DOC clarify that the data is not available yet

Author: TomDLT

tutorials/movies_3T/00_download_vim4.py

@@ -3,28 +3,32 @@
 Download the data set from CRCNS
 ================================
 
-In this script, we download the data set from CRCNS.
-A (free) account is required.
+In this script, we download the data set from CRCNS. A (free) account is
+required.
+
+.. Warning:: The data has not been publicly released yet, so this notebook will
+    not work !
 
 Cite this data set
 ------------------
 
-This tutorial is based on publicly available data
-`published on CRCNS <https://crcns.org/data-sets/vc/TBD>`_.
-If you publish any work using this data set, please cite the original
-publication [1]_, and the data set [2]_.
+This tutorial is based on publicly available data `published on CRCNS
+<https://crcns.org/data-sets/vc/TBD>`_. If you publish any work using this data
+set, please cite the original publication [1]_, and the data set [2]_.
 
 .. [1] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2012). A
     continuous semantic space describes the representation of thousands of
     object and action categories across the human brain. Neuron, 76(6),
     1210-1224.
 
-.. [2] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2020):
-    Gallant Lab Natural Movie 3T fMRI Data. CRCNS.org.
-    http://dx.doi.org/10.6080/TBD
+.. [2] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2020): Gallant
+    Lab Natural Movie 3T fMRI Data. CRCNS.org. http://dx.doi.org/10.6080/TBD
 """
 # sphinx_gallery_thumbnail_path = "static/crcns.png"
 
+raise RuntimeError("The data has not been publicly released yet, so "
+                   "this script/notebook will not work !")
+
 ###############################################################################
 # Download
 # --------

tutorials/notebooks/movies_3T/00_download_vim4.ipynb

@@ -15,7 +15,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Download the data set from CRCNS\n\n\nIn this script, we download the data set from CRCNS.\nA (free) account is required.\n\nCite this data set\n------------------\n\nThis tutorial is based on publicly available data\n`published on CRCNS <https://crcns.org/data-sets/vc/TBD>`_.\nIf you publish any work using this data set, please cite the original\npublication [1]_, and the data set [2]_.\n\n.. [1] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2012). A\n    continuous semantic space describes the representation of thousands of\n    object and action categories across the human brain. Neuron, 76(6),\n    1210-1224.\n\n.. [2] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2020):\n    Gallant Lab Natural Movie 3T fMRI Data. CRCNS.org.\n    http://dx.doi.org/10.6080/TBD\n"
+        "\n# Download the data set from CRCNS\n\n\nIn this script, we download the data set from CRCNS. A (free) account is\nrequired.\n\n.. Warning:: The data has not been publicly released yet, so this notebook will\n    not work !\n\nCite this data set\n------------------\n\nThis tutorial is based on publicly available data `published on CRCNS\n<https://crcns.org/data-sets/vc/TBD>`_. If you publish any work using this data\nset, please cite the original publication [1]_, and the data set [2]_.\n\n.. [1] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2012). A\n    continuous semantic space describes the representation of thousands of\n    object and action categories across the human brain. Neuron, 76(6),\n    1210-1224.\n\n.. [2] Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2020): Gallant\n    Lab Natural Movie 3T fMRI Data. CRCNS.org. http://dx.doi.org/10.6080/TBD\n"
       ]
     },
     {
@@ -26,7 +26,7 @@
       },
       "outputs": [],
       "source": [
-        ""
+        "raise RuntimeError(\"The data has not been publicly released yet, so \"\n                   \"this script/notebook will not work !\")"
       ]
     },
     {

voxelwise_tutorials/io.py

@@ -69,6 +69,7 @@ def download_crcns(datafile, username, password, destination,
                     bar.update_with_increment_value(chunk_size)
                     if chunk:
                         f.write(chunk)
+            print('%s downloaded.' % local_filename)
 
     # uncompress archives
     if unpack and os.path.splitext(local_filename)[1] in [".zip", ".gz"]: