diff --git a/pystencils/cpu/cpujit.py b/pystencils/cpu/cpujit.py
index 26dfc7b21169408efa62269b83dafe7b477cc845..dbd0c3c8a4a6190a9b5c6f95ee625caa8aebd582 100644
--- a/pystencils/cpu/cpujit.py
+++ b/pystencils/cpu/cpujit.py
@@ -255,6 +255,8 @@ type_mapping = {
     np.uint16: ('PyLong_AsUnsignedLong', 'uint16_t'),
     np.uint32: ('PyLong_AsUnsignedLong', 'uint32_t'),
     np.uint64: ('PyLong_AsUnsignedLong', 'uint64_t'),
+    np.complex64: (('PyComplex_RealAsDouble', 'PyComplex_ImagAsDouble'), 'ComplexFloat'),
+    np.complex128: (('PyComplex_RealAsDouble', 'PyComplex_ImagAsDouble'), 'ComplexDouble'),
 }
 
 
@@ -265,6 +267,13 @@ if( obj_{name} == NULL) {{  PyErr_SetString(PyExc_TypeError, "Keyword argument '
 if( PyErr_Occurred() ) {{ return NULL; }}
 """
 
+template_extract_complex = """
+PyObject * obj_{name} = PyDict_GetItemString(kwargs, "{name}");
+if( obj_{name} == NULL) {{  PyErr_SetString(PyExc_TypeError, "Keyword argument '{name}' missing"); return NULL; }};
+{target_type} {name}{{ {extract_function_real}( obj_{name} ), {extract_function_imag}( obj_{name} ) }};
+if( PyErr_Occurred() ) {{ return NULL; }}
+"""
+
 template_extract_array = """
 PyObject * obj_{name} = PyDict_GetItemString(kwargs, "{name}");
 if( obj_{name} == NULL) {{  PyErr_SetString(PyExc_TypeError, "Keyword argument '{name}' missing"); return NULL; }};
@@ -396,8 +405,16 @@ def create_function_boilerplate_code(parameter_info, name, insert_checks=True):
             parameters.append("buffer_{name}.shape[{i}]".format(i=param.symbol.coordinate, name=param.field_name))
         else:
             extract_function, target_type = type_mapping[param.symbol.dtype.numpy_dtype.type]
-            pre_call_code += template_extract_scalar.format(extract_function=extract_function, target_type=target_type,
-                                                            name=param.symbol.name)
+            if np.issubdtype(param.symbol.dtype.numpy_dtype, np.complexfloating):
+                pre_call_code += template_extract_complex.format(extract_function_real=extract_function[0],
+                                                                 extract_function_imag=extract_function[1],
+                                                                 target_type=target_type,
+                                                                 name=param.symbol.name)
+            else:
+                pre_call_code += template_extract_scalar.format(extract_function=extract_function,
+                                                                target_type=target_type,
+                                                                name=param.symbol.name)
+
             parameters.append(param.symbol.name)
 
     pre_call_code += equal_size_check(variable_sized_normal_fields)
diff --git a/pystencils_tests/test_complex_numbers.py b/pystencils_tests/test_complex_numbers.py
index abfed6473be8b8b306caacf0f94dfedd1116cddd..9f9164640f50e417348ee635af620dd891249d77 100644
--- a/pystencils_tests/test_complex_numbers.py
+++ b/pystencils_tests/test_complex_numbers.py
@@ -106,7 +106,8 @@ def test_complex_numbers_64(assignment, target):
 
 @pytest.mark.parametrize('dtype', (np.float32, np.float64))
 @pytest.mark.parametrize('target', ('cpu', 'gpu'))
-def test_complex_execution(dtype, target):
+@pytest.mark.parametrize('with_complex_argument', ('with_complex_argument', False))
+def test_complex_execution(dtype, target, with_complex_argument):
 
     complex_dtype = f'complex{64 if dtype ==np.float32 else 128}'
     x, y = pystencils.fields(f'x, y:  {complex_dtype}[2d]')
@@ -114,8 +115,13 @@ def test_complex_execution(dtype, target):
     x_arr = np.zeros((20, 30), complex_dtype)
     y_arr = np.zeros((20, 30), complex_dtype)
 
+    if with_complex_argument:
+        a = pystencils.TypedSymbol('a', create_type(complex_dtype))
+    else:
+        a = (2j+1)
+
     assignments = AssignmentCollection({
-        y.center: x.center * (2j+1)
+        y.center: x.center + a
     })
 
     if target == 'gpu':
@@ -125,4 +131,12 @@ def test_complex_execution(dtype, target):
 
     kernel = pystencils.create_kernel(assignments, target=target, data_type=dtype).compile()
 
-    kernel(x=x_arr, y=y_arr)
+    if with_complex_argument:
+        kernel(x=x_arr, y=y_arr, a=2j+1)
+    else:
+        kernel(x=x_arr, y=y_arr)
+
+    if target == 'gpu':
+        y_arr = y_arr.get()
+    assert np.allclose(y_arr, 2j+1)
+