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Remove -inl patterns in systems/analysis and move implementations to …
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#include "drake/systems/analysis/antiderivative_function.h" | ||
#include "drake/systems/analysis/antiderivative_function-inl.h" | ||
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#include "drake/common/default_scalars.h" | ||
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namespace drake { | ||
namespace systems { | ||
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DRAKE_DEFINE_CLASS_TEMPLATE_INSTANTIATIONS_ON_DEFAULT_NONSYMBOLIC_SCALARS( | ||
class AntiderivativeFunction); | ||
class drake::systems::AntiderivativeFunction) | ||
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} // namespace systems | ||
} // namespace drake |
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#include "drake/systems/analysis/bogacki_shampine3_integrator.h" | ||
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#include "drake/common/autodiff.h" | ||
#include <cmath> | ||
#include <stdexcept> | ||
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#include "drake/common/drake_assert.h" | ||
#include "drake/common/unused.h" | ||
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namespace drake { | ||
namespace systems { | ||
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/* | ||
* Bogacki-Shampine-specific initialization function. | ||
* @throws std::logic_error if *neither* the initial step size target nor the | ||
* maximum step size have been set before calling. | ||
*/ | ||
template <class T> | ||
void BogackiShampine3Integrator<T>::DoInitialize() { | ||
using std::isnan; | ||
const double kDefaultAccuracy = 1e-3; // Good for this particular integrator. | ||
const double kLoosestAccuracy = 1e-1; // Integrator specific. | ||
const double kMaxStepFraction = 0.1; // Fraction of max step size for | ||
// less aggressive first step. | ||
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// Set an artificial step size target, if not set already. | ||
if (isnan(this->get_initial_step_size_target())) { | ||
// Verify that maximum step size has been set. | ||
if (isnan(this->get_maximum_step_size())) | ||
throw std::logic_error("Neither initial step size target nor maximum " | ||
"step size has been set!"); | ||
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this->request_initial_step_size_target( | ||
this->get_maximum_step_size() * kMaxStepFraction); | ||
} | ||
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// Sets the working accuracy to a good value. | ||
double working_accuracy = this->get_target_accuracy(); | ||
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// If the user asks for accuracy that is looser than the loosest this | ||
// integrator can provide, use the integrator's loosest accuracy setting | ||
// instead. | ||
if (working_accuracy > kLoosestAccuracy) | ||
working_accuracy = kLoosestAccuracy; | ||
else if (isnan(working_accuracy)) | ||
working_accuracy = kDefaultAccuracy; | ||
this->set_accuracy_in_use(working_accuracy); | ||
} | ||
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template <class T> | ||
bool BogackiShampine3Integrator<T>::DoStep(const T& h) { | ||
using std::abs; | ||
Context<T>& context = *this->get_mutable_context(); | ||
const T t0 = context.get_time(); | ||
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// CAUTION: This is performance-sensitive inner loop code that uses dangerous | ||
// long-lived references into state and cache to avoid unnecessary copying and | ||
// cache invalidation. Be careful not to insert calls to methods that could | ||
// invalidate any of these references before they are used. | ||
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// We use Butcher tableau notation with labels for each coefficient: | ||
// 0 (c1) | | ||
// 1/2 (c2) | 1/2 (a21) | ||
// 3/4 (c3) | 0 (a31) 3/4 (a32) | ||
// 1 (c4) | 2/9 (a41) 1/3 (a42) 4/9 (a43) | ||
// --------------------------------------------------------------------------- | ||
// 2/9 (b1) 1/3 (b2) 4/9 (b3) 0 (b4) | ||
// 7/24 (d1) 1/4 (d2) 1/3 (d3) 1/8 (d4) | ||
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// Save the continuous state at t₀. | ||
context.get_continuous_state_vector().CopyToPreSizedVector(&save_xc0_); | ||
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// Evaluate the derivative at t₀, xc₀. | ||
derivs1_->get_mutable_vector().SetFrom( | ||
this->EvalTimeDerivatives(context).get_vector()); | ||
const VectorBase<T>& k1 = derivs1_->get_vector(); | ||
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// Cache: k1 references a *copy* of the derivative result so is immune | ||
// to subsequent evaluations. | ||
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// Compute the first intermediate state and derivative (i.e., Stage 2). | ||
// This call marks t- and xc-dependent cache entries out of date, including | ||
