Merge branch 'dev' into enh/tutorial_order

CHANGELOG.md

@@ -7,6 +7,7 @@
 
 ### Tutorial enhancements:
 - Enhanced ordering of sphinx gallery tutorials to use alphabetic ordering based on tutorial headings. @oruebel (#1399)
+- Updated the general tutorial to add documentation about the ``Images`` type. @bendichter (#1353)
 
 ## PyNWB 2.0.0 (August 13, 2021)
 

docs/gallery/domain/plot_icephys.py

@@ -51,7 +51,7 @@
 - :py:class:`~pynwb.icephys.RepetitionsTable` groups sequential recordings from
   the :py:class:`~pynwb.icephys.SequentialRecordingsTable`. In practice a
   repetition is often also referred to a run. A typical use of the
-  py:class:`~pynwb.icephys.RepetitionsTable` is to group sets of different stimuli
+  :py:class:`~pynwb.icephys.RepetitionsTable` is to group sets of different stimuli
   that are applied in sequence that may be repeated.
 - :py:class:`~pynwb.icephys.ExperimentalConditionsTable` groups repetitions of
   intracellular recording from the :py:class:`~pynwb.icephys.RepetitionsTable`
@@ -387,13 +387,13 @@
 
 #####################################################################
 # The :py:class:`~pynwb.icephys.IntracellularRecordingsTable` table is not just a ``DynamicTable``
-# but an ``AlignedDynamicTable`. The ``AlignedDynamicTable` type is itself a ``DynamicTable``
+# but an ``AlignedDynamicTable``. The ``AlignedDynamicTable`` type is itself a ``DynamicTable``
 # that may contain an arbitrary number of additional ``DynamicTable``, each of which defines
 # a "category". This is similar to a table with "sub-headings". In the case of the
 # :py:class:`~pynwb.icephys.IntracellularRecordingsTable`, we have three predefined categories,
 # i.e., electrodes, stimuli, and responses. We can also dynamically add new categories to
-# the table. As each category corresponds to a DynamicTable, this means we have to create a
-# new DynamicTable and add it to our table.
+# the table. As each category corresponds to a ``DynamicTable``, this means we have to create a
+# new ``DynamicTable`` and add it to our table.
 
 # Create a new DynamicTable for our category that contains a location column of type VectorData
 location_column = VectorData(

docs/gallery/general/file.py

@@ -411,19 +411,61 @@
 nwbfile.add_unit(id=3, spike_times=[1.2, 2.3, 3.3, 4.5],
                  obs_intervals=[[1, 10], [20, 30]], location='CA1', quality=0.90)
 
-####################
-# Now we overwrite the file with all of the data
-
-with NWBHDF5IO('example_file_path.nwb', 'w') as io:
-    io.write(nwbfile)
-
 ####################
 # .. _units_fields_ref:
 #
 # .. note::
 #    The Units table has some predefined optional columns. Please review the documentation for
 #    :py:meth:`~pynwb.file.NWBFile.add_unit` before adding custom columns.
 
+####################
+# Images
+# ------
+#
+# You can store static images within the NWB file as well. These can be images of the subject, the environment, stimuli,
+# or really anything.
+#
+# .. note::
+#          All basic image types :py:class:`~pynwb.image.RGBAImage`, py:class:`~pynwb.image.RGBImage`, and
+#          py:class:`~pynwb.image.GrayscaleImage` provide the optional: 1) ``description`` parameter to include a
+#          text description about the image and 2) ``resolution`` parameter to specify the *pixels / cm* resolution
+#          of the image.
+
+from PIL import Image
+import numpy as np
+
+from pynwb.image import RGBAImage, RGBImage, GrayscaleImage
+from pynwb.base import Images
+
+img = Image.open('docs/source/logo.png')  # an example image
+
+# you can store an RGBA image
+rgba_logo = RGBAImage(name='RGBA_logo', data=np.array(img))
+
+# or RGB
+rgb_logo = RGBImage(name='RGB_logo', data=np.array(img.convert('RGB')))
+
+# or Grayscale. Here with the optional description and resolution specified.
+gs_logo = GrayscaleImage(name='Grayscale_logo',
+                         data=np.array(img.convert('L')),
+                         description='Grayscale version of the NWB logo',
+                         resolution=35.433071)
+
+# Images is a container that accepts any of these image types
+images = Images(
+    name='logo_images',
+    images=[rgb_logo, rgba_logo, gs_logo]
+)
+
+# Finally, do not forget to add the images object to the nwb file.
+nwbfile.processing['behavior'].add(images)
+
+####################
+# Now we overwrite the file with all of the data
+
+with NWBHDF5IO('example_file_path.nwb', 'w') as io:
+    io.write(nwbfile)
+
 ####################
 # .. _basic_appending:
 #

docs/source/conf.py

@@ -159,7 +159,9 @@
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the
 # documentation.
-# html_theme_options = {}
+html_theme_options = {
+    "style_nav_header_background": "#AFD2E8"
+}
 
 # Add any paths that contain custom themes here, relative to this directory.
 # html_theme_path = []

requirements-doc.txt

@@ -4,3 +4,4 @@ matplotlib
 sphinx_rtd_theme
 sphinx-gallery
 allensdk>=2.11.0  # python 3.8 is not supported in allensdk<2.11
+Pillow