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[upstream_utils] Upgrade to Sleipnir 0.6.3 (#9030)

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Also drop patches since we're now on C++23.
This commit is contained in:
Tyler Veness
2026-06-27 12:10:39 -07:00
committed by GitHub
parent f8de482385
commit 32bf24aa19
31 changed files with 536 additions and 1853 deletions
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20
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/autodiff/expression_type.hpp vendored
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@@ -4,9 +4,8 @@
#include <stdint.h>
#include <fmt/base.h>
#include "sleipnir/util/unreachable.hpp"
#include <format>
#include <utility>
namespace slp {
@@ -28,16 +27,14 @@ enum class ExpressionType : uint8_t {
} // namespace slp
// @cond Suppress Doxygen
/// Formatter for ExpressionType.
template <>
struct fmt::formatter<slp::ExpressionType> {
struct std::formatter<slp::ExpressionType> {
/// Parse format string.
///
/// @param ctx Format parse context.
/// @return Format parse context iterator.
constexpr auto parse(fmt::format_parse_context& ctx) {
constexpr auto parse(std::format_parse_context& ctx) {
return m_underlying.parse(ctx);
}
@@ -48,8 +45,7 @@ struct fmt::formatter<slp::ExpressionType> {
/// @param ctx Format context.
/// @return Format context iterator.
template <typename FmtContext>
constexpr auto format(const slp::ExpressionType& type,
FmtContext& ctx) const {
auto format(const slp::ExpressionType& type, FmtContext& ctx) const {
using enum slp::ExpressionType;
switch (type) {
@@ -64,12 +60,10 @@ struct fmt::formatter<slp::ExpressionType> {
case NONLINEAR:
return m_underlying.format("nonlinear", ctx);
default:
slp::unreachable();
std::unreachable();
}
}
private:
fmt::formatter<const char*> m_underlying;
std::formatter<const char*> m_underlying;
};
// @endcond

4
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/autodiff/hessian.hpp vendored
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@@ -111,9 +111,9 @@ class Hessian {
auto grad = detail::gradient_tree(m_top_lists[row], m_wrt);
for (int col = 0; col < m_wrt.rows(); ++col) {
if (grad[col].expr != nullptr) {
result(row, col) = std::move(grad[col]);
result[row, col] = std::move(grad[col]);
} else {
result(row, col) = Variable{Scalar(0)};
result[row, col] = Variable{Scalar(0)};
}
}
}

4
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/autodiff/jacobian.hpp vendored
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@@ -114,9 +114,9 @@ class Jacobian {
auto grad = detail::gradient_tree(m_top_lists[row], m_wrt);
for (int col = 0; col < m_wrt.rows(); ++col) {
if (grad[col].expr != nullptr) {
result(row, col) = std::move(grad[col]);
result[row, col] = std::move(grad[col]);
} else {
result(row, col) = Variable{Scalar(0)};
result[row, col] = Variable{Scalar(0)};
}
}
}

24
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/autodiff/variable.hpp vendored
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@@ -73,7 +73,7 @@ class Variable : public SleipnirBase {
///
/// @param value The value of the Variable.
// NOLINTNEXTLINE (google-explicit-constructor)
Variable(SleipnirMatrixLike<Scalar> auto value) : expr{value(0, 0).expr} {
Variable(SleipnirMatrixLike<Scalar> auto value) : expr{value[0, 0].expr} {
slp_assert(value.rows() == 1 && value.cols() == 1);
}
@@ -733,7 +733,11 @@ auto make_constraints(LHS&& lhs, RHS&& rhs) {
for (int row = 0; row < rhs.rows(); ++row) {
for (int col = 0; col < rhs.cols(); ++col) {
// Make right-hand side zero
constraints.emplace_back(lhs - rhs(row, col));
if constexpr (EigenMatrixLike<RHS>) {
constraints.emplace_back(lhs - rhs(row, col));
} else {
constraints.emplace_back(lhs - rhs[row, col]);
}
}
}
@@ -749,7 +753,11 @@ auto make_constraints(LHS&& lhs, RHS&& rhs) {
for (int row = 0; row < lhs.rows(); ++row) {
for (int col = 0; col < lhs.cols(); ++col) {
// Make right-hand side zero
constraints.emplace_back(lhs(row, col) - rhs);
if constexpr (EigenMatrixLike<LHS>) {
constraints.emplace_back(lhs(row, col) - rhs);
} else {
constraints.emplace_back(lhs[row, col] - rhs);
}
}
}
@@ -767,7 +775,13 @@ auto make_constraints(LHS&& lhs, RHS&& rhs) {
for (int row = 0; row < lhs.rows(); ++row) {
for (int col = 0; col < lhs.cols(); ++col) {
// Make right-hand side zero
constraints.emplace_back(lhs(row, col) - rhs(row, col));
if constexpr (!EigenMatrixLike<LHS> && !EigenMatrixLike<RHS>) {
constraints.emplace_back(lhs[row, col] - rhs[row, col]);
} else if constexpr (!EigenMatrixLike<LHS> && EigenMatrixLike<RHS>) {
constraints.emplace_back(lhs[row, col] - rhs(row, col));
} else if constexpr (EigenMatrixLike<LHS> && !EigenMatrixLike<RHS>) {
constraints.emplace_back(lhs(row, col) - rhs[row, col]);
}
}
}
@@ -843,7 +857,7 @@ struct InequalityConstraints {
///
/// @param inequality_constraints The list of InequalityConstraints to
/// concatenate.
InequalityConstraints( // NOLINT
InequalityConstraints(
std::initializer_list<InequalityConstraints> inequality_constraints) {
for (const auto& elem : inequality_constraints) {
constraints.insert(constraints.end(), elem.constraints.begin(),

