diff --git a/ci/docker_images/ubuntu/bionic/Dockerfile b/ci/docker_images/ubuntu/bionic/Dockerfile
index dcd4f1cd110ce34a79048d31e69c72465265eacb..4c2cb4e8a5143cec09d74c8492d5ad82ac3ec774 100644
--- a/ci/docker_images/ubuntu/bionic/Dockerfile
+++ b/ci/docker_images/ubuntu/bionic/Dockerfile
@@ -65,7 +65,6 @@ RUN pip install --upgrade scipy
RUN pip install --upgrade sympy
RUN pip install --upgrade matplotlib
RUN pip install --upgrade mpi4py
-RUN pip install --upgrade sphinx
RUN pip install --upgrade h5py
RUN pip install --upgrade gmpy2
RUN pip install --upgrade psutil
@@ -82,6 +81,16 @@ RUN pip install --upgrade weave
RUN pip install --upgrade argparse_color_formatter
RUN pip install --upgrade numba
+# For documentation
+# RUN pip install --upgrade sphinx
+# RUN pip install --upgrade sphinxcontrib-bibtex
+# RUN pip install --upgrade sphinx_bootstrap_theme
+# RUN pip install --upgrade strip-hints
+# RUN cd /tmp && git clone https://github.com/sphinx-contrib/doxylink.git && cd doxylink/sphinxcontrib/doxylink \
+# && mv doxylink.py doxylink.py3 && strip-hints doxylink.py3 > doxylink.py && rm doxylink.py3 \
+# && mv parsing.py parsing.py3 && strip-hints parsing.py3 > parsing.py && rm parsing.py3 \
+# && python setup.py install
+
# scitools (python-scitools does not exist on ubuntu:bionic)
RUN cd /tmp \
diff --git a/cmake/hysop_tests.cmake b/cmake/hysop_tests.cmake
index 9978521f9a1799f500eae7b2636052a09edd1609..7c5e3c3e16e401e7201a8696015b295e1fdf4f68 100755
--- a/cmake/hysop_tests.cmake
+++ b/cmake/hysop_tests.cmake
@@ -22,7 +22,7 @@ file(MAKE_DIRECTORY ${CMAKE_BINARY_DIR}/dataForTests)
# Declaration of python test
# Usage:
-# Add_python_test(name file) with 'name' is the name of the test
+# Add_python_test(name file) with 'name' is the name of the test
# and file the source file for the test.
macro(add_python_test test_name test_file)
add_test(${test_name} py.test "${pytest_opt}" ${test_file})
@@ -31,7 +31,7 @@ macro(add_python_test test_name test_file)
set_tests_properties(${test_name} PROPERTIES ENVIRONMENT "PYTHONPATH=$ENV{PYTHONPATH}:${HYSOP_BUILD_PYTHONPATH}")
set_tests_properties(${test_name} PROPERTIES ENVIRONMENT "PYTHONPATH=$ENV{PYTHONPATH}:${HYSOP_BUILD_PYTHONPATH},LD_LIBRARY_PATH=$ENV{LD_LIBRARY_PATH}:${HYSOP_BUILD_PYTHONPATH}")
set_tests_properties(${test_name} PROPERTIES TIMEOUT ${TEST_TIMEOUT})
-
+
if(WITH_MPI_TESTS)
# Run the same test using mpi multi process run.
# The number of processes used is set with NBPROCS_FOR_TESTS variable (user option for cmake, default=8)
@@ -44,7 +44,7 @@ macro(add_python_test test_name test_file)
set_tests_properties(${test_name}_mpi PROPERTIES ENVIRONMENT "PYTHONPATH=$ENV{PYTHONPATH}:${HYSOP_BUILD_PYTHONPATH},LD_LIBRARY_PATH=$ENV{LD_LIBRARY_PATH}:${HYSOP_BUILD_PYTHONPATH}")
set_tests_properties(${test_name}_mpi PROPERTIES TIMEOUT ${TEST_TIMEOUT})
endif()
-
+
endmacro()
# Choose python build dir as directory where tests will be run.
@@ -52,7 +52,7 @@ endmacro()
set(testDir ${HYSOP_BUILD_PYTHONPATH})
# === Set the list of all directories which may contain tests ===
-set(py_src_dirs core/arrays numerics fields operator)
+set(py_src_dirs core/arrays core/graph core/memory fields operator numerics numerics/splitting)
# === Create the files list from all directories in py_src_dirs ===
@@ -68,7 +68,7 @@ endforeach()
# Build doctests
# Handling doctest in *.py files recursively for each directory of hysop/${py_src_dirs}
-# excluding __init__ or test_ files.
+# excluding __init__ or test_ files.
# Doctest are run for every line which contains '>>>'
set(py_doctest_files)
foreach(testdir ${py_src_dirs})
@@ -96,6 +96,11 @@ foreach(testfile ${py_doctest_files})
add_test("doctest_${testName}" py.test -v --doctest-modules ${exename})
endforeach()
+# Setup extra timeout for some specific test (used with ctest, not in CI)
+set_tests_properties("test_poisson" PROPERTIES TIMEOUT 600)
+set_tests_properties("test_poisson_curl" PROPERTIES TIMEOUT 600)
+set_tests_properties("test_solenoidal_projection" PROPERTIES TIMEOUT 600)
+set_tests_properties("test_spectral_derivative" PROPERTIES TIMEOUT 600)
+
# Add custom target to launch continuous integration tests
add_custom_target(ci COMMAND ${CMAKE_SOURCE_DIR}/ci/scripts/test.sh ${CMAKE_BINARY_DIR} ${CMAKE_SOURCE_DIR}/hysop)
-
diff --git a/docs/CMakeLists.txt b/docs/CMakeLists.txt
index a571f89d7ee41266eb79179eb06b92688b35b5ae..4c58de609b76f0d85f428a0cd09da7d3b5293a6d 100644
--- a/docs/CMakeLists.txt
+++ b/docs/CMakeLists.txt
@@ -4,7 +4,7 @@
# - automatic doxygen documentation, from C, Fortran, C++ sources
# - automatic sphinx/apidoc documentaion from python sources
# - sphinx documentation for manuals
-#
+#
# ===============================================================
if(WITH_DOCUMENTATION)
@@ -12,7 +12,7 @@ if(WITH_DOCUMENTATION)
if(NOT DOC_ROOT_DIR)
set(DOC_ROOT_DIR ${CMAKE_BINARY_DIR}/docs/build/html CACHE INTERNAL "Path to html documentation.")
endif()
-
+
# --------------------- Doxygen setup ---------------------
find_package(Doxygen)
@@ -25,7 +25,7 @@ if(WITH_DOCUMENTATION)
file(MAKE_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/build/html)
# config file name (generated later from hysop.doxyfile.in)
set(DOXY_CONFIG "${CMAKE_CURRENT_BINARY_DIR}/config/hysop.doxyfile")
-
+
# --------------------------------
# Update doxy.config to take
# into account sources/headers files
@@ -35,12 +35,12 @@ if(WITH_DOCUMENTATION)
${CMAKE_SOURCE_DIR}/src
${CMAKE_SOURCE_DIR}/hysop
)
-
+
foreach(_dir ${DOXY_INPUTS})
set(DOXYGEN_INPUTS "${DOXYGEN_INPUTS} ${_dir}")
endforeach()
list(REMOVE_DUPLICATES DOXYGEN_INPUTS)
-
+
set(GENERATE_HTML YES)
set(GENERATE_XML YES)
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/config/hysop.doxyfile.in ${DOXY_CONFIG})
@@ -54,7 +54,7 @@ if(WITH_DOCUMENTATION)
include(FindSphinxModule)
find_python_module(sphinx REQUIRED)
find_sphinx_module(sphinxcontrib bibtex REQUIRED)
- find_sphinx_module(sphinxcontrib doxylink REQUIRED)
+#import ISSUE: find_sphinx_module(sphinxcontrib doxylink REQUIRED)
# generate sphinx conf file
configure_file (
@@ -107,7 +107,7 @@ if(WITH_DOCUMENTATION)
"${CMAKE_CURRENT_SOURCE_DIR}/sphinx/${filename}"
"${CMAKE_CURRENT_BINARY_DIR}/sphinx/${filename}" @ONLY)
endforeach()
-
+
# --> use make html or make latex ... to build documentation.
set(SPHINX_EXECUTABLE sphinx-build )
set(SPHINX_PARAMETERS
@@ -128,13 +128,13 @@ if(WITH_DOCUMENTATION)
-d build/doctrees # path to doctree files
${CMAKE_CURRENT_BINARY_DIR}/sphinx # path to rst source
)
-
+
add_custom_target(latex
COMMAND ${SPHINX_EXECUTABLE} ${SPHINX_LATEX_PARAMETERS}
${CMAKE_CURRENT_BINARY_DIR}/build/latex
)
-
+
add_custom_target(doc DEPENDS html)
# Doxygen css comes from sphinx setup
# --> link to sphinx
@@ -148,5 +148,5 @@ if(WITH_DOCUMENTATION)
# # DEPENDS update_css)
# add_dependencies(html doxygen)
# add_dependencies(html apidoc)
-
+
endif()
diff --git a/hysop/backend/device/codegen/kernels/tests/test_directional_advection.py b/hysop/backend/device/codegen/kernels/tests/test_codegen_directional_advection.py
similarity index 100%
rename from hysop/backend/device/codegen/kernels/tests/test_directional_advection.py
rename to hysop/backend/device/codegen/kernels/tests/test_codegen_directional_advection.py
diff --git a/hysop/backend/device/codegen/kernels/tests/test_directional_remesh.py b/hysop/backend/device/codegen/kernels/tests/test_codegen_directional_remesh.py
similarity index 100%
rename from hysop/backend/device/codegen/kernels/tests/test_directional_remesh.py
rename to hysop/backend/device/codegen/kernels/tests/test_codegen_directional_remesh.py
diff --git a/hysop/backend/device/codegen/kernels/tests/test_directional_stretching.py b/hysop/backend/device/codegen/kernels/tests/test_codegen_directional_stretching.py
similarity index 100%
rename from hysop/backend/device/codegen/kernels/tests/test_directional_stretching.py
rename to hysop/backend/device/codegen/kernels/tests/test_codegen_directional_stretching.py
diff --git a/hysop/backend/device/codegen/kernels/tests/test_transpose.py b/hysop/backend/device/codegen/kernels/tests/test_codegen_transpose.py
similarity index 100%
rename from hysop/backend/device/codegen/kernels/tests/test_transpose.py
rename to hysop/backend/device/codegen/kernels/tests/test_codegen_transpose.py
diff --git a/hysop/core/graph/tests/test_graph.py b/hysop/core/graph/tests/test_graph.py
index 25746378e3a27f826ae22f947aaf2553c086f734..a359a69b1368d63ab28d1530216f5905673f8d10 100644
--- a/hysop/core/graph/tests/test_graph.py
+++ b/hysop/core/graph/tests/test_graph.py
@@ -1,4 +1,3 @@
-
from hysop.domain.box import Box
from hysop.topology.cartesian_topology import CartesianTopology
from hysop.tools.parameters import CartesianDiscretization
@@ -9,7 +8,7 @@ class _ComputationalGraph(ComputationalGraph):
@classmethod
def supports_multiple_topologies(cls):
return True
-
+
class _ComputationalGraphOperator(ComputationalGraphOperator):
def apply(self):
pass
@@ -18,71 +17,88 @@ class _ComputationalGraphOperator(ComputationalGraphOperator):
def supports_multiple_topologies(cls):
return True
-def test_graph_build(display=False):
- box = Box(length=[1.0]*3, origin=[0.0]*3)
- Vg = Field(domain=box, name='Vg', is_vector=True)
- Vp = Field(domain=box, name='Vp', is_vector=True)
- Wg = Field(domain=box, name='Wg', is_vector=True)
- Wp = Field(domain=box, name='Wp', is_vector=True)
- rho0g = Field(domain=box, name='rho0g')
- rho0p = Field(domain=box, name='rho0p')
- rho1g = Field(domain=box, name='rho1g')
- rho1p = Field(domain=box, name='rho1p')
-
- d3d0 = CartesianDiscretization(resolution=(64,64,64), ghosts=None, default_boundaries=True)
- d3d1 = CartesianDiscretization(resolution=(128,128,128), ghosts=None, default_boundaries=True)
- t0 = CartesianTopology(domain=box, discretization=d3d0)
- t1 = CartesianTopology(domain=box, discretization=d3d1)
-
- ops = [
- ('copyW', [Wg], [Wp]),
- ('copyS0', [rho0g], [rho0p]),
- ('copyS1', [rho1g], [rho1p]),
- ('copyV', [Vg], [Vg]),
- ]
- g0 = _ComputationalGraph(name='g0')
- for (opname,_in,_out) in ops:
- invars = {}
- outvars = {}
- for var in _in:
- invars[var] = t0 if (var.name.find('rho')) else t1
- for var in _out:
- outvars[var] = t0 if (var.name.find('rho')) else t1
- g0.push_nodes(_ComputationalGraphOperator(name=opname,
- input_fields=invars,output_fields=outvars))
-
- ops = [
- ('advecWx', [Vg, Wp], [Wg]),
- ('stretchWx', [Vg, Wg], [Wg]),
- ('diffWx', [Wg], [Wg]),
- ('advecS0x', [Vg,rho0p], [rho0g]),
- ('advecS1x', [Vg,rho1p], [rho1g]),
- ('diffS0x', [rho0g], [rho0g]),
- ('diffS1x', [rho1g], [rho1g]),
- ('forceWx', [rho0g,rho1g,Wg], [Wg]),
- ]
- g1 = _ComputationalGraph(name='g1')
- for (opname,_in,_out) in ops:
- invars = {}
- outvars = {}
- for var in _in:
- invars[var] = t0 if (var.name.find('rho')) else t1
- for var in _out:
- outvars[var] = t0 if (var.name.find('rho')) else t1
- g1.push_nodes(_ComputationalGraphOperator(name=opname,
- input_fields=invars,output_fields=outvars))
-
- g = _ComputationalGraph(name='exec')
- g.push_nodes(g0)
- g.push_nodes(g1)
-
- g.initialize()
- g.discretize()
- g.setup(None)
- g.apply()
-
- if display:
- g.display()
+class TestGraph(object):
+
+ @classmethod
+ def setup_class(cls):
+ pass
+
+ @classmethod
+ def teardown_class(cls):
+ pass
+
+ def setup_method(self, method):
+ pass
+
+ def teardown_method(self, method):
+ pass
+
+ def test_graph_build(self, display=False):
+ box = Box(length=[1.0]*3, origin=[0.0]*3)
+ Vg = Field(domain=box, name='Vg', is_vector=True)
+ Vp = Field(domain=box, name='Vp', is_vector=True)
+ Wg = Field(domain=box, name='Wg', is_vector=True)
+ Wp = Field(domain=box, name='Wp', is_vector=True)
+ rho0g = Field(domain=box, name='rho0g')
+ rho0p = Field(domain=box, name='rho0p')
+ rho1g = Field(domain=box, name='rho1g')
+ rho1p = Field(domain=box, name='rho1p')
+
+ d3d0 = CartesianDiscretization(resolution=(64,64,64), ghosts=None, default_boundaries=True)
+ d3d1 = CartesianDiscretization(resolution=(128,128,128), ghosts=None, default_boundaries=True)
+ t0 = CartesianTopology(domain=box, discretization=d3d0)
+ t1 = CartesianTopology(domain=box, discretization=d3d1)
+
+ ops = [
+ ('copyW', [Wg], [Wp]),
+ ('copyS0', [rho0g], [rho0p]),
+ ('copyS1', [rho1g], [rho1p]),
+ ('copyV', [Vg], [Vg]),
+ ]
+ g0 = _ComputationalGraph(name='g0')
+ for (opname,_in,_out) in ops:
+ invars = {}
+ outvars = {}
+ for var in _in:
+ invars[var] = t0 if (var.name.find('rho')) else t1
+ for var in _out:
+ outvars[var] = t0 if (var.name.find('rho')) else t1
+ g0.push_nodes(_ComputationalGraphOperator(name=opname,
+ input_fields=invars,output_fields=outvars))
+
+ ops = [
+ ('advecWx', [Vg, Wp], [Wg]),
+ ('stretchWx', [Vg, Wg], [Wg]),
+ ('diffWx', [Wg], [Wg]),
+ ('advecS0x', [Vg,rho0p], [rho0g]),
+ ('advecS1x', [Vg,rho1p], [rho1g]),
+ ('diffS0x', [rho0g], [rho0g]),
+ ('diffS1x', [rho1g], [rho1g]),
+ ('forceWx', [rho0g,rho1g,Wg], [Wg]),
+ ]
+ g1 = _ComputationalGraph(name='g1')
+ for (opname,_in,_out) in ops:
+ invars = {}
+ outvars = {}
+ for var in _in:
+ invars[var] = t0 if (var.name.find('rho')) else t1
+ for var in _out:
+ outvars[var] = t0 if (var.name.find('rho')) else t1
+ g1.push_nodes(_ComputationalGraphOperator(name=opname,
+ input_fields=invars,output_fields=outvars))
+
+ g = _ComputationalGraph(name='exec')
+ g.push_nodes(g0)
+ g.push_nodes(g1)
+
+ g.initialize()
+ g.discretize()
+ g.setup(None)
+ g.apply()
+
+ if display:
+ g.display()
if __name__ == '__main__':
- test_graph_build(display=False)
+ test = TestGraph()
+ test.test_graph_build(display=False)
diff --git a/hysop/core/memory/memory_request.py b/hysop/core/memory/memory_request.py
index e6c65a33aa2b712a6c051e2f29f0b9f3eab8f18d..747f7b870597e37e1e78bfe46a380c972ee79bfb 100644
--- a/hysop/core/memory/memory_request.py
+++ b/hysop/core/memory/memory_request.py
@@ -494,12 +494,8 @@ class MultipleOperatorMemoryRequests(object):
ss=''
for (backend, backend_srequests) in all_requests.iteritems():
-<<<<<<< HEAD
- kind = backend.kind
-=======
total = totals[backend]
kind = backend.kind
->>>>>>> master
if (kind == Backend.OPENCL):
precision = u' on device {}'.format(backend.device.name.strip())
else:
diff --git a/hysop/core/memory/tests/test_allocator.py b/hysop/core/memory/tests/test_allocator.py
index 919e65bc553e904bd082587053ae42408308ce63..eff44af2151080206bed02bf30522d351abe29af 100644
--- a/hysop/core/memory/tests/test_allocator.py
+++ b/hysop/core/memory/tests/test_allocator.py
@@ -1,13 +1,13 @@
-
from hysop.backend import __HAS_OPENCL_BACKEND__, __HAS_CUDA_BACKEND__
from hysop.backend.host.host_allocator import HostAllocator
+from hysop.core.mpi import default_mpi_params
sizes = (1,89,7919,32*1024*1024)
alignments = (1,2,4,8,16,32,64,128,256,512,1024)
def test_host_allocator():
allocator = HostAllocator()
-
+
for nbytes in sizes:
for alignment in alignments:
buf = allocator.allocate(nbytes)
@@ -27,16 +27,16 @@ if __HAS_OPENCL_BACKEND__:
OpenClDeferredAllocator
from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
- cl_env = get_or_create_opencl_env()
+ cl_env = get_or_create_opencl_env(mpi_params=default_mpi_params())
def test_opencl_immediate_allocator():
- allocator = OpenClImmediateAllocator(cl_env.default_queue)
+ allocator = OpenClImmediateAllocator(queue=cl_env.default_queue)
for nbytes in sizes:
buf = allocator.allocate(nbytes)
assert buf.size == nbytes
-
+
def test_opencl_deferred_allocator():
- allocator = OpenClDeferredAllocator(cl_env.default_queue)
+ allocator = OpenClDeferredAllocator(queue=cl_env.default_queue)
for nbytes in sizes:
buf = allocator.allocate(nbytes)
cl.enqueue_barrier(cl_env.default_queue)
diff --git a/hysop/core/memory/tests/test_buffer.py b/hysop/core/memory/tests/test_buffer.py
index e7bcd97182a99643aaef5887f7a5668dbbbc27b1..abb00ff2d4b576a7d33ce724539a80fab01e5765 100644
--- a/hysop/core/memory/tests/test_buffer.py
+++ b/hysop/core/memory/tests/test_buffer.py
@@ -1,6 +1,6 @@
-
from hysop.deps import np
from hysop.backend.host.host_buffer import HostBuffer
+from hysop.core.mpi import default_mpi_params
from hysop.backend import __HAS_OPENCL_BACKEND__, __HAS_CUDA_BACKEND__
size = 32*1024*1024 # 32Mo
@@ -10,19 +10,19 @@ def test_host_buffer():
assert buf1.get_int_ptr() == buf1.int_ptr
assert buf1.get_size() == buf1.size
assert buf1.get_buffer() is buf1.buf
-
+
buf2 = HostBuffer(size=size)
assert buf1.int_ptr != buf2.int_ptr
assert buf1.size == size
assert buf1.size == buf2.size
-
+
arr1 = np.frombuffer(buf1, dtype=np.uint8)
arr2 = np.frombuffer(buf2, dtype=np.uint8)
arr1.fill(0)
arr2.fill(1)
assert (arr1==0).all()
assert (arr2==1).all()
-
+
buf2 = HostBuffer.from_buffer(buf1)
assert buf1.int_ptr == buf2.int_ptr
assert buf1.size == buf2.size
@@ -30,7 +30,7 @@ def test_host_buffer():
buf3 = HostBuffer.from_int_ptr(buf2.int_ptr, buf2.size)
assert buf1.int_ptr == buf3.int_ptr
assert buf1.size == buf3.size
-
+
arr1 = np.frombuffer(buf1, dtype=np.uint8)
arr2 = np.frombuffer(buf2, dtype=np.uint8)
arr3 = np.frombuffer(buf3, dtype=np.uint8)
@@ -75,18 +75,18 @@ if __HAS_OPENCL_BACKEND__:
from hysop.backend.device.opencl.opencl_buffer import OpenClBuffer
from hysop.backend.device.opencl.opencl_tools import get_or_create_opencl_env
- cl_env = get_or_create_opencl_env()
-
+ cl_env = get_or_create_opencl_env(mpi_params=default_mpi_params())
+
def test_opencl_buffer():
mf = cl.mem_flags
-
+
buf = cl.Buffer(cl_env.context, size=size, flags=mf.READ_ONLY)
