diff --git a/.gitlab-ci.yml b/.gitlab-ci.yml
index 7e77a76053345e34f70811b6498a8758dbf7d305..918f65ab8164ff97f01d7e37dc1fa86b7bfd3766 100644
--- a/.gitlab-ci.yml
+++ b/.gitlab-ci.yml
@@ -4,15 +4,23 @@ stages:
- report
variables:
+ # Instruct Testcontainers to use the daemon of DinD.
+ DOCKER_HOST: "unix:///var/run/docker.sock"
+# # Improve performance with overlayfs.
+# DOCKER_DRIVER: overlay2
GRADLE_OPTS: "-Dorg.gradle.daemon=false"
TEST_REPORTS: "/builds/OpenLicht/eraser/eraser-base/build/reports/tests/test/"
+ TEST_LOG: "/builds/OpenLicht/eraser/eraser-base/logs/eraser-test.log"
JACOCO_REPORT: "/builds/OpenLicht/eraser/eraser-base/build/reports/jacoco/test/jacocoTestReport.xml"
+ TESTCONTAINERS_RYUK_DISABLED: "true"
before_script:
- export GRADLE_USER_HOME=`pwd`/.gradle
build:
- image: gradle:jdk8
+ image: openjdk:8
+ tags:
+ - docker
stage: build
script:
- ./gradlew --console=plain --build-cache assemble
@@ -24,7 +32,9 @@ build:
- .gradle
test:
- image: gradle:jdk8
+ image: openjdk:8
+ tags:
+ - docker
stage: test
script:
- ./gradlew --continue --console=plain check jacocoTestReport
@@ -37,11 +47,14 @@ test:
artifacts:
when: always
paths:
+ - $TEST_LOG
- $TEST_REPORTS
- $JACOCO_REPORT
coverage:
image: python:3.7.1-alpine
+ tags:
+ - docker
stage: report
dependencies:
- test
diff --git a/build.gradle b/build.gradle
index 7348f5134a49d4e0231a68894601c7c8684af1d6..60b72b700ec5d34db48006da121885e5adc6b4d4 100644
--- a/build.gradle
+++ b/build.gradle
@@ -31,4 +31,12 @@ subprojects {
artifacts {
testArtifacts testJar
}
+
+ dependencies {
+ compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.2'
+ compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.2'
+ testCompile group: 'junit', name: 'junit', version: '4.12'
+ testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
+ }
+
}
diff --git a/commons.color/build.gradle b/commons.color/build.gradle
index 135a0194474bfeab48418cd7589d117a4f360805..b94df8ebb2332f7ee82611202e287541a285d86b 100644
--- a/commons.color/build.gradle
+++ b/commons.color/build.gradle
@@ -7,12 +7,7 @@ apply plugin: 'java'
sourceCompatibility = 1.8
dependencies {
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- compile 'org.apache.commons:commons-math3:3.6.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
+ compile group: 'org.apache.commons', name: 'commons-math3', version: '3.6.1'
}
sourceSets {
diff --git a/eraser-base/build.gradle b/eraser-base/build.gradle
index 3a10d245278fb767c332deca63785bfb0c60a270..78903e66d8d681ff431c671c6e17c75145bfdce4 100644
--- a/eraser-base/build.gradle
+++ b/eraser-base/build.gradle
@@ -5,23 +5,24 @@ repositories {
apply plugin: 'jastadd'
apply plugin: 'application'
apply plugin: 'jacoco'
+apply plugin: 'idea'
+apply plugin: 'distribution'
dependencies {
compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
compile group: 'net.sf.beaver', name: 'beaver-rt', version: '0.9.11'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- compile 'org.fusesource.mqtt-client:mqtt-client:1.14'
- compile 'org.apache.commons:commons-math3:3.6.1'
- compile 'org.influxdb:influxdb-java:2.14'
- testCompile group: 'junit', name: 'junit', version: '4.12'
+ compile group: 'org.fusesource.mqtt-client', name: 'mqtt-client', version: '1.15'
+ compile group: 'org.influxdb', name: 'influxdb-java', version: '2.15'
+ testCompile group: 'org.testcontainers', name: 'testcontainers', version: '1.11.2'
+ testCompile group: 'org.testcontainers', name: 'influxdb', version: '1.11.2'
+ testCompile group: 'org.apache.logging.log4j', name: 'log4j-slf4j-impl', version: '2.11.2'
}
buildscript {
repositories.mavenLocal()
repositories.mavenCentral()
dependencies {
- classpath 'org.jastadd:jastaddgradle:1.13.2'
+ classpath group: 'org.jastadd', name: 'jastaddgradle', version: '1.13.2'
}
}
@@ -47,18 +48,22 @@ jacocoTestReport {
}
}
+def relastFiles = fileTree('src/main/jastadd/') {
+ include '**/*.relast' }.toList().toArray()
+String[] relastArguments = [
+ "libs/relast.jar",
+ "--grammarName=./src/main/jastadd/mainGen",
+ "--useJastAddNames",
+ "--listClass=RefList",
+ "--jastAddList=JastAddList",
+ "--file"
+]
task preprocess(type: JavaExec) {
group = 'Build'
main = "-jar"
- args = [
- "libs/relast-compiler.jar",
- "./src/main/jastadd/main.relast",
- "--listClass=RefList",
- "--jastAddList=JastAddList",
- "--file"
- ]
-
- inputs.files file("./src/main/jastadd/main.relast")
+ args relastArguments + relastFiles
+
+ inputs.files relastFiles
outputs.files file("./src/main/jastadd/mainGen.ast"), file("./src/main/jastadd/mainGen.jadd")
}
@@ -79,6 +84,12 @@ jastadd {
parser.genDir = "src/gen/java/de/tudresden/inf/st/eraser/jastadd/parser"
}
+idea {
+ module {
+ generatedSourceDirs += file('src/gen/java')
+ }
+}
+
sourceSets.main {
java {
srcDir 'src/gen/java'
diff --git a/eraser-base/libs/relast-compiler.jar b/eraser-base/libs/relast-compiler.jar
deleted file mode 100644
index a1a9b656a4eb4f990decbcb8a522b063332133bf..0000000000000000000000000000000000000000
Binary files a/eraser-base/libs/relast-compiler.jar and /dev/null differ
diff --git a/eraser-base/libs/relast.jar b/eraser-base/libs/relast.jar
new file mode 100644
index 0000000000000000000000000000000000000000..9b52866a399cfdd0c4fe29c102125beab5d77989
Binary files /dev/null and b/eraser-base/libs/relast.jar differ
diff --git a/eraser-base/src/main/jastadd/AdditionalTypes.jadd b/eraser-base/src/main/jastadd/AdditionalTypes.jadd
index bd81b87f0419f275d10c95a09a9c4205999e47bc..32651117408970af5b3a57f4ddc48e2f7f2a0d8c 100644
--- a/eraser-base/src/main/jastadd/AdditionalTypes.jadd
+++ b/eraser-base/src/main/jastadd/AdditionalTypes.jadd
@@ -11,15 +11,19 @@ aspect AdditionalTypes {
}
}
- public class StringMap extends beaver.Symbol implements Iterable<AbstractMap.SimpleEntry<String, String>> {
- private java.util.Deque<AbstractMap.SimpleEntry<String, String>> delegatee = new java.util.ArrayDeque<>();
+ public class TypedKeyMap<T> extends beaver.Symbol implements Iterable<AbstractMap.SimpleEntry<T, String>> {
+ private java.util.Deque<AbstractMap.SimpleEntry<T, String>> delegatee = new java.util.ArrayDeque<>();
- public java.util.Iterator<AbstractMap.SimpleEntry<String, String>> iterator() {
+ public java.util.Iterator<AbstractMap.SimpleEntry<T, String>> iterator() {
return delegatee.descendingIterator();
}
- public void put(String key, String value) {
+ public void put(T key, String value) {
delegatee.add(new AbstractMap.SimpleEntry<>(key, value));
}
}
+
+ public class StringKeyMap extends TypedKeyMap<String> { }
+
+ public class IntegerKeyMap extends TypedKeyMap<Integer> { }
}
diff --git a/eraser-base/src/main/jastadd/DecisionTree.jrag b/eraser-base/src/main/jastadd/DecisionTree.jrag
index 84894e304b8573a1997018d7977fca8aba55ce7e..f50ca0562a920844e46a838c0f655f97bf804a01 100644
--- a/eraser-base/src/main/jastadd/DecisionTree.jrag
+++ b/eraser-base/src/main/jastadd/DecisionTree.jrag
@@ -4,20 +4,20 @@ aspect DecisionTree {
public class DecisionTreeLeaf implements Leaf { }
//--- classify ---
- syn Leaf DecisionTreeRoot.classify() {
+ syn DecisionTreeLeaf DecisionTreeRoot.classify() {
return getRootRule().classify();
}
- syn Leaf DecisionTreeElement.classify();
+ syn DecisionTreeLeaf DecisionTreeElement.classify();
- syn Leaf DecisionTreeRule.classify();
+ syn DecisionTreeLeaf DecisionTreeRule.classify();
- syn Leaf ItemStateCheckRule.classify() {
+ syn DecisionTreeLeaf ItemStateCheckRule.classify() {
boolean chooseLeft = getItemStateCheck().holds();
return (chooseLeft ? getLeft() : getRight()).classify();
}
- syn Leaf DecisionTreeLeaf.classify() = this;
+ syn DecisionTreeLeaf DecisionTreeLeaf.classify() = this;
//--- holds ---
syn boolean ItemStateCheck.holds() = holdsFor(getItem());
@@ -46,6 +46,27 @@ aspect DecisionTree {
return false;
}
+ //--- computePreferences ---
+ syn List<ItemPreference> DecisionTreeLeaf.computePreferences() {
+ // iterate over preference of this leaf, and all its parents and ancestors
+ List<ItemPreference> result = new ArrayList<>();
+ Set<Item> seenItems = new HashSet<>();
+ List<DecisionTreeElement> ancestors = ancestors();
+ for (ItemPreference pref : getPreferenceList()) {
+ result.add(pref);
+ seenItems.add(pref.getItem());
+ }
+ for (DecisionTreeElement ancestor : ancestors) {
+ for (ItemPreference pref : ancestor.getPreferenceList()) {
+ if (!seenItems.contains(pref.getItem())) {
+ result.add(pref);
+ seenItems.add(pref.getItem());
+ }
+ }
+ }
+ return result;
+ }
+
//--- ancestors ---
inh List<DecisionTreeElement> DecisionTreeElement.ancestors();
eq DecisionTreeRule.getLeft().ancestors() {
@@ -59,6 +80,7 @@ aspect DecisionTree {
return result;
}
eq DecisionTreeRoot.getRootRule().ancestors() = new ArrayList();
+ eq DummyMachineLearningModel.getCurrent().ancestors() = Collections.emptyList();
public void DecisionTreeRoot.connectItems(List<String> itemNames) {
// TODO walk through the tree using depth-first-search
diff --git a/eraser-base/src/main/jastadd/DecisionTree.relast b/eraser-base/src/main/jastadd/DecisionTree.relast
new file mode 100644
index 0000000000000000000000000000000000000000..17a1e65c1c6cd12ba2d49eeceba1eb920dae31bd
--- /dev/null
+++ b/eraser-base/src/main/jastadd/DecisionTree.relast
@@ -0,0 +1,12 @@
+// ---------------- Decision Tree ------------------------------
+DecisionTreeRoot : InternalMachineLearningModel ::= RootRule:DecisionTreeRule ;
+abstract DecisionTreeElement ::= Preference:ItemPreference*;
+abstract DecisionTreeRule : DecisionTreeElement ::= Left:DecisionTreeElement Right:DecisionTreeElement <Label:String> ;
+ItemStateCheckRule : DecisionTreeRule ::= ItemStateCheck ;
+
+abstract ItemStateCheck ::= <Comparator:ComparatorType> ;
+rel ItemStateCheck.Item -> Item ;
+
+ItemStateNumberCheck : ItemStateCheck ::= <Value:double> ;
+ItemStateStringCheck : ItemStateCheck ::= <Value:String> ;
+DecisionTreeLeaf : DecisionTreeElement ::= <ActivityIdentifier:int> <Label:String> ;
diff --git a/eraser-base/src/main/jastadd/Imports.jadd b/eraser-base/src/main/jastadd/Imports.jadd
index 1c1a2e648f78bb681a54f23efa80e5febb59f013..319b024d1698c7efaabc89feed700f98fa24fa9c 100644
--- a/eraser-base/src/main/jastadd/Imports.jadd
+++ b/eraser-base/src/main/jastadd/Imports.jadd
@@ -1,5 +1,7 @@
import java.util.*;
+import java.time.Instant;
import de.tudresden.inf.st.eraser.util.MemberPrinter;
+import de.tudresden.inf.st.eraser.util.JavaUtils;
aspect Imports {
diff --git a/eraser-base/src/main/jastadd/Item.jrag b/eraser-base/src/main/jastadd/Item.jrag
index 5a7804a3008e8f81e744c5bb557c3941e2523be6..07a45574afc6e2fd72c10530f51250dd6e685115 100644
--- a/eraser-base/src/main/jastadd/Item.jrag
+++ b/eraser-base/src/main/jastadd/Item.jrag
@@ -1,20 +1,19 @@
aspect ItemHandling {
- protected static final java.text.DateFormat Item.FORMAT = new java.text.SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS") {{
- setTimeZone(TimeZone.getTimeZone("UTC"));
- }};
protected boolean Item.isFrozen = false;
public void Item.freeze() { isFrozen = true; }
public void Item.unfreeze() { isFrozen = false; }
+ public final boolean Item.isFrozen() { return isFrozen; }
protected boolean Item.sendState = true;
public void Item.disableSendState() { sendState = false; }
public void Item.enableSendState() { sendState = true; }
+ public final boolean Item.isSendState() { return sendState; }
//--- getStateAsString ---
syn String Item.getStateAsString();
eq ColorItem.getStateAsString() = getState().toString();
- eq DateTimeItem.getStateAsString() = FORMAT.format(getState());
+ eq DateTimeItem.getStateAsString() = getState().toString();
eq ItemWithBooleanState.getStateAsString() = Boolean.toString(getState());
eq ItemWithDoubleState.getStateAsString() = Double.toString(getState());
eq ItemWithStringState.getStateAsString() = getState();
@@ -24,9 +23,9 @@ aspect ItemHandling {
// TupleHSB and String work like default
eq ColorItem.getStateAsDouble() {
logger.warn("getStateAsDouble called on item " + getLabel() + ". Using brightness.");
- return getState().brightness;
+ return getState().getBrightness();
}
- eq DateTimeItem.getStateAsDouble() = getState().getTime();
+ eq DateTimeItem.getStateAsDouble() = getState().toEpochMilli();
eq ItemWithBooleanState.getStateAsDouble() = getState() ? 1 : 0;
eq ItemWithDoubleState.getStateAsDouble() = getState();
eq ItemWithStringState.getStateAsDouble() {
@@ -51,12 +50,12 @@ aspect ItemHandling {
}
public void DateTimeItem.setStateFromString(String value) {
try{
- this.setState(FORMAT.parse(value));
- } catch (java.text.ParseException e1) {
+ this.setState(Instant.parse(value));
+ } catch (java.time.format.DateTimeParseException e1) {
// try to read input as number and use that
try {
long time = Long.parseLong(value);
- this.setState(new Date(time));
+ this.setStateFromLong(time);
// exit the method to avoid printing the error message for e1
return;
} catch (NumberFormatException e2) {
@@ -85,10 +84,10 @@ aspect ItemHandling {
public abstract void Item.setStateFromLong(long value);
public void ColorItem.setStateFromLong(long value) {
// only set brightness
- this.setState(TupleHSB.of(getState().hue, getState().saturation, Math.toIntExact(value)));
+ this.setState(getState().withDifferentBrightness(Math.toIntExact(value)));
}
public void DateTimeItem.setStateFromLong(long value) {
- this.setState(new Date(value));
+ this.setState(Instant.ofEpochMilli(value));
}
public void ItemWithBooleanState.setStateFromLong(long value) {
this.setState(value != 0);
@@ -113,7 +112,7 @@ aspect ItemHandling {
}
public void DateTimeItem.setStateFromBoolean(boolean value) {
// there is no good way here
- logger.warn("Ignoring color update using {} for {}", this, value);
+ logger.warn("Ignoring boolean update using {} for {}", value, this);
}
public void ItemWithBooleanState.setStateFromBoolean(boolean value) {
this.setState(value);
@@ -137,7 +136,7 @@ aspect ItemHandling {
setBrightness((int) value);
}
public void DateTimeItem.setStateFromDouble(double value) {
- this.setState(new Date((int) value));
+ this.setStateFromLong((long) value);
}
public void ItemWithBooleanState.setStateFromDouble(double value) {
this.setState(value != 0);
@@ -162,13 +161,13 @@ aspect ItemHandling {
}
public void DateTimeItem.setStateFromColor(TupleHSB value) {
// there is no good way here
- logger.warn("Ignoring color update using {} for {}", this, value);
+ logger.warn("Ignoring color update using {} for {}", value, this);
}
public void ItemWithBooleanState.setStateFromColor(TupleHSB value) {
- this.setState(value != null && value.brightness > 0);
+ this.setState(value != null && value.getBrightness() > 0);
}
public void ItemWithDoubleState.setStateFromColor(TupleHSB value) {
- this.setState(value.brightness);
+ this.setState(value.getBrightness());
}
public void ItemWithStringState.setStateFromColor(TupleHSB value) {
this.setState(value.toString());
@@ -180,28 +179,28 @@ aspect ItemHandling {
sendState = before;
}
- //--- setStateFromDate ---
- public abstract void Item.setStateFromDate(Date value);
- public void ColorItem.setStateFromDate(Date value) {
+ //--- setStateFromInstant ---
+ public abstract void Item.setStateFromInstant(Instant value);
+ public void ColorItem.setStateFromInstant(Instant value) {
// there is no good way here
logger.warn("Ignoring date update using {} for {}", this, value);
}
- public void DateTimeItem.setStateFromDate(Date value) {
- this.setState(new Date(value.getTime()));
+ public void DateTimeItem.setStateFromInstant(Instant value) {
+ this.setState(value);
}
- public void ItemWithBooleanState.setStateFromDate(Date value) {
+ public void ItemWithBooleanState.setStateFromInstant(Instant value) {
this.setState(value != null);
}
- public void ItemWithDoubleState.setStateFromDate(Date value) {
- this.setState(value.getTime());
+ public void ItemWithDoubleState.setStateFromInstant(Instant value) {
+ this.setState(value.toEpochMilli());
}
- public void ItemWithStringState.setStateFromDate(Date value) {
- this.setState(FORMAT.format(value));
+ public void ItemWithStringState.setStateFromInstant(Instant value) {
+ this.setState(value.toString());
}
- public void Item.setStateFromDate(Date value, boolean shouldSendState) {
+ public void Item.setStateFromInstant(Instant value, boolean shouldSendState) {
boolean before = sendState;
sendState = shouldSendState;
- setStateFromDate(value);
+ setStateFromInstant(value);
sendState = before;
}
@@ -210,58 +209,58 @@ aspect ItemHandling {
public String ItemWithStringState.getState() { return get_state(); }
public double ItemWithDoubleState.getState() { return get_state(); }
public TupleHSB ColorItem.getState() { return get_state(); }
- public Date DateTimeItem.getState() { return get_state(); }
-
- //--- copyState ---
- public abstract Object Item.copyState();
- // boolean can be copied
- public Boolean ItemWithBooleanState.copyState() { return get_state(); }
- public String ItemWithStringState.copyState() { return new String(get_state()); }
- // long can be copied
- public Double ItemWithDoubleState.copyState() { return get_state(); }
- public TupleHSB ColorItem.copyState() { return get_state().clone(); }
- public Object DateTimeItem.copyState() { return get_state().clone(); }
+ public Instant DateTimeItem.getState() { return get_state(); }
//--- setState(value) ---
public void ItemWithBooleanState.setState(boolean value) { setState(value, sendState); }
public void ItemWithStringState.setState(String value) { setState(value, sendState); }
public void ItemWithDoubleState.setState(double value) { setState(value, sendState); }
public void ColorItem.setState(TupleHSB value) { setState(value, sendState); }
- public void DateTimeItem.setState(Date value) { setState(value, sendState); }
+ public void DateTimeItem.setState(Instant value) { setState(value, sendState); }
//--- setState(value,shouldSendState) ---
public void ItemWithBooleanState.setState(boolean value, boolean shouldSendState) {
- if (isFrozen) { return; }
+ if (isFrozen || stateEquals(value)) { return; }
set_state(value);
- sendState0(shouldSendState);
+ stateUpdated(shouldSendState);
}
public void ItemWithStringState.setState(String value, boolean shouldSendState) {
- if (isFrozen) { return; }
+ if (isFrozen || stateEquals(value)) { return; }
set_state(value);
- sendState0(shouldSendState);
+ stateUpdated(shouldSendState);
}
public void ItemWithDoubleState.setState(double value, boolean shouldSendState) {
- if (isFrozen) { return; }
+ if (isFrozen || stateEquals(value)) { return; }
set_state(value);
- sendState0(shouldSendState);
+ stateUpdated(shouldSendState);
}
public void ColorItem.setState(TupleHSB value, boolean shouldSendState) {
- if (isFrozen) { return; }
+ if (isFrozen || stateEquals(value)) { return; }
set_state(value);
- sendState0(shouldSendState);
+ stateUpdated(shouldSendState);
}
- public void DateTimeItem.setState(Date value, boolean shouldSendState) {
- if (isFrozen) { return; }
+ public void DateTimeItem.setState(Instant value, boolean shouldSendState) {
+ if (isFrozen || stateEquals(value)) { return; }
set_state(value);
- sendState0(shouldSendState);
- }
-
- //--- sendState0 ---
- protected void Item.sendState0(boolean shouldSendState) {
+ stateUpdated(shouldSendState);
+ }
+
+ //--- stateUpdated ---
+ /**
+ * Called, whenever the state of an item is updated. Does various things including:
+ * <ul>
+ * <li>Send the new state via MQTT</li>
+ * <li>Send the new state to Influx DB</li>
+ * <li>Notify the attached {@link ItemObserver}, if any</li>
+ * <li>Update state of controlled items</li>
+ * </ul>
+ * @param shouldSendState whether to send the new state (currently affects MQTT and Influx)
+ */
+ protected void Item.stateUpdated(boolean shouldSendState) {
if (shouldSendState) {
try {
// sendState() defined in MQTT aspect
@@ -288,6 +287,9 @@ aspect ItemHandling {
}
public boolean ItemWithStringState.stateEquals(Object otherState) {
+ if (getState() == null) {
+ return otherState == null;
+ }
return getState().equals(otherState);
}
@@ -299,23 +301,29 @@ aspect ItemHandling {
}
public boolean ColorItem.stateEquals(Object otherState) {
+ if (getState() == null) {
+ return otherState == null;
+ }
return getState().equals(otherState);
}
public boolean DateTimeItem.stateEquals(Object otherState) {
+ if (getState() == null) {
+ return otherState == null;
+ }
return getState().equals(otherState);
}
//--- setStateToDefault ---
public abstract void Item.setStateToDefault();
public void ColorItem.setStateToDefault() { this.setState(TupleHSB.of(0, 0, 0)); }
- public void DateTimeItem.setStateToDefault() { this.setState(new Date(0)); }
+ public void DateTimeItem.setStateToDefault() { this.setState(Instant.ofEpochSecond(0)); }
public void ItemWithBooleanState.setStateToDefault() { this.setState(false); }
public void ItemWithDoubleState.setStateToDefault() { this.setState(0.0); }
public void ItemWithStringState.setStateToDefault() { this.setState(""); }
//--- as$ItemType ---
- // those attributes will raise a ClassCastException if called on the wrong item type. But else can we do?
