Merge pull request #772 from apdavison/flake8

fix or ignore flake8 errors and warnings; add flake8 checks to CI

Author: apdavison

.github/workflows/full-test.yml

@@ -31,7 +31,7 @@ jobs:
     - name: Install basic Python dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install pytest pytest-cov coveralls
+        python -m pip install pytest pytest-cov coveralls flake8
         python -m pip install mpi4py
         python -m pip install -r requirements.txt
     - name: Install Brian 2
@@ -60,6 +60,12 @@ jobs:
         pushd pyNN/neuron/nmodl
         nrnivmodl
         popd
+    - name: Lint with flake8
+      run: |
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 pyNN --count --select=E9,F63,F7,F82 --show-source --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 pyNN --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Run unit and system tests
       run: |
         pytest -v --cov=pyNN --cov-report=term test

pyNN/brian2/__init__.py

@@ -6,19 +6,23 @@
 """
 
 import logging
-import brian2
-from pyNN import common, space
+import brian2                                                             # noqa: F401
+from pyNN import common, space                                            # noqa: F401
 from pyNN.common.control import DEFAULT_MAX_DELAY, DEFAULT_TIMESTEP, DEFAULT_MIN_DELAY
-from pyNN.connectors import *
+from pyNN.standardmodels import StandardCellType
+from pyNN.connectors import *                                             # noqa: F401, F403
+from pyNN.connectors import FixedProbabilityConnector
 from pyNN.brian2 import simulator
-from pyNN.brian2.standardmodels.cells import *
-from pyNN.brian2.standardmodels.synapses import *
-from pyNN.brian2.standardmodels.electrodes import *
-from pyNN.brian2.standardmodels.receptors import (
+from pyNN.brian2.standardmodels.cells import *                            # noqa: F401, F403
+from pyNN.brian2.standardmodels.synapses import *                         # noqa: F401, F403
+from pyNN.brian2.standardmodels.synapses import StaticSynapse
+from pyNN.brian2.standardmodels.electrodes import *                       # noqa: F401, F403
+from pyNN.brian2.standardmodels.electrodes import update_currents
+from pyNN.brian2.standardmodels.receptors import (                        # noqa: F401
     CondAlphaPostSynapticResponse, AlphaPSR,
     CondExpPostSynapticResponse, ExpPSR,
     CurrExpPostSynapticResponse)
-from pyNN.brian2.populations import Population, PopulationView, Assembly
+from pyNN.brian2.populations import Population, PopulationView, Assembly  # noqa: F401
 from pyNN.brian2.projections import Projection
 from pyNN.recording import get_io
 
@@ -27,7 +31,8 @@
 
 def list_standard_models():
     """Return a list of all the StandardCellType classes available for this simulator."""
-    return [obj.__name__ for obj in globals().values() if isinstance(obj, type) and issubclass(obj, StandardCellType)]
+    return [obj.__name__ for obj in globals().values()
+            if isinstance(obj, type) and issubclass(obj, StandardCellType)]
 
 
 def setup(timestep=DEFAULT_TIMESTEP, min_delay=DEFAULT_MIN_DELAY,
@@ -48,7 +53,7 @@ def setup(timestep=DEFAULT_TIMESTEP, min_delay=DEFAULT_MIN_DELAY,
     simulator.state.num_processes = 1
 
     simulator.state.network.add(
-        NetworkOperation(update_currents, when="start", clock=simulator.state.network.clock)
+        brian2.NetworkOperation(update_currents, when="start", clock=simulator.state.network.clock)
     )
     return rank()
 

pyNN/brian2/cells.py

@@ -9,6 +9,7 @@
 
 import numpy as np
 import brian2
+from functools import reduce
 from pyNN.parameters import Sequence, simplify
 from pyNN.core import is_listlike
 from pyNN import errors
@@ -156,13 +157,10 @@ def tau_refrac(self):
 
     @tau_refrac.setter
     def tau_refrac(self, tau_refrac_value):
-        #self._refracvalue = tau_refrac_value * ms
-        #brian2.NeuronGroup.__setattr__(self, 'tau_refrac', tau_refrac_value)
         self._refractory = tau_refrac_value
 