94
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/autodiff/variable_block.hpp vendored
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@@ -49,7 +49,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) = values(row, col);
(*this)[row, col] = values[row, col];
}
}
}
@@ -80,7 +80,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) = values(row, col);
(*this)[row, col] = values[row, col];
}
}
}
@@ -135,7 +135,7 @@ class VariableBlock : public SleipnirBase {
VariableBlock<Mat>& operator=(ScalarLike auto value) {
slp_assert(rows() == 1 && cols() == 1);
(*this)(0, 0) = value;
(*this)[0, 0] = value;
return *this;
}
@@ -148,7 +148,7 @@ class VariableBlock : public SleipnirBase {
void set_value(Scalar value) {
slp_assert(rows() == 1 && cols() == 1);
(*this)(0, 0).set_value(value);
(*this)[0, 0].set_value(value);
}
/// Assigns an Eigen matrix to the block.
@@ -161,7 +161,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) = values(row, col);
(*this)[row, col] = values(row, col);
}
}
@@ -178,7 +178,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col).set_value(values(row, col));
(*this)[row, col].set_value(values(row, col));
}
}
}
@@ -192,7 +192,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) = values(row, col);
(*this)[row, col] = values[row, col];
}
}
return *this;
@@ -207,7 +207,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) = std::move(values(row, col));
(*this)[row, col] = std::move(values[row, col]);
}
}
return *this;
@@ -218,13 +218,13 @@ class VariableBlock : public SleipnirBase {
/// @param row The scalar subblock's row.
/// @param col The scalar subblock's column.
/// @return A scalar subblock at the given row and column.
Variable<Scalar>& operator()(int row, int col)
Variable<Scalar>& operator[](int row, int col)
requires(!std::is_const_v<Mat>)
{
slp_assert(row >= 0 && row < rows());
slp_assert(col >= 0 && col < cols());
return (*m_mat)(m_row_slice.start + row * m_row_slice.step,
m_col_slice.start + col * m_col_slice.step);
return (*m_mat)[m_row_slice.start + row * m_row_slice.step,
m_col_slice.start + col * m_col_slice.step];
}
/// Returns a scalar subblock at the given row and column.
@@ -232,11 +232,11 @@ class VariableBlock : public SleipnirBase {
/// @param row The scalar subblock's row.
/// @param col The scalar subblock's column.
/// @return A scalar subblock at the given row and column.
const Variable<Scalar>& operator()(int row, int col) const {
const Variable<Scalar>& operator[](int row, int col) const {
slp_assert(row >= 0 && row < rows());
slp_assert(col >= 0 && col < cols());
return (*m_mat)(m_row_slice.start + row * m_row_slice.step,
m_col_slice.start + col * m_col_slice.step);
return (*m_mat)[m_row_slice.start + row * m_row_slice.step,
m_col_slice.start + col * m_col_slice.step];
}
/// Returns a scalar subblock at the given index.
@@ -247,7 +247,7 @@ class VariableBlock : public SleipnirBase {
requires(!std::is_const_v<Mat>)
{
slp_assert(index >= 0 && index < rows() * cols());
return (*this)(index / cols(), index % cols());
return (*this)[index / cols(), index % cols()];
}
/// Returns a scalar subblock at the given index.
@@ -256,7 +256,7 @@ class VariableBlock : public SleipnirBase {
/// @return A scalar subblock at the given index.
const Variable<Scalar>& operator[](int index) const {
slp_assert(index >= 0 && index < rows() * cols());
return (*this)(index / cols(), index % cols());
return (*this)[index / cols(), index % cols()];
}
/// Returns a block of the variable matrix.
@@ -272,8 +272,8 @@ class VariableBlock : public SleipnirBase {
slp_assert(col_offset >= 0 && col_offset <= cols());
slp_assert(block_rows >= 0 && block_rows <= rows() - row_offset);
slp_assert(block_cols >= 0 && block_cols <= cols() - col_offset);
return (*this)({row_offset, row_offset + block_rows, 1},
{col_offset, col_offset + block_cols, 1});
return (*this)[Slice{row_offset, row_offset + block_rows, 1},
Slice{col_offset, col_offset + block_cols, 1}];
}
/// Returns a block slice of the variable matrix.
@@ -289,8 +289,8 @@ class VariableBlock : public SleipnirBase {
slp_assert(col_offset >= 0 && col_offset <= cols());
slp_assert(block_rows >= 0 && block_rows <= rows() - row_offset);
slp_assert(block_cols >= 0 && block_cols <= cols() - col_offset);
return (*this)({row_offset, row_offset + block_rows, 1},
{col_offset, col_offset + block_cols, 1});
return (*this)[Slice{row_offset, row_offset + block_rows, 1},
Slice{col_offset, col_offset + block_cols, 1}];
}
/// Returns a slice of the variable matrix.
@@ -298,10 +298,10 @@ class VariableBlock : public SleipnirBase {
/// @param row_slice The row slice.
/// @param col_slice The column slice.