+ // those attributes will raise a ClassCastException if called on the wrong item type. But what else can we do?
syn ColorItem Item.asColorItem() = (ColorItem) this;
syn ColorItem ColorItem.asColorItem() = this;
syn ItemWithBooleanState Item.asItemWithBooleanState() = (ItemWithBooleanState) this;
@@ -342,13 +350,11 @@ aspect ItemHandling {
controlling.setStateFromColor(this.getState());
}
protected void DateTimeItem.doUpdateFor(Item controlling) {
- controlling.setStateFromDate(this.getState());
+ controlling.setStateFromInstant(this.getState());
}
private void ColorItem.setBrightness(int value) {
- TupleHSB newState = getState().clone();
- newState.brightness = value;
- setState(newState);
+ setState(getState().withDifferentBrightness(value));
}
//--- ItemPreference.apply ---
diff --git a/eraser-base/src/main/jastadd/ItemHistoryPoints.jadd b/eraser-base/src/main/jastadd/ItemHistoryPoints.jadd
index f349743611f46e326a5514ae0ba3418653c70fc0..dcb050d0c8e09887a0809689ddfaa0a854d1edef 100644
--- a/eraser-base/src/main/jastadd/ItemHistoryPoints.jadd
+++ b/eraser-base/src/main/jastadd/ItemHistoryPoints.jadd
@@ -8,8 +8,8 @@ aspect ItemHistory{
.build();
}
protected abstract org.influxdb.dto.Point.Builder createMeasurement();
- public abstract java.time.Instant getTime();
- public abstract void setTime(java.time.Instant time);
+ public abstract Instant getTime();
+ public abstract void setTime(Instant time);
public abstract String getId();
public abstract void setId(String id);
public abstract T getState();
@@ -23,18 +23,18 @@ aspect ItemHistory{
@org.influxdb.annotation.Measurement(name = BooleanStatePoint.NAME)
public class BooleanStatePoint extends AbstractItemPoint<Boolean> {
- @org.influxdb.annotation.Column(name = "time") protected java.time.Instant time;
+ @org.influxdb.annotation.Column(name = "time") protected Instant time;
@org.influxdb.annotation.Column(name = "state") protected Boolean state;
@org.influxdb.annotation.Column(name = "id", tag = true) protected String id;
- public java.time.Instant getTime() { return time; }
- public void setTime(java.time.Instant time) { this.time = time; }
+ public Instant getTime() { return time; }
+ public void setTime(Instant time) { this.time = time; }
public String getId() { return id; }
public void setId(String id) { this.id = id; }
public void setState(Boolean state) { this.state = state; }
public Boolean getState() { return state; }
public static final String NAME = "ItemB";
- public static BooleanStatePoint of(java.time.Instant time, Boolean state, String id) {
+ public static BooleanStatePoint of(Instant time, Boolean state, String id) {
BooleanStatePoint result = new BooleanStatePoint();
result.setTime(time); result.setState(state); result.setId(id);
return result;
@@ -46,18 +46,18 @@ aspect ItemHistory{
@org.influxdb.annotation.Measurement(name = StringStatePoint.NAME)
public class StringStatePoint extends AbstractItemPoint<String> {
- @org.influxdb.annotation.Column(name = "time") protected java.time.Instant time;
+ @org.influxdb.annotation.Column(name = "time") protected Instant time;
@org.influxdb.annotation.Column(name = "state") protected String state;
@org.influxdb.annotation.Column(name = "id", tag = true) protected String id;
- public java.time.Instant getTime() { return time; }
- public void setTime(java.time.Instant time) { this.time = time; }
+ public Instant getTime() { return time; }
+ public void setTime(Instant time) { this.time = time; }
public String getId() { return id; }
public void setId(String id) { this.id = id; }
public void setState(String state) { this.state = state; }
public String getState() { return state; }
public static final String NAME = "ItemS";
- public static StringStatePoint of(java.time.Instant time, String state, String id) {
+ public static StringStatePoint of(Instant time, String state, String id) {
StringStatePoint result = new StringStatePoint();
result.setTime(time); result.setState(state); result.setId(id);
return result;
@@ -69,18 +69,18 @@ aspect ItemHistory{
@org.influxdb.annotation.Measurement(name = DoubleStatePoint.NAME)
public class DoubleStatePoint extends AbstractItemPoint<Double> {
- @org.influxdb.annotation.Column(name = "time") protected java.time.Instant time;
+ @org.influxdb.annotation.Column(name = "time") protected Instant time;
@org.influxdb.annotation.Column(name = "state") protected Double state;
@org.influxdb.annotation.Column(name = "id", tag = true) protected String id;
- public java.time.Instant getTime() { return time; }
- public void setTime(java.time.Instant time) { this.time = time; }
+ public Instant getTime() { return time; }
+ public void setTime(Instant time) { this.time = time; }
public String getId() { return id; }
public void setId(String id) { this.id = id; }
public void setState(Double state) { this.state = state; }
public Double getState() { return state; }
public static final String NAME = "ItemD";
- public static DoubleStatePoint of(java.time.Instant time, Double state, String id) {
+ public static DoubleStatePoint of(Instant time, Double state, String id) {
DoubleStatePoint result = new DoubleStatePoint();
result.setTime(time); result.setState(state); result.setId(id);
return result;
@@ -92,18 +92,18 @@ aspect ItemHistory{
@org.influxdb.annotation.Measurement(name = ColorStatePoint.NAME)
public class ColorStatePoint extends AbstractItemPoint<TupleHSB> {
- @org.influxdb.annotation.Column(name = "time") protected java.time.Instant time;
+ @org.influxdb.annotation.Column(name = "time") protected Instant time;
@org.influxdb.annotation.Column(name = "state") protected String state;
@org.influxdb.annotation.Column(name = "id", tag = true) protected String id;
- public java.time.Instant getTime() { return time; }
- public void setTime(java.time.Instant time) { this.time = time; }
+ public Instant getTime() { return time; }
+ public void setTime(Instant time) { this.time = time; }
public String getId() { return id; }
public void setId(String id) { this.id = id; }
public void setState(TupleHSB state) { this.state = state.toString(); }
public TupleHSB getState() { return TupleHSB.parse(state); }
public static final String NAME = "ItemC";
- public static ColorStatePoint of(java.time.Instant time, TupleHSB state, String id) {
+ public static ColorStatePoint of(Instant time, TupleHSB state, String id) {
ColorStatePoint result = new ColorStatePoint();
result.setTime(time); result.setState(state); result.setId(id);
return result;
@@ -114,19 +114,19 @@ aspect ItemHistory{
}
@org.influxdb.annotation.Measurement(name = DateTimeStatePoint.NAME)
- public class DateTimeStatePoint extends AbstractItemPoint<Date> {
- @org.influxdb.annotation.Column(name = "time") protected java.time.Instant time;
+ public class DateTimeStatePoint extends AbstractItemPoint<Instant> {
+ @org.influxdb.annotation.Column(name = "time") protected Instant time;
@org.influxdb.annotation.Column(name = "state") protected long state;
@org.influxdb.annotation.Column(name = "id", tag = true) protected String id;
- public java.time.Instant getTime() { return time; }
- public void setTime(java.time.Instant time) { this.time = time; }
+ public Instant getTime() { return time; }
+ public void setTime(Instant time) { this.time = time; }
public String getId() { return id; }
public void setId(String id) { this.id = id; }
- public void setState(Date state) { this.state = state.getTime(); }
- public Date getState() { return new Date(state); }
+ public void setState(Instant state) { this.state = state.toEpochMilli(); }
+ public Instant getState() { return Instant.ofEpochMilli(state); }
public static final String NAME = "ItemT";
- public static DateTimeStatePoint of(java.time.Instant time, Date state, String id) {
+ public static DateTimeStatePoint of(Instant time, Instant state, String id) {
DateTimeStatePoint result = new DateTimeStatePoint();
result.setTime(time); result.setState(state); result.setId(id);
return result;
diff --git a/eraser-base/src/main/jastadd/Location.jrag b/eraser-base/src/main/jastadd/Location.jrag
new file mode 100644
index 0000000000000000000000000000000000000000..b61b260c998e15a89712e00f3e2c2a44eb84759b
--- /dev/null
+++ b/eraser-base/src/main/jastadd/Location.jrag
@@ -0,0 +1,10 @@
+aspect Location {
+ syn Optional<Location> Item.myLocation() {
+ if (this.hasLocation()) {
+ return Optional.of(this.getLocation());
+ } else {
+ return JavaUtils.ifPresentOrElseReturn(linkedThing(),
+ thing -> thing.hasLocation() ? Optional.of(thing.getLocation()) : Optional.empty(), () -> Optional.empty());
+ }
+ }
+}
diff --git a/eraser-base/src/main/jastadd/Location.relast b/eraser-base/src/main/jastadd/Location.relast
new file mode 100644
index 0000000000000000000000000000000000000000..3cdf199776adc6eaa575b31f867a16bae891e8d5
--- /dev/null
+++ b/eraser-base/src/main/jastadd/Location.relast
@@ -0,0 +1,3 @@
+Location ::= <Label:String> SubLocation:Location ;
+rel Location.Thing* <-> Thing.Location? ;
+rel Location.Item* <-> Item.Location? ;
diff --git a/eraser-base/src/main/jastadd/Logging.jadd b/eraser-base/src/main/jastadd/Logging.jadd
index 55c48fc56bbc88fe65274435b5b2da864f94487d..dd41bc70f125081ea2ab6291ae48fa0272eea4c4 100644
--- a/eraser-base/src/main/jastadd/Logging.jadd
+++ b/eraser-base/src/main/jastadd/Logging.jadd
@@ -6,7 +6,7 @@ aspect Logging {
private org.apache.logging.log4j.Logger DummyMachineLearningModel.logger = org.apache.logging.log4j.LogManager.getLogger(DummyMachineLearningModel.class);
private org.apache.logging.log4j.Logger Rule.logger = org.apache.logging.log4j.LogManager.getLogger(Rule.class);
private org.apache.logging.log4j.Logger MqttRoot.logger = org.apache.logging.log4j.LogManager.getLogger(MqttRoot.class);
- private org.apache.logging.log4j.Logger MachineLearningModel.logger = org.apache.logging.log4j.LogManager.getLogger(MachineLearningModel.class);
+ private org.apache.logging.log4j.Logger InternalMachineLearningModel.logger = org.apache.logging.log4j.LogManager.getLogger(MachineLearningModel.class);
private org.apache.logging.log4j.Logger NeuralNetworkRoot.logger = org.apache.logging.log4j.LogManager.getLogger(NeuralNetworkRoot.class);
private org.apache.logging.log4j.Logger OutputLayer.logger = org.apache.logging.log4j.LogManager.getLogger(OutputLayer.class);
}
diff --git a/eraser-base/src/main/jastadd/MachineLearning.jrag b/eraser-base/src/main/jastadd/MachineLearning.jrag
index 53942b474a2944a9dee8bdb524780c91c970d61c..3ad31d3eac046655aa5d60ad6c13ee382a686041 100644
--- a/eraser-base/src/main/jastadd/MachineLearning.jrag
+++ b/eraser-base/src/main/jastadd/MachineLearning.jrag
@@ -1,43 +1,39 @@
aspect MachineLearning {
+ public static final MachineLearningRoot MachineLearningRoot.createDefault() {
+ MachineLearningRoot result = new MachineLearningRoot();
+ return result;
+ }
+
public interface Leaf {
String getLabel();
int getActivityIdentifier();
List<ItemPreference> computePreferences();
}
- syn Leaf MachineLearningModel.classify();
+ syn Leaf InternalMachineLearningModel.classify();
//--- currentActivityName ---
- syn String Root.currentActivityName() = getMachineLearningRoot().hasActivityRecognition() ? getMachineLearningRoot().getActivityRecognition().classify().getLabel() : "no activity";
+ syn String Root.currentActivityName() = JavaUtils.ifPresentOrElseReturn(
+ currentActivity(),
+ Activity::getLabel,
+ () -> "no activity"
+ );
//--- currentActivity ---
- syn java.util.Optional<Activity> Root.currentActivity() = resolveActivity(getMachineLearningRoot().hasActivityRecognition() ? getMachineLearningRoot().getActivityRecognition().classify().getActivityIdentifier() : -1);
-
- //--- currentPreferences ---
- syn List<ItemPreference> Root.currentPreferences() = getMachineLearningRoot().getPreferenceLearning().classify().computePreferences();
-
- //--- computePreferences ---
- syn List<ItemPreference> DecisionTreeLeaf.computePreferences() {
- // iterate over preference of this leaf, and all its parents and ancestors
- List<ItemPreference> result = new ArrayList<>();
- Set<Item> seenItems = new HashSet<>();
- List<DecisionTreeElement> ancestors = ancestors();
- for (ItemPreference pref : getPreferenceList()) {
- result.add(pref);
- seenItems.add(pref.getItem());
- }
- for (DecisionTreeElement ancestor : ancestors) {
- for (ItemPreference pref : ancestor.getPreferenceList()) {
- if (!seenItems.contains(pref.getItem())) {
- result.add(pref);
- seenItems.add(pref.getItem());
- }
- }
+ syn java.util.Optional<Activity> Root.currentActivity() {
+ return resolveActivity((int) getOpenHAB2Model().getActivityItem().getState());
+ }
+ private int Root.extractActivityIdentifier(List<ItemPreference> preferences) {
+ if (preferences.isEmpty()) {
+ return -1;
}
- return result;
+ return (int) ((ItemPreferenceDouble) preferences.get(0)).getPreferredValue();
}
+ //--- currentPreferences ---
+ syn List<ItemPreference> Root.currentPreferences() = getMachineLearningRoot().getPreferenceLearning().getDecoder().classify().getPreferences();
+
//--- canSetActivity ---
syn boolean MachineLearningModel.canSetActivity() = false;
eq DummyMachineLearningModel.canSetActivity() = true;
@@ -49,31 +45,48 @@ aspect MachineLearning {
}
//--- DummyMachineLearningModel.classify ---
- eq DummyMachineLearningModel.classify() = getCurrent();
+ eq DummyMachineLearningModel.classify() {
+ if (logger.isInfoEnabled() && getItemList().size() > 0) {
+ logger.info("Dummy classification of {}, values of connected items: {}",
+ mlKind(),
+ getItemList().stream()
+ .map(item -> item.getID() + ":" + item.getStateAsString())
+ .collect(java.util.stream.Collectors.toList()));
+ }
+ return getCurrent();
+ }
//--- DummyMachineLearningModel.createDefault() ---
public static DummyMachineLearningModel DummyMachineLearningModel.createDefault() {
- DummyMachineLearningModel dmlm = new DummyMachineLearningModel();
+ DummyMachineLearningModel dummy = new DummyMachineLearningModel();
DecisionTreeLeaf current = new DecisionTreeLeaf();
current.setActivityIdentifier(0);
current.setLabel("Dummy");
// no item preference set
- dmlm.setCurrent(current);
- return dmlm;
+ dummy.setCurrent(current);
+ return dummy;
}
//--- connectItems ---
public abstract void MachineLearningModel.connectItems(List<String> itemNames);
public void DummyMachineLearningModel.connectItems(List<String> itemNames) {
- logger.info("Ignoring items to connect");
+ logger.info("Storing items to connect");
+ for (String itemName : itemNames) {
+ JavaUtils.ifPresentOrElse(getRoot().getOpenHAB2Model().resolveItem(itemName),
+ this::addItem,
+ () -> logger.warn("Could not resolve item '{}'", itemName));
+ }
}
//--- check ---
/**
- * Checks the NeuralNetwork for all necessary children.
+ * Checks the ML model for all necessary children.
* @return true, if everything is alright. false otherwise
*/
- public boolean MachineLearningModel.check() {
+ public abstract boolean MachineLearningModel.check();
+
+ @Override
+ public boolean InternalMachineLearningModel.check() {
boolean good = true;
if (getOutputApplication() == null) {
logger.warn("{}: OutputApplication function is null!", mlKind());
@@ -97,8 +110,54 @@ aspect MachineLearning {
return good;
}
+ @Override
+ public boolean ExternalMachineLearningModel.check() {
+ throw new UnsupportedOperationException("check not available for external ML models (yet)!");
+ }
+
+ //--- mlKind ---
inh String MachineLearningModel.mlKind();
eq MachineLearningRoot.getActivityRecognition().mlKind() = "ActivityRecognition";
eq MachineLearningRoot.getPreferenceLearning().mlKind() = "PreferenceLearning";
+ //... ExternalMachineLearningModel ...
+ private MachineLearningEncoder ExternalMachineLearningModel.encoder;
+ public void ExternalMachineLearningModel.setEncoder(MachineLearningEncoder encoder) {
+ this.encoder = encoder;
+ }
+ private MachineLearningDecoder ExternalMachineLearningModel.decoder;
+ public void ExternalMachineLearningModel.setDecoder(MachineLearningDecoder decoder) {
+ this.decoder = decoder;
+ }
+// eq ExternalMachineLearningModel.classify() = null;
+ public void ExternalMachineLearningModel.connectItems(List<String> itemNames) { }
+
+ //... InternalMachineLearningModel ...
