updates to formatting for bumping psf/black version #3330

Author: terhorstd

pynest/examples/EI_clustered_network/network_EI.py

@@ -147,14 +147,18 @@ def create_populations(self):
             "t_ref": self._params["t_ref"],
             "V_th": self._params["V_th_E"],
             "V_reset": self._params["V_r"],
-            "I_e": I_xE
-            if self._params["delta_I_xE"] == 0
-            else I_xE * nest.random.uniform(1 - self._params["delta_I_xE"] / 2, 1 + self._params["delta_I_xE"] / 2),
+            "I_e": (
+                I_xE
+                if self._params["delta_I_xE"] == 0
+                else I_xE * nest.random.uniform(1 - self._params["delta_I_xE"] / 2, 1 + self._params["delta_I_xE"] / 2)
+            ),
             "tau_syn_ex": self._params["tau_syn_ex"],
             "tau_syn_in": self._params["tau_syn_in"],
-            "V_m": self._params["V_m"]
-            if not self._params["V_m"] == "rand"
-            else self._params["V_th_E"] - 20 * nest.random.lognormal(0, 1),
+            "V_m": (
+                self._params["V_m"]
+                if not self._params["V_m"] == "rand"
+                else self._params["V_th_E"] - 20 * nest.random.lognormal(0, 1)
+            ),
         }
         I_neuron_params = {
             "E_L": self._params["E_L"],
@@ -163,14 +167,18 @@ def create_populations(self):
             "t_ref": self._params["t_ref"],
             "V_th": self._params["V_th_I"],
             "V_reset": self._params["V_r"],
-            "I_e": I_xI
-            if self._params["delta_I_xE"] == 0
-            else I_xI * nest.random.uniform(1 - self._params["delta_I_xE"] / 2, 1 + self._params["delta_I_xE"] / 2),
+            "I_e": (
+                I_xI
+                if self._params["delta_I_xE"] == 0
+                else I_xI * nest.random.uniform(1 - self._params["delta_I_xE"] / 2, 1 + self._params["delta_I_xE"] / 2)
+            ),
             "tau_syn_ex": self._params["tau_syn_ex"],
             "tau_syn_in": self._params["tau_syn_in"],
-            "V_m": self._params["V_m"]
-            if not self._params["V_m"] == "rand"
-            else self._params["V_th_I"] - 20 * nest.random.lognormal(0, 1),
+            "V_m": (
+                self._params["V_m"]
+                if not self._params["V_m"] == "rand"
+                else self._params["V_th_I"] - 20 * nest.random.lognormal(0, 1)
+            ),
         }
 
         # iaf_psc_exp allows stochasticity, if not used - don't supply the parameters and use

pynest/examples/lin_rate_ipn_network.py

@@ -74,7 +74,7 @@
     # time constant of neuronal dynamics in ms
     "mu": 2.0,
     # mean input
-    "sigma": 5.0
+    "sigma": 5.0,
     # noise parameter
 }
 

testsuite/pytests/test_erfc_neuron.py

@@ -71,7 +71,6 @@ def activation_function_theory(sigma, theta):
 
 
 class ErfcNeuronTheoryTestCase(unittest.TestCase):
-
     """Compare results to theoretical predictions"""
 
     def setUp(self):

testsuite/pytests/test_rate_copy_model.py

@@ -27,7 +27,6 @@
 
 @nest.ll_api.check_stack
 class RateCopyModelTestCase(unittest.TestCase):
-
     """
     Test whether a rate connection created by copy model behaves
     identical to the original version

testsuite/pytests/test_rate_instantaneous_and_delayed.py

@@ -27,7 +27,6 @@
 
 @nest.ll_api.check_stack
 class RateInstantaneousAndDelayedTestCase(unittest.TestCase):
-
     """
     Test whether delayed rate connections have same properties as
     instantaneous connections but with the correct delay

testsuite/pytests/test_rate_neuron.py

@@ -33,7 +33,6 @@
 
 @nest.ll_api.check_stack
 class RateNeuronTestCase(unittest.TestCase):
-
     """Check rate_neuron"""
 
     def setUp(self):

testsuite/pytests/test_rate_neuron_communication.py

@@ -34,7 +34,6 @@ def H(x):
 
 @nest.ll_api.check_stack
 class RateNeuronCommunicationTestCase(unittest.TestCase):
-
     """Check rate_neuron"""
 
     def setUp(self):

testsuite/pytests/test_sp/test_growth_curves.py

@@ -217,7 +217,6 @@ def growth_curve(self, t):
 
 
 class SigmoidNumericSEI(SynapticElementIntegrator):
-
     """
     Compute the number of synaptic element corresponding to a
     sigmoid growth curve

testsuite/pytests/test_step_rate_generator.py

@@ -27,7 +27,6 @@
 
 @nest.ll_api.check_stack
 class StepRateGeneratorTestCase(unittest.TestCase):
-
     """
     Test whether the step_rate_generator produces and
     communicates the desired rates

testsuite/pytests/test_vogels_sprekeler_synapse.py

@@ -29,7 +29,6 @@
 
 @nest.ll_api.check_stack
 class VogelsSprekelerConnectionTestCase(unittest.TestCase):
-
     """Check vogels_sprekeler_synapse model properties."""
 
     def setUp(self):