From ec3c6f65e9e8f36d56dcced6d3e8ca1c32830519 Mon Sep 17 00:00:00 2001
From: Michiel Cottaar <MichielCottaar@gmail.com>
Date: Fri, 16 Feb 2018 14:16:19 +0000
Subject: [PATCH] BUG: updated the ipython notebook files
---
talks/nibabel_cifti/nibabel_cifti.ipynb | 183 ++++--------------------
talks/packages/packages.ipynb | 90 +-----------
2 files changed, 29 insertions(+), 244 deletions(-)
diff --git a/talks/nibabel_cifti/nibabel_cifti.ipynb b/talks/nibabel_cifti/nibabel_cifti.ipynb
index a98c7aa..890f974 100644
--- a/talks/nibabel_cifti/nibabel_cifti.ipynb
+++ b/talks/nibabel_cifti/nibabel_cifti.ipynb
@@ -2,18 +2,9 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/Users/ndcn0236/miniconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
- " from ._conv import register_converters as _register_converters\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"%matplotlib nbagg\n",
"import numpy as np\n",
@@ -50,9 +41,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"img = nib.load('100307/T1w.nii.gz')\n",
@@ -74,9 +63,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"img = nib.load('100307/fsaverage_LR32k/100307.L.white.32k_fs_LR.surf.gii')\n",
@@ -87,9 +74,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"from nibabel import freesurfer\n",
@@ -98,21 +83,9 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "array([2.9977965, 2.7661548, 3.0803757, ..., 2.47089 , 2.2333388,\n",
- " 2.363499 ], dtype=float32)"
- ]
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"thickness = nib.load('100307/fsaverage_LR32k/100307.L.thickness.32k_fs_LR.shape.gii').darrays[0].data\n",
"thickness"
@@ -153,9 +126,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"!pip install git+https://github.com/MichielCottaar/cifti.git"
@@ -172,7 +143,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -188,9 +159,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii random_ctx.dscalar.nii"
@@ -198,26 +167,24 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
- "img = ni.load('100307/aparc+aseg.nii.gz')\n",
+ "img = nib.load('100307/aparc+aseg.nii.gz')\n",
"cerebellum = img.get_data() == 8\n",
"\n",
"bm_cerebellum = cifti.BrainModel.from_mask(cerebellum, name='CerebellumLeft', affine=img.affine)\n",
"bm = bm_ctx + bm_cerebellum\n",
- "sc = cifti.Scalar.from_names(['random'])\n",
- "arr = np.random.rand(len(bm))\n",
- "cifti.write('random_ctx_cerebellum.dscalar.nii', arr[None, :], (sc, bm))"
+ "sc = cifti.Scalar.from_names(['random1', 'random2'])\n",
+ "arr = np.random.rand(2, len(bm))\n",
+ "cifti.write('random_ctx_cerebellum.dscalar.nii', arr, (sc, bm))"
]
},
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii 100307/T1w.nii.gz random_ctx_cerebellum.dscalar.nii"
@@ -226,9 +193,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"arr = abs(thickness[ctx, None] - thickness[None, ctx])\n",
@@ -238,9 +203,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii diff_thickness.dconn.nii"
@@ -255,10 +218,8 @@
},
{
"cell_type": "code",
- "execution_count": 7,
- "metadata": {
- "collapsed": true
- },
+ "execution_count": null,
+ "metadata": {},
"outputs": [],
"source": [
"parcels = cifti.Parcels.from_brain_models([('thin', bm_ctx[thickness[ctx] < 2]),\n",
@@ -266,7 +227,9 @@
" ('thick', bm_ctx[thickness[ctx] > 3]),\n",
" ])\n",
"scl = cifti.Scalar.from_names(['rgb'])\n",
- "label = scl.to_label([{1: ('red', (1, 0, 0, 1)), 2: ('green', (0, 1, 0, 1)), 3: ('blue', (0, 0, 1, 1))}])\n",
+ "label = scl.to_label([{1: ('red', (1, 0, 0, 1)),\n",
+ " 2: ('green', (0, 1, 0, 1)),\n",
+ " 3: ('blue', (0, 0, 1, 1))}])\n",
"arr = np.array([[1, 2, 3]])\n",
"cifti.write('labels.plabel.nii', arr, (label, parcels))"
]
@@ -275,109 +238,13 @@
"cell_type": "code",
"execution_count": null,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "\n",
- "Info: Resources loaded:\n",
- " :/About :/Cursor :/Fonts :/HelpFiles :/LayersPanel :/PaletteSettings :/resources.qrc :/SpecFileDialog :/Splash :/ToolBar :/trolltech :/update_resources.sh\n",
- "\n",
- "\n",
