NavigationInterpolators

class NavigationInterpolatorLatLon(*args, **kwargs)

The NavInterpolator class: Interpolate navigation (lat/lon) values and attitude information and transform the values using the offsets specified in the sensor configuration class

__init__(self, sensor_configuration: SensorConfiguration, extrapolation_mode: themachinethatgoesping.tools_nanopy.vectorinterpolators.o_extr_mode = t_extr_mode.extrapolate) → None

Construct a new i navigationinterpolator interface

Parameters:

• sensor_configuration – sensor configuration used for this navigation interpolator

• extrapolation_mode – extrapolate, fail or nearest

add_target(self, target_id: str, x: float, y: float, z: float, yaw: float, pitch: float, roll: float) → None

add_target(self, target_id: str, target_offsets: PositionalOffsets) → None

Overloaded function.

1. add_target(self, target_id: str, x: float, y: float, z: float, yaw: float, pitch: float, roll: float) -> None

add a target sensor with positional offsets

Parameters:

• target_id – name of the target sensor

• x – x position of the sensor in m, positive forward

• y – y position of the sensor in m, positive starboard

• z – z position of the sensor in m, positive down

• yaw – yaw angle of the sensor in °, positive clockwise

• pitch – pitch angle of the sensor in °, positive is bow up

• roll – roll angle of the sensor in °, positive is port up

2. add_target(self, target_id: str, target_offsets: themachinethatgoesping.navigation_nanopy.datastructures.PositionalOffsets) -> None

add a target sensor with positional offsets

Parameters:

• target_id – name of the target sensor

• sensor_offsets – structure that contains the sensor position

compute_target_position(self, target_id: str, timestamp: float) → GeolocationLatLon

compute_target_position(self, target_id: str, timestamps: Sequence[float], mp_cores: int = 1) → themachinethatgoesping.navigation_nanopy.datastructures.GeolocationLatLonVector

Overloaded function.

1. compute_target_position(self, target_id: str, timestamp: float) -> themachinethatgoesping.navigation_nanopy.datastructures.GeolocationLatLon

Compute the position of the target “target_id” based on the sensor data for the given timestamp stamp

Parameters:

• target_id – name of the target (e.g. “MBES”)

• timestamp – timestamp in seconds since epoch

Returns:

data structure that contains the position of the target in the world coordinate system

2. compute_target_position(self, target_id: str, timestamps: collections.abc.Sequence[float], mp_cores: int = 1) -> themachinethatgoesping.navigation_nanopy.datastructures.GeolocationLatLonVector

Compute the position of the target “target_id” for multiple timestamps (vectorized)

Parameters:

• target_id – name of the target (e.g. “MBES”)

• timestamps – vector of timestamps in seconds since epoch

• mp_cores – Number of OpenMP threads to use for parallelization. Default is 1

Returns:

GeolocationLatLonVector containing positions for all timestamps

copy(self) → NavigationInterpolatorLatLon

return a copy using the c++ default copy constructor

from_binary = <nanobind.nb_func object>

get_sampled_timestamps(self, downsample_interval: float = nan, max_gap: float = nan, sensor_names: Set[str] = {'longitude', 'latitude'}) → numpy.ndarray[dtype=float64, order='C']

Get sampled timestamps from the specified sensor interpolators

This function retrieves timestamps from the specified sensors and returns their intersection (timestamps that are common to all specified sensors within max_gap).

Parameters:

• downsample_interval – Interval for downsampling timestamps. If NaN, no downsampling

• max_gap – Maximum allowed gap between consecutive timestamps

• sensor_names – Set of sensor names to include. Valid names are: “latitude”, “longitude”, “attitude”, “heading”, “heave”, “depth”

Returns:

xt::xtensor<double, 1> Array of timestamps that are common to all

specified sensors

get_sensor_configuration(self) → SensorConfiguration

direct reference to the sensor configuration

Returns:

SensorConfiguration&

get_sensor_data(self, timestamp: float) → SensordataLatLon

get_sensor_data(self, timestamps: Sequence[float], mp_cores: int = 1) → themachinethatgoesping.navigation_nanopy.datastructures.SensordataLatLonVector

Overloaded function.

1. get_sensor_data(self, timestamp: float) -> themachinethatgoesping.navigation_nanopy.datastructures.SensordataLatLon

Interpolate the saved sensor data for a specified timestamp stamp

Parameters:

timestamp – timestamp in seconds since epoch

Returns:

data structure that contains the sensor data interpolated for the given timestamp stamp

2. get_sensor_data(self, timestamps: collections.abc.Sequence[float], mp_cores: int = 1) -> themachinethatgoesping.navigation_nanopy.datastructures.SensordataLatLonVector

Interpolate the saved sensor data for multiple timestamps (vectorized)

Parameters:

• timestamps – vector of timestamps in seconds since epoch

• mp_cores – Number of OpenMP threads to use for parallelization. Default is 1

Returns:

SensordataLatLonVector containing sensor data for all timestamps

hash(self) → int

hash function implemented using binary_hash

info_string(self, float_precision: int = 3, superscript_exponents: bool = True) → str

Return object information as string

property interpolator_attitude

interpolator that stores attitude data (pitch and roll)

property interpolator_depth

interpolator that stores depth data (depth, positive downwards) [m]

property interpolator_heading

interpolator that stores compass data (yaw/heading) [°]

property interpolator_heave

interpolator that stores heave data (relative change in depth, positive upwards) [m]

property interpolator_latitude

interpolator for the latitude data

property interpolator_longitude

interpolator for the longitude data

merge(self, other: NavigationInterpolatorLatLon) → None

Merge data from another interpolator. Only works of the SensorConfiguration is compatible.

