src.blocks.DecisionMaking module

This module is responsible for decision making.

It includes one class for the decision making. See details in its own documentation.

Contact person: Stefan Riedmaier Creation date: 20.04.2020 Python version: 3.8

class src.blocks.DecisionMaking.DecisionMaking(config, domain)

Bases: object

This class is responsible for decision making.

It includes one main method called “check_tolerances” for the decision making in the validation domain and one main method called “check_regulation” for the decision making in the application domain. See more details in the documentation of the check_tolerances and check_regulation method.

static calculate_iso19364_boundaries(x, y, axis=-1, y_offset=5.0, y_gain=0.03, x_offset=0.1, x_gain=0.06)

This function calculates the ISO 19364 time series boundaries.

Example: - x: lateral acceleration with x_offset = 0.1 and x_gain = 0.06 - y: steering wheel angle with y_offset = 5.0 and y_gain = 0.03

Parameters:

  • x (np.ndarray) – input signal

  • y (np.ndarray) – output signal

  • axis – along this axis the operations shall be applied

  • y_offset (float) – aditive tolerance for the output quantity

  • y_gain (float) – multiplicative tolerance for the output quantity

  • x_offset (float) – aditive tolerance for the input quantity

  • x_gain (float) – multiplicative tolerance for the input quantity

Returns:

x and y values of bottom and top boundaries

Return type:

(np.ndarray, np.ndarray, np.ndarray, np.ndarray)

check_regulation(qois_kpi_da)

This function compares assessment results with regulation thresholds.

It returns a boolean data array with the same shape as the input array, as well as one global boolean value.

Parameters:

qois_kpi_da (xr.DataArray) – result data array

Returns:

boolean decision data array and overall boolean value

Return type:

tuple(xr.DataArray, bool)

check_tolerances(metric_da, qois_model_da, qois_system_da)

This function compares model validation results with defined thresholds.

It offers absolute and relative tolerances as well as tolerances based on ISO 19364 with interleaves (calculate_iso19364_boundaries).

It returns a boolean data array with the same shape as the input array, as well as one global boolean value.

Parameters:

  • metric_da (xr.DataArray) – data array from validation metric

  • qois_model_da (xr.DataArray) – data array of the model from the qoi assessment

  • qois_system_da (xr.DataArray) – data array of the system from the qoi assessment

Returns:

boolean decision data array and overall boolean value

Return type:

tuple(xr.DataArray, bool)