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8fd8dd3374
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demo.ipynb
179
demo.ipynb
@ -67,7 +67,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 65,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -76,15 +76,7 @@
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"\n",
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"def get_tile(feature, name):\n",
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" return list(data_dir.glob('**/{}_vox_50cm_tile_{}.tif'.format(feature, name)))[0]\n",
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"\n",
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"def load_tile(feature, name):\n",
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" model['im'] = rio.open(get_tile(feature, name)).read()[0]\n",
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" model['im_hs'] = ui8_clip(hillshades(model['im']), -1, 1)\n",
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" model['im_hs_alpha'] = ((model['im_hs'].astype(float) - 127) / 127) ** 2 * .4\n",
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" kwargs = {}\n",
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" kwargs['vmin'], kwargs['vmax'] = np.quantile(model['im'], (.01, .99))\n",
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" model['im_kwargs'] = kwargs\n",
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" model['im_mesh'] = np.meshgrid(np.arange(model['im'].shape[1]), np.arange(model['im'].shape[0]))"
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"\n"
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]
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},
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{
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@ -218,7 +210,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 90,
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"metadata": {
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"tags": []
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},
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@ -226,7 +218,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "baf2371d25d543739572153d8e331efa",
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"model_id": "bb4daff9ec66456ab58f00021b778efd",
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"version_major": 2,
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"version_minor": 0
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},
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@ -243,7 +235,7 @@
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"<function __main__.spectrum_widget(tree=<class 'sap.trees.MaxTree'>, x='area', y='compactness', x_log=True, y_log=False, hillshade_overlay=True, highlight=False)>"
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]
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},
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"execution_count": 8,
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"execution_count": 90,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -320,6 +312,8 @@
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" x1, x2 = model['x1'], model['x2']\n",
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" y1, y2 = model['y1'], model['y2']\n",
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" \n",
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" model['ax_dtm'].clear()\n",
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"\n",
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" # No filter\n",
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" if x1 == x2 == y1 == y2 == 0:\n",
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" if not model['overlay']:\n",
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@ -337,7 +331,6 @@
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"\n",
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" img = model['tree_cache'].reconstruct((X < x1) | (X > x2) | (Y < y1) | (Y > y2), filtering='subtractive')\n",
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" \n",
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" model['ax_dtm'].clear()\n",
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" if not model['overlay']:\n",
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" model['ax_dtm'].imshow(img)\n",
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" else:\n",
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@ -408,6 +401,164 @@
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" y=sap.available_attributes().keys())"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 58,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[('AlphaTree', sap.trees.AlphaTree),\n",
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" ('MaxTree', sap.trees.MaxTree),\n",
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" ('MinTree', sap.trees.MinTree),\n",
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" ('OmegaTree', sap.trees.OmegaTree),\n",
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" ('TosTree', sap.trees.TosTree)]"
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]
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},
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"execution_count": 58,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"inspect.getmembers(sap.trees, lambda t: inspect.isclass(t) and issubclass(t, sap.Tree) and t != sap.Tree)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 87,
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_tile():\n",
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" model['im'] = rio.open(get_tile(model['lidar_feature'].value, model['tile_name'].value)).read()[0]\n",
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" model['im_hs'] = ui8_clip(hillshades(model['im']), -1, 1)\n",
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" model['im_hs_alpha'] = ((model['im_hs'].astype(float) - 127) / 127) ** 2 * .4\n",
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" kwargs = {}\n",
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" kwargs['vmin'], kwargs['vmax'] = np.quantile(model['im'], (.01, .99))\n",
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" model['im_kwargs'] = kwargs\n",
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" model['im_mesh'] = np.meshgrid(np.arange(model['im'].shape[1]), np.arange(model['im'].shape[0]))\n",
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"\n",
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"def load_tree():\n",
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" model['tree_cache'] = model['tree_type'].value(model['im'])\n",
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"\n",
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"def reset_selections():\n",
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" model.update({\n",
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" 'x1': 0,\n",
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" 'x2': 0,\n",
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" 'y1': 0,\n",
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" 'y2': 0,\n",
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" 'dtm_x1': 0,\n",
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" 'dtm_x2': 0,\n",
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" 'dtm_y1': 0,\n",
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" 'dtm_y2': 0,\n",
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" 'overlay': True,\n",
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" 'highlight': False\n",
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"})"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 89,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "db0b0312a8e44889a7bfd821b6578afe",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"HBox(children=(Dropdown(description='Tile ID', options=('-11_7', '-12_-1', '-13_-3', '-10_-1', '-4_4', '-9_1',…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"model['lidar_feature'] = ipw.Dropdown(description='LiDAR feature', options=lidar_features)\n",
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"model['tile_name'] = ipw.Dropdown(description='Tile ID', options=tile_names)\n",
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"model['tree_type'] = ipw.Dropdown(description='Hierarchy', value=sap.trees.MaxTree, options=inspect.getmembers(sap.trees, lambda t: inspect.isclass(t) and issubclass(t, sap.Tree) and t != sap.Tree))\n",
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"load_button = ipw.Button(description='Analyse', icon='rocket')\n",
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"\n",
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"\n",
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"def load_change(change):\n",
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" print('Loading tile...')\n",
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" load_tile()\n",
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" print('Loading tree...')\n",
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" load_tree()\n",
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" print('Loading complete')\n",
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" reset_selections()\n",
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" show_spectrum()\n",
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" filter_dtm()\n",
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" plt.show()\n",
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"\n",
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"lidar_feature.observe(feature_change, names='value')\n",
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"tile_name.observe(name_change, names='value')\n",
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"tree_type.observe(tree_change, names='value')\n",
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"load_button.on_click(load_change)\n",
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"\n",
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"ipw.HBox([model['tile_name'], model['lidar_feature'], model['tree_type'] , load_button])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 82,
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"metadata": {},
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"outputs": [],
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"source": [
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"tree_type.value = sap.trees.MinTree"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'ndsm'"
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]
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},
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"execution_count": 26,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"lidar_feature.value"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"outputs": [],
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"source": [
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"def feature_change(change):\n",
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" print(feature)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"<ipython-input-18-012395bc2283>:1: DeprecationWarning: on_trait_change is deprecated in traitlets 4.1: use observe instead\n",
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" lidar_feature.on_trait_change(ld)\n"
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]
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}
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],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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