- "Info: Time to color volume data is 0.581 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/T1w.nii.gz was 1.06257 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.L.inflated.32k_fs_LR.surf.gii was 0.111264 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.L.midthickness.32k_fs_LR.surf.gii was 0.019432 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.L.pial.32k_fs_LR.surf.gii was 0.019506 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.L.very_inflated.32k_fs_LR.surf.gii was 0.019134 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.L.white.32k_fs_LR.surf.gii was 0.018743 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.R.inflated.32k_fs_LR.surf.gii was 0.087767 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.R.midthickness.32k_fs_LR.surf.gii was 0.019677 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.R.pial.32k_fs_LR.surf.gii was 0.019088 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.R.very_inflated.32k_fs_LR.surf.gii was 0.019656 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/100307/fsaverage_LR32k/100307.R.white.32k_fs_LR.surf.gii was 0.018397 seconds.\n",
- "\n",
- "\n",
- "Info: Time to read /Users/ndcn0236/Work/projects/pytreat-2018-practicals/talks/nibabel_cifti/labels.plabel.nii was 0.651135 seconds.\n",
- "\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii 100307/T1w.nii.gz labels.plabel.nii"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "collapsed": true
- },
- "outputs": [],
- "source": []
}
],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.6.2"
- },
- "toc": {
- "colors": {
- "hover_highlight": "#DAA520",
- "running_highlight": "#FF0000",
- "selected_highlight": "#FFD700"
- },
- "moveMenuLeft": true,
- "nav_menu": {
- "height": "176px",
- "width": "252px"
- },
- "navigate_menu": true,
- "number_sections": true,
- "sideBar": true,
- "threshold": 4,
- "toc_cell": false,
- "toc_section_display": "block",
- "toc_window_display": false
- }
- },
+ "metadata": {},
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/talks/packages/packages.ipynb b/talks/packages/packages.ipynb
index 0c2b66f..84bc379 100644
--- a/talks/packages/packages.ipynb
+++ b/talks/packages/packages.ipynb
@@ -32,7 +32,10 @@
"source": [
"Numpy includes support for:\n",
"- N-dimensional arrays with various datatypes\n",
- "- basic functions (e.g., polynomials)\n",
+ " - masked arrays\n",
+ " - matrices\n",
+ " - structured/record array\n",
+ "- basic functions (e.g., sin, log, arctan, polynomials)\n",
"- basic linear algebra\n",
"- random number generation\n",
"\n",
@@ -513,91 +516,6 @@
"## Neuroimage packages\n",
"The [nipy](http://nipy.org/) ecosystem covers most of these.\n",
"\n",
- "### [CIFTI](https://github.com/MichielCottaar/cifti): easy creation/manipulation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import nibabel\n",
- "thickness = nibabel.load('100307/fsaverage_LR32k/100307.L.thickness.32k_fs_LR.shape.gii').darrays[0].data\n",
- "thickness"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "import cifti\n",
- "ctx = thickness != 0\n",
- "arr = np.random.rand(ctx.sum())\n",
- "\n",
- "bm_ctx = cifti.BrainModel.from_mask(ctx, name='CortexLeft')\n",
- "sc = cifti.Scalar.from_names(['random'])\n",
- "cifti.write('random_ctx.dscalar.nii', arr[None, :], (sc, bm_ctx))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii random_ctx.dscalar.nii"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "img = nibabel.load('100307/aparc+aseg.nii.gz')\n",
- "cerebellum = img.get_data() == 8\n",
- "\n",
- "bm = bm_ctx + cifti.BrainModel.from_mask(cerebellum, name='CerebellumLeft', affine=img.affine)\n",
- "sc = cifti.Scalar.from_names(['random'])\n",
- "arr = np.random.rand(len(bm))\n",
- "cifti.write('random_ctx_cerebellum.dscalar.nii', arr[None, :], (sc, bm))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii 100307/aparc+aseg.nii.gz random_ctx_cerebellum.dscalar.nii"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "arr = abs(thickness[ctx, None] - thickness[None, ctx])\n",
- "cifti.write('diff_thickness.dconn.nii', arr, (bm_ctx, bm_ctx))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "!wb_view 100307/fsaverage_LR32k/100307.*.32k_fs_LR.surf.gii diff_thickness.dconn.nii"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
"## [networkx](https://networkx.github.io/): graph theory\n",
"\n",
"## GUI\n",
--
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