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Add reciprocal function for elementwise 1/x #116

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19 changes: 17 additions & 2 deletions c++/nda/mapped_functions.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ namespace nda {
/**
* @brief Function pow for nda::ArrayOrScalar types (lazy and coefficient-wise for nda::Array types).
*
* @tparam A nda::ArrayOrScalar type..
* @tparam A nda::ArrayOrScalar type.
* @param a nda::ArrayOrScalar object.
* @param p Exponent value.
* @return A lazy nda::expr_call object (nda::Array) or the result of `std::pow` applied to the object (nda::Scalar).
Expand All @@ -84,7 +84,7 @@ namespace nda {
* @brief Function conj for nda::ArrayOrScalar types (lazy and coefficient-wise for nda::Array types with a complex
* value type).
*
* @tparam A nda::ArrayOrScalar type..
* @tparam A nda::ArrayOrScalar type.
* @param a nda::ArrayOrScalar object.
* @return A lazy nda::expr_call object (nda::Array and complex valued), the forwarded input object (nda::Array and
* not complex valued) or the complex conjugate of the scalar input.
Expand All @@ -97,6 +97,21 @@ namespace nda {
return std::forward<A>(a);
}

/**
* @brief Reciprocal function for nda::ArrayOrScalar types (lazy and coefficient-wise for nda::Array types).
*
* @tparam A nda::ArrayOrScalar type.
* @param a nda::ArrayOrScalar object.
* @return A lazy nda::expr_call object (nda::Array) or the result of \f$ 1 / x \f$ applied to the object
* (nda::Scalar).
*/
template <ArrayOrScalar A>
auto reciprocal(A &&a) {
return nda::map([](auto const &x) {
return 1 / x;
})(std::forward<A>(a));
}

/** @} */

} // namespace nda
13 changes: 13 additions & 0 deletions test/c++/nda_math_functions.cpp
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Expand Up @@ -228,6 +228,17 @@ TEST_F(NDAMathFunction, Real) {
EXPECT_EQ(nda::real(cplx_c), std::real(cplx_c));
}

TEST_F(NDAMathFunction, Reciprocal) {
auto B_d = nda::reciprocal(A_d);
auto B_c = nda::reciprocal(A_c);
nda::for_each(shape, [&](auto... idxs) {
EXPECT_DOUBLE_EQ(B_d(idxs...), 1 / A_d(idxs...));
EXPECT_COMPLEX_NEAR(B_c(idxs...), 1 / A_c(idxs...), 1e-14);
});
EXPECT_DOUBLE_EQ(nda::reciprocal(dbl_c), 1 / dbl_c);
EXPECT_COMPLEX_NEAR(nda::reciprocal(cplx_c), 1 / cplx_c);
}

TEST_F(NDAMathFunction, Sin) {
auto B_d = nda::sin(A_d);
auto B_c = nda::sin(A_c);
Expand Down Expand Up @@ -295,10 +306,12 @@ TEST_F(NDAMathFunction, Combinations) {
auto B_d = nda::pow(nda::pow(nda::abs(A_d), 1.5), 2.0 / 3.0);
auto C_d = nda::sqrt(nda::pow(A_d, 2));
auto D_d = nda::log(nda::exp(A_d));
auto B_c = nda::reciprocal(nda::reciprocal(A_c));
nda::for_each(shape, [&](auto... idxs) {
EXPECT_NEAR(B_d(idxs...), std::abs(A_d(idxs...)), 1e-10);
EXPECT_NEAR(C_d(idxs...), std::abs(A_d(idxs...)), 1e-10);
EXPECT_NEAR(D_d(idxs...), A_d(idxs...), 1e-10);
EXPECT_COMPLEX_NEAR(B_c(idxs...), A_c(idxs...), 1e-10);
});
}

Expand Down
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