/// @return A slice of the variable matrix.
VariableBlock<Mat> operator()(Slice row_slice, Slice col_slice) {
VariableBlock<Mat> operator[](Slice row_slice, Slice col_slice) {
int row_slice_length = row_slice.adjust(m_row_slice_length);
int col_slice_length = col_slice.adjust(m_col_slice_length);
return (*this)(row_slice, row_slice_length, col_slice, col_slice_length);
return (*this)[row_slice, row_slice_length, col_slice, col_slice_length];
}
/// Returns a slice of the variable matrix.
@@ -309,11 +309,11 @@ class VariableBlock : public SleipnirBase {
/// @param row_slice The row slice.
/// @param col_slice The column slice.
/// @return A slice of the variable matrix.
const VariableBlock<const Mat> operator()(Slice row_slice,
const VariableBlock<const Mat> operator[](Slice row_slice,
Slice col_slice) const {
int row_slice_length = row_slice.adjust(m_row_slice_length);
int col_slice_length = col_slice.adjust(m_col_slice_length);
return (*this)(row_slice, row_slice_length, col_slice, col_slice_length);
return (*this)[row_slice, row_slice_length, col_slice, col_slice_length];
}
/// Returns a slice of the variable matrix.
@@ -326,7 +326,7 @@ class VariableBlock : public SleipnirBase {
/// @param col_slice The column slice.
/// @param col_slice_length The column slice length.
/// @return A slice of the variable matrix.
VariableBlock<Mat> operator()(Slice row_slice, int row_slice_length,
VariableBlock<Mat> operator[](Slice row_slice, int row_slice_length,
Slice col_slice, int col_slice_length) {
return VariableBlock{
*m_mat,
@@ -350,7 +350,7 @@ class VariableBlock : public SleipnirBase {
/// @param col_slice The column slice.
/// @param col_slice_length The column slice length.
/// @return A slice of the variable matrix.
const VariableBlock<const Mat> operator()(Slice row_slice,
const VariableBlock<const Mat> operator[](Slice row_slice,
int row_slice_length,
Slice col_slice,
int col_slice_length) const {
@@ -438,9 +438,13 @@ class VariableBlock : public SleipnirBase {
for (int j = 0; j < rhs.cols(); ++j) {
Variable sum{Scalar(0)};
for (int k = 0; k < cols(); ++k) {
sum += lhs_old_row[k] * rhs(k, j);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
sum += lhs_old_row[k] * rhs(k, j);
} else {
sum += lhs_old_row[k] * rhs[k, j];
}
}
(*this)(i, j) = sum;
(*this)[i, j] = sum;
}
}
@@ -454,7 +458,7 @@ class VariableBlock : public SleipnirBase {
VariableBlock<Mat>& operator*=(const ScalarLike auto& rhs) {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) *= rhs;
(*this)[row, col] *= rhs;
}
}
@@ -470,7 +474,11 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) /= rhs(0, 0);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
(*this)[row, col] /= rhs(0, 0);
} else {
(*this)[row, col] /= rhs[0, 0];
}
}
}
@@ -484,7 +492,7 @@ class VariableBlock : public SleipnirBase {
VariableBlock<Mat>& operator/=(const ScalarLike auto& rhs) {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) /= rhs;
(*this)[row, col] /= rhs;
}
}
@@ -500,7 +508,11 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) += rhs(row, col);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
(*this)[row, col] += rhs(row, col);
} else {
(*this)[row, col] += rhs[row, col];
}
}
}
@@ -516,7 +528,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) += rhs;
(*this)[row, col] += rhs;
}
}
@@ -532,7 +544,11 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) -= rhs(row, col);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
(*this)[row, col] -= rhs(row, col);
} else {
(*this)[row, col] -= rhs[row, col];
}
}
}
@@ -548,7 +564,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) -= rhs;
(*this)[row, col] -= rhs;
}
}
@@ -559,7 +575,7 @@ class VariableBlock : public SleipnirBase {
// NOLINTNEXTLINE (google-explicit-constructor)
operator Variable<Scalar>() const {
slp_assert(rows() == 1 && cols() == 1);
return (*this)(0, 0);
return (*this)[0, 0];
}
/// Returns the transpose of the variable matrix.
@@ -570,7 +586,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
result(col, row) = (*this)(row, col);
result[col, row] = (*this)[row, col];
}
}
@@ -592,7 +608,7 @@ class VariableBlock : public SleipnirBase {
/// @param row The row of the element to return.
/// @param col The column of the element to return.
/// @return An element of the variable matrix.
Scalar value(int row, int col) { return (*this)(row, col).value(); }
Scalar value(int row, int col) { return (*this)[row, col].value(); }
/// Returns an element of the variable block.
///
@@ -630,7 +646,7 @@ class VariableBlock : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
result(row, col) = unary_op((*this)(row, col));
result[row, col] = unary_op((*this)[row, col]);
}
}

