Use black and isort for autoformatting (#152)

* Add black and isort for autoformatting
* add isort and black for tests. move pylint settings to pyproject.toml
* Updated CHANGELOG.rst

CHANGELOG.rst

@@ -1,6 +1,13 @@
 Changelog
 =========
 
+Version v0.13.2
+---------------
+
+Improvements
+~~~~~~~~~~~~
+- Add black & isort to handle formatting
+
 Version v0.13.1
 ---------------
 

bluepysnap/__init__.py

@@ -19,5 +19,5 @@
 
 from bluepysnap.circuit import Circuit
 from bluepysnap.config import Config
-from bluepysnap.simulation import Simulation
 from bluepysnap.exceptions import BluepySnapError
+from bluepysnap.simulation import Simulation

bluepysnap/_doctools.py

@@ -15,10 +15,10 @@
 # along with this library; if not, write to the Free Software Foundation, Inc.,
 # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
 """Module containing tools related to the documentation and docstrings."""
+import abc
+import functools
 import inspect
 import types
-import functools
-import abc
 
 
 def _word_swapper(doc, source_word, target_word):
@@ -32,8 +32,9 @@ def _word_swapper(doc, source_word, target_word):
 
 def _copy_func(f):
     """Based on http://stackoverflow.com/a/6528148/190597 (Glenn Maynard)."""
-    g = types.FunctionType(f.__code__, f.__globals__, name=f.__name__, argdefs=f.__defaults__,
-                           closure=f.__closure__)
+    g = types.FunctionType(
+        f.__code__, f.__globals__, name=f.__name__, argdefs=f.__defaults__, closure=f.__closure__
+    )
     g = functools.update_wrapper(g, f)
     g.__kwdefaults__ = f.__kwdefaults__
     return g
@@ -52,6 +53,7 @@ class DocSubstitutionMeta(type):
         <class 'bluepysnap.CircuitNodeIds'>
         It works well with Sphinx also.
     """
+
     def __new__(mcs, name, parents, attrs, source_word=None, target_word=None):
         """Define the new class to return."""
         original_attrs = attrs.copy()

bluepysnap/_plotting.py

@@ -16,6 +16,7 @@
 # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
 """Plotting module for the different snap objects."""
 import logging
+
 import numpy as np
 import pandas as pd
 from more_itertools import roundrobin
@@ -64,30 +65,31 @@ def spikes_firing_rate_histogram(filtered_report, time_binsize=None, ax=None):
     spike_report = filtered_report.spike_report
 
     times = filtered_report.report.index
-    node_count = filtered_report.report[['ids', 'population']].drop_duplicates().shape[0]
+    node_count = filtered_report.report[["ids", "population"]].drop_duplicates().shape[0]
 
     if len(times) == 0:
-        raise BluepySnapError("No data to display. You should check your "
-                              f"'group' query: {spike_report.group}.")
+        raise BluepySnapError(
+            "No data to display. You should check your " f"'group' query: {spike_report.group}."
+        )
 
     time_start = np.min(times)
     time_stop = np.max(times)
 
     if time_binsize is None:
         # heuristic for a nice bin size (~100 spikes per bin on average)
-        time_binsize = min(50.0, (time_stop - time_start) / ((len(times) / 100.) + 1.))
+        time_binsize = min(50.0, (time_stop - time_start) / ((len(times) / 100.0) + 1.0))
 
     bins = np.append(np.arange(time_start, time_stop, time_binsize), time_stop)
     hist, bin_edges = np.histogram(times, bins=bins)
     freq = 1.0 * hist / node_count / (0.001 * time_binsize)
 
     if ax is None:
         ax = plt.gca()
-        ax.set_xlabel('Time [ms]')
-        ax.set_ylabel('PSTH [Hz]')
+        ax.set_xlabel("Time [ms]")
+        ax.set_ylabel("PSTH [Hz]")
 
     # use the middle of the bins instead of the start of the bin
-    ax.plot(0.5 * (bin_edges[1:] + bin_edges[:-1]), freq, label="PSTH", drawstyle='steps-mid')
+    ax.plot(0.5 * (bin_edges[1:] + bin_edges[:-1]), freq, label="PSTH", drawstyle="steps-mid")
     return ax
 
 
@@ -114,12 +116,13 @@ def spike_raster(filtered_report, y_axis=None, ax=None):  # pragma: no cover
     spike_report = filtered_report.spike_report
     population_names = filtered_report.spike_report.population_names
 
