🛤 bertini.tracking

Notes

Trackers in Bertini2 are stateful objects, that refer to a system they are tracking, hold their specific settings, and have a notion of current time and space value.

Here are some particular classes and functions to pay attention to:

bertini.tracking.AMPTracker
bertini.tracking.DoublePrecisionTracker
bertini.tracking.MultiplePrecisionTracker

Here are the implemented ODE predictors you can choose from:

bertini.tracking.Predictor

Calls to track_path() return a bertini.tracking.SuccessCode.

And, trackers are implemented using observer pattern. They live in the bertini.tracking.observers namespace, with provisions for each tracker type available under a submodule thereof: amp, multiple, and double. They are also conveniently available using the tr.observers, where tr is a tracker you already made. See bertini.tracking.observers.amp

Auto-generated docs

Tracking-specific things – trackers, configs

class bertini.tracking.AMPTracker((object)arg1, (bertini._pybertini.system.System)arg2)

The adaptive multiple precision (AMP) tracker. Ambient numeric type is multiple-precision (mpfr_complex). Contruct one by feeding it a system – cannot be constructed without feeding it a system. Adjust its settings via configs and the setup function. Then, call method track_path.

__init__((object)arg1, (bertini._pybertini.system.System)arg2) → None

add_observer((object)self, (object)observer) → None :: Attach an observer to this observable object

current_point((AMPTracker)self) → numpy.ndarray :: what is the current point?

current_precision((AMPTracker)self) → int :: what is the current working precision?

current_time((AMPTracker)self) → bertini._pybertini.multiprec.Complex :: what is the current time?

get_newton((AMPTracker)self) → bertini._pybertini.tracking.config.NewtonConfig :: Get the tracker’s internal configuration for Newton correction

get_stepping((AMPTracker)self) → bertini._pybertini.tracking.config.SteppingConfig :: Get the tracker’s internal configuration for things that control stepping behaviour

get_system((AMPTracker)arg1) → bertini._pybertini.system.System :: Gets an internal reference to the tracked system.

infinite_truncation((AMPTracker)self, (bool)val) → None :

Decide whether the tracker should truncate infinite paths. See also infinite_truncation_tolerance

infinite_truncation( (AMPTracker)self) -> bool :: Get the bool for whether the tracker should truncate infinite paths. See also infinite_truncation_tolerance

infinite_truncation_tolerance((AMPTracker)self, (float)tol) → None :

Set the path truncation tolerance for infinite paths for the tracker

infinite_truncation_tolerance( (AMPTracker)self) -> float :: Get the path truncation tolerance for infinite paths for the tracker

num_total_steps_taken((AMPTracker)self) → int :: Ask how many steps have been taken so far, including failures

observers = ['Abstract', 'FirstPrecisionRecorder', 'GoryDetailLogger', '__doc__', '__loader__', '__name__', '__package__', '__spec__']

precision_preservation((AMPTracker)arg1, (bool)arg2) → None :: Turn on or off the preservation of precision. That is, if this is on (true), then the precision of the final point will be the precision of the start point. Generally, you want to let precision drift, methinks.

precision_setup((AMPTracker)arg1, (bertini._pybertini.tracking.config.AMPConfig)arg2) → None

predictor((AMPTracker)self) → Predictor :

Query the current predictor method used by the tracker.

predictor( (AMPTracker)self, (Predictor)predictor) -> None :: Set the predictor method used by the tracker.

refine((AMPTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (complex)time) → SuccessCode :

refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.

refine( (AMPTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (bertini._pybertini.multiprec.Complex)time) -> SuccessCode :: refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.
refine( (AMPTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (complex)time, (float)tolerance, (int)max_iterations) -> SuccessCode :: refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.
refine( (AMPTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (bertini._pybertini.multiprec.Complex)time, (float)tolerance, (int)max_iterations) -> SuccessCode :: refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.

