swing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Controls\n",
    "\n",
    "- Timing\n",
    "  - grid\n",
    "    - mapping\n",
    "    - slider bending factor\n",
    "  - offset (applied after grid)\n",
    "    - choose: msecs, or % of beat\n",
    "- Velocity\n",
    "  - envelope\n",
    "  - accentuation rules from phrasing / articulation\n",
    "    - pitch peak\n",
    "- Chaotic variation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.interpolate import interp1d\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "def norm(a):\n",
    "    cs = np.cumsum(a)\n",
    "    cycle_len = cs[-1]\n",
    "    cs = np.insert(cs, 0, 0)\n",
    "    #cs = np.delete(cs, -1)\n",
    "    return cs / cycle_len * 8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 2., 3., 5., 6., 8.])"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fully_swung = norm([2, 1, 2, 1, 2])\n",
    "fully_swung"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 1.33333333, 2.66666667, 5.33333333, 6.66666667,\n",
       "       8.        ])"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# even = np.linspace(0, 8, num=6, endpoint=True)\n",
    "even = norm([1, 1, 2, 1, 1])\n",
    "even"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([0, 2, 4, 6, 8]),\n",
       " array([1, 3, 5, 7]),\n",
       " array([0, 1, 2, 3, 4, 5, 6, 7, 8]))"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quavers = np.arange(0, 9)\n",
    "onbeats = np.arange(0, 9, step=2)\n",
    "offbeats = np.arange(1, 8, step=2)\n",
    "onbeats, offbeats, quavers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 1.55333333, 2.77666667, 5.22333333, 6.44666667,\n",
       "       8.        ])"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "percent = 33\n",
    "smoothed = np.average([fully_swung, even], weights=[percent, 100 - percent], axis=0)\n",
    "#smoothed = even\n",
    "smoothed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [],
   "source": [
    "linear = interp1d(fully_swung, smoothed)\n",
    "cubic = interp1d(fully_swung, smoothed, kind='cubic')\n",
    "many = np.linspace(0, 8, num=50)\n",
    "# cubic(many)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.ticker as plticker\n",
    "\n",
    "fig = plt.figure(figsize=(7,7))\n",
    "ax = plt.axes()\n",
    "\n",
    "loc = plticker.MultipleLocator(base=1)\n",
    "ax.xaxis.set_major_locator(loc)\n",
    "ax.yaxis.set_major_locator(loc)\n",
    "\n",
    "#plt.plot(quavers, linear(quavers), 'o')\n",
    "plt.plot(fully_swung, even, 'o-', label='full')\n",
    "plt.plot(many, many, color='grey', linestyle='-', linewidth=1)\n",
    "plt.plot(many, linear(many), linestyle='--', label='cubic')\n",
    "plt.xlabel('swung')\n",
    "plt.ylabel('even')\n",
    "plt.grid(b=True, color='aqua', alpha=0.3, linestyle=':', linewidth=2, markevery=1)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "# plt.hlines(1,0,8)  # Draw a horizontal line\n",
    "plt.eventplot(onbeats, orientation='horizontal', colors='black', linelengths=0.5)\n",
    "plt.eventplot(offbeats, orientation='horizontal', colors='grey', linelengths=0.3, lineoffsets=1.1)\n",
    "plt.eventplot(linear(quavers), orientation='horizontal', colors='gold', linelengths=0.2, lineoffsets=1.9)\n",
    "plt.eventplot(even, orientation='horizontal', colors='orange', linelengths=0.3, lineoffsets=1.9)\n",
    "plt.eventplot(fully_swung, orientation='horizontal', colors='red', linelengths=0.3, lineoffsets=1.5)\n",
    "# plt.eventplot(np.average(even, fully_swung), orientation='horizontal', colors='cyan', linelengths=0.3, lineoffsets=1.5)\n",
    "plt.axis('off')\n",
    "plt.show()"
   ]
  }
 ],
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