173
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/autodiff/variable_matrix.hpp vendored
View File

@@ -204,7 +204,7 @@ class VariableMatrix : public SleipnirBase {
m_storage.reserve(rows() * cols());
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
m_storage.emplace_back(values(row, col));
m_storage.emplace_back(values[row, col]);
}
}
}
@@ -218,7 +218,7 @@ class VariableMatrix : public SleipnirBase {
m_storage.reserve(rows() * cols());
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
m_storage.emplace_back(values(row, col));
m_storage.emplace_back(values[row, col]);
}
}
}
@@ -262,7 +262,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < values.rows(); ++row) {
for (int col = 0; col < values.cols(); ++col) {
(*this)(row, col) = values(row, col);
(*this)[row, col] = values(row, col);
}
}
@@ -278,7 +278,7 @@ class VariableMatrix : public SleipnirBase {
VariableMatrix& operator=(ScalarLike auto value) {
slp_assert(rows() == 1 && cols() == 1);
(*this)(0, 0) = value;
(*this)[0, 0] = value;
return *this;
}
@@ -293,7 +293,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < values.rows(); ++row) {
for (int col = 0; col < values.cols(); ++col) {
(*this)(row, col).set_value(values(row, col));
(*this)[row, col].set_value(values(row, col));
}
}
}
@@ -303,7 +303,7 @@ class VariableMatrix : public SleipnirBase {
/// @param row The row.
/// @param col The column.
/// @return The element at the given row and column.
Variable<Scalar>& operator()(int row, int col) {
Variable<Scalar>& operator[](int row, int col) {
slp_assert(row >= 0 && row < rows());
slp_assert(col >= 0 && col < cols());
return m_storage[row * cols() + col];
@@ -314,7 +314,7 @@ class VariableMatrix : public SleipnirBase {
/// @param row The row.
/// @param col The column.
/// @return The element at the given row and column.
const Variable<Scalar>& operator()(int row, int col) const {
const Variable<Scalar>& operator[](int row, int col) const {
slp_assert(row >= 0 && row < rows());
slp_assert(col >= 0 && col < cols());
return m_storage[row * cols() + col];
@@ -377,7 +377,7 @@ class VariableMatrix : public SleipnirBase {
/// @param row_slice The row slice.
/// @param col_slice The column slice.
/// @return A slice of the variable matrix.
VariableBlock<VariableMatrix> operator()(Slice row_slice, Slice col_slice) {
VariableBlock<VariableMatrix> operator[](Slice row_slice, Slice col_slice) {
int row_slice_length = row_slice.adjust(rows());
int col_slice_length = col_slice.adjust(cols());
return VariableBlock{*this, std::move(row_slice), row_slice_length,
@@ -389,7 +389,7 @@ class VariableMatrix : public SleipnirBase {
/// @param row_slice The row slice.
/// @param col_slice The column slice.
/// @return A slice of the variable matrix.
const VariableBlock<const VariableMatrix> operator()(Slice row_slice,
const VariableBlock<const VariableMatrix> operator[](Slice row_slice,
Slice col_slice) const {
int row_slice_length = row_slice.adjust(rows());
int col_slice_length = col_slice.adjust(cols());
@@ -407,7 +407,7 @@ class VariableMatrix : public SleipnirBase {
/// @param col_slice The column slice.
/// @param col_slice_length The column slice length.
/// @return A slice of the variable matrix.
VariableBlock<VariableMatrix> operator()(Slice row_slice,
VariableBlock<VariableMatrix> operator[](Slice row_slice,
int row_slice_length,
Slice col_slice,
int col_slice_length) {
@@ -425,7 +425,7 @@ class VariableMatrix : public SleipnirBase {
/// @param col_slice The column slice.
/// @param col_slice_length The column slice length.
/// @return A slice of the variable matrix.
const VariableBlock<const VariableMatrix> operator()(
const VariableBlock<const VariableMatrix> operator[](
Slice row_slice, int row_slice_length, Slice col_slice,
int col_slice_length) const {
return VariableBlock{*this, std::move(row_slice), row_slice_length,
@@ -503,17 +503,13 @@ class VariableMatrix : public SleipnirBase {
VariableMatrix<Scalar> result(detail::empty, lhs.rows(), rhs.cols());
#if __GNUC__ >= 12
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
#endif
for (int i = 0; i < lhs.rows(); ++i) {
for (int j = 0; j < rhs.cols(); ++j) {
Variable sum{Scalar(0)};
for (int k = 0; k < lhs.cols(); ++k) {
sum += lhs(i, k) * rhs(k, j);
sum += lhs(i, k) * rhs[k, j];
}
result(i, j) = sum;
result[i, j] = sum;
}
}
@@ -534,9 +530,9 @@ class VariableMatrix : public SleipnirBase {
for (int j = 0; j < rhs.cols(); ++j) {
Variable sum{Scalar(0)};
for (int k = 0; k < lhs.cols(); ++k) {
sum += lhs(i, k) * rhs(k, j);
sum += lhs[i, k] * rhs(k, j);
}
result(i, j) = sum;
result[i, j] = sum;
}
}
@@ -557,14 +553,11 @@ class VariableMatrix : public SleipnirBase {
for (int j = 0; j < rhs.cols(); ++j) {
Variable sum{Scalar(0)};
for (int k = 0; k < lhs.cols(); ++k) {
sum += lhs(i, k) * rhs(k, j);
sum += lhs[i, k] * rhs[k, j];
}
result(i, j) = sum;
result[i, j] = sum;
}
}
#if __GNUC__ >= 12
#pragma GCC diagnostic pop
#endif
return result;
}
@@ -580,7 +573,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) * rhs;
result[row, col] = lhs(row, col) * rhs;
}
}
@@ -597,7 +590,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) * rhs;
result[row, col] = lhs[row, col] * rhs;
}
}
@@ -615,7 +608,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = rhs(row, col) * lhs;
result[row, col] = rhs(row, col) * lhs;
}
}
@@ -632,7 +625,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = rhs(row, col) * lhs;
result[row, col] = rhs[row, col] * lhs;
}
}
@@ -651,9 +644,13 @@ class VariableMatrix : public SleipnirBase {
for (int j = 0; j < rhs.cols(); ++j) {
Variable sum{Scalar(0)};
for (int k = 0; k < cols(); ++k) {
sum += lhs_old_row[k] * rhs(k, j);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
sum += lhs_old_row[k] * rhs(k, j);
} else {
sum += lhs_old_row[k] * rhs[k, j];
}
}
(*this)(i, j) = sum;
(*this)[i, j] = sum;
}
}
@@ -667,7 +664,7 @@ class VariableMatrix : public SleipnirBase {
VariableMatrix& operator*=(const ScalarLike auto& rhs) {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) *= rhs;
(*this)[row, col] *= rhs;
}
}
@@ -686,7 +683,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) / rhs;
result[row, col] = lhs(row, col) / rhs;
}
}
@@ -705,7 +702,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) / rhs;
result[row, col] = lhs[row, col] / rhs;
}
}
@@ -724,7 +721,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) / rhs;
result[row, col] = lhs[row, col] / rhs;
}
}
@@ -738,7 +735,7 @@ class VariableMatrix : public SleipnirBase {