reinitialize_initial_step_size((AMPTracker)self, (bool)val) → None :: Set whether the tracker should re-set the stepsize to the configured-initial stepsize when it starts tracking. Feed it a bool

remove_observer((object)self, (object)observer) → None :: Remove an observer to this observable object

set_newton((AMPTracker)self, (bertini._pybertini.tracking.config.NewtonConfig)config) → None :: Set the tracker’s internal configuration for Newton correction

set_stepping((AMPTracker)self, (bertini._pybertini.tracking.config.SteppingConfig)config) → None :: Set the tracker’s internal configuration for things that control stepping behaviour

set_stepsize((AMPTracker)self, (bertini._pybertini.multiprec.Float)stepsize) → None :: Set the stepsize for the tracker

setup((AMPTracker)arg1, (Predictor)predictor, (float)tolerance, (float)truncation, (bertini._pybertini.tracking.config.SteppingConfig)stepping, (bertini._pybertini.tracking.config.NewtonConfig)newton) → None :: Set values for the internal configuration of the tracker. tolerance and truncation are both real doubles. predictor is a valid value for predictor choice. stepping and newton are the config structs from bertini.tracking.config.

track_path((AMPTracker)self, (numpy.ndarray)result, (bertini._pybertini.multiprec.Complex)start_time, (bertini._pybertini.multiprec.Complex)end_time, (numpy.ndarray)start_point) → SuccessCode :: The main function of the tracker, once its set up. The first argument is the output. Feed it, in (result, start_time, end_time, start_point

tracking_tolerance((AMPTracker)self) → float :

Get. A step is labeled as a failure if newton correcting doesn’t yield a residual less than this tolerance. A real number, the smaller the slower tracking, generally speaking

tracking_tolerance( (AMPTracker)self, (float)tol) -> None :: Set the tracking tolerance for the tracker

class bertini.tracking.DoublePrecisionTracker((object)arg1, (bertini._pybertini.system.System)arg2)

The double precision tracker. Tracks using only complex doubles. Ambient numeric type is double. Contruct one by feeding it a system – cannot be constructed without feeding it a system. Adjust its settings via configs and the setup function. Then, call method track_path.

__init__((object)arg1, (bertini._pybertini.system.System)arg2) → None

add_observer((object)self, (object)observer) → None :: Attach an observer to this observable object

current_point((DoublePrecisionTracker)self) → numpy.ndarray :: what is the current point?

current_precision((DoublePrecisionTracker)self) → int :: what is the current working precision?

current_time((DoublePrecisionTracker)self) → complex :: what is the current time?

get_newton((DoublePrecisionTracker)self) → bertini._pybertini.tracking.config.NewtonConfig :: Get the tracker’s internal configuration for Newton correction

get_stepping((DoublePrecisionTracker)self) → bertini._pybertini.tracking.config.SteppingConfig :: Get the tracker’s internal configuration for things that control stepping behaviour

get_system((DoublePrecisionTracker)arg1) → bertini._pybertini.system.System :: Gets an internal reference to the tracked system.

infinite_truncation((DoublePrecisionTracker)self, (bool)val) → None :

Decide whether the tracker should truncate infinite paths. See also infinite_truncation_tolerance

infinite_truncation( (DoublePrecisionTracker)self) -> bool :: Get the bool for whether the tracker should truncate infinite paths. See also infinite_truncation_tolerance

infinite_truncation_tolerance((DoublePrecisionTracker)self, (float)tol) → None :

Set the path truncation tolerance for infinite paths for the tracker

infinite_truncation_tolerance( (DoublePrecisionTracker)self) -> float :: Get the path truncation tolerance for infinite paths for the tracker

num_total_steps_taken((DoublePrecisionTracker)self) → int :: Ask how many steps have been taken so far, including failures

observers = ['Abstract', 'FirstPrecisionRecorder', 'GoryDetailLogger', '__doc__', '__loader__', '__name__', '__package__', '__spec__']

predictor((DoublePrecisionTracker)self) → Predictor :

Query the current predictor method used by the tracker.

predictor( (DoublePrecisionTracker)self, (Predictor)predictor) -> None :: Set the predictor method used by the tracker.

refine((DoublePrecisionTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (complex)time) → SuccessCode :

refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.

refine( (DoublePrecisionTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (complex)time, (float)tolerance, (int)max_iterations) -> SuccessCode :: refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.