buf1 = OpenClBuffer(cl_env.context, size=size, mem_flags=mf.READ_WRITE)
assert buf1.int_ptr == buf1.get_int_ptr()
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf1,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf1,
byte_count=size).wait()
-
+
assert buf1.ref_count() == 1
buf1.release()
@@ -102,26 +102,26 @@ if __HAS_OPENCL_BACKEND__:
assert buf3.ref_count() == 3
assert buf1.int_ptr == buf2.int_ptr
assert buf1.int_ptr == buf3.int_ptr
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf1,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf1,
byte_count=size).wait()
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
byte_count=size).wait()
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf3,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf3,
byte_count=size).wait()
buf1.release()
assert buf2.ref_count() == 2
assert buf3.ref_count() == 2
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
byte_count=size).wait()
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf3,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf3,
byte_count=size).wait()
buf3.release()
assert buf2.ref_count() == 1
- cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
+ cl.enqueue_copy_buffer(queue=cl_env.default_queue, src=buf, dst=buf2,
byte_count=size).wait()
buf2.release()
-
+
def test_opencl_host_device_buffer():
mf = cl.mem_flags
@@ -131,11 +131,11 @@ if __HAS_OPENCL_BACKEND__:
# try to use unified memory (or something like zero copy memory)
hbuf = np.ndarray(shape=size, dtype=np.float32)
buf = OpenClBuffer(cl_env.context, mem_flags=mf.USE_HOST_PTR, hostbuf=hbuf)
-
+
# copy host buf at creation
hbuf = np.ndarray(shape=(1024,1024,), dtype=np.int64)
buf = OpenClBuffer(cl_env.context, mem_flags=mf.COPY_HOST_PTR, hostbuf=hbuf)
-
+
if __name__ == '__main__':
test_host_buffer()
diff --git a/hysop/core/memory/tests/test_mempool.py b/hysop/core/memory/tests/test_mempool.py
index 64e1f07fae9dbe11fa05420571ff164a54fabddd..ac43f5ee301aef79d4979afb4663b40d2c212704 100644
--- a/hysop/core/memory/tests/test_mempool.py
+++ b/hysop/core/memory/tests/test_mempool.py
@@ -1,9 +1,8 @@
-
from hysop.deps import np
from hysop.testsenv import opencl_failed, iter_clenv, \
__HAS_OPENCL_BACKEND__, __ENABLE_LONG_TESTS__
from hysop.core.memory.mempool import MemoryPool
-
+
import random
max_bytes_per_alloc = 1024*1024*128 # 128MB
free = lambda: bool(random.random()>0.1) # 80% probability of free
@@ -19,11 +18,11 @@ def test_mempool_opencl_immediate_allocator():
from hysop.backend.device.opencl.opencl_allocator import OpenClImmediateAllocator
for cl_env in iter_clenv():
- allocator = OpenClImmediateAllocator(cl_env.default_queue)
+ allocator = OpenClImmediateAllocator(queue=cl_env.default_queue)
_test_mempool_allocator(cl_env.platform.name, allocator)
def _test_mempool_allocator(name, allocator):
- pool = allocator.memory_pool(name=name, verbose=True)
+ pool = allocator.memory_pool(name=name)
buffers = []
try:
while True:
diff --git a/hysop/fields/discrete_field.py b/hysop/fields/discrete_field.py
index e909ebbc733ff4ba59be47b8452ebf5651a55275..91be593970a969dd2899374a7763a4172ac11b43 100644
--- a/hysop/fields/discrete_field.py
+++ b/hysop/fields/discrete_field.py
@@ -25,7 +25,7 @@ from hysop.mesh.mesh import MeshView
class DiscreteScalarFieldViewContainerI(object):
"""
- Common abstract interface for scalar and tensor-like container of
+ Common abstract interface for scalar and tensor-like container of
discrete field views.
"""
@@ -38,7 +38,7 @@ class DiscreteScalarFieldViewContainerI(object):
@abstractmethod
def discrete_field_views(self):
"""
- Return all unique discrete field views contained in this discrete
+ Return all unique discrete field views contained in this discrete
field view container.
"""
pass
@@ -91,7 +91,7 @@ class DiscreteScalarFieldViewContainerI(object):
@abstractmethod
def clone(self, tstate=None):
"""
- Create a new temporary DiscreteScalarField container and allocate it
+ Create a new temporary DiscreteScalarField container and allocate it
like the current object, with possibly a different topology state.
This should only be used for debugging and testing purpose.
@@ -104,7 +104,7 @@ class DiscreteScalarFieldViewContainerI(object):
def tmp_dfield_like(self, name, **kwds):
"""
Create a new Field container and a new temporary CartesianDiscreteField.
- like the current object, possibly on a different backend.
+ like the current object, possibly on a different backend.
/!\ The returned discrete field is not allocated.
"""
pass
@@ -117,7 +117,7 @@ class DiscreteScalarFieldViewContainerI(object):
@abstractmethod
def build_ghost_exchanger(self, **kwds):
"""
- Build a ghost exchanger, possibly on different data.
+ Build a ghost exchanger, possibly on different data.
Usefull for operator apply.
"""
pass
@@ -149,7 +149,7 @@ class DiscreteScalarFieldViewContainerI(object):
Return a view on this DiscreteScalarField using given topology state.
"""
pass
-
+
@abstractmethod
def as_any_dfield(self, memory_order, **kwds):
"""
@@ -201,7 +201,7 @@ class DiscreteScalarFieldViewContainerI(object):
def _get_buffers():
"""Return all array data as a buffers as a tuple."""
pass
-
+
@abstractmethod
def _get_sdata(self):
"""Return contained array."""
@@ -216,7 +216,7 @@ class DiscreteScalarFieldViewContainerI(object):
def _get_sbuffer():
"""Return contained buffer."""
pass
-
+
def get_attributes(self, *attrs):
"""
Return all matching attributes contained in self.discrete_field_views(),
@@ -301,9 +301,9 @@ class DiscreteScalarFieldViewContainerI(object):
def get_unique_attribute(self, *attr):
"""
Try to return the unique attribute common to all contained discrete fields.
- Raise an AttributeError if a attribute is not unique accross contained
+ Raise an AttributeError if a attribute is not unique accross contained
discrete field views.
-
+
/!\ Can be slow to evaluate due to uniqueness check /!\
"""
if self.has_unique_attribute(*attr):
@@ -401,7 +401,7 @@ class DiscreteScalarFieldView(DiscreteScalarFieldViewContainerI, TaggedObjectVie
def __new__(cls, dfield, topology_state, **kwds):
check_instance(dfield, DiscreteScalarField, allow_none=issubclass(cls, DiscreteScalarField))
check_instance(topology_state, TopologyState)
- obj = super(DiscreteScalarFieldView, cls).__new__(cls, obj_view=dfield,
+ obj = super(DiscreteScalarFieldView, cls).__new__(cls, obj_view=dfield,
variable_kind=Variable.DISCRETE_FIELD, **kwds)
dfield = first_not_None(dfield, obj)
obj._dfield = dfield
@@ -453,7 +453,7 @@ class DiscreteScalarFieldView(DiscreteScalarFieldViewContainerI, TaggedObjectVie
def _get_is_read_only(self):
"""Return true if this view is a read-only."""
return self._topology_state.is_read_only
-
+
def _get_name(self):
"""Get the name of the discrete field."""
return self._dfield._name
@@ -466,7 +466,7 @@ class DiscreteScalarFieldView(DiscreteScalarFieldViewContainerI, TaggedObjectVie
def _get_var_name(self):
"""Get the latex name of the discrete field."""
return self._dfield._var_name
-
+
def _get_dtype(self):
"""Get the data type of the discrete field."""
return self._dfield._field.dtype
@@ -506,10 +506,10 @@ class DiscreteScalarFieldView(DiscreteScalarFieldViewContainerI, TaggedObjectVie
return not eq
else:
return eq
-
+
def honor_memory_request(self, *args, **kwds):
self._dfield.honor_memory_request(*args, **kwds)
-
+
def _get_memory_request(self):
"""Get memory request that should be allocated for this TmpCartesianDiscreteField."""
return getattr(self._dfield, '_memory_request', None)
@@ -518,7 +518,7 @@ class DiscreteScalarFieldView(DiscreteScalarFieldViewContainerI, TaggedObjectVie
return getattr(self._dfield, '_memory_request_id', None)
def __hash__(self):
- h = id(self._dfield._topology)
+ h = id(self._dfield._topology)
h ^= id(self._dfield._field)
h ^= hash(self._dfield._name)
h ^= hash(self._dfield._pretty_name)
@@ -536,12 +536,12 @@ class DiscreteScalarFieldView(DiscreteScalarFieldViewContainerI, TaggedObjectVie
field = property(_get_field)
topology_state = property(_get_topology_state)
is_read_only = property(_get_is_read_only)
-
+
name = property(_get_name)
pretty_name = property(_get_pretty_name)
latex_name = property(_get_latex_name)
var_name = property(_get_var_name)
-
+
dtype = property(_get_dtype)
initial_values = property(_get_initial_values)
@@ -563,21 +563,21 @@ class DiscreteScalarField(NamedScalarContainerI, TaggedObject):
wich are a collection of numpy like multidimensional arrays allocated using a
specific backend (hysop.core.arrays.array.ArrayBackend).
- A DiscreteScalarField is the result of discretizing a continuous Field
- (hysop.field.continuous_field.Field) defined on a specific domain
- (hysop.domain.domain.Domain) distributed accross processes through
+ A DiscreteScalarField is the result of discretizing a continuous Field
+ (hysop.field.continuous_field.Field) defined on a specific domain
+ (hysop.domain.domain.Domain) distributed accross processes through
a topology (hysop.topology.topology.Topology).
Ghost exchangers are automatically built for all discrete fields.
- Ghost exchangers may require additional memory buffers,
+ Ghost exchangers may require additional memory buffers,
depending on the discrete field topology backend and the ghost exchange strategy.
"""
__metaclass__ = ABCMeta
@debug
- def __new__(cls, field, topology, register_discrete_field=True,
- name=None, pretty_name=None,
+ def __new__(cls, field, topology, register_discrete_field=True,
+ name=None, pretty_name=None,
var_name=None, latex_name=None,
**kwds):
"""
@@ -609,12 +609,12 @@ class DiscreteScalarField(NamedScalarContainerI, TaggedObject):
check_instance(pretty_name, (str,unicode), allow_none=True)
_name, _pretty_name, _var_name, _latex_name = \
- cls.format_discrete_names(field.name,
- field.pretty_name,
+ cls.format_discrete_names(field.name,
+ field.pretty_name,
field.var_name,
field.latex_name,
topology)
-
+
pretty_name = first_not_None(pretty_name, name, _pretty_name)
var_name = first_not_None(var_name, name, _var_name)
latex_name = first_not_None(latex_name, name, _latex_name)
@@ -668,8 +668,8 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
A tensor discrete field is a collection of scalar discrete fields views.
This object handles a numpy.ndarray of discrete scalar field views,
- which may have different attributes (different data types for
- example) and different topology states.
+ which may have different attributes (different data types for
+ example) and different topology states.
A tensor field garanties that each different field objects have
unique names and pretty names within the tensor field. A given
@@ -678,20 +678,20 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
Some components may also be set to None.
- Is also garanties that all fields shares the same domain, but contained
+ Is also garanties that all fields shares the same domain, but contained
discrete fields may be defined on different topologies.
"""
- def __new__(cls, field, dfields, name=None,
+ def __new__(cls, field, dfields, name=None,
pretty_name=None, latex_name=None, **kwds):
check_instance(field, TensorField)
check_instance(dfields, npw.ndarray, dtype=object, values=DiscreteScalarFieldView)
assert npw.array_equal(field.shape, dfields.shape)
-
+
tensor_cls = cls.determine_tensor_cls(dfields)
if (tensor_cls is not cls):
- return tensor_cls.__new__(tensor_cls,
- field=field, dfields=dfields,
+ return tensor_cls.__new__(tensor_cls,
+ field=field, dfields=dfields,
name=name, pretty_name=pretty_name,
**kwds)
@@ -701,9 +701,9 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
pretty_name = first_not_None(pretty_name, _pretty_name)
latex_name = first_not_None(latex_name, _latex_name)
- obj = super(DiscreteTensorField, cls).__new__(cls, name=name,
+ obj = super(DiscreteTensorField, cls).__new__(cls, name=name,
pretty_name=pretty_name, latex_name=latex_name,
- tag_prefix='tdf', tagged_cls=DiscreteTensorField,
+ tag_prefix='tdf', tagged_cls=DiscreteTensorField,
contained_objects=dfields, **kwds)
obj._field = field
obj._dfields = dfields
@@ -731,7 +731,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
@classmethod
def from_dfields(cls, name, dfields, shape, pretty_name=None, **kwds):
"""
- Create a TensorField and a DiscreteTensorField
+ Create a TensorField and a DiscreteTensorField
from a list of discrete fields and a shape.
"""
dfields = to_tuple(dfields)
@@ -747,7 +747,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
fields=fields, shape=shape)
dfields = npw.asarray(dfields, dtype=object).reshape(shape)
-
+
return cls(field=field, dfields=dfields, **kwds)
@classmethod
@@ -773,7 +773,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
msg='Tensor discrete field {} should at least contain a valid DiscreteScalarField.'
msg=msg.format(name)
raise ValueError(msg)
-
+
def _check_names(self):
"""Check that discrete fields names are unique."""
names = {}
@@ -794,7 +794,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
def discrete_field_views(self):
"""
- Return all unique discrete field views contained in this discrete
+ Return all unique discrete field views contained in this discrete
field view container.
"""
ordered_dfields = self._dfields.ravel().tolist()
@@ -836,7 +836,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
def clone(self, tstate=None,
name=None, pretty_name=None, **kwds):
"""
- Create a new temporary DiscreteScalarField container and allocate it
+ Create a new temporary DiscreteScalarField container and allocate it
like the current object, with possibly a different topology state.
This should only be used for debugging and testing purpose.
@@ -844,19 +844,19 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
field.
"""
name = first_not_None(name, '{}__{}'.format(self.name, self._clone_id))
- pretty_name = first_not_None(pretty_name, '{}__{}'.format(self.pretty_name,
+ pretty_name = first_not_None(pretty_name, '{}__{}'.format(self.pretty_name,
self._clone_id))
dfields = npw.empty(shape=self.shape, dtype=object)
for (idx, dfield) in self.nd_iter():
dfields[idx] = dfield.clone(tstate=tstate, **kwds)
self._clone_id += 1
- return self.from_dfield_array(name=name, pretty_name=pretty_name, dfields=dfields,
+ return self.from_dfield_array(name=name, pretty_name=pretty_name, dfields=dfields,
**kwds)
def tmp_dfield_like(self, name, pretty_name=None, **kwds):
"""
Create a new Field container and a new temporary CartesianDiscreteField.
- like the current object, possibly on a different backend.
+ like the current object, possibly on a different backend.
/!\ The returned discrete field is not allocated.
"""
from hysop.core.memory.memory_request import OperatorMemoryRequests
@@ -867,9 +867,10 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
_name = TensorField.default_name_formatter(basename=name, idx=idx)
_pretty_name = TensorField.default_pretty_name_formatter(
basename=pretty_name, idx=idx)
- _name, _pretty_name = DiscreteScalarField.format_discrete_names(_name, _pretty_name,
- dfield.topology)
- (dfield, request, request_id) = dfield.tmp_dfield_like(name=_name,
+ _name, _pretty_name, _var_name, _latex_name = \
+ DiscreteScalarField.format_discrete_names(_name, _pretty_name,
+ _name, self.latex_name, dfield.topology)
+ (dfield, request, request_id) = dfield.tmp_dfield_like(name=_name,
pretty_name=_pretty_name,
**kwds)
requests.push_mem_request(request_id, request)
@@ -877,7 +878,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
dfields[idx] = dfield
dfield = self.from_dfield_array(name=name, pretty_name=pretty_name, dfields=dfields)
return (dfield, requests)
-
+
def honor_memory_request(self, work, op=None):
"""Honour memory requests for contained temporary discrete fields."""
op = first_not_None(op, self.name)
@@ -894,7 +895,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
"""Check if two DiscreteScalarFieldViews container are equivalent."""
check_instance(other, DiscreteTensorField)
assert npw.array_equal(self.shape, other.shape)
- eq = all(dfield.match(other[idx], invert=False)
+ eq = all(dfield.match(other[idx], invert=False)
for (idx, dfield) in self.nd_iter())
eq &= npw.array_equal(self.shape, other.shape)
eq &= (self._name == other._name)
@@ -921,7 +922,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
dfields[idx] = dfield.view(topology_state=topology_state)
dfield = self.from_dfield_array(name=name, pretty_name=pretty_name, dfields=dfields)
return dfield
-
+
def as_any_dfield(self, memory_order, name=None, pretty_name=None, **kwds):
"""
Quickly take a view on this DiscreteScalarFieldView using self topology state
@@ -955,7 +956,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
def short_description(self):
"""Short description of this discrete field container."""
s = '{}[name={}, pname={}, shape={}, nb_components={}]'
- s = s.format(self.full_tag, self.name, self.pretty_name,
+ s = s.format(self.full_tag, self.name, self.pretty_name,
self.shape, self.nb_components)
return s
@@ -990,14 +991,14 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
integrals[idx] = dfield.integrate(scale=scale, **kwds).tolist()[0]
return integrals
- def exchange_ghosts(self, build_exchanger=False, build_launcher=False,
+ def exchange_ghosts(self, build_exchanger=False, build_launcher=False,
evt=None, **kwds):
"""
Exchange ghosts using cached ghost exchangers which are built at first use.
ie. Exchange every ghosts components of self.data using current topology state.
