Prepare for release 1.0.7 (#225)

- Fix changelog
- Fix docs formatting
- More tests for _logical_and and _logical_or

CHANGELOG.rst

@@ -8,11 +8,14 @@ New Features
 ~~~~~~~~~~~~
 - Added ``CircuitIds.intersection`` to take the intersection of two ``CircuitIds``.
 
+Improvements
+~~~~~~~~~~~~
+- Improve performance when querying a population with get() and ids().
+
 Bug Fixes
 ~~~~~~~~~
 - Fix CircuitIds.sample() to always return different samples.
 - Ensure that the report DataFrames have the same schema even when empty.
-- Improve performance when querying a population with get() and ids().
 
 Version v1.0.6
 --------------

bluepysnap/_plotting.py

@@ -248,12 +248,13 @@ def spikes_firing_animation(
         ax(matplotlib.Axis): matplotlib Axis to draw on (if not specified, pyplot.gca()
             and plt.figure() are used).
 
-    Returns :
+    Returns:
         (matplotlib.animation.FuncAnimation, matplotlib.Axis): the matplotlib animation object and
-            the corresponding axis.
+        the corresponding axis.
 
-    Notes:
+    Examples:
         From scripts:
+
         >>> import matplotlib.pyplot as plt
         >>> from bluepysnap import Simulation
         >>> report = Simulation("config.json").spikes["my_population"]
@@ -262,6 +263,7 @@ def spikes_firing_animation(
         >>> # to save the animation : do not plt.show() and just anim.save('my_movie.mp4')
 
         From notebooks:
+
         >>> from IPython.display import HTML
         >>> from bluepysnap import Simulation
         >>> report = Simulation("config.json").spikes["my_population"]

bluepysnap/edges/edge_population.py

@@ -121,7 +121,8 @@ def _topology_property_names(self):
     def config(self):
         """Access the configuration for the population.
 
-        This configuration is extended with
+        This configuration is extended with:
+
         * 'components' of the circuit config
         * 'edges_file': the path the h5 file containing the population.
         """
@@ -154,7 +155,7 @@ def container_property_names(self, container):
 
         Returns:
             list: A list of strings corresponding to the properties that you can use from the
-                container class
+            container class
 
         Examples:
             >>> from bluepysnap.sonata_constants import Edge
@@ -244,6 +245,7 @@ def ids(self, group=None, limit=None, sample=None, raise_missing_property=True):
         Args:
             group (None/int/CircuitEdgeId/CircuitEdgeIds/sequence): Which IDs will be
                 returned depends on the type of the ``group`` argument:
+
                 - ``None``: return all IDs.
                 - ``int``, ``CircuitEdgeId``: return a single edge ID.
                 - ``CircuitEdgeIds`` return IDs of edges the edge population in an array.
@@ -299,8 +301,8 @@ def get(self, edge_ids, properties):
 
         Returns:
             pandas.Series/pandas.DataFrame:
-                A pandas Series indexed by edge IDs if ``properties`` is scalar.
-                A pandas DataFrame indexed by edge IDs if ``properties`` is list.
+                - A pandas Series indexed by edge IDs if ``properties`` is scalar.
+                - A pandas DataFrame indexed by edge IDs if ``properties`` is list.
 
         Notes:
             The EdgePopulation.property_names function will give you all the usable properties
@@ -394,9 +396,9 @@ def pathway_edges(self, source=None, target=None, properties=None):
             properties: None / edge property name / list of edge property names
 
         Returns:
-            List of edge IDs, if ``properties`` is None;
-            Pandas Series indexed by edge IDs if ``properties`` is string;
-            Pandas DataFrame indexed by edge IDs if ``properties`` is list.
+            - List of edge IDs, if ``properties`` is None;
+            - Pandas Series indexed by edge IDs if ``properties`` is string;
+            - Pandas DataFrame indexed by edge IDs if ``properties`` is list.
         """
         if source is None and target is None:
             raise BluepySnapError("Either `source` or `target` should be specified")
@@ -424,9 +426,9 @@ def afferent_edges(self, node_id, properties=None):
 