reinitialize_initial_step_size((DoublePrecisionTracker)self, (bool)val) → None :: Set whether the tracker should re-set the stepsize to the configured-initial stepsize when it starts tracking. Feed it a bool

remove_observer((object)self, (object)observer) → None :: Remove an observer to this observable object

set_newton((DoublePrecisionTracker)self, (bertini._pybertini.tracking.config.NewtonConfig)config) → None :: Set the tracker’s internal configuration for Newton correction

set_stepping((DoublePrecisionTracker)self, (bertini._pybertini.tracking.config.SteppingConfig)config) → None :: Set the tracker’s internal configuration for things that control stepping behaviour

set_stepsize((DoublePrecisionTracker)self, (float)stepsize) → None :: Set the stepsize for the tracker

setup((DoublePrecisionTracker)arg1, (Predictor)predictor, (float)tolerance, (float)truncation, (bertini._pybertini.tracking.config.SteppingConfig)stepping, (bertini._pybertini.tracking.config.NewtonConfig)newton) → None :: Set values for the internal configuration of the tracker. tolerance and truncation are both real doubles. predictor is a valid value for predictor choice. stepping and newton are the config structs from bertini.tracking.config.

track_path((DoublePrecisionTracker)self, (numpy.ndarray)result, (complex)start_time, (complex)end_time, (numpy.ndarray)start_point) → SuccessCode :: The main function of the tracker, once its set up. The first argument is the output. Feed it, in (result, start_time, end_time, start_point

tracking_tolerance((DoublePrecisionTracker)self) → float :

Get. A step is labeled as a failure if newton correcting doesn’t yield a residual less than this tolerance. A real number, the smaller the slower tracking, generally speaking

tracking_tolerance( (DoublePrecisionTracker)self, (float)tol) -> None :: Set the tracking tolerance for the tracker

class bertini.tracking.MultiplePrecisionTracker((object)arg1, (bertini._pybertini.system.System)arg2)

The fixed multiple precision tracker. Ambient numeric type is multiple-precision (mpfr_complex). Precision is the value of bertini.default_precision() at contruction. Errors if you try to feed it things not at that precision. Contruct one by feeding it a system – cannot be constructed without feeding it a system. Adjust its settings via configs and the setup function. Then, call method track_path.

__init__((object)arg1, (bertini._pybertini.system.System)arg2) → None

add_observer((object)self, (object)observer) → None :: Attach an observer to this observable object

current_point((MultiplePrecisionTracker)self) → numpy.ndarray :: what is the current point?

current_precision((MultiplePrecisionTracker)self) → int :: what is the current working precision?

current_time((MultiplePrecisionTracker)self) → bertini._pybertini.multiprec.Complex :: what is the current time?

get_newton((MultiplePrecisionTracker)self) → bertini._pybertini.tracking.config.NewtonConfig :: Get the tracker’s internal configuration for Newton correction

get_stepping((MultiplePrecisionTracker)self) → bertini._pybertini.tracking.config.SteppingConfig :: Get the tracker’s internal configuration for things that control stepping behaviour

get_system((MultiplePrecisionTracker)arg1) → bertini._pybertini.system.System :: Gets an internal reference to the tracked system.

infinite_truncation((MultiplePrecisionTracker)self, (bool)val) → None :

Decide whether the tracker should truncate infinite paths. See also infinite_truncation_tolerance

infinite_truncation( (MultiplePrecisionTracker)self) -> bool :: Get the bool for whether the tracker should truncate infinite paths. See also infinite_truncation_tolerance

infinite_truncation_tolerance((MultiplePrecisionTracker)self, (float)tol) → None :

Set the path truncation tolerance for infinite paths for the tracker

infinite_truncation_tolerance( (MultiplePrecisionTracker)self) -> float :: Get the path truncation tolerance for infinite paths for the tracker

num_total_steps_taken((MultiplePrecisionTracker)self) → int :: Ask how many steps have been taken so far, including failures

observers = ['Abstract', 'FirstPrecisionRecorder', 'GoryDetailLogger', '__doc__', '__loader__', '__name__', '__package__', '__spec__']

predictor((MultiplePrecisionTracker)self) → Predictor :

Query the current predictor method used by the tracker.

predictor( (MultiplePrecisionTracker)self, (Predictor)predictor) -> None :: Set the predictor method used by the tracker.

refine((MultiplePrecisionTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (bertini._pybertini.multiprec.Complex)time) → SuccessCode :

refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.

refine( (MultiplePrecisionTracker)self, (numpy.ndarray)result, (numpy.ndarray)start_point, (bertini._pybertini.multiprec.Complex)time, (float)tolerance, (int)max_iterations) -> SuccessCode :: refine a point using this tracker, from start_point, at fixed time. returns a success code, computed refined point is in result.

