TimbreTrack_SOM.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import decimal\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from scipy.spatial.distance import cityblock\n",
    "import glob\n",
    "import statistics as st\n",
    "\n",
    "from apollon.som.som import IncrementalMap\n",
    "from apollon.som.utilities import best_match"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepare features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "features = {1:'Spectral Centroid',\n",
    "           2 : 'Spectral Spread',\n",
    "           3 :'Spectral Flux',\n",
    "           4 : 'Roughness',\n",
    "           5 : 'Sharpness',\n",
    "           6 : 'SPL',\n",
    "           7 : 'Correlation Dimension'}\n",
    "\n",
    "#Define a feature set from features, {count (1,2,3...), feature number in features}\n",
    "nfeatures = {1 :6}    #6: SPL\n",
    "             #2: 5,   #5: Sharpness\n",
    "             #3: 3}   #...\n",
    "             #4: 4,\n",
    "             #5: 5,\n",
    "             #6: 1}\n",
    "#.csv Files of extracted features, see Example Notebook 'TimbreTrack_Extract_Features'\n",
    "files = list(glob.glob(\"FilePath/*.csv\"))\n",
    "numfiles = len(files)\n",
    "numfeatures = len(nfeatures)\n",
    "lal1 = np.empty((numfiles, numfeatures))\n",
    "for j, f in enumerate(files):\n",
    "    la = pd.read_csv(f, index_col=0)\n",
    "    for i in nfeatures:\n",
    "        lal1[j][i-1] = la[features[nfeatures[i]]].std()      #calculate standard deviation of feature over time\n",
    "        #lal1[j][i-1] = la[features[nfeatures[i]]].mean()#calculate mean of features over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#In case of multiple file sets in different file folders:\n",
    "files = list(glob.glob(\"AnotherFilePath/*.csv\"))\n",
    "numfiles = len(files)\n",
    "numfeatures = len(nfeatures)\n",
    "lbl1 = np.empty((numfiles, numfeatures))\n",
    "for j, f in enumerate(files):\n",
    "    la = pd.read_csv(f, index_col=0)\n",
    "    for i in nfeatures:\n",
    "        lbl1[j][i-1] = la[features[nfeatures[i]]].std()\n",
    "        #lbl1[j][i-1] = la[features[nfeatures[i]]].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Build training vector in case of two sets\n",
    "train_X = np.concatenate((lal1,lbl1))\n",
    "features=numfeatures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Example target for two sets\n",
    "target = [('a', i+1) for i in range(0,len(lal1))] + [('b', i+1) for i in range(0,len(lbl1))]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit SOM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "dx = int(np.sqrt(train_X.shape[0]))+10\n",
    "dw = train_X.shape[1]\n",
    "som = IncrementalMap((dx, dx, dw), n_iter=500, eta=0.05, nhr=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "som.fit(train_X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "um = som.umatrix()\n",
    "bmu, err = best_match(som.weights, train_X, som.metric)\n",
    "px, py = np.unravel_index(bmu, som.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot SOM and matched sound files\n",
    "color_map = {'a': 'red', 'b': 'violet'}\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n",
    "ax.imshow(um, aspect='equal', origin='lower')\n",
    "\n",
    "ax.scatter(py, px, c=[color_map[t[0]] for t in target])\n",
    "\n",
    "for t, (y, x) in zip(target, zip(px, py)):\n",
    "    ax.text(x, y, t[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x2520 with 14 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot component plate, each subplot is a feature selected above\n",
    "fig, (axs) = plt.subplots(7, 2, figsize=(8, 35), sharex=True, sharey=True)\n",
    "fig.tight_layout()\n",
    "for i, (fn, ax) in enumerate(zip(nfeatures, axs.flatten())):\n",
    "    ax.set_title(fn)\n",
    "    ax.imshow(som.weights[:, i].reshape(som.shape), origin='lower', aspect='equal')"
   ]
  }
 ],
 "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}