By default all ghosts are exchanged.
"""
- if (build_launcher or build_exchanger):
+ if (build_launcher or build_exchanger):
assert (evt is None), 'Cannot spevify event while building a launcher.'
from hysop.fields.ghost_exchangers import MultiGhostExchanger
ghost_exchangers = MultiGhostExchanger(name='{}_ghost_exchange'.format(self.name))
@@ -1023,7 +1024,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
ie. Exchange every ghosts components of self.data using current topology state.
Specialization for ghost summation.
"""
- if (build_launcher or build_exchanger):
+ if (build_launcher or build_exchanger):
assert (evt is None), 'Cannot spevify event while building a launcher.'
from hysop.fields.ghost_exchangers import MultiGhostExchanger
ghost_exchangers = MultiGhostExchanger(name='{}_ghost_exchange'.format(self.name))
@@ -1045,7 +1046,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
def build_ghost_exchanger(self, **kwds):
"""
- Build a ghost exchanger, possibly on different data.
+ Build a ghost exchanger, possibly on different data.
Usefull for operator apply.
"""
from hysop.fields.ghost_exchangers import MultiGhostExchanger
@@ -1075,7 +1076,7 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
dfield._set_data(data)
def _get_buffers(self):
return tuple(dfield.sbuffer for dfield in self.discrete_field_views())
-
+
def _get_sdata(self):
self._raise_sdata()
def _set_sdata(self, copy_data):
@@ -1088,10 +1089,10 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
raise RuntimeError(msg)
data = property(_get_data, _set_data)
- buffers = property(_get_buffers)
+ buffers = property(_get_buffers)
sdata = property(_get_sdata, _set_sdata)
- sbuffer = property(_get_sbuffer)
-
+ sbuffer = property(_get_sbuffer)
+
def initialize(self, *args, **kwds):
msg='This method is only defined for specific topologies '
msg+='(see CartesianDiscreteTensorField).'
@@ -1109,4 +1110,3 @@ class DiscreteTensorField(NamedTensorContainerI, DiscreteScalarFieldViewContaine
DiscreteField = (DiscreteScalarField, DiscreteTensorField)
"""A DiscreteField is either of DiscreteScalarField or a DiscreteTensorField"""
-
diff --git a/hysop/fields/tests/test_cartesian.py b/hysop/fields/tests/test_cartesian.py
index 3b8a5ed96122e4ebaca67f72b2d885430b955830..499b37484ce0bd0b85e7000a9a41528473d6e7c2 100644
--- a/hysop/fields/tests/test_cartesian.py
+++ b/hysop/fields/tests/test_cartesian.py
@@ -41,7 +41,7 @@ def test_serial_initialization_1d():
dim = 1
npts = (10,)
nghosts = (2,)
-
+
for (lbd, rbd) in domain_boundary_iterator(dim):
domain = Box(dim=dim, lboundaries=lbd,
rboundaries=rbd)
@@ -49,8 +49,8 @@ def test_serial_initialization_1d():
F1 = Field(domain=domain, name='F1', nb_components=2)
F2 = Field(domain=domain, name='F2', shape=(2,2))
print '[{}]'.format(F0.format_boundaries())
-
- discretization = CartesianDiscretization(npts, nghosts,
+
+ discretization = CartesianDiscretization(npts, nghosts,
lboundaries=F0.lboundaries,
rboundaries=F0.rboundaries)
@@ -124,8 +124,8 @@ def test_serial_initialization_2d():
F0 = Field(domain=domain, name='F0', nb_components=1)
F1 = Field(domain=domain, name='F1', nb_components=2)
print '[{}]'.format(F0.format_boundaries())
-
- discretization = CartesianDiscretization(npts, nghosts,
+
+ discretization = CartesianDiscretization(npts, nghosts,
lboundaries=F0.lboundaries,
rboundaries=F0.rboundaries)
@@ -147,7 +147,7 @@ def test_serial_initialization_2d():
dfields = dF0.dfields + dF1.dfields
assert all(np.all(d.local_lboundaries == F0.lboundaries) for d in dfields)
assert all(np.all(d.local_rboundaries == F0.rboundaries) for d in dfields)
-
+
Ny,Nx = npts
Gy,Gx = nghosts
Ly,Lx = tuple(discretization.lboundaries)
@@ -212,7 +212,7 @@ def test_serial_initialization_2d():
assert b[Fy,Fx].shape == (Ny-2*Gy, Nx-2*Gx)
else:
raise NotImplementedError(ghost_mask)
-
+
if (Lx==BoundaryCondition.PERIODIC):
assert np.all(b[Fy,Xo[0]] == b[Fy,Xi[2]]), '\n'+str(d)
elif (Lx==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -222,7 +222,7 @@ def test_serial_initialization_2d():
assert (b[Fy,:Gx] == +b[Fy,Gx+1:2*Gx+1][Ix]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Lx))
-
+
if (Rx==BoundaryCondition.PERIODIC):
assert np.all(b[Fy,Xo[2]] == b[Fy,Xi[0]]), '\n'+str(d)
elif (Rx==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -232,7 +232,7 @@ def test_serial_initialization_2d():
assert (b[Fy,Nx-1:Nx+Gx-1] == +b[Fy,Nx+Gx:][Ix]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Rx))
-
+
if (Ly==BoundaryCondition.PERIODIC):
assert np.all(b[Yo[0],Fx] == b[Yi[2],Fx]), '\n'+str(d)
elif (Ly==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -242,7 +242,7 @@ def test_serial_initialization_2d():
assert (b[:Gy,Fx] == +b[Gy+1:2*Gy+1,Fx][Iy]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Ly))
-
+
if (Ry==BoundaryCondition.PERIODIC):
assert np.all(b[Yo[2],Fx] == b[Yi[0],Fx]), '\n'+str(d)
elif (Ry==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -285,8 +285,8 @@ def test_serial_initialization_3d():
F0 = Field(domain=domain, name='F0', nb_components=1)
F1 = Field(domain=domain, name='F1', nb_components=3)
print '[{}]'.format(F0.format_boundaries())
-
- discretization = CartesianDiscretization(npts, nghosts,
+
+ discretization = CartesianDiscretization(npts, nghosts,
lboundaries=F0.lboundaries,
rboundaries=F0.rboundaries)
@@ -308,7 +308,7 @@ def test_serial_initialization_3d():
dfields = dF0.dfields + dF1.dfields
assert all(np.all(d.local_lboundaries == F0.lboundaries) for d in dfields)
assert all(np.all(d.local_rboundaries == F0.rboundaries) for d in dfields)
-
+
Nz,Ny,Nx = npts
Gz,Gy,Gx = nghosts
Lz,Ly,Lx = tuple(discretization.lboundaries)
@@ -389,7 +389,7 @@ def test_serial_initialization_3d():
assert b[Fz,Fy,Fx].shape == (Nz-2*Gz,Ny-2*Gy, Nx-2*Gx)
else:
raise NotImplementedError(ghost_mask)
-
+
if (Lx==BoundaryCondition.PERIODIC):
assert np.all(b[Fz,Fy,Xo[0]] == b[Fz,Fy,Xi[2]]), '\n'+str(d)
elif (Lx==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -399,7 +399,7 @@ def test_serial_initialization_3d():
assert (b[Fz,Fy,:Gx] == +b[Fz,Fy,Gx+1:2*Gx+1][Ix]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Lx))
-
+
if (Rx==BoundaryCondition.PERIODIC):
assert np.all(b[Fz,Fy,Xo[2]] == b[Fz,Fy,Xi[0]]), '\n'+str(d)
elif (Rx==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -409,7 +409,7 @@ def test_serial_initialization_3d():
assert (b[Fz,Fy,Nx-1:Nx+Gx-1] == +b[Fz,Fy,Nx+Gx:][Ix]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Rx))
-
+
if (Ly==BoundaryCondition.PERIODIC):
assert np.all(b[Fz,Yo[0],Fx] == b[Fz,Yi[2],Fx]), '\n'+str(d)
elif (Ly==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -419,7 +419,7 @@ def test_serial_initialization_3d():
assert (b[Fz,:Gy,Fx] == +b[Fz,Gy+1:2*Gy+1,Fx][Iy]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Ly))
-
+
if (Ry==BoundaryCondition.PERIODIC):
assert np.all(b[Fz,Yo[2],Fx] == b[Fz,Yi[0],Fx]), '\n'+str(d)
elif (Ry==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -429,7 +429,7 @@ def test_serial_initialization_3d():
assert (b[Fz,Ny-1:Ny+Gy-1,Fx] == +b[Fz,Ny+Gy:,Fx][Iy]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Ry))
-
+
if (Lz==BoundaryCondition.PERIODIC):
assert np.all(b[Zo[0],Fy,Fx] == b[Zi[2],Fy,Fx]), '\n'+str(d)
elif (Lz==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -439,7 +439,7 @@ def test_serial_initialization_3d():
assert (b[:Gz,Fy,Fx] == +b[Gz+1:2*Gz+1,Fy,Fx][Iz]).all(), '\n'+str(d)
else:
raise NotImplementedError('Unknown boundary condition {}.'.format(Lz))
-
+
if (Rz==BoundaryCondition.PERIODIC):
assert np.all(b[Zo[2],Fy,Fx] == b[Zi[0],Fy,Fx]), '\n'+str(d)
elif (Rz==BoundaryCondition.HOMOGENEOUS_DIRICHLET):
@@ -483,7 +483,10 @@ def iter_backends():
for cl_env in iter_clenv():
yield (Backend.OPENCL, cl_env)
-def test_mpi_ghost_exchange_periodic(comm):
+def test_mpi_ghost_exchange_periodic(comm=None):
+ if comm is None:
+ from mpi4py import MPI
+ comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
dtypes = (np.float32, np.float32, np.float64,
@@ -582,19 +585,22 @@ def test_mpi_ghost_exchange_periodic(comm):
ldata = np.atleast_1d(ldata.get())
target_vals = ghost_vals(ldata.shape, dtype, i, d,
left_rank,1)
- assert np.allclose(ldata, target_vals), (rank,
+ assert np.allclose(ldata, target_vals), (rank,
target_vals)
rdata = np.atleast_1d(rdata.get())
- target_vals = ghost_vals(rdata.shape, dtype, i, d,
+ target_vals = ghost_vals(rdata.shape, dtype, i, d,
right_rank, 0)
- assert np.allclose(rdata, target_vals), (rank,
+ assert np.allclose(rdata, target_vals), (rank,
target_vals)
if rank==0:
print
-def test_mpi_ghost_exchange_runtime(comm):
+def test_mpi_ghost_exchange_runtime(comm=None):
"""Just bruteforce all exchange possibilities to see if nothing crashes in 1D and 2D."""
+ if comm is None:
+ from mpi4py import MPI
+ comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
dtype = np.float32
@@ -614,13 +620,13 @@ def test_mpi_ghost_exchange_runtime(comm):
npts = (17,16,19)[:dim]
nghosts = (2,1,3)[:dim]
-
+
for shape in it.product(xrange(0,size+1), repeat=dim):
if np.prod(shape, dtype=np.uint32)!=size:
continue
if rank==0:
sys.stdout.write(' >CART SHAPE: {}\n'.format(shape))
-
+
for (backend, cl_env) in iter_backends():
if rank==0:
sys.stdout.write(' >BACKEND.{:<7} '.format(str(backend)+':'))
@@ -631,7 +637,7 @@ def test_mpi_ghost_exchange_runtime(comm):
sys.stdout.flush()
return True
return False
-
+
i=0
brk = False
try:
@@ -639,10 +645,10 @@ def test_mpi_ghost_exchange_runtime(comm):
domain = Box(dim=dim, lboundaries=lbd,
rboundaries=rbd)
- F = Field(domain=domain, name='F', nb_components=1,
+ F = Field(domain=domain, name='F', nb_components=1,
dtype=dtype, _register=False)
- discretization = CartesianDiscretization(npts, nghosts,
+ discretization = CartesianDiscretization(npts, nghosts,
lboundaries=F.lboundaries,
rboundaries=F.rboundaries)
@@ -673,7 +679,10 @@ def test_mpi_ghost_exchange_runtime(comm):
sys.stdout.flush()
-def test_mpi_ghost_accumulate_periodic(comm):
+def test_mpi_ghost_accumulate_periodic(comm=None):
+ if comm is None:
+ from mpi4py import MPI
+ comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size = comm.Get_size()
if rank==0:
@@ -780,7 +789,7 @@ def test_mpi_ghost_accumulate_periodic(comm):
assert (ishape is not None)
data[oview] = ghost_vals(oshape, dtype, rank, directions,
displacements, i)
-
+
dF.accumulate_ghosts(directions=directions,
exchange_method=exchange_method)
@@ -836,9 +845,8 @@ if __name__ == '__main__':
test_serial_initialization_2d()
if __ENABLE_LONG_TESTS__:
test_serial_initialization_3d()
-
+
disable_hysop_warnings()
test_mpi_ghost_exchange_runtime(comm=comm)
test_mpi_ghost_exchange_periodic(comm=comm)
test_mpi_ghost_accumulate_periodic(comm=comm)
-
diff --git a/hysop/fields/tests/test_fields.py b/hysop/fields/tests/test_fields.py
index 86314bb5b2fee90d41c6429238b8044d1566a7e9..e4bb0f94d412a516a24cf319c9a5519773e19b5f 100644
--- a/hysop/fields/tests/test_fields.py
+++ b/hysop/fields/tests/test_fields.py
@@ -34,10 +34,10 @@ def test_field():
DF5 = F5.discretize(T0)
DF6 = F6.discretize(T0)
DF7 = F7.discretize(T0)
-
- requests = DF5._dfield.memory_request(op=DF5.name,
+
+ requests = DF5._dfield.memory_request(op=DF5.name,
request_identifier=DF5.memory_request_id)
- requests += DF7._dfield.memory_request(op=DF7.name,
+ requests += DF7._dfield.memory_request(op=DF7.name,
request_identifier=DF7.memory_request_id)
work = requests.allocate(True)
DF5.honor_memory_request(work)
@@ -89,19 +89,19 @@ def test_field():
assert F4.dtype == np.uint16
assert F4.name == 'F4'
assert F4.pretty_name == 'F4'
-
+
def func(data, coords):
for (d, coord) in zip(data, coords):
x,y,z = coord
d[...] = x*y*z
-
+
DF7.initialize(func)
DF7.initialize(DF5.data)
DF7.fill(4)
DF7.randomize()
DF7.copy(DF0)
DF7.integrate()
-
+
DF7.has_ghosts()
DF7.exchange_ghosts()
DF7.accumulate_ghosts()
@@ -123,9 +123,10 @@ def test_tensor_field():
T0 = TensorField(domain, 'T0', (3,3))
T0_bis = Field(domain, 'T0b', shape=(3,3))
T1 = T0.field_like('T1', dtype=np.float16)
- T2 = T0[1:,1:].rename(name='T2')
+ T2 = T0[1:,1:]
+ T2.rename(name='T2')
T3 = T0[1,1]
- T4 = TensorField.from_fields(name='T4',
+ T4 = TensorField.from_fields(name='T4',
fields=(T0[0,0], T0[1,1], T1[0,1], T1[1,0]), shape=(2,2))
T5 = TensorField.from_field_array('T5', T0._fields)
T6 = T5.field_like(name='T6')
@@ -178,10 +179,10 @@ def test_tensor_field():
DT6 = T6.discretize(topo)
DT7 = T7.discretize(topo)
- DT8 = DiscreteTensorField.from_dfields(name='DT8',
- dfields=(DT0.dfields[0],
- DT1.dfields[0],
- DT2.dfields[0],
+ DT8 = DiscreteTensorField.from_dfields(name='DT8',
+ dfields=(DT0.dfields[0],
+ DT1.dfields[0],
+ DT2.dfields[0],
DT3.dfields[0]),
shape=(2,2))
DT9 = DT0[:2,:2]
@@ -207,7 +208,7 @@ def test_tensor_field():
DT9.fill(4)
DT9.randomize()
DT9.copy(DT0[1:,1:])
-
+
DT9.has_ghosts()
DT9.exchange_ghosts()
DT9.accumulate_ghosts()
@@ -329,8 +330,8 @@ def test_boundaries():
"""This test checks that all boundaries are compatible for velocity and vorticity."""
