fixed create_kernel parameter data_type="float" to procucde single precision

Currently if create_kernel(assignments, data_type="float") is used then the untyped symbols are typed with float64, since the np.dtype("float") creates this during the construction of a new TypedSymbol.

Since data_type or as it is called in cpu.create_kernel type_info can be an string of an C type, At least following the documentation of cpu.create_kernel this behavior is a bit confusing, since typical the C type specifier "float" is meant to be single precision.

So I added a small function that just replaces "float" with "single" in the symbol_to_type dict, so the untyped symbols get the single precision type.

pystencils/transformations.py

@@ -960,6 +960,8 @@ def add_types(eqs, type_for_symbol, check_independence_condition, check_double_w
     if isinstance(type_for_symbol, (str, type)) or not hasattr(type_for_symbol, '__getitem__'):
         type_for_symbol = typing_from_sympy_inspection(eqs, type_for_symbol)
 
+    type_for_symbol = adjust_c_single_precision_type(type_for_symbol)
+
     check = KernelConstraintsCheck(type_for_symbol, check_independence_condition,
                                    check_double_write_condition=check_double_write_condition)
 
@@ -1397,3 +1399,16 @@ def implement_interpolations(ast_node: ast.Node,
             ast_node.subs(substitutions)
 
     return ast_node
+
+
+def adjust_c_single_precision_type(type_for_symbol):
+    """Replaces every occurrence of 'float' with 'single' to enforce the numpy single precision type."""
+    def single_factory():
+        return "single"
+
+    for symbol in type_for_symbol:
+        if type_for_symbol[symbol] == "float":
+            type_for_symbol[symbol] = single_factory()
+    if hasattr(type_for_symbol, "default_factory") and type_for_symbol.default_factory() == "float":
+        type_for_symbol.default_factory = single_factory
+    return type_for_symbol