reinitialize_initial_step_size((MultiplePrecisionTracker)self, (bool)val) → None :: Set whether the tracker should re-set the stepsize to the configured-initial stepsize when it starts tracking. Feed it a bool

remove_observer((object)self, (object)observer) → None :: Remove an observer to this observable object

set_newton((MultiplePrecisionTracker)self, (bertini._pybertini.tracking.config.NewtonConfig)config) → None :: Set the tracker’s internal configuration for Newton correction

set_stepping((MultiplePrecisionTracker)self, (bertini._pybertini.tracking.config.SteppingConfig)config) → None :: Set the tracker’s internal configuration for things that control stepping behaviour

set_stepsize((MultiplePrecisionTracker)self, (bertini._pybertini.multiprec.Float)stepsize) → None :: Set the stepsize for the tracker

setup((MultiplePrecisionTracker)arg1, (Predictor)predictor, (float)tolerance, (float)truncation, (bertini._pybertini.tracking.config.SteppingConfig)stepping, (bertini._pybertini.tracking.config.NewtonConfig)newton) → None :: Set values for the internal configuration of the tracker. tolerance and truncation are both real doubles. predictor is a valid value for predictor choice. stepping and newton are the config structs from bertini.tracking.config.

track_path((MultiplePrecisionTracker)self, (numpy.ndarray)result, (bertini._pybertini.multiprec.Complex)start_time, (bertini._pybertini.multiprec.Complex)end_time, (numpy.ndarray)start_point) → SuccessCode :: The main function of the tracker, once its set up. The first argument is the output. Feed it, in (result, start_time, end_time, start_point

tracking_tolerance((MultiplePrecisionTracker)self) → float :

Get. A step is labeled as a failure if newton correcting doesn’t yield a residual less than this tolerance. A real number, the smaller the slower tracking, generally speaking

tracking_tolerance( (MultiplePrecisionTracker)self, (float)tol) -> None :: Set the tracking tolerance for the tracker

class bertini.tracking.Predictor

Constant = bertini._pybertini.tracking.Predictor.Constant

Euler = bertini._pybertini.tracking.Predictor.Euler

Heun = bertini._pybertini.tracking.Predictor.Heun

HeunEuler = bertini._pybertini.tracking.Predictor.HeunEuler

RK4 = bertini._pybertini.tracking.Predictor.RK4

RKCashKarp45 = bertini._pybertini.tracking.Predictor.RKCashKarp45

RKDormandPrince56 = bertini._pybertini.tracking.Predictor.RKDormandPrince56

RKF45 = bertini._pybertini.tracking.Predictor.RKF45

RKNorsett34 = bertini._pybertini.tracking.Predictor.RKNorsett34

RKVerner67 = bertini._pybertini.tracking.Predictor.RKVerner67

names = {'Constant': bertini._pybertini.tracking.Predictor.Constant, 'Euler': bertini._pybertini.tracking.Predictor.Euler, 'Heun': bertini._pybertini.tracking.Predictor.Heun, 'HeunEuler': bertini._pybertini.tracking.Predictor.HeunEuler, 'RK4': bertini._pybertini.tracking.Predictor.RK4, 'RKCashKarp45': bertini._pybertini.tracking.Predictor.RKCashKarp45, 'RKDormandPrince56': bertini._pybertini.tracking.Predictor.RKDormandPrince56, 'RKF45': bertini._pybertini.tracking.Predictor.RKF45, 'RKNorsett34': bertini._pybertini.tracking.Predictor.RKNorsett34, 'RKVerner67': bertini._pybertini.tracking.Predictor.RKVerner67}

values = {0: bertini._pybertini.tracking.Predictor.Constant, 1: bertini._pybertini.tracking.Predictor.Euler, 2: bertini._pybertini.tracking.Predictor.Heun, 3: bertini._pybertini.tracking.Predictor.RK4, 4: bertini._pybertini.tracking.Predictor.HeunEuler, 5: bertini._pybertini.tracking.Predictor.RKNorsett34, 6: bertini._pybertini.tracking.Predictor.RKF45, 7: bertini._pybertini.tracking.Predictor.RKCashKarp45, 8: bertini._pybertini.tracking.Predictor.RKDormandPrince56, 9: bertini._pybertini.tracking.Predictor.RKVerner67}

class bertini.tracking.SuccessCode

CycleNumTooHigh = bertini._pybertini.tracking.SuccessCode.CycleNumTooHigh

ExternallyTerminated = bertini._pybertini.tracking.SuccessCode.ExternallyTerminated