+ syn InternalMachineLearningHandler InternalMachineLearningModel.handler() {
+ return new InternalMachineLearningHandler().setModel(this);
+ }
+ cache InternalMachineLearningModel.handler();
+
+ //--- getEncoder ---
+ public abstract MachineLearningEncoder MachineLearningModel.getEncoder();
+ @Override
+ public MachineLearningEncoder InternalMachineLearningModel.getEncoder() {
+ return handler();
+ }
+ @Override
+ public MachineLearningEncoder ExternalMachineLearningModel.getEncoder() {
+ return this.encoder;
+ }
+
+ //--- getDecoder ---
+ public abstract MachineLearningDecoder MachineLearningModel.getDecoder();
+ @Override
+ public MachineLearningDecoder InternalMachineLearningModel.getDecoder() {
+ return handler();
+ }
+ @Override
+ public MachineLearningDecoder ExternalMachineLearningModel.getDecoder() {
+ return this.decoder;
+ }
+
}
diff --git a/eraser-base/src/main/jastadd/MachineLearning.relast b/eraser-base/src/main/jastadd/MachineLearning.relast
new file mode 100644
index 0000000000000000000000000000000000000000..5bfeaddda253ba37b4d730dfd3638e2c1b1b70d5
--- /dev/null
+++ b/eraser-base/src/main/jastadd/MachineLearning.relast
@@ -0,0 +1,26 @@
+// ---------------- Machine Learning Model ------------------------------
+MachineLearningRoot ::= [ActivityRecognition:MachineLearningModel] [PreferenceLearning:MachineLearningModel] Activity* ChangeEvent* ;
+
+Activity ::= <Identifier:int> <Label:String> ;
+
+abstract ChangeEvent ::= <Identifier:int> <Timestamp:long> ChangedItem* ;
+
+ChangedItem ::= <NewStateAsString:String> ;
+rel ChangedItem.Item -> Item ;
+
+RecognitionEvent : ChangeEvent ;
+rel RecognitionEvent.Activity -> Activity ;
+
+ManualChangeEvent : ChangeEvent ;
+
+abstract MachineLearningModel ::= ;
+ExternalMachineLearningModel : MachineLearningModel ;
+abstract InternalMachineLearningModel : MachineLearningModel ::= <OutputApplication:DoubleDoubleFunction> ;
+rel InternalMachineLearningModel.RelevantItem* <-> Item.RelevantInMachineLearningModel* ;
+rel InternalMachineLearningModel.TargetItem* <-> Item.TargetInMachineLearningModel* ;
+
+abstract ItemPreference ::= ;
+rel ItemPreference.Item -> Item ;
+
+ItemPreferenceColor : ItemPreference ::= <PreferredHSB:TupleHSB> ;
+ItemPreferenceDouble : ItemPreference ::= <PreferredValue:double> ;
diff --git a/eraser-base/src/main/jastadd/ModelStatistics.jrag b/eraser-base/src/main/jastadd/ModelStatistics.jrag
index 293fcd920a69bbdf3393add6fd62c451d0abe87a..443635f1e2f3ceb71785e5977d43ba27f55c2b6c 100644
--- a/eraser-base/src/main/jastadd/ModelStatistics.jrag
+++ b/eraser-base/src/main/jastadd/ModelStatistics.jrag
@@ -1,7 +1,7 @@
aspect ModelStatistics {
//--- numChannels ---
- syn int Root.numChannels() {
+ syn int OpenHAB2Model.numChannels() {
int sum = 0;
for (Thing thing : getThingList()) {
sum += thing.getNumChannel();
@@ -10,7 +10,7 @@ aspect ModelStatistics {
}
//--- description ---
- syn String Root.description() = "["
+ syn String OpenHAB2Model.description() = "["
+ this.getNumThingType() + " thing type(s), "
+ this.getNumChannelType() + " channel type(s), "
+ this.numChannels() + " channel(s), "
diff --git a/eraser-base/src/main/jastadd/Navigation.jrag b/eraser-base/src/main/jastadd/Navigation.jrag
index bb57ce614c40c68bf1afc4bc53680d3c9a3a8884..69592c1bf0b980b6287cb28d10b7b131bd4383ef 100644
--- a/eraser-base/src/main/jastadd/Navigation.jrag
+++ b/eraser-base/src/main/jastadd/Navigation.jrag
@@ -1,36 +1,36 @@
aspect Navigation {
- syn Comparator<ModelElement> Root.modelElementComparator() {
+ syn Comparator<ModelElement> OpenHAB2Model.modelElementComparator() {
return (e1, e2) -> (e1.getID().compareTo(e2.getID()));
}
//--- items ---
- syn java.util.List<Item> Root.items() {
+ syn java.util.List<Item> OpenHAB2Model.items() {
java.util.List<Item> result = new java.util.ArrayList<>();
addItems(result, getGroupList());
return result;
}
- private void Root.addItems(java.util.List<Item> result, JastAddList<Group> groups) {
+ private void OpenHAB2Model.addItems(java.util.List<Item> result, JastAddList<Group> groups) {
groups.forEach(group -> group.getItemList().forEach(item -> result.add(item)));
}
//--- parameters ---
- syn java.util.Set<Parameter> Root.parameters() {
+ syn java.util.Set<Parameter> OpenHAB2Model.parameters() {
java.util.Set<Parameter> result = new java.util.TreeSet<>(modelElementComparator());
getThingTypeList().forEach(tt -> tt.getParameterList().forEach(parameter -> result.add(parameter)));
return result;
}
//--- channels ---
- syn java.util.Set<Channel> Root.channels() {
+ syn java.util.Set<Channel> OpenHAB2Model.channels() {
java.util.Set<Channel> result = new java.util.TreeSet<>(modelElementComparator());
getThingList().forEach(thing -> thing.getChannelList().forEach(channel -> result.add(channel)));
return result;
}
//--- resolveThingType ---
- syn java.util.Optional<ThingType> Root.resolveThingType(String thingTypeId) {
+ syn java.util.Optional<ThingType> OpenHAB2Model.resolveThingType(String thingTypeId) {
for (ThingType thingType : this.getThingTypeList()) {
if (thingType.getID().equals(thingTypeId)) {
return java.util.Optional.of(thingType);
@@ -40,7 +40,7 @@ aspect Navigation {
}
//--- resolveChannel ---
- syn java.util.Optional<Channel> Root.resolveChannel(String channelId) {
+ syn java.util.Optional<Channel> OpenHAB2Model.resolveChannel(String channelId) {
for (Thing thing : this.getThingList()) {
for (Channel channel : thing.getChannelList()) {
if (channel.getID().equals(channelId)) {
@@ -52,7 +52,7 @@ aspect Navigation {
}
//--- resolveChannelType ---
- syn java.util.Optional<ChannelType> Root.resolveChannelType(String channelTypeId) {
+ syn java.util.Optional<ChannelType> OpenHAB2Model.resolveChannelType(String channelTypeId) {
for (ChannelType channelType : this.getChannelTypeList()) {
if (channelType.getID().equals(channelTypeId)) {
return java.util.Optional.of(channelType);
@@ -62,7 +62,10 @@ aspect Navigation {
}
//--- resolveItem ---
- syn java.util.Optional<Item> Root.resolveItem(String itemId) {
+ syn java.util.Optional<Item> OpenHAB2Model.resolveItem(String itemId) {
+ if ("activity".equals(itemId)) {
+ return Optional.of(getActivityItem());
+ }
for (Item item : items()) {
if (item.getID().equals(itemId)) {
return java.util.Optional.of(item);
@@ -72,7 +75,7 @@ aspect Navigation {
}
//--- resolveGroup ---
- syn java.util.Optional<Group> Root.resolveGroup(String groupId) {
+ syn java.util.Optional<Group> OpenHAB2Model.resolveGroup(String groupId) {
for (Group group : this.getGroupList()) {
if (group.getID().equals(groupId)) {
return java.util.Optional.of(group);
@@ -87,7 +90,7 @@ aspect Navigation {
}
//--- resolveItemCategory ---
- syn java.util.Optional<ItemCategory> Root.resolveItemCategory(String categoryName) {
+ syn java.util.Optional<ItemCategory> OpenHAB2Model.resolveItemCategory(String categoryName) {
for (ItemCategory category : getItemCategoryList()) {
if (category.getName().equals(categoryName)) {
return java.util.Optional.of(category);
@@ -116,10 +119,6 @@ aspect Navigation {
return java.util.Optional.empty();
}
- //--- containingChannel ---
- inh Channel Link.containingChannel();
- eq Channel.getLink().containingChannel() = this;
-
//--- containingThing ---
inh Thing Channel.containingThing();
eq Thing.getChannel().containingThing() = this;
@@ -128,17 +127,23 @@ aspect Navigation {
inh NeuralNetworkRoot OutputLayer.containingNeuralNetwork();
eq NeuralNetworkRoot.getOutputLayer().containingNeuralNetwork() = this;
+ //--- linkedThing ---
+ syn Optional<Thing> Item.linkedThing() {
+ if (!this.hasChannel()) {
+ return Optional.empty();
+ }
+ Channel channel = this.getChannel();
+ Thing thing = channel.containingThing();
+ return Optional.of(thing);
+ }
+
//--- getRoot ---
inh Root ASTNode.getRoot();
- eq Root.getChannelCategory().getRoot() = this;
+ eq Root.getOpenHAB2Model().getRoot() = this;
eq Root.getMqttRoot().getRoot() = this;
eq Root.getInfluxRoot().getRoot() = this;
eq Root.getMachineLearningRoot().getRoot() = this;
- eq Root.getThing().getRoot() = this;
- eq Root.getGroup().getRoot() = this;
- eq Root.getThingType().getRoot() = this;
- eq Root.getChannelType().getRoot() = this;
eq Root.getRule().getRoot() = this;
- eq Root.getItemCategory().getRoot() = this;
eq Root.getUser().getRoot() = this;
+ eq Root.getLocation().getRoot() = this;
}
diff --git a/eraser-base/src/main/jastadd/NeuralNetwork.jrag b/eraser-base/src/main/jastadd/NeuralNetwork.jrag
index a5d04cee57e017d037d3defb882dbf0560f1c0c1..e673b69a1ea95c386320630fae1c8152cfe9cf78 100644
--- a/eraser-base/src/main/jastadd/NeuralNetwork.jrag
+++ b/eraser-base/src/main/jastadd/NeuralNetwork.jrag
@@ -57,7 +57,7 @@ aspect NeuralNetwork {
//--- value ---
syn double Neuron.value();
- syn double HiddenNeuron.value() {
+ eq HiddenNeuron.value() {
double[] inputs = new double[getInputs().size()];
for (int i=0; i<inputs.length; ++i) {
NeuronConnection connection = getInputList().get(i);
@@ -67,9 +67,11 @@ aspect NeuralNetwork {
double result = getActivationFormula().apply(inputs);
// logger.debug("{}: {} -> {}", this, java.util.Arrays.toString(inputs), result);
return result;
- }
+ }
+
+ eq BiasNeuron.value() = 1;
- syn double InputNeuron.value() {
+ eq InputNeuron.value() {
return getItem().getStateAsDouble();
}
@@ -98,7 +100,7 @@ aspect NeuralNetwork {
}
String itemName = itemNames.get(i);
InputNeuron neuron = getInputNeuron(i);
- de.tudresden.inf.st.eraser.util.JavaUtils.ifPresentOrElse(getRoot().resolveItem(itemName),
+ JavaUtils.ifPresentOrElse(getRoot().getOpenHAB2Model().resolveItem(itemName),
neuron::setItem,
() -> logger.warn("Could not resolve item '{}'", itemName));
}
@@ -165,6 +167,12 @@ aspect NeuralNetwork {
return good;
}
+ @Override
+ public boolean BiasNeuron.check() {
+ setActivationFormula(inputs -> 1.0);
+ return super.check();
+ }
+
//--- mlKind ---
inh String OutputLayer.mlKind();
inh String Neuron.mlKind();
diff --git a/eraser-base/src/main/jastadd/NeuralNetwork.relast b/eraser-base/src/main/jastadd/NeuralNetwork.relast
new file mode 100644
index 0000000000000000000000000000000000000000..1214eb199e7ae39e9bae4754eabe6ee0fcd14ae3
--- /dev/null
+++ b/eraser-base/src/main/jastadd/NeuralNetwork.relast
@@ -0,0 +1,20 @@
+// ---------------- Neural Network ------------------------------
+NeuralNetworkRoot : InternalMachineLearningModel ::= InputNeuron* HiddenNeuron* OutputLayer ;
+
+OutputLayer ::= OutputNeuron* <Combinator:DoubleArrayDoubleFunction> ;
+rel OutputLayer.AffectedItem -> Item ;
+
+abstract Neuron ::= Output:NeuronConnection* ;
+
+NeuronConnection ::= <Weight:double> ;
+rel NeuronConnection.Neuron <-> Neuron.Input* ;
+
+InputNeuron : Neuron ;
+rel InputNeuron.Item -> Item ;
+
+HiddenNeuron : Neuron ::= <ActivationFormula:DoubleArrayDoubleFunction> ;
+BiasNeuron : HiddenNeuron ;
+OutputNeuron : HiddenNeuron ::= <Label:String> ;
+
+DummyMachineLearningModel : InternalMachineLearningModel ::= Current:DecisionTreeLeaf ;
+rel DummyMachineLearningModel.Item* -> Item ;
diff --git a/eraser-base/src/main/jastadd/Printing.jrag b/eraser-base/src/main/jastadd/Printing.jrag
index 106332708ec4239f0cf044ba562417c4e0aa06a2..53206bc16b2a09708a33386393ade1f3310e1666 100644
--- a/eraser-base/src/main/jastadd/Printing.jrag
+++ b/eraser-base/src/main/jastadd/Printing.jrag
@@ -3,8 +3,17 @@ aspect Printing {
String ASTNode.safeID(ModelElement elem) { return elem == null ? "NULL" : elem.getID(); }
-//Root ::= Thing* Item* Group* ThingType* ChannelType* MqttRoot ;
syn String Root.prettyPrint() {
+ StringBuilder sb = new StringBuilder();
+ sb.append(getOpenHAB2Model().prettyPrint());
+ sb.append(getMqttRoot().prettyPrint());
+ sb.append(getInfluxRoot().prettyPrint());
+ sb.append(getMachineLearningRoot().prettyPrint());
+ return sb.toString();
+ }
+
+//--- OpenHAB2Model.prettyPrint() ---
+ syn String OpenHAB2Model.prettyPrint() {
StringBuilder sb = new StringBuilder();
for (Thing t : getThingList()) {
sb.append(t.prettyPrint());
@@ -27,8 +36,6 @@ aspect Printing {
for (Channel c : channels()) {
sb.append(c.prettyPrint());
}
- sb.append(getMqttRoot().prettyPrint());
- sb.append(getInfluxRoot().prettyPrint());
return sb.toString();
}
@@ -49,9 +56,10 @@ aspect Printing {
.addNonDefault("label", getLabel())
.addRequired("state", getStateAsString())
.addOptional("category", hasCategory(), () -> getCategory().getName())
- .addOptional("topic", getTopic() != null, () -> getTopic().allParts())
+ .addOptional("topic", hasTopic(), () -> getTopic().getTopicString())
.addIds("controls", getControllingList())
- .addNodes("metaData", getNumMetaData(), getMetaDataList(), md -> "\"" + md.getKey() + "\":\"" + md.getValue() + "\"",
+ .addNodes("metaData", getNumMetaData(), getMetaDataList(),
+ md -> "\"" + md.getKey() + "\":\"" + md.getValue() + "\"",
MemberPrinter.ListBracketType.CURLY)
.build();
}
@@ -68,8 +76,24 @@ aspect Printing {
eq RollerShutterItem.prettyPrintType() = "RollerShutter Item" ;
eq StringItem.prettyPrintType() = "String Item" ;
eq SwitchItem.prettyPrintType() = "Switch Item" ;
+ eq ActivityItem.prettyPrintType() = "Activity Item" ;
eq DefaultItem.prettyPrintType() = "Item" ;
+ // special ActivityItem printing. Always omit state.
+ syn String ActivityItem.prettyPrint() {
+ return new MemberPrinter(prettyPrintType())
+ .addRequired("id", getID())
+ .addNonDefault("label", getLabel())
+ .addOptional("category", hasCategory(), () -> getCategory().getName())
+ .addOptional("topic", hasTopic(), () -> getTopic().getTopicString())
+ .addIds("controls", getControllingList())
+ .addNodes("metaData", getNumMetaData(), getMetaDataList(),
+ md -> "\"" + md.getKey() + "\":\"" + md.getValue() + "\"",
+ MemberPrinter.ListBracketType.CURLY)
+ .build();
+ }
+
+
//Group: id="" groups=["GROUP_ID", "GROUP_ID"] items=["ITEM_ID", "ITEM_ID"] aggregation=AGG;
// AGG either '"agg-name"', or '"agg-name" ("param1", "param2")'
syn String Group.prettyPrint() {
@@ -142,7 +166,7 @@ aspect Printing {
return new MemberPrinter("Channel")
.addRequired("id", getID())
.addRequired("type", getType(), ChannelType::getID)
- .addIds("links", getNumLink(), getLinkList(), Link::getItem)
+ .addIds("links", getLinkedItems())
.build();
}
@@ -174,8 +198,13 @@ aspect Printing {
.build();
}
- private boolean InfluxRoot.nonDefault(String actual, String expected) {
- return actual != null && !actual.equals(expected);
+// Activities: { index: "name" }
+ syn String MachineLearningRoot.prettyPrint() {
+ return new MemberPrinter("ML")
+ .addNodes("activities", getNumActivity(), getActivityList(),
+ activity -> activity.getIdentifier() + ":\"" + activity.getLabel() + "\"",
+ MemberPrinter.ListBracketType.CURLY)
+ .build();
}
}
diff --git a/eraser-base/src/main/jastadd/Rules.jrag b/eraser-base/src/main/jastadd/Rules.jrag
index 0a3d508c146d9c325bd067cf4d0a915c276ceb39..69ae87d306a004978c0638c59ebba11335c2a27d 100644
--- a/eraser-base/src/main/jastadd/Rules.jrag
+++ b/eraser-base/src/main/jastadd/Rules.jrag
@@ -1,18 +1,10 @@
aspect Rules {
- Object ItemObserver.last_known_state = null;
-
- // idea: abuse dependency tracking to trigger rule only iff item state has changed
- syn boolean ItemObserver.apply() {
- if (!observedItem().stateEquals(last_known_state)) {
- // state has changed
- last_known_state = observedItem().copyState();
- for (Rule rule : getTriggeredRuleList()) {
- rule.trigger(observedItem());
- }
- return true;
+ public void ItemObserver.apply() {
+ // state has changed, so trigger rules
+ for (Rule rule : getTriggeredRuleList()) {
+ rule.trigger(observedItem());
}
- return false;
}
public void Rule.trigger(Item triggeringItem) {
@@ -46,7 +38,6 @@ aspect Rules {
} else {
itemObserver = new ItemObserver();
item.setItemObserver(itemObserver);
- itemObserver.last_known_state = item.copyState();
}
// 2) Link event and itemObserver
itemObserver.addTriggeredRule(this);
diff --git a/eraser-base/src/main/jastadd/Rules.relast b/eraser-base/src/main/jastadd/Rules.relast
new file mode 100644
index 0000000000000000000000000000000000000000..69854a70199e2d08dc3baa9fc1f49f2ac5ef2999
--- /dev/null
+++ b/eraser-base/src/main/jastadd/Rules.relast
@@ -0,0 +1,25 @@
+// --- New ECA rules ---
+Rule ::= Condition* Action* ;
+abstract Condition ;
+ItemStateCheckCondition : Condition ::= ItemStateCheck ;
+abstract Action ;
+LambdaAction : Action ::= <Lambda:Action2EditConsumer> ;
+
+TriggerRuleAction : Action ;
+rel TriggerRuleAction.Rule -> Rule ;
+
+abstract SetStateAction : Action ;
+rel SetStateAction.AffectedItem -> Item ;
+
+SetStateFromConstantStringAction : SetStateAction ::= <NewState:String> ;
+SetStateFromLambdaAction : SetStateAction ::= <NewStateProvider:NewStateProvider> ;
+SetStateFromTriggeringItemAction : SetStateAction ::= ;
+
+SetStateFromItemsAction : SetStateAction ::= <Combinator:ItemsToStringFunction> ;
+rel SetStateFromItemsAction.SourceItem* -> Item ;
+
+AddDoubleToStateAction : SetStateAction ::= <Increment:double> ;
+MultiplyDoubleToStateAction : SetStateAction ::= <Multiplier:double> ;
+
+ItemObserver ::= ;
+rel ItemObserver.TriggeredRule* <-> Rule.Observer* ;
diff --git a/eraser-base/src/main/jastadd/Util.jrag b/eraser-base/src/main/jastadd/Util.jrag
index b7e252afd51fda93273eba63e745483f7c78df59..282a44413c80ee2b5c5d71dca179ce4cf45c1fde 100644
--- a/eraser-base/src/main/jastadd/Util.jrag
+++ b/eraser-base/src/main/jastadd/Util.jrag
@@ -5,19 +5,31 @@ aspect Util {
// return new ExternalHost(hostName, 1883);
// }
public void MqttRoot.setHostByName(String hostName) {
- setHost(new ExternalHost(hostName, 1883));
+ setHost(ExternalHost.of(hostName, DEFAULT_PORT));
}
public void InfluxRoot.setHostByName(String hostName) {
- setHost(new ExternalHost(hostName, 8086));
+ setHost(ExternalHost.of(hostName, DEFAULT_PORT));
+ }
+
+ public static ExternalHost ExternalHost.of(String hostName, int defaultPort) {
+ String host = hostName;
+ int port = defaultPort;
+ if (hostName.contains(":")) {
+ String[] parts = hostName.split(":");
+ host = parts[0];
+ port = Integer.parseInt(parts[1]);
+ }
+ return new ExternalHost(host, port);
}
syn String ExternalHost.urlAsString() = String.format("http://%s:%s", getHostName(), getPort());
public static Root Root.createEmptyRoot() {
Root model = new Root();
+ model.setOpenHAB2Model(new OpenHAB2Model());
model.setMqttRoot(new MqttRoot());
- model.setInfluxRoot(new InfluxRoot());
+ model.setInfluxRoot(InfluxRoot.createDefault());
model.setMachineLearningRoot(new MachineLearningRoot());
return model;
}
diff --git a/eraser-base/src/main/jastadd/eraser.flex b/eraser-base/src/main/jastadd/eraser.flex
index 57627fc2a3fec198c70cc9f89b6a30c44745b374..58d16b9c919ba44d71366752650beca252df557b 100644
--- a/eraser-base/src/main/jastadd/eraser.flex
+++ b/eraser-base/src/main/jastadd/eraser.flex
@@ -33,7 +33,7 @@ WhiteSpace = [ ] | \t | \f | \n | \r | \r\n
//Identifier = [:jletter:][:jletterdigit:]*
Text = \" ([^\"]*) \"
-//Integer = [:digit:]+ // | "+" [:digit:]+ | "-" [:digit:]+
+Integer = [:digit:]+ // | "+" [:digit:]+ | "-" [:digit:]+
//Real = [:digit:]+ "." [:digit:]* | "." [:digit:]+
Comment = "//" [^\n\r]+
@@ -55,7 +55,9 @@ Comment = "//" [^\n\r]+
"Channel" { return sym(Terminals.CHANNEL); }
"Mqtt" { return sym(Terminals.MQTT); }
"Influx" { return sym(Terminals.INFLUX); }
+"ML" { return sym(Terminals.ML); }
// special items (group already has a token definition)
+"Activity" { return sym(Terminals.ACTIVITY); }
"Color" { return sym(Terminals.COLOR); }
"Contact" { return sym(Terminals.CONTACT); }
"DateTime" { return sym(Terminals.DATE_TIME); }
@@ -68,6 +70,7 @@ Comment = "//" [^\n\r]+
"String" { return sym(Terminals.STRING); }
"Switch" { return sym(Terminals.SWITCH); }
// within specification
+"activities" { return sym(Terminals.ACTIVITIES); }
"aggregation" { return sym(Terminals.AGGREGATION); }
"category" { return sym(Terminals.CATEGORY); }
"channels" { return sym(Terminals.CHANNELS); }
@@ -110,5 +113,7 @@ Comment = "//" [^\n\r]+
//{Identifier} { return sym(Terminals.NAME); }
{Text} { return symText(Terminals.TEXT); }
//{Real} { return sym(Terminals.REAL); }
-//{Integer} { return sym(Terminals.INTEGER); }
+{Integer} { return sym(Terminals.INTEGER); }
