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‎Makefile

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# Put the path to your Python.h here
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includes = -I /usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/include/python3.7m
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includes = -I /usr/local/Cellar/python/3.7.4/Frameworks/Python.framework/Versions/3.7/include/python3.7m
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# Numpy include
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# Numpy include
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includes += -I /usr/local/lib/python3.7/site-packages/numpy/core/include
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# Add the path to the directory containing libpython*.a here if the linking fails
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includes += -L /usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/lib
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includes += -L /usr/local/Cellar/python/3.7.4/Frameworks/Python.framework/Versions/3.7/lib
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# Link your python version
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# Link your python version
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linkings = -lpython3.7
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# Compiler definitions
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definitions = -std=c++11
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# Eigen include
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eigen_include = -I /usr/local/include/eigen3
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examples: minimal basic modern animation nonblock xkcd quiver bar surface subplot fill_inbetween fill update
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eigen: eigen_basic eigen_modern eigen_loglog eigen_semilogx eigen_semilogy
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minimal: examples/minimal.cpp matplotlibcpp.h
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cd examples && g++ -DWITHOUT_NUMPY minimal.cpp ${includes} ${linkings} -o minimal ${definitions}
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#cd examples && g++ minimal.cpp ${includes} ${linkings} -o minimal ${definitions}
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fill: examples/fill.cpp matplotlibcpp.h
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cd examples && g++ fill.cpp ${includes} ${linkings} -o fill ${definitions}
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update: examples/update.cpp matplotlibcpp.h
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cd examples && g++ update.cpp ${includes} ${linkings} -o update ${definitions}
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eigen_basic: examples/eigen/basic.cpp matplotlibcpp.h
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cd examples/eigen && g++ basic.cpp ${includes} ${eigen_include} ${linkings} -o $@ ${definitions}
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eigen_modern: examples/eigen/modern.cpp matplotlibcpp.h
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cd examples/eigen && g++ modern.cpp ${includes} ${eigen_include} ${linkings} -o $@ ${definitions}
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eigen_loglog: examples/eigen/loglog.cpp matplotlibcpp.h
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cd examples/eigen && g++ loglog.cpp ${includes} ${eigen_include} ${linkings} -o $@ ${definitions}
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eigen_semilogx: examples/eigen/semilogx.cpp matplotlibcpp.h
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cd examples/eigen && g++ semilogx.cpp ${includes} ${eigen_include} ${linkings} -o $@ ${definitions}
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eigen_semilogy: examples/eigen/semilogy.cpp matplotlibcpp.h
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cd examples/eigen && g++ semilogy.cpp ${includes} ${eigen_include} ${linkings} -o $@ ${definitions}
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clean:
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rm -f examples/{minimal,basic,modern,animation,nonblock,xkcd,quiver,bar,surface,subplot,fill_inbetween,fill,update}
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rm -f examples/eigen/{eigen_basic,eigen_modern,eigen_loglog}

‎docs/Makefile

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# Minimal makefile for Sphinx documentation
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#
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# You can set these variables from the command line, and also
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# from the environment for the first two.
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SPHINXOPTS ?=
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SPHINXBUILD ?= sphinx-build
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SOURCEDIR = source
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BUILDDIR = build
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# Put it first so that "make" without argument is like "make help".
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help:
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@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
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.PHONY: help Makefile
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# Catch-all target: route all unknown targets to Sphinx using the new
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# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
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%: Makefile
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@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

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‎docs/build/html/.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: dc893f442bc417e3df3035107b7d8bde
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tags: 645f666f9bcd5a90fca523b33c5a78b7

‎docs/build/html/_images/matplotlib_icon.png

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‎docs/build/html/_sources/compiling.rst.txt