for dim in (1,2,):
i=0
- for (lbd, rbd) in domain_boundary_iterator(dim):
- domain = Box(dim=dim, lboundaries=lbd,
+ for (lbd, rbd) in domain_boundary_iterator(dim):
+ domain = Box(dim=dim, lboundaries=lbd,
rboundaries=rbd)
V = VelocityField(domain)
S = ScalarField(name='S0', domain=domain)
@@ -358,7 +359,7 @@ def test_boundaries():
print '{} (VORTICITY) BOUNDARIES:'.format(rotV.pretty_name)
for Wi in rotV.fields:
print ' *{} boundaries=[{}]'.format(Wi.pretty_name, Wi.format_boundaries())
-
+
if __name__ == '__main__':
diff --git a/hysop/numerics/splitting/test/test_strang.py b/hysop/numerics/splitting/test/test_strang.py
index fb86d81c959aaedfb75a9050fbbeb90ba42c93fd..ac6048a007526bf67185159abb49987678dbf953 100644
--- a/hysop/numerics/splitting/test/test_strang.py
+++ b/hysop/numerics/splitting/test/test_strang.py
@@ -1,6 +1,5 @@
-
from hysop.problem import Problem
-from hysop.operators import DirectionalAdvection, Poisson
+from hysop.operators import DirectionalAdvection, PoissonCurl
from hysop.numerics.splitting.strang import StrangSplitting
from hysop.domain.box import Box
@@ -10,8 +9,6 @@ from hysop.tools.parameters import CartesianDiscretization
from hysop.simulation import Simulation
from hysop.methods import *
-from hysop.backend.device.kernel_autotuner import AutotunerConfig, AutotunerFlags
-# from hysop.constants import callback_profiler
class TestStrang(object):
@@ -22,7 +19,7 @@ class TestStrang(object):
@classmethod
def teardown_class(cls):
pass
-
+
def setup_method(self, method):
pass
@@ -49,43 +46,45 @@ class TestStrang(object):
def _test_strang_nd(self, dim, n):
## Simulation
- simu = Simulation(start=0.0, end=1.0, max_iter=100, time_step=0.1)
+ dt0=0.1
+ simu = Simulation(start=0.0, end=1.0, max_iter=100, dt0=dt0)
simu.initialize()
-
+
## Domain and continuous fields
box, velo, vorti, scalars = self.make_fields(dim,2)
## CartesianDiscretizations and topologies
resolution = (n,)*dim
- dnd = CartesianDiscretization(resolution=resolution, ghosts=None)
- topo = CartesianTopology(box,dnd,dim)
+ dnd = CartesianDiscretization(resolution=resolution, ghosts=None, default_boundaries=True)
+ topo = CartesianTopology(domain=box,discretization=dnd)
## Operators
advec = DirectionalAdvection(
- name='advec',
- velocity = velo,
- advected_fields = (vorti,)+scalars,
- variables = { velo: topo, vorti: topo,
- scalars[0]: topo, scalars[1]: topo},
- split_fields=(vorti, scalars)
+ name='advec',
+ dt = simu.dt,
+ velocity = velo,velocity_cfl=1.*dt0*n,
+ advected_fields = (vorti,)+scalars,
+ variables = { velo: topo, vorti: topo,
+ scalars[0]: topo, scalars[1]: topo},
)
- poisson = Poisson(name='poisson',
- velocity=velo, vorticity=vorti,
- topology=topo)
+ poisson = PoissonCurl(name='poisson',
+ velocity=velo, vorticity=vorti,
+ variables={velo: topo, vorti: topo})
## Graph
- splitting = StrangSplitting(dim=dim, order=StrangOrder.STRANG_FIRST_ORDER)
- splitting.push_operator(advec)
+ splitting = StrangSplitting(splitting_dim=dim,
+ order=StrangOrder.STRANG_FIRST_ORDER)
+ splitting.push_operators(advec)
problem = Problem()
problem.insert(splitting)
problem.insert(poisson)
problem.build()
-
+
problem.display()
problem.finalize()
-
+
def test_strang_2d(self, n=33):
self._test_strang_nd(dim=2, n=n)
def test_strang_3d(self, n=33):
diff --git a/hysop/numerics/tests/test_fft.py b/hysop/numerics/tests/test_fft.py
index 4b42e4e001d74ed1e7f9c4d6631e9ea3ea768f9a..58f4112b21ea92ac1bf0900a2e5fcaa086cc7b6c 100644
--- a/hysop/numerics/tests/test_fft.py
+++ b/hysop/numerics/tests/test_fft.py
@@ -26,14 +26,14 @@ class TestFFT(object):
implementations = {
Implementation.PYTHON: {
- 'numpy': NumpyFFT(warn_on_allocation=False),
- 'scipy': ScipyFFT(warn_on_allocation=False),
+ 'numpy': NumpyFFT(warn_on_allocation=False),
+ 'scipy': ScipyFFT(warn_on_allocation=False),
'fftw': FftwFFT(warn_on_allocation=False,
warn_on_misalignment=False)
},
Implementation.OPENCL: {}
}
-
+
print
print ':: STARTING FFT BACKEND TESTS ::'
for (i,cl_env) in enumerate(iter_clenv()):
@@ -59,7 +59,7 @@ class TestFFT(object):
print '::Testing 1D transform, precision {}::'.format(dtype.__name__)
eps = np.finfo(dtype).eps
ctype = float_to_complex_dtype(dtype)
-
+
def check_distances(results, eps, report_eps, tag, failures):
if len(results.keys())==0:
print 'no support'
@@ -111,9 +111,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=ctype)
plan = impl.fft(a=Bin).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == ctype, self.msg_dtype.format(ctype, Bout.dtype,
+ assert Bout.dtype == ctype, self.msg_dtype.format(ctype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -130,9 +130,9 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results, eps, self.report_eps, 'forward C2C', failures)
-
+
print '\n BACKWARD C2C: complex to complex backward transform'
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' IFFT shape={:12s} ghosts={:12s} '.format(shape, str(ghosts)+':'),
Href = np.random.rand(2*N).astype(dtype).view(dtype=ctype).reshape(shape)
@@ -145,9 +145,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=ctype)
plan = impl.ifft(a=Bin).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == ctype, self.msg_dtype.format(ctype, Bout.dtype,
+ assert Bout.dtype == ctype, self.msg_dtype.format(ctype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -164,9 +164,9 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results, eps, self.report_eps, 'backward C2C', failures)
-
+
print '\n FORWARD R2C: real to hermitian complex transform'
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' RFFT shape={:12s} ghosts={:12s} '.format(shape, str(ghosts)+':'),
Href = np.random.rand(*shape).astype(dtype).reshape(shape)
@@ -179,9 +179,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=dtype)
plan = impl.rfft(a=Bin).setup()
Bout = plan.output_array
- assert Bout.shape == cshape, self.msg_shape.format(cshape, Bout.shape,
+ assert Bout.shape == cshape, self.msg_shape.format(cshape, Bout.shape,
name)
- assert Bout.dtype == ctype, self.msg_dtype.format(ctype, Bout.dtype,
+ assert Bout.dtype == ctype, self.msg_dtype.format(ctype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -198,9 +198,9 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results, eps, self.report_eps, 'R2C', failures)
-
+
print '\n BACKWARD C2R: real to hermitian complex transform'
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' IRFFT shape={:12s} ghosts={:12s} '.format(shape, str(ghosts)+':'),
Href = np.random.rand(2*Nc).astype(dtype).view(dtype=ctype).reshape(cshape)
@@ -213,9 +213,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=cshape, dtype=ctype)
plan = impl.irfft(a=Bin).setup()
Bout = plan.output_array
- assert Bout.shape == rshape, self.msg_shape.format(rshape, Bout.shape,
+ assert Bout.shape == rshape, self.msg_shape.format(rshape, Bout.shape,
name)
- assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
+ assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -235,7 +235,7 @@ class TestFFT(object):
print ('\n BACKWARD FORCED C2R: real to hermitian complex transform with specified '
+'shape')
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' IRFFT shape={:12s} ghosts={:12s} '.format(shape, str(ghosts)+':'),
Href = np.random.rand(2*Nc).astype(dtype).view(dtype=ctype).reshape(cshape)
@@ -248,9 +248,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=cshape, dtype=ctype)
plan = impl.irfft(a=Bin, n=shape[-1]).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
+ assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -267,12 +267,12 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results, eps, self.report_eps, 'forced C2R', failures)
-
+
types = ['I ','II ','III','IV ']
for (itype,stype) in enumerate(types, 1):
print '\n DCT-{}: real to real discrete cosine transform {}'.format(
stype.strip(), itype)
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' DCT-{} shape={:12s} ghosts={:12s} '.format(stype, shape, str(ghosts)+':'),
if (itype==1): # real size is 2*(N-1)
@@ -289,9 +289,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=dtype)
plan = impl.dct(a=Bin, type=itype).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
+ assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -307,14 +307,14 @@ class TestFFT(object):
results[name] = H1 / shape[-1]
except HysopFFTDataLayoutError as e:
results[name] = e
- check_distances(results, eps, self.report_eps,
+ check_distances(results, eps, self.report_eps,
'DCT-{}'.format(stype), failures)
-
+
for (itype,stype) in enumerate(types, 1):
iitype = [1,3,2,4][itype-1]
print '\n IDCT-{}: real to real inverse discrete cosine transform {}'.format(
stype.strip(), itype)
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' IDCT-{} shape={:12s} ghosts={:12s} '.format(stype, shape, str(ghosts)+':'),
if (iitype==1): # real size is 2*(N-1)
@@ -331,9 +331,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=dtype)
plan = impl.idct(a=Bin, type=itype).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
+ assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -349,14 +349,14 @@ class TestFFT(object):
results[name] = H1
except HysopFFTDataLayoutError as e:
results[name] = e
- check_distances(results, eps, self.report_eps,
+ check_distances(results, eps, self.report_eps,
'IDCT-{}'.format(stype), failures)
types = ['I ','II ','III','IV ']
for (itype,stype) in enumerate(types, 1):
print '\n DST-{}: real to real discrete sine transform {}'.format(
stype.strip(), itype)
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' DST-{} shape={:12s} ghosts={:12s} '.format(stype, shape, str(ghosts)+':'),
if (itype==1): # real size will be 2*(N+1)
@@ -373,9 +373,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=dtype)
plan = impl.dst(a=Bin, type=itype).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
+ assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -391,14 +391,14 @@ class TestFFT(object):
results[name] = H1 / shape[-1]
except HysopFFTDataLayoutError as e:
results[name] = e
- check_distances(results, eps, self.report_eps,
+ check_distances(results, eps, self.report_eps,
'DST-{}'.format(stype), failures)
-
+
for (itype,stype) in enumerate(types, 1):
iitype = [1,3,2,4][itype-1]
print '\n IDST-{}: real to real inverse discrete sine transform {}'.format(
stype.strip(), itype)
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' IDST-{} shape={:12s} ghosts={:12s} '.format(stype, shape, str(ghosts)+':'),
if (iitype==1): # real size will be 2*(N+1)
@@ -415,9 +415,9 @@ class TestFFT(object):
Bin = mk_buffer(backend=impl.backend, shape=shape, dtype=dtype)
plan = impl.idst(a=Bin, type=itype).setup()
Bout = plan.output_array
- assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
+ assert Bout.shape == shape, self.msg_shape.format(shape, Bout.shape,
name)
- assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
+ assert Bout.dtype == dtype, self.msg_dtype.format(dtype, Bout.dtype,
name)
Bin[...] = Href
plan.execute()
@@ -433,9 +433,9 @@ class TestFFT(object):
results[name] = H1
except HysopFFTDataLayoutError as e:
results[name] = e
- check_distances(results, eps, self.report_eps,
+ check_distances(results, eps, self.report_eps,
'IDST-{}'.format(stype), failures)
-
+
@@ -467,7 +467,7 @@ class TestFFT(object):
raise RuntimeError(msg)
print '\n C2C-C2C transform'
- for (shape, cshape, rshape, N, Nc, Nr,
+ for (shape, cshape, rshape, N, Nc, Nr,
ghosts, mk_buffer) in self.iter_shapes():
print ' X - IFFT(FFT(X)) shape={:12s} ghosts={:12s}'.format(shape, str(ghosts)+':'),
Href = np.random.rand(2*N).astype(dtype).view(dtype=ctype).reshape(shape)
@@ -525,7 +525,7 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results)
-
+
print '\n R2R-R2R transforms'
types = ['I ','II ','III','IV ']
@@ -568,7 +568,7 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results)
-
+
for (itype,stype) in enumerate(types, 1):
print '\n DST-{}: real to real discrete sinine transform {}'.format(
stype.strip(), itype)
@@ -608,7 +608,7 @@ class TestFFT(object):
except HysopFFTDataLayoutError as e:
results[name] = e
check_distances(results)
-
+
def iter_shapes(self):
minj=(3,3)
maxj=(6,6)
@@ -643,7 +643,7 @@ class TestFFT(object):
assert buf.dtype == dtype
return buf
yield (shape, cshape, rshape, N, Nc, Nr, ghosts, mk_buffer)
-
+
def report_failures(self, failures):
print
print '== TEST FAILURES REPORT =='
@@ -682,7 +682,7 @@ class TestFFT(object):
msg+='\n***************************************************'
msg+='\n'
print msg
-
+
def perform_tests(self):
# not testing np.longdouble because only one implementation supports it
@@ -696,11 +696,18 @@ class TestFFT(object):
self._test_forward_backward_1d(dtype=dtype)
self._test_1d(dtype=dtype, failures=failures.setdefault(dtype.__name__, {}))
self.report_failures(failures)
-
+
+ def test_1d(self):
+ failures = {}
+ self._test_forward_backward_1d(dtype=HYSOP_REAL)
+ self._test_1d(dtype=HYSOP_REAL, failures=failures.setdefault(HYSOP_REAL.__name__, {}))
+ self.report_failures(failures)
+
+
if __name__ == '__main__':
test = TestFFT()
- with printoptions(threshold=10000, linewidth=240,
- nanstr='nan', infstr='inf',
+ with printoptions(threshold=10000, linewidth=240,
+ nanstr='nan', infstr='inf',
formatter={'float': lambda x: '{:>0.2f}'.format(x)}):
test.perform_tests()
diff --git a/hysop/operator/base/custom_symbolic_operator.py b/hysop/operator/base/custom_symbolic_operator.py
index 913530cd267ad84b2cf5a6d984a3cd31abdcc830..2c5562461b370a4a26de37399204e529ee68b2e0 100644
--- a/hysop/operator/base/custom_symbolic_operator.py
+++ b/hysop/operator/base/custom_symbolic_operator.py
@@ -344,12 +344,8 @@ class SymbolicExpressionInfo(object):
else:
msg='No discrete fields found in custom symbolic operator.'
raise RuntimeError(msg)
-<<<<<<< HEAD
-
-=======
self.axes = axes
->>>>>>> master
SymbolicExpressionParser.discretize_expressions(self)
self.check_dfield_sizes()
diff --git a/hysop/operator/tests/test_analytic.py b/hysop/operator/tests/test_analytic.py
index 7822a30cab1283a89b42c740950dfd21effe457f..47b66cd7e059252f98f42af617768e832b8cc876 100644
--- a/hysop/operator/tests/test_analytic.py
+++ b/hysop/operator/tests/test_analytic.py
@@ -19,26 +19,26 @@ from hysop import Field, Box
class TestAnalyticField(object):
@classmethod
- def setup_class(cls,
+ def setup_class(cls,
enable_extra_tests=__ENABLE_LONG_TESTS__,
enable_debug_mode=False):
IO.set_default_path('/tmp/hysop_tests/test_analytic')
-
+
if enable_debug_mode:
cls.size_min = 15
cls.size_max = 16
else:
cls.size_min = 23
cls.size_max = 87
-
+
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
cls.t = ScalarParameter(name='t', dtype=HYSOP_REAL)
-
+
cls.build_analytic_expressions()
-
+
@classmethod
def build_analytic_expressions(cls):
from hysop.tools.sympy_utils import enable_pretty_printing
@@ -46,7 +46,7 @@ class TestAnalyticField(object):
from hysop.symbolic.frame import SymbolicFrame
from hysop.symbolic.field import curl, laplacian
enable_pretty_printing()
-
+
#at this moment we just test a periodic solver
analytic_expressions = {}
analytic_functions = {}
@@ -57,13 +57,13 @@ class TestAnalyticField(object):
def gen_F0():
kis = tuple(random.randint(1,5) for _ in xrange(dim))
qis = tuple(npw.random.rand(dim).round(decimals=3).tolist())
- basis = tuple( (sm.cos(ki*xi+qi), sm.sin(ki*xi+qi))
+ basis = tuple( (sm.cos(ki*xi+qi), sm.sin(ki*xi+qi))
for (ki,qi,xi) in zip(kis, qis, coords) )
F0 = sm.Integer(1) / (sm.Integer(1) + cls.t.s)
for i in xrange(dim):
F0 *= random.choice(basis[i])
return F0
-
+
def gen_F1():
base = tuple(tuple( coords[i]**k for k in xrange(5) ) for i in xrange(dim))
base = tuple(set(npw.prod(x) for x in it.product(*base)))
@@ -71,7 +71,7 @@ class TestAnalyticField(object):
F1 = sm.Integer(1) / (sm.Integer(1) + cls.t.s)
F1 *= (base * (npw.random.rand(len(base)).round(2))).sum()
return F1
-
+
params = coords + (cls.t.s,)
Fs = npw.asarray([gen_F0(), gen_F1()], dtype=object).view(TensorBase)
fFs = tuple(sm.lambdify(params, F) for F in Fs)
@@ -110,16 +110,16 @@ class TestAnalyticField(object):
size_max = first_not_None(size_max, self.size_max)
shape = tuple(npw.random.randint(low=size_min, high=size_max+1, size=dim).tolist())
-
+
domain = Box(length=(1,)*dim)
F = Field(domain=domain, name='F', dtype=dtype,
nb_components=2, register_object=False)
-
- self._test_one(shape=shape, dim=dim, dtype=dtype,
+
+ self._test_one(shape=shape, dim=dim, dtype=dtype,
domain=domain, F=F)
-
- def _test_one(self, shape, dim, dtype,
+
+ def _test_one(self, shape, dim, dtype,
domain, F):
print '\nTesting {}D AnalyticField: dtype={} shape={}'.format(
@@ -132,19 +132,19 @@ class TestAnalyticField(object):
print ' >Testing all implementations:'
implementations = AnalyticField.implementations()
-
+
variables = { F:shape }
fns = self.analytic_functions[dim]['F']
exprs = self.analytic_expressions[dim]['F']
def iter_impl(impl):
base_kwds = dict(field=F, variables=variables,
- implementation=impl,
+ implementation=impl,
name='analytic_{}'.format(str(impl).lower()))
if impl is Implementation.PYTHON:
msg=' *Python: '
print msg,
- yield AnalyticField(formula=self.__analytic_init,
+ yield AnalyticField(formula=self.__analytic_init,
extra_input_kwds={'fns':fns, 't':self.t},
**base_kwds)
print
@@ -153,7 +153,7 @@ class TestAnalyticField(object):
msg=' *Opencl: '
print msg
for cl_env in iter_clenv():
- msg=' >platform {}, device {}:'.format(cl_env.platform.name.strip(),
+ msg=' >platform {}, device {}:'.format(cl_env.platform.name.strip(),
cl_env.device.name.strip())
print msg,
yield AnalyticField(cl_env=cl_env, formula=exprs, **base_kwds)
@@ -162,24 +162,24 @@ class TestAnalyticField(object):
else:
msg='Unknown implementation to test {}.'.format(impl)
raise NotImplementedError(msg)
-
+
# Compare to analytic solution
Fref = None
for impl in implementations:
for op in iter_impl(impl):
op = op.build()
dF = op.get_output_discrete_field(F)
-
+
if (Fref is None):
dF.initialize(self.__analytic_init, fns=fns, t=self.t)
Fref = tuple( data.get().handle.copy() for data in dF.data )
-
+
dF.initialize(self.__random_init)
op.apply()
-
+
Fout = tuple( data.get().handle.copy() for data in dF.data )
self._check_output(impl, op, Fref, Fout)
-
+
@classmethod
def _check_output(cls, impl, op, Fref, Fout):