Parameters:

other

print(self, float_precision: int = 3, superscript_exponents: bool = True) → None

Print object information

set_data_attitude(self, timestamp: Sequence[float], pitch: Sequence[float], roll: Sequence[float]) → None

Set the attitude data (no yaw, this is set in set_data_heading)

Parameters:

• timestamp – in seconds since epoch

• pitch – in °, positive is bow up

• roll – in °, positive is port up

set_data_depth(self, timestamp: Sequence[float], depth: Sequence[float]) → None

Set the depth data

Parameters:

• timestamp – in seconds since epoch

• depth – in meters, positive downwards

set_data_heading(self, timestamp: Sequence[float], heading: Sequence[float]) → None

Set the compass data

Parameters:

• timestamp – in seconds since epoch

• heading – in °, positive clockwise (north is 0°)

set_data_heave(self, timestamp: Sequence[float], heave: Sequence[float]) → None

Set the heave data

Parameters:

• timestamp – in seconds since epoch

• heave – in meters, positive upwards

set_data_position(self, timestamp: Sequence[float], latitude: Sequence[float], longitude: Sequence[float]) → None

Set the data of the position system (latitude, longitude)

Parameters:

• timestamp – in seconds since epoch

• latitude – latitude in °

• longitude – longitude in °

set_extrapolation_mode(self, extrapolation_mode: themachinethatgoesping.tools_nanopy.vectorinterpolators.o_extr_mode = t_extr_mode.extrapolate) → None

Set the extrapolation mode for all interpolators

Parameters:

extrapolation_mode – extrapolate, fail or nearest

set_sensor_configuration(self, sensor_configuration: SensorConfiguration) → None

to_binary(self, resize_buffer: bool = True) → bytes

convert object to bytearray

class NavigationInterpolatorLocal(*args, **kwargs)

The NavInterpolator class: Interpolate navigation (northing/easting no zone specified) values and attitude information and transform the values using the offsets specified in the sensor configuration class

__init__(self, sensor_configuration: SensorConfiguration, extrapolation_mode: themachinethatgoesping.tools_nanopy.vectorinterpolators.o_extr_mode = t_extr_mode.extrapolate) → None

Construct a new i navigationinterpolator interface

Parameters:

• sensor_configuration – sensor configuration used for this navigation interpolator

• extrapolation_mode – extrapolate, fail or nearest

add_target(self, target_id: str, x: float, y: float, z: float, yaw: float, pitch: float, roll: float) → None

add_target(self, target_id: str, target_offsets: PositionalOffsets) → None

Overloaded function.

1. add_target(self, target_id: str, x: float, y: float, z: float, yaw: float, pitch: float, roll: float) -> None

add a target sensor with positional offsets

Parameters:

• target_id – name of the target sensor

• x – x position of the sensor in m, positive forward

• y – y position of the sensor in m, positive starboard

• z – z position of the sensor in m, positive down

• yaw – yaw angle of the sensor in °, positive clockwise

• pitch – pitch angle of the sensor in °, positive is bow up

• roll – roll angle of the sensor in °, positive is port up

2. add_target(self, target_id: str, target_offsets: themachinethatgoesping.navigation_nanopy.datastructures.PositionalOffsets) -> None

add a target sensor with positional offsets

Parameters:

• target_id – name of the target sensor

• sensor_offsets – structure that contains the sensor position

compute_target_position(self, target_id: str, timestamp: float) → GeolocationLocal

compute_target_position(self, target_id: str, timestamps: Sequence[float], mp_cores: int = 1) → themachinethatgoesping.navigation_nanopy.datastructures.GeolocationLocalVector

Overloaded function.

