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Commit f46b5976 authored by Michael Kuron's avatar Michael Kuron :mortar_board:
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restore fixed interpolation test

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pystencils_tests/test_interpolation.py
+ 48
− 46
View file @ f46b5976
......@@ -14,8 +14,6 @@ import numpy as np
import pytest
import sympy
import pytest
import pystencils
from pystencils.interpolation_astnodes import LinearInterpolator
from pystencils.spatial_coordinates import x_, y_
......@@ -51,7 +49,7 @@ def test_interpolation():
print(assignments)
ast = pystencils.create_kernel(assignments)
print(ast)
pystencils.show_code(ast)
print(pystencils.show_code(ast))
kernel = ast.compile()
pyconrad.imshow(lenna)
......@@ -71,7 +69,7 @@ def test_scale_interpolation():
print(assignments)
ast = pystencils.create_kernel(assignments)
print(ast)
pystencils.show_code(ast)
print(pystencils.show_code(ast))
kernel = ast.compile()
out = np.zeros_like(lenna)
......@@ -83,9 +81,9 @@ def test_scale_interpolation():
['border',
'clamp',
pytest.param('warp', marks=pytest.mark.xfail(
reason="Fails on newer SymPy version due to complex conjugate()")),
reason="requires interpolation-refactoring branch")),
pytest.param('mirror', marks=pytest.mark.xfail(
reason="Fails on newer SymPy version due to complex conjugate()")),
reason="requires interpolation-refactoring branch")),
])
def test_rotate_interpolation(address_mode):
"""
......@@ -102,7 +100,7 @@ def test_rotate_interpolation(address_mode):
print(assignments)
ast = pystencils.create_kernel(assignments)
print(ast)
pystencils.show_code(ast)
print(pystencils.show_code(ast))
kernel = ast.compile()
out = np.zeros_like(lenna)
......@@ -114,10 +112,10 @@ def test_rotate_interpolation(address_mode):
@pytest.mark.parametrize('address_mode', ('border', 'wrap', 'clamp', 'mirror'))
@pytest.mark.parametrize('use_textures', ('use_textures', False))
def test_rotate_interpolation_gpu(dtype, address_mode, use_textures):
pytest.importorskip("pycuda")
import pycuda.autoinit # NOQA
import pycuda.gpuarray as gpuarray
pytest.importorskip('pycuda')
import pycuda.gpuarray as gpuarray
import pycuda.autoinit # noqa
rotation_angle = sympy.pi / 5
scale = 1
......@@ -144,52 +142,56 @@ def test_rotate_interpolation_gpu(dtype, address_mode, use_textures):
kernel(x=lenna_gpu, y=out)
pyconrad.imshow(out,
f"out {address_mode} texture:{use_textures} {type_map[dtype]}")
skimage.io.imsave(f"/tmp/out {address_mode} texture:{use_textures} {type_map[dtype]}.tif",
np.ascontiguousarray(out.get(), np.float32))
@pytest.mark.parametrize('address_mode', ['border', 'wrap', 'clamp', 'mirror'])
@pytest.mark.parametrize('address_mode', ['border', 'wrap',
pytest.param('warp', marks=pytest.mark.xfail(
reason="% printed as fmod on old sympy")),
pytest.param('mirror', marks=pytest.mark.xfail(
reason="% printed as fmod on old sympy")),
])
@pytest.mark.parametrize('dtype', [np.float64, np.float32, np.int32])
@pytest.mark.parametrize('use_textures', ('use_textures', False,))
def test_shift_interpolation_gpu(address_mode, dtype, use_textures):
pytest.importorskip("pycuda")
import pycuda.autoinit # NOQA
sver = sympy.__version__.split(".")
if (int(sver[0]) == 1 and int(sver[1]) < 2) and address_mode in ['mirror', 'warp']:
pytest.skip()
pytest.importorskip('pycuda')
import pycuda.gpuarray as gpuarray
import pycuda.autoinit # noqa
rotation_angle = 0 # sympy.pi / 5
scale = 1
# shift = - sympy.Matrix([1.5, 1.5])
shift = sympy.Matrix((0.0, 0.0))
for dtype in [np.float64, np.float32, np.int32]:
if dtype == np.int32:
lenna_gpu = gpuarray.to_gpu(
np.ascontiguousarray(lenna * 255, dtype))
else:
lenna_gpu = gpuarray.to_gpu(
np.ascontiguousarray(lenna, dtype))
for use_textures in [True, False]:
x_f, y_f = pystencils.fields('x,y: %s [2d]' % type_map[dtype], ghost_layers=0)
if use_textures:
transformed = scale * sympy.rot_axis3(rotation_angle)[:2, :2] * sympy.Matrix((x_, y_)) + shift
else:
transformed = scale * sympy.rot_axis3(rotation_angle)[:2, :2] * sympy.Matrix((x_, y_)) + shift
assignments = pystencils.AssignmentCollection({
y_f.center(): LinearInterpolator(x_f, address_mode=address_mode).at(transformed)
})
# print(assignments)
ast = pystencils.create_kernel(assignments, target='gpu', use_textures_for_interpolation=use_textures)
# print(ast)
pystencils.show_code(ast)
kernel = ast.compile()
out = gpuarray.zeros_like(lenna_gpu)
kernel(x=lenna_gpu, y=out)
pyconrad.imshow(out,
f"out {address_mode} texture:{use_textures} {type_map[dtype]}")
skimage.io.imsave(f"/tmp/out {address_mode} texture:{use_textures} {type_map[dtype]}.tif",
np.ascontiguousarray(out.get(), np.float32))
if dtype == np.int32:
lenna_gpu = gpuarray.to_gpu(
np.ascontiguousarray(lenna * 255, dtype))
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)
if use_textures:
transformed = scale * sympy.rot_axis3(rotation_angle)[:2, :2] * sympy.Matrix((x_, y_)) + shift
else:
transformed = scale * sympy.rot_axis3(rotation_angle)[:2, :2] * sympy.Matrix((x_, y_)) + shift
assignments = pystencils.AssignmentCollection({
y_f.center(): LinearInterpolator(x_f, address_mode=address_mode).at(transformed)
})
# print(assignments)
ast = pystencils.create_kernel(assignments, target='gpu', use_textures_for_interpolation=use_textures)
# print(ast)
print(pystencils.show_code(ast))
kernel = ast.compile()
out = gpuarray.zeros_like(lenna_gpu)
kernel(x=lenna_gpu, y=out)
pyconrad.imshow(out,
f"out {address_mode} texture:{use_textures} {type_map[dtype]}")
@pytest.mark.parametrize('address_mode', ['border', 'clamp'])
......@@ -208,7 +210,7 @@ def test_rotate_interpolation_size_change(address_mode):
print(assignments)
ast = pystencils.create_kernel(assignments)
print(ast)
pystencils.show_code(ast)
print(pystencils.show_code(ast))
kernel = ast.compile()
out = np.zeros((100, 150), np.float64)
......@@ -227,7 +229,7 @@ def test_field_interpolated(address_mode, target):
print(assignments)
ast = pystencils.create_kernel(assignments, target=target)
print(ast)
pystencils.show_code(ast)
print(pystencils.show_code(ast))
kernel = ast.compile()
out = np.zeros_like(lenna)
......
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