Parameters

module trajectopy.core.alignment.parameters

Trajectopy - Trajectory Evaluation in Python

Gereon Tombrink, 2025 tombrink@igg.uni-bonn.de

Global Variables

• UNIT_FORMAT_RULES

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class AlignmentParametersError

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class Parameter

Class representing a Parameter

A parameter holds a stochastic value with some variance. It can be enabled and disabled.

If a parameter is disabled, its value value is equal to the default value. The default value of a parameter should be chosen in a way so that the parameter has no effect on computations. For example, a default scale value of 1 will not affect any computations this scale parameter is involved in. The same holds true for a rotation or translation of 0. The disabling of parameters is meant to be used to exclude parameter from being estimated during least-squares adjustment.

method Parameter.__init__

__init__(
    value: float,
    variance: float = 0.0,
    default: float = 0.0,
    enabled: bool = True,
    name: str = '',
    unit: trajectopy.definitions.Unit = <Unit.NONE: 6>
) → None

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property Parameter.value

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property Parameter.variance

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method Parameter.disable

disable() → None

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method Parameter.enable

enable() → None

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class ParameterSet

Abstract class representing a set of parameters

This class groups related parameters. For example, 3 parameters for a 3d translation.

method ParameterSet.__init__

__init__(
    enabled: bool = True,
    covariance_matrix: numpy.ndarray = <factory>
) → None

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property ParameterSet.any_enabled

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property ParameterSet.enabled_bool_list

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property ParameterSet.enabled_indices

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property ParameterSet.num_enabled

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property ParameterSet.values

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property ParameterSet.values_enabled

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property ParameterSet.variances

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property ParameterSet.variances_enabled

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method ParameterSet.disable

disable() → None

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method ParameterSet.enable

enable() → None

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method ParameterSet.get_covariance_matrix

get_covariance_matrix(enabled_only: bool = True) → ndarray

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method ParameterSet.set_covariance_matrix

set_covariance_matrix(cov_matrix: numpy.ndarray) → None

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method ParameterSet.to_dict

to_dict(enabled_only: bool = True) → Dict[str, List[float]]

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method ParameterSet.to_name_list

to_name_list(enabled_only: bool = True, lower_case: bool = True) → List[str]

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method ParameterSet.to_string_list

to_string_list(enabled_only: bool = True) → List[str]

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method ParameterSet.validate_covariance

validate_covariance()

Checks dimensions of covariance matrix and sets variances accordingly

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class HelmertTransformation

Parameter set for a similarity transformation

method HelmertTransformation.__init__

__init__(
    enabled: bool = True,
    covariance_matrix: numpy.ndarray = <factory>,
    trans_x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    trans_y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    trans_z: trajectopy.core.alignment.parameters.Parameter = <factory>,
    rot_x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    rot_y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    rot_z: trajectopy.core.alignment.parameters.Parameter = <factory>,
    scale: trajectopy.core.alignment.parameters.Parameter = <factory>
) → None

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property HelmertTransformation.any_enabled

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property HelmertTransformation.enabled_bool_list

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property HelmertTransformation.enabled_indices

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property HelmertTransformation.num_enabled

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property HelmertTransformation.rotation

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property HelmertTransformation.rotation_matrix

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property HelmertTransformation.rotation_set

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property HelmertTransformation.translation

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property HelmertTransformation.values

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property HelmertTransformation.values_enabled

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property HelmertTransformation.variances

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property HelmertTransformation.variances_enabled

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method HelmertTransformation.apply_to

apply_to(xyz: numpy.ndarray) → ndarray

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method HelmertTransformation.disable

disable() → None

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method HelmertTransformation.enable

enable() → None

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method HelmertTransformation.get_covariance_matrix

get_covariance_matrix(enabled_only: bool = True) → ndarray

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method HelmertTransformation.set_covariance_matrix

set_covariance_matrix(cov_matrix: numpy.ndarray) → None

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method HelmertTransformation.to_dict

to_dict(enabled_only: bool = True) → Dict[str, List[float]]

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method HelmertTransformation.to_name_list

to_name_list(enabled_only: bool = True, lower_case: bool = True) → List[str]

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method HelmertTransformation.to_string_list

to_string_list(enabled_only: bool = True) → List[str]

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method HelmertTransformation.validate_covariance

validate_covariance()

Checks dimensions of covariance matrix and sets variances accordingly

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class Leverarm

Parameter set for a leverarm

method Leverarm.__init__

__init__(
    enabled: bool = True,
    covariance_matrix: numpy.ndarray = <factory>,
    x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    z: trajectopy.core.alignment.parameters.Parameter = <factory>
) → None

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property Leverarm.any_enabled

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property Leverarm.enabled_bool_list

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property Leverarm.enabled_indices

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property Leverarm.num_enabled

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property Leverarm.values

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property Leverarm.values_enabled

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property Leverarm.variances

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property Leverarm.variances_enabled

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method Leverarm.apply_to

apply_to(xyz: numpy.ndarray, quat_body: numpy.ndarray) → ndarray

Applies the leverarm to a set of positions using orientations

Args:

• xyz (np.ndarray): Positions
• quat_body (np.ndarray): Orientations

Returns:

• np.ndarray: Leverarm applied positions

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method Leverarm.disable

disable() → None

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method Leverarm.enable

enable() → None

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method Leverarm.get_covariance_matrix

get_covariance_matrix(enabled_only: bool = True) → ndarray

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method Leverarm.set_covariance_matrix

set_covariance_matrix(cov_matrix: numpy.ndarray) → None

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method Leverarm.to_dict

to_dict(enabled_only: bool = True) → Dict[str, List[float]]

