Update jupyter notebook tutorial.

Author: binarybottle

docs/mindboggle_tutorial.ipynb

@@ -6,12 +6,13 @@
    "source": [
     "<img align=\"left\" style=\"padding-right:10px; width:150px;\" src=\"https://mfr.osf.io/export?url=https://osf.io/q7ym9/?action=download%26direct%26mode=render&initialWidth=673&childId=mfrIframe&format=1200x1200.jpeg\">\n",
     "<font size=\"1\">\n",
-    "This jupyter notebook provides a tutorial for [Mindboggle](http://mindboggle.info), and assumes that you have ``[1]`` entered the bash shell of a docker container from your $HOST (e.g., /Users/arno) and ``[2]`` that the notebook is running within the container:\n",
+    "This jupyter notebook provides a tutorial for [Mindboggle](http://mindboggle.info), and assumes that you have [1] entered the bash shell of a docker container from your \\$HOST (e.g., /Users/arno) and [2] that the notebook is running within the container:\n",
     "<br>\n",
-    "&nbsp;&nbsp;[1] ``docker run --rm -ti -v $HOST:/home/jovyan/work -p 8888:8888 --entrypoint /bin/bash nipy/mindboggle``<br>\n",
-    "&nbsp;&nbsp;[2] ``jupyter notebook /opt/mindboggle/docs/mindboggle_tutorial.ipynb``\n",
+    "[1] docker run --rm -ti -v \\$HOST:/home/jovyan/work -p 8888:8888 --entrypoint /bin/bash nipy/mindboggle\n",
     "<br>\n",
-    "&nbsp;&nbsp;-- <a href=\"http://binarybottle.com\">Arno Klein</a> and Anisha Keshavan (please refer to the [Mindboggle reference](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005350#sec007))\n",
+    "[2] jupyter notebook /opt/mindboggle/docs/mindboggle_tutorial.ipynb\n",
+    "<br>\n",
+    "-- <a href=\"http://binarybottle.com\">Arno Klein</a> and Anisha Keshavan (please refer to the [Mindboggle reference](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005350#sec007))\n",
     "</font>"
    ]
   },
@@ -179,7 +180,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],
@@ -366,26 +366,12 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "ls /opt/conda/lib/python3.5/site-packages/nbpapaya/Papaya/release/current/standard/papaya.js"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "from nbpapaya import Overlay\n",
-    "Overlay"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -397,9 +383,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from mindboggle.mio.plots import histograms_of_lists\n",
@@ -421,9 +405,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from mindboggle.features.folds import find_depth_threshold\n",
@@ -443,9 +425,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from mindboggle.features.folds import extract_folds\n",
@@ -493,11 +473,11 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],
    "source": [
+    "import numpy as np\n",
     "just_folds = np.ones(len(folds))\n",
     "df = pd.DataFrame(just_folds, columns=[\"folds\"])\n",
     "df.to_csv('folds.csv', index=False)\n",
@@ -573,7 +553,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
@@ -591,6 +570,37 @@
     "n_sulci"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Remove all vertices but the sulci:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#from mindboggle.mio.vtks import rewrite_scalars\n",
+    "#rewrite_scalars(input_vtk=depth_file,\n",
+    "#                output_vtk='sulci_depth.vtk',\n",
+    "#                new_scalars=[depths, sulci],\n",
+    "#                new_scalar_names=['depth', 'sulci'],\n",
+    "#                filter_scalars=sulci,\n",
+    "#                background_value=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#sulci_depths = [depths[i] for i,x in enumerate(depths) if sulci[i] != -1]"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -602,14 +612,13 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],
    "source": [
-    "df = pd.DataFrame(sulci, columns=[\"sulci\"])\n",
+    "df = pd.DataFrame(depths, columns=[\"sulci\"])\n",
     "df.to_csv('sulci.csv', index=False)\n",
-    "MeshOpts = getMeshOpts('sulci.vtk', \"sulci.csv\" , 1,10,1)\n",
+    "MeshOpts = getMeshOpts(sulci_file, \"sulci.csv\" , 1,10,1)\n",
     "Overlay(MeshOpts)"
    ]
   },
@@ -623,9 +632,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "from mindboggle.mio.tables import write_shape_stats\n",
@@ -653,9 +660,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "pd.read_csv(sulcus_table)"
@@ -673,7 +678,7 @@
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3.0
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
@@ -684,5 +689,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
-}
+ "nbformat_minor": 1
+}