         Returns:
             pandas.Series/pandas.DataFrame/list:
-                A pandas Series indexed by edge ID if ``properties`` is a string.
-                A pandas DataFrame indexed by edge ID if ``properties`` is a list.
-                A list of edge IDs, if ``properties`` is None.
+                - A pandas Series indexed by edge ID if ``properties`` is a string.
+                - A pandas DataFrame indexed by edge ID if ``properties`` is a list.
+                - A list of edge IDs, if ``properties`` is None.
         """
         return self.pathway_edges(source=None, target=node_id, properties=properties)
 
@@ -438,9 +440,9 @@ def efferent_edges(self, node_id, properties=None):
             properties: None / edge property name / list of edge property names
 
         Returns:
-            List of edge IDs, if ``properties`` is None;
-            Pandas Series indexed by edge IDs if ``properties`` is string;
-            Pandas DataFrame indexed by edge IDs if ``properties`` is list.
+            - List of edge IDs, if ``properties`` is None;
+            - Pandas Series indexed by edge IDs if ``properties`` is string;
+            - Pandas DataFrame indexed by edge IDs if ``properties`` is list.
         """
         return self.pathway_edges(source=node_id, target=None, properties=properties)
 
@@ -453,9 +455,9 @@ def pair_edges(self, source_node_id, target_node_id, properties=None):
             properties: None / edge property name / list of edge property names
 
         Returns:
-            List of edge IDs, if ``properties`` is None;
-            Pandas Series indexed by edge IDs if ``properties`` is string;
-            Pandas DataFrame indexed by edge IDs if ``properties`` is list.
+            - List of edge IDs, if ``properties`` is None;
+            - Pandas Series indexed by edge IDs if ``properties`` is string;
+            - Pandas DataFrame indexed by edge IDs if ``properties`` is list.
         """
         return self.pathway_edges(
             source=source_node_id, target=target_node_id, properties=properties
@@ -554,9 +556,9 @@ def iter_connections(
         ``return_edge_count`` and ``return_edge_ids`` are mutually exclusive.
 
         Yields:
-            (source_node_id, target_node_id, edge_ids) if return_edge_ids == True;
-            (source_node_id, target_node_id, edge_count) if return_edge_count == True;
-            (source_node_id, target_node_id) otherwise.
+            - (source_node_id, target_node_id, edge_ids) if ``return_edge_ids`` is True;
+            - (source_node_id, target_node_id, edge_count) if ``return_edge_count`` is True;
+            - (source_node_id, target_node_id) otherwise.
         """
         if return_edge_ids and return_edge_count:
             raise BluepySnapError(

bluepysnap/edges/edges.py

@@ -51,14 +51,15 @@ def ids(self, group=None, sample=None, limit=None):
 
         Args:
             group (None/int/CircuitEdgeId/CircuitEdgeIds/sequence): Which IDs will be
-            returned depends on the type of the ``group`` argument:
+                returned depends on the type of the ``group`` argument:
+
                 - ``None``: return all CircuitEdgeIds.
                 - ``CircuitEdgeId``: return the ID in a CircuitEdgeIds object.
                 - ``CircuitEdgeIds``: return the IDs in a CircuitNodeIds object.
                 - ``int``: returns a CircuitEdgeIds object containing the corresponding edge ID
-                    for all populations.
+                  for all populations.
                 - ``sequence``: returns a CircuitEdgeIds object containing the corresponding edge
-                    IDs for all populations.
+                  IDs for all populations.
             sample (int): If specified, randomly choose ``sample`` number of
                 IDs from the match result. If the size of the sample is greater than
                 the size of all the EdgePopulations then all ids are taken and shuffled.
@@ -68,8 +69,8 @@ def ids(self, group=None, sample=None, limit=None):
 
         Returns:
             CircuitEdgeIds: returns a CircuitEdgeIds containing all the edge IDs and the
-                corresponding populations. For performance reasons we do not test if the edge ids
-                are present or not in the circuit.
+            corresponding populations. For performance reasons we do not test if the edge ids
+            are present or not in the circuit.
 
