From 52e67bc6f1a65e362baa3f30ecbbb8e16872b2e7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jan=20H=C3=B6nig?= <jan.hoenig@fau.de>
Date: Tue, 8 Feb 2022 14:40:09 +0100
Subject: [PATCH] Fix RNG test cases

---
 pystencils/backends/cbackend.py          | 2 +-
 pystencils_tests/test_conditional_vec.py | 5 ++---
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/pystencils/backends/cbackend.py b/pystencils/backends/cbackend.py
index b631f0a8a..03ab76ea9 100644
--- a/pystencils/backends/cbackend.py
+++ b/pystencils/backends/cbackend.py
@@ -611,7 +611,7 @@ class VectorizedCustomSympyPrinter(CustomSympyPrinter):
         basic_data_type = data_type.base_type
         symbol = self._print(expr)
         if basic_data_type != expr.dtype:
-            symbol = f'(({basic_data_type.data_type})({symbol}))'
+            symbol = f'(({basic_data_type})({symbol}))'
 
         instruction = 'makeVecConst'
         if basic_data_type.is_bool():
diff --git a/pystencils_tests/test_conditional_vec.py b/pystencils_tests/test_conditional_vec.py
index 2d8193a46..c633f5058 100644
--- a/pystencils_tests/test_conditional_vec.py
+++ b/pystencils_tests/test_conditional_vec.py
@@ -86,7 +86,7 @@ def test_boolean_before_loop():
     ast = ps.create_kernel(a, cpu_vectorize_info={'instruction_set': supported_instruction_sets[-1]})
     kernel = ast.compile()
     kernel(f=f_arr, g=g_arr, t2=1.0)
-    print(g)
+    # print(g)
     np.testing.assert_array_equal(g_arr, 1.0)
     kernel(f=f_arr, g=g_arr, t2=-1.0)
     np.testing.assert_array_equal(g_arr, 42.0)
@@ -102,8 +102,7 @@ def test_vec_maskstore(instruction_set, dtype):
     c = [Conditional(data.center() < 1.0, Block([SympyAssignment(data.center(), 2.0)]))]
 
     assignmets = NodeCollection(c)
-    ast = ps.create_kernel(assignmets, target=Target.CPU,
-                           cpu_vectorize_info={'instruction_set': instruction_set})
+    ast = ps.create_kernel(assignmets, target=Target.CPU, cpu_vectorize_info={'instruction_set': instruction_set})
     kernel = ast.compile()
     kernel(data=data_arr)
     np.testing.assert_equal(data_arr[:3, :], 2.0)
-- 
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