Merge branch 'main' of github.com:gallantlab/voxelwise_tutorials into main

* 'main' of github.com:gallantlab/voxelwise_tutorials:
  DOC update website text

Author: mvdoc

doc/index.rst

@@ -11,13 +11,22 @@ Getting started
 This website contains tutorials describing how to use the
 `voxelwise modeling framework <voxelwise_modeling.html>`_.
 
-The tutorials consist of Python scripts, which are rendered in a `gallery of
-examples <_auto_examples/index.html>`_. Each Python script is also available as
-a Jupyter notebook (non-rendered). The tutorials are best explored in
-order, starting with the "Movies 3T tutorial".
-
-To run the tutorials yourself, we recommend to download the project on GitHub
-at `gallantlab/voxelwise_tutorials
+To explore these tutorials, one can:
+
+- read the rendered examples in the tutorials
+  `gallery of examples <_auto_examples/index.html>`_ (recommended)
+- run the Python scripts located in the GitHub repository (`tutorials <https://github.com/gallantlab/voxelwise_tutorials/tree/main/tutorials>`_ directory)
+- run the Jupyter notebooks located in the GitHub repository 
+  (`tutorials/notebooks
+  <https://github.com/gallantlab/voxelwise_tutorials/tree/main/tutorials/notebooks>`_
+  directory)
+- run the merged notebook in
+  `Colab <https://colab.research.google.com/github/gallantlab/voxelwise_tutorials/blob/main/tutorials/notebooks/movies_3T/merged_for_colab.ipynb>`_.
+
+The tutorials are best explored in order, starting with the "Movies 3T"
+tutorial.
+
+The project is available on GitHub at `gallantlab/voxelwise_tutorials
 <https://github.com/gallantlab/voxelwise_tutorials>`_. On top of the tutorials,
 the GitHub repository contains a Python package called ``voxelwise_tutorials``,
 which contains useful functions to download the data sets, load the files,

doc/voxelwise_package.rst

@@ -12,7 +12,14 @@ results.
 Installation
 ------------
 
-To install the ``voxelwise_tutorials`` package, run
+To install the ``voxelwise_tutorials`` package, run:
+
+.. code-block:: bash
+
+   pip install voxelwise_tutorials
+
+
+To also download the tutorial scripts and notebooks, clone the repository via:
 
 .. code-block:: bash
 

tutorials/movies_3T/00_load_colab.py

@@ -41,7 +41,7 @@
 # Uncomment and run the following command to check that Google Drive was
 # correctly mounted.
 
-# !ls 'drive' && echo SUCCESS || echo FAILURE
+# !ls drive/MyDrive/vim-5
 
 ###############################################################################
 # Tell the voxelwise_tutorials package where the data is. (If you placed the

tutorials/movies_3T/02_plot_wordnet_model.py

@@ -493,4 +493,4 @@
 # .. [2] Saunders, C., Gammerman, A., & Vovk, V. (1998).
 #    Ridge regression learning algorithm in dual variables.
 
-del pipeline
+del pipeline, kernel_ridge_cv

tutorials/movies_3T/03_plot_hemodynamic_response.py

@@ -252,4 +252,4 @@
 # weights. Note that in this dataset, the brain responses are recorded every
 # two seconds.
 
-del pipeline
+del pipeline, pipeline_no_delay