Add --roygbiv to README examples

Author: binarybottle

README.rst

@@ -185,20 +185,25 @@ To learn about Mindboggle's command options, type this in a terminal window::
     mindboggle -h
 
 **Example 1:**
-This command runs Mindboggle on data run through FreeSurfer but not ANTs::
+Run Mindboggle on data processed by FreeSurfer but not ANTs::
 
     mindboggle $FREESURFER_SUBJECT --out $OUT
 
 **Example 2:**
+Same as Example 1 with output to visualize surface data with roygbiv::
+
+    mindboggle $FREESURFER_SUBJECT --out $OUT --roygbiv
+
+**Example 3:**
 Take advantage of ANTs output as well ("\\" splits for readability)::
 
-    mindboggle $FREESURFER_SUBJECT --out $OUT \
+    mindboggle $FREESURFER_SUBJECT --out $OUT --roygbiv \
         --ants $ANTS_SUBJECT/antsBrainSegmentation.nii.gz
 
-**Example 3:**
+**Example 4:**
 Generate only volume (no surface) labels and shapes::
 
-    mindboggle $FREESURFER_SUBJECT --out $OUT \
+    mindboggle $FREESURFER_SUBJECT --out $OUT --roygbiv \
         --ants $ANTS_SUBJECT/antsBrainSegmentation.nii.gz \
         --no_surfaces
 

docs/mindboggle_tutorial.ipynb

@@ -6,13 +6,12 @@
    "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 $HOST (e.g., /Users/arno) and ``[2]`` that the notebook is running within the container:\n",
     "<br>\n",
-    "[1] docker run --rm -ti -v \\$HOST:/home/jovyan/work -p 8888:8888 --entrypoint /bin/bash nipy/mindboggle\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",
     "<br>\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",
+    "&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",
     "</font>"
    ]
   },
@@ -180,6 +179,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],
@@ -366,12 +366,26 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "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": {},
@@ -383,7 +397,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from mindboggle.mio.plots import histograms_of_lists\n",
@@ -405,7 +421,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from mindboggle.features.folds import find_depth_threshold\n",
@@ -425,7 +443,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from mindboggle.features.folds import extract_folds\n",
@@ -473,11 +493,11 @@
    "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",
@@ -553,6 +573,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
@@ -570,37 +591,6 @@
     "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": {},
@@ -612,13 +602,14 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],
    "source": [
-    "df = pd.DataFrame(depths, columns=[\"sulci\"])\n",
+    "df = pd.DataFrame(sulci, columns=[\"sulci\"])\n",
     "df.to_csv('sulci.csv', index=False)\n",
-    "MeshOpts = getMeshOpts(sulci_file, \"sulci.csv\" , 1,10,1)\n",
+    "MeshOpts = getMeshOpts('sulci.vtk', \"sulci.csv\" , 1,10,1)\n",
     "Overlay(MeshOpts)"
    ]
   },
@@ -632,7 +623,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "from mindboggle.mio.tables import write_shape_stats\n",
@@ -660,7 +653,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "pd.read_csv(sulcus_table)"
@@ -678,7 +673,7 @@
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3
+    "version": 3.0
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
@@ -689,5 +684,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
-}
+ "nbformat_minor": 0
+}