Test net updating.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test Network Updating when loading new data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from clustergrammer_widget import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# generate random matrix\n",
    "num_rows = 500\n",
    "num_cols = 10\n",
    "np.random.seed(seed=100)\n",
    "mat = np.random.rand(num_rows, num_cols)\n",
    "\n",
    "# make row and col labels\n",
    "rows = range(num_rows)\n",
    "cols = range(num_cols)\n",
    "rows = [str(i) for i in rows]\n",
    "cols = [str(i) for i in cols]\n",
    "\n",
    "# make dataframe \n",
    "df = pd.DataFrame(data=mat, columns=cols, index=rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "net = Network()\n",
    "net.load_df(df)\n",
    "net.make_clust()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bbd0a29325b045e98eaab48bd14e78bc"
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "clustergrammer_widget(network=net.widget())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "net.filter_N_top('row', 10, 'sum')\n",
    "small_df = net.export_df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "model_id": "8b4fbd2c08ea4f67b7234b47095edbf7"
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   "source": [
    "net.load_df(small_df)\n",
    "net.make_clust()\n",
    "clustergrammer_widget(network=net.widget())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data from File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "model_id": "ec5cca206bd649cb873aa4773253eb61"
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   "source": [
    "net.load_file('txt/rc_two_cats.txt')\n",
    "net.make_clust()\n",
    "clustergrammer_widget(network=net.widget())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Loading new data into `net` appears to be working correctly, will test in nbviewer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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\"#ff7f0e\"}}, \"row\": {\"cat-0\": {\"Gene Type: Interesting\": \"#393b79\", \"Gene Type: Not Interesting\": \"#eee\"}}}, \"row_nodes\": [{\"group\": [10.0, 9.0, 8.0, 5.0, 5.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: CDK4\", \"clust\": 14, \"cat_0_index\": 0, \"rank\": 30, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 20, \"ini\": 38}, {\"group\": [21.0, 20.0, 19.0, 13.0, 11.0, 5.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: LMTK3\", \"clust\": 20, \"cat_0_index\": 17, \"rank\": 28, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 24, \"ini\": 37}, {\"group\": [26.0, 25.0, 22.0, 16.0, 13.0, 6.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: LRRK2\", \"clust\": 26, \"cat_0_index\": 18, \"rank\": 9, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 10, \"ini\": 36}, {\"group\": [28.0, 27.0, 24.0, 18.0, 14.0, 6.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: UHMK1\", \"clust\": 25, \"cat_0_index\": 19, \"rank\": 26, \"cat-0\": \"Gene Type: Not Interesting\", 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\"cat_0_index\": 11, \"rank\": 37, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 31, \"ini\": 12}, {\"group\": [18.0, 17.0, 16.0, 10.0, 9.0, 4.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: GRK1\", \"clust\": 19, \"cat_0_index\": 32, \"rank\": 15, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 23, \"ini\": 11}, {\"group\": [38.0, 37.0, 34.0, 26.0, 20.0, 8.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: ROS1\", \"clust\": 37, \"cat_0_index\": 12, \"rank\": 31, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 37, \"ini\": 10}, {\"group\": [15.0, 14.0, 13.0, 8.0, 7.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: MAP2K4\", \"clust\": 10, \"cat_0_index\": 13, \"rank\": 23, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 28, \"ini\": 9}, {\"group\": [27.0, 26.0, 23.0, 17.0, 13.0, 6.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: SRC\", \"clust\": 27, \"cat_0_index\": 14, \"rank\": 21, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 21, \"ini\": 8}, {\"group\": [19.0, 18.0, 17.0, 11.0, 9.0, 4.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: TGFBR1\", \"clust\": 17, \"cat_0_index\": 15, \"rank\": 12, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 13, \"ini\": 7}, {\"group\": [2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: CAMK2B\", \"clust\": 5, \"cat_0_index\": 33, \"rank\": 3, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 17, \"ini\": 6}, {\"group\": [9.0, 8.0, 7.0, 4.0, 4.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: STK24\", \"clust\": 6, \"cat_0_index\": 16, \"rank\": 0, \"cat-0\": \"Gene Type: Interesting\", \"rankvar\": 36, \"ini\": 5}, {\"group\": [5.0, 4.