Add contour highlight

demo.ipynb

@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -121,6 +121,10 @@
     "\n",
     "dtm_hs = ui8_clip(hillshades(dtm), -1, 1)\n",
     "cm_hud = mpl.colors.LinearSegmentedColormap.from_list('GreenHUD', [(0.,0.,0.,0.), (0.,1.,0.,1.)], 256)\n",
+    "alpha = ((dtm_hs.astype(float) - 127) / 127) ** 2 * .4\n",
+    "cX, cY = np.meshgrid(np.arange(dtm.shape[1]), np.arange(dtm.shape[0]))\n",
+    "kwargs = {}\n",
+    "kwargs['vmin'], kwargs['vmax'] = np.quantile(dtm, (.01, .99))\n",
     "\n",
     "model = {}"
    ]
@@ -134,13 +138,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "87b90d0f6d584b83af83965b32f15118",
+       "model_id": "6a5848b7f64b487fae0ecb76d2ff5f72",
        "version_major": 2,
        "version_minor": 0
       },
@@ -154,10 +158,10 @@
     {
      "data": {
       "text/plain": [
-       "<function __main__.spectrum_widget(tree=<class 'sap.trees.MaxTree'>, x='area', y='compactness', x_log=True, y_log=False, hillshade_overlay=False, highlight=True)>"
+       "<function __main__.spectrum_widget(tree=<class 'sap.trees.MaxTree'>, x='area', y='compactness', x_log=True, y_log=False, hillshade_overlay=True, highlight=True)>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -218,7 +222,6 @@
     "        ps_mask = spectrum2d(model['tree_cache'], x, y, 200, 100, x_log, y_log, node_mask=node_mask)\n",
     "        ps[0][:] = ps_mask[0] / ps[0]\n",
     "\n",
-    "    \n",
     "    # Display spectrum\n",
     "    plt.sca(model['ax_spectrum'])\n",
     "    plt.cla()\n",
@@ -238,9 +241,12 @@
     "    # No filter\n",
     "    if x1 == x2 == y1 == y2 == 0:\n",
     "        if not model['overlay']:\n",
-    "            model['ax_dtm'].imshow(dtm)\n",
+    "            model['ax_dtm'].imshow(dtm, **kwargs)\n",
     "        else:\n",
-    "            model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys)\n",
+    "            #model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys)\n",
+    "            model['ax_dtm'].imshow(dtm, **kwargs)\n",
+    "            model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys, alpha=alpha)\n",
+    "\n",
     "        return\n",
     "    \n",
     "    # Filter\n",
@@ -253,14 +259,18 @@
     "    if not model['overlay']:\n",
     "        model['ax_dtm'].imshow(img)\n",
     "    else:\n",
-    "        over = img != model['tree_cache']._alt[-1]\n",
+    "        #over = img != model['tree_cache']._alt[-1]\n",
-    "        model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys)\n",
+    "        #model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys)\n",
-    "        model['ax_dtm'].imshow(over, cmap=cm_hud, alpha=.4)\n",
+    "        #model['ax_dtm'].imshow(over, cmap=cm_hud, alpha=.4)\n",
+    "        model['ax_dtm'].clear()\n",
+    "        model['ax_dtm'].imshow(dtm, **kwargs)\n",
+    "        model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys, alpha=alpha)\n",
+    "        model['ax_dtm'].contour(cX, cY, img, [model['tree_cache']._alt[-1]], colors='lime')\n",
     "\n",
     "    plt.gcf().canvas.draw()\n",
     "\n",
     "def spectrum_widget(tree=sap.MaxTree, x='area', y='compactness', x_log=True, y_log=False,\n",
-    "                    hillshade_overlay=False, highlight=True):\n",
+    "                    hillshade_overlay=True, highlight=True):\n",
     "    # Update only toggle of hillshade_overlay\n",
     "    if hillshade_overlay != model['overlay']:\n",
     "        model['overlay'] = hillshade_overlay\n",
@@ -312,8 +322,7 @@
     "plt.connect('key_press_event', selector)\n",
     "\n",
     "\n",
-    "#model['ax_dtm'].imshow(dtm_hs, cmap=plt.cm.Greys)\n",
+    "#filter_dtm()\n",
-    "filter_dtm()\n",
     "\n",
     "ipw.interact(spectrum_widget, \n",
     "             tree=inspect.getmembers(sap.trees, lambda t: inspect.isclass(t) and issubclass(t, sap.Tree) and t != sap.Tree),\n",
@@ -321,6 +330,181 @@
     "             y=sap.available_attributes().keys())"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2001, 2001)"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model['tree_cache'].reconstruct().shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2001"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "16.93000030517578"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model['tree_cache']._alt[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'img' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-62-77a7949ba908>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mimg\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'img' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "img"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.contour.QuadContourSet at 0x7fe61585e430>"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "plt.close()\n",
+    "plt.figure()\n",
+    "ax = plt.gca()\n",
+    "\n",
+    "plt.imshow(dtm, **kwargs)\n",
+    "plt.colorbar()\n",
+    "ax.imshow(dtm_hs, cmap=plt.cm.Greys, alpha=alpha)\n",
+    "ax.contour(X, Y, dtm, [30], colors='lime')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2001, 2001)"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dtm_hs.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2001, 2001)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dtm.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.12586920037702484"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "alpha.mean()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,