{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotly\n",
    "from plotly.graph_objs import FigureWidget\n",
    "from plotly.callbacks import Points, InputDeviceState\n",
    "\n",
    "# pandas\n",
    "import pandas as pd\n",
    "\n",
    "# numpy\n",
    "import numpy as np\n",
    "\n",
    "# scikit learn\n",
    "from sklearn import datasets\n",
    "\n",
    "# ipywidgets\n",
    "from ipywidgets import HBox, VBox, Button\n",
    "\n",
    "# functools\n",
    "from functools import partial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width\n",
       "0           5.1          3.5           1.4          0.2\n",
       "1           4.9          3.0           1.4          0.2\n",
       "2           4.7          3.2           1.3          0.2\n",
       "3           4.6          3.1           1.5          0.2\n",
       "4           5.0          3.6           1.4          0.2"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load iris dataset\n",
    "iris_data = datasets.load_iris()\n",
    "feature_names = [name.replace(' (cm)', '').replace(' ', '_') for name in iris_data.feature_names]\n",
    "iris_df = pd.DataFrame(iris_data.data, columns=feature_names)\n",
    "iris_class = iris_data.target + 1\n",
    "N = len(iris_df)\n",
    "iris_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "version_minor": 0
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      "text/plain": [
       "FigureWidget({\n",
       "    'data': [{'marker': {'cmax': 1.5,\n",
       "                         'cmin': -0.5,\n",
       "                  …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f1 = FigureWidget(**{\n",
    "    'data': [{'marker': {'cmax': 1.5,\n",
    "                         'cmin': -0.5,\n",
    "                         'color': np.zeros(N),\n",
    "                         'colorbar': {'ticks': 'outside', 'ticktext': ['unselected', 'selected'], 'tickvals': [0, 1]},\n",
    "                         'colorscale': [[0, 'lightgray'], [0.5, 'lightgray'],\n",
    "                                        [0.5, 'red'], [1, 'red']],\n",
    "                         'showscale': False,\n",
    "                         'size': 8},\n",
    "              'mode': 'markers',\n",
    "              'type': 'scatter',\n",
    "              'uid': '9fb32f14-6f15-11e8-973c-645aede86e5b',\n",
    "              'x': iris_df.sepal_length,\n",
    "              'y': iris_df.petal_width}],\n",
    "    'layout': {'dragmode': 'lasso', 'width': 500}\n",
    "})\n",
    "scatt1 = f1.data[0]\n",
    "f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "4c51444614944c4b86845955abea9af5",
       "version_major": 2,
       "version_minor": 0
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      "text/plain": [
       "FigureWidget({\n",
       "    'data': [{'marker': {'cmax': 1.5,\n",
       "                         'cmin': -0.5,\n",
       "                  …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f2 = FigureWidget(**{\n",
    "    'data': [{'marker': {'cmax': 1.5,\n",
    "                         'cmin': -0.5,\n",
    "                         'color': np.zeros(N),\n",
    "                         'colorbar': {'ticks': 'outside', 'ticktext': ['unselected', 'selected'], 'tickvals': [0, 1]},\n",
    "                         'colorscale': [[0, 'lightgray'], [0.5, 'lightgray'],\n",
    "                                        [0.5, 'red'], [1, 'red']],\n",
    "                         'size': 8},\n",
    "              'mode': 'markers',\n",
    "              'type': 'scatter',\n",
    "              'uid': 'e3f13218-6f15-11e8-b2a9-645aede86e5b',\n",
    "              'x': iris_df.petal_length,\n",
    "              'y': iris_df.sepal_width}],\n",
    "    'layout': {'dragmode': 'lasso', 'width': 500, 'xaxis': {'title': 'petal_length'}, 'yaxis': {'title': 'sepal_width'}}\n",
    "})\n",
    "scatt2 = f2.data[0]\n",
    "f2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure brush on both plots to update both plots\n",
    "def brush(trace, points, state):\n",
    "    inds = np.array(points.point_inds)\n",
    "    if inds.size:\n",
    "        selected = scatt1.marker.color.copy()\n",
    "        selected[inds] = 1\n",
    "        scatt1.marker.color = selected\n",
    "        scatt2.marker.color = selected    \n",
    "    \n",
    "scatt1.on_selection(brush)\n",
    "scatt2.on_selection(brush)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "d1c1be71a89b4645968b388757c89fe4",
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      },
      "text/plain": [
       "Button(description='clear', style=ButtonStyle())"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reset brush\n",
    "def reset_brush(btn):\n",
    "    selected = np.zeros(iris_class.size)\n",
    "    scatt1.marker.color = selected\n",
    "    scatt2.marker.color = selected\n",
    "    \n",
    "# Create reset button\n",
    "button = Button(description=\"clear\")\n",
    "button.on_click(reset_brush)\n",
    "button"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "8c239aac5f54409d85592c22ed25cb82",
       "version_major": 2,
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      "text/plain": [
       "VBox(children=(HBox(children=(FigureWidget({\n",
       "    'data': [{'marker': {'cmax': 1.5,\n",
       "                         'c…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dashboard = VBox([HBox([f1, f2]), button])\n",
    "dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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