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Commit 87f5cfdd authored by Markus Holzer's avatar Markus Holzer
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Replaced all format strings with f-strings in test cases

parent bced838a
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......@@ -19,7 +19,7 @@ def check_equivalence(assignments, src_arr):
with_blocking = ps.create_kernel(assignments, cpu_blocking=(8, 16, 4), cpu_openmp=openmp,
cpu_vectorize_info=vectorization).compile()
without_blocking = ps.create_kernel(assignments).compile()
print(" openmp {}, vectorization {}".format(openmp, vectorization))
print(f" openmp {openmp}, vectorization {vectorization}")
dst_arr = np.zeros_like(src_arr)
ref_arr = np.zeros_like(src_arr)
np.copyto(src_arr, np.random.rand(*src_arr.shape))
......
......@@ -125,7 +125,7 @@ def test_rotate_interpolation_gpu(dtype, address_mode, use_textures):
else:
lenna_gpu = gpuarray.to_gpu(
np.ascontiguousarray(lenna, dtype))
x_f, y_f = pystencils.fields('x,y: %s [2d]' % type_map[dtype], ghost_layers=0)
x_f, y_f = pystencils.fields(f'x,y: {type_map[dtype]} [2d]', ghost_layers=0)
transformed = scale * \
sympy.rot_axis3(rotation_angle)[:2, :2] * sympy.Matrix((x_, y_)) - sympy.Matrix([2, 2])
......@@ -173,7 +173,7 @@ def test_shift_interpolation_gpu(address_mode, dtype, use_textures):
lenna_gpu = gpuarray.to_gpu(
np.ascontiguousarray(lenna, dtype))
x_f, y_f = pystencils.fields('x,y: %s [2d]' % type_map[dtype], ghost_layers=0)
x_f, y_f = pystencils.fields(f'x,y: {type_map[dtype]} [2d]', ghost_layers=0)
if use_textures:
transformed = scale * sympy.rot_axis3(rotation_angle)[:2, :2] * sympy.Matrix((x_, y_)) + shift
......
......@@ -112,7 +112,7 @@ def test_staggered_iteration_manual():
def test_staggered_gpu():
dim = 2
f = ps.fields("f: double[{dim}D]".format(dim=dim))
f = ps.fields(f"f: double[{dim}D]")
s = ps.fields("s({dim}): double[{dim}D]".format(dim=dim), field_type=FieldType.STAGGERED)
expressions = [(f[0, 0] + f[-1, 0]) / 2,
(f[0, 0] + f[0, -1]) / 2]
......
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