check_instance(Fref, tuple, values=npw.ndarray)
@@ -197,12 +197,12 @@ class TestAnalyticField(object):
print
msg = msg0.format(iname)
raise ValueError(msg)
-
+
for i, (fout,fref) in enumerate(zip(Fout, Fref)):
iname = '{}{}'.format('F',i)
assert fout.dtype == fref.dtype, iname
assert fout.shape == fref.shape, iname
-
+
eps = npw.finfo(fout.dtype).eps
dist = npw.abs(fout-fref)
dinf = npw.max(dist)
@@ -212,7 +212,7 @@ class TestAnalyticField(object):
continue
has_nan = npw.any(npw.isnan(fout))
has_inf = npw.any(npw.isinf(fout))
-
+
print
print
print 'Test output comparisson for {} failed for component {}:'.format(name, i)
@@ -246,9 +246,9 @@ class TestAnalyticField(object):
print w
print
print
-
+
msg = 'Test failed for {} on component {} for implementation {}.'.format(name, i, impl)
- raise RuntimeError(msg)
+ raise RuntimeError(msg)
def test_1d_float32(self):
@@ -274,15 +274,15 @@ class TestAnalyticField(object):
self.test_1d_float64()
self.test_2d_float64()
self.test_3d_float64()
-
+
if __name__ == '__main__':
- TestAnalyticField.setup_class(enable_extra_tests=False,
+ TestAnalyticField.setup_class(enable_extra_tests=False,
enable_debug_mode=False)
-
+
test = TestAnalyticField()
- with printoptions(threshold=10000, linewidth=240,
- nanstr='nan', infstr='inf',
+ with printoptions(threshold=10000, linewidth=240,
+ nanstr='nan', infstr='inf',
formatter={'float': lambda x: '{:>6.2f}'.format(x)}):
test.perform_tests()
diff --git a/hysop/operator/tests/test_custom_symbolic.py b/hysop/operator/tests/test_custom_symbolic.py
index 62dd3e00bc4f95851103d5d99e362545b41a3c12..8f3ca661b1b9769411fac469b4d352aa9fd19ab5 100644
--- a/hysop/operator/tests/test_custom_symbolic.py
+++ b/hysop/operator/tests/test_custom_symbolic.py
@@ -1,4 +1,3 @@
-
from hysop import Field, Box
from hysop.deps import np, it, sm
from hysop.constants import Implementation, ComputeGranularity, SpaceDiscretization, HYSOP_REAL
@@ -23,12 +22,12 @@ from hysop.numerics.odesolvers.runge_kutta import TimeIntegrator, Euler, RK2, RK
class TestCustomSymbolic(object):
@classmethod
- def setup_class(cls,
+ def setup_class(cls,
enable_extra_tests=__ENABLE_LONG_TESTS__,
enable_debug_mode=False):
-
+
IO.set_default_path('/tmp/hysop_tests/test_custom_symbolic')
-
+
if enable_debug_mode:
cls.size_min0 = 20
cls.size_max0 = 20
@@ -39,10 +38,10 @@ class TestCustomSymbolic(object):
cls.size_max0 = 4096
cls.size_min = 3
cls.size_max = 16
-
+
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
cls.dtypes = [np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64,
np.float32, np.float64]
@@ -56,17 +55,17 @@ class TestCustomSymbolic(object):
shape = data[0].shape
if is_integer(dtype):
for d in data:
- d[...] = np.random.random_integers(low=0, high=255, size=shape)
+ d[...] = np.random.random_integers(low=0, high=255, size=shape)
elif is_fp(dtype):
for d in data:
if pollute:
d[...] = np.nan
else:
- d[...] = np.random.random(size=d.shape)
+ d[...] = np.random.random(size=d.shape)
else:
msg='Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
-
+
@staticmethod
def iter_implementations(op_cls, base_kwds):
for impl in op_cls.implementations():
@@ -74,7 +73,7 @@ class TestCustomSymbolic(object):
base_kwds['implementation'] = impl
if impl is Implementation.OPENCL:
for cl_env in iter_clenv():
- print ' *platform {}, device {}: '.format(cl_env.platform.name.strip(),
+ print ' *platform {}, device {}: '.format(cl_env.platform.name.strip(),
cl_env.device.name.strip()),
yield impl, op_cls(cl_env=cl_env, **base_kwds)
else:
@@ -82,7 +81,7 @@ class TestCustomSymbolic(object):
yield impl, op_cls(**base_kwds)
@classmethod
- def _check_output(cls, impl, op, in_names, refin_buffers, out_names, refout_buffers,
+ def _check_output(cls, impl, op, in_names, refin_buffers, out_names, refout_buffers,
out_buffers):
check_instance(out_buffers, tuple, values=np.ndarray)
check_instance(refout_buffers, tuple, values=np.ndarray)
@@ -91,7 +90,7 @@ class TestCustomSymbolic(object):
for i, (oname, out, refout) in enumerate(zip(out_names, out_buffers, refout_buffers)):
assert refout.dtype == out.dtype, '{} vs {}'.format(refout.dtype, out.dtype)
assert refout.shape == out.shape, '{} vs {}'.format(refout.shape, out.shape)
-
+
has_nan = np.any(np.isnan(refout))
has_inf = np.any(np.isinf(refout))
if (out.dtype != refout.dtype):
@@ -103,7 +102,7 @@ class TestCustomSymbolic(object):
has_nan = np.any(np.isnan(out))
has_inf = np.any(np.isinf(out))
-
+
distances = np.abs(out - refout) / np.max(refout)
if is_integer(out.dtype):
mask = (out == refout)
@@ -123,7 +122,7 @@ class TestCustomSymbolic(object):
if (not has_nan) and (not has_inf) and mask.all():
print msg,
continue
- print
+ print
print 'Failed to match output of {}:'.format(oname)
print
print 'Test output comparisson failed for component {}:'.format(i)
@@ -131,7 +130,7 @@ class TestCustomSymbolic(object):
print ' *has_inf: {}'.format(has_inf)
print
if cls.enable_debug_mode:
- mask[...] = False
+ mask[...] = False
print 'REFERENCE INPUTS:'
for name, _in in zip(in_names, refin_buffers):
print name
@@ -154,16 +153,16 @@ class TestCustomSymbolic(object):
print '{} DISTANCES (EPS):'.format(oname)
print eps_distances[~mask]
print
-
+
msg = 'Test failed on component {} for implementation {}.'.format(i, impl)
- raise RuntimeError(msg)
+ raise RuntimeError(msg)
print
-
+
def _test_simple(self, dim, _size_min=None, _size_max=None):
enable_extra_tests = self.enable_extra_tests
assert dim >= 1
-
- print 'TEST SIMPLE'
+
+ print 'TEST SIMPLE'
print ' DIM {}'.format(dim)
size_min = first_not_None(_size_min, self.size_min)
@@ -173,34 +172,34 @@ class TestCustomSymbolic(object):
domain = Box(length=(1.0,)*dim)
- discretization = tuple(np.random.randint(low=size_min, high=size_max+1,
+ discretization = tuple(np.random.randint(low=size_min, high=size_max+1,
size=dim-1).tolist())
- discretization0 = tuple(np.random.randint(low=size_min0, high=size_max0+1,
+ discretization0 = tuple(np.random.randint(low=size_min0, high=size_max0+1,
size=1).tolist())
discretization = discretization + discretization0
print ' DISCRETIZATION {}'.format(discretization)
-
+
if __ENABLE_LONG_TESTS__:
dtypes = (np.float32, np.float64)
else:
dtypes = (HYSOP_REAL,)
-
+
for dtype in dtypes:
print ' DTYPE {}'.format(dtype.__name__)
- A = Field(domain=domain, name='A', dtype=dtype,
+ A = Field(domain=domain, name='A', dtype=dtype,
nb_components=1, register_object=False)
- B = Field(domain=domain, name='B', dtype=dtype,
+ B = Field(domain=domain, name='B', dtype=dtype,
nb_components=1, register_object=False)
- C = Field(domain=domain, name='C', dtype=dtype,
+ C = Field(domain=domain, name='C', dtype=dtype,
nb_components=3, register_object=False)
-
+
P0 = ScalarParameter('P0', dtype=np.float32, initial_value=1.0)
P1 = ScalarParameter('P1', dtype=np.float64, initial_value=2.0, const=True)
- T0 = TensorParameter('T0', shape=(13,), dtype=np.int32,
+ T0 = TensorParameter('T0', shape=(13,), dtype=np.int32,
initial_value=np.arange(13, dtype=np.int32))
T1 = TensorParameter('T1', shape=(3,3), dtype=np.int32)
-
+
As = A.s()
Bs = B.s()
Cs = C.s()
@@ -209,60 +208,60 @@ class TestCustomSymbolic(object):
for granularity in xrange(dim):
print ' GRANULARITY {}'.format(granularity)
-
+
self._test_affect((A,), (42,), discretization, granularity)
self._test_affect((A,B,C), (1,2,3), discretization, granularity)
-
+
if __ENABLE_LONG_TESTS__:
expr = Assignment(As, 1+P0s)
compute_outputs = lambda ifields, iparams, dfields, ovar, i: \
np.full(fill_value=1+iparams['P0'], shape=ovar.resolution, dtype=ovar.dtype)
- self._test_expr(expr, compute_outputs,
+ self._test_expr(expr, compute_outputs,
variables={A:discretization}, method={ComputeGranularity:granularity})
P0.value = 4.0
compute_outputs = lambda ifields, iparams, dfields, ovar, i: np.full(fill_value=5, shape=ovar.resolution, dtype=ovar.dtype)
- self._test_expr(expr, compute_outputs,
+ self._test_expr(expr, compute_outputs,
variables={A:discretization}, method={ComputeGranularity:granularity})
-
+
expr = Assignment(Bs, np.sum(T0s[1::2]))
compute_outputs = lambda ifields, iparams, dfields, ovar, i: np.full(fill_value=1+3+5+7+9+11, shape=ovar.resolution, dtype=ovar.dtype)
- self._test_expr(expr, compute_outputs,
+ self._test_expr(expr, compute_outputs,
variables={B:discretization}, method={ComputeGranularity:granularity})
compute_outputs = lambda ifields, iparams, dfields, ovar, i: ifields[C[0]]
- self._test_expr(Assignment(As, C.s[0]()), compute_outputs,
- variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
-
+ self._test_expr(Assignment(As, C.s[0]()), compute_outputs,
+ variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
+
compute_outputs = lambda ifields, iparams, dfields, ovar, i: 2*ifields[C[0]] + 8
- self._test_expr(Assignment(As, 2*C.s[0]()+8), compute_outputs,
- variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
-
+ self._test_expr(Assignment(As, 2*C.s[0]()+8), compute_outputs,
+ variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
+
if (dim==3):
- compute_outputs = lambda ifields, iparams, dfields, ovar, i: ifields[C][0]*ifields[C][1]*ifields[C][2]
- self._test_expr(Assignment(As, C.s[0]()*C.s[1]()*C.s[2]()), compute_outputs,
+ compute_outputs = lambda ifields, iparams, dfields, ovar, i: ifields[C[0]]*ifields[C[1]]*ifields[C[2]]
+ self._test_expr(Assignment(As, C.s[0]()*C.s[1]()*C.s[2]()), compute_outputs,
variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
-
+
x0 = domain.frame.coords[0]
- compute_outputs = lambda ifields, iparams, dfields, ovar, i: 2*ifields[A] - 3*ifields[C][0]*ifields[C][1]*ifields[C][2]
- self._test_expr(Assignment(As, 2*As-3*C.s[0]()*C.s[1]()*C.s[2]()), compute_outputs,
+ compute_outputs = lambda ifields, iparams, dfields, ovar, i: 2*ifields[A] - 3*ifields[C[0]]*ifields[C[1]]*ifields[C[2]]
+ self._test_expr(Assignment(As, 2*As-3*C.s[0]()*C.s[1]()*C.s[2]()), compute_outputs,
variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
-
- compute_outputs = lambda ifields, iparams, dfields, ovar, i: (2*np.cos(ifields[C][0])*np.sin(ifields[C][1])*np.tan(ifields[C][2])).astype(ovar.dtype)
- self._test_expr(Assignment(As, 2*sm.cos(C.s[0]())*sm.sin(C.s[1]())*sm.tan(C.s[2]())), compute_outputs,
+
+ compute_outputs = lambda ifields, iparams, dfields, ovar, i: (2*np.cos(ifields[C[0]])*np.sin(ifields[C[1]])*np.tan(ifields[C[2]])).astype(ovar.dtype)
+ self._test_expr(Assignment(As, 2*sm.cos(C.s[0]())*sm.sin(C.s[1]())*sm.tan(C.s[2]())), compute_outputs,
variables={A:discretization, C:discretization}, method={ComputeGranularity:granularity})
-
- def _test_expr(self, exprs, compute_outputs, variables, method,
+
+ def _test_expr(self, exprs, compute_outputs, variables, method,
apply_kwds=None, no_ref_view=False, dt=None):
exprs = to_tuple(exprs)
print ' CustomExpr: {}'.format(' || '.join(str(e) for e in exprs))
-
+
assert ComputeGranularity in method
base_kwds = dict(name='array_affect', exprs=exprs, variables=variables, method=method, dt=dt)
apply_kwds = first_not_None(apply_kwds, {})
for impl, op in self.iter_implementations(CustomSymbolicOperator, base_kwds):
problem = op.build()
-
+
for field, dfield in problem.iter_output_discrete_fields():
dfield.initialize(self.__field_init, dtype=dfield.dtype, pollute=True, only_finite=False)
for field, dfield in problem.iter_input_discrete_fields():
@@ -295,7 +294,7 @@ class TestCustomSymbolic(object):
out_names.append(pname)
problem.apply(**apply_kwds)
-
+
out = {'f': {}, 'p': {}, 'dfields': {}}
for field, ofield in problem.iter_output_discrete_fields(as_scalars=True):
out['f'][field] = ()
@@ -322,7 +321,7 @@ class TestCustomSymbolic(object):
for _ in x['p'].values():
out += (np.asarray(_),)
return out
-
+
self._check_output(impl, op, in_names, flatten(refin), out_names, flatten(refout), flatten(out))
def _test_affect(self, fields, rhs, discretization, granularity):
@@ -333,9 +332,9 @@ class TestCustomSymbolic(object):
for i in xrange(f.nb_components):
e = Assignment(f.s[i](),c)
exprs += (e,)
-
+
print ' CustomExpr: {}'.format(' || '.join(str(e) for e in exprs))
-
+
method={ComputeGranularity: granularity}
base_kwds = dict(name='custom_affect', exprs=exprs, variables=variables, method=method)
for impl, op in self.iter_implementations(CustomSymbolicOperator, base_kwds):
@@ -350,9 +349,9 @@ class TestCustomSymbolic(object):
for i in xrange(dfield.nb_components):
refin += (dfield.data[i].get().handle[view],)
in_names.append(ofield.name+'::{}'.format(i))
-
+
problem.apply()
-
+
out = ()
refout = ()
out_names = []
@@ -374,7 +373,7 @@ class TestCustomSymbolic(object):
def _test_stencil(self, dim, _size_min=None, _size_max=None):
enable_extra_tests = self.enable_extra_tests
assert dim >= 1
- print 'TEST STENCIL'
+ print 'TEST STENCIL'
print ' DIM {}'.format(dim)
size_min = first_not_None(_size_min, self.size_min)
@@ -385,23 +384,23 @@ class TestCustomSymbolic(object):
domain = Box(length=(1.0,)*dim)
frame = domain.frame
- discretization = tuple(np.random.randint(low=size_min, high=size_max+1,
+ discretization = tuple(np.random.randint(low=size_min, high=size_max+1,
size=dim-1).tolist())
- discretization0 = tuple(np.random.randint(low=size_min0, high=size_max0+1,
+ discretization0 = tuple(np.random.randint(low=size_min0, high=size_max0+1,
size=1).tolist())
discretization = discretization + discretization0
print ' DISCRETIZATION {}'.format(discretization)
- A = Field(domain=domain, name='A', dtype=np.float32,
+ A = Field(domain=domain, name='A', dtype=np.float32,
nb_components=1, register_object=False)
- B = Field(domain=domain, name='B', dtype=np.float32,
+ B = Field(domain=domain, name='B', dtype=np.float32,
nb_components=2, register_object=False)
- C = Field(domain=domain, name='C', dtype=np.float64,
+ C = Field(domain=domain, name='C', dtype=np.float64,
nb_components=3, register_object=False)
P0 = ScalarParameter('P0', dtype=np.float32, initial_value=3.14)
T0 = TensorParameter('T', shape=(3,), dtype=np.int32, initial_value=[4,3,2])
-
+
As = A.s()
Bs = B.s()
Cs = C.s()
@@ -409,7 +408,7 @@ class TestCustomSymbolic(object):
T0s = T0.s
x0 = frame.coords[0]
-
+
csg = CenteredStencilGenerator()
csg.configure(dtype=MPQ, dim=1)
@@ -417,31 +416,31 @@ class TestCustomSymbolic(object):
orders = (2,4)
else:
orders = (4,)
-
+
for order in orders:
print ' ORDER {}'.format(order)
for granularity in xrange(dim):
print ' GRANULARITY {}'.format(granularity)
-
+
if __ENABLE_LONG_TESTS__:
expr = Assignment(As, B.s[0]().diff(x0,x0))
stencil = csg.generate_exact_stencil(derivative=2, order=order)
def compute_outputs(fields, iparams, ifields, ovar, i):
return stencil.apply(fields[B[0]], symbols={stencil.dx:ovar.space_step[-1]}, axis=-1)[ifields[B[0]].compute_slices]
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
method={ComputeGranularity:granularity, SpaceDiscretization:order})
-
-
+
+
expr = Assignment(As, 1+2*B.s[0]().diff(x0))
stencil = csg.generate_exact_stencil(derivative=1, order=order)
def compute_outputs(fields, iparams, ifields, ovar, i):
res = stencil.apply(fields[B[0]], symbols={stencil.dx:ovar.space_step[-1]}, axis=-1)[ifields[B[0]].compute_slices]
return 1+2*res
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
method={ComputeGranularity:granularity, SpaceDiscretization:order})
-
+
expr = Assignment(Bs[0](), (1+np.dot([3,-2], Bs.diff(x0)))*As.diff(x0))
stencil = csg.generate_exact_stencil(derivative=1, order=order)
@@ -454,10 +453,10 @@ class TestCustomSymbolic(object):
else:
return ovar.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
method={ComputeGranularity:granularity, SpaceDiscretization:order})
-
+
expr0 = Assignment(B.s[0](), (1+np.dot([3,-2], Bs.diff(x0)))*As.diff(x0))
expr1 = Assignment(B.s[1](), (1-np.dot([3,-2], Bs.diff(x0)))*As.diff(x0))
expr2 = Assignment(A.s[0](), 0.27 + 1.57*sm.cos(Bs[0].diff(x0))*sm.sin(Bs[1].diff(x0)))
@@ -473,10 +472,10 @@ class TestCustomSymbolic(object):
return (1-(3*res0)+(2*res1))*res2
else:
return 0.27 + 1.57*np.cos(res0)*np.sin(res1)
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
method={ComputeGranularity:granularity, SpaceDiscretization:order})
-
+
expr = Assignment(B.s[0](), T0s[2]*((4+P0s)*As*B.s[0]().diff(x0)+T0s[1]*Bs[1]).diff(x0) + P0s*T0s[0])
stencil0 = csg.generate_exact_stencil(derivative=1, order=order)
stencil1 = csg.generate_exact_stencil(derivative=2, order=order)
@@ -494,15 +493,15 @@ class TestCustomSymbolic(object):
return P0[0]*T0[0] + T0[2]*((4+P0[0])*(A0*d2B0+dA0*dB0) + T0[1]*dB1)
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
method={ComputeGranularity:granularity, SpaceDiscretization:order})
-
-
+
+
def _test_time_integrator(self, dim, _size_min=None, _size_max=None):
enable_extra_tests = self.enable_extra_tests
assert dim >= 1
- print 'TEST INTEGRATOR'
+ print 'TEST INTEGRATOR'
print ' DIM {}'.format(dim)
size_min = first_not_None(_size_min, self.size_min)
@@ -513,38 +512,38 @@ class TestCustomSymbolic(object):
domain = Box(length=(1.0,)*dim)
frame = domain.frame
- discretization = tuple(np.random.randint(low=size_min, high=size_max+1,
+ discretization = tuple(np.random.randint(low=size_min, high=size_max+1,
size=dim-1).tolist())
- discretization0 = tuple(np.random.randint(low=size_min0, high=size_max0+1,
+ discretization0 = tuple(np.random.randint(low=size_min0, high=size_max0+1,
size=1).tolist())
discretization = discretization + discretization0
print ' DISCRETIZATION {}'.format(discretization)
- A = Field(domain=domain, name='A', dtype=np.float32,
+ A = Field(domain=domain, name='A', dtype=np.float32,
nb_components=1, register_object=False)
- B = Field(domain=domain, name='B', dtype=np.float32,
+ B = Field(domain=domain, name='B', dtype=np.float32,
nb_components=2, register_object=False)
- C = Field(domain=domain, name='C', dtype=np.float32,
+ C = Field(domain=domain, name='C', dtype=np.float32,
nb_components=3, register_object=False)
-
+
P0 = ScalarParameter('P0', dtype=np.float32, initial_value=3.14)
T0 = TensorParameter('T', shape=(3,), dtype=np.int32, initial_value=[4,3,2])
-
+
As = A.s()
Bs = B.s()
Cs = C.s()
P0s = P0.s
T0s = T0.s
-
+
T = ScalarParameter(name=frame.time, dtype=np.float32, initial_value=0.0)
DT = ScalarParameter(name=dtime_symbol, dtype=np.float32, initial_value=0.1)
t = T.s