VariableMatrix& operator/=(const ScalarLike auto& rhs) {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) /= rhs;
(*this)[row, col] /= rhs;
}
}
@@ -758,7 +755,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) + rhs(row, col);
result[row, col] = lhs(row, col) + rhs[row, col];
}
}
@@ -778,7 +775,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) + rhs(row, col);
result[row, col] = lhs[row, col] + rhs(row, col);
}
}
@@ -798,7 +795,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) + rhs(row, col);
result[row, col] = lhs[row, col] + rhs[row, col];
}
}
@@ -814,7 +811,11 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) += rhs(row, col);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
(*this)[row, col] += rhs(row, col);
} else {
(*this)[row, col] += rhs[row, col];
}
}
}
@@ -830,7 +831,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) += rhs;
(*this)[row, col] += rhs;
}
}
@@ -850,7 +851,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) - rhs(row, col);
result[row, col] = lhs(row, col) - rhs[row, col];
}
}
@@ -870,7 +871,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) - rhs(row, col);
result[row, col] = lhs[row, col] - rhs(row, col);
}
}
@@ -890,7 +891,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = lhs(row, col) - rhs(row, col);
result[row, col] = lhs[row, col] - rhs[row, col];
}
}
@@ -906,7 +907,11 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) -= rhs(row, col);
if constexpr (EigenMatrixLike<decltype(rhs)>) {
(*this)[row, col] -= rhs(row, col);
} else {
(*this)[row, col] -= rhs[row, col];
}
}
}
@@ -922,7 +927,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
(*this)(row, col) -= rhs;
(*this)[row, col] -= rhs;
}
}
@@ -938,7 +943,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < result.rows(); ++row) {
for (int col = 0; col < result.cols(); ++col) {
result(row, col) = -lhs(row, col);
result[row, col] = -lhs[row, col];
}
}
@@ -949,7 +954,7 @@ class VariableMatrix : public SleipnirBase {
// NOLINTNEXTLINE (google-explicit-constructor)
operator Variable<Scalar>() const {
slp_assert(rows() == 1 && cols() == 1);
return (*this)(0, 0);
return (*this)[0, 0];
}
/// Returns the transpose of the variable matrix.
@@ -960,7 +965,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
result(col, row) = (*this)(row, col);
result[col, row] = (*this)[row, col];
}
}
@@ -982,7 +987,7 @@ class VariableMatrix : public SleipnirBase {
/// @param row The row of the element to return.
/// @param col The column of the element to return.
/// @return An element of the variable matrix.
Scalar value(int row, int col) { return (*this)(row, col).value(); }
Scalar value(int row, int col) { return (*this)[row, col].value(); }
/// Returns an element of the variable matrix.
///
@@ -1017,7 +1022,7 @@ class VariableMatrix : public SleipnirBase {
for (int row = 0; row < rows(); ++row) {
for (int col = 0; col < cols(); ++col) {
result(row, col) = unary_op((*this)(row, col));
result[row, col] = unary_op((*this)[row, col]);
}
}
@@ -1270,7 +1275,7 @@ VariableMatrix<Scalar> cwise_reduce(
for (int row = 0; row < lhs.rows(); ++row) {
for (int col = 0; col < lhs.cols(); ++col) {
result(row, col) = binary_op(lhs(row, col), rhs(row, col));
result[row, col] = binary_op(lhs[row, col], rhs[row, col]);
}
}
@@ -1403,17 +1408,17 @@ VariableMatrix<Scalar> solve(const VariableMatrix<Scalar>& A,
if (A.rows() == 1 && A.cols() == 1) {
// Compute optimal inverse instead of using Eigen's general solver
return B(0, 0) / A(0, 0);
return B[0, 0] / A[0, 0];
} else if (A.rows() == 2 && A.cols() == 2) {
// Compute optimal inverse instead of using Eigen's general solver
//
// [a b]⁻¹ ___1___ [ d −b]
// [c d] = ad − bc [−c a]
const auto& a = A(0, 0);
const auto& b = A(0, 1);
const auto& c = A(1, 0);
const auto& d = A(1, 1);
const auto& a = A[0, 0];
const auto& b = A[0, 1];
const auto& c = A[1, 0];
const auto& d = A[1, 1];
VariableMatrix adj_A{{d, -b}, {-c, a}};
auto det_A = a * d - b * c;
@@ -1430,15 +1435,15 @@ VariableMatrix<Scalar> solve(const VariableMatrix<Scalar>& A,
//
// https://www.wolframalpha.com/input?i=inverse+%7B%7Ba%2C+b%2C+c%7D%2C+%7Bd%2C+e%2C+f%7D%2C+%7Bg%2C+h%2C+i%7D%7D
const auto& a = A(0, 0);
const auto& b = A(0, 1);
const auto& c = A(0, 2);
const auto& d = A(1, 0);
const auto& e = A(1, 1);
const auto& f = A(1, 2);
const auto& g = A(2, 0);
const auto& h = A(2, 1);
const auto& i = A(2, 2);
const auto& a = A[0, 0];
const auto& b = A[0, 1];
const auto& c = A[0, 2];
const auto& d = A[1, 0];
const auto& e = A[1, 1];
const auto& f = A[1, 2];
const auto& g = A[2, 0];
const auto& h = A[2, 1];
const auto& i = A[2, 2];
auto ae = a * e;
auto af = a * f;
@@ -1478,22 +1483,22 @@ VariableMatrix<Scalar> solve(const VariableMatrix<Scalar>& A,
//
// https://www.wolframalpha.com/input?i=inverse+%7B%7Ba%2C+b%2C+c%2C+d%7D%2C+%7Be%2C+f%2C+g%2C+h%7D%2C+%7Bi%2C+j%2C+k%2C+l%7D%2C+%7Bm%2C+n%2C+o%2C+p%7D%7D
const auto& a = A(0, 0);
const auto& b = A(0, 1);
const auto& c = A(0, 2);
const auto& d = A(0, 3);
const auto& e = A(1, 0);
const auto& f = A(1, 1);
const auto& g = A(1, 2);
const auto& h = A(1, 3);
const auto& i = A(2, 0);
const auto& j = A(2, 1);
const auto& k = A(2, 2);
const auto& l = A(2, 3);
const auto& m = A(3, 0);
const auto& n = A(3, 1);
const auto& o = A(3, 2);
const auto& p = A(3, 3);
const auto& a = A[0, 0];
const auto& b = A[0, 1];
const auto& c = A[0, 2];
const auto& d = A[0, 3];
const auto& e = A[1, 0];
const auto& f = A[1, 1];
const auto& g = A[1, 2];
const auto& h = A[1, 3];
const auto& i = A[2, 0];
const auto& j = A[2, 1];
const auto& k = A[2, 2];
const auto& l = A[2, 3];
const auto& m = A[3, 0];
const auto& n = A[3, 1];
const auto& o = A[3, 2];
const auto& p = A[3, 3];
auto afk = a * f * k;
auto afl = a * f * l;
@@ -1624,14 +1629,14 @@ VariableMatrix<Scalar> solve(const VariableMatrix<Scalar>& A,
MatrixXv eigen_A{A.rows(), A.cols()};
for (int row = 0; row < A.rows(); ++row) {
for (int col = 0; col < A.cols(); ++col) {
eigen_A(row, col) = A(row, col);
eigen_A(row, col) = A[row, col];
}
}
MatrixXv eigen_B{B.rows(), B.cols()};
for (int row = 0; row < B.rows(); ++row) {
for (int col = 0; col < B.cols(); ++col) {
eigen_B(row, col) = B(row, col);
eigen_B(row, col) = B[row, col];
}
}
@@ -1640,7 +1645,7 @@ VariableMatrix<Scalar> solve(const VariableMatrix<Scalar>& A,
VariableMatrix<Scalar> X{detail::empty, A.cols(), B.cols()};
for (int row = 0; row < X.rows(); ++row) {
for (int col = 0; col < X.cols(); ++col) {
X(row, col) = eigen_X(row, col);
X[row, col] = eigen_X(row, col);
}
}