-    props = {"node_id_offset": 0,
-             "pop_separators": [],
-             "categorical_values": set(),
-             "ymin": np.inf,
-             "ymax": -np.inf
-             }
+    props = {
+        "node_id_offset": 0,
+        "pop_separators": [],
+        "categorical_values": set(),
+        "ymin": np.inf,
+        "ymax": -np.inf,
+    }
 
     def _update_raster_properties():
         if y_axis is None:
@@ -159,7 +162,7 @@ def _update_raster_properties():
         ax = plt.gca()
         ax.xaxis.grid()
         ax.set_xlabel("Time [ms]")
-        ax.tick_params(axis='y', which='both', length=0)
+        ax.tick_params(axis="y", which="both", length=0)
         ax.set_xlim(spike_report.time_start, spike_report.time_stop)
         if y_axis is None:
             ax.set_ylim(0, props["node_id_offset"])
@@ -176,10 +179,10 @@ def _update_raster_properties():
                     ax.set_ylim(-0.5, len(labels) - 0.5)
             ax.set_ylabel(y_axis)
 
-    ax.scatter(data.index.to_numpy(), data.to_numpy(), s=10, marker='|')
+    ax.scatter(data.index.to_numpy(), data.to_numpy(), s=10, marker="|")
     if len(props["pop_separators"]) > 1:
         for separator in props["pop_separators"]:
-            ax.axhline(y=separator, color='black', lw=2)
+            ax.axhline(y=separator, color="black", lw=2)
     return ax
 
 
@@ -210,31 +213,34 @@ def spikes_isi(filtered_report, use_frequency=False, binsize=None, ax=None):  #
     values = np.concatenate([np.diff(node_spikes.index.to_numpy()) for _, node_spikes in gb])
 
     if len(values) == 0:
-        raise BluepySnapError("No data to display. You should check your "
-                              f"'group' query: {filtered_report.spike_report.group}.")
+        raise BluepySnapError(
+            "No data to display. You should check your "
+            f"'group' query: {filtered_report.spike_report.group}."
+        )
     if use_frequency:
         values = values[values > 0]  # filter out zero intervals
         values = 1000.0 / values
 
     if binsize is None:
-        bins = 'auto'
+        bins = "auto"
     else:
         bins = np.arange(0, np.max(values), binsize)
 
     if ax is None:
         ax = plt.gca()
         if use_frequency:
-            ax.set_xlabel('Frequency [Hz]')
+            ax.set_xlabel("Frequency [Hz]")
         else:
-            ax.set_xlabel('Interspike interval [ms]')
-        ax.set_ylabel('Bin weight')
+            ax.set_xlabel("Interspike interval [ms]")
+        ax.set_ylabel("Bin weight")
 
-    ax.hist(values, bins=bins, edgecolor='black', density=True)
+    ax.hist(values, bins=bins, edgecolor="black", density=True)
     return ax
 
 
-def spikes_firing_animation(filtered_report, x_axis=Node.X, y_axis=Node.Y,
-                            dt=20, ax=None):  # pragma: no cover
+def spikes_firing_animation(
+    filtered_report, x_axis=Node.X, y_axis=Node.Y, dt=20, ax=None
+):  # pragma: no cover
     # pylint: disable=too-many-locals,too-many-arguments,anomalous-backslash-in-string
     """Simple animation of simulation spikes.
 
@@ -275,7 +281,7 @@ def _check_axis(axis):
         """Verifies axes values."""
         axes = {Node.X, Node.Y, Node.Z}
         if axis not in axes:
-            raise BluepySnapError(f'{axis} is not a valid axis')
+            raise BluepySnapError(f"{axis} is not a valid axis")
 
     _check_axis(x_axis)
     _check_axis(y_axis)
@@ -302,22 +308,22 @@ def _check_axis(axis):
     if ax is None:
         fig = plt.figure()
         ax = plt.gca()
-        ax.set_title(f'time = {np.min(data.index)}ms')
+        ax.set_title(f"time = {np.min(data.index)}ms")
         x_limits = [data[x_axis].min(), data[x_axis].max()]
         y_limits = [data[y_axis].min(), data[y_axis].max()]
         ax.set_xlim(*x_limits)
         ax.set_ylim(*y_limits)
-        ax.set_xlabel(rf'{x_axis} $\mu$m')  # noqa
-        ax.set_ylabel(rf'{y_axis} $\mu$m')  # noqa
+        ax.set_xlabel(rf"{x_axis} $\mu$m")  # noqa
+        ax.set_ylabel(rf"{y_axis} $\mu$m")  # noqa
 
     else:
         fig = ax.figure
 
-    dots = ax.plot([], [], '.k')
+    dots = ax.plot([], [], ".k")
 
     def update_animation(frame):
         """Update the animation plots and axes."""
-        ax.set_title('time = ' + str(frame * dt) + ' ms')
+        ax.set_title("time = " + str(frame * dt) + " ms")
         mask = (data.index >= frame * dt) & (data.index <= (frame + 1) * dt)
         positions = data.loc[mask, [x_axis, y_axis]].values
         x = positions[:, 0]
@@ -330,7 +336,7 @@ def update_animation(frame):
     return anim, ax
 
 
-def frame_trace(filtered_report, plot_type='mean', ax=None):  # pragma: no cover
+def frame_trace(filtered_report, plot_type="mean", ax=None):  # pragma: no cover
     """Returns a plot displaying the voltage of a node or a compartment as a function of time.
 