<<EOF>> { return sym(Terminals.EOF); }
+/* error fallback */
+[^] { throw new Error("Illegal character '"+ yytext() +"' at line " + (yyline+1) + " column " + (yycolumn+1)); }
diff --git a/eraser-base/src/main/jastadd/eraser.parser b/eraser-base/src/main/jastadd/eraser.parser
index 2994b762e69f83a61986c0e843cc46710a47289d..acd54d7c68b1aca2eb8d811d5da685e37347d0a4 100644
--- a/eraser-base/src/main/jastadd/eraser.parser
+++ b/eraser-base/src/main/jastadd/eraser.parser
@@ -25,24 +25,26 @@ import java.util.HashMap;
%goal goal;
Root goal =
- thing.t goal.r {: insertZero(r.getThingList(), t); return r; :}
- | item.i goal.r {: return r; :}
- | group.g goal.r {: insertZero(r.getGroupList(), g); return r; :}
- | thing_type.tt goal.r {: insertZero(r.getThingTypeList(), tt); return r; :}
- | parameter goal.r {: return r; :}
- | channel_type.ct goal.r {: insertZero(r.getChannelTypeList(), ct); return r; :}
- | channel.c goal.r {: return r; :}
- | mqtt_root.mr goal.r {: r.setMqttRoot(mr); return r; :}
- | influx_root.ir goal.r {: r.setInfluxRoot(ir); return r; :}
- | thing.t {: return eph.createRoot(t); :}
- | item.i {: return eph.createRoot(); :}
- | group.g {: return eph.createRoot(g); :}
- | thing_type.tt {: return eph.createRoot(tt); :}
- | parameter {: return eph.createRoot(); :}
- | channel_type.ct {: return eph.createRoot(ct); :}
- | channel.c {: return eph.createRoot(); :}
- | mqtt_root.mr {: return eph.createRoot(mr); :}
- | influx_root.ir {: return eph.createRoot(ir); :}
+ thing.t goal.r {: insertZero(r.getOpenHAB2Model().getThingList(), t); return r; :}
+ | item.i goal.r {: return r; :}
+ | group.g goal.r {: insertZero(r.getOpenHAB2Model().getGroupList(), g); return r; :}
+ | thing_type.tt goal.r {: insertZero(r.getOpenHAB2Model().getThingTypeList(), tt); return r; :}
+ | parameter goal.r {: return r; :}
+ | channel_type.ct goal.r {: insertZero(r.getOpenHAB2Model().getChannelTypeList(), ct); return r; :}
+ | channel.c goal.r {: return r; :}
+ | mqtt_root.mr goal.r {: r.setMqttRoot(mr); return r; :}
+ | influx_root.ir goal.r {: r.setInfluxRoot(ir); return r; :}
+ | machine_learning_root.ml goal.r {: r.setMachineLearningRoot(ml); return r; :}
+ | thing.t {: return eph.createRoot(t); :}
+ | item.i {: return eph.createRoot(); :}
+ | group.g {: return eph.createRoot(g); :}
+ | thing_type.tt {: return eph.createRoot(tt); :}
+ | parameter {: return eph.createRoot(); :}
+ | channel_type.ct {: return eph.createRoot(ct); :}
+ | channel.c {: return eph.createRoot(); :}
+ | mqtt_root.mr {: return eph.createRoot(mr); :}
+ | influx_root.ir {: return eph.createRoot(ir); :}
+ | machine_learning_root.ml {: return eph.createRoot(ml); :}
;
Thing thing =
@@ -73,10 +75,11 @@ Item item =
| ROLLER_SHUTTER ITEM COLON item_body.ib SEMICOLON {: return eph.retype(new RollerShutterItem(), ib); :}
| STRING ITEM COLON item_body.ib SEMICOLON {: return eph.retype(new StringItem(), ib); :}
| SWITCH ITEM COLON item_body.ib SEMICOLON {: return eph.retype(new SwitchItem(), ib); :}
+ | ACTIVITY ITEM COLON item_body.ib SEMICOLON {: return eph.retype(new ActivityItem(), ib); :}
| ITEM COLON item_body.ib SEMICOLON {: return eph.retype(new DefaultItem(), ib); :}
;
-// ITEM_TYPE Item: id="" label="" state="" category="" topic="" controls=["ITEM_ID"] metaData=["key":"value"] ;
+// ITEM_TYPE Item: id="" label="" state="" category="" topic="" controls=["ITEM_ID"] metaData={"key":"value"} ;
Item item_body =
ID EQUALS TEXT.n item_body.i {: return eph.setID(i, n); :}
| LABEL EQUALS TEXT.n item_body.i {: i.setLabel(n); return i; :}
@@ -194,8 +197,20 @@ InfluxRoot influx_root_body =
| {: return InfluxRoot.createDefault(); :}
;
+// Machine Learning
+MachineLearningRoot machine_learning_root =
+ ML COLON machine_learning_root_body.b SEMICOLON {: return b; :}
+ ;
+
+// ML: activities={index:"name"} ;
+MachineLearningRoot machine_learning_root_body =
+ ACTIVITIES EQUALS integer_map.map machine_learning_root_body.b {: return eph.setActivities(b, map); :}
+ | {: return MachineLearningRoot.createDefault(); :}
+ ;
+
StringList string_list =
LB_SQUARE string_list_body.slb RB_SQUARE {: return slb; :}
+ | LB_SQUARE RB_SQUARE {: return new StringList(); :}
;
StringList string_list_body =
@@ -206,11 +221,11 @@ StringList string_list_body =
result.add(n);
return result;
:}
- | {: return new StringList(); :}
;
StringList round_string_list =
LB_ROUND round_string_list_body.slb RB_ROUND {: return slb; :}
+ | LB_ROUND RB_ROUND {: return new StringList(); :}
;
StringList round_string_list_body =
@@ -221,20 +236,34 @@ StringList round_string_list_body =
result.add(n);
return result;
:}
- | {: return new StringList(); :}
;
-StringMap string_map =
+StringKeyMap string_map =
LB_CURLY string_map_body.smb RB_CURLY {: return smb; :}
+ | LB_CURLY RB_CURLY {: return new StringKeyMap(); :}
;
-StringMap string_map_body =
+StringKeyMap string_map_body =
TEXT.key COLON TEXT.value COMMA string_map_body.smb {: smb.put(key, value); return smb; :}
| TEXT.key COLON TEXT.value
{:
- StringMap result = new StringMap();
+ StringKeyMap result = new StringKeyMap();
result.put(key, value);
return result;
:}
- | {: return new StringMap(); :}
+ ;
+
+IntegerKeyMap integer_map =
+ LB_CURLY integer_map_body.imb RB_CURLY {: return imb; :}
+ | LB_CURLY RB_CURLY {: return new IntegerKeyMap(); :}
+ ;
+
+IntegerKeyMap integer_map_body =
+ INTEGER.key COLON TEXT.value COMMA integer_map_body.imb {: imb.put(Integer.parseInt(key), value); return imb; :}
+ | INTEGER.key COLON TEXT.value
+ {:
+ IntegerKeyMap result = new IntegerKeyMap();
+ result.put(Integer.parseInt(key), value);
+ return result;
+ :}
;
diff --git a/eraser-base/src/main/jastadd/main.relast b/eraser-base/src/main/jastadd/main.relast
index 425ede01d98a532f6ff8c43920c9e983735c6dc4..066ffbbc6f4eeb18930c645d246cb57112a2c8a9 100644
--- a/eraser-base/src/main/jastadd/main.relast
+++ b/eraser-base/src/main/jastadd/main.relast
@@ -1,135 +1,12 @@
// ---------------- Main ------------------------------
-Root ::= Thing* Group* ThingType* ChannelType* ChannelCategory* ItemCategory* User* MqttRoot InfluxRoot
- MachineLearningRoot Rule* ;
-
-// ---------------- openHAB ------------------------------
-abstract ModelElement ::= <ID:String> ;
-abstract LabelledModelElement : ModelElement ::= <Label:String> ;
-abstract DescribableModelElement : LabelledModelElement ::= <Description:String> ;
-
-ThingType : DescribableModelElement ::= Parameter* ;
-
-Thing : LabelledModelElement ::= Channel* ;
-
-ChannelType : DescribableModelElement ::= <ItemType:ItemType> <ReadOnly:boolean> ;
-
-abstract ChannelCategory ;
-DefaultChannelCategory : ChannelCategory ::= <Value:DefaultChannelCategoryValue> ;
-SimpleChannelCategory : ChannelCategory ::= <Value:String> ;
-
-Channel : ModelElement ::= Link* ;
-
-Link ::= <Item:Item> ;
-
-Parameter : DescribableModelElement ::= <Type:ParameterValueType> [DefaultValue:ParameterDefaultValue] <Context:String> <Required:boolean> ;
-ParameterDefaultValue ::= <Value:String> ;
-
-abstract Item : LabelledModelElement ::= <_fetched_data:boolean> MetaData:ItemMetaData* [ItemObserver] ;
-ItemMetaData ::= <Key:String> <Value:String> ;
-abstract ItemWithBooleanState : Item ::= <_state:boolean> ;
-abstract ItemWithStringState : Item ::= <_state:String> ;
-abstract ItemWithDoubleState : Item ::= <_state:double> ;
-ColorItem : Item ::= <_state:TupleHSB> ;
-DateTimeItem : Item ::= <_state:Date> ;
-ContactItem : ItemWithBooleanState ;
-DimmerItem : ItemWithDoubleState ;
-ImageItem : ItemWithStringState ;
-LocationItem : ItemWithStringState ;
-NumberItem : ItemWithDoubleState ;
-PlayerItem : ItemWithStringState ;
-RollerShutterItem : ItemWithBooleanState ;
-StringItem : ItemWithStringState ;
-SwitchItem : ItemWithBooleanState ;
-DefaultItem : ItemWithStringState ;
-
-ItemCategory ::= <Name:String> ;
-
-Group : LabelledModelElement ::= Group* Item* [AggregationFunction:GroupAggregationFunction] ;
-abstract GroupAggregationFunction ;
-SimpleGroupAggregationFunction : GroupAggregationFunction ::= <FunctionName:SimpleGroupAggregationFunctionName> ;
-ParameterizedGroupAggregationFunction : GroupAggregationFunction ::= <FunctionName:ParameterizedGroupAggregationFunctionName>
- <Param1:String> <Param2:String> ;
+Root ::= OpenHAB2Model User* MqttRoot InfluxRoot MachineLearningRoot Rule* Location* ;
// ---------------- Users ------------------------------
User : LabelledModelElement ;
+rel Root.CurrentUser? -> User ;
// ---------------- Util ------------------------------
ExternalHost ::= <HostName:String> <Port:int> ;
-// ---------------- MQTT ------------------------------
-MqttRoot ::= Topic:MqttTopic* <IncomingPrefix:String> <OutgoingPrefix:String> [Host:ExternalHost] ;
-MqttTopic ::= <Part:String> SubTopic:MqttTopic* ;
-
// ---------------- InfluxDB ------------------------------
InfluxRoot ::= <User:String> <Password:String> <DbName:String> [Host:ExternalHost] ;
-
-// ---------------- Machine Learning Model ------------------------------
-MachineLearningRoot ::= [ActivityRecognition:MachineLearningModel] [PreferenceLearning:MachineLearningModel] Activity* ChangeEvent* ;
-Activity ::= <Identifier:int> <Label:String> ;
-abstract ChangeEvent ::= <Identifier:int> <Timestamp:long> ChangedItem* ;
-ChangedItem ::= <NewStateAsString:String> ;
-RecognitionEvent : ChangeEvent ;
-ManualChangeEvent : ChangeEvent ;
-abstract MachineLearningModel ::= <OutputApplication:DoubleDoubleFunction> ;
-abstract ItemPreference ::= ;
-ItemPreferenceColor : ItemPreference ::= <PreferredHSB:TupleHSB> ;
-ItemPreferenceDouble : ItemPreference ::= <PreferredValue:double> ;
-
-// ---------------- Decision Tree ------------------------------
-DecisionTreeRoot : MachineLearningModel ::= RootRule:DecisionTreeRule ;
-abstract DecisionTreeElement ::= Preference:ItemPreference*;
-abstract DecisionTreeRule : DecisionTreeElement ::= Left:DecisionTreeElement Right:DecisionTreeElement <Label:String> ;
-ItemStateCheckRule : DecisionTreeRule ::= ItemStateCheck ;
-abstract ItemStateCheck ::= <Comparator:ComparatorType> ;
-ItemStateNumberCheck : ItemStateCheck ::= <Value:double> ;
-ItemStateStringCheck : ItemStateCheck ::= <Value:String> ;
-DecisionTreeLeaf : DecisionTreeElement ::= <ActivityIdentifier:int> <Label:String> ;
-
-// ---------------- Neural Network ------------------------------
-NeuralNetworkRoot : MachineLearningModel ::= InputNeuron* HiddenNeuron* OutputLayer ;
-OutputLayer ::= OutputNeuron* <Combinator:DoubleArrayDoubleFunction> ;
-abstract Neuron ::= Output:NeuronConnection* ;
-NeuronConnection ::= <Weight:double> ;
-InputNeuron : Neuron ;
-HiddenNeuron : Neuron ::= <ActivationFormula:DoubleArrayDoubleFunction> ;
-OutputNeuron : HiddenNeuron ::= <Label:String> ;
-
-DummyMachineLearningModel : MachineLearningModel ::= <Current:DecisionTreeLeaf> ;
-
-// --- New ECA rules ---
-Rule ::= Condition* Action* ;
-abstract Condition ;
-ItemStateCheckCondition : Condition ::= ItemStateCheck ;
-abstract Action ;
-LambdaAction : Action ::= <Lambda:Action2EditConsumer> ;
-TriggerRuleAction : Action ;
-abstract SetStateAction : Action ;
-SetStateFromConstantStringAction : SetStateAction ::= <NewState:String> ;
-SetStateFromLambdaAction : SetStateAction ::= <NewStateProvider:NewStateProvider> ;
-SetStateFromTriggeringItemAction : SetStateAction ::= ;
-SetStateFromItemsAction : SetStateAction ::= <Combinator:ItemsToStringFunction> ;
-AddDoubleToStateAction : SetStateAction ::= <Increment:double> ;
-MultiplyDoubleToStateAction : SetStateAction ::= <Multiplier:double> ;
-ItemObserver ::= ;
-
-// ---------------- Relations ------------------------------
-rel ThingType.ChannelType* -> ChannelType ;
-rel Thing.Type -> ThingType ;
-rel Channel.Type -> ChannelType ;
-rel ChannelType.ChannelCategory -> ChannelCategory ;
-rel Item.Topic <-> MqttTopic.Item ;
-rel Item.Category? -> ItemCategory ;
-rel ItemStateCheck.Item -> Item ;
-rel NeuronConnection.Neuron <-> Neuron.Input* ;
-rel InputNeuron.Item -> Item ;
-rel OutputLayer.AffectedItem -> Item ;
-rel ItemPreference.Item -> Item ;
-rel Item.Controlling* <-> Item.ControlledBy* ;
-rel Root.CurrentUser? -> User ;
-rel ChangedItem.Item -> Item ;
-rel RecognitionEvent.Activity -> Activity ;
-
-rel TriggerRuleAction.Rule -> Rule ;
-rel SetStateAction.AffectedItem -> Item ;
-rel SetStateFromItemsAction.SourceItem* -> Item ;
-rel ItemObserver.TriggeredRule* <-> Rule.Observer* ;
diff --git a/eraser-base/src/main/jastadd/mqtt.jrag b/eraser-base/src/main/jastadd/mqtt.jrag
index ba20820fedd6cc368313145f443daf7961c3983e..65b36d151111c4a7a58fa7ae14f57a37accb1033 100644
--- a/eraser-base/src/main/jastadd/mqtt.jrag
+++ b/eraser-base/src/main/jastadd/mqtt.jrag
@@ -3,39 +3,25 @@ aspect MQTT {
// --- default values ---
private static final int MqttRoot.DEFAULT_PORT = 1883;
- java.util.Set<String> MqttRoot.ignoredTopics = new java.util.HashSet<>();
-
//--- resolveTopic ---
syn java.util.Optional<MqttTopic> MqttRoot.resolveTopic(String topic) {
ensureCorrectPrefixes();
if (!topic.startsWith(getIncomingPrefix())) {
- logger.debug("Topic '{}' does not start with incoming prefix '{}'", topic, getIncomingPrefix());
+ logger.warn("Topic '{}' does not start with incoming prefix '{}'", topic, getIncomingPrefix());
return java.util.Optional.empty();
}
- topic = topic.substring(getIncomingPrefix().length());
- String[] tokens = topic.split("/");
- int tokenIndex = 0;
- java.util.Optional<MqttTopic> result = check(tokens, 0, getTopics());
- if (!result.isPresent() && !ignoredTopics.contains(topic)) {
- logger.error("Could not resolve {}, ignoring it.", topic);
- ignoredTopics.add(topic);
- }
- return result;
+ String suffix = topic.substring(getIncomingPrefix().length());
+ return resolveTopicSuffix(suffix);
}
- java.util.Optional<MqttTopic> MqttRoot.check(String[] tokens, int tokenIndex, JastAddList<MqttTopic> topics) {
- for (MqttTopic current : topics) {
- if (tokens[tokenIndex].equals(current.getPart())) {
- // topic part matches, move on or return if tokens are empty
- ++tokenIndex;
- if (tokens.length == tokenIndex) {
- return java.util.Optional.of(current);
- } else {
- return check(tokens, tokenIndex, current.getSubTopics());
- }
+ //--- resolveTopicSuffix ---
+ syn java.util.Optional<MqttTopic> MqttRoot.resolveTopicSuffix(String suffix) {
+ for (MqttTopic current : getTopics()) {
+ if (current.getTopicString().equals(suffix)) {
+ return Optional.of(current);
}
}
- return java.util.Optional.empty();
+ return Optional.empty();
}
public void MqttRoot.ensureCorrectPrefixes() {
@@ -48,19 +34,10 @@ aspect MQTT {
}
//--- getIncomingTopic ---
- syn String MqttTopic.getIncomingTopic() = getMqttRoot().getIncomingPrefix() + allParts();
+ syn String MqttTopic.getIncomingTopic() = getMqttRoot().getIncomingPrefix() + getTopicString();
//--- getOutgoingTopic ---
- syn String MqttTopic.getOutgoingTopic() = getMqttRoot().getOutgoingPrefix() + allParts();
-
- //--- allParts ---
- inh String MqttTopic.allParts();
- eq MqttTopic.getSubTopic(int i).allParts() {
- return allParts() + "/" + getSubTopic(i).getPart();
- }
- eq MqttRoot.getTopic(int i).allParts() {
- return getTopic(i).getPart();
- }
+ syn String MqttTopic.getOutgoingTopic() = getMqttRoot().getOutgoingPrefix() + getTopicString();
//--- getMqttSender (should be cached) ---
cache MqttRoot.getMqttSender();
@@ -78,7 +55,6 @@ aspect MQTT {
inh MqttRoot MqttTopic.getMqttRoot();
eq MqttRoot.getTopic().getMqttRoot() = this;
- eq MqttTopic.getSubTopic().getMqttRoot() = getMqttRoot();
/**
* Sends the current state via MQTT.
diff --git a/eraser-base/src/main/jastadd/mqtt.relast b/eraser-base/src/main/jastadd/mqtt.relast
new file mode 100644
index 0000000000000000000000000000000000000000..cf477ff72e303415e47f42c939afe26cdfc4ed54
--- /dev/null
+++ b/eraser-base/src/main/jastadd/mqtt.relast
@@ -0,0 +1,4 @@
+// ---------------- MQTT ------------------------------
+MqttRoot ::= Topic:MqttTopic* <IncomingPrefix:String> <OutgoingPrefix:String> [Host:ExternalHost] ;
+MqttTopic ::= <TopicString:String> ;
+rel Item.Topic? <-> MqttTopic.Item* ;
diff --git a/eraser-base/src/main/jastadd/openhab.jrag b/eraser-base/src/main/jastadd/openhab.jrag
new file mode 100644
index 0000000000000000000000000000000000000000..6d30e4b3e0fb91225c9e8ea08bfdf3ab1afb1357
--- /dev/null
+++ b/eraser-base/src/main/jastadd/openhab.jrag
@@ -0,0 +1,5 @@
+aspect OpenHAB2 {
+ syn ActivityItem OpenHAB2Model.getActivityItem() {
+ return new ActivityItem();
+ }
+}
diff --git a/eraser-base/src/main/jastadd/openhab.relast b/eraser-base/src/main/jastadd/openhab.relast
new file mode 100644
index 0000000000000000000000000000000000000000..7d7d9afa27f9f9998f6c5bd4b9822f0dfa774e8d
--- /dev/null
+++ b/eraser-base/src/main/jastadd/openhab.relast
@@ -0,0 +1,57 @@
+// ---------------- openHAB ------------------------------
+OpenHAB2Model ::= Thing* Group* ThingType* ChannelType* ChannelCategory* ItemCategory* /ActivityItem:Item/ ;
+
+abstract ModelElement ::= <ID:String> ;
+abstract LabelledModelElement : ModelElement ::= <Label:String> ;
+abstract DescribableModelElement : LabelledModelElement ::= <Description:String> ;
+
+ThingType : DescribableModelElement ::= Parameter* ;
+rel ThingType.ChannelType* -> ChannelType ;
+
+Thing : LabelledModelElement ::= Channel* ;
+rel Thing.Type -> ThingType ;
+
+ChannelType : DescribableModelElement ::= <ItemType:ItemType> <ReadOnly:boolean> ;
+rel ChannelType.ChannelCategory -> ChannelCategory ;
+
+abstract ChannelCategory ;
+DefaultChannelCategory : ChannelCategory ::= <Value:DefaultChannelCategoryValue> ;
+SimpleChannelCategory : ChannelCategory ::= <Value:String> ;
+
+Channel : ModelElement ::= ;
+rel Channel.Type -> ChannelType ;
+rel Channel.LinkedItem* <-> Item.Channel? ;
+
+Parameter : DescribableModelElement ::= <Type:ParameterValueType> [DefaultValue:ParameterDefaultValue] <Context:String> <Required:boolean> ;
+ParameterDefaultValue ::= <Value:String> ;
+
+abstract Item : LabelledModelElement ::= <_fetched_data:boolean> MetaData:ItemMetaData* [ItemObserver] ;
+rel Item.Category? -> ItemCategory ;
+rel Item.Controlling* <-> Item.ControlledBy* ;
+
+abstract ItemWithBooleanState : Item ::= <_state:boolean> ;
+abstract ItemWithStringState : Item ::= <_state:String> ;
+abstract ItemWithDoubleState : Item ::= <_state:double> ;
+ColorItem : Item ::= <_state:TupleHSB> ;
+DateTimeItem : Item ::= <_state:Instant> ;
+ContactItem : ItemWithBooleanState ;
+DimmerItem : ItemWithDoubleState ;
+ImageItem : ItemWithStringState ;
+LocationItem : ItemWithStringState ;
+NumberItem : ItemWithDoubleState ;
+PlayerItem : ItemWithStringState ;
+RollerShutterItem : ItemWithBooleanState ;
+StringItem : ItemWithStringState ;
+SwitchItem : ItemWithBooleanState ;
+DefaultItem : ItemWithStringState ;
+ActivityItem : ItemWithDoubleState ;
+
+ItemMetaData ::= <Key:String> <Value:String> ;
+
+ItemCategory ::= <Name:String> ;
+
+Group : LabelledModelElement ::= Group* Item* [AggregationFunction:GroupAggregationFunction] ;
+abstract GroupAggregationFunction ;
+SimpleGroupAggregationFunction : GroupAggregationFunction ::= <FunctionName:SimpleGroupAggregationFunctionName> ;
+ParameterizedGroupAggregationFunction : GroupAggregationFunction ::= <FunctionName:ParameterizedGroupAggregationFunctionName>
+ <Param1:String> <Param2:String> ;
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/Main.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/Main.java
index 9b98f688fce2bba0dadffeb6584f03ff1f28628d..9b9aaba5b25e860177545415c5ca1c088a3e7165 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/Main.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/Main.java
@@ -6,8 +6,6 @@ import de.tudresden.inf.st.eraser.jastadd.model.Root;
import de.tudresden.inf.st.eraser.openhab2.OpenHab2Importer;
import de.tudresden.inf.st.eraser.openhab2.mqtt.MQTTUpdater;
import de.tudresden.inf.st.eraser.util.ParserUtils;
-import org.apache.commons.math3.linear.MatrixUtils;
-import org.apache.commons.math3.linear.RealMatrix;
import org.apache.logging.log4j.LogManager;
import java.io.*;
@@ -16,7 +14,7 @@ import java.io.*;
* Main entry point for testing eraser.