FailedToConverge = bertini._pybertini.tracking.SuccessCode.FailedToConverge

Failure = bertini._pybertini.tracking.SuccessCode.Failure

GoingToInfinity = bertini._pybertini.tracking.SuccessCode.GoingToInfinity

HigherPrecisionNecessary = bertini._pybertini.tracking.SuccessCode.HigherPrecisionNecessary

MatrixSolveFailure = bertini._pybertini.tracking.SuccessCode.MatrixSolveFailure

MatrixSolveFailureFirstPartOfPrediction = bertini._pybertini.tracking.SuccessCode.MatrixSolveFailureFirstPartOfPrediction

MaxNumStepsTaken = bertini._pybertini.tracking.SuccessCode.MaxNumStepsTaken

MaxPrecisionReached = bertini._pybertini.tracking.SuccessCode.MaxPrecisionReached

MinStepSizeReached = bertini._pybertini.tracking.SuccessCode.MinStepSizeReached

MinTrackTimeReached = bertini._pybertini.tracking.SuccessCode.MinTrackTimeReached

ReduceStepSize = bertini._pybertini.tracking.SuccessCode.ReduceStepSize

SecurityMaxNormReached = bertini._pybertini.tracking.SuccessCode.SecurityMaxNormReached

SingularStartPoint = bertini._pybertini.tracking.SuccessCode.SingularStartPoint

Success = bertini._pybertini.tracking.SuccessCode.Success

names = {'CycleNumTooHigh': bertini._pybertini.tracking.SuccessCode.CycleNumTooHigh, 'ExternallyTerminated': bertini._pybertini.tracking.SuccessCode.ExternallyTerminated, 'FailedToConverge': bertini._pybertini.tracking.SuccessCode.FailedToConverge, 'Failure': bertini._pybertini.tracking.SuccessCode.Failure, 'GoingToInfinity': bertini._pybertini.tracking.SuccessCode.GoingToInfinity, 'HigherPrecisionNecessary': bertini._pybertini.tracking.SuccessCode.HigherPrecisionNecessary, 'MatrixSolveFailure': bertini._pybertini.tracking.SuccessCode.MatrixSolveFailure, 'MatrixSolveFailureFirstPartOfPrediction': bertini._pybertini.tracking.SuccessCode.MatrixSolveFailureFirstPartOfPrediction, 'MaxNumStepsTaken': bertini._pybertini.tracking.SuccessCode.MaxNumStepsTaken, 'MaxPrecisionReached': bertini._pybertini.tracking.SuccessCode.MaxPrecisionReached, 'MinStepSizeReached': bertini._pybertini.tracking.SuccessCode.MinStepSizeReached, 'MinTrackTimeReached': bertini._pybertini.tracking.SuccessCode.MinTrackTimeReached, 'ReduceStepSize': bertini._pybertini.tracking.SuccessCode.ReduceStepSize, 'SecurityMaxNormReached': bertini._pybertini.tracking.SuccessCode.SecurityMaxNormReached, 'SingularStartPoint': bertini._pybertini.tracking.SuccessCode.SingularStartPoint, 'Success': bertini._pybertini.tracking.SuccessCode.Success}

values = {0: bertini._pybertini.tracking.SuccessCode.Success, 1: bertini._pybertini.tracking.SuccessCode.HigherPrecisionNecessary, 2: bertini._pybertini.tracking.SuccessCode.ReduceStepSize, 3: bertini._pybertini.tracking.SuccessCode.GoingToInfinity, 4: bertini._pybertini.tracking.SuccessCode.FailedToConverge, 5: bertini._pybertini.tracking.SuccessCode.MatrixSolveFailure, 6: bertini._pybertini.tracking.SuccessCode.MatrixSolveFailureFirstPartOfPrediction, 7: bertini._pybertini.tracking.SuccessCode.MaxNumStepsTaken, 8: bertini._pybertini.tracking.SuccessCode.MaxPrecisionReached, 9: bertini._pybertini.tracking.SuccessCode.MinStepSizeReached, 10: bertini._pybertini.tracking.SuccessCode.Failure, 11: bertini._pybertini.tracking.SuccessCode.SingularStartPoint, 12: bertini._pybertini.tracking.SuccessCode.ExternallyTerminated, 13: bertini._pybertini.tracking.SuccessCode.MinTrackTimeReached, 14: bertini._pybertini.tracking.SuccessCode.SecurityMaxNormReached, 15: bertini._pybertini.tracking.SuccessCode.CycleNumTooHigh}

