Port test_spatial_pairwise_bernoulli_on_source_param from SLI to Py

testsuite/pytests/sli2py_mpi/test_spatial_randomized_positions.py

@@ -0,0 +1,57 @@
+# -*- coding: utf-8 -*-
+#
+# test_spatial_randomized_positions.py
+#
+# This file is part of NEST.
+#
+# Copyright (C) 2004 The NEST Initiative
+#
+# NEST is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 2 of the License, or
+# (at your option) any later version.
+#
+# NEST is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with NEST.  If not, see <http://www.gnu.org/licenses/>.
+
+import pytest
+from mpi_test_wrapper import MPITestAssertEqual
+
+"""
+Confirm that spatial positions are consistently generated from random parameters.
+"""
+
+
+@pytest.mark.skipif_incompatible_mpi
+@pytest.mark.skipif_missing_threads
+@MPITestAssertEqual([1, 2, 4], debug=False)
+def test_spatial_connections():
+    """
+    Confirm that spatial positions are created consistently.
+
+    The test is performed on connection data written to OTHER_LABEL.
+    """
+
+    import nest
+    import numpy as np
+    import pandas as pd
+
+    nest.total_num_virtual_procs = 4
+
+    layer = nest.Create(
+        "parrot_neuron",
+        n=10,
+        positions=nest.spatial.free([nest.random.uniform(0, 1), nest.random.uniform(2, 3), nest.random.uniform(4, 5)]),
+    )
+    pos = pd.DataFrame(layer.spatial["positions"], columns=["x", "y", "z"])
+
+    assert all((0 <= pos.x) & (pos.x <= 1))
+    assert all((2 <= pos.y) & (pos.y <= 3))
+    assert all((4 <= pos.z) & (pos.z <= 5))
+
+    pos.to_csv(OTHER_LABEL.format(nest.num_processes, nest.Rank()), index=False, sep="\t")  # noqa: F821