     @v_reset.setter
     def v_reset(self, resetvalue):
-        #self._resetvalue = resetvalue * mV
         self.event_codes['spike'] = 'v = {}*mV'.format(resetvalue / mV)
 
 
@@ -189,17 +187,6 @@ def __init__(self, n, equations, **parameters):
         reset = 'v = {}*mV; g_r+= {}*nS; g_s+={}*nS'.format(
             self._resetvalue / mV, self._q_rvalue / nS, self._q_svalue / nS)
         refractory = self._refracvalue
-        '''
-        threshold = brian2.SimpleFunThreshold(self.check_threshold)
-        period = simplify(parameters['tau_refrac'])
-        assert not hasattr(period, "__len__"), "Brian2 does not support heterogenerous refractory periods with CustomRefractoriness"
-        reset = brian2.SimpleCustomRefractoriness(
-                    AdaptiveReset2(parameters.pop('v_reset'),
-                                   parameters.pop('q_r'),
-                                   parameters.pop('q_s')),
-                    period=period * second)
-        refractory = None
-        '''
         BaseNeuronGroup.__init__(self, n, equations,
                                  threshold, reset=reset, refractory=refractory,
                                  method="rk2", **parameters)
@@ -222,24 +209,12 @@ def tau_refrac(self):
 
     @tau_refrac.setter
     def tau_refrac(self, tau_refrac_value):
-        #self._refracvalue = tau_refrac_value * ms
-        #brian2.NeuronGroup.__setattr__(self, 'tau_refrac', tau_refrac_value)
         self._refractory = tau_refrac_value
 
     @v_reset.setter
     def v_reset(self, resetvalue):
-        #self._resetvalue = resetvalue * mV
         self.event_codes['spike'] = 'v = {}*mV'.format(resetvalue / mV)
 
-    '''
-    tau_refrac = _new_property('', '_refractory_array', ms)
-    v_reset = _new_property('_resetfun.resetfun', 'v_reset', mV)
-    q_r = _new_property('_resetfun.resetfun', 'q_r', nA)
-    q_s = _new_property('_resetfun.resetfun', 'q_s', nA)
-
-    def check_threshold(self, v):
-        return v >= self.v_thresh
-    '''
 
 # The below can be replaced by
 # reset = '''v = v_reset
@@ -260,28 +235,14 @@ def __call__(self, P, spikes):
 class IzhikevichNeuronGroup(BaseNeuronGroup):
 
     def __init__(self, n, equations, **parameters):
-        #threshold = brian2.SimpleFunThreshold(self.check_threshold)
-        #threshold = 'v >= {}*mV'.format(parameters["v_thresh"][0]*1000)
         threshold = 'v >= 30*mV'
         self._resetvalue = parameters.pop('v_reset')[0]
         self._dvalue = parameters.pop('d')[0]
         reset = 'v = {}*mV; u+={}*mV/ms'.format(self._resetvalue / mV, self._dvalue / (mV/ms))
-        '''
-        reset = brian2.SimpleCustomRefractoriness(
-                    IzhikevichReset(parameters['v_reset'],
-                                    parameters['d']),
-                    period=0 * ms)
-        '''
         refractory = 0 * ms
         BaseNeuronGroup.__init__(self, n, equations,
                                  threshold=threshold, reset=reset, refractory=refractory,
                                  **parameters)
-        #self._variable_refractory_time = True
-        #self._refractory_variable = None
-        #self._S0 = self._S[:, 0]
-
-    #v_reset = _new_property('_resetfun.resetfun', 'Vr', mV)
-    #b = _new_property('_resetfun.resetfun', 'b', nA)
 
     @property
     def v_reset(self):
@@ -293,7 +254,6 @@ def d(self):
 
     @v_reset.setter
     def v_reset(self, resetvalue):
-        #self._resetvalue = resetvalue * mV
         self.event_codes['spike'] = 'v = {}*mV'.format(resetvalue / mV)
 
