44 lines
1.9 KiB
Markdown
44 lines
1.9 KiB
Markdown
[linalg.conjtransposed]
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# 29 Numerics library [[numerics]](./#numerics)
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## 29.9 Basic linear algebra algorithms [[linalg]](linalg#conjtransposed)
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### 29.9.11 Conjugate transpose in-place transform [linalg.conjtransposed]
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[1](#1)
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[#](http://github.com/Eelis/draft/tree/9adde4bc1c62ec234483e63ea3b70a59724c745a/source/numerics.tex#L13268)
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The conjugate_transposed function
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returns a conjugate transpose view of an object[.](#1.sentence-1)
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This combines the effects of transposed and conjugated[.](#1.sentence-2)
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[ð](#lib:conjugate_transposed)
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` template<class ElementType, class Extents, class Layout, class Accessor>
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constexpr auto conjugate_transposed(mdspan<ElementType, Extents, Layout, Accessor> a);
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`
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[2](#2)
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[#](http://github.com/Eelis/draft/tree/9adde4bc1c62ec234483e63ea3b70a59724c745a/source/numerics.tex#L13279)
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*Effects*: Equivalent to: return conjugated(transposed(a));
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[3](#3)
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[#](http://github.com/Eelis/draft/tree/9adde4bc1c62ec234483e63ea3b70a59724c745a/source/numerics.tex#L13284)
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[*Example [1](#example-1)*: void test_conjugate_transposed(mdspan<complex<double>, extents<size_t, 3, 4>> a) {const auto num_rows = a.extent(0); const auto num_cols = a.extent(1); auto a_ct = conjugate_transposed(a);
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assert(num_rows == a_ct.extent(1));
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assert(num_cols == a_ct.extent(0));
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assert(a.stride(0) == a_ct.stride(1));
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assert(a.stride(1) == a_ct.stride(0)); for (size_t row = 0; row < num_rows; ++row) {for (size_t col = 0; col < num_rows; ++col) { assert(a[row, col] == conj(a_ct[col, row])); }}auto a_ct_ct = conjugate_transposed(a_ct);
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assert(num_rows == a_ct_ct.extent(0));
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assert(num_cols == a_ct_ct.extent(1));
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assert(a.stride(0) == a_ct_ct.stride(0));
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assert(a.stride(1) == a_ct_ct.stride(1)); for (size_t row = 0; row < num_rows; ++row) {for (size_t col = 0; col < num_rows; ++col) { assert(a[row, col] == a_ct_ct[row, col]);
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assert(conj(a_ct[col, row]) == a_ct_ct[row, col]); }}} â *end example*]
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