minor fixes

NeuralEnsemble · Oct 14, 2022 · df7568c · df7568c
1 parent a79a351
commit df7568c
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Showing 10 changed files with 41 additions and 48 deletions.
diff --git a/test/system/scenarios/test_issue274.py b/test/system/scenarios/test_issue274.py
@@ -1,7 +1,6 @@
 
 from pyNN.random import RandomDistribution as rnd
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron", "brian2")

diff --git a/test/system/scenarios/test_parameter_handling.py b/test/system/scenarios/test_parameter_handling.py
@@ -3,7 +3,6 @@
 from numpy import nan
 from numpy.testing import assert_array_equal, assert_allclose
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron", "brian2")

diff --git a/test/system/scenarios/test_procedural_api.py b/test/system/scenarios/test_procedural_api.py
@@ -3,7 +3,6 @@
 from numpy.testing import assert_allclose
 from pyNN.utility import init_logging
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron", "brian2")

diff --git a/test/system/scenarios/test_recording.py b/test/system/scenarios/test_recording.py
@@ -7,7 +7,6 @@
 from neo.io import get_io
 from pyNN.utility import normalized_filename
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("neuron", "brian2")

diff --git a/test/system/scenarios/test_scenario1.py b/test/system/scenarios/test_scenario1.py
@@ -3,7 +3,6 @@
 import os
 from pyNN.random import NumpyRNG, RandomDistribution
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron", "brian2")

diff --git a/test/system/scenarios/test_scenario2.py b/test/system/scenarios/test_scenario2.py
@@ -1,7 +1,6 @@
 
 import numpy as np
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron", "brian2")

diff --git a/test/system/scenarios/test_scenario4.py b/test/system/scenarios/test_scenario4.py
@@ -5,7 +5,6 @@
 from pyNN.space import Space, Grid3D, RandomStructure, Cuboid
 from pyNN.utility import init_logging
 from .fixtures import run_with_simulators
-import pytest
 
 
 logger = logging.getLogger("TEST")

diff --git a/test/system/scenarios/test_synapse_types.py b/test/system/scenarios/test_synapse_types.py
@@ -1,7 +1,6 @@
 
 import numpy as np
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron")

diff --git a/test/system/scenarios/test_ticket166.py b/test/system/scenarios/test_ticket166.py
@@ -1,7 +1,6 @@
 
 import numpy as np
 from .fixtures import run_with_simulators
-import pytest
 
 
 @run_with_simulators("nest", "neuron", "brian2")

diff --git a/test/system/test_serialization.py b/test/system/test_serialization.py
@@ -21,45 +21,47 @@
 import pytest
 
 def test():
-    if not HAVE_H5PY and HAVE_NEST:
-        pytest.skip("Either h5py or nest is not available")
-
-    sim.setup()
-
-    p1 = sim.Population(10,
-                        sim.IF_cond_exp(
-                            v_rest=-65,
-                            tau_m=lambda i: 10 + 0.1*i,
-                            cm=RD('normal', (0.5, 0.05))),
-                        label="population_one")
-    p2 = sim.Population(20,
-                        sim.IF_curr_alpha(
-                            v_rest=-64,
-                            tau_m=lambda i: 11 + 0.1*i),
-                        label="population_two")
-
-    prj = sim.Projection(p1, p2,
-                         sim.FixedProbabilityConnector(p_connect=0.5),
-                         synapse_type=sim.StaticSynapse(weight=RD('uniform', [0.0, 0.1]),
-                                                        delay=0.5),
-                         receptor_type='excitatory')
-
-    net = Network(p1, p2, prj)
-
-    export_to_sonata(net, "tmp_serialization_test", overwrite=True)
-
-    net2 = import_from_sonata("tmp_serialization_test/circuit_config.json", sim)
-
-    for orig_population in net.populations:
-        imp_population = net2.get_component(orig_population.label)
-        assert orig_population.size == imp_population.size
-        for name in orig_population.celltype.default_parameters:
-            assert_array_almost_equal(orig_population.get(name), imp_population.get(name), 12)
-
-    w1 = prj.get('weight', format='array')
-    prj2 = net2.get_component(asciify(prj.label).decode('utf-8') + "-0")
-    w2 = prj2.get('weight', format='array')
-    assert_array_almost_equal(w1, w2, 12)
+    if not HAVE_H5PY:
+        pytest.skip("h5py not available")
+    elif not HAVE_NEST:
+        pytest.skip("nest not available")
+    else:
+        sim.setup()
+
+        p1 = sim.Population(10,
+                            sim.IF_cond_exp(
+                                v_rest=-65,
+                                tau_m=lambda i: 10 + 0.1*i,
+                                cm=RD('normal', (0.5, 0.05))),
+                            label="population_one")
+        p2 = sim.Population(20,
+                            sim.IF_curr_alpha(
+                                v_rest=-64,
+                                tau_m=lambda i: 11 + 0.1*i),
+                            label="population_two")
+
+        prj = sim.Projection(p1, p2,
+                            sim.FixedProbabilityConnector(p_connect=0.5),
+                            synapse_type=sim.StaticSynapse(weight=RD('uniform', [0.0, 0.1]),
+                                                            delay=0.5),
+                            receptor_type='excitatory')
+
+        net = Network(p1, p2, prj)
+
+        export_to_sonata(net, "tmp_serialization_test", overwrite=True)
+
+        net2 = import_from_sonata("tmp_serialization_test/circuit_config.json", sim)
+
+        for orig_population in net.populations:
+            imp_population = net2.get_component(orig_population.label)
+            assert orig_population.size == imp_population.size
+            for name in orig_population.celltype.default_parameters:
+                assert_array_almost_equal(orig_population.get(name), imp_population.get(name), 12)
+
+        w1 = prj.get('weight', format='array')
+        prj2 = net2.get_component(asciify(prj.label).decode('utf-8') + "-0")
+        w2 = prj2.get('weight', format='array')
+        assert_array_almost_equal(w1, w2, 12)
 
 
 if __name__ == "__main__":