sensorarray

class pyvale.sensorarray.ISensorArray

Bases: ABC

Interface (abstract base class) for an array of sensors of the same type sampling a given physical field.

This class implements the pyvale sensor measurement simulation model. Here a measurement is taken as: measurement = truth + random errors + systematic errors. The truth value for each sensor is interpolated from the physical field (an implementation of the IField interface, nominally a FieldScalar, FieldVector or FieldTensor object).

The random and systematic errors are calculated by a user specified error integrator (ErrIntegrator class). This class contains a chain of different types of user selected errors (implementations of the IErrCalculator interface). Further information can be found in the ErrIntegrator class and in implementations of the IErrCalculator interface.

In pyvale, function and methods with calc in their name will cause probability distributions to be resampled and any additional calculations, such as interpolation, to be performed. Functions and methods with get in the name will directly return the previously calculated values without resampling probability distributions.

Calling the class method calc_measurements() will create and return an array of simulated sensor measurements with the following shape=(num_sensors ,num_field_component,num_time_steps). When calling calc_measurements() all sensor errors that are based on probability distributions are resampled and any required interpolations are performed (e.g. a random perturbation of the sensor positions requiring interpolation at the perturbed sensor location).

Calling the class method get_measurements() just returns the previously calculated set of sensor measurements without resampling of probability. Distributions.

Without an error integrator this class can be used for interpolating simulated physical fields quickly using finite element shape functions.

abstractmethod calc_measurements() → ndarray

Abstract method. Calculates measurements as: measurement = truth + systematic errors + random errors. The truth is calculated once and is interpolated from the input simulation field. The errors are calculated based on the user specified error chain.

NOTE: this is a 'calc' method and will sample all probability distributions in the error chain returning a new simulated experiment for this sensor array.

Returns:

np.ndarray -- The calculated measurements for this sensor array with shape: (num_sensors,num_field_components,num_time_steps)

abstractmethod get_errors_random() → ndarray | None

Abstract method. Gets the random error array from the previously calculated sensor measurements. Returns None is no error integrator has been specified.

Returns:

np.ndarray | None -- Array of random errors for this sensor array. shape=(num_sensors ,num_field_components,num_time_steps). Returns None if no error integrator has been set.

abstractmethod get_errors_systematic() → ndarray | None

Abstract method. Gets the systematic error array from the previously calculated sensor measurements. Returns None is no error integrator has been specified.

Returns:

np.ndarray | None -- Array of systematic errors for this sensor array. shape=(num_sensors ,num_field_components,num_time_steps). Returns None if no error integrator has been set.

abstractmethod get_errors_total() → ndarray | None

Abstract method. Gets the total error array from the previously calculated sensor measurements. Returns None is no error integrator has been specified.

Returns:

np.ndarray | None -- Array of total errors for this sensor array. shape=(num_sensors ,num_field_components,num_time_steps). Returns None if no error integrator has been set.

abstractmethod get_field() → IField

Abstract method. Gets the field object that this array of sensors is sampling to simulate measurements.

Returns:

IField -- A field object interface.

abstractmethod get_measurement_shape() → tuple[int, int, int]

Abstract method. Gets the shape of the measurement array: shape=(num_sensors,num_field_components,num_time_steps).

The number of sensors is specified by the user with a SensorData object. The number of field components is dependent on the field being sampled (i.e. 1 for a scalar field and 3 for a vector field in 3D). The number of time steps is specified by the user in the SensorData object or defaults to the time steps taken from the simulation.

Returns:

tuple[int,int,int] -- Shape of the measurement array as (num_sensors, num_field_components,num_time_steps)

abstractmethod get_measurements() → ndarray

Abstract method. Returns the current set of simulated measurements if theses have been calculated. If these have not been calculated then 'calc_measurements()' is called and a set of measurements in then returned.

NOTE: this is a 'get' method and does not sample from probability distributions in the error chain and directly returns the current set of measurements if they exist.

Returns:

np.ndarray -- The calculated measurements for this sensor array with shape: (num_sensors,num_field_components,num_time_steps)

abstractmethod get_truth() → ndarray

Abstract method. Gets the ground truth sensor values that were calculated previously. If the ground truth values have not been calculated then calc_truth_values() is called first.

Returns:

np.ndarray -- Array of ground truth sensor values. shape=(num_sensors, num_field_components,num_time_steps).