     Args:
@@ -349,9 +355,9 @@ def frame_trace(filtered_report, plot_type='mean', ax=None):  # pragma: no cover
         ax = plt.gca()
         data_units = filtered_report.frame_report.data_units
         if plot_type == "mean":
-            ax.set_ylabel(f'Avg volt. [{data_units}]')
+            ax.set_ylabel(f"Avg volt. [{data_units}]")
         elif plot_type == "all":
-            ax.set_ylabel(f'Voltage [{data_units}]')
+            ax.set_ylabel(f"Voltage [{data_units}]")
         ax.set_xlabel(f"Time [{filtered_report.frame_report.time_units}]")
         ax.set_xlim([filtered_report.report.index.min(), filtered_report.report.index.max()])
 

bluepysnap/bbp.py

@@ -19,8 +19,8 @@
 
 from bluepysnap.sonata_constants import DYNAMICS_PREFIX, Edge, Node
 
-NODE_TYPES = {'biophysical', 'virtual', 'astrocyte', 'single_compartment', 'point_neuron'}
-EDGE_TYPES = {'chemical', 'electrical', 'synapse_astrocyte', 'endfoot'}
+NODE_TYPES = {"biophysical", "virtual", "astrocyte", "single_compartment", "point_neuron"}
+EDGE_TYPES = {"chemical", "electrical", "synapse_astrocyte", "endfoot"}
 
 
 class Cell(Node):
@@ -32,8 +32,8 @@ class Cell(Node):
     LAYER = "layer"  #:
     REGION = "region"  #:
     SYNAPSE_CLASS = "synapse_class"  #:
-    HOLDING_CURRENT = DYNAMICS_PREFIX + 'holding_current'  #:
-    THRESHOLD_CURRENT = DYNAMICS_PREFIX + 'threshold_current'  #:
+    HOLDING_CURRENT = DYNAMICS_PREFIX + "holding_current"  #:
+    THRESHOLD_CURRENT = DYNAMICS_PREFIX + "threshold_current"  #:
 
 
 class Synapse(Edge):

bluepysnap/circuit.py

@@ -20,9 +20,9 @@
 from cached_property import cached_property
 
 from bluepysnap.config import Config
+from bluepysnap.edges import Edges
 from bluepysnap.node_sets import NodeSets
 from bluepysnap.nodes import Nodes
-from bluepysnap.edges import Edges
 
 
 class Circuit:

bluepysnap/circuit_ids.py

@@ -23,9 +23,8 @@
 import pandas as pd
 
 from bluepysnap import utils
-from bluepysnap.exceptions import BluepySnapError
 from bluepysnap._doctools import AbstractDocSubstitutionMeta
-
+from bluepysnap.exceptions import BluepySnapError
 
 CircuitNodeId = namedtuple("CircuitNodeId", ("population", "id"))
 CircuitEdgeId = namedtuple("CircuitEdgeId", ("population", "id"))
@@ -40,6 +39,7 @@ class CircuitIds(abc.ABC):
     A global circuit node id is the combination of a population and an ID inside this
     population.
     """
+
     def __init__(self, index, sort_index=True):
         """Return an instance of CircuitIds.
 
@@ -79,8 +79,10 @@ def from_arrays(cls, populations, population_ids, sort_index=True):
         population_ids = utils.ensure_ids(population_ids)
 
         if len(populations) != len(population_ids):
-            raise BluepySnapError("populations and population_ids must have the same size. "
-                                  f"{len(populations)} != {len(population_ids)}")
+            raise BluepySnapError(
+                "populations and population_ids must have the same size. "
+                f"{len(populations)} != {len(population_ids)}"
+            )
 
         index = pd.MultiIndex.from_arrays([populations, population_ids])
         return cls(index, sort_index=sort_index)
@@ -288,8 +290,12 @@ def __getitem__(self, item):  # pragma: no cover
         """Getter on the CircuitIds."""
 
 
-class CircuitNodeIds(CircuitIds, metaclass=AbstractDocSubstitutionMeta,
-                     source_word="CircuitId", target_word="CircuitNodeId"):
+class CircuitNodeIds(
+    CircuitIds,
+    metaclass=AbstractDocSubstitutionMeta,
+    source_word="CircuitId",
+    target_word="CircuitNodeId",
+):
     """High performances CircuitNodeID container."""
 
     def __init__(self, index, sort_index=True):
@@ -313,8 +319,12 @@ def __getitem__(self, item):
         return CircuitNodeId(*self.index[item])
 
 
-class CircuitEdgeIds(CircuitIds, metaclass=AbstractDocSubstitutionMeta,
-                     source_word="CircuitId", target_word="CircuitEdgeId"):
+class CircuitEdgeIds(
+    CircuitIds,
+    metaclass=AbstractDocSubstitutionMeta,
+    source_word="CircuitId",
+    target_word="CircuitEdgeId",
+):
     """High performances CircuitEdgeID container."""
 
     def __init__(self, index, sort_index=True):