add notebook create_subregions

python/doc/_notebooks/create_subregions.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Demo for `tffpy.create_subregions.create_subregions`\n",
+    "\n",
+    "A simple demonstration for creating sub-regions from a boolean time-frequency mask"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%javascript\n",
+    "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
+    "    return false;\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib as mpl\n",
+    "mpl.rcParams['figure.figsize'] = [15.0, 7.0]\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from tffpy.datasets import get_mix\n",
+    "from tffpy.create_subregions import create_subregions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig_dir = 'fig_create_subregions'\n",
+    "x_mix, dgt_params, signal_params, mask, x_loc, x_wb = \\\n",
+    "            get_mix(loc_source='bird',\n",
+    "                    wideband_src='car',\n",
+    "                    crop=8192,\n",
+    "                    win_dur=256/8000,\n",
+    "                    win_type='gauss',\n",
+    "                    hop_ratio=1/4,\n",
+    "                    n_bins_ratio=4,\n",
+    "                    n_iter_closing=3,\n",
+    "                    n_iter_opening=3,\n",
+    "                    closing_first=True,\n",
+    "                    delta_mix_db=0,\n",
+    "                    delta_loc_db=20,\n",
+    "                    wb_to_loc_ratio_db=16,\n",
+    "                    or_mask=True,\n",
+    "                    fig_dir=None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tol = 1e-9\n",
+    "mask_with_subregions, norms = create_subregions(mask_bool=mask, \n",
+    "                                                dgt_params=dgt_params, signal_params=signal_params, \n",
+    "                                                tol=tol, fig_dir=fig_dir, return_norms=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print('Values in mask:', np.unique(mask_with_subregions))\n",
+    "print('Number of sub-regions:', np.max(mask_with_subregions))\n",
+    "plt.semilogy(np.sort(np.unique(norms)))\n",
+    "plt.title('Distances between sub-regions (sorted norm coefficients without duplicates)')\n",
+    "plt.grid()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "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": "3.6.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}