Settings¶

settings ¶

Settings `dataclass` ¶

Settings()

Bases: ABC

Base class for all settings dataclasses.

Provides serialization/deserialization functionality to and from dictionaries, JSON strings, and files.

to_dict ¶

to_dict() -> dict

Converts settings to a dictionary.

Returns:

dict ( dict ) –

Dictionary representation of the settings

Source code in trajectopy\core\settings.py

def to_dict(self) -> dict:
    """Converts settings to a dictionary.

    Returns:
        dict: Dictionary representation of the settings
    """
    return {
        key: (value.to_dict() if issubclass(type(value), Settings) else self.encoder(key, value))
        for key, value in self.__dict__.items()
    }

encoder `staticmethod` ¶

encoder(name: str, value: Any) -> Any

Encodes values for JSON serialization.

Parameters:

name (str) –

Name of the attribute being encoded
value (Any) –

Value to encode

Returns:

Any ( Any ) –

Encoded value suitable for JSON serialization

Source code in trajectopy\core\settings.py

@staticmethod
def encoder(name: str, value: Any) -> Any:
    """Encodes values for JSON serialization.

    Args:
        name: Name of the attribute being encoded
        value: Value to encode

    Returns:
        Any: Encoded value suitable for JSON serialization
    """
    return value

decoder `staticmethod` ¶

decoder(name: str, value: Any) -> Any

Decodes values from JSON deserialization.

Parameters:

name (str) –

Name of the attribute being decoded
value (Any) –

Value to decode

Returns:

Any ( Any ) –

Decoded value

Source code in trajectopy\core\settings.py

@staticmethod
def decoder(name: str, value: Any) -> Any:
    """Decodes values from JSON deserialization.

    Args:
        name: Name of the attribute being decoded
        value: Value to decode

    Returns:
        Any: Decoded value
    """
    return value

to_json ¶

to_json() -> str

Converts settings to a JSON string.

Returns:

str ( str ) –

JSON string representation of the settings

Source code in trajectopy\core\settings.py

def to_json(self) -> str:
    """Converts settings to a JSON string.

    Returns:
        str: JSON string representation of the settings
    """
    return json.dumps(self.to_dict(), indent=4)

to_file ¶

to_file(path: str) -> None

Writes settings to a JSON file.

Parameters:

path (str) –

Path to the output file

Source code in trajectopy\core\settings.py

def to_file(self, path: str) -> None:
    """Writes settings to a JSON file.

    Args:
        path: Path to the output file
    """
    with open(path, "w", encoding="utf-8") as f:
        f.write(self.to_json())

from_dict `classmethod` ¶

from_dict(dct: dict) -> Settings

Creates settings instance from a dictionary.

Parameters:

dct (dict) –

Dictionary containing settings data

Returns:

Settings ( Settings ) –

New settings instance

Raises:

ValueError –

If required attribute is missing from dictionary

Source code in trajectopy\core\settings.py

@classmethod
def from_dict(cls, dct: dict) -> "Settings":
    """Creates settings instance from a dictionary.

    Args:
        dct: Dictionary containing settings data

    Returns:
        Settings: New settings instance

    Raises:
        ValueError: If required attribute is missing from dictionary
    """
    settings = cls()
    for attribute_name, attribute_type in cls.__annotations__.items():
        if attribute_name not in dct:
            raise ValueError(f"Attribute {attribute_name} not found in input data")

        attribute_data = dct[attribute_name]
        if isinstance(attribute_data, dict) and issubclass(attribute_type, Settings):
            setattr(settings, attribute_name, attribute_type.from_dict(attribute_data))
        else:
            setattr(settings, attribute_name, settings.decoder(attribute_name, attribute_data))

    return settings

from_file `classmethod` ¶

from_file(path: str) -> Settings

Loads settings from a JSON file.

Parameters:

path (str) –

Path to the JSON file

Returns:

Settings ( Settings ) –

Settings instance loaded from file

Source code in trajectopy\core\settings.py

@classmethod
def from_file(cls, path: str) -> "Settings":
    """Loads settings from a JSON file.

    Args:
        path: Path to the JSON file

    Returns:
        Settings: Settings instance loaded from file
    """
    with open(path, "r", encoding="utf-8") as f:
        data = json.load(f)

    return cls.from_dict(data)

update_from_dict ¶

update_from_dict(dct: dict) -> None

Updates settings from a dictionary.

Parameters:

dct (dict) –

Dictionary containing updated settings data

Raises:

ValueError –

If required attribute is missing from dictionary

Source code in trajectopy\core\settings.py

def update_from_dict(self, dct: dict) -> None:
    """Updates settings from a dictionary.

    Args:
        dct: Dictionary containing updated settings data

    Raises:
        ValueError: If required attribute is missing from dictionary
    """
    for attribute_name, attribute_type in self.__annotations__.items():
        if attribute_name not in dct:
            raise ValueError(f"Attribute {attribute_name} not found in input data")

        attribute_data = dct[attribute_name]
        if isinstance(attribute_data, dict) and issubclass(attribute_type, Settings):
            getattr(self, attribute_name).update_from_dict(attribute_data)
        else:
            setattr(self, attribute_name, self.decoder(attribute_name, attribute_data))

AlignmentPreprocessing `dataclass` ¶

AlignmentPreprocessing(
    min_speed: float = 0.0,
    time_start: float = 0.0,
    time_end: float = 0.0,
)

Bases: Settings

Configuration for alignment preprocessing filters.