14
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/optimization/ocp.hpp vendored
View File

@@ -123,7 +123,7 @@ class OCP : public Problem<Scalar> {
if (timestep_method == TimestepMethod::FIXED) {
m_DT = VariableMatrix<Scalar>{1, m_num_steps + 1};
for (int i = 0; i < num_steps + 1; ++i) {
m_DT(0, i) = dt.count();
m_DT[0, i] = dt.count();
}
} else if (timestep_method == TimestepMethod::VARIABLE_SINGLE) {
Variable single_dt = this->decision_variable();
@@ -132,12 +132,12 @@ class OCP : public Problem<Scalar> {
// Set the member variable matrix to track the decision variable
m_DT = VariableMatrix<Scalar>{1, m_num_steps + 1};
for (int i = 0; i < num_steps + 1; ++i) {
m_DT(0, i) = single_dt;
m_DT[0, i] = single_dt;
}
} else if (timestep_method == TimestepMethod::VARIABLE) {
m_DT = this->decision_variable(1, m_num_steps + 1);
for (int i = 0; i < num_steps + 1; ++i) {
m_DT(0, i).set_value(dt.count());
m_DT[0, i].set_value(dt.count());
}
}
@@ -206,7 +206,7 @@ class OCP : public Problem<Scalar> {
for (int i = 0; i < m_num_steps + 1; ++i) {
auto x = X().col(i);
auto u = U().col(i);
auto dt = this->dt()(0, i);
auto dt = this->dt()[0, i];
callback(time, x, u, dt);
time += dt;
@@ -326,7 +326,7 @@ class OCP : public Problem<Scalar> {
// Derivation at https://mec560sbu.github.io/2016/09/30/direct_collocation/
for (int i = 0; i < m_num_steps; ++i) {
Variable h = dt()(0, i);
Variable h = dt()[0, i];
auto& f = m_dynamics;
@@ -363,7 +363,7 @@ class OCP : public Problem<Scalar> {
auto x_begin = X().col(i);
auto x_end = X().col(i + 1);
auto u = U().col(i);
Variable dt = this->dt()(0, i);
Variable dt = this->dt()[0, i];
if (m_dynamics_type == DynamicsType::EXPLICIT_ODE) {
this->subject_to(
@@ -386,7 +386,7 @@ class OCP : public Problem<Scalar> {
auto x_begin = X().col(i);
auto x_end = X().col(i + 1);
auto u = U().col(i);
Variable dt = this->dt()(0, i);
Variable dt = this->dt()[0, i];
if (m_dynamics_type == DynamicsType::EXPLICIT_ODE) {
x_end = rk4<const decltype(m_dynamics)&, VariableMatrix<Scalar>,

24
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/optimization/problem.hpp vendored
View File

