Merge pull request #404 from brian-team/lio_optional

Make the "loop-invariant optimisations" optional via a preference

brian2/codegen/_prefs.py

@@ -39,5 +39,15 @@
         Accepts the same arguments as `codegen.target`.
         ''',
         validator=lambda target: isinstance(target, basestring) or issubclass(target, CodeObject),
+        ),
+    loop_invariant_optimisations=BrianPreference(
+        default=True,
+        docs='''
+        Whether to pull out scalar expressions out of the statements, so that
+        they are only evaluated once instead of once for every neuron/synapse/...
+        Can be switched off, e.g. because it complicates the code (and the same
+        optimisation is already performed by the compiler) or because the
+        code generation target does not deal well with it. Defaults to ``True``.
+        '''
     )
-    )
+)

brian2/codegen/translation.py

@@ -24,6 +24,7 @@
 
 import numpy as np
 
+from brian2.core.preferences import prefs
 from brian2.core.variables import Variable, Subexpression, AuxiliaryVariable
 from brian2.core.functions import Function
 from brian2.utils.stringtools import (deindent, strip_empty_lines,
@@ -469,10 +470,12 @@ def make_statements(code, variables, dtype):
 
     scalar_statements = [s for s in statements if s.scalar]
     vector_statements = [s for s in statements if not s.scalar]
-    scalar_constants, vector_statements = apply_loop_invariant_optimisations(vector_statements,
-                                                                             variables,
-                                                                             dtype)
-    scalar_statements.extend(scalar_constants)
+
+    if prefs.codegen.loop_invariant_optimisations:
+        scalar_constants, vector_statements = apply_loop_invariant_optimisations(vector_statements,
+                                                                                 variables,
+                                                                                 dtype)
+        scalar_statements.extend(scalar_constants)
 
     return scalar_statements, vector_statements