         Notes:
             This envision also the maybe future selection of edges on queries.
@@ -91,8 +92,8 @@ def get(self, edge_ids=None, properties=None):  # pylint: disable=arguments-rena
 
         Returns:
             pandas.Series/pandas.DataFrame:
-                A pandas Series indexed by edge IDs if ``properties`` is scalar.
-                A pandas DataFrame indexed by edge IDs if ``properties`` is list.
+                - A pandas Series indexed by edge IDs if ``properties`` is scalar.
+                - A pandas DataFrame indexed by edge IDs if ``properties`` is list.
 
         Notes:
             The Edges.property_names function will give you all the usable properties
@@ -171,9 +172,9 @@ def pathway_edges(self, source=None, target=None, properties=None):
             properties: None / edge property name / list of edge property names
 
         Returns:
-            CircuitEdgeIDs, if ``properties`` is None;
-            Pandas Series indexed by CircuitEdgeIDs if ``properties`` is string;
-            Pandas DataFrame indexed by CircuitEdgeIDs if ``properties`` is list.
+            - CircuitEdgeIDs, if ``properties`` is None;
+            - Pandas Series indexed by CircuitEdgeIDs if ``properties`` is string;
+            - Pandas DataFrame indexed by CircuitEdgeIDs if ``properties`` is list.
         """
         if source is None and target is None:
             raise BluepySnapError("Either `source` or `target` should be specified")
@@ -198,9 +199,9 @@ def afferent_edges(self, node_id, properties=None):
 
         Returns:
             pandas.Series/pandas.DataFrame/list:
-                A pandas Series indexed by edge ID if ``properties`` is a string.
-                A pandas DataFrame indexed by edge ID if ``properties`` is a list.
-                A list of edge IDs, if ``properties`` is None.
+                - A pandas Series indexed by edge ID if ``properties`` is a string.
+                - A pandas DataFrame indexed by edge ID if ``properties`` is a list.
+                - A list of edge IDs, if ``properties`` is None.
         """
         return self.pathway_edges(source=None, target=node_id, properties=properties)
 
@@ -212,9 +213,9 @@ def efferent_edges(self, node_id, properties=None):
             properties: None / edge property name / list of edge property names
 
         Returns:
-            List of edge IDs, if ``properties`` is None;
-            Pandas Series indexed by edge IDs if ``properties`` is string;
-            Pandas DataFrame indexed by edge IDs if ``properties`` is list.
+            - List of edge IDs, if ``properties`` is None;
+            - Pandas Series indexed by edge IDs if ``properties`` is string;
+            - Pandas DataFrame indexed by edge IDs if ``properties`` is list.
         """
         return self.pathway_edges(source=node_id, target=None, properties=properties)
 
@@ -227,9 +228,9 @@ def pair_edges(self, source_node_id, target_node_id, properties=None):
             properties: None / edge property name / list of edge property names
 
         Returns:
-            List of edge IDs, if ``properties`` is None;
-            Pandas Series indexed by edge IDs if ``properties`` is string;
-            Pandas DataFrame indexed by edge IDs if ``properties`` is list.
+            - List of edge IDs, if ``properties`` is None;
+            - Pandas Series indexed by edge IDs if ``properties`` is string;
+            - Pandas DataFrame indexed by edge IDs if ``properties`` is list.
         """
         return self.pathway_edges(
             source=source_node_id, target=target_node_id, properties=properties
@@ -282,9 +283,9 @@ def iter_connections(
         ``return_edge_count`` and ``return_edge_ids`` are mutually exclusive.
 
         Yields:
-            (source_node_id, target_node_id, edge_ids) if return_edge_ids == True;
-            (source_node_id, target_node_id, edge_count) if return_edge_count == True;
-            (source_node_id, target_node_id) otherwise.
+            - (source_node_id, target_node_id, edge_ids) if ``return_edge_ids`` is True;
+            - (source_node_id, target_node_id, edge_count) if ``return_edge_count`` is True;
+            - (source_node_id, target_node_id) otherwise.
         """
         if return_edge_ids and return_edge_count:
             raise BluepySnapError(

bluepysnap/frame_report.py

@@ -156,9 +156,10 @@ def report(self):
 
         Returns:
             pandas.DataFrame: A DataFrame containing the data from the report. Row's indices are the
-                different timestamps and the column's MultiIndex are :
-                - (population_name, node_id, compartment id) for the CompartmentReport
-                - (population_name, node_id) for the SomaReport
+            different timestamps and the column's MultiIndex are:
+
+            - (population_name, node_id, compartment id) for the CompartmentReport
+            - (population_name, node_id) for the SomaReport
         """
         dataframes = {}
         for population in self.frame_report.population_names:

bluepysnap/nodes/node_population.py

@@ -250,7 +250,8 @@ def target_in_edges(self):
     def config(self):
         """Access the configuration for the population.
 