* @author rschoene - Initial contribution
*/
-@SuppressWarnings({"unused", "WeakerAccess", "RedundantThrows"})
+@SuppressWarnings({"unused", "RedundantThrows"})
public class Main {
public static void main(String[] args) throws IOException, Parser.Exception {
@@ -25,35 +23,6 @@ public class Main {
// Root model = importFromOpenHab();
// testPrinterWith(model);
// testUpdaterWith(model);
- testXY_to_RGB();
- }
-
- private static void testXY_to_RGB() {
- /*
- XYZ to RGB [M]-1
- 2.0413690 -0.5649464 -0.3446944
- -0.9692660 1.8760108 0.0415560
- 0.0134474 -0.1183897 1.0154096
- */
- double[][] matrixData = { { 2.0413690, -0.5649464, -0.3446944},
- {-0.9692660, 1.8760108, 0.0415560},
- { 0.0134474, -0.1183897, 1.0154096}};
- RealMatrix mInverted = MatrixUtils.createRealMatrix(matrixData);
- BufferedReader in = new BufferedReader(new InputStreamReader(System.in));
-
- while (true) {
- try {
- double x = readFromSystemIn(in, "x:");
- double y = readFromSystemIn(in, "y:");
- double z = 1;
- RealMatrix xyz = MatrixUtils.createColumnRealMatrix(new double[] {x,y,z});
- RealMatrix result = mInverted.multiply(xyz);
- System.out.println(result);
- } catch (IOException | NumberFormatException e) {
- e.printStackTrace();
- break;
- }
- }
}
private static double readFromSystemIn(BufferedReader in, String prompt) throws IOException {
@@ -70,7 +39,7 @@ public class Main {
private static void testPrinterWith(Root model) {
model.flushTreeCache();
- System.out.println("Got model: " + model.description());
+ System.out.println("Got model: " + model.getOpenHAB2Model().description());
System.out.println("PrettyPrinted:");
System.out.println(model.prettyPrint());
}
@@ -79,7 +48,7 @@ public class Main {
Root model;
// model = importFromOpenHab();
model = importFromFile();
- System.out.println("Got model: " + model.description());
+ System.out.println("Got model: " + model.getOpenHAB2Model().description());
// JsonSerializer.write(model, "openhab2-data.json");
testUpdaterWith(model);
}
@@ -106,7 +75,7 @@ public class Main {
public static Root importFromOpenHab() {
OpenHab2Importer importer = new OpenHab2Importer();
- return importer.importFrom("192.168.1.250", 8080);
+ return importer.importFrom("192.168.1.250", 8080).getRoot();
}
public static Root importFromFile() {
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/deserializer/ASTNodeDeserializer.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/deserializer/ASTNodeDeserializer.java
index 95f1d470c014ce4a123b5e01e33e7b049ba8ceff..d349331de9e8e43b7513001c659f94e61cc94ae8 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/deserializer/ASTNodeDeserializer.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/deserializer/ASTNodeDeserializer.java
@@ -48,12 +48,17 @@ public class ASTNodeDeserializer extends StdDeserializer<ASTNode> {
r.put(c.getName(), ((node, model) -> f.apply(model, termValue(node, terminalName))));
}
+ private void addResolverForOpenHAB2Model(Map<String, ResolveAstNodeForOpenHAB2Model> r, Class<?> c, BiFunction<OpenHAB2Model, String, Optional<? extends ASTNode>> f, String terminalName) {
+ r.put(c.getName(), ((node, model) -> f.apply(model, termValue(node, terminalName))));
+ }
+
private Map<String, ResolveAstNode> resolvers = new HashMap<>();
+ private Map<String, ResolveAstNodeForOpenHAB2Model> resolversForOpenHAB2Model = new HashMap<>();
private void initResolvers() {
- addResolver(resolvers, ThingType.class, Root::resolveThingType, "ID");
- addResolver(resolvers, ChannelType.class, Root::resolveChannelType, "ID");
- addResolver(resolvers, Item.class, Root::resolveItem, "ID");
+ addResolverForOpenHAB2Model(resolversForOpenHAB2Model, ThingType.class, OpenHAB2Model::resolveThingType, "ID");
+ addResolverForOpenHAB2Model(resolversForOpenHAB2Model, ChannelType.class, OpenHAB2Model::resolveChannelType, "ID");
+ addResolverForOpenHAB2Model(resolversForOpenHAB2Model, Item.class, OpenHAB2Model::resolveItem, "ID");
addResolver(resolvers, MqttTopic.class, Root::resolveMqttTopic, "IncomingTopic");
}
@@ -363,11 +368,15 @@ public class ASTNodeDeserializer extends StdDeserializer<ASTNode> {
}
}
-
interface ResolveAstNode {
Optional<? extends ASTNode> resolve(JsonNode node, Root model) throws IOException;
}
+
+interface ResolveAstNodeForOpenHAB2Model {
+ Optional<? extends ASTNode> resolve(JsonNode node, OpenHAB2Model model) throws IOException;
+}
+
class ResolveLater {
JsonNode node;
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/InternalMachineLearningHandler.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/InternalMachineLearningHandler.java
new file mode 100644
index 0000000000000000000000000000000000000000..2c59f46ca48fc18afa7aa096571a19ef9bef4b44
--- /dev/null
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/InternalMachineLearningHandler.java
@@ -0,0 +1,54 @@
+package de.tudresden.inf.st.eraser.jastadd.model;
+
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+
+import java.time.Instant;
+import java.util.List;
+
+/**
+ * Adapter for internally held machine learning models.
+ *
+ * @author rschoene - Initial contribution
+ */
+public class InternalMachineLearningHandler implements MachineLearningEncoder, MachineLearningDecoder {
+
+ private static final Logger logger = LogManager.getLogger(InternalMachineLearningHandler.class);
+ private InternalMachineLearningModel model;
+
+ public InternalMachineLearningHandler setModel(InternalMachineLearningModel model) {
+ this.model = model;
+ return this;
+ }
+
+ @Override
+ public void newData(Root model, List<Item> changedItems) {
+ logger.debug("Ignored new data of {}", changedItems);
+ }
+
+ @Override
+ public List<Item> getTargets() {
+ return model.getTargetItems();
+ }
+
+ @Override
+ public List<Item> getRelevantItems() {
+ return model.getRelevantItems();
+ }
+
+ @Override
+ public void triggerTraining() {
+ logger.debug("Ignored training trigger.");
+ }
+
+ @Override
+ public MachineLearningResult classify() {
+ List<ItemPreference> preferences = model.classify().computePreferences();
+ return new InternalMachineLearningResult(preferences);
+ }
+
+ @Override
+ public Instant lastModelUpdate() {
+ return null;
+ }
+}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/InternalMachineLearningResult.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/InternalMachineLearningResult.java
new file mode 100644
index 0000000000000000000000000000000000000000..087020b383fee89ea839b2056e22072af799a9f3
--- /dev/null
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/InternalMachineLearningResult.java
@@ -0,0 +1,21 @@
+package de.tudresden.inf.st.eraser.jastadd.model;
+
+import java.util.List;
+
+/**
+ * Result of a classification returned by an internally held machine learning model.
+ *
+ * @author rschoene - Initial contribution
+ */
+public class InternalMachineLearningResult implements MachineLearningResult {
+ private final List<ItemPreference> preferences;
+
+ InternalMachineLearningResult(List<ItemPreference> preferences) {
+ this.preferences = preferences;
+ }
+
+ @Override
+ public List<ItemPreference> getPreferences() {
+ return this.preferences;
+ }
+}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningDecoder.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningDecoder.java
new file mode 100644
index 0000000000000000000000000000000000000000..a6e01fb945226bcf91e4bc94663c24b561f7cd6f
--- /dev/null
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningDecoder.java
@@ -0,0 +1,28 @@
+package de.tudresden.inf.st.eraser.jastadd.model;
+
+import java.time.Instant;
+
+/**
+ * This interface represents the connection from a machine learning model back to the knowledge base.
+ * It decodes the output of the machine learning model and outputs the result of the classification.
+ *
+ * @author rschoene - Initial contribution
+ */
+@SuppressWarnings("unused")
+public interface MachineLearningDecoder {
+
+ /**
+ * Execute the machine learning model and returns the classification result.
+ * @return the result of the classification
+ */
+ MachineLearningResult classify();
+
+ // less important
+
+ /**
+ * Returns the time when the model was last updated, i.e., when the last training was completed.
+ * @return the time when the model was last updated, or <code>null</code> if the model was not trained yet
+ */
+ Instant lastModelUpdate();
+
+}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningEncoder.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningEncoder.java
new file mode 100644
index 0000000000000000000000000000000000000000..8cf4d78fd92a2c18bd4914ab5b805db63995be85
--- /dev/null
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningEncoder.java
@@ -0,0 +1,48 @@
+package de.tudresden.inf.st.eraser.jastadd.model;
+
+import de.tudresden.inf.st.eraser.jastadd.model.Item;
+import de.tudresden.inf.st.eraser.jastadd.model.Root;
+
+import java.util.List;
+
+/**
+ * This interface represents the connection from knowledge base to one machine learning model.
+ * It takes information from the knowledge base, and encodes them to a representation that is readable both for
+ * the used technique and the purpose of the machine learning model.
+ *
+ * @author rschoene - Initial contribution
+ */
+@SuppressWarnings("unused")
+public interface MachineLearningEncoder {
+
+ /**
+ * Update when new data is available.
+ * @param model The underlying model
+ * @param changedItems A list of items whose state has changed
+ */
+ void newData(Root model, List<Item> changedItems);
+
+ // to be discussed, in which form this is specified
+
+ /**
+ * Get the items that this model is supposed to change.
+ * @return the list of targeted items
+ */
+ List<Item> getTargets();
+
+ // to be discussed, in which form this is specified
+
+ /**
+ * Get the items which are relevant for the decision making of this model.
+ * @return the list of items relevant for decision making
+ */
+ List<Item> getRelevantItems();
+
+ // to be discussed, if this is necessary
+
+ /**
+ * Explicit hint for this model to start/trigger training. The model might ignore this hint.
+ */
+ void triggerTraining();
+
+}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningResult.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningResult.java
new file mode 100644
index 0000000000000000000000000000000000000000..eebd16d3679c1531cb02d1ba1abd0c1610303668
--- /dev/null
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/MachineLearningResult.java
@@ -0,0 +1,25 @@
+package de.tudresden.inf.st.eraser.jastadd.model;
+
+import de.tudresden.inf.st.eraser.jastadd.model.ItemPreference;
+
+import java.util.List;
+
+/**
+ * Representation of a classification result using a MachineLearningModel.
+ *
+ * @author rschoene - Initial contribution
+ */
+@SuppressWarnings("unused")
+public interface MachineLearningResult {
+
+ // Object rawClass();
+
+ // double rawConfidence();
+
+ // can be used for both activity and preferences
+ /**
+ * Get the result as a list of item preferences, i.e., new states to be set for those items.
+ * @return the classification result as item preferences
+ */
+ List<ItemPreference> getPreferences();
+}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/TupleHSB.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/TupleHSB.java
index a3520402e367ba88ab6f5f218915f3b0c5447f84..8e9ee2ad31f8d16ff415bcb7fe82bd34eb87f02a 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/TupleHSB.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/jastadd/model/TupleHSB.java
@@ -8,9 +8,9 @@ import java.util.Objects;
* @author rschoene - Initial contribution
*/
public class TupleHSB implements Cloneable {
- public int hue;
- public int saturation;
- public int brightness;
+ private int hue;
+ private int saturation;
+ private int brightness;
public static TupleHSB of(int hue, int saturation, int brightness) {
TupleHSB result = new TupleHSB();
result.hue = hue;
@@ -19,6 +19,30 @@ public class TupleHSB implements Cloneable {
return result;
}
+ public int getHue() {
+ return hue;
+ }
+
+ public int getSaturation() {
+ return saturation;
+ }
+
+ public int getBrightness() {
+ return brightness;
+ }
+
+ public TupleHSB withDifferentHue(int hue) {
+ return TupleHSB.of(hue, this.saturation, this.brightness);
+ }
+
+ public TupleHSB withDifferentSaturation(int saturation) {
+ return TupleHSB.of(this.hue, saturation, this.brightness);
+ }
+
+ public TupleHSB withDifferentBrightness(int brightness) {
+ return TupleHSB.of(this.hue, this.saturation, brightness);
+ }
+
public String toString() {
return String.format("%s,%s,%s", hue, saturation, brightness);
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/OpenHab2Importer.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/OpenHab2Importer.java
index 627167f83a7773e2923dc31508904405042bc25b..4e1742c7f48b31e040cc70866e8ecd5070622172 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/OpenHab2Importer.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/OpenHab2Importer.java
@@ -42,7 +42,7 @@ public class OpenHab2Importer {
nonDefaultChannelCategories = new HashSet<>();
}
- public Root importFrom(String host, int port) {
+ public OpenHAB2Model importFrom(String host, int port) {
/*
Plan:
- requesting: thing-types, channel-types, things, items, links
@@ -58,7 +58,8 @@ public class OpenHab2Importer {
mapper.registerModule(module);
try {
- Root model = Root.createEmptyRoot();
+ Root root = Root.createEmptyRoot();
+ OpenHAB2Model model = root.getOpenHAB2Model();
ThingTypeData[] thingTypeList = mapper.readValue(makeURL(thingTypesUrl, hostAndPort), ThingTypeData[].class);
logger.info("Read a total of {} thing type(s).", thingTypeList.length);
update(model, thingTypeList);
@@ -84,17 +85,6 @@ public class OpenHab2Importer {
ThingTypeData data = mapper.readValue(makeURL(thingTypeDetailUrl, hostAndPort, thingType.getID()), ThingTypeData.class);
update(thingType, data);
}
-
- // create empty MQTT root
- MqttRoot mqttRoot = new MqttRoot();
- mqttRoot.setHostByName(host);
- model.setMqttRoot(mqttRoot);
-
- // create empty Influx root
- InfluxRoot influxRoot = InfluxRoot.createDefault();
- influxRoot.setHostByName(host);
- model.setInfluxRoot(influxRoot);
-
return model;
} catch (IOException e) {
logger.catching(e);
@@ -110,7 +100,7 @@ public class OpenHab2Importer {
return URI.create(String.format(formatUrlString, hostAndPort, id)).toURL();
}
- private void update(Root model, ThingTypeData[] thingTypeList) {
+ private void update(OpenHAB2Model model, ThingTypeData[] thingTypeList) {
for (ThingTypeData thingTypeData : thingTypeList) {
ThingType thingType = new ThingType();
thingType.setID(thingTypeData.UID);
@@ -120,7 +110,7 @@ public class OpenHab2Importer {
}
}
- private void update(Root model, ChannelTypeData[] channelTypeList) {
+ private void update(OpenHAB2Model model, ChannelTypeData[] channelTypeList) {
for (ChannelTypeData channelTypeData : channelTypeList) {
ChannelType channelType = new ChannelType();
channelType.setID(channelTypeData.UID);
@@ -173,7 +163,7 @@ public class OpenHab2Importer {
}
}
- private void update(Root model, ThingData[] thingList) {
+ private void update(OpenHAB2Model model, ThingData[] thingList) {
for (ThingData thingData : thingList) {
Thing thing = new Thing();
thing.setID(thingData.UID);
@@ -192,7 +182,7 @@ public class OpenHab2Importer {
}
}
- private void update(Root model, AbstractItemData[] itemList) {
+ private void update(OpenHAB2Model model, AbstractItemData[] itemList) {
List<Tuple<Group, GroupItemData>> groupsWithMembers = new ArrayList<>();
List<Tuple<Group, GroupItemData>> groupsInGroups = new ArrayList<>();
List<Tuple<Item, AbstractItemData>> itemsInGroups = new ArrayList<>();
@@ -309,12 +299,10 @@ public class OpenHab2Importer {
}
}
- private void update(Root model, LinkData[] linkList) {
+ private void update(OpenHAB2Model model, LinkData[] linkList) {
for (LinkData linkData : linkList) {
- Link link = new Link();
ifPresent(model.resolveChannel(linkData.channelUID), "Channel", linkData,
- channel -> channel.addLink(link));
- ifPresent(model.resolveItem(linkData.itemName), "Item", linkData, link::setItem);
+ channel -> ifPresent(model.resolveItem(linkData.itemName), "Item", linkData, channel::addLinkedItem));
}
}
@@ -353,7 +341,7 @@ public class OpenHab2Importer {
}
}
- public Root importFrom(URL baseUrl) {
+ public OpenHAB2Model importFrom(URL baseUrl) {
return importFrom(baseUrl.getHost(),
baseUrl.getPort() == -1 ? baseUrl.getDefaultPort() : baseUrl.getPort());
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/mqtt/MQTTUpdater.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/mqtt/MQTTUpdater.java
index 2bf5880087ccc171ea4e2799c0db4fa1bda11e9d..647114843839aef335b5337cb62e744870d3a0e3 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/mqtt/MQTTUpdater.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/openhab2/mqtt/MQTTUpdater.java
@@ -1,23 +1,15 @@
package de.tudresden.inf.st.eraser.openhab2.mqtt;
+import de.tudresden.inf.st.eraser.jastadd.model.ExternalHost;
import de.tudresden.inf.st.eraser.jastadd.model.Item;
import de.tudresden.inf.st.eraser.jastadd.model.Root;
import de.tudresden.inf.st.eraser.util.MqttReceiver;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
-import org.fusesource.hawtbuf.Buffer;
-import org.fusesource.hawtbuf.UTF8Buffer;
-import org.fusesource.mqtt.client.*;
+import org.fusesource.mqtt.client.QoS;
import java.io.IOException;
-import java.net.URI;
-import java.util.Arrays;
-import java.util.Objects;
import java.util.concurrent.TimeUnit;
-import java.util.concurrent.atomic.AtomicReference;
-import java.util.concurrent.locks.Condition;
-import java.util.concurrent.locks.Lock;
-import java.util.concurrent.locks.ReentrantLock;
/**
* Update an imported model by subscribing to MQTT topics.
