| 1 | package dk.deepthought.sidious.rules; |
| 2 | |
| 3 | import java.util.ArrayList; |
| 4 | import java.util.Arrays; |
| 5 | import java.util.Collection; |
| 6 | |
| 7 | import dk.deepthought.sidious.goalhandler.Goal; |
| 8 | import dk.deepthought.sidious.greenhouse.ClimaticState; |
| 9 | import dk.deepthought.sidious.greenhouse.SensorInput; |
| 10 | import dk.deepthought.sidious.supportsystem.State; |
| 11 | import dk.deepthought.sidious.supportsystem.Step; |
| 12 | import dk.deepthought.sidious.supportsystem.SuperLinkID; |
| 13 | |
| 14 | /** |
| 15 | * Rule to keep conventionally unconstrained sensors constrained. I.e. adds cost |
| 16 | * to otherwise "free" adjustments. |
| 17 | * |
| 18 | * @author Deepthought |
| 19 | * |
| 20 | */ |
| 21 | public class ConstrainingRule extends Rule { |
| 22 | |
| 23 | /** |
| 24 | * A list of sensor id's which will be constrained by this. |
| 25 | */ |
| 26 | private Collection<SuperLinkID> idsToConstrain; |
| 27 | |
| 28 | /** |
| 29 | * Constructs a constraining rule that constrains sensors with input IDs. |
| 30 | * |
| 31 | * @param sensorIDs |
| 32 | * the ids of the sensors to constrain |
| 33 | */ |
| 34 | public ConstrainingRule(SuperLinkID... sensorIDs) { |
| 35 | idsToConstrain = Arrays.asList(sensorIDs); |
| 36 | } |
| 37 | |
| 38 | /* |
| 39 | * (non-Javadoc) |
| 40 | * |
| 41 | * @see dk.deepthought.sidious.rules.Rule#desire(dk.deepthought.sidious.supportsystem.State, |
| 42 | * dk.deepthought.sidious.supportsystem.State, dk.deepthought.sidious.supportsystem.Step) |
| 43 | */ |
| 44 | @Override |
| 45 | public double desire(State currentState, State newState, Step step) { |
| 46 | ClimaticState currentClima = null; |
| 47 | ClimaticState newClima = null; |
| 48 | if (currentState instanceof ClimaticState) { |
| 49 | currentClima = (ClimaticState) currentState; |
| 50 | } |
| 51 | if (newState instanceof ClimaticState) { |
| 52 | newClima = (ClimaticState) newState; |
| 53 | } |
| 54 | if (currentClima == null || newClima == null) { |
| 55 | throw new IllegalArgumentException( |
| 56 | "Only climaticStates allowed as parameters!"); |
| 57 | } |
| 58 | double returnValue = 0; |
| 59 | for (SuperLinkID id : idsToConstrain) { |
| 60 | SensorInput currentSensor = null; |
| 61 | SensorInput newSensor = null; |
| 62 | for (SensorInput sensor : currentClima.getSensors()) { |
| 63 | if (sensor.getID().equals(id)) { |
| 64 | currentSensor = sensor; |
| 65 | break; |
| 66 | } |
| 67 | } |
| 68 | for (SensorInput sensor : newClima.getSensors()) { |
| 69 | if (sensor.getID().equals(id)) { |
| 70 | newSensor = sensor; |
| 71 | break; |
| 72 | } |
| 73 | } |
| 74 | returnValue += normalizedDistance(currentSensor, newSensor); |
| 75 | } |
| 76 | return returnValue; |
| 77 | } |
| 78 | |
| 79 | /* |
| 80 | * (non-Javadoc) |
| 81 | * |
| 82 | * @see dk.deepthought.sidious.rules.Rule#getGoals() |
| 83 | */ |
| 84 | @Override |
| 85 | public Collection<Goal> getGoals() { |
| 86 | return new ArrayList<Goal>(); |
| 87 | } |
| 88 | |
| 89 | /** |
| 90 | * Calculates the normalized distance between two sensors. |
| 91 | * <p> |
| 92 | * It takes two sensors and normalizes the distance between them to a value |
| 93 | * between 0 and 1. |
| 94 | * |
| 95 | * @param currentSensor |
| 96 | * the first sensor |
| 97 | * @param newSensor |
| 98 | * the second sensor |
| 99 | * @return the normalized value of the distance. |
| 100 | */ |
| 101 | private double normalizedDistance(SensorInput currentSensor, |
| 102 | SensorInput newSensor) { |
| 103 | double newValue = newSensor == null ? 0 : newSensor.getValue(); |
| 104 | double currentValue = currentSensor == null ? 0 : currentSensor |
| 105 | .getValue(); |
| 106 | double normalizer; |
| 107 | double distance = Math.abs(newValue - currentValue); |
| 108 | // Normalizes to log 10 value |
| 109 | if (Math.abs(newValue) > 0 && Math.abs(currentValue) > 0 |
| 110 | && Math.abs(distance) > 0) { |
| 111 | double flooredNorm = Math.floor(Math.min(Math.log10(distance), Math |
| 112 | .min(Math.log10(newValue), Math.log10(currentValue)))); |
| 113 | normalizer = flooredNorm > 0 ? flooredNorm : 0; |
| 114 | } else { |
| 115 | normalizer = 0; |
| 116 | } |
| 117 | if (normalizer >= 0) { |
| 118 | normalizer += 1; |
| 119 | double div = Math.pow(10, normalizer); |
| 120 | newValue /= div; |
| 121 | currentValue /= div; |
| 122 | distance = Math.abs(newValue - currentValue); |
| 123 | } |
| 124 | if (distance > 1) { |
| 125 | distance = 1; |
| 126 | } |
| 127 | return distance; |
| 128 | } |
| 129 | |
| 130 | } |