Attributes:

min_speed (float) –

Only poses with speed above this threshold are considered for alignment (meters/second). Defaults to 0.0.
time_start (float) –

Only poses with timestamp above this threshold are considered. Timestamp is in seconds relative to first common timestamp. Defaults to 0.0.
time_end (float) –

Only poses with timestamp below this threshold are considered. Timestamp is in seconds relative to first common timestamp. Defaults to 0.0.

AlignmentEstimationSettings `dataclass` ¶

AlignmentEstimationSettings(
    translation_x: bool = True,
    translation_y: bool = True,
    translation_z: bool = True,
    rotation_x: bool = True,
    rotation_y: bool = True,
    rotation_z: bool = True,
    scale: bool = False,
    time_shift: bool = False,
    leverarm_x: bool = False,
    leverarm_y: bool = False,
    leverarm_z: bool = False,
    sensor_rotation: bool = False,
)

Bases: Settings

Configuration for parameters to estimate during trajectory alignment.

Attributes:

translation_x (bool) –

Enable x-translation of similarity transformation
translation_y (bool) –

Enable y-translation of similarity transformation
translation_z (bool) –

Enable z-translation of similarity transformation
rotation_x (bool) –

Enable rotation around X-axis of similarity transformation
rotation_y (bool) –

Enable rotation around Y-axis of similarity transformation
rotation_z (bool) –

Enable rotation around Z-axis of similarity transformation
scale (bool) –

Enable scaling of similarity transformation
time_shift (bool) –

Enable estimation of time shift between trajectories
leverarm_x (bool) –

Enable estimation of lever arm in X-direction
leverarm_y (bool) –

Enable estimation of lever arm in Y-direction
leverarm_z (bool) –

Enable estimation of lever arm in Z-direction
sensor_rotation (bool) –

Enable computation of sensor rotation offsets (independent of least squares, computes constant offsets between roll, pitch, yaw)

all_disabled `property` ¶

all_disabled: bool

Checks if all alignment parameters are disabled.

Returns:

bool ( bool ) –

True if all parameters (Helmert, time shift, leverarm, sensor rotation) are disabled

all_lq_disabled `property` ¶

all_lq_disabled: bool

Checks if all least-squares parameters are disabled.

Returns:

bool ( bool ) –

True if all parameters estimated with least-squares are disabled

helmert_enabled `property` ¶

helmert_enabled: bool

Checks if any Helmert transformation parameter is enabled.

Returns:

bool ( bool ) –

True if any translation, rotation, or scale parameter is enabled

leverarm_enabled `property` ¶

leverarm_enabled: bool

Checks if any leverarm parameter is enabled.

Returns:

bool ( bool ) –

True if any leverarm component (x, y, z) is enabled

time_shift_enabled `property` ¶

time_shift_enabled: bool

Checks if time shift estimation is enabled.

Returns:

bool ( bool ) –

True if time shift is enabled

short_mode_str `property` ¶

short_mode_str: str

Gets a short string describing enabled parameter groups.

Returns:

str ( str ) –

Space-separated string of enabled parameter groups (e.g., "Helmert Time-Shift Leverarm")

time_shift_filter `property` ¶

time_shift_filter: List[bool]

Gets time shift parameter filter.

Returns:

List[bool] –

List[bool]: List of 3 bools, all True if time shift enabled, else all False

helmert_filter `property` ¶

helmert_filter: List[bool]

Gets Helmert parameter filter.

Returns:

List[bool] –

List[bool]: List of 7 bools indicating which Helmert parameters are enabled

leverarm_filter `property` ¶

leverarm_filter: List[bool]

Gets leverarm parameter filter.

Returns:

List[bool] –

List[bool]: List of 3 bools indicating which leverarm components are enabled

enabled_lq_parameter_filter `property` ¶

enabled_lq_parameter_filter: List[bool]

Gets filter for enabled least-squares parameters only.

Returns:

List[bool] –

List[bool]: List of bools for only the enabled parameter groups

lq_parameter_filter `property` ¶

lq_parameter_filter: List[bool]

Gets complete least-squares parameter filter.

Returns:

List[bool] –

List[bool]: List of 11 bools for all LQ parameters (7 Helmert + 1 time shift + 3 leverarm)

bool ¶

__bool__() -> bool

Returns True if any least-squares parameter is enabled.

Returns:

bool ( bool ) –

True if at least one least-squares parameter is enabled

Source code in trajectopy\core\settings.py

def __bool__(self) -> bool:
    """Returns True if any least-squares parameter is enabled.

    Returns:
        bool: True if at least one least-squares parameter is enabled
    """
    return not self.all_lq_disabled

from_components `classmethod` ¶

from_components(
    similarity: bool = False,
    time_shift: bool = False,
    leverarm: bool = False,
    sensor_rotation: bool = False,
) -> AlignmentEstimationSettings

Creates settings from high-level component flags.