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: DCLK3\", \"clust\": 1, \"cat_0_index\": 34, \"rank\": 5, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 25, \"ini\": 4}, {\"group\": [25.0, 24.0, 21.0, 15.0, 12.0, 6.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: LATS1\", \"clust\": 22, \"cat_0_index\": 35, \"rank\": 29, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 27, \"ini\": 3}, {\"group\": [6.0, 5.0, 4.0, 2.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: NEK9\", \"clust\": 0, \"cat_0_index\": 36, \"rank\": 4, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 6, \"ini\": 2}, {\"group\": [30.0, 29.0, 26.0, 19.0, 15.0, 7.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Gene: MYLK3\", \"clust\": 29, \"cat_0_index\": 37, \"rank\": 32, \"cat-0\": \"Gene Type: Not Interesting\", \"rankvar\": 35, \"ini\": 1}], \"col_nodes\": [{\"group\": [15.0, 15.0, 15.0, 15.0, 12.0, 10.0, 5.0, 2.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H1650\", \"clust\": 12, \"cat_1_index\": 10, \"cat_0_index\": 24, \"rank\": 6, \"cat-1\": \"Gender: Male\", \"ini\": 29, \"cat-0\": \"Category: two\", \"rankvar\": 4}, {\"group\": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H23\", \"clust\": 2, \"cat_1_index\": 11, \"cat_0_index\": 25, \"rank\": 17, \"cat-1\": \"Gender: 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\"name\": \"Cell Line: HCC78\", \"clust\": 21, \"cat_1_index\": 17, \"cat_0_index\": 1, \"rank\": 25, \"cat-1\": \"Gender: Male\", \"ini\": 20, \"cat-0\": \"Category: five\", \"rankvar\": 27}, {\"group\": [11.0, 11.0, 11.0, 11.0, 9.0, 8.0, 4.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H1666\", \"clust\": 7, \"cat_1_index\": 2, \"cat_0_index\": 6, \"rank\": 18, \"cat-1\": \"Gender: Female\", \"ini\": 19, \"cat-0\": \"Category: four\", \"rankvar\": 15}, {\"group\": [18.0, 18.0, 18.0, 18.0, 14.0, 11.0, 6.0, 3.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H661\", \"clust\": 16, \"cat_1_index\": 18, \"cat_0_index\": 2, \"rank\": 3, \"cat-1\": \"Gender: Male\", \"ini\": 18, \"cat-0\": \"Category: five\", \"rankvar\": 26}, {\"group\": [16.0, 16.0, 16.0, 16.0, 13.0, 11.0, 6.0, 3.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H838\", \"clust\": 17, \"cat_1_index\": 19, \"cat_0_index\": 3, \"rank\": 7, \"cat-1\": \"Gender: Male\", \"ini\": 17, \"cat-0\": \"Category: five\", \"rankvar\": 23}, {\"group\": [12.0, 12.0, 12.0, 12.0, 10.0, 9.0, 5.0, 2.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H1703\", \"clust\": 14, \"cat_1_index\": 20, \"cat_0_index\": 4, \"rank\": 11, \"cat-1\": \"Gender: Male\", \"ini\": 16, \"cat-0\": \"Category: five\", \"rankvar\": 21}, {\"group\": [21.0, 21.0, 21.0, 21.0, 17.0, 13.0, 7.0, 4.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: CALU-3\", \"clust\": 19, \"cat_1_index\": 21, \"cat_0_index\": 7, \"rank\": 8, \"cat-1\": \"Gender: Male\", \"ini\": 15, \"cat-0\": \"Category: four\", \"rankvar\": 7}, {\"group\": [17.0, 17.0, 17.0, 17.0, 13.0, 11.0, 6.0, 3.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H2342\", \"clust\": 18, \"cat_1_index\": 3, \"cat_0_index\": 8, \"rank\": 26, \"cat-1\": \"Gender: Female\", \"ini\": 14, \"cat-0\": \"Category: four\", \"rankvar\": 22}, {\"group\": [26.0, 26.0, 26.0, 25.0, 19.0, 15.0, 8.0, 4.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H2228\", \"clust\": 26, \"cat_1_index\": 4, \"cat_0_index\": 15, \"rank\": 2, \"cat-1\": \"Gender: 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1.0, 1.0], \"name\": \"Cell Line: H1734\", \"clust\": 24, \"cat_1_index\": 6, \"cat_0_index\": 17, \"rank\": 19, \"cat-1\": \"Gender: Female\", \"ini\": 5, \"cat-0\": \"Category: one\", \"rankvar\": 18}, {\"group\": [14.0, 14.0, 14.0, 14.0, 11.0, 9.0, 5.0, 2.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: LOU-NH91\", \"clust\": 13, \"cat_1_index\": 7, \"cat_0_index\": 5, \"rank\": 15, \"cat-1\": \"Gender: Female\", \"ini\": 4, \"cat-0\": \"Category: five\", \"rankvar\": 16}, {\"group\": [2.0, 2.0, 2.0, 2.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: HCC44\", \"clust\": 3, \"cat_1_index\": 8, \"cat_0_index\": 11, \"rank\": 14, \"cat-1\": \"Gender: Female\", \"ini\": 3, \"cat-0\": \"Category: four\", \"rankvar\": 2}, {\"group\": [8.0, 8.0, 8.0, 8.0, 6.0, 5.0, 3.0, 1.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: A549\", \"clust\": 9, \"cat_1_index\": 28, \"cat_0_index\": 12, \"rank\": 21, \"cat-1\": \"Gender: Male\", \"ini\": 2, \"cat-0\": \"Category: four\", \"rankvar\": 3}, {\"group\": [25.0, 25.0, 25.0, 24.0, 19.0, 15.0, 8.0, 4.0, 1.0, 1.0, 1.0], \"name\": \"Cell Line: H1781\", \"clust\": 28, \"cat_1_index\": 9, \"cat_0_index\": 18, \"rank\": 13, \"cat-1\": \"Gender: Female\", \"ini\": 1, \"cat-0\": \"Category: one\", \"rankvar\": 13}]}",
       "viz_title": "updating python by restarting kernel"
      }
     }
    },
    "version_major": 1,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}