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method Leverarm.to_name_list

to_name_list(enabled_only: bool = True, lower_case: bool = True) → List[str]

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method Leverarm.to_string_list

to_string_list(enabled_only: bool = True) → List[str]

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method Leverarm.validate_covariance

validate_covariance()

Checks dimensions of covariance matrix and sets variances accordingly

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class AlignmentParameters

Parameter set for spatio-temporal alignment

method AlignmentParameters.__init__

__init__(
    enabled: bool = True,
    covariance_matrix: numpy.ndarray = <factory>,
    sim_trans_x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sim_trans_y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sim_trans_z: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sim_rot_x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sim_rot_y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sim_rot_z: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sim_scale: trajectopy.core.alignment.parameters.Parameter = <factory>,
    time_shift: trajectopy.core.alignment.parameters.Parameter = <factory>,
    lever_x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    lever_y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    lever_z: trajectopy.core.alignment.parameters.Parameter = <factory>
) → None

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property AlignmentParameters.any_enabled

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property AlignmentParameters.enabled_bool_list

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property AlignmentParameters.enabled_indices

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property AlignmentParameters.helmert

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property AlignmentParameters.leverarm

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property AlignmentParameters.num_enabled

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property AlignmentParameters.sim3_matrix

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property AlignmentParameters.values

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property AlignmentParameters.values_enabled

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property AlignmentParameters.variances

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property AlignmentParameters.variances_enabled

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method AlignmentParameters.apply_settings

apply_settings(settings: trajectopy.settings.AlignmentEstimationSettings) → None

Applies the estimation settings to the parameters by enabling or disabling them

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method AlignmentParameters.disable

disable() → None

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method AlignmentParameters.enable

enable() → None

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classmethod AlignmentParameters.from_file

from_file(filename: str) → AlignmentParameters

Reads the alignment parameters from a file

Args:

• filename (str): Path to the file

Returns:

• AlignmentParameters: AlignmentParameters instance

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classmethod AlignmentParameters.from_settings

from_settings(
    settings: trajectopy.settings.AlignmentEstimationSettings
) → AlignmentParameters

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method AlignmentParameters.get_covariance_matrix

get_covariance_matrix(enabled_only: bool = True) → ndarray

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method AlignmentParameters.params_labels

params_labels(enabled_only: bool = True, lower_case: bool = True) → List[str]

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method AlignmentParameters.set_covariance_matrix

set_covariance_matrix(cov_matrix: numpy.ndarray) → None

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method AlignmentParameters.to_dataframe

to_dataframe() → DataFrame

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method AlignmentParameters.to_dict

to_dict(enabled_only: bool = True) → Dict[str, List[float]]

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method AlignmentParameters.to_estimation_settings

to_estimation_settings() → AlignmentEstimationSettings

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method AlignmentParameters.to_file

to_file(filename: str) → None

Writes the alignment parameters to a file

All parameters are written to the file no matter if they are enabled or not. If they are not enabled, the default value is written. Enabled parameters are marked with a 1, disabled with a 0. The order of the parameters is:

• Translation x
• Translation y
• Translation z
• Rotation x
• Rotation y
• Rotation z
• Scale
• Time Shift
• Leverarm x
• Leverarm y
• Leverarm z

Besides the parameters, the covariance matrix is written to the file. The covariance matrix is written row by row next to the parameters.

Args:

• filename (str): Path to the file

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method AlignmentParameters.to_name_list

to_name_list(enabled_only: bool = True, lower_case: bool = True) → List[str]

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method AlignmentParameters.to_string_list

to_string_list(enabled_only: bool = True) → List[str]

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method AlignmentParameters.validate_covariance

validate_covariance()

Checks dimensions of covariance matrix and sets variances accordingly

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class SensorRotationParameters

Parameter set for sensor b-frame rotation

method SensorRotationParameters.__init__

__init__(
    enabled: bool = True,
    covariance_matrix: numpy.ndarray = <factory>,
    sensor_rot_x: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sensor_rot_y: trajectopy.core.alignment.parameters.Parameter = <factory>,
    sensor_rot_z: trajectopy.core.alignment.parameters.Parameter = <factory>
) → None

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property SensorRotationParameters.any_enabled

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property SensorRotationParameters.enabled_bool_list

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property SensorRotationParameters.enabled_indices

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property SensorRotationParameters.num_enabled

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property SensorRotationParameters.rotation

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property SensorRotationParameters.rotation_matrix

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property SensorRotationParameters.rotation_set

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property SensorRotationParameters.values

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property SensorRotationParameters.values_enabled

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property SensorRotationParameters.variances

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property SensorRotationParameters.variances_enabled

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method SensorRotationParameters.disable

disable() → None

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method SensorRotationParameters.enable

enable() → None

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classmethod SensorRotationParameters.from_file

from_file(filename: str) → SensorRotationParameters

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method SensorRotationParameters.get_covariance_matrix

get_covariance_matrix(enabled_only: bool = True) → ndarray

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method SensorRotationParameters.set_covariance_matrix

set_covariance_matrix(cov_matrix: numpy.ndarray) → None

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method SensorRotationParameters.to_dict

to_dict(enabled_only: bool = True) → Dict[str, List[float]]

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method SensorRotationParameters.to_file

to_file(filename: str) → None

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method SensorRotationParameters.to_name_list

to_name_list(enabled_only: bool = True, lower_case: bool = True) → List[str]

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method SensorRotationParameters.to_string_list

to_string_list(enabled_only: bool = True) → List[str]

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method SensorRotationParameters.validate_covariance

validate_covariance()

Checks dimensions of covariance matrix and sets variances accordingly