Parameters:

similarity (bool, default: False ) –

Enable all similarity transformation parameters. Defaults to False.
time_shift (bool, default: False ) –

Enable time shift estimation. Defaults to False.
leverarm (bool, default: False ) –

Enable all leverarm parameters. Defaults to False.
sensor_rotation (bool, default: False ) –

Enable sensor rotation estimation. Defaults to False.

Returns:

AlignmentEstimationSettings ( AlignmentEstimationSettings ) –

New settings instance

Source code in trajectopy\core\settings.py

@classmethod
def from_components(
    cls,
    similarity: bool = False,
    time_shift: bool = False,
    leverarm: bool = False,
    sensor_rotation: bool = False,
) -> "AlignmentEstimationSettings":
    """Creates settings from high-level component flags.

    Args:
        similarity: Enable all similarity transformation parameters. Defaults to False.
        time_shift: Enable time shift estimation. Defaults to False.
        leverarm: Enable all leverarm parameters. Defaults to False.
        sensor_rotation: Enable sensor rotation estimation. Defaults to False.

    Returns:
        AlignmentEstimationSettings: New settings instance
    """
    return cls(
        translation_x=similarity,
        translation_y=similarity,
        translation_z=similarity,
        rotation_x=similarity,
        rotation_y=similarity,
        rotation_z=similarity,
        scale=similarity,
        time_shift=time_shift,
        leverarm_x=leverarm,
        leverarm_y=leverarm,
        leverarm_z=leverarm,
        sensor_rotation=sensor_rotation,
    )

all `classmethod` ¶

all(
    sensor_rotation: bool = True,
) -> AlignmentEstimationSettings

Creates settings with all parameters enabled.

Parameters:

sensor_rotation (bool, default: True ) –

Enable sensor rotation. Defaults to True.

Returns:

AlignmentEstimationSettings ( AlignmentEstimationSettings ) –

Settings with all parameters enabled

Source code in trajectopy\core\settings.py

@classmethod
def all(cls, sensor_rotation: bool = True) -> "AlignmentEstimationSettings":
    """Creates settings with all parameters enabled.

    Args:
        sensor_rotation: Enable sensor rotation. Defaults to True.

    Returns:
        AlignmentEstimationSettings: Settings with all parameters enabled
    """
    return cls(
        translation_x=True,
        translation_y=True,
        translation_z=True,
        rotation_x=True,
        rotation_y=True,
        rotation_z=True,
        scale=True,
        time_shift=True,
        leverarm_x=True,
        leverarm_y=True,
        leverarm_z=True,
        sensor_rotation=sensor_rotation,
    )

from_bool_list `classmethod` ¶

from_bool_list(
    bool_list: List[bool],
) -> AlignmentEstimationSettings

Creates settings from a list of boolean values.

Parameters:

bool_list (List[bool]) –

List of 14 booleans corresponding to parameter enable flags

Returns:

AlignmentEstimationSettings ( AlignmentEstimationSettings ) –

New settings instance

Raises:

ValueError –

If bool_list length is not 14

Source code in trajectopy\core\settings.py

@classmethod
def from_bool_list(cls, bool_list: List[bool]) -> "AlignmentEstimationSettings":
    """Creates settings from a list of boolean values.

    Args:
        bool_list: List of 14 booleans corresponding to parameter enable flags

    Returns:
        AlignmentEstimationSettings: New settings instance

    Raises:
        ValueError: If bool_list length is not 14
    """
    if len(bool_list) != 14:
        raise ValueError(
            f"Size mismatch: bool_list must have length 14 (Number of configurable parameters) (got {len(bool_list)})"
        )

    return AlignmentEstimationSettings(
        translation_x=bool_list[0],
        translation_y=bool_list[1],
        translation_z=bool_list[2],
        rotation_x=bool_list[3],
        rotation_y=bool_list[4],
        rotation_z=bool_list[5],
        scale=bool_list[6],
        time_shift=bool_list[7],
        leverarm_x=bool_list[8],
        leverarm_y=bool_list[9],
        leverarm_z=bool_list[10],
        sensor_rotation=any(bool_list[11:]),
    )

AlignmentStochastics `dataclass` ¶

AlignmentStochastics(
    std_xy_from: float = 1.0,
    std_z_from: float = 1.0,
    std_xy_to: float = 1.0,
    std_z_to: float = 1.0,
    std_roll_pitch: float = float(deg2rad(1.0)),
    std_yaw: float = float(deg2rad(1.0)),
    std_speed: float = 1.0,
    error_probability: float = 0.05,
    variance_estimation: bool = False,
)

Bases: Settings

Configuration for alignment stochastic model (observation uncertainties).

