backend.runners

class backend.runners.Runner

prompt_source = 'Generated Trajectory'

feature_source = 'Live'

use_decoder = False

is_target = False

start_msg = 'starting message'

end_msg = 'ending message'

cancel_msg = 'cancel message'

prompt_msg = 'Showing prompt'

commands = []

excluded_params = ['_movements', 'movements_order', 'relax_pos']

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

property movements

copy(source)

Copy Runner attributes from source to self

n_moves()

n_reps(mov_idx: int)

get_mov(idx)

get_mov_num(idx)

shuffle_movs()

if self.shuffle is nonzero, shuffle the movements with self.shuffle repetitions of each movement per loop if self.shuffle is zero, then unshuffle the movements

unshuffle_movs()

static compute_output(self, traj, params, _predict)

class backend.runners.Collector

use_decoder = False

start_msg = 'Collecting training data'

end_msg = 'Finished data collection'

cancel_msg = 'Data collection canceled'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.TrajCollect

prompt_source = 'Generated Trajectory'

feature_source = 'Live'

start_msg = 'Collecting training data with trajectory-generated prompts'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.ActionSelection

excluded_params = ['_movements', 'movements_order', 'relax_pos', '_backup_movements', '_backup_movements_order', '_backup_relax_pos']

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

set_as_movement(dofs=1, moving=- 1)

store_movements()

restore_movements()

property start_msg

str(object=’’) -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.__str__() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to ‘strict’.

movements_order: List[int, int]

class backend.runners.FreeCollect

prompt_source = 'Live'

feature_source = 'Live'

start_msg = 'Free collecting training data'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.SourceCollect

prompt_source = 'File'

feature_source = 'Live'

start_msg = 'Collecting training data with file-sourced prompts'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.Tester

use_decoder = True

start_msg = 'Starting test'

end_msg = 'Finished testing'

cancel_msg = 'Testing canceled'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.TrajTest

prompt_source = 'Generated Trajectory'

feature_source = 'Live'

start_msg = 'Testing with trajectory-generated prompts'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.TargetTest

is_target = True

start_msg = 'Testing with trajectory-generated targets'

prompt_msg = 'Showing next target'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

movements_order: List[int, int]

class backend.runners.FreeTest

prompt_source = 'Live'

feature_source = 'Live'

start_msg = 'Free testing'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.SourceTest

prompt_source = 'File'

feature_source = 'Live'

start_msg = 'Testing with file-sourced prompts'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.FileTest

prompt_source = 'File'

feature_source = 'File'

start_msg = 'File testing'

__init__()

• self.movements is a list of the movements available to this runner

• self.movements_order shows the order in which movements are to be shown for a prompted movement Each element is a tuple (movement_index, number of repetitions). This does not need to be in the same order as written in self.movements, and movements may be repeated. This does not need to contain all the movements.

When self.movements is set, self.movements_order is reset to the default (unshuffled) ordering

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.Control

use_decoder = True

prompt_source = 'Live'

feature_source = 'Live'

start_msg = 'Starting free control'

end_msg = 'Free control finished'

cancel_msg = 'Free control canceled'

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.Replay

use_decoder = False

prompt_source = 'File'

feature_source = 'File'

start_msg = 'Starting replay'

end_msg = 'Replay finished'

cancel_msg = 'Replay canceled'

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]

class backend.runners.Calibrate

use_decoder = False

prompt_source = 'Live'

feature_source = 'Live'

start_msg = 'Starting calibration'

end_msg = 'Calibration finished'

cancel_msg = 'Calibration canceled'

static compute_output(self, traj, params, _predict)

movements_order: List[int, int]