-        This configuration is extended with
+        This configuration is extended with:
+
         * 'components' of the circuit config
         * 'nodes_file': the path the h5 file containing the population.
         """
@@ -273,7 +274,7 @@ def container_property_names(self, container):
 
         Returns:
             list: A list of strings corresponding to the properties that you can use from the
-                container class
+            container class
 
         Examples:
             >>> from bluepysnap.sonata_constants import Node

bluepysnap/nodes/nodes.py

@@ -59,20 +59,21 @@ def ids(self, group=None, sample=None, limit=None):
 
         Args:
             group (CircuitNodeId/CircuitNodeIds/int/sequence/str/mapping/None): Which IDs will be
-            returned depends on the type of the ``group`` argument:
+                returned depends on the type of the ``group`` argument:
+
                 - ``CircuitNodeId``: return the ID in a CircuitNodeIds object if it belongs to
-                    the circuit.
+                  the circuit.
                 - ``CircuitNodeIds``: return the IDs in a CircuitNodeIds object if they belong to
-                    the circuit.
+                  the circuit.
                 - ``int``: if the node ID is present in all populations, returns a CircuitNodeIds
-                    object containing the corresponding node ID for all populations.
+                  object containing the corresponding node ID for all populations.
                 - ``sequence``: if all the values contained in the sequence are present in all
-                    populations, returns a CircuitNodeIds object containing the corresponding node
-                    IDs for all populations.
+                  populations, returns a CircuitNodeIds object containing the corresponding node
+                  IDs for all populations.
                 - ``str``: use a node set name as input. Returns a CircuitNodeIds object containing
-                    nodes selected by the node set.
+                  nodes selected by the node set.
                 - ``mapping``: Returns a CircuitNodeIds object containing nodes matching a
-                    properties filter.
+                  properties filter.
                 - ``None``: return all node IDs of the circuit in a CircuitNodeIds object.
             sample (int): If specified, randomly choose ``sample`` number of
                 IDs from the match result. If the size of the sample is greater than
@@ -83,8 +84,8 @@ def ids(self, group=None, sample=None, limit=None):
 
         Returns:
             CircuitNodeIds: returns a CircuitNodeIds containing all the node IDs and the
-                corresponding populations. All the explicitly requested IDs must be present inside
-                the circuit.
+            corresponding populations. All the explicitly requested IDs must be present inside
+            the circuit.
 
         Raises:
             BluepySnapError: when a population from a CircuitNodeIds is not present in the circuit.

bluepysnap/spike_report.py

@@ -156,7 +156,7 @@ def report(self):
 
         Returns:
             pandas.DataFrame: A DataFrame containing the data from the report. Row's indices are the
-                different timestamps and the columns are ids and population names.
+            different timestamps and the columns are ids and population names.
         """
         res = pd.DataFrame()
         for population in self.spike_report.population_names:

tests/test_query.py

@@ -74,6 +74,7 @@ def test_resolve_ids():
         ([np.array([False])], np.array([False])),
         ([np.array([True, True]), np.array([True, False])], np.array([True, False])),
         ([np.array([100, 100]), np.array([True, False])], np.array([True, False])),
+        ([pd.Series([100, 100]), np.array([True, False])], np.array([True, False])),
         (
             [np.array([True, False, True, False]), np.array([True, True, False, False])],
             np.array([True, False, False, False]),
@@ -112,6 +113,7 @@ def test__logical_and(masks, expected):
         ([np.array([False])], np.array([False])),
         ([np.array([True, True]), np.array([True, False])], np.array([True, True])),
         ([np.array([100, 100]), np.array([True, False])], np.array([True, True])),
+        ([pd.Series([100, 100]), np.array([True, False])], np.array([True, True])),
         (
             [np.array([True, False, True, False]), np.array([True, True, False, False])],
             np.array([True, True, True, False]),