plot file (#1732)

Author: bendichter

docs/gallery/general/file.py renamed to docs/gallery/general/plot_file.py

@@ -177,7 +177,7 @@
     experiment_description="I went on an adventure to reclaim vast treasures.",  # optional
     related_publications="DOI:10.1016/j.neuron.2016.12.011",  # optional
 )
-print(nwbfile)
+nwbfile
 
 ####################
 # .. note::
@@ -212,21 +212,25 @@
 # The fields in the :py:class:`~pynwb.file.Subject` object are all free-form text (any format will be valid),
 # however it is recommended to follow particular conventions to help software tools interpret the data:
 #
-# * **age**: `ISO 8601 Duration format <https://en.wikipedia.org/wiki/ISO_8601#Durations>`_, e.g., ``"P90D"`` for 90 days old
+# * **age**: `ISO 8601 Duration format <https://en.wikipedia.org/wiki/ISO_8601#Durations>`_, e.g., ``"P90D"`` for 90
+#   days old
 # * **species**: The formal Latin binomial nomenclature, e.g., ``"Mus musculus"``, ``"Homo sapiens"``
 # * **sex**: Single letter abbreviation, e.g., ``"F"`` (female), ``"M"`` (male), ``"U"`` (unknown), and ``"O"`` (other)
 #
 # Add the subject information to the :py:class:`~pynwb.file.NWBFile`
 # by setting the ``subject`` field to the new :py:class:`~pynwb.file.Subject` object.
 
-nwbfile.subject = Subject(
+subject = Subject(
     subject_id="001",
     age="P90D",
     description="mouse 5",
     species="Mus musculus",
     sex="M",
 )
 
+nwbfile.subject = subject
+subject
+
 ####################
 # .. _basic_timeseries:
 #
@@ -254,6 +258,7 @@
     starting_time=0.0,
     rate=1.0,
 )
+time_series_with_rate
 
 ####################
 # For irregularly sampled recordings, we need to provide the ``timestamps`` for the ``data``:
@@ -265,6 +270,7 @@
     unit="m",
     timestamps=timestamps,
 )
+time_series_with_timestamps
 
 ####################
 # :py:class:`~pynwb.base.TimeSeries` objects can be added directly to :py:class:`~pynwb.file.NWBFile` using:
@@ -316,7 +322,7 @@
 # create fake data with shape (50, 2)
 # the first dimension should always represent time
 position_data = np.array([np.linspace(0, 10, 50), np.linspace(0, 8, 50)]).T
-position_timestamps = np.linspace(0, 50) / 200
+position_timestamps = np.linspace(0, 50).astype(float) / 200
 
 spatial_series_obj = SpatialSeries(
     name="SpatialSeries",
@@ -325,12 +331,13 @@
     timestamps=position_timestamps,
     reference_frame="(0,0) is bottom left corner",
 )
-print(spatial_series_obj)
+spatial_series_obj
 
 ####################
 # To help data analysis and visualization tools know that this :py:class:`~pynwb.behavior.SpatialSeries` object
 # represents the position of the subject, store the :py:class:`~pynwb.behavior.SpatialSeries` object inside
-# of a :py:class:`~pynwb.behavior.Position` object, which can hold one or more :py:class:`~pynwb.behavior.SpatialSeries` objects.
+# of a :py:class:`~pynwb.behavior.Position` object, which can hold one or more :py:class:`~pynwb.behavior.SpatialSeries`
+# objects.
 #
 # .. only:: html
 #
@@ -350,6 +357,7 @@
 
 # name is set to "Position" by default
 position_obj = Position(spatial_series=spatial_series_obj)
+position_obj
 
 ####################
 # Behavior Processing Module
@@ -395,7 +403,7 @@
 # Once the behavior processing module is added to the :py:class:`~pynwb.file.NWBFile`,
 # you can access it with:
 
-print(nwbfile.processing["behavior"])
+nwbfile.processing["behavior"]
 
 ####################
 # .. _basic_writing:
@@ -559,7 +567,7 @@
 # :py:class:`~hdmf.common.table.DynamicTable` and its subclasses can be converted to a pandas
 # :py:class:`~pandas.DataFrame` for convenient analysis using :py:meth:`.DynamicTable.to_dataframe`.
 
-print(nwbfile.trials.to_dataframe())
+nwbfile.trials.to_dataframe()
 
 ####################
 # .. _basic_epochs:
@@ -587,6 +595,8 @@
     timeseries=[time_series_with_timestamps],
 )
 
+nwbfile.epochs.to_dataframe()
+
 ####################
 # Other time intervals
 # ^^^^^^^^^^^^^^^^^^^^

docs/source/conf.py

@@ -75,7 +75,7 @@ class CustomSphinxGallerySectionSortKey(ExampleTitleSortKey):
     # listed here will be added in alphabetical order based on title after the
     # explicitly listed galleries
     GALLERY_ORDER = {
-        'general': ['file.py'],
+        'general': ['plot_file.py'],
         # Sort domain-specific tutorials based on domain to group tutorials belonging to the same domain
         'domain': [
             "ecephys.py",