Attributes:

std_xy_from (float) –

Standard deviation of XY source position components in meters. Defaults to 1.0.
std_z_from (float) –

Standard deviation of Z source position component in meters. Defaults to 1.0.
std_xy_to (float) –

Standard deviation of XY target position components in meters. Defaults to 1.0.
std_z_to (float) –

Standard deviation of Z target position component in meters. Defaults to 1.0.
std_roll_pitch (float) –

Standard deviation of roll and pitch angles in radians. Defaults to ~0.017 rad (1°).
std_yaw (float) –

Standard deviation of yaw angle in radians. Defaults to ~0.017 rad (1°).
std_speed (float) –

Standard deviation of platform speed in meters per second. Defaults to 1.0.
error_probability (float) –

Probability of error for stochastic testing. Defaults to 0.05.
variance_estimation (bool) –

Enable a-posteriori variance factor estimation. Defaults to False.

var_xy_from `property` ¶

var_xy_from: float

Gets variance of XY source position components.

Returns:

float ( float ) –

Variance (squared standard deviation)

var_z_from `property` ¶

var_z_from: float

Gets variance of Z source position component.

Returns:

float ( float ) –

Variance (squared standard deviation)

var_xy_to `property` ¶

var_xy_to: float

Gets variance of XY target position components.

Returns:

float ( float ) –

Variance (squared standard deviation)

var_z_to `property` ¶

var_z_to: float

Gets variance of Z target position component.

Returns:

float ( float ) –

Variance (squared standard deviation)

var_roll_pitch `property` ¶

var_roll_pitch: float

Gets variance of roll and pitch angles.

Returns:

float ( float ) –

Variance (squared standard deviation)

var_yaw `property` ¶

var_yaw: float

Gets variance of yaw angle.

Returns:

float ( float ) –

Variance (squared standard deviation)

var_speed_to `property` ¶

var_speed_to: float

Gets variance of platform speed.

Returns:

float ( float ) –

Variance (squared standard deviation)

AlignmentSettings `dataclass` ¶

AlignmentSettings(
    preprocessing: AlignmentPreprocessing = AlignmentPreprocessing(),
    estimation_settings: AlignmentEstimationSettings = AlignmentEstimationSettings(),
    stochastics: AlignmentStochastics = AlignmentStochastics(),
    metric_threshold: float = METRIC_THRESHOLD,
    time_threshold: float = TIME_THRESHOLD,
)

Bases: Settings

Complete configuration for trajectory alignment.

Combines preprocessing, estimation, and stochastic settings for trajectory alignment.

Attributes:

preprocessing (AlignmentPreprocessing) –

Preprocessing filter settings
estimation_settings (AlignmentEstimationSettings) –

Parameter estimation settings
stochastics (AlignmentStochastics) –

Stochastic model (observation uncertainty) settings
metric_threshold (float) –

Iteration threshold for metric parameters in least squares. Defaults to 1e-4.
time_threshold (float) –

Iteration threshold for time shift parameter in least squares (seconds). Defaults to 1e-4.

str ¶

__str__() -> str

Returns string representation of all settings.

Returns:

str ( str ) –

Concatenated string of preprocessing, estimation, and stochastics settings

Source code in trajectopy\core\settings.py

def __str__(self) -> str:
    """Returns string representation of all settings.

    Returns:
        str: Concatenated string of preprocessing, estimation, and stochastics settings
    """
    return str(self.preprocessing) + str(self.estimation_settings) + str(self.stochastics)

ApproximationSettings `dataclass` ¶

ApproximationSettings(
    position_interval_size: float = 0.15,
    position_min_observations: int = 25,
    rotation_window_size: float = 0.15,
)

Bases: Settings

Configuration for trajectory approximation and smoothing.

Attributes:

position_interval_size (float) –

Size of position intervals in meters for cubic approximation. Defaults to 0.15.
position_min_observations (int) –

Minimum number of observations required in each interval for cubic approximation. Defaults to 25.
rotation_window_size (float) –

Size of rotation smoothing window in meters (not cubic). Defaults to 0.15.

PairDistanceUnit ¶

Bases: Enum

Unit of measurement for pose pair distances in relative comparison.

from_str `classmethod` ¶

from_str(unit_str: str) -> PairDistanceUnit

Converts a string to a PairDistanceUnit.

Parameters:

unit_str (str) –

String to convert ("m", "meter", "s", "sec", "second")

Returns:

PairDistanceUnit ( PairDistanceUnit ) –

Converted unit

Raises:

ValueError –

If unit string is not recognized

Source code in trajectopy\core\settings.py

@classmethod
def from_str(cls, unit_str: str) -> "PairDistanceUnit":
    """Converts a string to a PairDistanceUnit.

    Args:
        unit_str: String to convert ("m", "meter", "s", "sec", "second")

    Returns:
        PairDistanceUnit: Converted unit

    Raises:
        ValueError: If unit string is not recognized
    """
    if unit_str.lower() in {"m", "meter"}:
        return cls.METER
    if unit_str.lower() in {"s", "sec", "second"}:
        return cls.SECOND

    raise ValueError(f"Unknown unit string {unit_str}")

ComparisonMethod ¶

Bases: Enum

Method for trajectory comparison.

from_string `classmethod` ¶

from_string(string: str) -> ComparisonMethod

Converts string to ComparisonMethod.

