Merge pull request #131 from AdaptiveParticles/develop

Develop: Preparing Master for APR Version 2.0 bump.

Author: cheesema

.gitignore

@@ -1,6 +1,9 @@
 
 # Created by https://www.gitignore.io/api/c++,intellij,matlab
 
+#ignore for apr files unless they are directly updated
+*.apr
+
 ### C++ ###
 # Prerequisites
 *.d

.travis.yml

@@ -18,20 +18,18 @@ matrix:
         - libhdf5-dev
         - libtiff5
   - os: osx
-    osx_image: xcode9.2
+    osx_image: xcode11.4
 
 install:
 - if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then brew update; fi
-- if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then brew install hdf5; fi
+- if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then brew install c-blosc; fi
 - if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then echo "UPDATESTARTUPTTY" | gpg-connect-agent > /dev/null 2>&1; fi
 - if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then brew install cmake || brew upgrade cmake ; fi
 - if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then export COMPILER=clang++-3.6; fi
 - if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then export CXX=clang++-3.6; fi
 - if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then export CC=clang-3.6; fi
 - git submodule init
 - git submodule update
-- pip install --user -U pip
-- pip install --user numpy
 
 script:
 - sh ./cmake-build.sh

CMakeLists.txt

@@ -16,7 +16,6 @@ option(APR_USE_LIBTIFF "Use LibTIFF" ON)
 option(APR_TESTS "Build APR tests" OFF)
 option(APR_PREFER_EXTERNAL_GTEST "When found, use the installed GTEST libs instead of included sources" OFF)
 option(APR_PREFER_EXTERNAL_BLOSC "When found, use the installed BLOSC libs instead of included sources" OFF)
-option(APR_BUILD_PYTHON_WRAPPERS "Build APR PYTHON wrappers (experimental - under development)" OFF)
 option(APR_USE_CUDA "should APR use CUDA? (experimental - under development)" OFF)
 option(APR_USE_OPENMP "should APR use OpenMP?" ON)
 option(APR_BENCHMARK "add benchmarking code" OFF)
@@ -38,8 +37,9 @@ list(APPEND CMAKE_MODULE_PATH
 ###############################################################################
 # Generate configuration file
 ###############################################################################
-set (APR_VERSION_MAJOR 1)
-set (APR_VERSION_MINOR 2)
+
+set (APR_VERSION_MAJOR 2)
+set (APR_VERSION_MINOR 0)
 set (APR_VERSION_PATCH 0)
 set (APR_VERSION_STRING ${APR_VERSION_MAJOR}.${APR_VERSION_MINOR}.${APR_VERSION_PATCH})
 execute_process(COMMAND git rev-parse HEAD
@@ -53,10 +53,14 @@ configure_file (
 include_directories("${PROJECT_BINARY_DIR}")
 message("Configuring for APR version: " ${APR_VERSION_STRING})
 
-
 ###############################################################################
 # Find all required libraries
 ###############################################################################
+
+#pthreads
+set(THREADS_PREFER_PTHREAD_FLAG ON)
+find_package(Threads REQUIRED)
+
 find_package(HDF5 REQUIRED)
 find_package(ZLIB REQUIRED)
 if(APR_USE_LIBTIFF)
@@ -113,17 +117,17 @@ include_directories("external/glm")
 # If you ever want to compile with Intel's icc (or any other compiler) provide
 # compiler names/paths in cmake command like this:
 # CC="icc" CXX="icc" CXXFLAGS="-O3" cmake -DAPR_TESTS=1
-set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14 -Wall -pedantic ")
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14 ")
 if(CMAKE_COMPILER_IS_GNUCC)
     set(CMAKE_CXX_FLAGS_RELEASE "-O4 -ffast-math")
-    set(CMAKE_CXX_FLAGS_DEBUG "-O0 -g")
+    set(CMAKE_CXX_FLAGS_DEBUG "-O0 -g  -Wall -pedantic")
     set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -Bdynamic")
     if(NOT WIN32)
         set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -ldl -lz")
     endif()
 elseif (CMAKE_CXX_COMPILER_ID MATCHES "Clang")
     set(CMAKE_CXX_FLAGS_RELEASE "-O3 -ffast-math")
-    set(CMAKE_CXX_FLAGS_DEBUG "-O0 -g")
+    set(CMAKE_CXX_FLAGS_DEBUG "-O0 -g  -Wall -pedantic")
     set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -lz")
 endif()
 
