Trait argmin::prelude::ArgminSolver

pub trait ArgminSolver: ArgminIter {
    fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>;
    fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>;
    fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>;
    fn modify(
        &self, 
        param: &Self::Param, 
        extent: f64
    ) -> Result<Self::Param, Error>;
    fn cur_param(&self) -> Self::Param;
    fn cur_grad(&self) -> Self::Param;
    fn cur_hessian(&self) -> Self::Hessian;
    fn set_cur_param(&mut self, param: Self::Param);
    fn set_cur_grad(&mut self, grad: Self::Param);
    fn set_cur_hessian(&mut self, hessian: Self::Hessian);
    fn set_best_param(&mut self, param: Self::Param);
    fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>;
    fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>;
    fn result(&self) -> ArgminResult<Self::Param>;
    fn set_termination_reason(&mut self, reason: TerminationReason);
    fn terminate(&mut self) -> TerminationReason;
    fn set_max_iters(&mut self, iters: u64);
    fn max_iters(&self) -> u64;
    fn cur_iter(&self) -> u64;
    fn increment_iter(&mut self);
    fn cur_cost(&self) -> f64;
    fn set_cur_cost(&mut self, cost: f64);
    fn best_cost(&self) -> f64;
    fn set_best_cost(&mut self, cost: f64);
    fn set_target_cost(&mut self, cost: f64);
    fn add_logger(&mut self, logger: Arc<dyn ArgminLog + 'static>);
    fn add_writer(
        &mut self, 
        writer: Arc<dyn ArgminWrite<Param = Self::Param> + 'static>
    );
    fn base_reset(&mut self);
    fn increment_cost_func_count(&mut self);
    fn increase_cost_func_count(&mut self, count: u64);
    fn cost_func_count(&self) -> u64;
    fn increment_grad_func_count(&mut self);
    fn increase_grad_func_count(&mut self, count: u64);
    fn grad_func_count(&self) -> u64;
    fn increment_hessian_func_count(&mut self);
    fn increase_hessian_func_count(&mut self, count: u64);
    fn hessian_func_count(&self) -> u64;
}

Defines the interface to a solver. Usually, there is no need to implement this manually, use the argmin_derive crate instead.

Required methods

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

apply cost function or operator to a parameter vector

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

compute the gradient for a parameter vector

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

compute the hessian for a parameter vector

fn modify(&self, param: &Self::Param, extent: f64) -> Result<Self::Param, Error>

modify the parameter vector

fn cur_param(&self) -> Self::Param

return current parameter vector

fn cur_grad(&self) -> Self::Param

return current gradient

fn cur_hessian(&self) -> Self::Hessian

return current gradient

fn set_cur_param(&mut self, param: Self::Param)

set current parameter vector

fn set_cur_grad(&mut self, grad: Self::Param)

set current gradient

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

set current gradient

fn set_best_param(&mut self, param: Self::Param)

set current parameter vector

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Execute the optimization algorithm.

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Execute the optimization algorithm without Ctrl-C handling, logging, writing and anything else which may cost unnecessary time.

fn result(&self) -> ArgminResult<Self::Param>

Returns the best solution found during optimization.

fn set_termination_reason(&mut self, reason: TerminationReason)

Set termination reason (doesn't terminate yet! -- this is helpful for terminating within the iterations)

fn terminate(&mut self) -> TerminationReason

Evaluate all stopping criterions and return the TerminationReason

fn set_max_iters(&mut self, iters: u64)

Set max number of iterations.

fn max_iters(&self) -> u64

Get max number of iterations.

fn cur_iter(&self) -> u64

Get current iteration number.

fn increment_iter(&mut self)

Increment the iteration number by one

fn cur_cost(&self) -> f64

Get current cost function value

fn set_cur_cost(&mut self, cost: f64)

Get current cost function value

fn best_cost(&self) -> f64

Get best cost function value

fn set_best_cost(&mut self, cost: f64)

set best cost value

fn set_target_cost(&mut self, cost: f64)

Set the target cost function value which is used as a stopping criterion

fn add_logger(&mut self, logger: Arc<dyn ArgminLog + 'static>)

Add a logger to the array of loggers

fn add_writer(
    &mut self,
    writer: Arc<dyn ArgminWrite<Param = Self::Param> + 'static>
)

Add a writer to the array of writers

fn base_reset(&mut self)