Parameters:

string (str) –

String containing "absolute" or "relative"

Returns:

ComparisonMethod ( ComparisonMethod ) –

Parsed comparison method

Source code in trajectopy\core\settings.py

@classmethod
def from_string(cls, string: str) -> "ComparisonMethod":
    """Converts string to ComparisonMethod.

    Args:
        string: String containing "absolute" or "relative"

    Returns:
        ComparisonMethod: Parsed comparison method
    """
    return comparison_method_from_string(string)

RelativeComparisonSettings `dataclass` ¶

RelativeComparisonSettings(
    pair_min_distance: float = 100.0,
    pair_max_distance: float = 800.0,
    pair_distance_step: float = 100.0,
    pair_distance_unit: PairDistanceUnit = METER,
    use_all_pose_pairs: bool = True,
)

Bases: Settings

Configuration for relative trajectory comparison (RPE - Relative Pose Error).

Relative comparison involves finding pose pairs separated by specific distances or time intervals and computing relative translation/rotation differences.

Attributes:

pair_min_distance (float) –

Minimum pose pair distance to consider during RPE computation. Defaults to 100.0.
pair_max_distance (float) –

Maximum pose pair distance to consider during RPE computation. Defaults to 800.0.
pair_distance_step (float) –

Step size for increasing pose pair distance. Defaults to 100.0.
pair_distance_unit (PairDistanceUnit) –

Unit of pose pair distance (METER or SECOND). Defaults to METER.
use_all_pose_pairs (bool) –

If True, use overlapping pose pairs; if False, use only consecutive (non-overlapping) pairs. Defaults to True.

encoder `staticmethod` ¶

encoder(name: str, value: Any) -> Any

Encodes pair_distance_unit enum to string value.

Parameters:

name (str) –

Attribute name
value (Any) –

Value to encode

Returns:

Any ( Any ) –

Encoded value

Source code in trajectopy\core\settings.py

@staticmethod
def encoder(name: str, value: Any) -> Any:
    """Encodes pair_distance_unit enum to string value.

    Args:
        name: Attribute name
        value: Value to encode

    Returns:
        Any: Encoded value
    """
    return value.value if name == "pair_distance_unit" else value

decoder `staticmethod` ¶

decoder(name: str, value: Any) -> Any

Decodes pair_distance_unit string to enum.

Parameters:

name (str) –

Attribute name
value (Any) –

Value to decode

Returns:

Any ( Any ) –

Decoded value

Source code in trajectopy\core\settings.py

@staticmethod
def decoder(name: str, value: Any) -> Any:
    """Decodes pair_distance_unit string to enum.

    Args:
        name: Attribute name
        value: Value to decode

    Returns:
        Any: Decoded value
    """
    return PairDistanceUnit(value) if name == "pair_distance_unit" else value

MatchingMethod ¶

Bases: Enum

Method for matching poses between two trajectories.

Attributes:

NEAREST_SPATIAL –

Match by nearest Euclidean distance
NEAREST_TEMPORAL –

Match by nearest timestamp
INTERPOLATION –

Match using linear interpolation (SLERP for rotations)
NEAREST_SPATIAL_INTERPOLATED –

Match spatially using k-nearest and 3D line fit
UNKNOWN –

Unknown matching method

InterpolationMethod ¶

Bases: Enum

Method for interpolation.

MatchingSettings `dataclass` ¶

MatchingSettings(
    method: MatchingMethod = INTERPOLATION,
    max_time_diff: float = 0.01,
    max_distance: float = 0.0,
    max_gap_size: float = 10.0,
    k_nearest: int = 2,
)

Bases: Settings

Configuration for trajectory matching.

Attributes:

method (MatchingMethod) –

Matching method to use. Defaults to INTERPOLATION.
max_time_diff (float) –

Maximum allowed time difference in seconds for temporal matching. Defaults to 0.01.
max_distance (float) –

Maximum allowed distance in meters for spatial matching. Defaults to 0.0.
max_gap_size (float) –

Maximum allowed gap size in seconds within trajectories. Defaults to 10.0.
k_nearest (int) –

Number of nearest neighbors for spatial interpolation matching. Defaults to 2.

encoder `staticmethod` ¶

encoder(name: str, value: Any) -> Any

Encodes method enum to string value.

Parameters:

name (str) –

Attribute name
value (Any) –

Value to encode

Returns:

Any ( Any ) –

Encoded value

Source code in trajectopy\core\settings.py

@staticmethod
def encoder(name: str, value: Any) -> Any:
    """Encodes method enum to string value.

    Args:
        name: Attribute name
        value: Value to encode

    Returns:
        Any: Encoded value
    """
    return value.value if name == "method" else value

decoder `staticmethod` ¶

decoder(name: str, value: Any) -> Any

Decodes method string to enum.

Parameters:

name (str) –

Attribute name
value (Any) –

Value to decode

Returns:

Any ( Any ) –

Decoded value

Source code in trajectopy\core\settings.py

@staticmethod
def decoder(name: str, value: Any) -> Any:
    """Decodes method string to enum.