 
@@ -339,7 +299,7 @@ def __init__(self, n, equations, spike_time_sequences=None):
     def _convert_sequences_to_arrays(self, spike_time_sequences):
         times = np.concatenate([seq.value for seq in spike_time_sequences])
         indices = np.concatenate([i * np.ones(seq.value.size)
-                                     for i, seq in enumerate(spike_time_sequences)])
+                                  for i, seq in enumerate(spike_time_sequences)])
         return indices, times * second
         # todo: try to push the multiplication by seconds back into the translation step.
         #       note that the scaling from ms to seconds does take place during translation

pyNN/brian2/populations.py

@@ -9,13 +9,7 @@
 from pyNN.parameters import ArrayParameter, ParameterSpace, simplify, LazyArray
 from . import simulator
 from .recording import Recorder
-import numpy as np
-from brian2.units.fundamentalunits import Quantity
-#from brian2.units import *
-#from quantities import *
-from brian2.core.variables import VariableView
 import brian2
-#from brian2.groups.neurongroup import *
 ms = brian2.ms
 mV = brian2.mV
 
@@ -34,7 +28,8 @@ def _get_parameters(self, *names):
         """
         def _get_component_parameters(component, names, component_label=None):
             if component.computed_parameters_include(names):
-                native_names = component.get_native_names()  # need all parameters in order to calculate values
+                # need all parameters in order to calculate values
+                native_names = component.get_native_names()
             else:
                 native_names = component.get_native_names(*names, suffix=component_label)
             native_parameter_space = self._get_native_parameters(*native_names)
@@ -67,10 +62,12 @@ def _get_component_parameters(component, names, component_label=None):
                 else:
                     parameter_space = ParameterSpace({})
                 for component_label, names in names_by_component.items():
-                    parameter_space.add_child(component_label,
-                                              _get_component_parameters(self.celltype.post_synaptic_receptors[component_label],
-                                                                        names_by_component[component_label],
-                                                                        component_label))
+                    parameter_space.add_child(
+                        component_label,
+                        _get_component_parameters(
+                            self.celltype.post_synaptic_receptors[component_label],
+                            names_by_component[component_label],
+                            component_label))
             else:
                 parameter_space = _get_component_parameters(self.celltype, names)
         else:
@@ -85,7 +82,8 @@ class PopulationView(common.PopulationView, PopulationMixin):
     def _get_parameters(self, *names):
         if isinstance(self.celltype, StandardCellType):
             if any(name in self.celltype.computed_parameters() for name in names):
-                native_names = self.celltype.get_native_names()  # need all parameters in order to calculate values
+                # need all parameters in order to calculate values
+                native_names = self.celltype.get_native_names()
             else:
                 native_names = self.celltype.get_native_names(*names)
             native_parameter_space = self._get_native_parameters(*native_names)
@@ -136,9 +134,9 @@ class Population(common.Population, PopulationMixin):
 
     def _create_cells(self):
         id_range = np.arange(simulator.state.id_counter,
-                                simulator.state.id_counter + self.size)
+                             simulator.state.id_counter + self.size)
         self.all_cells = np.array([simulator.ID(id) for id in id_range],
-                                     dtype=simulator.ID)
+                                  dtype=simulator.ID)
         # all cells are local. This doesn't seem very efficient.
         self._mask_local = np.ones((self.size,), bool)
 

pyNN/brian2/projections.py

@@ -8,11 +8,11 @@
 from collections import defaultdict
 import numpy as np
 import brian2
-from brian2 import uS, nA, mV, ms, second
+from brian2 import uS, nA, mV, ms
 from pyNN import common
 from pyNN.standardmodels.synapses import TsodyksMarkramSynapse
 from pyNN.core import is_listlike
-from pyNN.parameters import ParameterSpace, simplify
+from pyNN.parameters import ParameterSpace
 from pyNN.space import Space
 from . import simulator
 from .standardmodels.synapses import StaticSynapse
@@ -112,7 +112,10 @@ def __init__(self, presynaptic_population, postsynaptic_population,
                 # complete the synapse type equations according to the
                 # post-synaptic response type
                 psv = post.celltype.post_synaptic_variables[self.receptor_type]
-                if hasattr(post.celltype, "voltage_based_synapses") and post.celltype.voltage_based_synapses:
+                if (
+                    hasattr(post.celltype, "voltage_based_synapses")
+                    and post.celltype.voltage_based_synapses
+                ):
                     weight_units = mV
                 else:
                     weight_units = post.celltype.conductance_based and uS or nA
@@ -222,10 +225,12 @@ def _convergent_connect(self, presynaptic_indices, postsynaptic_index,
                             except TypeError as err:
                                 if "read-only" in str(err):
                                     logger.info(
-                                        "Cannot set synaptic initial value for variable {}".format(name))
+                                        f"Cannot set synaptic initial value for variable {name}")
                                 else:
                                     raise
-                    # brian2_var[i, j] = value  # doesn't work with multiple connections between a given neuron pair. Need to understand the internals of Synapses and SynapticVariable better
+                    # brian2_var[i, j] = value
+                    # ^ doesn't work with multiple connections between a given neuron pair.
+                    #   Need to understand the internals of Synapses and SynapticVariable better
 