@@ -15,7 +15,6 @@
#include <Eigen/Core>
#include <Eigen/SparseCore>
#include <fmt/chrono.h>
#include <gch/small_vector.hpp>
#include "sleipnir/autodiff/expression_type.hpp"
@@ -38,7 +37,6 @@
#include "sleipnir/util/profiler.hpp"
#include "sleipnir/util/spy.hpp"
#include "sleipnir/util/symbol_exports.hpp"
#include "sleipnir/util/to_underlying.hpp"
namespace slp {
@@ -98,7 +96,7 @@ class Problem {
for (int row = 0; row < rows; ++row) {
for (int col = 0; col < cols; ++col) {
m_decision_variables.emplace_back();
vars(row, col) = m_decision_variables.back();
vars[row, col] = m_decision_variables.back();
}
}
@@ -133,8 +131,8 @@ class Problem {
for (int row = 0; row < rows; ++row) {
for (int col = 0; col <= row; ++col) {
m_decision_variables.emplace_back();
vars(row, col) = m_decision_variables.back();
vars(col, row) = m_decision_variables.back();
vars[row, col] = m_decision_variables.back();
vars[col, row] = m_decision_variables.back();
}
}
@@ -774,11 +772,11 @@ class Problem {
// Print problem structure
slp::println("\nProblem structure:");
slp::println(" ↳ {} cost function",
types[slp::to_underlying(cost_function_type())]);
types[std::to_underlying(cost_function_type())]);
slp::println(" ↳ {} equality constraints",
types[slp::to_underlying(equality_constraint_type())]);
types[std::to_underlying(equality_constraint_type())]);
slp::println(" ↳ {} inequality constraints",
types[slp::to_underlying(inequality_constraint_type())]);
types[std::to_underlying(inequality_constraint_type())]);
if (m_decision_variables.size() == 1) {
slp::print("\n1 decision variable\n");
@@ -790,13 +788,11 @@ class Problem {
[](const gch::small_vector<Variable<Scalar>>& constraints) {
std::array<size_t, 5> counts{};
for (const auto& constraint : constraints) {
++counts[slp::to_underlying(constraint.type())];
++counts[std::to_underlying(constraint.type())];
}
for (size_t i = 0; i < counts.size(); ++i) {
constexpr std::array names{"empty", "constant", "linear",
"quadratic", "nonlinear"};
const auto& count = counts[i];
const auto& name = names[i];
for (const auto& [count, name] :
std::views::zip(counts, std::array{"empty", "constant", "linear",
"quadratic", "nonlinear"})) {
if (count > 0) {
slp::println(" ↳ {} {}", count, name);
}

20
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/optimization/solver/exit_status.hpp vendored
View File

@@ -4,9 +4,8 @@
#include <stdint.h>
#include <fmt/base.h>
#include "sleipnir/util/unreachable.hpp"
#include <format>
#include <utility>
namespace slp {
@@ -46,16 +45,14 @@ enum class ExitStatus : int8_t {
} // namespace slp
// @cond Suppress Doxygen
/// Formatter for ExitStatus.
template <>
struct fmt::formatter<slp::ExitStatus> {
struct std::formatter<slp::ExitStatus> {
/// Parses format string.
///
/// @param ctx Format parse context.
/// @return Format parse context iterator.
constexpr auto parse(fmt::format_parse_context& ctx) {
constexpr auto parse(std::format_parse_context& ctx) {
return m_underlying.parse(ctx);
}
@@ -66,8 +63,7 @@ struct fmt::formatter<slp::ExitStatus> {
/// @param ctx Format context.
/// @return Format context iterator.
template <typename FmtContext>
constexpr auto format(const slp::ExitStatus& exit_status,
FmtContext& ctx) const {
auto format(const slp::ExitStatus& exit_status, FmtContext& ctx) const {
using enum slp::ExitStatus;
switch (exit_status) {
@@ -96,12 +92,10 @@ struct fmt::formatter<slp::ExitStatus> {
case TIMEOUT:
return m_underlying.format("timeout", ctx);
default:
slp::unreachable();
std::unreachable();
}
}
private:
fmt::formatter<const char*> m_underlying;
std::formatter<const char*> m_underlying;
};
// @endcond

4
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/optimization/solver/util/feasibility_restoration.hpp vendored
View File

@@ -96,8 +96,6 @@ compute_p_n(const Eigen::Vector<Scalar, Eigen::Dynamic>& c, Scalar ρ,
return {std::move(p), std::move(n)};
}
// @cond Suppress Doxygen
/// Finds the iterate that minimizes the constraint violation while not
/// deviating too far from the starting point. This is a fallback procedure when
/// the normal Sequential Quadratic Programming method fails to converge to a
@@ -626,8 +624,6 @@ ExitStatus feasibility_restoration(
}
}
// @endcond
} // namespace slp
#include "sleipnir/optimization/solver/interior_point.hpp"

22
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/optimization/solver/util/inertia.hpp vendored
View File

@@ -2,10 +2,10 @@
#pragma once
#include <format>
#include <limits>
#include <Eigen/Core>
#include <fmt/format.h>
namespace slp {
@@ -77,16 +77,14 @@ class Inertia {
} // namespace slp
// @cond Suppress Doxygen
/// Formatter for Inertia.
template <>
struct fmt::formatter<slp::Inertia> {
struct std::formatter<slp::Inertia> {
/// Parses format string.
///
/// @param ctx Format parse context.
/// @return Format parse context iterator.
constexpr auto parse(fmt::format_parse_context& ctx) {
constexpr auto parse(std::format_parse_context& ctx) {
return m_underlying.parse(ctx);
}
@@ -97,20 +95,18 @@ struct fmt::formatter<slp::Inertia> {
/// @param ctx Format context.
/// @return Format context iterator.
template <typename FmtContext>
constexpr auto format(const slp::Inertia& inertia, FmtContext& ctx) const {
auto format(const slp::Inertia& inertia, FmtContext& ctx) const {
auto out = ctx.out();
out = fmt::format_to(out, "(");
out = std::format_to(out, "(");
out = m_underlying.format(inertia.positive, ctx);
out = fmt::format_to(out, ", ");
out = std::format_to(out, ", ");
out = m_underlying.format(inertia.negative, ctx);
out = fmt::format_to(out, ", ");
out = std::format_to(out, ", ");
out = m_underlying.format(inertia.zero, ctx);
return fmt::format_to(out, ")");
return std::format_to(out, ")");
}
private:
fmt::formatter<int> m_underlying;
std::formatter<int> m_underlying;
};
// @endcond