@@ -36,28 +28,33 @@ public class MQTTUpdater implements AutoCloseable {
this.delegatee = new MqttReceiver();
}
- public MQTTUpdater(Root model) throws IllegalArgumentException {
+ public MQTTUpdater(Root root) throws IllegalArgumentException {
this();
- this.setModel(model);
+ this.setRoot(root);
}
/**
- * Sets the model to update
- * @param model the model to update
+ * Sets the model root to update
+ * @param root the model root to update
*/
- public void setModel(Root model) {
- delegatee.setHost(model.getMqttRoot().getHost().getHostName());
+ public void setRoot(Root root) {
+ ExternalHost host = root.getMqttRoot().getHost();
+ delegatee.setHost(host.getHostName(), host.getPort());
delegatee.setOnMessage((topicString, message) ->
- model.getMqttRoot().resolveTopic(topicString).ifPresent(topic ->
- itemUpdate(topic.getItem(), message)));
- delegatee.setTopicsForSubscription(model.getMqttRoot().getIncomingPrefix() + "#");
+ root.getMqttRoot().resolveTopic(topicString).ifPresent(topic ->
+ topic.getItems().forEach(
+ item -> itemUpdate(item, message))));
+ delegatee.setTopicsForSubscription(root.getMqttRoot().getIncomingPrefix() + "#");
delegatee.setQoSForSubscription(QoS.AT_LEAST_ONCE);
}
private void itemUpdate(Item item, String state) {
- this.logger.debug("Update state of {} [{}] from '{}' to '{}'.",
- item.getLabel(), item.getID(), item.getStateAsString(), state);
- item.setStateFromString(state, false);
+ String oldState = item.getStateAsString();
+ if (oldState == null || !oldState.equals(state)) {
+ this.logger.debug("Update state of {} [{}] from '{}' to '{}'.",
+ item.getLabel(), item.getID(), oldState, state);
+ item.setStateFromString(state, false);
+ }
}
/**
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/parser/EraserParserHelper.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/parser/EraserParserHelper.java
index 0d1d7334b5ef642cc94a02a47aeb475b44ed13b1..400a09affa32b8990ccc82396d795b2dd6ce8cb4 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/parser/EraserParserHelper.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/parser/EraserParserHelper.java
@@ -1,6 +1,7 @@
package de.tudresden.inf.st.eraser.parser;
import de.tudresden.inf.st.eraser.jastadd.model.*;
+import de.tudresden.inf.st.eraser.util.JavaUtils;
import de.tudresden.inf.st.eraser.util.ParserUtils;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
@@ -72,7 +73,7 @@ public class EraserParserHelper {
this.root.getMqttRoot().ensureCorrectPrefixes();
resolveList(channelMap, missingChannelListMap, Thing::addChannel);
- resolveList(itemMap, missingItemLinkListMap, (channel, item) -> channel.addLink(new Link(item)));
+ resolveList(itemMap, missingItemLinkListMap, Channel::addLinkedItem);
resolveList(groupMap, missingSubGroupListMap, Group::addGroup);
resolveList(itemMap, missingItemListMap, this::addItemToGroup);
resolveList(channelTypeMap, missingChannelTypeListMap, ThingType::addChannelType);
@@ -114,13 +115,13 @@ public class EraserParserHelper {
sortedDanglingItems.add(item);
}
}
- ParserUtils.createUnknownGroup(this.root, sortedDanglingItems);
+ ParserUtils.createUnknownGroup(this.root.getOpenHAB2Model(), sortedDanglingItems);
}
}
private void createChannelCategories() {
channelCategoryMap.values().stream().sorted(Comparator.comparing(this::ident)).forEach(
- cc -> root.addChannelCategory(cc));
+ cc -> root.getOpenHAB2Model().addChannelCategory(cc));
channelCategoryMap.clear();
}
@@ -128,7 +129,7 @@ public class EraserParserHelper {
Map<String, ItemCategory> newCategories = new HashMap<>();
missingItemCategoryMap.forEach((item, category) ->
item.setCategory(newCategories.computeIfAbsent(category, ItemCategory::new)));
- newCategories.values().forEach(root::addItemCategory);
+ newCategories.values().forEach(node -> root.getOpenHAB2Model().addItemCategory(node));
}
private void checkUnusedElements() {
@@ -139,7 +140,7 @@ public class EraserParserHelper {
if (elem instanceof ModelElement) {
return ((ModelElement) elem).getID();
} else if (elem instanceof MqttTopic) {
- return safeAllParts((MqttTopic) elem);
+ return ((MqttTopic) elem).getTopicString();
} else if (elem instanceof DefaultChannelCategory) {
return ((DefaultChannelCategory) elem).getValue().name();
} else if (elem instanceof SimpleChannelCategory) {
@@ -148,85 +149,73 @@ public class EraserParserHelper {
return elem.toString();
}
- private String safeAllParts(MqttTopic elem) {
- StringBuilder sb = new StringBuilder(elem.getPart());
- ASTNode parent;
- while (true) {
- parent = elem.getParent();
- if (parent == null) break;
- assert parent instanceof List;
- parent = parent.getParent();
- if (parent == null || parent instanceof MqttRoot) {
- break;
- }
- elem = (MqttTopic) parent;
- sb.insert(0, elem.getPart() + "/");
- }
- return sb.toString();
+ private <Src extends ASTNode, Target extends ASTNode> void resolveList(
+ Map<String, Target> resolved, Map<Src, Iterable<String>> missing, BiConsumer<Src, Target> adder) {
+ missing.forEach(
+ (elem, keyList) -> keyList.forEach(
+ key -> resolve0(resolved, key, elem, adder)));
+ missing.clear();
}
- private <Src extends ASTNode, Target extends ASTNode> void resolveList(Map<String, Target> resolved, Map<Src, Iterable<String>> missing, BiConsumer<Src, Target> adder) {
- missing.forEach((elem, keyList) -> keyList.forEach(key -> {
- Target value = resolved.get(key);
- if (value == null) {
- logger.warn("Reference in {} {} for '{}' cannot be resolved",
- elem.getClass().getSimpleName(), ident(elem), key);
- return;
- }
- if (checkUnusedElements) {
- unusedElements.remove(value);
- }
- adder.accept(elem, value);
- }));
+ private <Src extends ASTNode, Target extends ASTNode> void resolve(
+ Map<String, Target> resolved, Map<Src, String> missing, BiConsumer<Src, Target> setter) {
+ missing.forEach(
+ (elem, key) -> resolve0(resolved, key, elem, setter));
missing.clear();
}
- private <Src extends ASTNode, Target extends ASTNode> void resolve(Map<String, Target> resolved, Map<Src, String> missing, BiConsumer<Src, Target> setter) {
- missing.forEach((elem, key) -> {
- Target value = resolved.get(key);
- if (value == null) {
- logger.warn("Reference in {} {} for '{}' cannot be resolved",
- elem.getClass().getSimpleName(), ident(elem), key);
- return;
- }
- if (checkUnusedElements) {
- unusedElements.remove(value);
- }
- setter.accept(elem, value);
- });
- missing.clear();
+ private <Src extends ASTNode, Target extends ASTNode> void resolve0(
+ Map<String, Target> resolved, String key, Src elem, BiConsumer<Src, Target> action) {
+ Target value = resolved.get(key);
+ if (value == null) {
+ logger.warn("Reference in {} {} for '{}' cannot be resolved",
+ elem.getClass().getSimpleName(), ident(elem), key);
+ return;
+ }
+ if (checkUnusedElements) {
+ unusedElements.remove(value);
+ }
+ action.accept(elem, value);
}
+ //--- Thing and ThingType ---
+
public Thing addThingType(Thing t, String typeName) {
missingThingTypeMap.put(t, typeName);
return t;
}
- public ChannelType setItemType(ChannelType ct, String itemTypeName) {
- ct.setItemType(ItemType.valueOf(itemTypeName));
- return ct;
+ public ThingType setChannelTypes(ThingType tt, StringList channelTypeNames) {
+ missingChannelTypeListMap.put(tt, channelTypeNames);
+ return tt;
}
- public Item setCategory(Item item, String categoryName) {
- missingItemCategoryMap.put(item, categoryName);
- return item;
+ public ThingType setParameters(ThingType tt, StringList parameterNames) {
+ missingParameterListMap.put(tt, parameterNames);
+ return tt;
}
- public Item setTopic(Item item, String mqttTopicName) {
- missingTopicMap.put(item, mqttTopicName);
- return item;
+ public Thing setChannels(Thing t, StringList channelNames) {
+ missingChannelListMap.put(t, channelNames);
+ return t;
}
- public Item setControlling(Item item, StringList controlling) {
- missingControllingListMap.put(item, controlling);
- return item;
+ public Thing setID(Thing thing, String id) {
+ thing.setID(id);
+ return thing;
}
- public Item setMetaData(Item item, StringMap metaData) {
- for (AbstractMap.SimpleEntry<String, String> entry : metaData) {
- item.addMetaData(new ItemMetaData(entry.getKey(), entry.getValue()));
- }
- return item;
+ public ThingType setID(ThingType thingType, String id) {
+ thingType.setID(id);
+ thingTypeMap.put(id, thingType);
+ return thingType;
+ }
+
+ //--- Channel and ChannelType ---
+
+ public ChannelType setItemType(ChannelType ct, String itemTypeName) {
+ ct.setItemType(ItemType.valueOf(itemTypeName));
+ return ct;
}
public ChannelType setChannelCategory(ChannelType ct, String name) {
@@ -244,6 +233,95 @@ public class EraserParserHelper {
return ct;
}
+ public Channel setChannelType(Channel c, String channelTypeName) {
+ missingChannelTypeMap.put(c, channelTypeName);
+ return c;
+ }
+
+ public Channel setLinks(Channel c, StringList linkNames) {
+ missingItemLinkListMap.put(c, linkNames);
+ return c;
+ }
+
+ public ChannelType setID(ChannelType channelType, String id) {
+ channelType.setID(id);
+ channelTypeMap.put(id, channelType);
+ return channelType;
+ }
+
+ public Channel setID(Channel channel, String id) {
+ channel.setID(id);
+ channelMap.put(id, channel);
+ return channel;
+ }
+
+ //--- Item ---
+
+ public Item createItem() {
+ ItemPrototype result = new ItemPrototype();
+ result.disableSendState();
+ return result;
+ }
+
+ public Item setCategory(Item item, String categoryName) {
+ missingItemCategoryMap.put(item, categoryName);
+ return item;
+ }
+
+ public Item setMetaData(Item item, StringKeyMap metaData) {
+ for (AbstractMap.SimpleEntry<String, String> entry : metaData) {
+ item.addMetaData(new ItemMetaData(entry.getKey(), entry.getValue()));
+ }
+ return item;
+ }
+
+ public Item setControlling(Item item, StringList controlling) {
+ missingControllingListMap.put(item, controlling);
+ return item;
+ }
+
+ public Item retype(Item itemWithCorrectType, Item prototype) {
+ itemWithCorrectType.setID(prototype.getID());
+ itemWithCorrectType.setLabel(prototype.getLabel());
+ itemWithCorrectType.setMetaDataList(prototype.getMetaDataList());
+ if (!(itemWithCorrectType instanceof ActivityItem)) {
+ String state = prototype.getStateAsString();
+ itemWithCorrectType.disableSendState();
+ if (state.isEmpty()) {
+ itemWithCorrectType.setStateToDefault();
+ } else {
+ itemWithCorrectType.setStateFromString(state);
+ }
+ itemWithCorrectType.enableSendState();
+ }
+
+ moveMissingForRetype(itemWithCorrectType, prototype, missingTopicMap);
+ moveMissingForRetype(itemWithCorrectType, prototype, missingControllingListMap);
+ moveMissingForRetype(itemWithCorrectType, prototype, missingItemCategoryMap);
+
+ itemMap.put(prototype.getID(), itemWithCorrectType);
+
+ itemOrder.add(itemWithCorrectType);
+
+ return itemWithCorrectType;
+ }
+
+ private <T> void moveMissingForRetype(Item itemWithCorrectType, Item prototype, Map<Item, T> missingXMap) {
+ T value = missingXMap.get(prototype);
+ if (value != null) {
+ missingXMap.put(itemWithCorrectType, value);
+ }
+ missingXMap.remove(prototype);
+ }
+
+ public Item setID(Item item, String id) {
+ item.setID(id);
+ itemMap.put(id, item);
+ return item;
+ }
+
+ //--- Group ---
+
public Group setSubGroups(Group g, StringList subGroupNames) {
missingSubGroupListMap.put(g, subGroupNames);
return g;
@@ -278,77 +356,77 @@ public class EraserParserHelper {
return g;
}
- public ThingType setChannelTypes(ThingType tt, StringList channelTypeNames) {
- missingChannelTypeListMap.put(tt, channelTypeNames);
- return tt;
+ public Group setID(Group group, String id) {
+ group.setID(id);
+ groupMap.put(id, group);
+ return group;
}
+ //--- Parameter ---
+
public Parameter setParameterValueType(Parameter p, String pvt) {
- p.setType(ParameterValueType.valueOf(toTitleCase(pvt)));
+ p.setType(ParameterValueType.valueOf(JavaUtils.toTitleCase(pvt)));
return p;
}
- private String toTitleCase(String s) {
- if (s == null || s.isEmpty()) {
- return s;
- }
- return s.substring(0, 1).toUpperCase() + s.substring(1);
- }
-
public Parameter setDefault(Parameter p, String defaultValue) {
p.setDefaultValue(new ParameterDefaultValue(defaultValue));
return p;
}
- public ThingType setParameters(ThingType tt, StringList parameterNames) {
- missingParameterListMap.put(tt, parameterNames);
- return tt;
+ public Parameter setID(Parameter parameter, String id) {
+ parameter.setID(id);
+ parameterMap.put(id, parameter);
+ return parameter;
}
- public Thing setChannels(Thing t, StringList channelNames) {
- missingChannelListMap.put(t, channelNames);
- return t;
- }
+ //--- MQTT ---
- public Channel setChannelType(Channel c, String channelTypeName) {
- missingChannelTypeMap.put(c, channelTypeName);
- return c;
+ public Item setTopic(Item item, String mqttTopicName) {
+ missingTopicMap.put(item, mqttTopicName);
+ return item;
}
- public Channel setLinks(Channel c, StringList linkNames) {
- missingItemLinkListMap.put(c, linkNames);
- return c;
+ //--- Activity ---
+
+ public MachineLearningRoot setActivities(MachineLearningRoot mlr, IntegerKeyMap map) {
+ for (AbstractMap.SimpleEntry<Integer, String> entry : map) {
+ Activity activity = new Activity();
+ activity.setIdentifier(entry.getKey());
+ activity.setLabel(entry.getValue());
+ mlr.addActivity(activity);
+ }
+ return mlr;
}
+ //--- Root ---
+
public Root createRoot() {
- this.root = new Root();
- this.root.setMqttRoot(new MqttRoot());
- this.root.setInfluxRoot(InfluxRoot.createDefault());
- this.root.setMachineLearningRoot(new MachineLearningRoot());
+ this.root = Root.createEmptyRoot();
return this.root;
}
public Root createRoot(Thing t) {
Root result = createRoot();
- result.addThing(t);
+ result.getOpenHAB2Model().addThing(t);
return result;
}
public Root createRoot(Group g) {
Root result = createRoot();
- result.addGroup(g);
+ result.getOpenHAB2Model().addGroup(g);
return result;
}
public Root createRoot(ThingType tt) {
Root result = createRoot();
- result.addThingType(tt);
+ result.getOpenHAB2Model().addThingType(tt);
return result;
}
public Root createRoot(ChannelType ct) {
Root result = createRoot();
- result.addChannelType(ct);
+ result.getOpenHAB2Model().addChannelType(ct);
return result;
}
@@ -364,83 +442,10 @@ public class EraserParserHelper {
return result;
}
- public Item createItem() {
- ItemPrototype result = new ItemPrototype();
- result.disableSendState();
+ public Root createRoot(MachineLearningRoot ml) {
+ Root result = createRoot();
+ result.setMachineLearningRoot(ml);
return result;
}
- public Item retype(Item itemWithCorrectType, Item prototype) {
- itemWithCorrectType.setID(prototype.getID());
- itemWithCorrectType.setLabel(prototype.getLabel());
- itemWithCorrectType.setMetaDataList(prototype.getMetaDataList());
- String state = prototype.getStateAsString();
- itemWithCorrectType.disableSendState();
- if (state.isEmpty()) {
- itemWithCorrectType.setStateToDefault();
- } else {
- itemWithCorrectType.setStateFromString(state);
- }
- itemWithCorrectType.enableSendState();
-
- moveMissingForRetype(itemWithCorrectType, prototype, missingTopicMap);
- moveMissingForRetype(itemWithCorrectType, prototype, missingControllingListMap);
- moveMissingForRetype(itemWithCorrectType, prototype, missingItemCategoryMap);
-
- itemMap.put(prototype.getID(), itemWithCorrectType);
-
- itemOrder.add(itemWithCorrectType);
-
- return itemWithCorrectType;
- }
-
- private <T> void moveMissingForRetype(Item itemWithCorrectType, Item prototype, Map<Item, T> missingXMap) {
- T value = missingXMap.get(prototype);
- if (value != null) {
- missingXMap.put(itemWithCorrectType, value);
- }
- missingXMap.remove(prototype);
- }
-
- public Thing setID(Thing thing, String id) {
- thing.setID(id);
- return thing;
- }
-
- public Item setID(Item item, String id) {
- item.setID(id);
- itemMap.put(id, item);
- return item;
- }
-
- public Group setID(Group group, String id) {
- group.setID(id);
- groupMap.put(id, group);
- return group;
- }
-
- public ThingType setID(ThingType thingType, String id) {
- thingType.setID(id);
- thingTypeMap.put(id, thingType);
- return thingType;
- }
-
- public Parameter setID(Parameter parameter, String id) {
- parameter.setID(id);
- parameterMap.put(id, parameter);
- return parameter;
- }
-
- public ChannelType setID(ChannelType channelType, String id) {
- channelType.setID(id);
- channelTypeMap.put(id, channelType);
- return channelType;
- }
-
- public Channel setID(Channel channel, String id) {
- channel.setID(id);
- channelMap.put(id, channel);
- return channel;
- }
-
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/JavaUtils.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/JavaUtils.java
index 5a66f6a1d321480e3356c37c72f90998ad888d77..79e02fb74f53357b69b464e472801afbf311c3fd 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/JavaUtils.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/JavaUtils.java
@@ -45,4 +45,11 @@ public class JavaUtils {
return StreamSupport.stream(jastAddList.spliterator(), false);
}
+ public static String toTitleCase(String s) {
+ if (s == null || s.isEmpty()) {
+ return s;
+ }
+ return s.substring(0, 1).toUpperCase() + s.substring(1);
+ }
+
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MemberPrinter.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MemberPrinter.java
index 7f9bb0e29dfa838242d6ad4b15ee1f83f5481366..a6c89a42bca8e978f837ad805ec4278634f3afa4 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MemberPrinter.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MemberPrinter.java
@@ -17,7 +17,9 @@ import java.util.function.Supplier;
public class MemberPrinter {
private static final Logger logger = LogManager.getLogger(MemberPrinter.class);
- private boolean addSemicolonNewlineWhenBuild;
+ private static boolean addSemicolonNewlineWhenBuild = true;
+ private static boolean emitNothingOnEmptyBody = true;
+ private boolean empty = true;
private final StringBuilder sb;
public enum ListBracketType {
@@ -35,14 +37,28 @@ public class MemberPrinter {
}
public MemberPrinter(String elementName) {
- this.addSemicolonNewlineWhenBuild = true;
this.sb = new StringBuilder();
if (elementName != null && !elementName.isEmpty()) {
sb.append(elementName).append(":");
}
}
+ public static void setAddSemicolonNewlineWhenBuild(boolean addSemicolonNewlineWhenBuild) {
+ MemberPrinter.addSemicolonNewlineWhenBuild = addSemicolonNewlineWhenBuild;
+ }
+
+ public static void setEmitNothingOnEmptyBody(boolean emitNothingOnEmptyBody) {
+ MemberPrinter.emitNothingOnEmptyBody = emitNothingOnEmptyBody;
+ }
+
public String build() {
+ if (empty) {
+ if (emitNothingOnEmptyBody) {
+ return "";
+ } else {
+ logger.debug("Emitting empty body {}", sb);
+ }
+ }
if (addSemicolonNewlineWhenBuild) {
sb.append(" ;\n");
}
@@ -117,6 +133,7 @@ public class MemberPrinter {
sb.append(' ').append(name).append("=[");
concatIds(listOfElements);
sb.append("]");
+ this.empty = false;
}
return this;
}
@@ -136,6 +153,7 @@ public class MemberPrinter {
sb.append(' ').append(name).append("=[");
concatIds(listOfNodes, mapping);
sb.append("]");
+ this.empty = false;
}
return this;
}
@@ -171,6 +189,7 @@ public class MemberPrinter {
sb.append(' ').append(name).append("=").append(bracketType.begin);
concatNodes(listOfNodes, mapping, false);
sb.append(bracketType.end);
+ this.empty = false;
}
return this;
}
@@ -197,6 +216,7 @@ public class MemberPrinter {
*/
public MemberPrinter addOptionalPrettyPrint(ASTNode child) {
if (child != null) {
+ this.empty = false;
sb.append(child.prettyPrint());
}
return this;
@@ -210,6 +230,7 @@ public class MemberPrinter {
*/
public MemberPrinter addFlag(String name, boolean isSet) {
if (isSet) {
+ this.empty = false;
sb.append(' ').append(name);
}
return this;
@@ -234,6 +255,7 @@ public class MemberPrinter {
*/
public MemberPrinter addNonDefault(String name, Object actualValue, Object defaultValue) {
if (!actualValue.equals(defaultValue)) {
+ this.empty = false;
return add(name, actualValue);
}
return this;
@@ -275,6 +297,7 @@ public class MemberPrinter {
}
private MemberPrinter add(String name, Object actualValue) {
+ this.empty = false;
sb.append(' ').append(name).append("=\"").append(actualValue).append("\"");
return this;
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java
index e433bf34d3b2e4848291a766ca3b5e1c55a80dc3..1f013ea25872e57e452a603616e95126bdd69e11 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/MqttReceiver.java
@@ -1,6 +1,5 @@
package de.tudresden.inf.st.eraser.util;
-import de.tudresden.inf.st.eraser.openhab2.mqtt.MQTTUpdater;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.fusesource.hawtbuf.Buffer;
@@ -40,7 +39,7 @@ public class MqttReceiver implements AutoCloseable {
private QoS qos;
public MqttReceiver() {
- this.logger = LogManager.getLogger(MQTTUpdater.class);
+ this.logger = LogManager.getLogger(MqttReceiver.class);
this.readyLock = new ReentrantLock();
this.readyCondition = readyLock.newCondition();
this.ready = false;
@@ -50,8 +49,8 @@ public class MqttReceiver implements AutoCloseable {
/**
* Sets the host to receive messages from
*/
- public void setHost(String host) {
- this.host = URI.create("tcp://" + host + ":1883");
+ public void setHost(String host, int port) {
+ this.host = URI.create("tcp://" + host + ":" + port);
logger.debug("Host is {}", this.host);
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/ParserUtils.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/ParserUtils.java
index 4147e65d032584a27e77c019f7e1f2172b6aa807..5eca1e63816e64d4c5811abcde3861b3b00dee14 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/ParserUtils.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/ParserUtils.java
@@ -3,10 +3,7 @@ package de.tudresden.inf.st.eraser.util;
import beaver.Parser;
import beaver.Scanner;
import beaver.Symbol;
-import de.tudresden.inf.st.eraser.jastadd.model.Group;
-import de.tudresden.inf.st.eraser.jastadd.model.Item;
-import de.tudresden.inf.st.eraser.jastadd.model.MqttTopic;
-import de.tudresden.inf.st.eraser.jastadd.model.Root;
+import de.tudresden.inf.st.eraser.jastadd.model.*;
import de.tudresden.inf.st.eraser.jastadd.parser.EraserParser;
import de.tudresden.inf.st.eraser.jastadd.scanner.EraserScanner;
import org.apache.logging.log4j.LogManager;
@@ -16,8 +13,8 @@ import java.io.*;
import java.net.URL;
import java.nio.file.Files;
import java.nio.file.Paths;
-import java.util.*;
-import java.util.stream.Collectors;
+import java.util.Collection;
+import java.util.Objects;
/**
* Utility methods involving scanner and parser of the models.
