2015-07-26 14:33:49 +00:00
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/*
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2015-07-29 15:51:54 +00:00
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example/example10.cpp -- auto-vectorize functions over NumPy array
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arguments
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2015-07-26 14:33:49 +00:00
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2016-04-17 18:21:41 +00:00
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Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
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2015-07-26 14:33:49 +00:00
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All rights reserved. Use of this source code is governed by a
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BSD-style license that can be found in the LICENSE file.
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*/
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#include "example.h"
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2015-10-15 16:13:33 +00:00
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#include <pybind11/numpy.h>
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double my_func(int x, float y, double z) {
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std::cout << "my_func(x:int=" << x << ", y:float=" << y << ", z:float=" << z << ")" << std::endl;
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2016-05-28 10:26:18 +00:00
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return (float) x*y*z;
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2015-07-26 14:33:49 +00:00
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}
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2015-07-28 14:12:20 +00:00
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std::complex<double> my_func3(std::complex<double> c) {
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return c * std::complex<double>(2.f);
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}
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2015-07-26 14:33:49 +00:00
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void init_ex10(py::module &m) {
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2015-07-29 15:51:54 +00:00
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// Vectorize all arguments of a function (though non-vector arguments are also allowed)
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m.def("vectorized_func", py::vectorize(my_func));
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2015-07-29 15:51:54 +00:00
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2015-07-26 14:33:49 +00:00
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// Vectorize a lambda function with a capture object (e.g. to exclude some arguments from the vectorization)
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m.def("vectorized_func2",
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2015-10-13 15:38:22 +00:00
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[](py::array_t<int> x, py::array_t<float> y, float z) {
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2015-07-26 14:33:49 +00:00
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return py::vectorize([z](int x, float y) { return my_func(x, y, z); })(x, y);
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}
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);
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2015-07-29 15:51:54 +00:00
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// Vectorize a complex-valued function
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m.def("vectorized_func3", py::vectorize(my_func3));
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2016-05-19 14:02:09 +00:00
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/// Numpy function which only accepts specific data types
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m.def("selective_func", [](py::array_t<int, py::array::c_style>) { std::cout << "Int branch taken. "<< std::endl; });
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m.def("selective_func", [](py::array_t<float, py::array::c_style>) { std::cout << "Float branch taken. "<< std::endl; });
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m.def("selective_func", [](py::array_t<std::complex<float>, py::array::c_style>) { std::cout << "Complex float branch taken. "<< std::endl; });
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2015-07-26 14:33:49 +00:00
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}
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