x0 = frame.coords[0]
-
+
csg = CenteredStencilGenerator()
csg.configure(dtype=MPQ, dim=1)
-
+
order = 4
granularity = 0
print ' GRANULARITY {}'.format(granularity)
@@ -553,7 +552,7 @@ class TestCustomSymbolic(object):
D1 = csg.generate_exact_stencil(derivative=1, order=order)
D2 = csg.generate_exact_stencil(derivative=2, order=order)
D3 = csg.generate_exact_stencil(derivative=3, order=order)
-
+
if __ENABLE_LONG_TESTS__:
integrators = [Euler, RK2, RK4, RK4_38]
else:
@@ -561,7 +560,7 @@ class TestCustomSymbolic(object):
for integrator in integrators:
print ' INTEGRATOR {}'.format(integrator)
-
+
if __ENABLE_LONG_TESTS__:
expr = Assignment(As.diff(t), 0)
def compute_outputs(fields, iparams, ifields, ovar, i):
@@ -570,9 +569,9 @@ class TestCustomSymbolic(object):
return fields[A].copy()
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization, C:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization, C:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT)
expr = Assignment(As.diff(t), 1)
@@ -587,12 +586,12 @@ class TestCustomSymbolic(object):
return Xout['a']
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization, C:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization, C:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT)
-
-
+
+
expr = Assignment(As.diff(t), np.dot([2,-3], Bs))
def compute_outputs(fields, iparams, ifields, ovar, i):
A0 = fields[A]
@@ -607,11 +606,11 @@ class TestCustomSymbolic(object):
return Xout['a']
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization, C:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization, C:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT)
-
+
expr = Assignment(As.diff(t), As*Bs[0] + Bs[1])
def compute_outputs(fields, iparams, ifields, ovar, i):
A0 = fields[A]
@@ -626,11 +625,11 @@ class TestCustomSymbolic(object):
return Xout['a']
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization, C:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization, C:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT)
-
+
expr0 = Assignment(Bs[0].diff(t), 1+Bs[1])
expr1 = Assignment(Bs[1].diff(t), 1-Bs[0])
expr = (expr0, expr1)
@@ -649,12 +648,12 @@ class TestCustomSymbolic(object):
return Xout[varname]
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization, C:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization, C:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT)
-
-
+
+
expr = Assignment(As.diff(t), Bs[0].diff(x0))
def compute_outputs(fields, iparams, ifields, ovar, i):
A0 = fields[A]
@@ -669,12 +668,12 @@ class TestCustomSymbolic(object):
return Xout['a']
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT)
-
-
+
+
expr = Assignment(As.diff(t), As.diff(x0))
def compute_outputs(fields, iparams, ifields, ovar, i):
A0 = fields[A]
@@ -689,11 +688,11 @@ class TestCustomSymbolic(object):
return Xout['a']
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT, no_ref_view=True)
-
+
expr = Assignment(As.diff(t), P0s*Bs[0]*As.diff(x0) + Bs[1].diff(x0,x0)*As)
def compute_outputs(fields, iparams, ifields, ovar, i):
A0 = fields[A]
@@ -715,11 +714,11 @@ class TestCustomSymbolic(object):
return Xout['a']
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT, no_ref_view=True)
-
+
expr0 = Assignment(Bs[0].diff(t), 1 - As*Bs[1].diff(x0))
expr1 = Assignment(Bs[1].diff(t), 1 + As*Bs[0].diff(x0))
expr = (expr0, expr1)
@@ -727,13 +726,13 @@ class TestCustomSymbolic(object):
A0 = fields[A]
B0 = fields[B[0]]
B1 = fields[B[1]]
- b0_view = ifields[B[0]].compute_slices
- b1_view = ifields[B[1]].compute_slices
+ b0_view = ifields[B[0]].compute_slices
+ b1_view = ifields[B[1]].compute_slices
assert order%2==0
bg = order//2
v = (Ellipsis, slice(bg, -bg))
if (ovar.dfield._field in B.fields):
- Xin = { 'b0': B0,
+ Xin = { 'b0': B0,
'b1': B1 }
Xout = { 'b0': np.empty_like(Xin['b0'][ifields[B[0]].compute_slices]),
'b1': np.empty_like(Xin['b1'][ifields[B[1]].compute_slices]) }
@@ -753,9 +752,9 @@ class TestCustomSymbolic(object):
return Xout[varname]
else:
return ovar.dfield.data[i].get().handle
- self._test_expr(expr, compute_outputs,
- variables={A:discretization, B:discretization},
- method={ComputeGranularity:granularity, SpaceDiscretization:order,
+ self._test_expr(expr, compute_outputs,
+ variables={A:discretization, B:discretization},
+ method={ComputeGranularity:granularity, SpaceDiscretization:order,
TimeIntegrator:integrator}, dt=DT, no_ref_view=True)
def test_simple_1d(self):
@@ -782,7 +781,7 @@ class TestCustomSymbolic(object):
self.test_simple_2d()
if __ENABLE_LONG_TESTS__:
self.test_simple_3d()
-
+
self.test_stencil_1d()
self.test_stencil_2d()
if __ENABLE_LONG_TESTS__:
@@ -792,13 +791,13 @@ class TestCustomSymbolic(object):
self.test_time_integrator_2d()
if __ENABLE_LONG_TESTS__:
self.test_time_integrator_3d()
-
+
if __name__ == '__main__':
- TestCustomSymbolic.setup_class(enable_extra_tests=False,
+ TestCustomSymbolic.setup_class(enable_extra_tests=False,
enable_debug_mode=False)
-
+
enable_pretty_printing()
-
+
test = TestCustomSymbolic()
test.perform_tests()
diff --git a/hysop/operator/tests/test_diffusion.py b/hysop/operator/tests/test_diffusion.py
index ddf2cbf9a4eaacb57ef553548c9a1d703454b449..4ac8706b20d697db6816486d8787ce969c060398 100644
--- a/hysop/operator/tests/test_diffusion.py
+++ b/hysop/operator/tests/test_diffusion.py
@@ -43,7 +43,7 @@ class TestDiffusionOperator(object):
size_max = first_not_None(size_max, self.size_max) + 1
shape = tuple(npw.random.randint(low=size_min, high=size_max, size=dim).tolist())
-
+
if __ENABLE_LONG_TESTS__:
flt_types = (npw.float32, npw.float64)
else:
@@ -105,10 +105,10 @@ class TestDiffusionOperator(object):
implementations = Diffusion.implementations()
ref_impl = Implementation.PYTHON # ref impl is always the first
-
+
def iter_impl(impl):
base_kwds = dict(Fin=fin, nu=nu, dt=dt,
- variables=variables, implementation=impl,
+ variables=variables, implementation=impl,
name='test_diffusion_{}'.format(str(impl).lower()))
if not is_inplace:
base_kwds['Fout'] = fout
@@ -224,7 +224,7 @@ class TestDiffusionOperator(object):
if not mask.all():
msg='\nFATAL ERROR: Output is not finite on axis {}.\n'.format(i)
print msg
- npw.fancy_print(output[i],
+ npw.fancy_print(output[i],
replace_values={(lambda a: npw.isfinite(a)): '.'})
raise RuntimeError(msg)
di = npw.abs(reference[i] - output[i])
@@ -269,7 +269,8 @@ class TestDiffusionOperator(object):
def test_diffusion_2D_inplace(self):
self._test(dim=2, is_inplace=True)
def test_diffusion_3D_inplace(self):
- self._test(dim=3, is_inplace=True)
+ if __ENABLE_LONG_TESTS__:
+ self._test(dim=3, is_inplace=True)
def perform_tests(self):
self.test_diffusion_1D_inplace()
diff --git a/hysop/operator/tests/test_directional_advection.py b/hysop/operator/tests/test_directional_advection.py
index 9463d3745899f5668bdcf916e8a5a3e58d0d7449..05e81ccff195130237328d68888f2b34d5cd4271 100644
--- a/hysop/operator/tests/test_directional_advection.py
+++ b/hysop/operator/tests/test_directional_advection.py
@@ -124,14 +124,14 @@ class TestDirectionalAdvectionOperator(object):
implementations = [ref_impl] + implementations
method = {TimeIntegrator: time_integrator, Remesh: remesh_kernel}
-
+
def iter_impl(impl):
base_kwds = dict(velocity=vin, advected_fields=sin, advected_fields_out=sout, dt=dt,
- velocity_cfl=velocity_cfl, variables=variables, implementation=impl,
+ velocity_cfl=velocity_cfl, variables=variables, implementation=impl,
method=method, name='advection_{}'.format(str(impl).lower()))
da = DirectionalAdvection(**base_kwds)
if impl is Implementation.PYTHON:
- split = StrangSplitting(splitting_dim=dim,
+ split = StrangSplitting(splitting_dim=dim,
order=StrangOrder.STRANG_SECOND_ORDER)
split.push_operators(da)
force_tstate = ForceTopologyState(fields=variables.keys(),
@@ -142,9 +142,9 @@ class TestDirectionalAdvectionOperator(object):
yield 'default', graph
elif impl is Implementation.OPENCL:
for cl_env in iter_clenv():
- msg='platform {}, device {}'.format(cl_env.platform.name.strip(),
+ msg='platform {}, device {}'.format(cl_env.platform.name.strip(),
cl_env.device.name.strip())
- split = StrangSplitting(splitting_dim=dim,
+ split = StrangSplitting(splitting_dim=dim,
extra_kwds=dict(cl_env=cl_env),
order=StrangOrder.STRANG_SECOND_ORDER)
split.push_operators(da)
@@ -178,7 +178,7 @@ class TestDirectionalAdvectionOperator(object):
#print 'SWITCHING TO AXES {}'.format(axes)
ref_outputs = reference_fields.setdefault(axes, {})
napplies = 10
- Vi = npw.asarray([+1.0 if (i in axes) else +0.0
+ Vi = npw.asarray([+1.0 if (i in axes) else +0.0
for i in xrange(dim)], dtype=dtype)
dvin = graph.get_input_discrete_field(vin)
@@ -225,7 +225,7 @@ class TestDirectionalAdvectionOperator(object):
print 'DSREF - DSOUT'
for (output, ref) in zip(dsout, dsref):
print (output.sdata[output.compute_slices].get() - ref.sdata[ref.compute_slices].get())
- msg='Test failed with V={}, k={}, dxk={}, inter-field L2 distances are {}.'
+ msg='Test failed with V={}, k={}, dxk={}, inter-field L2 distances are {}.'
msg=msg.format(Vi, k, to_tuple(dxk, cast=float), to_tuple(d, cast=float))
raise RuntimeError(msg)
ref_outputs[k] = output
@@ -272,25 +272,25 @@ class TestDirectionalAdvectionOperator(object):
sys.stdout.flush()
raise
- def test_advec_1D_out_of_place(self):
- self._test(dim=1, is_inplace=False)
- def test_advec_2D_out_of_place(self):
- self._test(dim=2, is_inplace=False)
- def test_advec_3D_out_of_place(self):
- self._test(dim=3, is_inplace=False)
-
+ # def test_advec_1D_out_of_place(self):
+ # self._test(dim=1, is_inplace=False)
+ # def test_advec_2D_out_of_place(self):
+ # self._test(dim=2, is_inplace=False)
+ # def test_advec_3D_out_of_place(self):
+ # self._test(dim=3, is_inplace=False)
+
def test_advec_1D_inplace(self):
self._test(dim=1, is_inplace=True)
def test_advec_2D_inplace(self):
self._test(dim=2, is_inplace=True)
def test_advec_3D_inplace(self):
self._test(dim=3, is_inplace=True)
-
+
def perform_tests(self):
self.test_advec_1D_inplace()
self.test_advec_2D_inplace()
self.test_advec_3D_inplace()
-
+
#self.test_advec_1D_out_of_place()
#self.test_advec_2D_out_of_place()
#self.test_advec_3D_out_of_place()
diff --git a/hysop/operator/tests/test_directional_diffusion.py b/hysop/operator/tests/test_directional_diffusion.py
index 9d70d201c3c636e90371e5530616237684794585..4949daad99774bbfb3261ceb694c8b2828041bcb 100644
--- a/hysop/operator/tests/test_directional_diffusion.py
+++ b/hysop/operator/tests/test_directional_diffusion.py
@@ -152,10 +152,10 @@ class TestDirectionalDiffusionOperator(object):
if (not is_inplace):
split.push_copy(dst=fin, src=fout)
split = split.build()
-
+
dfin = split.get_input_discrete_field(fin)
dfout = split.get_output_discrete_field(fout)
-
+
view = dfin.compute_slices
reference = None
@@ -170,15 +170,15 @@ class TestDirectionalDiffusionOperator(object):
if not npw.all(npw.isfinite(S0)):
msg='Integral is not finite. Got {}.'.format(S0)
raise RuntimeError(msg)
-
- _input = tuple(dfin.data[i].get().handle.copy()
+
+ _input = tuple(dfin.data[i].get().handle.copy()
for i in xrange(dfin.nb_components))
if (reference is None):
reference = self._compute_reference(fin=dfin, dfin=_input, dt=dt(), dim=dim,
time_integrator=time_integrator, order=order, coeffs=coeffs, view=view)
split.apply()
-
+
output = tuple(dfout.data[i].get().handle.copy()[view]
for i in xrange(dfout.nb_components))
@@ -272,12 +272,12 @@ class TestDirectionalDiffusionOperator(object):
return out
- def test_diffusion_1D_out_of_place(self):
- self._test(dim=1, is_inplace=False)
- def test_diffusion_2D_out_of_place(self):
- self._test(dim=2, is_inplace=False)
- def test_diffusion_3D_out_of_place(self):
- self._test(dim=3, is_inplace=False)
+ # def test_diffusion_1D_out_of_place(self):
+ # self._test(dim=1, is_inplace=False)
+ # def test_diffusion_2D_out_of_place(self):
+ # self._test(dim=2, is_inplace=False)
+ # def test_diffusion_3D_out_of_place(self):
+ # self._test(dim=3, is_inplace=False)
def test_diffusion_1D_inplace(self):
self._test(dim=1, is_inplace=True)
@@ -298,9 +298,9 @@ class TestDirectionalDiffusionOperator(object):
if __name__ == '__main__':
- TestDirectionalDiffusionOperator.setup_class(enable_extra_tests=False,
+ TestDirectionalDiffusionOperator.setup_class(enable_extra_tests=False,
enable_debug_mode=False)
-
+
test = TestDirectionalDiffusionOperator()
enable_pretty_printing()
diff --git a/hysop/operator/tests/test_directional_stretching.py b/hysop/operator/tests/test_directional_stretching.py
index 99f8006e251d9677312a3ee403957621932efb78..326327d3acf0c7ce3945347ea431ee5b211f064e 100644
--- a/hysop/operator/tests/test_directional_stretching.py
+++ b/hysop/operator/tests/test_directional_stretching.py
@@ -119,8 +119,8 @@ class TestDirectionalStretchingOperator(object):
msg='Out of place stretching has not been implemented yet.'
raise NotImplementedError(msg)
- implementations = (Implementation.PYTHON, Implementation.OPENCL)
- # currently we have to different implementations:
+ implementations = (Implementation.PYTHON, Implementation.OPENCL)
+ # currently we have to different implementations:
# DirectionalStretching and StaticDirectionalStretching
method = {TimeIntegrator: time_integrator, SpaceDiscretization: order}
@@ -158,11 +158,11 @@ class TestDirectionalStretchingOperator(object):
if (not is_inplace):
split.push_copy(dst=win, src=wout)
split = split.build()
-
+
dvin = split.get_input_discrete_field(vin)
dwin = split.get_input_discrete_field(win)
dwout = split.get_output_discrete_field(wout)
-
+
sys.stdout.write('.')
sys.stdout.flush()
try:
@@ -170,9 +170,9 @@ class TestDirectionalStretchingOperator(object):
dwin.initialize(self.__random_init)
dvin.initialize(self.__random_init)
- V_input = tuple(df.sdata.get()[df.compute_slices].handle.copy()
+ V_input = tuple(df.sdata.get()[df.compute_slices].handle.copy()
for df in dvin)
- W_input = tuple(df.sdata.get()[df.compute_slices].handle.copy()
+ W_input = tuple(df.sdata.get()[df.compute_slices].handle.copy()
for df in dwin)
V0 = dvin.integrate()
@@ -194,8 +194,8 @@ class TestDirectionalStretchingOperator(object):
dvin.initialize(V_input, only_finite=False)
split.apply(dt=dt)
-
- W_output = tuple(df.sdata.get()[df.compute_slices].handle.copy()
+
+ W_output = tuple(df.sdata.get()[df.compute_slices].handle.copy()
for df in dwout)
V1 = dvin.integrate()
@@ -273,7 +273,7 @@ class TestDirectionalStretchingOperator(object):
wis = tuple('W{}'.format(i) for i in xrange(3))
Xin = dict(zip(wis, Win))
views = { 'W{}'.format(i): Wi.compute_slices for (i,Wi) in enumerate(dwin) }
-
+
ghost_exchanger = dwin.build_ghost_exchanger(data=Win)
for (j, dt_coeff) in zip(directions, dt_coeffs):
@@ -291,7 +291,7 @@ class TestDirectionalStretchingOperator(object):
D1_VW = ()
for (i,Vi) in enumerate(V):
ghosts = [0,]*3
- ghosts[2-j] = dvin.ghosts[-1]
+ ghosts[2-j] = dvin.ghosts[-1]
a=Vi*W[j]
d1_vw = D1(a=a, axis=ndir, symbols={D1.dx:dwin.space_step[ndir]})
D1_VW += (d1_vw,)
@@ -340,23 +340,23 @@ class TestDirectionalStretchingOperator(object):
def test_stretching_3D_inplace_conservative(self):
self._test(formulation=StretchingFormulation.CONSERVATIVE, is_inplace=True)
- def test_stretching_3D_inplace_gradU_W(self):
- self._test(formulation=StretchingFormulation.GRAD_UW, is_inplace=True)
- def test_stretching_3D_inplace_gradU_T_W(self):
- self._test(formulation=StretchingFormulation.GRAD_UW_T, is_inplace=True)
- def test_stretching_3D_inplace_mixed_gradient(self):
- As = (None, sm.Rational(1,3))
- self._test(formulation=StretchingFormulation.MIXED_GRAD_UW, is_inplace=True, As=As)
-
- def test_stretching_3D_out_of_place_conservative(self):
- self._test(formulation=StretchingFormulation.CONSERVATIVE, is_inplace=False)
- def test_stretching_3D_out_of_place_gradU_W(self):
- self._test(formulation=StretchingFormulation.GRAD_UW, is_inplace=False)
- def test_stretching_3D_out_of_place_gradU_T_W(self):
- self._test(formulation=StretchingFormulation.GRAD_UW_T, is_inplace=False)
- def test_stretching_3D_out_of_place_mixed_gradient(self):
- As = (None, sm.Rational(1,3))
- self._test(formulation=StretchingFormulation.MIXED_GRAD_UW, is_inplace=False, As=As)
+ # def test_stretching_3D_inplace_gradU_W(self):
+ # self._test(formulation=StretchingFormulation.GRAD_UW, is_inplace=True)
+ # def test_stretching_3D_inplace_gradU_T_W(self):
+ # self._test(formulation=StretchingFormulation.GRAD_UW_T, is_inplace=True)
+ # def test_stretching_3D_inplace_mixed_gradient(self):
+ # As = (None, sm.Rational(1,3))
+ # self._test(formulation=StretchingFormulation.MIXED_GRAD_UW, is_inplace=True, As=As)
+
+ # def test_stretching_3D_out_of_place_conservative(self):
+ # self._test(formulation=StretchingFormulation.CONSERVATIVE, is_inplace=False)
+ # def test_stretching_3D_out_of_place_gradU_W(self):
+ # self._test(formulation=StretchingFormulation.GRAD_UW, is_inplace=False)
+ # def test_stretching_3D_out_of_place_gradU_T_W(self):
+ # self._test(formulation=StretchingFormulation.GRAD_UW_T, is_inplace=False)
+ # def test_stretching_3D_out_of_place_mixed_gradient(self):
+ # As = (None, sm.Rational(1,3))
+ # self._test(formulation=StretchingFormulation.MIXED_GRAD_UW, is_inplace=False, As=As)
def perform_tests(self):
# self.test_stretching_3D_inplace_gradU_W()
diff --git a/hysop/operator/tests/test_fd_derivative.py b/hysop/operator/tests/test_fd_derivative.py
index 334f8bed9b79800878d7b2c700bdd2d5f317d1bf..6bca7fbe37e20fb9af0b529a08e95b6cfccf175a 100644
--- a/hysop/operator/tests/test_fd_derivative.py
+++ b/hysop/operator/tests/test_fd_derivative.py
@@ -25,22 +25,22 @@ from hysop import Field, Box
class TestFiniteDifferencesDerivative(object):
@classmethod
- def setup_class(cls,
+ def setup_class(cls,
enable_extra_tests=__ENABLE_LONG_TESTS__,
enable_debug_mode=False):
IO.set_default_path('/tmp/hysop_tests/test_fd_derivative')
-
+
cls.size_min = 23
cls.size_max = 35
-
+
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
cls.t = ScalarParameter(name='t', dtype=HYSOP_REAL)
-
+
cls.build_analytic_expressions()
-
+
@classmethod
def build_analytic_expressions(cls):
from hysop.tools.sympy_utils import enable_pretty_printing
@@ -48,7 +48,7 @@ class TestFiniteDifferencesDerivative(object):
