xtensor-python/test/test_pyvectorize.cpp at master · xtensor-stack/xtensor-python · GitHub

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/***************************************************************************

* Copyright (c) Wolf Vollprecht, Johan Mabille and Sylvain Corlay *

* Copyright (c) QuantStack *

* *

* Distributed under the terms of the BSD 3-Clause License. *

* *

* The full license is in the file LICENSE, distributed with this software. *

****************************************************************************/

#include "gtest/gtest.h"

#include "test_common.hpp"

#include "xtensor-python/pytensor.hpp"

#include "xtensor-python/pyvectorize.hpp"

#include "pybind11/pybind11.h"

#include "pybind11/numpy.h"

namespace xt

{

double f1(double a, double b)

{

return a + b;

}

using shape_type = std::vector<std::size_t>;

TEST(pyvectorize, function)

{

auto vecf1 = pyvectorize(f1);

shape_type shape = { 3, 2 };

pyarray<double> a(shape, 1.5);

pyarray<double> b(shape, 2.3);

pyarray<double> c = vecf1(a, b);

EXPECT_EQ(a(0, 0) + b(0, 0), c(0, 0));

}

TEST(pyvectorize, lambda)

{

auto vecf1 = pyvectorize([](double a, double b) { return a + b; });

shape_type shape = { 3, 2 };

pyarray<double> a(shape, 1.5);

pyarray<double> b(shape, 2.3);

pyarray<double> c = vecf1(a, b);

EXPECT_EQ(a(0, 0) + b(0, 0), c(0, 0));

}

TEST(pyvectorize, complex)

{

using complex_t = std::complex<double>;

shape_type shape = { 3, 2 };

pyarray<complex_t> a(shape, complex_t(1.2, 2.5));

auto f = pyvectorize([](complex_t x) { return std::abs(x); });

auto res = f(a);

double exp = std::abs(a(1, 1));

EXPECT_EQ(exp, res(1, 1));

}

xtensor-python/test/test_pyvectorize.cpp at master · xtensor-stack/xtensor-python · GitHub

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