    Args:
        name: Attribute name
        value: Value to decode

    Returns:
        Any: Decoded value
    """
    return MatchingMethod(value) if name == "method" else value

MPLPlotSettings `dataclass` ¶

MPLPlotSettings(
    colorbar_show_zero_crossing: bool = True,
    colorbar_steps: int = 4,
    colorbar_max_std: float = 3.0,
    scatter_hide_axes: bool = False,
    scatter_3d: bool = False,
    scatter_smooth: bool = False,
    scatter_smooth_window: int = 5,
    ate_unit_is_mm: bool = False,
    ate_remove_above: float = 0.0,
    hist_as_stairs: bool = False,
    hist_percentile: float = 1.0,
    directed_ate: bool = False,
    dofs_tab: bool = True,
    velocity_tab: bool = True,
    height_tab: bool = True,
)

Bases: Settings

Configuration for matplotlib plotting backend.

Attributes:

colorbar_show_zero_crossing (bool) –

Show zero in colorbar. Defaults to True.
colorbar_steps (int) –

Number of colorbar steps. Defaults to 4.
colorbar_max_std (float) –

Upper colorbar limit as mean + this * std. Defaults to 3.0.
scatter_hide_axes (bool) –

Hide axes in scatter plots. Defaults to False.
scatter_3d (bool) –

Use 3D scatter plots. Defaults to False.
scatter_smooth (bool) –

Smooth scatter plot color data. Defaults to False.
scatter_smooth_window (int) –

Window size for scatter smoothing. Defaults to 5.
ate_unit_is_mm (bool) –

Use millimeters for ATE units. Defaults to False.
ate_remove_above (float) –

Cap ATE values above this (0.0 = no cap). Defaults to 0.0.
hist_as_stairs (bool) –

Display histogram as stairs. Defaults to False.
hist_percentile (float) –

Show histogram data up to this percentile. Defaults to 1.0.
directed_ate (bool) –

Split ATE into along/cross-track directions. Defaults to False.
dofs_tab (bool) –

Show degrees of freedom tab. Defaults to True.
velocity_tab (bool) –

Show velocity tab. Defaults to True.
height_tab (bool) –

Show height tab. Defaults to True.

unit_multiplier `property` ¶

unit_multiplier: float

Gets unit multiplier for converting meters to display unit.

Returns:

float ( float ) –

1000 if using millimeters, 1 otherwise

unit_str `property` ¶

unit_str: str

Gets unit string for display.

Returns:

str ( str ) –

"[mm]" if using millimeters, "[m]" otherwise

PlotBackend ¶

Bases: Enum

Plotting backend selection.

SortingSettings `dataclass` ¶

SortingSettings(
    voxel_size: float = 0.05,
    movement_threshold: float = 0.005,
    k_nearest: int = 4,
)

Bases: Settings

Configuration for trajectory sorting and downsampling using Moving Least Squares.

Attributes:

voxel_size (float) –

Size of voxel grid for downsampling (meters). Voxel centroids are used for nearest neighbor searches instead of raw points. Defaults to 0.05.
movement_threshold (float) –

Maximum allowed point movement between MLS iterations (meters). Algorithm terminates when all points move less than this. Defaults to 0.005.
k_nearest (int) –

Number of nearest voxels to consider during MLS smoothing. Defaults to 4.

ProcessingSettings `dataclass` ¶

ProcessingSettings(
    alignment: AlignmentSettings = AlignmentSettings(),
    matching: MatchingSettings = MatchingSettings(),
    relative_comparison: RelativeComparisonSettings = RelativeComparisonSettings(),
    approximation: ApproximationSettings = ApproximationSettings(),
    sorting: SortingSettings = SortingSettings(),
)

Bases: Settings

Complete configuration for trajectory processing.

Combines all processing-related settings including alignment, matching, relative comparison, approximation, and sorting.

Attributes:

alignment (AlignmentSettings) –

Alignment configuration
matching (MatchingSettings) –

Matching configuration
relative_comparison (RelativeComparisonSettings) –

Relative comparison (RPE) configuration
approximation (ApproximationSettings) –

Approximation and smoothing configuration
sorting (SortingSettings) –

Sorting and downsampling configuration

ExportSettings `dataclass` ¶

ExportSettings(
    format: str = "png",
    height: int = 500,
    width: int = 800,
    scale: int = 1,
)

Bases: Settings

Configuration for exporting plots to image files.

Attributes:

format (str) –

Export format ("png", "svg", "jpeg", "webp"). Defaults to "png".
height (int) –

Export height in pixels. Defaults to 500.
width (int) –

Export width in pixels. Defaults to 800.
scale (int) –

Export scale factor. Defaults to 1.

to_config ¶

to_config() -> dict

Converts export settings to plotly configuration dictionary.

Returns:

dict ( dict ) –

Plotly toImageButtonOptions configuration

Source code in trajectopy\core\settings.py

def to_config(self) -> dict:
    """Converts export settings to plotly configuration dictionary.