🛤 bertini.tracking.config

Tracking-specific configs

class bertini.tracking.config.AMPConfig((object)arg1)

__init__( (object)arg1, (bertini._pybertini.system.System)arg2) -> None

__init__((object)arg1) → None: __init__( (object)arg1, (bertini._pybertini.system.System)arg2) -> None

property coefficient_bound: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> float

property consecutive_successful_steps_before_precision_decrease: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> int

property degree_bound: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> float

property epsilon: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> float

property max_num_precision_decreases: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> int

property maximum_precision: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> int

property phi: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> float

property psi: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> float

property safety_digits_1: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> int

property safety_digits_2: None( (bertini._pybertini.tracking.config.AMPConfig)arg1) -> int

set_amp_config_from((AMPConfig)arg1, (bertini._pybertini.system.System)arg2) → None

set_bounds_and_epsilon_from((AMPConfig)arg1, (bertini._pybertini.system.System)arg2) → None

set_phi_psi_from_bounds((AMPConfig)arg1) → None

class bertini.tracking.config.FixedPrecisionConfig((object)arg1, (bertini._pybertini.system.System)arg2)

__init__((object)arg1, (bertini._pybertini.system.System)arg2) → None

class bertini.tracking.config.NewtonConfig((object)arg1)

__init__((object)arg1) → None

property max_num_newton_iterations: None( (bertini._pybertini.tracking.config.NewtonConfig)arg1) -> int

property min_num_newton_iterations: None( (bertini._pybertini.tracking.config.NewtonConfig)arg1) -> int

class bertini.tracking.config.SteppingConfig((object)arg1)

__init__((object)arg1) → None

property consecutive_successful_steps_before_stepsize_increase: This number of successful steps have to taken consecutively, and then the stepsize is permitted to increase

property frequency_of_CN_estimation: How frequently the condition number should be updated. Less frequently is faster (estimation requires an additional linear solve), but may cause precision adjustment to lag behind.

property initial_step_size: The initial stepsize when tracking is started. See also tracking.AMPTracker.reinitialize_initial_step_size

property max_num_steps: The maximum number of steps. Tracking will die if it tries to take more than this number, sad day.

property max_step_size: The maximum allowed stepsize during tracking. See also min_num_steps

property min_num_steps: The minimum number of steps the tracker can take between now and then. This is useful if you are tracking closely between times, and want to guarantee some number of steps are taken. Then again, this could be wasteful, too.

property min_step_size: The minimum stepsize the tracker is allowed to take. See also max_step_size

property step_size_fail_factor: The scale factor for stepsize, after a fail happens. See also step_size_success_factor

property step_size_success_factor: The scale factor for stepsize, after some consecutive steps. See also consecutive_successful_steps_before_stepsize_increase

bertini.tracking.config.amp_config_from((bertini._pybertini.system.System)arg1) → AMPConfig :: make an AMPConfig from a System with generated settings for system-specific things, and default settings otherwise (such as safety digits).

🛤 bertini.tracking.observers

📝 All of these are available for all trackers, though you should use the ones for your tracker type. Look in bertini.tracking.AMPTracker.observers, etc.

Observers built to watch a tracker

bertini.tracking.observers.amp
bertini.tracking.observers.double
bertini.tracking.observers.multiple

📝 Symmetrically, there are the same observers in all three.

Observers built to watch an adaptive precision tracker

Know that you are loved and appreciated, dear reader. 💟

class bertini.tracking.observers.amp.Abstract((object)arg1)

__init__((object)arg1) → None

class bertini.tracking.observers.amp.FirstPrecisionRecorder((object)arg1)

__init__((object)arg1) → None

class bertini.tracking.observers.amp.GoryDetailLogger((object)arg1)

__init__((object)arg1) → None