// the derivative cache entry. Note that xc is a live reference into the | ||
// context -- subsequent changes through that reference are unobservable so | ||
// will require manual out-of-date notifications. | ||
const double c2 = 1.0 / 2; | ||
const double a21 = 1.0 / 2; | ||
VectorBase<T>& xc = context.SetTimeAndGetMutableContinuousStateVector( | ||
t0 + c2 * h); | ||
xc.PlusEqScaled(a21 * h, k1); | ||
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// Evaluate the derivative (denoted k2) at t₀ + c2 * h, xc₀ + a21 * h * k1. | ||
derivs2_->get_mutable_vector().SetFrom( | ||
this->EvalTimeDerivatives(context).get_vector()); | ||
const VectorBase<T>& k2 = derivs2_->get_vector(); // xcdot⁽ᵃ⁾ | ||
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// Cache: k2 references a *copy* of the derivative result so is immune | ||
// to subsequent evaluations. | ||
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// Compute the second intermediate state and derivative (i.e., Stage 3). | ||
const double c3 = 3.0 / 4; | ||
const double a31 = 0.0; | ||
const double a32 = 3.0 / 4; | ||
// This call marks t- and xc-dependent cache entries out of date, including | ||
// the derivative cache entry. (We already have the xc reference but must | ||
// issue the out-of-date notification here since we're about to change it.) | ||
context.SetTimeAndNoteContinuousStateChange(t0 + c3 * h); | ||
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// Evaluate the derivative (denoted k3) at t₀ + c3 * h, | ||
// xc₀ + a31 * h * k1 + a32 * h * k2. | ||
// Note that a31 is zero, so we leave that term out. | ||
unused(a31); | ||
xc.SetFromVector(save_xc0_); // Restore xc ← xc₀. | ||
xc.PlusEqScaled({{a32 * h, k2}}); | ||
derivs3_->get_mutable_vector().SetFrom( | ||
this->EvalTimeDerivatives(context).get_vector()); | ||
const VectorBase<T>& k3 = derivs3_->get_vector(); | ||
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// Compute the propagated solution (we're able to do this because b1 = a41, | ||
// b2 = a42, b3 = a43, and b4 = 0). | ||
const double c4 = 1.0; | ||
const double a41 = 2.0 / 9; | ||
const double a42 = 1.0 / 3; | ||
const double a43 = 4.0 / 9; | ||
// This call marks t- and xc-dependent cache entries out of date, including | ||
// the derivative cache entry. (We already have the xc reference but must | ||
// issue the out-of-date notification here since we're about to change it.) | ||
context.SetTimeAndNoteContinuousStateChange(t0 + c4 * h); | ||
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// Evaluate the derivative (denoted k4) at t₀ + c4 * h, xc₀ + a41 * h * k1 + | ||
// a42 * h * k2 + a43 * h * k3. This will be used to compute the second | ||
// order solution. | ||
xc.SetFromVector(save_xc0_); // Restore xc ← xc₀. | ||
xc.PlusEqScaled({{a41 * h, k1}, {a42 * h, k2}, {a43 * h, k3}}); | ||
const ContinuousState<T>& derivs4 = this->EvalTimeDerivatives(context); | ||
const VectorBase<T>& k4 = derivs4.get_vector(); | ||
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// WARNING: k4 is a live reference into the cache. Be careful of adding | ||
// code below that modifies the context until after k4 is used below. In fact, | ||
// it is best not to modify the context from here on out, as modifying the | ||
// context will effectively destroy the FSAL benefit that this integrator | ||
// provides. | ||
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// Compute the second order solution used for the error estimate and then | ||
// the error estimate itself. The first part of this formula (the part that | ||
// uses the d coefficients) computes the second error solution. The last part | ||
// subtracts the third order propagated solution from that second order | ||
// solution, thereby yielding the error estimate. | ||
const double d1 = 7.0 / 24; | ||
const double d2 = 1.0 / 4; | ||
const double d3 = 1.0 / 3; | ||
const double d4 = 1.0 / 8; | ||
err_est_vec_->SetZero(); | ||
err_est_vec_->PlusEqScaled({{(a41 - d1) * h, k1}, | ||
{(a42 - d2) * h, k2}, | ||
{(a43 - d3) * h, k3}, | ||
{(-d4) * h, k4}}); | ||
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// If the size of the system has changed, the error estimate will no longer | ||
// be sized correctly. Verify that the error estimate is the correct size. | ||
DRAKE_DEMAND(this->get_error_estimate()->size() == xc.size()); | ||
this->get_mutable_error_estimate()->SetFromVector(err_est_vec_-> | ||
CopyToVector().cwiseAbs()); | ||
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// Bogacki-Shampine always succeeds in taking its desired step. | ||
return true; | ||
} | ||
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} // namespace systems | ||
} // namespace drake | ||
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DRAKE_DEFINE_CLASS_TEMPLATE_INSTANTIATIONS_ON_DEFAULT_NONSYMBOLIC_SCALARS( | ||
class ::drake::systems::BogackiShampine3Integrator) | ||
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