@@ -160,8 +164,13 @@ if(APR_USE_CUDA)
 	        src/algorithm/ComputeGradientCuda.cu
             src/data_structures/Mesh/PixelData.cu
             src/algorithm/LocalIntensityScale.cu
+            src/algorithm/OVPC.cu
+            src/data_structures/APR/access/GPUAccess.cu
+            src/numerics/APRDownsampleGPU.cu
+            src/numerics/APRIsoConvGPU.cu
             )
     include_directories(${CMAKE_CUDA_TOOLKIT_INCLUDE_DIRECTORIES})
+
 endif()
 
 if(APR_BUILD_STATIC_LIB)
@@ -296,21 +305,15 @@ if(APR_TESTS)
 endif(APR_TESTS)
 
 ###############################################################################
-# PYTHON wrappers
+# Performance Benchmarks
 ###############################################################################
-if(APR_BUILD_PYTHON_WRAPPERS)
-    message(STATUS "APR: Building PYTHON wrappers")
-    set(PYBIND11_PYTHON_VERSION 2.7)
-
-    add_subdirectory("external/pybind11")
-
-    set(APR_PYTHON_MODULE_NAME pyApr)
-    add_definitions(-DAPR_PYTHON_MODULE_NAME=${APR_PYTHON_MODULE_NAME})
-    add_library(${APR_PYTHON_MODULE_NAME} MODULE src/wrapper/pythonBind.cpp $<TARGET_OBJECTS:aprObjLib>)
-    target_include_directories(${APR_PYTHON_MODULE_NAME} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/src)
-    target_link_libraries(${APR_PYTHON_MODULE_NAME} PRIVATE pybind11::module ${HDF5_LIBRARIES} ${TIFF_LIBRARIES} ${BLOSC_LIBRARIES} ${ZLIB_LIBRARIES})
-    set_target_properties(${APR_PYTHON_MODULE_NAME} PROPERTIES OUTPUT_NAME ${APR_PYTHON_MODULE_NAME})
-    set_target_properties(${APR_PYTHON_MODULE_NAME} PROPERTIES PREFIX "${PYTHON_MODULE_PREFIX}"
-                                                               SUFFIX "${PYTHON_MODULE_EXTENSION}")
-
-endif(APR_BUILD_PYTHON_WRAPPERS)
+
+if(APR_BENCHMARK)
+    message(STATUS "APR: Benchmarking performance")
+    add_subdirectory(benchmarks)
+endif(APR_BENCHMARK)
+
+###############################################################################
+# PYTHON wrappers These are now external please ask us for access
+###############################################################################
+

README.md

@@ -16,7 +16,7 @@ Labeled Zebrafish nuclei: Gopi Shah, Huisken Lab ([MPI-CBG](https://www.mpi-cbg.
 * CMake 3.6 or higher
 * LibTIFF 4.0 or higher
 
-NB: This branch introduces changes to IO and iteration that are not compatable with old versions.
+NB: This update to 2.0 introduces changes to IO and iteration that are not compatable with old versions.
 
 ## Building
 
@@ -50,7 +50,7 @@ This will create the `libapr.so` library in the `build` directory, as well as al
 
 ### Docker build
 
-We provide working Dockerfile that install the library within the image on a separate [repo](https://github.com/MSusik/libaprdocker).
+We provide a working Dockerfile that install the library within the image on a separate [repo](https://github.com/MSusik/libaprdocker).
 
