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Bump required C++ standard to c++17
According to SciPy's Toolchain Roadmap [1], C++17 core features became available in 2022. This was concluded based on minimum compiler versions in `manylinux2014` images, AIX systems, FreeBSD systems, and Windows. Note, some standard library features are not universally supported. This commit does not move much code to C++17, just a couple of minor improvements that I could easily change. [1] https://docs.scipy.org/doc/scipy/dev/toolchain.html#c-language-standards
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‎doc/api/next_api_changes/development/27012-ES.rst

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Extensions require C++17
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~~~~~~~~~~~~~~~~~~~~~~~~
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Matplotlib now requires a compiler that supports C++17 in order to build its extensions.
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According to `SciPy's analysis
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<https://docs.scipy.org/doc/scipy/dev/toolchain.html#c-language-standards>`_, this
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should be available on all supported platforms.

‎meson.build

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meson_version: '>=1.1.0',
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default_options: [
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'b_lto=true',
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'cpp_std=c++11',
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'cpp_std=c++17',
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'auto_features=disabled', # Force FreeType to avoid extra dependencies.
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],
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)

‎src/_image_wrapper.cpp

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* */
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const char* image_resample__doc__ =
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"Resample input_array, blending it in-place into output_array, using an\n"
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"affine transformation.\n\n"
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R"""(Resample input_array, blending it in-place into output_array, using an affine transform.
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"Parameters\n"
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"----------\n"
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"input_array : 2-d or 3-d NumPy array of float, double or `numpy.uint8`\n"
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" If 2-d, the image is grayscale. If 3-d, the image must be of size\n"
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" 4 in the last dimension and represents RGBA data.\n\n"
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Parameters
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----------
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input_array : 2-d or 3-d NumPy array of float, double or `numpy.uint8`
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If 2-d, the image is grayscale. If 3-d, the image must be of size 4 in the last
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dimension and represents RGBA data.
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"output_array : 2-d or 3-d NumPy array of float, double or `numpy.uint8`\n"
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" The dtype and number of dimensions must match `input_array`.\n\n"
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output_array : 2-d or 3-d NumPy array of float, double or `numpy.uint8`
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The dtype and number of dimensions must match `input_array`.
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"transform : matplotlib.transforms.Transform instance\n"
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" The transformation from the input array to the output array.\n\n"
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transform : matplotlib.transforms.Transform instance
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The transformation from the input array to the output array.
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"interpolation : int, default: NEAREST\n"
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" The interpolation method. Must be one of the following constants\n"
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" defined in this module:\n\n"
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interpolation : int, default: NEAREST
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The interpolation method. Must be one of the following constants defined in this
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module:
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" NEAREST, BILINEAR, BICUBIC, SPLINE16, SPLINE36,\n"
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" HANNING, HAMMING, HERMITE, KAISER, QUADRIC, CATROM, GAUSSIAN,\n"
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" BESSEL, MITCHELL, SINC, LANCZOS, BLACKMAN\n\n"
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NEAREST, BILINEAR, BICUBIC, SPLINE16, SPLINE36, HANNING, HAMMING, HERMITE, KAISER,
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QUADRIC, CATROM, GAUSSIAN, BESSEL, MITCHELL, SINC, LANCZOS, BLACKMAN
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"resample : bool, optional\n"
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" When `True`, use a full resampling method. When `False`, only\n"
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" resample when the output image is larger than the input image.\n\n"
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resample : bool, optional
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When `True`, use a full resampling method. When `False`, only resample when the
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output image is larger than the input image.
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"alpha : float, default: 1\n"
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" The transparency level, from 0 (transparent) to 1 (opaque).\n\n"
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alpha : float, default: 1
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The transparency level, from 0 (transparent) to 1 (opaque).
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"norm : bool, default: False\n"
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" Whether to norm the interpolation function.\n\n"
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norm : bool, default: False
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Whether to norm the interpolation function.
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"radius: float, default: 1\n"
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" The radius of the kernel, if method is SINC, LANCZOS or BLACKMAN.\n";
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radius: float, default: 1
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The radius of the kernel, if method is SINC, LANCZOS or BLACKMAN.
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)""";
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static pybind11::array_t<double>

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