Reset the base of the algorithm to its initial state

fn increment_cost_func_count(&mut self)

Increment the cost function evaluation count

fn increase_cost_func_count(&mut self, count: u64)

Increaese the cost function evaluation count by a given value

fn cost_func_count(&self) -> u64

Return the cost function evaluation count

fn increment_grad_func_count(&mut self)

Increment the gradient evaluation count

fn increase_grad_func_count(&mut self, count: u64)

Increase the gradient evaluation count by a given value

fn grad_func_count(&self) -> u64

Return the gradient evaluation count

fn increment_hessian_func_count(&mut self)

Increment the hessian evaluation count

fn increase_hessian_func_count(&mut self, count: u64)

Increase the hessian evaluation count by a given value

fn hessian_func_count(&self) -> u64

Return the gradient evaluation count

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Implementors

impl<'a, O> ArgminSolver for NonlinearConjugateGradient<'a, O> where
    O: 'a + ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param> + ArgminAdd<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminMul<f64, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminNorm<f64>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<'a, O> ArgminSolver for SteepestDescent<'a, O> where
    O: 'a + ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param> + ArgminMul<f64, <O as ArgminOp>::Param> + ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminNorm<f64>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<'a, O> ArgminSolver for NewtonCG<'a, O> where
    O: 'a + ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminAdd<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param> + ArgminMul<f64, <O as ArgminOp>::Param> + ArgminZero + ArgminNorm<f64>,
    <O as ArgminOp>::Hessian: ArgminInv<<O as ArgminOp>::Hessian> + ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<'a, O> ArgminSolver for BFGS<'a, O> where
    O: 'a + ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Hessian> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param> + ArgminNorm<f64> + ArgminMul<f64, <O as ArgminOp>::Param>,
    <O as ArgminOp>::Hessian: ArgminSub<<O as ArgminOp>::Hessian, <O as ArgminOp>::Hessian> + ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Hessian, <O as ArgminOp>::Hessian> + ArgminAdd<<O as ArgminOp>::Hessian, <O as ArgminOp>::Hessian> + ArgminMul<f64, <O as ArgminOp>::Hessian> + ArgminTranspose + ArgminEye, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<'a, O> ArgminSolver for TrustRegion<'a, O> where
    O: 'a + ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminMul<f64, <O as ArgminOp>::Param> + ArgminWeightedDot<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Hessian> + ArgminNorm<f64> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminAdd<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminZero + ArgminMul<f64, <O as ArgminOp>::Param>,
    <O as ArgminOp>::Hessian: ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for ConjugateGradient<O> where
    O: ArgminOp<Output = <O as ArgminOp>::Param>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param> + ArgminAdd<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminMul<f64, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for Landweber<O> where
    <O as ArgminOp>::Param: ArgminScaledSub<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param>,
    O: ArgminOp, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for BacktrackingLineSearch<O> where
    O: ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for HagerZhangLineSearch<O> where
    O: ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for MoreThuenteLineSearch<O> where
    O: ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminScaledAdd<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for Newton<O> where
    O: ArgminOp,
    <O as ArgminOp>::Param: ArgminScaledSub<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Param>,
    <O as ArgminOp>::Hessian: ArgminInv<<O as ArgminOp>::Hessian> + ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for SimulatedAnnealing<O> where
    O: ArgminOp<Output = f64>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for CauchyPoint<O> where
    O: ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminMul<f64, <O as ArgminOp>::Param> + ArgminWeightedDot<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Hessian> + ArgminNorm<f64>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for Dogleg<O> where
    O: ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminMul<f64, <O as ArgminOp>::Param> + ArgminWeightedDot<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Hessian> + ArgminNorm<f64> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminAdd<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param>,
    <O as ArgminOp>::Hessian: ArgminInv<<O as ArgminOp>::Hessian> + ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

impl<O> ArgminSolver for Steihaug<O> where
    O: ArgminOp<Output = f64>,
    <O as ArgminOp>::Param: ArgminMul<f64, <O as ArgminOp>::Param> + ArgminWeightedDot<<O as ArgminOp>::Param, f64, <O as ArgminOp>::Hessian> + ArgminNorm<f64> + ArgminDot<<O as ArgminOp>::Param, f64> + ArgminAdd<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminSub<<O as ArgminOp>::Param, <O as ArgminOp>::Param> + ArgminZero + ArgminMul<f64, <O as ArgminOp>::Param>,
    <O as ArgminOp>::Hessian: ArgminDot<<O as ArgminOp>::Param, <O as ArgminOp>::Param>, 

fn run(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the optimization algorithm

fn run_fast(&mut self) -> Result<ArgminResult<Self::Param>, Error>

Run the essential parts of the optimization algorithm (no logging, no Ctrl-C handling)

fn apply(&mut self, param: &Self::Param) -> Result<Self::Output, Error>

Applies the cost function or operator to a parameter vector param. Returns an Err if apply of ArgminOperator is not implemented.

