",
+        "\n",
+        "for s in song_f:\n",
+        "  x.append(s[1] / 1000)\n",
+        "  y.append(s[4])\n",
+        "  c.append(colors[s[3]])\n",
+        "\n",
+        "if render_MIDI_to_audio:\n",
+        "  FluidSynth(\"/usr/share/sounds/sf2/FluidR3_GM.sf2\", 16000).midi_to_audio(str(fname + '.mid'), str(fname + '.wav'))\n",
+        "  display(Audio(str(fname + '.wav'), rate=16000))\n",
+        "\n",
+        "plt.figure(figsize=(14,5))\n",
+        "ax=plt.axes(title=fname)\n",
+        "ax.set_facecolor('black')\n",
+        "\n",
+        "plt.scatter(x,y, c=c)\n",
+        "plt.xlabel(\"Time\")\n",
+        "plt.ylabel(\"Pitch\")\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "JmV8VNj-tz1m"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Metadata Search\n",
+        "search_query = \"Come To My Window\" #@param {type:\"string\"}\n",
+        "case_sensitive_search = False #@param {type:\"boolean\"}\n",
+        "\n",
+        "fields_to_search = ['track_name', \n",
+        "                    'text_event', \n",
+        "                    'lyric', \n",
+        "                    'copyright_text_event', \n",
+        "                    'marker',\n",
+        "                    'text_event_08',\n",
+        "                    'text_event_09',\n",
+        "                    'text_event_0a',\n",
+        "                    'text_event_0b',\n",
+        "                    'text_event_0c',\n",
+        "                    'text_event_0d',\n",
+        "                    'text_event_0e',\n",
+        "                    'text_event_0f',\n",
+        "                    ]\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Sarching...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "for d in tqdm(meta_data):\n",
+        "  for dd in d[1]:\n",
+        "    if dd[0] in fields_to_search:\n",
+        "      if case_sensitive_search:\n",
+        "        if str(search_query) in str(dd[2]):\n",
+        "          print('Found!')\n",
+        "          print('=' * 70)\n",
+        "          print('Metadata index:', meta_data.index(d))\n",
+        "          print('MIDI file name:', meta_data[meta_data.index(d)][0])\n",
+        "          print('Result:', dd[2])\n",
+        "          print('=' * 70)\n",
+        "      \n",
+        "      else:\n",
+        "        if str(search_query).lower() in str(dd[2]).lower():\n",
+        "          print('Found!')\n",
+        "          print('=' * 70)\n",
+        "          print('Metadata index:', meta_data.index(d))\n",
+        "          print('MIDI file name:', meta_data[meta_data.index(d)][0])\n",
+        "          print('Result:', dd[2])\n",
+        "          print('=' * 70)"
+      ],
+      "metadata": {
+        "cellView": "form",
+        "id": "98JuBEdMqIE3"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# (CUSTOM ANALYSIS TEMPLATE)"
+      ],
+      "metadata": {
+        "id": "jNH-J2ry7sLj"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "#@title Los Angeles MIDI Dataset Reader\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Los Angeles MIDI Dataset Reader')\n",
+        "print('=' * 70)\n",
+        "print('Starting up...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "###########\n",
+        "\n",
+        "print('Loading MIDI files...')\n",
+        "print('This may take a while on a large dataset in particular.')\n",
+        "\n",
+        "dataset_addr = \"/content/LAMD/MIDIs\"\n",
+        "\n",
+        "# os.chdir(dataset_addr)\n",
+        "filez = list()\n",
+        "for (dirpath, dirnames, filenames) in os.walk(dataset_addr):\n",
+        "    filez += [os.path.join(dirpath, file) for file in filenames]\n",
+        "\n",
+        "if filez == []:\n",
+        "    print('Could not find any MIDI files. Please check Dataset dir...')\n",
+        "    print('=' * 70)\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Randomizing file list...')\n",
+        "random.shuffle(filez)\n",
+        "print('=' * 70)\n",
+        "\n",
+        "###########\n",
+        "\n",
+        "START_FILE_NUMBER = 0\n",
+        "LAST_SAVED_BATCH_COUNT = 0\n",
+        "\n",
+        "input_files_count = START_FILE_NUMBER\n",
+        "files_count = LAST_SAVED_BATCH_COUNT\n",
+        "\n",
+        "stats = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
+        "\n",
+        "print('Reading MIDI files. Please wait...')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "for f in tqdm(filez[START_FILE_NUMBER:]):\n",
+        "    try:\n",
+        "        input_files_count += 1\n",
+        "\n",
+        "        fn = os.path.basename(f)\n",
+        "        fn1 = fn.split('.mid')[0]\n",
+        "\n",
+        "        #=======================================================\n",
+        "        # START PROCESSING\n",
+        "        #=======================================================\n",
+        "\n",
+        "        # Convering MIDI to score with MIDI.py module\n",
+        "        score = MIDI.midi2score(open(f, 'rb').read())\n",
+        "\n",
+        "        events_matrix = []\n",
+        "        \n",
+        "        itrack = 1\n",
+        "\n",
+        "        while itrack < len(score):\n",
+        "            for event in score[itrack]:        \n",
+        "              events_matrix.append(event)\n",
+        "            itrack += 1\n",
+        "\n",
+        "        # Sorting...\n",
+        "        events_matrix.sort(key=lambda x: x[1])\n",
+        "\n",
+        "        if len(events_matrix) > 0:\n",
+        "          \n",
+        "          #=======================================================\n",
+        "          # INSERT YOUR CUSTOM ANAYLSIS CODE RIGHT HERE\n",
+        "          #=======================================================\n",
+        "\n",
+        "          # Processed files counter\n",
+        "          files_count += 1\n",
+        "\n",
+        "          # Saving every 5000 processed files\n",
+        "          if files_count % 10000 == 0:\n",
+        "            print('=' * 70)\n",
+        "            print('Processed so far:', files_count, 'out of', input_files_count, '===', files_count / input_files_count, 'good files ratio')\n",
+        "            print('=' * 70)\n",
+        "\n",
+        "    except KeyboardInterrupt:\n",
+        "        print('Saving current progress and quitting...')\n",
+        "        break  \n",
+        "\n",
+        "    except Exception as ex:\n",
+        "        print('WARNING !!!')\n",
+        "        print('=' * 70)\n",
+        "        print('Bad MIDI:', f)\n",
+        "        print('Error detected:', ex)\n",
+        "        print('=' * 70)\n",
+        "        continue\n",
+        "\n",
+        "print('=' * 70)\n",
+        "print('Final files counts:', files_count, 'out of', input_files_count, '===', files_count / input_files_count, 'good files ratio')\n",
+        "print('=' * 70)\n",
+        "\n",
+        "print('Resulting Stats:')\n",
+        "print('=' * 70)\n",
+        "print('Total good processed MIDI files:', files_count)\n",
+        "print('=' * 70)\n",
+        "print('Done!')   \n",
+        "print('=' * 70)"
+      ],
+      "metadata": {
+        "id": "xrmnVUkXGsUi",
+        "cellView": "form"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "YzCMd94Tu_gz"
+      },
+      "source": [
+        "# Congrats! You did it! :)"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "private_outputs": true,
+      "provenance": [],
+      "machine_shape": "hm"
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "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": "3.9.7"
+    },
+    "gpuClass": "standard"
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}