Correctly handle random parameters appearing in the denominator

lib/sli/nest-init.sli

@@ -413,7 +413,7 @@ def
 
 /CreateParameter trie
 [/dictionarytype] /CreateParameter_D load addtotrie
-[/doubletype] /CreateParameter_D load addtotrie
+[/doubletype] { /val Set << /constant << /value val >> >> CreateParameter_D } addtotrie
 def
 
 /GetValue [/parametertype]

pynest/nest/lib/hl_api_types.py

@@ -1077,8 +1077,7 @@ def __truediv__(self, rhs):
         return self._binop("div", rhs)
 
     def __rtruediv__(self, lhs):
-        rhs_inv = CreateParameter("constant", {"value": 1 / float(self.GetValue())})
-        return rhs_inv._binop("mul", lhs)
+        return self**-1 * lhs
 
     def __pow__(self, exponent):
         try:

testsuite/pytests/test_regression_issue-3156.py

@@ -0,0 +1,86 @@
+# -*- coding: utf-8 -*-
+#
+# test_regression_issue-3156.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 operator as ops
+
+import nest
+import pytest
+
+"""
+Tests to ensure that random parameters can be used with all operators that support parameters.
+
+We expect that each parameter value drawn will differ from all others.
+"""
+
+
+@pytest.fixture(autouse=True)
+def reset():
+    nest.ResetKernel()
+
+
+num_neurons = 10
+operators = [ops.add, ops.sub, ops.mul, ops.truediv, ops.pow, ops.mod]
+
+
+@pytest.mark.parametrize("lhs", [1, 2, 2.0])
+@pytest.mark.parametrize("op", operators)
+def test_params_random_denominator(lhs, op):
+    num_neurons = 10
+    try:
+        n = nest.Create("iaf_psc_alpha", num_neurons, {"V_m": op(lhs, nest.random.uniform(1, 2))})
+    except TypeError:
+        pass  # operation not supported for parameter
+    else:
+        assert len(set(n.V_m)) == num_neurons
+
+
+@pytest.mark.parametrize("op", operators)
+@pytest.mark.parametrize("rhs", [1, 2, 2.0])
+def test_params_random_numerator(op, rhs):
+    num_neurons = 10
+
+    try:
+        n = nest.Create("iaf_psc_alpha", num_neurons, {"V_m": op(nest.random.uniform(1, 2), rhs)})
+    except TypeError:
+        pass  # operation not supported for parameter
+    else:
+        assert len(set(n.V_m)) == num_neurons
+
+
+def test_random_numer_and_denom():
+    """
+    For random parameters in numerator and denominator, we make the denominator uniform
+    on the set {-1, +1}. For 50 neurons, the probability that the denominator has the same
+    sign (either positive or negative) is 2 * 2^-50 ≈ 2e-15.
+    """
+
+    num_neurons = 50
+    try:
+        n = nest.Create(
+            "iaf_psc_alpha", num_neurons, {"V_m": nest.random.uniform(1, 2) / (1.0 - 2.0 * nest.random.uniform_int(2))}
+        )
+    except TypeError:
+        pass
+    else:
+        V_m = n.V_m
+        assert len(set(n.V_m)) == num_neurons
+        assert sum(V < 0 for V in V_m) > 0
+        assert sum(V >= 0 for V in V_m) > 0