fn gradient(&mut self, param: &Self::Param) -> Result<Self::Param, Error>

Computes the gradient at parameter param. Returns an Err if gradient of ArgminOperator is not implemented.

fn hessian(&mut self, param: &Self::Param) -> Result<Self::Hessian, Error>

Computes the Hessian at parameter param. Returns an Err if hessian of ArgminOperator is not implemented.

fn cur_param(&self) -> Self::Param

Returns the current parameter vector.

fn cur_grad(&self) -> Self::Param

Returns the most recently stored gradient.

fn cur_hessian(&self) -> Self::Hessian

Returns the most recently stored Hessian.

fn set_cur_param(&mut self, param: Self::Param)

Sets the current parameter to param.

fn set_cur_grad(&mut self, grad: Self::Param)

Sets the current gradient to grad.

fn set_cur_hessian(&mut self, hessian: Self::Hessian)

Sets the current Hessian to hessian.

fn set_best_param(&mut self, param: Self::Param)

Sets the best parameter vector to param.

fn modify(&self, param: &Self::Param, factor: f64) -> Result<Self::Param, Error>

Modify the parameter vector by calling the modify method of the trait ArgminOperator. Will return an Err if modify is not implemented.

fn result(&self) -> ArgminResult<Self::Param>

Returns the result of the optimization.

fn set_max_iters(&mut self, iters: u64)

Sets the maximum number of iterations to iters.

fn max_iters(&self) -> u64

Returns the maximum number of iterations.

fn increment_iter(&mut self)

Increments the iteration counter.

fn cur_iter(&self) -> u64

Returns the current number of iterations.

fn cur_cost(&self) -> f64

Returns the most recently stored cost function value.

fn set_cur_cost(&mut self, cost: f64)

Sets the current cost function value to cost

fn best_cost(&self) -> f64

Returns the best cost function value obtained so far.

fn set_best_cost(&mut self, cost: f64)

Sets the best cost function value.

fn set_target_cost(&mut self, cost: f64)

Sets the target cost function value to cost. The optimization algorithm will be terminated when this limit is reached.

fn increment_cost_func_count(&mut self)

Increments the counter for the computations of the cost function by 1.

fn increase_cost_func_count(&mut self, count: u64)

Increases the counter for the computations of the cost function by count.

fn cost_func_count(&self) -> u64

Returns the current value of the counter for the computations of the cost function.

fn increment_grad_func_count(&mut self)

Increments the counter for the computations of the gradient by 1.

fn increase_grad_func_count(&mut self, count: u64)

Increases the counter for the computations of the gradient by count.

fn grad_func_count(&self) -> u64

Returns the current value of the counter for the computations of the gradient.

fn increment_hessian_func_count(&mut self)

Increments the counter for the computations of the Hessian by 1.

fn increase_hessian_func_count(&mut self, count: u64)

Increases the counter for the computations of the Hessian by count.

fn hessian_func_count(&self) -> u64

Returns the current value of the counter for the computations of the Hessian.

fn add_logger(&mut self, logger: Arc<dyn ArgminLog>)

Attaches a logger which implements ArgminLog to the solver.

fn add_writer(&mut self, writer: Arc<dyn ArgminWrite<Param = Self::Param>>)

Attaches a writer which implements ArgminWrite to the solver.

fn set_termination_reason(&mut self, reason: TerminationReason)

Sets the TerminationReason

fn terminate(&mut self) -> TerminationReason

Checks whether any of the conditions to terminate is true and terminates the algorithm.

fn base_reset(&mut self)

Resets the base field to it's initial conditions. This is helpful for implementing a solver which is initialized once, but called several times. It is recommended to only call this method inside the init function of ArgminNextIter.

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