from hysop.symbolic.frame import SymbolicFrame
from hysop.symbolic.field import curl, laplacian
enable_pretty_printing()
-
+
#at this moment we just test a periodic solver
analytic_expressions = {}
analytic_functions = {}
@@ -59,7 +59,7 @@ class TestFiniteDifferencesDerivative(object):
def gen_Fi():
kis = tuple(random.randint(1,5)*2*sm.pi for _ in xrange(dim))
qis = tuple(npw.random.rand(dim).round(decimals=3).tolist())
- basis = tuple( (sm.cos(ki*xi+qi), sm.sin(ki*xi+qi))
+ basis = tuple( (sm.cos(ki*xi+qi), sm.sin(ki*xi+qi))
for (ki,qi,xi) in zip(kis, qis, coords) )
F0 = sm.Integer(1) / (sm.Integer(1) + npw.random.randint(1,5)*cls.t.s)
for i in xrange(dim):
@@ -69,18 +69,18 @@ class TestFiniteDifferencesDerivative(object):
def gen_F():
F = npw.round(random.random(),2)*gen_Fi() - npw.round(random.random(),2)*gen_Fi()
return F
-
+
params = coords + (cls.t.s,)
Fs = npw.asarray([gen_F(), gen_F(), gen_F()], dtype=object).view(TensorBase)
fFs = tuple(sm.lambdify(params, F) for F in Fs)
-
+
dFs = npw.empty(shape=(3, dim), dtype=object)
fdFs = npw.empty_like(dFs)
for (i, Fi) in enumerate(Fs):
for (j, xj) in enumerate(coords):
dFij = Fi.diff(xj)
dFs[i,j] = dFij
- fdFs[i,j] = sm.lambdify(params, dFij)
+ fdFs[i,j] = sm.lambdify(params, dFij)
analytic_expressions[dim] = {'F':Fs, 'gradF':dFs}
analytic_functions[dim] = {'F':fFs, 'gradF':fdFs}
@@ -116,17 +116,17 @@ class TestFiniteDifferencesDerivative(object):
size_max = first_not_None(size_max, self.size_max)
shape = tuple(npw.random.randint(low=size_min, high=size_max+1, size=dim).tolist())
-
+
domain = Box(length=(1,)*dim)
F = Field(domain=domain, name='F', dtype=dtype,
nb_components=3, register_object=False)
gradF = F.gradient(register_object=False)
-
- self._test_one(shape=shape, dim=dim, dtype=dtype,
+
+ self._test_one(shape=shape, dim=dim, dtype=dtype,
domain=domain, F=F, gradF=gradF)
-
- def _test_one(self, shape, dim, dtype,
+
+ def _test_one(self, shape, dim, dtype,
domain, F, gradF):
print '\nTesting {}D Gradient: dtype={} shape={}'.format(
@@ -139,15 +139,15 @@ class TestFiniteDifferencesDerivative(object):
for (i,j) in npw.ndindex(*self.analytic_expressions[dim]['gradF'].shape):
dFij = self.analytic_expressions[dim]['gradF'][i,j]
print ' *{p}F{}/{p}x{}(x,t) = {}'.format(subscript(i).encode('utf-8'),
- subscript(j).encode('utf-8'),
- dFij,
+ subscript(j).encode('utf-8'),
+ dFij,
p=partial.encode('utf-8'))
self.t.value = random.random()
print ' >Parameter t has been set to {}.'.format(self.t())
print ' >Testing all implementations:'
implementations = FiniteDifferencesSpaceDerivative.implementations()
-
+
variables = { F:shape, gradF: shape }
fns = self.analytic_functions[dim]['F']
dfns = tuple(self.analytic_functions[dim]['gradF'].ravel().tolist())
@@ -156,7 +156,7 @@ class TestFiniteDifferencesDerivative(object):
def iter_impl(impl):
base_kwds = dict(F=F, gradF=gradF, variables=variables,
- implementation=impl,
+ implementation=impl,
method={SpaceDiscretization: 8})
if impl is Implementation.PYTHON:
msg=' *Python: '
@@ -168,12 +168,12 @@ class TestFiniteDifferencesDerivative(object):
msg=' *Opencl: '
print msg
for cl_env in iter_clenv():
- msg=' >platform {}, device {}:'.format(cl_env.platform.name.strip(),
+ msg=' >platform {}, device {}:'.format(cl_env.platform.name.strip(),
cl_env.device.name.strip())
print msg,
op0 = Gradient(cl_env=cl_env, **base_kwds)
op1 = ForceTopologyState(fields=gradF, variables={gradF: shape},
- backend=Backend.OPENCL,
+ backend=Backend.OPENCL,
extra_kwds={'cl_env':cl_env})
op = op0.to_graph()
op.push_nodes(op1)
@@ -183,8 +183,8 @@ class TestFiniteDifferencesDerivative(object):
else:
msg='Unknown implementation to test {}.'.format(impl)
raise NotImplementedError(msg)
-
-
+
+
# Compare to analytic solution
Fref = None
for impl in implementations:
@@ -204,12 +204,12 @@ class TestFiniteDifferencesDerivative(object):
dgradF.initialize(self.__random_init)
op.apply()
-
+
Fout = tuple( data.get().handle.copy() for data in dF.data )
gradFout = tuple( data.get().handle.copy() for data in dgradF.data )
-
+
self._check_output(impl, op, Fref, gradFref, Fout, gradFout)
-
+
@classmethod
def _check_output(cls, impl, op, Fref, gradFref, Fout, gradFout):
check_instance(Fref, tuple, values=npw.ndarray)
@@ -222,7 +222,7 @@ class TestFiniteDifferencesDerivative(object):
iname = '{}{}'.format(name,i)
assert fout.dtype == fref.dtype, iname
assert fout.shape == fref.shape, iname
-
+
eps = npw.finfo(fout.dtype).eps
dist = npw.abs(fout-fref)
dL1 = npw.nansum(dist) / dist.size
@@ -231,7 +231,7 @@ class TestFiniteDifferencesDerivative(object):
continue
has_nan = npw.any(npw.isnan(fout))
has_inf = npw.any(npw.isinf(fout))
-
+
print
print
print 'Test output comparisson for {} failed for component {}:'.format(name, i)
@@ -265,9 +265,9 @@ class TestFiniteDifferencesDerivative(object):
print w
print
print
-
+
msg = 'Test failed for {} on component {} for implementation {}.'.format(name, i, impl)
- raise RuntimeError(msg)
+ raise RuntimeError(msg)
@@ -297,15 +297,15 @@ class TestFiniteDifferencesDerivative(object):
self.test_2d_float64()
if __ENABLE_LONG_TESTS__:
self.test_3d_float64()
-
+
if __name__ == '__main__':
- TestFiniteDifferencesDerivative.setup_class(enable_extra_tests=False,
+ TestFiniteDifferencesDerivative.setup_class(enable_extra_tests=False,
enable_debug_mode=False)
-
+
test = TestFiniteDifferencesDerivative()
- with printoptions(threshold=10000, linewidth=1000,
- nanstr='nan', infstr='inf',
+ with printoptions(threshold=10000, linewidth=1000,
+ nanstr='nan', infstr='inf',
formatter={'float': lambda x: '{:>6.2f}'.format(x)}):
test.perform_tests()
diff --git a/hysop/operator/tests/test_poisson.py b/hysop/operator/tests/test_poisson.py
index d4cf58ea095dc926c07c905c3fc2d392fb5ebc41..c874a5e5b4ebf6f9fbe9fa18ceef4876aafec785 100644
--- a/hysop/operator/tests/test_poisson.py
+++ b/hysop/operator/tests/test_poisson.py
@@ -30,7 +30,7 @@ class TestPoissonOperator(object):
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
from hysop.tools.sympy_utils import enable_pretty_printing
enable_pretty_printing()
@@ -39,23 +39,23 @@ class TestPoissonOperator(object):
pass
@classmethod
- def build_analytic_solutions(cls, polynomial,
+ def build_analytic_solutions(cls, polynomial,
dim, nb_components,
lboundaries, rboundaries,
origin, end):
from hysop.symbolic.base import TensorBase
from hysop.symbolic.frame import SymbolicFrame
from hysop.symbolic.field import laplacian
-
+
frame = SymbolicFrame(dim=dim)
coords = frame.coords
-
+
def gen_psi():
psis = ()
for i in xrange(nb_components):
if polynomial:
psi, y = make_multivariate_polynomial(origin, end,
- lboundaries, rboundaries,
+ lboundaries, rboundaries,
10, 4)
else:
psi, y = make_multivariate_trigonometric_polynomial(origin, end,
@@ -109,7 +109,7 @@ class TestPoissonOperator(object):
shape = tuple(npw.random.randint(low=size_min, high=size_max+1, size=dim).tolist())
for Si in shape:
factors.update( set(primefac.primefac(int(Si))) )
-
+
domain_boundaries = list(domain_boundary_iterator(dim=dim))
periodic = domain_boundaries[0]
domain_boundaries = domain_boundaries[1:]
@@ -127,7 +127,7 @@ class TestPoissonOperator(object):
W = Field(domain=domain, name='W', dtype=dtype,
nb_components=nb_components, register_object=False)
- self._test_one(shape=shape, dim=dim, dtype=dtype,
+ self._test_one(shape=shape, dim=dim, dtype=dtype,
domain=domain, Psi=Psi, W=W,
polynomial=polynomial, nb_components=nb_components)
if (max_runs is not None) and (i==max_runs):
@@ -147,15 +147,15 @@ class TestPoissonOperator(object):
def _test_one(self, shape, dim, dtype,
domain, Psi, W, polynomial, nb_components):
-
+
(analytic_expressions, analytic_functions) = \
self.build_analytic_solutions(
- dim=dim, nb_components=nb_components, polynomial=polynomial,
+ dim=dim, nb_components=nb_components, polynomial=polynomial,
lboundaries=W.lboundaries[::-1], # => boundaries in variable order x0,...,xn
rboundaries=W.rboundaries[::-1],
origin=domain.origin[::-1],
end=domain.end[::-1])
-
+
def format_expr(e):
return truncate_expr(round_expr(e, 3), 80)
@@ -341,13 +341,13 @@ class TestPoissonOperator(object):
self._test(dim=3, dtype=npw.float64, **kwds)
def test_4d_float64(self, **kwds):
self._test(dim=4, dtype=npw.float64, **kwds)
-
- def test_polynomial_1d_float32(self, **kwds):
- self._test(dim=1, dtype=npw.float32, polynomial=True, **kwds)
- def test_polynomial_2d_float32(self, **kwds):
- self._test(dim=2, dtype=npw.float32, polynomial=True, **kwds)
- def test_polynomial_3d_float32(self, **kwds):
- self._test(dim=3, dtype=npw.float32, polynomial=True, **kwds)
+
+ # def test_polynomial_1d_float32(self, **kwds):
+ # self._test(dim=1, dtype=npw.float32, polynomial=True, **kwds)
+ # def test_polynomial_2d_float32(self, **kwds):
+ # self._test(dim=2, dtype=npw.float32, polynomial=True, **kwds)
+ # def test_polynomial_3d_float32(self, **kwds):
+ # self._test(dim=3, dtype=npw.float32, polynomial=True, **kwds)
def perform_tests(self):
diff --git a/hysop/operator/tests/test_poisson_curl.py b/hysop/operator/tests/test_poisson_curl.py
index 33e779441918ce96aa44add9969a752c5ef8bb09..82d7bdd3de2bdee6dc3949c98cb527056dbcbb44 100644
--- a/hysop/operator/tests/test_poisson_curl.py
+++ b/hysop/operator/tests/test_poisson_curl.py
@@ -33,17 +33,17 @@ class TestPoissonCurlOperator(object):
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
from hysop.tools.sympy_utils import enable_pretty_printing
enable_pretty_printing()
-
+
@classmethod
def teardown_class(cls):
pass
@classmethod
- def build_analytic_solutions(cls, polynomial,
+ def build_analytic_solutions(cls, polynomial,
dim, nb_components,
lboundaries, rboundaries,
origin, end):
@@ -53,7 +53,7 @@ class TestPoissonCurlOperator(object):
assert len(lboundaries)==nb_components
assert len(rboundaries)==nb_components
-
+
frame = SymbolicFrame(dim=dim)
coords = frame.coords
def gen_psi():
@@ -61,7 +61,7 @@ class TestPoissonCurlOperator(object):
for i in xrange(nb_components):
if polynomial:
psi, y = make_multivariate_polynomial(origin, end,
- lboundaries[i], rboundaries[i],
+ lboundaries[i], rboundaries[i],
10, 4)
else:
psi, y = make_multivariate_trigonometric_polynomial(origin, end,
@@ -69,7 +69,7 @@ class TestPoissonCurlOperator(object):
psi = psi.xreplace({yi: xi for (yi,xi) in zip(y, coords)})
psis += (psi,)
return npw.asarray(psis).view(TensorBase)
-
+
Psis = gen_psi()
Ws = npw.atleast_1d(-laplacian(Psis, frame))
Us = curl(Psis, frame)
@@ -82,7 +82,7 @@ class TestPoissonCurlOperator(object):
analytic_functions = {'Psi':fPsis, 'W':fWs, 'U':fUs}
return (analytic_expressions, analytic_functions)
-
+
@staticmethod
def __random_init(data, coords, dtype):
for d in data:
@@ -91,7 +91,7 @@ class TestPoissonCurlOperator(object):
else:
msg = 'Unknown dtype {}.'.format(d.dtype)
raise NotImplementedError(msg)
-
+
@staticmethod
def __analytic_init(data, coords, dtype, fns):
assert len(fns) == len(data)
@@ -115,7 +115,7 @@ class TestPoissonCurlOperator(object):
shape = tuple(npw.random.randint(low=size_min, high=size_max+1, size=dim).tolist())
for Si in shape:
factors.update( set(primefac.primefac(int(Si))) )
-
+
domain_boundaries = list(domain_boundary_iterator(dim=dim))
periodic = domain_boundaries[0]
domain_boundaries = domain_boundaries[1:]
@@ -130,7 +130,7 @@ class TestPoissonCurlOperator(object):
U = VelocityField(domain=domain, dtype=dtype)
W = VorticityField(velocity=U, dtype=dtype)
- self._test_one(shape=shape, dim=dim, dtype=dtype,
+ self._test_one(shape=shape, dim=dim, dtype=dtype,
domain=domain, W=W, U=U, polynomial=polynomial)
if (max_runs is not None) and (i==max_runs):
missing = ((4**(dim+1) - 1) / 3) - i
@@ -148,15 +148,15 @@ class TestPoissonCurlOperator(object):
def _test_one(self, shape, dim, dtype,
domain, U, W, polynomial):
-
+
(analytic_expressions, analytic_functions) = \
self.build_analytic_solutions(
- dim=dim, nb_components=W.nb_components, polynomial=polynomial,
+ dim=dim, nb_components=W.nb_components, polynomial=polynomial,
lboundaries=[Wi.lboundaries[::-1] for Wi in W.fields], # => boundaries in variable order x0,...,xn
rboundaries=[Wi.rboundaries[::-1] for Wi in W.fields],
origin=domain.origin[::-1],
end=domain.end[::-1])
-
+
def format_expr(e):
return truncate_expr(round_expr(e, 3), 80)
@@ -221,10 +221,10 @@ class TestPoissonCurlOperator(object):
name='{}_{}'.format(impl, i)
op = op.build()
-
+
dw = op.get_input_discrete_field(W).as_contiguous_dfield()
du = op.get_output_discrete_field(U).as_contiguous_dfield()
-
+
dw.initialize(self.__analytic_init, dtype=dtype,
fns=analytic_functions['W'])
diff --git a/hysop/operator/tests/test_scales_advection.py b/hysop/operator/tests/test_scales_advection.py
index 77672ac4354ddddbf653c06a3a981618c4a43d48..3b69adde2a16a9de2a0f3087bd300ac9f18a7b19 100644
--- a/hysop/operator/tests/test_scales_advection.py
+++ b/hysop/operator/tests/test_scales_advection.py
@@ -169,7 +169,7 @@ class TestScalesAdvectionOperator(object):
#print 'SWITCHING TO AXES {}'.format(axes)
ref_outputs = reference_fields.setdefault(axes, {})
napplies = 10
- Vi = npw.asarray([+1.0 if (i in axes) else +0.0
+ Vi = npw.asarray([+1.0 if (i in axes) else +0.0
for i in xrange(dim)], dtype=dtype)
dvin = graph.get_input_discrete_field(vin).as_contiguous_dfield()
@@ -213,7 +213,7 @@ class TestScalesAdvectionOperator(object):
print dsref.sdata[dsref.compute_slices]
print 'DSREF - DSOUT'
print (dsout.sdata[dsout.compute_slices].get() - dsref.sdata[dsref.compute_slices].get())
- msg='Test failed with V={}, k={}, dxk={}, inter-field L2 distances are {}.'
+ msg='Test failed with V={}, k={}, dxk={}, inter-field L2 distances are {}.'
msg=msg.format(Vi, k, to_tuple(dxk, cast=float), to_tuple(d, cast=float))
raise RuntimeError(msg)
ref_outputs[k] = output
@@ -265,6 +265,9 @@ class TestScalesAdvectionOperator(object):
self._test(dim=3, is_inplace=True)
print
+ def test_3D(self):
+ self._test(dim=3, is_inplace=True)
+
if __name__ == '__main__':
import hysop
diff --git a/hysop/operator/tests/test_solenoidal_projection.py b/hysop/operator/tests/test_solenoidal_projection.py
index 49da261b081919cedf36884e4f156c74a8ec1664..234a1e8459a7459b8b8fa9b201627ab092d3930c 100644
--- a/hysop/operator/tests/test_solenoidal_projection.py
+++ b/hysop/operator/tests/test_solenoidal_projection.py
@@ -1,4 +1,3 @@
-
import random, primefac, scipy
from hysop.deps import it, sm, random, np
from hysop.constants import HYSOP_REAL, Implementation, BoxBoundaryCondition
@@ -20,18 +19,18 @@ from hysop import Field, Box
class TestSolenoidalProjectionOperator(object):
@classmethod
- def setup_class(cls,
+ def setup_class(cls,
enable_extra_tests=__ENABLE_LONG_TESTS__,
enable_debug_mode=False):
IO.set_default_path('/tmp/hysop_tests/test_solenoidal_projection')
-
+
cls.size_min = 8
cls.size_max = 16
-
+
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
from hysop.tools.sympy_utils import enable_pretty_printing
enable_pretty_printing()
@@ -43,17 +42,17 @@ class TestSolenoidalProjectionOperator(object):
assert len(lboundaries)==4
assert len(rboundaries)==4
-
+
frame = SymbolicFrame(dim=3)
coords = frame.coords
-
+
def gen_fn(nb_components, left_boundaries, right_boundaries):
assert len(left_boundaries)==len(right_boundaries)==nb_components
fns = ()
for i in xrange(nb_components):
if polynomial:
fn, y = make_multivariate_polynomial(origin, end,
- left_boundaries[i], right_boundaries[i],
+ left_boundaries[i], right_boundaries[i],
10, 2)
else:
fn, y = make_multivariate_trigonometric_polynomial(origin, end,
@@ -64,11 +63,11 @@ class TestSolenoidalProjectionOperator(object):
analytic_solutions = {}
analytic_functions = {}
-
- psis = gen_fn(nb_components=3,
+
+ psis = gen_fn(nb_components=3,
left_boundaries=lboundaries[:3],
right_boundaries=rboundaries[:3])
- phis = gen_fn(nb_components=1,
+ phis = gen_fn(nb_components=1,
left_boundaries=lboundaries[3:],
right_boundaries=rboundaries[3:])
@@ -85,7 +84,7 @@ class TestSolenoidalProjectionOperator(object):
fUs = tuple(sm.lambdify(coords, Ui) for Ui in Us)
fdivUs = tuple(sm.lambdify(coords, Ui) for Ui in divUs)
- sols = {'U0s': U0s, 'U1s': U1s, 'Us':Us,
+ sols = {'U0s': U0s, 'U1s': U1s, 'Us':Us,
'divUs':divUs, 'divU0s':divU0s, 'divU1s':divU1s}
lambdified_sols = {'U0s': fU0s, 'U1s': fU1s, 'Us':fUs, 'divUs':fdivUs}
@@ -98,14 +97,14 @@ class TestSolenoidalProjectionOperator(object):
def teardown_class(cls):
pass
-
+
def _test(self, dtype, max_runs=5,
polynomial=False, size_min=None, size_max=None):
enable_extra_tests = self.enable_extra_tests
size_min = first_not_None(size_min, self.size_min)
size_max = first_not_None(size_max, self.size_max)
-
+
dim = 3
valid_factors = {2,3,5,7,11,13}
factors = {1}
@@ -114,19 +113,19 @@ class TestSolenoidalProjectionOperator(object):
shape = tuple(npw.random.randint(low=size_min, high=size_max+1, size=dim).tolist())
for Si in shape:
factors.update( set(primefac.primefac(int(Si))) )
-
+
domain_boundaries = list(domain_boundary_iterator(dim=dim))
periodic = domain_boundaries[0]
domain_boundaries = domain_boundaries[1:]
random.shuffle(domain_boundaries)
domain_boundaries.insert(0, periodic)
-
+
for i, (lboundaries, rboundaries) in enumerate(domain_boundaries, 1):
domain = Box(origin=(npw.random.rand(dim)-0.5),
length=(0.5+npw.random.rand(dim))*2*npw.pi,
lboundaries=lboundaries,
rboundaries=rboundaries)
-
+
U = VelocityField(domain=domain, name='U', dtype=dtype)
U0 = VelocityField(domain=domain, name='U0', dtype=dtype)
U1 = VelocityField(domain=domain, name='U1', dtype=dtype)
@@ -156,12 +155,12 @@ class TestSolenoidalProjectionOperator(object):
assert len(fns) == len(data)
for (d,fn,coord) in zip(data,fns,coords):
d[...] = npw.asarray(fn(*coord)).astype(dtype)
-
+
@classmethod
def __zero_init(cls, data, coords, dtype):
for d in data:
d[...] = 0
-
+
@staticmethod
def __random_init(data, coords, dtype):
shape = data[0].shape
@@ -174,36 +173,36 @@ class TestSolenoidalProjectionOperator(object):
def _test_one(self, shape, dtype, polynomial,
domain, U, U0, U1, divU, divU0, divU1):
-
+
print '\nTesting {}D SolenoidalProjection: dtype={} shape={}, polynomial={}, bc=[{}]'.format(
3, dtype.__name__, shape, polynomial, domain.format_boundaries())
print ' >Building U = U0 + U1 = curl(Psi) + grad(Phi)...'