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.. _compiling:
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Compiling a program
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*******************
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Requirements
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============
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Matplotlib for C++ requires a working Python installation as well as
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Matplotlib. Python2.7 and Python3 (>= 3.6) have been tested, but
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other versions should work as well. In the linking process the exact
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version of Python to use can be specified by linking the according library.
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On Unix it is recommended to install Python via the package manager to
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assert that all dependencies are installed properly.
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.. code-block:: bash
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<package-manager> install python3 python3-dev # or -devel depending on the platform
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If Python is installed from source problems in the linking may occur.
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How to resolve these is explained in the next section, or in
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:ref:`this <pyfromsource>` code-block.
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Install matplotlib via pip
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.. code-block:: bash
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pip3 install matplotlib # or pip for Python 2
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Includes and Linking
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====================
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The header ``matplotlibcpp.h`` depends on the Python header, ``Python.h``,
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the corresponding Python library ``libpython``, and on ``numpy/arrayobject.h``.
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If not in the standard include paths, the paths to the header files,
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the path to the library, and the library itself have to be specified
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for the compiler using the options ``-I``, ``-L`` and ``-l`` respectively.
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Note, that all Python constituents should be of the same Python version.
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Matplotlib for C++ supports both, Python 2.7 and Python 3 versions.
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In detail:
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- The Python header ``Python.h``
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The Python header comes with the Python installation. It it cannot be
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found on your system try installing the Python development packages.
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The location of this header has to be specified using the option ``-I``.
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Typical locations:
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- Linux: `/usr/local/include/python3.7`
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- Mac: if installed with Homebrew `/usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/include/python3.7m`
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- The Python library ``libpython*.so``
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The program has to be linked against the compiled Python library.
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Depending on the Python version the name of the library differs, for
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Python 3.7 it is ``libpython3.7.so`` (or ``libpython3.7m.so``).
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Then link the library by specifying ``-lpython3.7`` (or ``-lpython3.7m``).
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Additionally to the linking the location of the library must be specified
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if not installed in the usual directory. For Linux systems this is
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usually not necessary, for Mac however it mostly is.
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The location of the library has to be specified using the option ``-L``.
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If Python has not been installed using the package manager (but e.g.
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from source) twofold problems with linking the library can occur.
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The first are missing dependencies of the Python library, these can be
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added via ``-lpthread -lutil -ldl``.
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The second is that dynamic libraries have to be exported which is
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resolved by adding ``-Xlinker -export-dynamic``.
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Typical locations:
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- Linux: Path usually already included
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- Mac: `/usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/lib`
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- Numpy array ``numpy/arrayobject.h``
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By default Matplotlib for C++ uses Numpy arrays. This requires the above
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header file. However it is possible to avoid this header by defining
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``-DWITHOUT_NUMPY``.
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- Linux: `/usr/local/lib/python3.7/site-packages/numpy/core/include`
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- Mac: If installed via Homebrew, same as for Linux.
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**Examples**
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On Linux with the GNU compiler ``g++`` and
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C++11.
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.. code-block:: bash
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# using Python 2.7
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g++ main.cpp -std=c++11 -I/usr/local/include/python2.7 \
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-I/usr/local/lib/python2.7/site-packages/numpy/core/include -lpython2.7
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.. code-block:: bash
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# using Python3.7 and no Numpy
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g++ main.cpp -std=c++11 -DWITHOUT_NUMPY -I/usr/local/include/python2.7 -lpython2.7
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On Mac with the GNU compiler ``g++`` and C++14.
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.. code-block:: bash
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g++ main.cpp -std=c++14 \
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-I /usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/include/python3.7m \
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-I /usr/local/lib/python3.7/site-packages/numpy/core/include \
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-L /usr/local/Cellar/python/3.7.3/Frameworks/Python.framework/Versions/3.7/lib \
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-lpython3.7
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With exporting dynamic libraries and linking to all dependencies of
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the Python library on a Linux system:
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.. _pyfromsource:
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.. code-block:: bash
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g++ main.cpp -std=c++11 -I/usr/local/include/python3.7m \
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-I/usr/local/lib/python3.7/site-packages/numpy/core/include \
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-lpython3.7m \
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-lpthread -lutil -ldl \ # library dependencies
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-Xlinker -export-dynamic \ # export dynamic libraries

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