Address #13: Use sympy.codegen.rewriting.optimize

It's really comfortable to write optimizations in terms of sympy.codegen.rewrite.RewriteOptim:

    # Evaluates all constant terms
    evaluate_constant_terms = ReplaceOptim(
        lambda e: hasattr(e, 'is_constant') and e.is_constant,
        lambda p: p.evalf()
    )

This PR adds a parameter sympy_optimizations to the create_*_kernel functions that applies the list of optimizations to the assignments before creating the AST.

sympy.codegen.rewrite already has some optimizations. Some similar to the optimizations of pystencils. For example create_expand_pow_optimization(limit) is really similar to the logic in CustomSympyPrinter._print_Pow.

See #13 (closed)

Problem: old versions of sympy (e.g. from ubuntu CI) don't have sympy.codegen.rewrite. The optimizations are skipped in that case. test_and_coverage applies all optimizations.

We could also try to implement a fma-optimization (fused-multipy add) with that and sympy.Wild.

pystencils/math_optimizations.py

@@ -9,6 +9,7 @@ import itertools
 
 from pystencils import Assignment
 from pystencils.astnodes import SympyAssignment
+from pystencils.integer_functions import IntegerFunctionTwoArgsMixIn
 
 try:
     from sympy.codegen.rewriting import optims_c99, optimize
@@ -24,6 +25,9 @@ try:
     optims_pystencils_cpu = [evaluate_constant_terms] + list(optims_c99)
     optims_pystencils_gpu = [evaluate_constant_terms] + list(optims_c99)
 except ImportError:
+    from warnings import warn
+    warn("Could not import ReplaceOptim, optims_c99, optimize from sympy.codegen.rewriting."
+         "Please update your sympy installation!")
     optims_c99 = []
     optims_pystencils_cpu = []
     optims_pystencils_gpu = []
@@ -34,7 +38,8 @@ def optimize_assignments(assignments, optimizations):
 
     if HAS_REWRITING:
         assignments = [Assignment(a.lhs, optimize(a.rhs, optimizations))
-                       if hasattr(a, 'lhs') else a for a in assignments]
+                       if hasattr(a, 'lhs') and not a.rhs.atoms(IntegerFunctionTwoArgsMixIn)
+                       else a for a in assignments]
         assignments_nodes = [a.atoms(SympyAssignment) for a in assignments]
         for a in itertools.chain.from_iterable(assignments_nodes):
             a.optimize(optimizations)