    Returns:
        dict: Plotly toImageButtonOptions configuration
    """
    return {
        "toImageButtonOptions": {
            "format": self.format,
            "height": self.height,
            "width": self.width,
            "scale": self.scale,
        }
    }

ReportSettings `dataclass` ¶

ReportSettings(
    single_plot_height: int = 750,
    two_subplots_height: int = 750,
    three_subplots_height: int = 860,
    scatter_max_std: float = 4.0,
    ate_unit_is_mm: bool = False,
    ate_remove_above: float = 0.0,
    directed_ate: bool = False,
    histogram_opacity: float = 0.7,
    histogram_bargap: float = 0.1,
    histogram_barmode: str = "overlay",
    histogram_yaxis_title: str = "Count",
    plot_mode: str = "lines+markers",
    scatter_mode: str = "markers",
    scatter_colorscale: str = "RdYlBu_r",
    scatter_axis_order: str = "xy",
    scatter_marker_size: int = 5,
    scatter_show_individual_dofs: bool = False,
    scatter_smooth: bool = False,
    scatter_smooth_window: int = 5,
    scatter_plot_on_map: bool = False,
    scatter_mapbox_style: str = "open-street-map",
    scatter_mapbox_zoom: int = 15,
    scatter_mapbox_token: str = "",
    pos_x_name: str = "x",
    pos_y_name: str = "y",
    pos_z_name: str = "z",
    pos_x_unit: str = "m",
    pos_y_unit: str = "m",
    pos_z_unit: str = "m",
    directed_pos_dev_x_name: str = "along",
    directed_pos_dev_y_name: str = "cross-h",
    directed_pos_dev_z_name: str = "cross-v",
    rot_x_name: str = "roll",
    rot_y_name: str = "pitch",
    rot_z_name: str = "yaw",
    rot_unit: str = "°",
    single_plot_export: ExportSettings = (
        lambda: ExportSettings(width=800, height=540)
    )(),
    two_subplots_export: ExportSettings = (
        lambda: ExportSettings(width=800, height=540)
    )(),
    three_subplots_export: ExportSettings = (
        lambda: ExportSettings(width=800, height=750)
    )(),
)

Bases: Settings

Configuration for interactive HTML report generation (plotly backend).

Controls visualization, styling, and export settings for trajectory comparison reports. The along-track direction is positive in travel direction, horizontal cross-track is positive to the right, and vertical cross-track is positive upwards.

Attributes:

single_plot_height (int) –

Height of single plots in pixels. Defaults to 750.
two_subplots_height (int) –

Height of two-subplot figures in pixels. Defaults to 750.
three_subplots_height (int) –

Height of three-subplot figures in pixels. Defaults to 860.
scatter_max_std (float) –

Upper colorbar limit as mean + this * std (prevents outlier dominance). Defaults to 4.0.
ate_unit_is_mm (bool) –

Use millimeters for ATE instead of meters. Defaults to False.
ate_remove_above (float) –

Cap ATE values above this (0.0 = no cap). Defaults to 0.0.
directed_ate (bool) –

Split ATE into along-track, horizontal cross-track, and vertical cross-track directions. Defaults to False.
histogram_opacity (float) –

Opacity of histogram bars [0-1]. Defaults to 0.7.
histogram_bargap (float) –

Gap between histogram bars. Defaults to 0.1.
histogram_barmode (str) –

Display mode for histogram bars. Defaults to "overlay".
histogram_yaxis_title (str) –

Y-axis label for histograms. Defaults to "Count".
plot_mode (str) –

Display mode for line plots. Defaults to "lines+markers".
scatter_mode (str) –

Display mode for scatter plots. Defaults to "markers".
scatter_colorscale (str) –

Colorscale for scatter plots. Defaults to "RdYlBu_r".
scatter_axis_order (str) –

Axes to display in scatter plots ("xy" or "xyz"). Defaults to "xy".
scatter_marker_size (int) –

Size of scatter plot markers. Defaults to 5.
scatter_show_individual_dofs (bool) –

Show scatter plots for each degree of freedom. Defaults to False.
scatter_smooth (bool) –

Smooth scatter plot color data. Defaults to False.
scatter_smooth_window (int) –

Window size for scatter smoothing. Defaults to 5.
scatter_plot_on_map (bool) –

Plot trajectories on mapbox map (requires valid EPSG). Defaults to False.
scatter_mapbox_style (str) –

Mapbox style (some require token). Defaults to "open-street-map".
scatter_mapbox_zoom (int) –

Mapbox zoom level. Defaults to 15.
scatter_mapbox_token (str) –

Mapbox access token (optional). Defaults to "".
pos_x_name (str) –

Label for X position coordinate. Defaults to "x".
pos_y_name (str) –

Label for Y position coordinate. Defaults to "y".
pos_z_name (str) –

Label for Z position coordinate. Defaults to "z".
pos_x_unit (str) –

Unit symbol for X position. Defaults to "m".
pos_y_unit (str) –

Unit symbol for Y position. Defaults to "m".
pos_z_unit (str) –

Unit symbol for Z position. Defaults to "m".
directed_pos_dev_x_name (str) –

Label for along-track direction deviation. Defaults to "along".
directed_pos_dev_y_name (str) –

Label for horizontal cross-track deviation. Defaults to "cross-h".
directed_pos_dev_z_name (str) –