@@ -29,6 +26,38 @@ public class ParserUtils {
private static boolean verboseLoading = false;
private static final Logger logger = LogManager.getLogger(ParserUtils.class);
+ private interface ReaderProvider {
+ Reader provide() throws IOException;
+ }
+
+ private static class ReaderProviderByName implements ReaderProvider {
+ private final String filename;
+ private final Class<?> clazz;
+
+ ReaderProviderByName(String filename, Class<?> clazz) {
+ this.filename = filename;
+ this.clazz = clazz;
+ }
+
+ @Override
+ public Reader provide() throws IOException {
+ return getReader(filename, clazz);
+ }
+ }
+
+ private static class ReaderProviderByURL implements ReaderProvider {
+ private final URL url;
+
+ ReaderProviderByURL(URL url) {
+ this.url = url;
+ }
+
+ @Override
+ public Reader provide() throws IOException {
+ return new InputStreamReader(url.openStream());
+ }
+ }
+
/**
* Print read tokens before loading the model.
* This will effectively parse the input two times, thus slowing the operation.
@@ -71,8 +100,23 @@ public class ParserUtils {
*/
public static Root load(String fileName, Class<?> clazz) throws IOException, Parser.Exception {
logger.info("Loading model DSL file '{}'", fileName);
+ return load(new ReaderProviderByName(fileName, clazz));
+ }
- Reader reader = getReader(fileName, clazz);
+ /**
+ * Loads a model in a file from the given URL.
+ * @param url an URL pointing to a file
+ * @return the parsed model
+ * @throws IOException if the file could not be found, or opened
+ * @throws Parser.Exception if the file contains a malformed model
+ */
+ public static Root load(URL url) throws IOException, Parser.Exception {
+ logger.info("Loading model DSL from '{}'", url);
+ return load(new ReaderProviderByURL(url));
+ }
+
+ private static Root load(ReaderProvider readerProvider) throws IOException, Parser.Exception {
+ Reader reader = readerProvider.provide();
if (verboseLoading) {
EraserScanner scanner = new EraserScanner(reader);
try {
@@ -87,7 +131,7 @@ public class ParserUtils {
try {
reader.reset();
} catch (IOException resetEx) {
- reader = getReader(fileName, clazz);
+ reader = readerProvider.provide();
}
}
}
@@ -120,7 +164,12 @@ public class ParserUtils {
}
}
- public static void createUnknownGroup(Root model, Collection<Item> danglingItems) {
+ /**
+ * Create well-known group call "Unknown" and add all dangling items to it.
+ * @param model The model to operate on
+ * @param danglingItems A list of items to add to the new group
+ */
+ public static void createUnknownGroup(OpenHAB2Model model, Collection<Item> danglingItems) {
Group unknownGroup = new Group();
unknownGroup.setID("Unknown");
model.addGroup(unknownGroup);
@@ -128,55 +177,19 @@ public class ParserUtils {
logger.info("Created new {}", unknownGroup.prettyPrint().trim());
}
- public static void createMqttTopic(Item item, String topicName, Root root) {
- String[] parts = topicName.split("/");
- String firstPart = parts[0];
- MqttTopic firstTopic = null;
- for (MqttTopic topic : root.getMqttRoot().getTopicList()) {
- if (topic.getPart().equals(firstPart)) {
- firstTopic = topic;
- break;
- }
- }
- if (firstTopic == null) {
- // no matching topic found for first part. create one.
- firstTopic = createTopic(firstPart, root);
- }
-// MqttTopic firstTopic = firstPartTopicMap.computeIfAbsent(firstPart, part -> createTopic(part, root));
- MqttTopic lastTopic = processRemainingTopicParts(firstTopic, parts, 1);
- item.setTopic(lastTopic);
- }
-
- private static MqttTopic processRemainingTopicParts(MqttTopic topic, String[] parts, int index) {
- if (index >= parts.length) {
- return topic;
- }
- for (MqttTopic subTopic : topic.getSubTopicList()) {
- if (subTopic.getPart().equals(parts[index])) {
- // matching part found
- return processRemainingTopicParts(subTopic, parts, index + 1);
- }
- }
- // no matching part was found. create remaining topics.
- for (int currentIndex = index; currentIndex < parts.length; currentIndex++) {
- MqttTopic newTopic = createSubTopic(parts[currentIndex]);
- topic.addSubTopic(newTopic);
- topic = newTopic;
- }
- return topic;
- }
-
- private static MqttTopic createSubTopic(String part) {
- return createTopic(part, null);
- }
-
- private static MqttTopic createTopic(String part, Root root) {
- MqttTopic result = new MqttTopic();
- result.setPart(part);
- if (root != null) {
+ /**
+ * Create a topic for the given topic name and assign it to the given item.
+ * @param item The item to which the topic will be assigned to
+ * @param topicSuffix The full topic name
+ * @param root The model to operate on
+ */
+ public static void createMqttTopic(Item item, String topicSuffix, Root root) {
+ item.setTopic(root.getMqttRoot().resolveTopicSuffix(topicSuffix).orElseGet(() -> {
+ MqttTopic result = new MqttTopic();
+ result.setTopicString(topicSuffix);
root.getMqttRoot().addTopic(result);
- }
- return result;
+ return result;
+ }));
}
}
diff --git a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/TestUtils.java b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/TestUtils.java
index f31ffd14dc1b8a017396a1efc5e15b76d65110bd..5f07ec7c576829975db82121e42e142497b49586 100644
--- a/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/TestUtils.java
+++ b/eraser-base/src/main/java/de/tudresden/inf/st/eraser/util/TestUtils.java
@@ -10,9 +10,9 @@ import de.tudresden.inf.st.eraser.jastadd.model.*;
public class TestUtils {
public static class ModelAndItem {
- public Root model;
+ public OpenHAB2Model model;
public NumberItem item;
- static ModelAndItem of(Root model, NumberItem item) {
+ static ModelAndItem of(OpenHAB2Model model, NumberItem item) {
ModelAndItem result = new ModelAndItem();
result.model = model;
result.item = item;
@@ -25,21 +25,21 @@ public class TestUtils {
}
public static ModelAndItem createModelAndItem(double initialValue, boolean useUpdatingItem) {
- Root model = Root.createEmptyRoot();
+ Root root = Root.createEmptyRoot();
Group g = new Group();
- model.addGroup(g);
+ root.getOpenHAB2Model().addGroup(g);
g.setID("group1");
NumberItem item = addItemTo(g, initialValue, useUpdatingItem);
- return ModelAndItem.of(model, item);
+ return ModelAndItem.of(root.getOpenHAB2Model(), item);
}
- public static NumberItem addItemTo(Root model, double initialValue) {
+ public static NumberItem addItemTo(OpenHAB2Model model, double initialValue) {
return addItemTo(model, initialValue, false);
}
- public static NumberItem addItemTo(Root model, double initialValue, boolean useUpdatingItem) {
+ public static NumberItem addItemTo(OpenHAB2Model model, double initialValue, boolean useUpdatingItem) {
return addItemTo(getDefaultGroup(model), initialValue, useUpdatingItem);
}
@@ -56,7 +56,7 @@ public class TestUtils {
return item;
}
- public static Group getDefaultGroup(Root model) {
+ public static Group getDefaultGroup(OpenHAB2Model model) {
// use first found group
return model.getGroup(0);
}
diff --git a/eraser-base/src/main/resources/log4j2.xml b/eraser-base/src/main/resources/log4j2.xml
index 89799a2f09ba34d288e610d960b3ed6348213105..18175a02521156259c8789745fb849fa893302e9 100644
--- a/eraser-base/src/main/resources/log4j2.xml
+++ b/eraser-base/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ControllingItemTest.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ControllingItemTest.java
index 75773e80bdd0ed7ad5ca6a9d13accb28c0f05a54..edc98e72719ef63ffa63f0cb19aac9b7106ab879 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ControllingItemTest.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ControllingItemTest.java
@@ -6,6 +6,8 @@ import de.tudresden.inf.st.eraser.jastadd.model.*;
import org.junit.Assert;
import org.junit.Test;
+import java.util.function.Consumer;
+
/**
* Testing the simple rule engine.
*
@@ -56,26 +58,22 @@ public class ControllingItemTest {
@Test
public void testManyToOneColor() {
ModelAndItem mai = TestUtils.createModelAndItem(0);
- Root model = mai.model;
+ OpenHAB2Model model = mai.model;
NumberItem numberItem = mai.item;
Group g = TestUtils.getDefaultGroup(model);
- StringItem stringItem = new StringItem();
- stringItem.setState("0");
- initAndAddItem(g, stringItem);
+ StringItem stringItem = initAndAddItem(g, new StringItem(),
+ item -> item.setState("0"));
- SwitchItem booleanItem = new SwitchItem();
- booleanItem.setState(false);
- initAndAddItem(g, booleanItem);
+ SwitchItem booleanItem = initAndAddItem(g, new SwitchItem(),
+ item -> item.setState(false));
- ColorItem colorItem = new ColorItem();
- colorItem.setState(TupleHSB.of(0, 0, 0));
- initAndAddItem(g, colorItem);
+ ColorItem colorItem = initAndAddItem(g, new ColorItem(),
+ item -> item.setState(TupleHSB.of(0, 0, 0)));
- ColorItem target = new ColorItem();
- target.setState(TupleHSB.of(0, 0, 0));
- initAndAddItem(g, target);
+ ColorItem target = initAndAddItem(g, new ColorItem(),
+ item -> item.setState(TupleHSB.of(0, 0, 0)));
target.addControlledBy(numberItem);
target.addControlledBy(stringItem);
@@ -119,9 +117,11 @@ public class ControllingItemTest {
Assert.assertEquals("Item was not controlled correctly", TupleHSB.of(33, 33, 44), target.getState());
}
- private void initAndAddItem(Group group, Item item) {
- item.enableSendState();
+ private <T extends Item> T initAndAddItem(Group group, T item, Consumer<T> setState) {
item.setID("item" + group.getNumItem());
group.addItem(item);
+ setState.accept(item);
+ item.enableSendState();
+ return item;
}
}
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/DecisionTreeTest.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/DecisionTreeTest.java
index 89fbacb6e128f72aea11eccb52155ca422906ac0..fa93e0691d782030d2e45c385f9327a57c9e1ae4 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/DecisionTreeTest.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/DecisionTreeTest.java
@@ -17,7 +17,7 @@ public class DecisionTreeTest {
TestUtils.ModelAndItem mai = TestUtils.createModelAndItem(4);
DecisionTreeRoot dtroot = new DecisionTreeRoot();
- mai.model.getMachineLearningRoot().setActivityRecognition(dtroot);
+ mai.model.getRoot().getMachineLearningRoot().setActivityRecognition(dtroot);
DecisionTreeLeaf isLessThanFour = newLeaf("less than four");
DecisionTreeLeaf isFourOrGreater = newLeaf("four or greater");
ItemStateNumberCheck check = new ItemStateNumberCheck(ComparatorType.LessThan, 4f);
@@ -44,7 +44,7 @@ public class DecisionTreeTest {
TestUtils.ModelAndItem mai = TestUtils.createModelAndItem(20);
DecisionTreeRoot dtroot = new DecisionTreeRoot();
- mai.model.getMachineLearningRoot().setActivityRecognition(dtroot);
+ mai.model.getRoot().getMachineLearningRoot().setActivityRecognition(dtroot);
DecisionTreeLeaf isLessThan25 = newLeaf("less than 25");
DecisionTreeLeaf is25OrGreater = newLeaf("25 or greater");
@@ -130,7 +130,7 @@ public class DecisionTreeTest {
TestUtils.ModelAndItem mai = TestUtils.createModelAndItem(0);
DecisionTreeRoot dtroot = new DecisionTreeRoot();
- mai.model.getMachineLearningRoot().setActivityRecognition(dtroot);
+ mai.model.getRoot().getMachineLearningRoot().setActivityRecognition(dtroot);
DecisionTreeLeaf left = newLeaf("left");
DecisionTreeLeaf right = newLeaf("right");
ItemStateNumberCheck check = new ItemStateNumberCheck(comparatorType, expected);
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/InfluxTest.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/InfluxTest.java
index 5fd3a3ac2320207da3ebf2bc7ff91c1470efeec8..a7d76202ffc30da22280f9a5ec95c643cb4aee42 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/InfluxTest.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/InfluxTest.java
@@ -1,11 +1,12 @@
package de.tudresden.inf.st.eraser;
+import de.tudresden.inf.st.eraser.jastadd.model.*;
import de.tudresden.inf.st.eraser.util.TestUtils;
import de.tudresden.inf.st.eraser.util.TestUtils.ModelAndItem;
-import de.tudresden.inf.st.eraser.jastadd.model.*;
import org.junit.*;
import org.junit.runner.RunWith;
import org.junit.runners.Parameterized;
+import org.testcontainers.containers.InfluxDBContainer;
import java.time.Instant;
import java.util.ArrayList;
@@ -29,6 +30,12 @@ public class InfluxTest {
private ModelAndItem mai;
+ @ClassRule
+ public static InfluxDBContainer influxDbContainer = new InfluxDBContainer()
+ .withDatabase(InfluxRoot.createDefault().getDbName())
+ .withUsername(InfluxRoot.createDefault().getUser())
+ .withPassword(InfluxRoot.createDefault().getPassword());
+
@Test
public void oneItem() {
NumberItem item = mai.item;
@@ -95,8 +102,8 @@ public class InfluxTest {
@Test
public void justAdapter() {
- InfluxAdapter influxAdapter = mai.model.getInfluxRoot().influxAdapter();
- Assume.assumeTrue("Adapter not connected", influxAdapter.isConnected());
+ InfluxAdapter influxAdapter = getInfluxRoot().influxAdapter();
+ Assert.assertTrue("Adapter not connected", influxAdapter.isConnected());
influxAdapter.deleteDatabase();
// write one point
@@ -151,12 +158,16 @@ public class InfluxTest {
influxRoot.setDbName(InfluxTest.class.getSimpleName());
influxRoot.setHostByName("vm2098.zih.tu-dresden.de");
}
- mai.model.setInfluxRoot(influxRoot);
+ mai.model.getRoot().setInfluxRoot(influxRoot);
Assume.assumeTrue(influxRoot.influxAdapter().isConnected());
influxRoot.influxAdapter().deleteDatabase();
return mai;
}
+ private InfluxRoot getInfluxRoot() {
+ return mai.model.getRoot().getInfluxRoot();
+ }
+
private List<DoubleStatePoint> query(ItemWithDoubleState... allItems) {
if (useStub) {
return points;
@@ -172,13 +183,13 @@ public class InfluxTest {
@Before
public void setNewModel() {
mai = createModel();
- mai.model.getInfluxRoot().influxAdapter().disableAsyncQuery();
+ getInfluxRoot().influxAdapter().disableAsyncQuery();
}
@After
public void closeInfluxAdapter() throws Exception {
if (mai != null && mai.model != null) {
- mai.model.getInfluxRoot().influxAdapter().close();
+ getInfluxRoot().influxAdapter().close();
}
}
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ItemTests.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ItemTests.java
index 0b02f08b9d6c12e2ac51935d2c1da8bb7660c5e6..ffda213bea9a359097db8b962f03a48e52502c57 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ItemTests.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ItemTests.java
@@ -1,9 +1,12 @@
package de.tudresden.inf.st.eraser;
import de.tudresden.inf.st.eraser.jastadd.model.*;
+import de.tudresden.inf.st.eraser.util.TestUtils;
+import de.tudresden.inf.st.eraser.util.TestUtils.ModelAndItem;
import org.junit.Assert;
import org.junit.Test;
+import java.time.Instant;
import java.util.Date;
/**
@@ -15,7 +18,7 @@ public class ItemTests {
@Test
public void testItemWithBooleanStateEquals() {
- ItemWithBooleanState sut = new SwitchItem();
+ ItemWithBooleanState sut = createItem(SwitchItem::new);
sut.setState(true);
Assert.assertTrue("State 'true' should match 'true'", sut.stateEquals(true));
@@ -28,7 +31,7 @@ public class ItemTests {
@Test
public void testItemWithStringStateEquals() {
- ItemWithStringState sut = new ImageItem();
+ ItemWithStringState sut = createItem(ImageItem::new);
sut.setState("correct");
Assert.assertTrue("State 'correct' should match 'correct'",
@@ -39,7 +42,7 @@ public class ItemTests {
@Test
public void testItemWithDoubleStateEquals() {
- ItemWithDoubleState sut = new NumberItem();
+ ItemWithDoubleState sut = createItem(NumberItem::new);
sut.setState(3.0);
Assert.assertTrue("State '3.0' should match '3.0'", sut.stateEquals(3.0));
@@ -52,7 +55,7 @@ public class ItemTests {
@Test
public void testItemWithTupleHSBStateEquals() {
- ColorItem sut = new ColorItem();
+ ColorItem sut = createItem(ColorItem::new);
sut.setState(TupleHSB.of(1, 2, 3));
Assert.assertTrue("State 'TupleHSB(1,2,3)' should match 'TupleHSB(1,2,3)'",
@@ -71,73 +74,27 @@ public class ItemTests {
@Test
public void testItemWithDateStateEquals() {
- DateTimeItem sut = new DateTimeItem();
+ DateTimeItem sut = createItem(DateTimeItem::new);
- sut.setState(new Date(1543415826));
+ sut.setState(Instant.ofEpochMilli(1543415826));
Assert.assertTrue("State 'Date(1543415826)' should match 'Date(1543415826)'",
- sut.stateEquals(new Date(1543415826)));
+ sut.stateEquals(Instant.ofEpochMilli(1543415826)));
Assert.assertFalse("State 'Date(1543415826)' should not match 'Date(4)'",
- sut.stateEquals(new Date(4)));
+ sut.stateEquals(Instant.ofEpochMilli(4)));
}
- @Test
- public void testItemWithBooleanCopyEquals() {
- ItemWithBooleanState sut = new SwitchItem();
-
- sut.setState(true);
- Object copiedState = sut.copyState();
- Assert.assertTrue("State 'true' should match copy", sut.stateEquals(copiedState));
-
- sut.setState(false);
- Assert.assertFalse("State 'false' should not match copy", sut.stateEquals(copiedState));
- }
-
- @Test
- public void testItemWithStringCopyEquals() {
- ItemWithStringState sut = new ImageItem();
-
- sut.setState("correct");
- Object copiedState = sut.copyState();
- Assert.assertTrue("State 'correct' should match copy", sut.stateEquals(copiedState));
-
- sut.setState("something else");
- Assert.assertFalse("State 'something else' should not match copy", sut.stateEquals(copiedState));
+ @FunctionalInterface
+ private interface CreateItem<T extends Item> {
+ T create();
}
- @Test
- public void testItemWithLongCopyEquals() {
- ItemWithDoubleState sut = new NumberItem();
-
- sut.setState(3.0);
- Object copiedState = sut.copyState();
- Assert.assertTrue("State '3.0' should match copy", sut.stateEquals(copiedState));
-
- sut.setState(4.0);
- Assert.assertFalse("State '4.0' should not match copy", sut.stateEquals(copiedState));
- }
-
- @Test
- public void testItemWithTupleHSBCopyEquals() {
- ColorItem sut = new ColorItem();
-
- sut.setState(TupleHSB.of(1, 2, 3));
- Object copiedState = sut.copyState();
- Assert.assertTrue("State 'TupleHSB(1,2,3)' should match copy", sut.stateEquals(copiedState));
-
- sut.setState(TupleHSB.of(5,5,5));
- Assert.assertFalse("State 'TupleHSB(5,5,5)' should not match copy", sut.stateEquals(copiedState));
- }
-
- @Test
- public void testItemWithDateCopyEquals() {
- DateTimeItem sut = new DateTimeItem();
-
- sut.setState(new Date(1543415826));
- Object copiedState = sut.copyState();
- Assert.assertTrue("State 'Date(1543415826' should match copy", sut.stateEquals(copiedState));
-
- sut.setState(new Date(4));
- Assert.assertFalse("State 'Date(4)' should not match copy", sut.stateEquals(copiedState));
+ private <T extends Item> T createItem(CreateItem<T> creator) {
+ // create a root with default group and one unused item
+ ModelAndItem mai = TestUtils.createModelAndItem(0);
+ // create wanted item, add it to default group, and return it
+ T result = creator.create();
+ TestUtils.getDefaultGroup(mai.model).addItem(result);
+ return result;
}
}
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/MqttTests.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/MqttTests.java
index a141d720ff794a7833010fe8c673c80d8f151f49..1c30aa8700ed3e2de0cda9fcb67086e83029db45 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/MqttTests.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/MqttTests.java
@@ -3,11 +3,16 @@ package de.tudresden.inf.st.eraser;
import de.tudresden.inf.st.eraser.jastadd.model.*;
import de.tudresden.inf.st.eraser.util.MqttReceiver;
import de.tudresden.inf.st.eraser.util.TestUtils;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
import org.junit.Assert;
import org.junit.Assume;
+import org.junit.ClassRule;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.junit.runners.Parameterized;
+import org.testcontainers.containers.GenericContainer;
+import org.testcontainers.containers.wait.strategy.Wait;
import java.io.IOException;
import java.util.ArrayList;
@@ -35,25 +40,29 @@ public class MqttTests {
private static final double thirdState = 3.0;
private List<String> messages = new ArrayList<>();
+ private static Logger logger = LogManager.getLogger(MqttTests.class);
+ @ClassRule
+ public static GenericContainer mqttBroker = new GenericContainer<>("eclipse-mosquitto:1.5")
+ .withExposedPorts(1883);
@Test
public void resolve1() {
- RootItemAndTwoTopics rootAB = createAB();
- MqttRoot sut = rootAB.model.getMqttRoot();
+ ModelItemAndTwoTopics modelAB = createAB();
+ MqttRoot sut = modelAB.model.getRoot().getMqttRoot();
// incoming mqtt topic might be "inc/a/" or "inc/a/b"
Assert.assertTrue(sut.resolveTopic("inc/a").isPresent());
- Assert.assertEquals("Could not resolve a.", rootAB.firstTopic, sut.resolveTopic("inc/a").get());
+ Assert.assertEquals("Could not resolve a.", modelAB.firstTopic, sut.resolveTopic("inc/a").get());
Assert.assertTrue(sut.resolveTopic("inc/a/b").isPresent());