1. compute_target_position(self, target_id: str, timestamp: float) -> themachinethatgoesping.navigation_nanopy.datastructures.GeolocationLocal

Compute the position of the target “target_id” based on the sensor data for the given timestamp stamp

Parameters:

• target_id – name of the target (e.g. “MBES”)

• timestamp – timestamp in seconds since epoch

Returns:

data structure that contains the position of the target in the world coordinate system

2. compute_target_position(self, target_id: str, timestamps: collections.abc.Sequence[float], mp_cores: int = 1) -> themachinethatgoesping.navigation_nanopy.datastructures.GeolocationLocalVector

Compute the position of the target “target_id” for multiple timestamps (vectorized)

Parameters:

• target_id – name of the target (e.g. “MBES”)

• timestamps – vector of timestamps in seconds since epoch

• mp_cores – Number of OpenMP threads to use for parallelization. Default is 1

Returns:

GeolocationLocalVector containing positions for all timestamps

copy(self) → NavigationInterpolatorLocal

return a copy using the c++ default copy constructor

from_binary = <nanobind.nb_func object>

get_sampled_timestamps(self, downsample_interval: float = nan, max_gap: float = nan, sensor_names: Set[str] = {'easting', 'northing'}) → numpy.ndarray[dtype=float64, order='C']

Get sampled timestamps from the specified sensor interpolators

This function retrieves timestamps from the specified sensors and returns their intersection (timestamps that are common to all specified sensors within max_gap).

Parameters:

• downsample_interval – Interval for downsampling timestamps. If NaN, no downsampling

• max_gap – Maximum allowed gap between consecutive timestamps

• sensor_names – Set of sensor names to include. Valid names are: “northing”, “easting”, “attitude”, “heading”, “heave”, “depth”

Returns:

xt::xtensor<double, 1> Array of timestamps that are common to all

specified sensors

Raises:

std::invalid_argument – if an unknown sensor name is specified

get_sensor_configuration(self) → SensorConfiguration

direct reference to the sensor configuration

Returns:

SensorConfiguration&

get_sensor_data(self, timestamp: float) → SensordataLocal

get_sensor_data(self, timestamps: Sequence[float], mp_cores: int = 1) → themachinethatgoesping.navigation_nanopy.datastructures.SensordataLocalVector

Overloaded function.

1. get_sensor_data(self, timestamp: float) -> themachinethatgoesping.navigation_nanopy.datastructures.SensordataLocal

Interpolate the saved sensor data for a specified timestamp stamp

Parameters:

timestamp – timestamp in seconds since epoch

Returns:

data structure that contains the sensor data interpolated for the given timestamp stamp

2. get_sensor_data(self, timestamps: collections.abc.Sequence[float], mp_cores: int = 1) -> themachinethatgoesping.navigation_nanopy.datastructures.SensordataLocalVector

Interpolate the saved sensor data for multiple timestamps (vectorized)

Parameters:

• timestamps – vector of timestamps in seconds since epoch

• mp_cores – Number of OpenMP threads to use for parallelization. Default is 1

Returns:

SensordataLocalVector containing sensor data for all timestamps

hash(self) → int

hash function implemented using binary_hash

info_string(self, float_precision: int = 3, superscript_exponents: bool = True) → str

Return object information as string

property interpolator_attitude

interpolator that stores attitude data (pitch and roll)

property interpolator_depth

interpolator that stores depth data (depth, positive downwards) [m]

property interpolator_easting

interpolator for the easting data

property interpolator_heading

interpolator that stores compass data (yaw/heading) [°]

property interpolator_heave

interpolator that stores heave data (relative change in depth, positive upwards) [m]

property interpolator_northing

interpolator for the northing data

merge(self, other: NavigationInterpolatorLocal) → None

Merge data from another interpolator. Only works of the SensorConfiguration is compatible.

Parameters:

other

print(self, float_precision: int = 3, superscript_exponents: bool = True) → None

Print object information

set_data_attitude(self, timestamp: Sequence[float], pitch: Sequence[float], roll: Sequence[float]) → None

Set the attitude data (no yaw, this is set in set_data_heading)

Parameters:

• timestamp – in seconds since epoch

• pitch – in °, positive is bow up

• roll – in °, positive is port up

set_data_depth(self, timestamp: Sequence[float], depth: Sequence[float]) → None

Set the depth data

Parameters:

• timestamp – in seconds since epoch

• depth – in meters, positive downwards

set_data_heading(self, timestamp: Sequence[float], heading: Sequence[float]) → None

Set the compass data

Parameters:

• timestamp – in seconds since epoch

• heading – in °, positive clockwise (north is 0°)

set_data_heave(self, timestamp: Sequence[float], heave: Sequence[float]) → None

Set the heave data

Parameters:

• timestamp – in seconds since epoch

• heave – in meters, positive upwards

set_data_position(self, timestamp: Sequence[float], northing: Sequence[float], easting: Sequence[float]) → None

Set the data of the position system (northing, easting)

Parameters:

• timestamp – in seconds since epoch

• northing – northing in meters

• easting – easting in meters

set_extrapolation_mode(self, extrapolation_mode: themachinethatgoesping.tools_nanopy.vectorinterpolators.o_extr_mode = t_extr_mode.extrapolate) → None

Set the extrapolation mode for all interpolators

Parameters:

extrapolation_mode – extrapolate, fail or nearest

set_sensor_configuration(self, sensor_configuration: SensorConfiguration) → None

to_binary(self, resize_buffer: bool = True) → bytes

convert object to bytearray