Label for vertical cross-track deviation. Defaults to "cross-v".
rot_x_name (str) –

Label for roll angle. Defaults to "roll".
rot_y_name (str) –

Label for pitch angle. Defaults to "pitch".
rot_z_name (str) –

Label for yaw angle. Defaults to "yaw".
rot_unit (str) –

Unit symbol for rotation angles. Defaults to "°".
single_plot_export (ExportSettings) –

Export settings for single plots.
two_subplots_export (ExportSettings) –

Export settings for two-subplot figures.
three_subplots_export (ExportSettings) –

Export settings for three-subplot figures.

comparison_method_from_string ¶

comparison_method_from_string(
    string: str,
) -> ComparisonMethod

Converts string to ComparisonMethod.

Parameters:

string (str) –

String containing "absolute" or "relative"

Returns:

ComparisonMethod ( ComparisonMethod ) –

ABSOLUTE, RELATIVE, or UNKNOWN

Source code in trajectopy\core\settings.py

def comparison_method_from_string(string: str) -> ComparisonMethod:
    """Converts string to ComparisonMethod.

    Args:
        string: String containing "absolute" or "relative"

    Returns:
        ComparisonMethod: ABSOLUTE, RELATIVE, or UNKNOWN
    """
    if "absolute" in string.lower():
        return ComparisonMethod.ABSOLUTE

    return ComparisonMethod.RELATIVE if "relative" in string.lower() else ComparisonMethod.UNKNOWN

Settings¶

settings ¶

Settings dataclass ¶

to_dict ¶

encoder staticmethod ¶

decoder staticmethod ¶

to_json ¶

to_file ¶

from_dict classmethod ¶

from_file classmethod ¶

update_from_dict ¶

AlignmentPreprocessing dataclass ¶

AlignmentEstimationSettings dataclass ¶

all_disabled property ¶

all_lq_disabled property ¶

helmert_enabled property ¶

leverarm_enabled property ¶

time_shift_enabled property ¶

short_mode_str property ¶

time_shift_filter property ¶

helmert_filter property ¶

leverarm_filter property ¶

enabled_lq_parameter_filter property ¶

lq_parameter_filter property ¶

__bool__ ¶

from_components classmethod ¶

all classmethod ¶

from_bool_list classmethod ¶

AlignmentStochastics dataclass ¶

var_xy_from property ¶

var_z_from property ¶

var_xy_to property ¶

var_z_to property ¶

var_roll_pitch property ¶

var_yaw property ¶

var_speed_to property ¶

AlignmentSettings dataclass ¶

__str__ ¶

ApproximationSettings dataclass ¶

PairDistanceUnit ¶

from_str classmethod ¶

ComparisonMethod ¶

from_string classmethod ¶

RelativeComparisonSettings dataclass ¶

encoder staticmethod ¶

decoder staticmethod ¶

MatchingMethod ¶

InterpolationMethod ¶

MatchingSettings dataclass ¶

encoder staticmethod ¶

decoder staticmethod ¶

MPLPlotSettings dataclass ¶

unit_multiplier property ¶

unit_str property ¶

PlotBackend ¶

SortingSettings dataclass ¶

ProcessingSettings dataclass ¶

ExportSettings dataclass ¶

to_config ¶

ReportSettings dataclass ¶

comparison_method_from_string ¶

Settings `dataclass` ¶

encoder `staticmethod` ¶

decoder `staticmethod` ¶

from_dict `classmethod` ¶

from_file `classmethod` ¶

AlignmentPreprocessing `dataclass` ¶

AlignmentEstimationSettings `dataclass` ¶

all_disabled `property` ¶

all_lq_disabled `property` ¶

helmert_enabled `property` ¶

leverarm_enabled `property` ¶

time_shift_enabled `property` ¶

short_mode_str `property` ¶

time_shift_filter `property` ¶

helmert_filter `property` ¶

leverarm_filter `property` ¶

enabled_lq_parameter_filter `property` ¶

lq_parameter_filter `property` ¶

bool ¶

from_components `classmethod` ¶

all `classmethod` ¶

from_bool_list `classmethod` ¶

AlignmentStochastics `dataclass` ¶

var_xy_from `property` ¶

var_z_from `property` ¶

var_xy_to `property` ¶

var_z_to `property` ¶

var_roll_pitch `property` ¶

var_yaw `property` ¶

var_speed_to `property` ¶

AlignmentSettings `dataclass` ¶

str ¶

ApproximationSettings `dataclass` ¶

from_str `classmethod` ¶

from_string `classmethod` ¶

RelativeComparisonSettings `dataclass` ¶

encoder `staticmethod` ¶

decoder `staticmethod` ¶

MatchingSettings `dataclass` ¶

encoder `staticmethod` ¶

decoder `staticmethod` ¶

MPLPlotSettings `dataclass` ¶

unit_multiplier `property` ¶

unit_str `property` ¶

SortingSettings `dataclass` ¶

ProcessingSettings `dataclass` ¶

ExportSettings `dataclass` ¶

ReportSettings `dataclass` ¶