     def _set_attributes(self, connection_parameters):
         if isinstance(self.post, common.Assembly) or isinstance(self.pre, common.Assembly):
@@ -288,7 +293,8 @@ def _get_attributes_as_list(self, attribute_names):
                 value = getattr(syn_obj, name)[:]
                 # should really use the translated name
                 native_ps = ParameterSpace({name: value}, shape=value.shape)
-                # this whole "get attributes" thing needs refactoring in all backends to properly use translation
+                # todo: this whole "get attributes" thing needs refactoring
+                #       in all backends to properly use translation
                 ps = self.synapse_type.reverse_translate(native_ps)
                 ps.evaluate()
                 value = ps[name]

pyNN/brian2/recording.py

@@ -5,11 +5,9 @@
 """
 
 import logging
-from collections import defaultdict
 import numpy as np
 import quantities as pq
 import brian2
-from pyNN.core import is_listlike
 from pyNN import recording
 from . import simulator
 
@@ -27,7 +25,6 @@ class Recorder(recording.Recorder):
     _simulator = simulator
 
     def __init__(self, population=None, file=None):
-        __doc__ = recording.Recorder.__doc__
         recording.Recorder.__init__(self, population, file)
         self._devices = {}  # defer creation until first call of run()
 
@@ -37,7 +34,8 @@ def _create_device(self, group, variable):
         if variable == 'spikes':
             self._devices[variable] = brian2.SpikeMonitor(group, record=self.recorded)
         else:
-            varname = self.population.celltype.state_variable_translations[variable]['translated_name']
+            translations = self.population.celltype.state_variable_translations
+            varname = translations[variable]['translated_name']
             neurons_to_record = np.sort(np.fromiter(
                 self.recorded[variable], dtype=int)) - self.population.first_id
             self._devices[variable] = brian2.StateMonitor(group, varname,
@@ -89,8 +87,8 @@ def _get_all_signals(self, variable, ids, clear=False):
             values = getattr(device, varname).T
         else:
             raise NotImplementedError  # todo - construct a mask to get only the desired signals
-        values = self.population.celltype.state_variable_translations[variable]['reverse_transform'](
-            values)
+        translations = self.population.celltype.state_variable_translations
+        values = translations[variable]['reverse_transform'](values)
         # because we use `when='end'`, need to add the value at the beginning of the run
         tmp = np.empty((values.shape[0] + 1, values.shape[1]))
         tmp[1:, :] = values
@@ -109,6 +107,5 @@ def _local_count(self, variable, filter_ids=None):
         indices = np.fromiter(filtered_ids, dtype=int) - padding
         spiky = self._devices['spikes'].spike_trains()
         for i, id in zip(indices, filtered_ids):
-            #N[id] = len(self._devices['spikes'].spiketimes[i])
             N[id] = len(spiky[i])
         return N

pyNN/brian2/simulator.py

@@ -24,7 +24,6 @@
 import brian2
 import numpy as np
 from pyNN import common
-from pyNN.parameters import simplify
 
 
 name = "Brian2"
@@ -113,7 +112,8 @@ def _get_min_delay(self):
             if np.isinf(min_delay):
                 self._min_delay = self.dt
             else:
-                self._min_delay = min_delay * self.dt  # Synapses.delay is an integer, the number of time steps
+                # Synapses.delay is an integer, the number of time steps
+                self._min_delay = min_delay * self.dt
         return self._min_delay
 
     def _set_min_delay(self, delay):