-
+
# U = curl(Psi) + grad(Phi)
Psi = VorticityField(velocity=U, name='Psi')
assert all(all(psic.lboundaries == u.lboundaries) for (psic,u) in zip(Psi.curl().fields, U.fields))
assert all(all(psic.rboundaries == u.rboundaries) for (psic,u) in zip(Psi.curl().fields, U.fields))
-
+
Phi = U.div(name='Phi')
assert all(all(phig.lboundaries == u.lboundaries) for (phig,u) in zip(Phi.gradient().fields, U.fields))
assert all(all(phig.rboundaries == u.rboundaries) for (phig,u) in zip(Phi.gradient().fields, U.fields))
-
+
lboundaries = tuple(psi.lboundaries[::-1] for psi in Psi.fields) + (Phi.lboundaries[::-1],)
rboundaries = tuple(psi.rboundaries[::-1] for psi in Psi.fields) + (Phi.rboundaries[::-1],)
(analytic_solutions, analytic_functions) = \
self.build_analytic_solutions(
- polynomial=polynomial,
+ polynomial=polynomial,
lboundaries=lboundaries, # => boundaries in variable order x0,...,xn
rboundaries=rboundaries,
origin=domain.origin[::-1],
end=domain.end[::-1])
-
+
del Psi
del Phi
del lboundaries
del rboundaries
-
+
def format_expr(e):
return truncate_expr(round_expr(e, 3), 80)
@@ -222,14 +221,14 @@ class TestSolenoidalProjectionOperator(object):
print ' >Testing all available implementations:'
implementations = SolenoidalProjection.implementations()
-
+
# Compute reference solution
variables = { U:shape, divU: shape, U0:shape, divU0:shape}
def iter_impl(impl):
base_kwds = dict(input_field=U, input_field_div=divU,
output_field=U0, output_field_div=divU0,
- variables=variables, implementation=impl,
+ variables=variables, implementation=impl,
name='projection_{}'.format(str(impl).lower()))
if impl is Implementation.PYTHON:
msg=' *Python FFTW: '
@@ -239,7 +238,7 @@ class TestSolenoidalProjectionOperator(object):
msg=' *OpenCl CLFFT: '
print msg
for cl_env in iter_clenv():
- msg=' |platform {}, device {}'.format(cl_env.platform.name.strip(),
+ msg=' |platform {}, device {}'.format(cl_env.platform.name.strip(),
cl_env.device.name.strip())
print msg,
yield SolenoidalProjection(cl_env=cl_env, **base_kwds)
@@ -255,7 +254,7 @@ class TestSolenoidalProjectionOperator(object):
else:
msg='Unknown implementation to test {}.'.format(impl)
raise NotImplementedError(msg)
-
+
# Compare to analytic solution
Uref, U0ref = None, None
for impl in implementations:
@@ -266,14 +265,14 @@ class TestSolenoidalProjectionOperator(object):
du0 = op.get_output_discrete_field(U0)
du_div = op.get_output_discrete_field(divU)
du0_div = op.get_output_discrete_field(divU0)
-
- du.initialize(self.__analytic_init, dtype=dtype,
+
+ du.initialize(self.__analytic_init, dtype=dtype,
fns=analytic_functions['Us'])
if (Uref is None):
- du0.initialize(self.__analytic_init, dtype=dtype,
+ du0.initialize(self.__analytic_init, dtype=dtype,
fns=analytic_functions['U0s'])
- du_div.initialize(self.__analytic_init, dtype=dtype,
+ du_div.initialize(self.__analytic_init, dtype=dtype,
fns=analytic_functions['divUs'])
du0_div.initialize(self.__zero_init, dtype=dtype)
Uref = tuple( data.get().handle.copy() for data in du.data )
@@ -284,9 +283,9 @@ class TestSolenoidalProjectionOperator(object):
du0.initialize(self.__random_init, dtype=dtype)
du_div.initialize(self.__random_init, dtype=dtype)
du0_div.initialize(self.__random_init, dtype=dtype)
-
+
op.apply(simulation=None)
-
+
Uout = tuple( data.get().handle.copy() for data in du.data )
U0out = tuple( data.get().handle.copy() for data in du0.data )
divUout = tuple( data.get().handle.copy() for data in du_div.data )
@@ -297,13 +296,13 @@ class TestSolenoidalProjectionOperator(object):
npw.sqrt(npw.sum(divUout[0]**2)*s),
npw.sqrt(npw.sum(divU0out[0]**2)*s)),
- self._check_output(impl, op, Uref, divUref, U0ref, divU0ref,
+ self._check_output(impl, op, Uref, divUref, U0ref, divU0ref,
Uout, divUout, U0out, divU0out)
print
-
+
@classmethod
- def _check_output(cls, impl, op,
- Uref, divUref, U0ref, divU0ref,
+ def _check_output(cls, impl, op,
+ Uref, divUref, U0ref, divU0ref,
Uout, divUout, U0out, divU0out):
check_instance(Uref, tuple, values=npw.ndarray, size=3)
check_instance(U0ref, tuple, values=npw.ndarray, size=3)
@@ -328,16 +327,16 @@ class TestSolenoidalProjectionOperator(object):
print
msg = msg0.format(iname)
raise ValueError(msg)
-
- for (out_buffers, ref_buffers, name) in zip((Uout, U0out, divUout, divU0out),
- (Uref, U0ref, divUref, divU0ref),
+
+ for (out_buffers, ref_buffers, name) in zip((Uout, U0out, divUout, divU0out),
+ (Uref, U0ref, divUref, divU0ref),
('U', 'U0', 'divU', 'divU0')):
print '| {}=('.format(name),
for i, (fout,fref) in enumerate(zip(out_buffers, ref_buffers)):
iname = '{}{}'.format(name,i)
assert fout.dtype == fref.dtype, iname
assert fout.shape == fref.shape, iname
-
+
eps = npw.finfo(fout.dtype).eps
dist = npw.abs(fout-fref)
dinf = npw.max(dist)
@@ -385,10 +384,10 @@ class TestSolenoidalProjectionOperator(object):
print
print
print
-
+
msg = 'Test failed for {} on component {} for implementation {}.'
msg = msg.format(name, i, impl)
- raise RuntimeError(msg)
+ raise RuntimeError(msg)
print ')',
@@ -403,15 +402,15 @@ class TestSolenoidalProjectionOperator(object):
self.test_3d_float32(max_runs=max_3d_runs)
if __ENABLE_LONG_TESTS__ or (HYSOP_REAL==npw.float64):
self.test_3d_float64(max_runs=max_3d_runs)
-
+
if __name__ == '__main__':
- TestSolenoidalProjectionOperator.setup_class(enable_extra_tests=False,
+ TestSolenoidalProjectionOperator.setup_class(enable_extra_tests=False,
enable_debug_mode=False)
-
+
test = TestSolenoidalProjectionOperator()
- with printoptions(threshold=10000, linewidth=240,
- nanstr='nan', infstr='inf',
+ with printoptions(threshold=10000, linewidth=240,
+ nanstr='nan', infstr='inf',
formatter={'float': lambda x: '{:>6.2f}'.format(x)}):
test.perform_tests()
diff --git a/hysop/operator/tests/test_spectral_derivative.py b/hysop/operator/tests/test_spectral_derivative.py
index 5702c7f73ec2256b14f911062cc23b97f4a072aa..d5004381ad6c3c985b3c38bb230217fab62d280d 100644
--- a/hysop/operator/tests/test_spectral_derivative.py
+++ b/hysop/operator/tests/test_spectral_derivative.py
@@ -24,20 +24,20 @@ from hysop import Field, Box
class TestSpectralDerivative(object):
@classmethod
- def setup_class(cls,
+ def setup_class(cls,
enable_extra_tests=__ENABLE_LONG_TESTS__,
enable_debug_mode=False):
IO.set_default_path('/tmp/hysop_tests/test_spectral_derivative')
-
+
cls.size_min = 8
cls.size_max = 16
-
+
cls.enable_extra_tests = enable_extra_tests
cls.enable_debug_mode = enable_debug_mode
-
+
cls.t = ScalarParameter(name='t', dtype=HYSOP_REAL)
-
+
@classmethod
def build_analytic_expressions(cls, polynomial, dim, max_derivative,
lboundaries, rboundaries, origin, end):
@@ -46,15 +46,15 @@ class TestSpectralDerivative(object):
from hysop.symbolic.frame import SymbolicFrame
from hysop.symbolic.field import curl, laplacian
enable_pretty_printing()
-
+
frame = SymbolicFrame(dim=dim)
coords = frame.coords
params = coords + (cls.t.s,)
-
+
def gen_F():
if polynomial:
f, y = make_multivariate_polynomial(origin, end,
- lboundaries, rboundaries,
+ lboundaries, rboundaries,
10, 4)
else:
f, y = make_multivariate_trigonometric_polynomial(origin, end,
@@ -65,7 +65,7 @@ class TestSpectralDerivative(object):
F = gen_F()
fF = sm.lambdify(params, F)
-
+
dFs = {}
fdFs = {}
symbolic_dvars = {}
@@ -80,7 +80,7 @@ class TestSpectralDerivative(object):
continue
dF = dF.diff(ci,i)
dFs[idx] = dF
- fdFs[idx] = sm.lambdify(params, dF)
+ fdFs[idx] = sm.lambdify(params, dF)
analytic_expressions = {'F':F, 'dF':dFs}
analytic_functions = {'F':fF, 'dF':fdFs}
@@ -110,18 +110,18 @@ class TestSpectralDerivative(object):
def _test(self, dim, dtype, polynomial, max_derivative=2,
size_min=None, size_max=None, max_runs=None):
enable_extra_tests = self.enable_extra_tests
-
+
size_min = first_not_None(size_min, self.size_min)
size_max = first_not_None(size_max, self.size_max)
shape = tuple(npw.random.randint(low=size_min, high=size_max+1, size=dim).tolist())
-
+
domain_boundaries = list(domain_boundary_iterator(dim=dim))
periodic = domain_boundaries[0]
domain_boundaries = domain_boundaries[1:]
random.shuffle(domain_boundaries)
domain_boundaries.insert(0, periodic)
-
+
for i, (lboundaries, rboundaries) in enumerate(domain_boundaries, 1):
domain = Box(origin=(npw.random.rand(dim)-0.5),
length=(npw.random.rand(dim)+0.5)*2*npw.pi,
@@ -130,11 +130,11 @@ class TestSpectralDerivative(object):
F = Field(domain=domain, name='F', dtype=dtype)
- self._test_one(shape=shape, dim=dim, dtype=dtype,
- domain=domain, F=F,
- polynomial=polynomial,
+ self._test_one(shape=shape, dim=dim, dtype=dtype,
+ domain=domain, F=F,
+ polynomial=polynomial,
max_derivative=max_derivative)
-
+
if (max_runs is not None) and (i==max_runs):
missing = ((4**(dim+1) - 1) / 3) - i
print
@@ -149,24 +149,24 @@ class TestSpectralDerivative(object):
print
print
-
- def _test_one(self, shape, dim, dtype,
+
+ def _test_one(self, shape, dim, dtype,
domain, F, polynomial, max_derivative):
-
+
implementations = SpectralSpaceDerivative.implementations()
(symbolic_dvars, analytic_expressions, analytic_functions) = \
self.build_analytic_expressions(
- dim=dim, polynomial=polynomial,
+ dim=dim, polynomial=polynomial,
max_derivative=max_derivative,
lboundaries=F.lboundaries[::-1], # => boundaries in variable order x0,...,xn
rboundaries=F.rboundaries[::-1],
origin=domain.origin[::-1],
end=domain.end[::-1])
-
+
Fs = analytic_expressions['F']
fFs = analytic_functions['F']
-
+
def format_expr(e):
return truncate_expr(round_expr(e, 3), 80)
@@ -190,11 +190,11 @@ class TestSpectralDerivative(object):
dFs = analytic_expressions['dF'][idx]
fdFs = analytic_functions['dF'][idx]
print ' *{}'.format(dF.pretty_name)
-
+
variables = { F:shape, dF: shape }
-
+
def iter_impl(impl):
- base_kwds = dict(F=F, dF=dF, derivative=idx,
+ base_kwds = dict(F=F, dF=dF, derivative=idx,
variables=variables,
implementation=impl,
testing=True)
@@ -209,7 +209,7 @@ class TestSpectralDerivative(object):
print msg
for cl_env in iter_clenv():
msg=' >platform {}, device {}:'.format(
- cl_env.platform.name.strip(),
+ cl_env.platform.name.strip(),
cl_env.device.name.strip())
print msg,
op = SpectralSpaceDerivative(cl_env=cl_env, **base_kwds)
@@ -219,7 +219,7 @@ class TestSpectralDerivative(object):
else:
msg='Unknown implementation to test {}.'.format(impl)
raise NotImplementedError(msg)
-
+
# Compare to analytic solution
Fref = None
for impl in implementations:
@@ -239,12 +239,12 @@ class TestSpectralDerivative(object):
dFd.initialize(self.__random_init)
op.apply()
-
+
Fout = tuple( data.get().handle.copy() for data in Fd.data )
dFout = tuple( data.get().handle.copy() for data in dFd.data )
-
+
self._check_output(impl, op, Fref, dFref, Fout, dFout, idx)
-
+
@classmethod
def _check_output(cls, impl, op, Fref, dFref, Fout, dFout, idx):
nidx = sum(idx)
@@ -253,19 +253,19 @@ class TestSpectralDerivative(object):
check_instance(Fout, tuple, values=npw.ndarray, size=len(Fref))
check_instance(dFout, tuple, values=npw.ndarray, size=len(dFref))
- for j,(out_buffers, ref_buffers, name) in enumerate(zip((Fout, dFout),
- (Fref, dFref),
+ for j,(out_buffers, ref_buffers, name) in enumerate(zip((Fout, dFout),
+ (Fref, dFref),
('F', 'dF'))):
for i, (fout,fref) in enumerate(zip(out_buffers, ref_buffers)):
iname = '{}{}'.format(name,i)
assert fout.dtype == fref.dtype, iname
assert fout.shape == fref.shape, iname
-
+
assert not npw.any(npw.isnan(fref))
assert not npw.any(npw.isinf(fref))
has_nan = npw.any(npw.isnan(fout))
has_inf = npw.any(npw.isinf(fout))
-
+
if (has_nan or has_inf):
pass
else:
@@ -279,7 +279,7 @@ class TestSpectralDerivative(object):
else:
print '{}eps, '.format(deps),
continue
-
+
print
print
print 'Test output comparisson for {} failed for component {}:'.format(name, i)
@@ -314,31 +314,31 @@ class TestSpectralDerivative(object):
print w
print
print
-
- msg = 'Test failed for {} on component {} for implementation {}.'.format(name,
+
+ msg = 'Test failed for {} on component {} for implementation {}.'.format(name,
i, impl)
- raise RuntimeError(msg)
+ raise RuntimeError(msg)
- def test_1d_trigonometric_float32(self, **kwds):
- self._test(dim=1, dtype=npw.float32, polynomial=False, **kwds)
- def test_2d_trigonometric_float32(self, **kwds):
- self._test(dim=2, dtype=npw.float32, polynomial=False, **kwds)
+ # def test_1d_trigonometric_float32(self, **kwds):
+ # self._test(dim=1, dtype=npw.float32, polynomial=False, **kwds)
+ # def test_2d_trigonometric_float32(self, **kwds):
+ # self._test(dim=2, dtype=npw.float32, polynomial=False, **kwds)
def test_3d_trigonometric_float32(self, **kwds):
self._test(dim=3, dtype=npw.float32, polynomial=False, **kwds)
- def test_1d_trigonometric_float64(self, **kwds):
- self._test(dim=1, dtype=npw.float64, polynomial=False, **kwds)
- def test_2d_trigonometric_float64(self, **kwds):
- self._test(dim=2, dtype=npw.float64, polynomial=False, **kwds)
+ # def test_1d_trigonometric_float64(self, **kwds):
+ # self._test(dim=1, dtype=npw.float64, polynomial=False, **kwds)
+ # def test_2d_trigonometric_float64(self, **kwds):
+ # self._test(dim=2, dtype=npw.float64, polynomial=False, **kwds)
def test_3d_trigonometric_float64(self, **kwds):
self._test(dim=3, dtype=npw.float64, polynomial=False, **kwds)
-
- def test_1d_polynomial_float32(self, **kwds):
- self._test(dim=1, dtype=npw.float32, polynomial=True, **kwds)
- def test_2d_polynomial_float32(self, **kwds):
- self._test(dim=2, dtype=npw.float32, polynomial=True, **kwds)
+
+ # def test_1d_polynomial_float32(self, **kwds):
+ # self._test(dim=1, dtype=npw.float32, polynomial=True, **kwds)
+ # def test_2d_polynomial_float32(self, **kwds):
+ # self._test(dim=2, dtype=npw.float32, polynomial=True, **kwds)
def test_3d_polynomial_float32(self, **kwds):
self._test(dim=3, dtype=npw.float32, polynomial=True, **kwds)
@@ -358,14 +358,14 @@ class TestSpectralDerivative(object):
self.test_1d_polynomial_float32(max_derivative=3)
self.test_2d_polynomial_float32(max_derivative=2)
self.test_3d_polynomial_float32(max_derivative=1)
-
+
if __name__ == '__main__':
- TestSpectralDerivative.setup_class(enable_extra_tests=False,
+ TestSpectralDerivative.setup_class(enable_extra_tests=False,
enable_debug_mode=False)
-
+
test = TestSpectralDerivative()
- with printoptions(threshold=10000, linewidth=1000,
+ with printoptions(threshold=10000, linewidth=1000,
nanstr='nan', infstr='inf',
formatter={'float': lambda x: '{:>6.2f}'.format(x)}):
test.perform_tests()