5
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/util/assert.hpp vendored
View File

@@ -3,17 +3,16 @@
#pragma once
#ifdef SLEIPNIR_PYTHON
#include <format>
#include <source_location>
#include <stdexcept>
#include <fmt/format.h>
/// Throws an exception in Python.
#define slp_assert(condition) \
do { \
if (!(condition)) { \
auto location = std::source_location::current(); \
throw std::invalid_argument(fmt::format( \
throw std::invalid_argument(std::format( \
"{}:{}: {}: Assertion `{}' failed.", location.file_name(), \
location.line(), location.function_name(), #condition)); \
} \

27
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/util/print.hpp vendored
View File

@@ -4,48 +4,47 @@
#ifndef SLEIPNIR_DISABLE_DIAGNOSTICS
#include <cstdio>
#include <print>
#include <system_error>
#include <utility>
#include <fmt/base.h>
#endif
namespace slp {
#ifndef SLEIPNIR_DISABLE_DIAGNOSTICS
/// Wrapper around fmt::print() that squelches write failure exceptions.
/// Wrapper around std::print() that squelches write failure exceptions.
template <typename... T>
void print(fmt::format_string<T...> fmt, T&&... args) {
void print(std::format_string<T...> fmt, T&&... args) {
try {
fmt::print(fmt, std::forward<T>(args)...);
std::print(fmt, std::forward<T>(args)...);
} catch (const std::system_error&) {
}
}
/// Wrapper around fmt::print() that squelches write failure exceptions.
/// Wrapper around std::print() that squelches write failure exceptions.
template <typename... T>
void print(std::FILE* f, fmt::format_string<T...> fmt, T&&... args) {
void print(std::FILE* f, std::format_string<T...> fmt, T&&... args) {
try {
fmt::print(f, fmt, std::forward<T>(args)...);
std::print(f, fmt, std::forward<T>(args)...);
} catch (const std::system_error&) {
}
}
/// Wrapper around fmt::println() that squelches write failure exceptions.
/// Wrapper around std::println() that squelches write failure exceptions.
template <typename... T>
void println(fmt::format_string<T...> fmt, T&&... args) {
void println(std::format_string<T...> fmt, T&&... args) {
try {
fmt::println(fmt, std::forward<T>(args)...);
std::println(fmt, std::forward<T>(args)...);
} catch (const std::system_error&) {
}
}
/// Wrapper around fmt::println() that squelches write failure exceptions.
/// Wrapper around std::println() that squelches write failure exceptions.
template <typename... T>
void println(std::FILE* f, fmt::format_string<T...> fmt, T&&... args) {
void println(std::FILE* f, std::format_string<T...> fmt, T&&... args) {
try {
fmt::println(f, fmt, std::forward<T>(args)...);
std::println(f, fmt, std::forward<T>(args)...);
} catch (const std::system_error&) {
}
}

3
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/util/print_diagnostics.hpp vendored
View File

@@ -17,7 +17,6 @@
#include "sleipnir/util/print.hpp"
#include "sleipnir/util/profiler.hpp"
#include "sleipnir/util/to_underlying.hpp"
namespace slp {
@@ -231,7 +230,7 @@ void print_iteration_diagnostics(int iterations, IterationType type,
slp::println(
"│{:4} {:1} {:9.3f} {:10.4e} {:11.4e} {:10.4e} {:8.2e} {:8.2e} {:<5} "
"{:<5} {:8.2e} {:8.2e} {:8.2e} {:8.2e} {:2d}│",
iterations, ITERATION_TYPES[slp::to_underlying(type)], to_ms(time), error,
iterations, ITERATION_TYPES[std::to_underlying(type)], to_ms(time), error,
cost, infeasibility, complementarity, μ, power_of_10(δ), power_of_10(γ),
full_primal_step_inf_norm, full_dual_step_inf_norm, primal_α, dual_α,
backtracks);

3
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/util/spy.hpp vendored
View File

@@ -12,7 +12,6 @@
#include <string_view>
#include <Eigen/SparseCore>
#include <wpi/util/bit.hpp>
namespace slp {
@@ -107,7 +106,7 @@ class Spy {
/// @param num A 32-bit signed integer.
void write32le(int32_t num) {
if constexpr (std::endian::native != std::endian::little) {
num = wpi::util::byteswap(num);
num = std::byteswap(num);
}
m_file.write(reinterpret_cast<char*>(&num), sizeof(num));
}

14
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/util/to_underlying.hpp vendored
View File

@@ -1,14 +0,0 @@
// Copyright (c) Sleipnir contributors
#pragma once
#include <type_traits>
namespace slp {
template <typename Enum>
constexpr std::underlying_type_t<Enum> to_underlying(Enum e) noexcept {
return static_cast<std::underlying_type_t<Enum>>(e);
}
} // namespace slp

16
wpimath/src/main/native/thirdparty/sleipnir/include/sleipnir/util/unreachable.hpp vendored
View File

@@ -1,16 +0,0 @@
// Copyright (c) Sleipnir contributors
#pragma once
namespace slp {
[[noreturn]]
inline void unreachable() {
#if defined(_MSC_VER) && !defined(__clang__)
__assume(false);
#else
__builtin_unreachable();
#endif
}
} // namespace slp