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Commitb013cee

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Merge pull request#256 from tdegeus/example
Add (CMake) example
2 parentsaa916ec +f4dc5e3 commitb013cee

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12 files changed

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12 files changed

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‎.azure-pipelines/unix-build.yml

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@@ -11,15 +11,16 @@ steps:
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mkdir build
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cd build
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cmake -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX -DPYTHON_EXECUTABLE=`which python` -DDOWNLOAD_GTEST=ON $(Build.SourcesDirectory)
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make install
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displayName: Configure xtensor-python
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workingDirectory: $(Build.BinariesDirectory)
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-script:|
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source activate xtensor-python
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make -j2 test_xtensor_python
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displayName: Build xtensor-python
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workingDirectory: $(Build.BinariesDirectory)/build
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-script:|
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source activate xtensor-python
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cd test
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py.test -s
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displayName: Test xtensor-python (Python)
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workingDirectory: $(Build.SourcesDirectory)
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-script:|
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source activate xtensor-python
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cmake . -DPYTHON_EXECUTABLE=`which python`
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cmake --build .
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python example.py
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displayName: Example - readme 1
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workingDirectory: $(Build.SourcesDirectory)/docs/source/examples/readme_example_1
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-script:|
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source activate xtensor-python
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cmake . -DPYTHON_EXECUTABLE=`which python`
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cmake --build .
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python example.py
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displayName: Example - SFINAE
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workingDirectory: $(Build.SourcesDirectory)/docs/source/examples/sfinae

‎README.md

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@@ -49,10 +49,10 @@ Both containers enable the numpy-style APIs of xtensor (see [the numpy to xtenso
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```cpp
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#include<numeric>// Standard library import for std::accumulate
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#include"pybind11/pybind11.h"// Pybind11 import to define Python bindings
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#include"xtensor/xmath.hpp"// xtensor import for the C++ universal functions
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#include<pybind11/pybind11.h>// Pybind11 import to define Python bindings
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#include<xtensor/xmath.hpp>// xtensor import for the C++ universal functions
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#defineFORCE_IMPORT_ARRAY
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#include"xtensor-python/pyarray.hpp"// Numpy bindings
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#include<xtensor-python/pyarray.hpp>// Numpy bindings
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doublesum_of_sines(xt::pyarray<double>& m)
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{
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v = np.arange(15).reshape(3, 5)
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s = xt.sum_of_sines(v)
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s
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print(s)
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```
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**Outputs**
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1.2853996391883833
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```
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**Working example**
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Get the working example here:
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*[`CMakeLists.txt`](docs/source/examples/readme_example_1/CMakeLists.txt)
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*[`main.cpp`](docs/source/examples/readme_example_1/main.cpp)
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*[`example.py`](docs/source/examples/readme_example_1/example.py)
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###Example 2: Create a universal function from a C++ scalar function
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**C++ code**
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```cpp
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#include"pybind11/pybind11.h"
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#include<pybind11/pybind11.h>
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#defineFORCE_IMPORT_ARRAY
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#include"xtensor-python/pyvectorize.hpp"
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#include<xtensor-python/pyvectorize.hpp>
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#include<numeric>
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#include<cmath>
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x = np.arange(15).reshape(3, 5)
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y = [1, 2, 3, 4, 5]
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z = xt.vectorized_func(x, y)
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z
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print(z)
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```
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**Outputs**

