Bugfix - Vectorization of in-place LB update wrong

Block.subs method tried to be too smart:
a = field[..]
b = a + b

was "simplified" incorrectly to
b = field[...] + b

pystencils/astnodes.py

@@ -212,6 +212,8 @@ class KernelFunction(Node):
 
         argument_symbols = self._body.undefined_symbols - self.global_variables
         parameters = [self.Parameter(symbol, get_fields(symbol)) for symbol in argument_symbols]
+        if hasattr(self, 'indexing'):
+            parameters += [self.Parameter(s, []) for s in self.indexing.symbolic_parameters()]
         parameters.sort(key=lambda p: p.symbol.name)
         return parameters
 
@@ -252,14 +254,6 @@ class Block(Node):
         return self._nodes
 
     def subs(self, subs_dict) -> None:
-        new_args = []
-        for a in self.args:
-            if isinstance(a, SympyAssignment) and a.is_declaration and a.rhs in subs_dict.keys():
-                subs_dict[a.lhs] = subs_dict[a.rhs]
-            else:
-                new_args.append(a)
-        self._nodes = new_args
-
         for a in self.args:
             a.subs(subs_dict)
 

pystencils_tests/test_vectorization.py

@@ -25,6 +25,26 @@ def test_vector_type_propagation():
     np.testing.assert_equal(dst[1:-1, 1:-1], 2 * 10.0 + 3)
 
 
+def test_inplace_update():
+    shape = (9, 9, 3)
+    arr = np.ones(shape, order='f')
+
+    @ps.kernel
+    def update_rule(s):
+        f = ps.fields("f(3) : [2D]", f=arr)
+        s.tmp0 @= f(0)
+        s.tmp1 @= f(1)
+        s.tmp2 @= f(2)
+        f0, f1, f2 = f(0), f(1), f(2)
+        f0 @= 2 * s.tmp0
+        f1 @= 2 * s.tmp0
+        f2 @= 2 * s.tmp0
+
+    ast = ps.create_kernel(update_rule, cpu_vectorize_info={'instruction_set': 'avx'})
+    kernel = ast.compile()
+    kernel(f=arr)
+    np.testing.assert_equal(arr, 2)
+
 def test_vectorization_fixed_size():
     configurations = []
     # Fixed size - multiple of four