 ### Building on OSX
 
@@ -75,11 +75,14 @@ In case you want to use the homebrew-installed clang (OpenMP support), modify th
 CC="/usr/local/opt/llvm/bin/clang" CXX="/usr/local/opt/llvm/bin/clang++" LDFLAGS="-L/usr/local/opt/llvm/lib -Wl,-rpath,/usr/local/opt/llvm/lib" CPPFLAGS="-I/usr/local/opt/llvm/include" cmake ..
 ```
 
-
 ### Building on Windows
 
+__The simplest way to utilise the library from Windows 10 is through using the Windows Subsystem for Linux; see: https://docs.microsoft.com/en-us/windows/wsl/install-win10 then follow linux instructions.__
+
 __Compilation only works with mingw64/clang or the Intel C++ Compiler, with Intel C++ being the recommended way__
 
+The below instructions for VS can be attempted; however they have not been reproduced.
+
 You need to have Visual Studio 2017 installed, with [the community edition](https://www.visualstudio.com/downloads/) being sufficient. LibAPR does not compile correctly with the default Visual Studio compiler, so you also need to have the [Intel C++ Compiler, 18.0 or higher](https://software.intel.com/en-us/c-compilers) installed. [`cmake`](https://cmake.org/download/) is also a requirement.
 
 Furthermore, you need to have HDF5 installed (binary distribution download at [The HDF Group](http://hdfgroup.org) and LibTIFF (source download from [SimpleSystems](http://www.simplesystems.org/libtiff/). LibTIFF needs to be compiled via `cmake`. LibTIFF's install target will then install the library into `C:\Program Files\tiff`.
@@ -96,6 +99,8 @@ cmake --build . --config Debug
 This will set the appropriate hints for Visual Studio to find both LibTIFF and HDF5. This will create the `apr.dll` library in the `build/Debug` directory, as well as all of the examples. If you need a `Release` build, run `cmake --build . --config Release` from the `build` directory.
 
 ## Examples and Documentation
+These examples can be turned on by adding -DAPR_BUILD_EXAMPLES=ON to the cmake command.
+
 There are nine basic examples, that show how to generate and compute with the APR:
 
 | Example | How to ... |
@@ -104,8 +109,6 @@ There are nine basic examples, that show how to generate and compute with the AP
 | [Example_apr_iterate](./examples/Example_apr_iterate.cpp) | iterate through a given APR. |
 | [Example_neighbour_access](./examples/Example_neighbour_access.cpp) | access particle and face neighbours. |
 | [Example_compress_apr](./examples/Example_compress_apr.cpp) |  additionally compress the intensities stored in an APR. |
-| [Example_compute_gradient](./examples/Example_compute_gradient.cpp) | compute a gradient based on the stored particles in an APR. |
-| [Example_produce_paraview_file](./examples/Example_produce_paraview_file.cpp) | produce a file for visualisation in ParaView or reading in Matlab. |
 | [Example_random_access](./examples/Example_random_access.cpp) | perform random access operations on particles. |
 | [Example_ray_cast](./examples/Example_ray_cast.cpp) | perform a maximum intensity projection ray cast directly on the APR data structures read from an APR. |
 | [Example_reconstruct_image](./examples/Example_reconstruct_image.cpp) | reconstruct a pixel image from an APR. |
@@ -114,22 +117,17 @@ All examples except Example_get_apr require an already produced APR, such as tho
 
 For tutorial on how to use the examples, and explanation of data-structures see [the library guide](./docs/lib_guide.pdf).
 
-## Python support
-
-Basic functionality is supported in Python through wrappers. To build the python module,
-use the CMake option 
+## LibAPR Tests
 
-`-DAPR_BUILD_PYTHON_WRAPPERS=ON`
-
-Example usage of the available functionality:
+The testing framework can be turned on by adding -DAPR_TESTS=ON to the cmake command. All tests can then be run by executing on the command line your build folder.
+```
+ctest
+```
+Please let us know by creating an issue, if any of these tests are failing on your machine.
 
-| Example | How to ... |
-|:--|:--|
-| [Example_get_apr_from_array](./examples/python_examples/Example_get_apr_from_array.py) | create an APR from an ndarray and store as hdf5. |
-| [Example_get_apr_from_file](./examples/python_examples/Example_get_apr_from_file.py) | create an APR from a TIFF and store as hdf5. |
-| [Example_reconstruct_image](./examples/python_examples/Example_reconstruct_image.py) | read in an APR and reconstruct a pixel image |
+## Python support
 
-Note that you may have to manually change the `sys.path.insert()` statements before `import pyApr` in these scripts to insert your build folder.
+Note: These have been updated and externalised, and will be released shortly.
 
 ## Java wrappers