‎docs/source/examples.rst

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****************
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(CMake) Examples
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****************
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Basic example (from readme)
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===========================
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Consider the following C++ code:
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:download:`main.cpp<examples/readme_example_1/main.cpp>`
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..literalinclude::examples/readme_example_1/main.cpp
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:language: cpp
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There are several options to build the module,
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whereby we will CMake here with the following ``CMakeLists.txt``:
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:download:`CMakeLists.txt<examples/readme_example_1/CMakeLists.txt>`
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..literalinclude::examples/readme_example_1/CMakeLists.txt
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:language: cmake
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Then we can test the module:
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:download:`example.py<examples/readme_example_1/example.py>`
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..literalinclude::examples/readme_example_1/example.py
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:language: cmake
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..note::
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Since we did not install the module,
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we should compile and run the example from the same folder.
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To install, please consult
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`this pybind11 / CMake example<https://github.com/pybind/cmake_example>`_.
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Type restriction with SFINAE
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============================
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..seealso::
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`Medium post by Johan Mabille<https://medium.com/@johan.mabille/designing-language-bindings-with-xtensor-f32aa0f20db>`__
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This example covers "Option 4".
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In this example we will design a module with a function that accepts an ``xt::xtensor`` as argument,
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but in such a way that an ``xt::pyxtensor`` can be accepted in the Python module.
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This is done by having a templated function
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..code-block::cpp
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template <class T>
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void times_dimension(T& t);
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As this might be a bit too permissive for your liking, we will show you how to limit the
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scope to *xtensor* types, and allow other overloads using the principle of SFINAE
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(Substitution Failure Is Not An Error).
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In particular:
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:download:`mymodule.hpp<examples/sfinae/mymodule.hpp>`
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..literalinclude::examples/sfinae/mymodule.hpp
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:language: cpp
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Consequently from C++, the interaction with the module's function is trivial
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:download:`main.cpp<examples/sfinae/main.cpp>`
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..literalinclude::examples/sfinae/main.cpp
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:language: cpp
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For the Python module we just have to specify the template to be
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``xt::pyarray`` or ``xt::pytensor``. E.g.
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:download:`src/python.cpp<examples/sfinae/python.cpp>`
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..literalinclude::examples/sfinae/python.cpp
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:language: cpp
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We will again use CMake to compile, with the following ``CMakeLists.txt``:
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:download:`CMakeLists.txt<examples/sfinae/CMakeLists.txt>`
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..literalinclude::examples/sfinae/CMakeLists.txt
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:language: cmake
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Then we can test the module:
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:download:`example.py<examples/readme_example_1/example.py>`
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..literalinclude::examples/readme_example_1/example.py
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:language: cmake
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..note::
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Since we did not install the module,
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we should compile and run the example from the same folder.
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To install, please consult
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`this pybind11 / CMake example<https://github.com/pybind/cmake_example>`_.
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cmake_minimum_required(VERSION 3.1..3.19)
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project(mymodule)
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find_package(pybind11 CONFIG REQUIRED)
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find_package(xtensor REQUIRED)
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find_package(xtensor-python REQUIRED)
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find_package(Python REQUIRED COMPONENTS NumPy)
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pybind11_add_module(mymodule main.cpp)
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target_link_libraries(mymodulePUBLIC pybind11::module xtensor-python Python::NumPy)
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target_compile_definitions(mymodulePRIVATE VERSION_INFO=0.1.0)
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importmymodule
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importnumpyasnp
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a=np.array([1,2,3])
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assertnp.isclose(np.sum(np.sin(a)),mymodule.sum_of_sines(a))
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#include<numeric>
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#include<xtensor.hpp>
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#include<pybind11/pybind11.h>
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#defineFORCE_IMPORT_ARRAY
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#include<xtensor-python/pyarray.hpp>
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doublesum_of_sines(xt::pyarray<double>& m)
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{
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auto sines =xt::sin(m);// sines does not actually hold values.
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returnstd::accumulate(sines.begin(), sines.end(),0.0);
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}
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PYBIND11_MODULE(mymodule, m)
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{
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xt::import_numpy();
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m.doc() ="Test module for xtensor python bindings";
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m.def("sum_of_sines", sum_of_sines,"Sum the sines of the input values");
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}
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cmake_minimum_required(VERSION 3.1..3.19)
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project(mymodule)
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find_package(pybind11 CONFIG REQUIRED)
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find_package(xtensor REQUIRED)
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find_package(xtensor-python REQUIRED)
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find_package(Python REQUIRED COMPONENTS NumPy)
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pybind11_add_module(mymodule python.cpp)
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target_link_libraries(mymodulePUBLIC pybind11::module xtensor-python Python::NumPy)
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target_compile_definitions(mymodulePRIVATE VERSION_INFO=0.1.0)
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add_executable(myexec main.cpp)
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target_link_libraries(myexecPUBLIC xtensor)
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importmymodule
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importnumpyasnp
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a=np.array([[1,2,3], [4,5,6]],dtype=np.float64)
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b=np.array(a,copy=True)
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mymodule.times_dimension(b)# changing in-place!
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assertnp.allclose(2*a,b)
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‎docs/source/examples/sfinae/main.cpp

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#include"mymodule.hpp"
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#include<xtensor/xio.hpp>
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intmain()
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{
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xt::xtensor<size_t,2> a = xt::arange<size_t>(2 *3).reshape({2,3});
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mymodule::times_dimension(a);
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std::cout << a << std::endl;
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return0;
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}
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#include<xtensor/xtensor.hpp>
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namespacemymodule {
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template<classT>
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structis_std_vector
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{
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staticconstbool value =false;
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};
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template<classT>
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structis_std_vector<std::vector<T> >
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{
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staticconstbool value =true;
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};
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// any xtensor object
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template<classT, std::enable_if_t<xt::is_xexpression<T>::value,bool> =true>
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voidtimes_dimension(T& t)
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{
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using value_type =typename T::value_type;
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t *= (value_type)(t.dimension());
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}
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// an std::vector
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template<classT, std::enable_if_t<is_std_vector<T>::value,bool> =true>
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voidtimes_dimension(T& t)
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{
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// do nothing
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}
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}
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#include"mymodule.hpp"
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#include<pybind11/pybind11.h>
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#defineFORCE_IMPORT_ARRAY
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#include<xtensor-python/pyarray.hpp>
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PYBIND11_MODULE(mymodule, m)
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{
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xt::import_numpy();
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m.doc() ="Test module for xtensor python bindings";
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m.def("times_dimension", &mymodule::times_dimension<xt::pyarray<double>>);
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}

‎docs/source/index.rst

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- ``xtensor`` is a C++ library for multi-dimensional arrays enabling numpy-style broadcasting and lazy computing.
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- ``xtensor-python`` enables inplace use of numpy arrays with all the benefits from ``xtensor``
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- C++ universal functions and broadcasting
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- C++ universal functions and broadcasting
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- STL - compliant APIs.
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basic_usage
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array_tensor
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numpy_capi
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examples
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cookiecutter
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..toctree::
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.. _NumPy:http://www.numpy.org
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.. _`Buffer Protocol`:https://docs.python.org/3/c-api/buffer.html
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.. _`numpy to xtensor cheat sheet`:http://xtensor.readthedocs.io/en/latest/numpy.html
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.. _`numpy to xtensor cheat sheet`:http://xtensor.readthedocs.io/en/latest/numpy.html
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.. _xtensor:https://github.com/xtensor-stack/xtensor
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.. _pybind11:https://github.com/pybind/pybind11
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.. _xtensor-python-cookiecutter:https://github.com/xtensor-stack/xtensor-python-cookiecutter
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.. _pybind11:https://github.com/pybind/pybind11
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.. _xtensor-python-cookiecutter:https://github.com/xtensor-stack/xtensor-python-cookiecutter

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