- Assert.assertEquals("Could not resolve a/b.", rootAB.secondTopic, sut.resolveTopic("inc/a/b").get());
+ Assert.assertEquals("Could not resolve a/b.", modelAB.secondTopic, sut.resolveTopic("inc/a/b").get());
}
@Test
public void brokerConnected() throws Exception {
- RootItemAndTwoTopics rootAB = createAB();
- MqttRoot sut = rootAB.model.getMqttRoot();
+ ModelItemAndTwoTopics modelAB = createAB();
+ MqttRoot sut = modelAB.model.getRoot().getMqttRoot();
// MqttRoot mqttRoot = new MqttRoot();
// mqttRoot.setHostByName("localhost");
// MQTTSender sender = new MQTTSenderImpl().setHost(mqttRoot.getHost());
@@ -67,11 +76,11 @@ public class MqttTests {
public void itemUpdateSend1() throws Exception {
String expectedTopic = outgoingPrefix + "/" + firstPart + "/" + secondPart;
- RootItemAndTwoTopics rootAB = createAB();
- assumeSenderConnected(rootAB.model);
+ ModelItemAndTwoTopics modelAB = createAB();
+ assertSenderConnected(modelAB);
- NumberItem sut = rootAB.item;
- sut.setTopic(rootAB.secondTopic);
+ NumberItem sut = modelAB.item;
+ sut.setTopic(modelAB.secondTopic);
createMqttReceiver(expectedTopic);
@@ -88,29 +97,20 @@ public class MqttTests {
Assert.assertEquals(Double.toString(secondState), messages.get(1));
}
- private void assumeSenderConnected(Root model) {
- Assume.assumeTrue("Broker is not connected", model.getMqttRoot().getMqttSender().isConnected());
- }
-
@Test
public void itemUpdateSend2() throws Exception {
String expectedTopic1 = outgoingPrefix + "/" + firstPart + "/" + secondPart;
String expectedTopic2 = outgoingPrefix + "/" + alternativeFirstPart + "/" + secondPart;
- RootItemAndTwoTopics rootAB = createAB();
- assumeSenderConnected(rootAB.model);
+ ModelItemAndTwoTopics modelAB = createAB();
+ assertSenderConnected(modelAB);
- NumberItem item1 = rootAB.item;
- item1.setTopic(rootAB.secondTopic);
+ NumberItem item1 = modelAB.item;
+ item1.setTopic(modelAB.secondTopic);
- MqttTopic alternative = new MqttTopic();
- alternative.setPart(alternativeFirstPart);
- MqttTopic alternativeB = new MqttTopic();
- alternativeB.setPart(secondPart);
- alternative.addSubTopic(alternativeB);
- rootAB.model.getMqttRoot().addTopic(alternative);
+ MqttTopic alternativeB = createAndAddMqttTopic(modelAB.model.getRoot().getMqttRoot(),alternativeFirstPart + "/" + secondPart);
- NumberItem item2 = TestUtils.addItemTo(rootAB.model, 0);
+ NumberItem item2 = TestUtils.addItemTo(modelAB.model, 0);
item2.setTopic(alternativeB);
createMqttReceiver(expectedTopic1, expectedTopic2);
@@ -136,6 +136,19 @@ public class MqttTests {
Assert.assertThat(messages, hasItem(Double.toString(thirdState)));
}
+ private void assertSenderConnected(ModelItemAndTwoTopics modelAB) {
+ MqttRoot mqttRoot = modelAB.model.getRoot().getMqttRoot();
+ mqttBroker.waitingFor(Wait.forHealthcheck());
+ if (!mqttRoot.getMqttSender().isConnected()) {
+ try {
+ Thread.sleep(1000);
+ } catch (InterruptedException e) {
+ logger.catching(e);
+ }
+ }
+ Assert.assertTrue("Broker is not connected", mqttRoot.getMqttSender().isConnected());
+ }
+
private void createMqttReceiver(String... expectedTopics) throws IOException {
if (useStub) {
// do not need receiver, as messages are directly written by MqttSenderStub and callback
@@ -143,7 +156,8 @@ public class MqttTests {
}
MqttReceiver receiver = new MqttReceiver();
List<String> expectedTopicList = Arrays.asList(expectedTopics);
- receiver.setHost("localhost");
+// receiver.setHost("localhost", 1883);
+ receiver.setHost(mqttBroker.getContainerIpAddress(), mqttBroker.getFirstMappedPort());
receiver.setTopicsForSubscription(expectedTopics);
receiver.setOnMessage((topic, message) -> {
Assert.assertThat(expectedTopicList, hasItem(topic));
@@ -153,9 +167,9 @@ public class MqttTests {
receiver.waitUntilReady(2, TimeUnit.SECONDS);
}
- private RootItemAndTwoTopics createAB() {
+ private ModelItemAndTwoTopics createAB() {
TestUtils.ModelAndItem mai = TestUtils.createModelAndItem(0);
- Root model = mai.model;
+ OpenHAB2Model model = mai.model;
MqttRoot mqttRoot = new MqttRoot();
mqttRoot.setIncomingPrefix("inc");
mqttRoot.setOutgoingPrefix(outgoingPrefix);
@@ -164,26 +178,23 @@ public class MqttTests {
// now a SenderStub is being used
((MQTTSenderStub) mqttRoot.getMqttSender()).setCallback(((topic, message, qos) -> messages.add(message)));
} else {
- mqttRoot.setHostByName("localhost");
+// mqttRoot.setHostByName("localhost");
+ mqttRoot.setHost(ExternalHost.of(mqttBroker.getContainerIpAddress(), mqttBroker.getFirstMappedPort()));
}
- MqttTopic a = new MqttTopic();
- a.setPart(firstPart);
- MqttTopic ab = new MqttTopic();
- ab.setPart(secondPart);
- a.addSubTopic(ab);
- mqttRoot.addTopic(a);
+ MqttTopic a = createAndAddMqttTopic(mqttRoot, firstPart);
+ MqttTopic ab = createAndAddMqttTopic(mqttRoot, firstPart + "/" + secondPart);
mqttRoot.ensureCorrectPrefixes();
- model.setMqttRoot(mqttRoot);
- return RootItemAndTwoTopics.of(model, mai.item, a, ab);
+ model.getRoot().setMqttRoot(mqttRoot);
+ return ModelItemAndTwoTopics.of(model, mai.item, a, ab);
}
- static class RootItemAndTwoTopics {
- Root model;
+ static class ModelItemAndTwoTopics {
+ OpenHAB2Model model;
NumberItem item;
MqttTopic firstTopic;
MqttTopic secondTopic;
- static RootItemAndTwoTopics of(Root model, NumberItem item, MqttTopic firstTopic, MqttTopic secondTopic) {
- RootItemAndTwoTopics result = new RootItemAndTwoTopics();
+ static ModelItemAndTwoTopics of(OpenHAB2Model model, NumberItem item, MqttTopic firstTopic, MqttTopic secondTopic) {
+ ModelItemAndTwoTopics result = new ModelItemAndTwoTopics();
result.model = model;
result.item = item;
result.firstTopic = firstTopic;
@@ -192,6 +203,13 @@ public class MqttTests {
}
}
+ private MqttTopic createAndAddMqttTopic(MqttRoot mqttRoot, String suffix) {
+ MqttTopic result = new MqttTopic();
+ result.setTopicString(suffix);
+ mqttRoot.addTopic(result);
+ return result;
+ }
+
private <T> void assertTimeoutEquals(long seconds, T expected, Supplier<T> actualProvider) throws InterruptedException {
if (expected == actualProvider.get()) {
// already matched right now. return immediately.
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/NeuralNetworkTest.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/NeuralNetworkTest.java
index 5d658500c5abb55e18b0ba6c5e5895e4341cdb01..0eb593fd0fc6c3cb3401f315afe33d550e4b3658 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/NeuralNetworkTest.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/NeuralNetworkTest.java
@@ -24,7 +24,7 @@ public class NeuralNetworkTest {
*/
NeuralNetworkRoot neuralNetworkRoot = NeuralNetworkRoot.createEmpty();
- mai.model.getMachineLearningRoot().setPreferenceLearning(neuralNetworkRoot);
+ mai.model.getRoot().getMachineLearningRoot().setPreferenceLearning(neuralNetworkRoot);
InputNeuron inputNeuron = new InputNeuron();
inputNeuron.setItem(mai.item);
HiddenNeuron hiddenNeuron = new HiddenNeuron();
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/OpenHabImporterTest.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/OpenHabImporterTest.java
index 37766dac143bd79c0a94e83873fd29393078b564..8c109638fea74d074cfc72168303d68a5d2e69a7 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/OpenHabImporterTest.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/OpenHabImporterTest.java
@@ -1,5 +1,6 @@
package de.tudresden.inf.st.eraser;
+import de.tudresden.inf.st.eraser.jastadd.model.OpenHAB2Model;
import de.tudresden.inf.st.eraser.jastadd.model.Root;
import de.tudresden.inf.st.eraser.jastadd_test.core.*;
import de.tudresden.inf.st.eraser.openhab2.OpenHab2Importer;
@@ -70,7 +71,7 @@ public class OpenHabImporterTest {
// call the modified importer, with the static host name, and an arbitrary chosen port
// port will not be used during the test
- Root model = importer.importFrom(HOST, 80);
+ OpenHAB2Model model = importer.importFrom(HOST, 80);
if (model == null) {
if (expected == Result.PARSE_FAILED) return;
@@ -88,7 +89,7 @@ public class OpenHabImporterTest {
}
}
- printAndCompare(config, model);
+ printAndCompare(config, model.getRoot());
}
}
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ParserTests.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ParserTests.java
deleted file mode 100644
index 02a6d30a19592b87a683cd9f0e1e63ae5bf6e3f5..0000000000000000000000000000000000000000
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/ParserTests.java
+++ /dev/null
@@ -1,105 +0,0 @@
-package de.tudresden.inf.st.eraser;
-
-import de.tudresden.inf.st.eraser.util.TestUtils;
-import de.tudresden.inf.st.eraser.util.TestUtils.ModelAndItem;
-import de.tudresden.inf.st.eraser.jastadd.model.MqttRoot;
-import de.tudresden.inf.st.eraser.jastadd.model.NumberItem;
-import de.tudresden.inf.st.eraser.jastadd.model.Root;
-import de.tudresden.inf.st.eraser.util.ParserUtils;
-import org.junit.Assert;
-import org.junit.Test;
-
-/**
- * Testing helper methods using in parsing.
- *
- * @author rschoene - Initial contribution
- */
-public class ParserTests {
-
- @Test
- public void testCreateMqttTopicSimple() {
- ModelAndItem mai = TestUtils.createModelAndItem(1);
-
- Root model = mai.model;
- model.setMqttRoot(new MqttRoot());
- NumberItem item = mai.item;
-
- Assert.assertNull(item.getTopic());
-
- String[] parts = { "one", "two", "three" };
- String topicName = String.join("/", parts);
-
- ParserUtils.createMqttTopic(item, topicName, model);
-
- Assert.assertNotNull(item.getTopic());
-
- MqttRoot mqttRoot = model.getMqttRoot();
- Assert.assertEquals("There must be only one topic", 1, mqttRoot.getNumTopic());
- Assert.assertEquals("First part is wrong",
- parts[0], mqttRoot.getTopic(0).getPart());
- Assert.assertEquals("First topic has wrong number of sub-topics",
- 1, mqttRoot.getTopic(0).getNumSubTopic());
- Assert.assertEquals("Second part is wrong",
- parts[1], mqttRoot.getTopic(0).getSubTopic(0).getPart());
- Assert.assertEquals("Second topic has wrong number of sub-topics",
- 1, mqttRoot.getTopic(0).getSubTopic(0).getNumSubTopic());
- Assert.assertEquals("Third part is wrong",
- parts[2], mqttRoot.getTopic(0).getSubTopic(0).getSubTopic(0).getPart());
- Assert.assertEquals("Third part is wrong object",
- item.getTopic(), mqttRoot.getTopic(0).getSubTopic(0).getSubTopic(0));
-
- Assert.assertEquals("Name does not match", topicName, item.getTopic().allParts());
- }
-
-
- @Test
- public void testCreateMqttTopicTwoInterleavedTopics() {
- ModelAndItem mai = TestUtils.createModelAndItem(1);
-
- Root model = mai.model;
- model.setMqttRoot(new MqttRoot());
- NumberItem item1 = mai.item;
- NumberItem item2 = TestUtils.addItemTo(model, 3);
-
- Assert.assertNull(item1.getTopic());
- Assert.assertNull(item2.getTopic());
-
- String[] parts = { "one", "two", "three" };
- String otherPart2 = "222";
- String topicName1 = String.join("/", parts);
- String topicName2 = String.join("/", parts[0], otherPart2, parts[2]);
-
- ParserUtils.createMqttTopic(item1, topicName1, model);
- ParserUtils.createMqttTopic(item2, topicName2, model);
-
- Assert.assertNotNull(item1.getTopic());
- Assert.assertNotNull(item2.getTopic());
-
- MqttRoot mqttRoot = model.getMqttRoot();
- Assert.assertEquals("There must be only one topic", 1, mqttRoot.getNumTopic());
- Assert.assertEquals("First part is wrong",
- parts[0], mqttRoot.getTopic(0).getPart());
- Assert.assertEquals("First topic has wrong number of sub-topics",
- 2, mqttRoot.getTopic(0).getNumSubTopic());
- Assert.assertEquals("Second part for first item is wrong",
- parts[1], mqttRoot.getTopic(0).getSubTopic(0).getPart());
- Assert.assertEquals("Second part for first item is wrong",
- otherPart2, mqttRoot.getTopic(0).getSubTopic(1).getPart());
- Assert.assertEquals("Second topic for first item has wrong number of sub-topics",
- 1, mqttRoot.getTopic(0).getSubTopic(0).getNumSubTopic());
- Assert.assertEquals("Third part for first item is wrong",
- parts[2], mqttRoot.getTopic(0).getSubTopic(0).getSubTopic(0).getPart());
- Assert.assertEquals("Second topic for second item has wrong number of sub-topics",
- 1, mqttRoot.getTopic(0).getSubTopic(1).getNumSubTopic());
- Assert.assertEquals("Third part for second item is wrong",
- parts[2], mqttRoot.getTopic(0).getSubTopic(1).getSubTopic(0).getPart());
- Assert.assertEquals("Third part for first item is wrong object",
- item1.getTopic(), mqttRoot.getTopic(0).getSubTopic(0).getSubTopic(0));
- Assert.assertEquals("Third part for second item is wrong object",
- item2.getTopic(), mqttRoot.getTopic(0).getSubTopic(1).getSubTopic(0));
-
- Assert.assertEquals("Name for first item does not match", topicName1, item1.getTopic().allParts());
- Assert.assertEquals("Name for second item does not match", topicName2, item2.getTopic().allParts());
- }
-
-}
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/RulesTest.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/RulesTest.java
index 1ec9aaef9f40bedd5744c344c55ac7b6338f3da1..2c318278f6b108c4a1c36fae567fe48d832a0734 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/RulesTest.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/RulesTest.java
@@ -50,13 +50,13 @@ public class RulesTest {
@Test
public void testUnconditionalLambdaAction() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
Rule rule = new Rule();
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Counter not initialized correctly"), 0, counter.get(item));
@@ -74,11 +74,11 @@ public class RulesTest {
@Test
public void testIdempotentActivation() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(4);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
Rule rule = new Rule();
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
rule.activateFor(item);
@@ -94,18 +94,18 @@ public class RulesTest {
@Test
public void testTwoRulesForOneItem() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(4);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
Counters counter1 = new Counters();
Rule ruleA = new Rule();
ruleA.addAction(new LambdaAction(counter1));
- model.addRule(ruleA);
+ root.addRule(ruleA);
Rule ruleB = new Rule();
Counters counter2 = new Counters();
ruleB.addAction(new LambdaAction(counter2));
- model.addRule(ruleB);
+ root.addRule(ruleB);
ruleA.activateFor(item);
ruleB.activateFor(item);
@@ -129,14 +129,14 @@ public class RulesTest {
@Test
public void testOneRuleForTwoItems() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(4);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item1 = modelAndItem.item;
- NumberItem item2 = TestUtils.addItemTo(model, 4, useUpdatingItem);
+ NumberItem item2 = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
Rule rule = new Rule();
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item1);
rule.activateFor(item2);
@@ -188,13 +188,13 @@ public class RulesTest {
@Test
public void testRemoveActivation() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(4);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
Rule rule = new Rule();
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
@@ -212,7 +212,7 @@ public class RulesTest {
@Test
public void testNumberConditions() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(2);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
Rule rule = new Rule();
@@ -222,7 +222,7 @@ public class RulesTest {
rule.addCondition(new ItemStateCheckCondition(check2));
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Counter not initialized correctly"), 0, counter.get(item));
@@ -246,7 +246,7 @@ public class RulesTest {
@Test
public void testTwoActions() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(2);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
Rule rule = new Rule();
@@ -254,7 +254,7 @@ public class RulesTest {
rule.addAction(new LambdaAction(counter1));
Counters counter2 = new Counters();
rule.addAction(new LambdaAction(counter2));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("First counter not initialized correctly"), 0, counter1.get(item));
@@ -272,9 +272,9 @@ public class RulesTest {
@Test
public void testChainedRules() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(2);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- NumberItem item2 = TestUtils.addItemTo(model, 4, useUpdatingItem);
+ NumberItem item2 = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
Rule ruleA = new Rule();
Counters counter1 = new Counters();
@@ -286,8 +286,8 @@ public class RulesTest {
ruleA.addAction(new TriggerRuleAction(ruleB));
- model.addRule(ruleA);
- model.addRule(ruleB);
+ root.addRule(ruleA);
+ root.addRule(ruleB);
ruleA.activateFor(item);
ruleB.activateFor(item2);
@@ -315,15 +315,15 @@ public class RulesTest {
@Test
public void testSetStateFromConstantStringAction() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- NumberItem item2 = TestUtils.addItemTo(model, 4, useUpdatingItem);
+ NumberItem item2 = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
Rule rule = new Rule();
rule.addAction(new SetStateFromConstantStringAction(item2, "5"));
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Affected item not initialized correctly"),
@@ -347,15 +347,15 @@ public class RulesTest {
public void testSetStateFromLambdaAction() {
ValuedStateProvider provider = new ValuedStateProvider();
TestUtils.ModelAndItem modelAndItem = createModelAndItem(0);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- NumberItem item2 = TestUtils.addItemTo(model, 3, useUpdatingItem);
+ NumberItem item2 = TestUtils.addItemTo(root.getOpenHAB2Model(), 3, useUpdatingItem);
Rule rule = new Rule();
rule.addAction(new SetStateFromLambdaAction(item2, provider));
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Affected item not initialized correctly"),
@@ -389,15 +389,15 @@ public class RulesTest {
@Test
public void testSetStateFromTriggeringItemAction() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- StringItem item2 = addStringItem(model, "0");
+ StringItem item2 = addStringItem(root.getOpenHAB2Model(), "0");
Rule rule = new Rule();
Counters counter = new Counters();
rule.addAction(new SetStateFromTriggeringItemAction(item2));
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Counter not initialized correctly"), 0, counter.get(item));
@@ -419,10 +419,10 @@ public class RulesTest {
@Test
public void testSetStateFromItemsAction() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- NumberItem item2 = TestUtils.addItemTo(model, 4, useUpdatingItem);
- StringItem affectedItem = addStringItem(model, "1");
+ NumberItem item2 = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
+ StringItem affectedItem = addStringItem(root.getOpenHAB2Model(), "1");
Rule rule = new Rule();
SetStateFromItemsAction action = new SetStateFromItemsAction(items ->
@@ -435,7 +435,7 @@ public class RulesTest {
rule.addAction(action);
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Counter not initialized correctly"), 0, counter.get(item));
@@ -467,7 +467,7 @@ public class RulesTest {
"12", affectedItem.getState());
// add new item to sum
- NumberItem item3 = TestUtils.addItemTo(model, -4, useUpdatingItem);
+ NumberItem item3 = TestUtils.addItemTo(root.getOpenHAB2Model(), -4, useUpdatingItem);
action.addSourceItem(item3);
// still 7 + 5 = 12, as rule should not trigger
@@ -486,15 +486,15 @@ public class RulesTest {
@Test
public void testAddDoubleToStateAction() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- NumberItem affectedItem = TestUtils.addItemTo(model, 4, useUpdatingItem);
+ NumberItem affectedItem = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
Rule rule = new Rule();
rule.addAction(new AddDoubleToStateAction(affectedItem, 2));
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Counter not initialized correctly"), 0, counter.get(item));
@@ -523,15 +523,15 @@ public class RulesTest {
@Test
public void testMultiplyDoubleToStateAction() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item = modelAndItem.item;
- NumberItem affectedItem = TestUtils.addItemTo(model, 4, useUpdatingItem);
+ NumberItem affectedItem = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
Rule rule = new Rule();
rule.addAction(new MultiplyDoubleToStateAction(affectedItem, 2));
Counters counter = new Counters();
rule.addAction(new LambdaAction(counter));
- model.addRule(rule);
+ root.addRule(rule);
rule.activateFor(item);
Assert.assertEquals(m("Counter not initialized correctly"), 0, counter.get(item));
@@ -560,10 +560,10 @@ public class RulesTest {
@Test
public void testChainAddMultiplyActions() {
TestUtils.ModelAndItem modelAndItem = createModelAndItem(3);
- Root model = modelAndItem.model;
+ Root root = modelAndItem.model.getRoot();
NumberItem item1 = modelAndItem.item;
- NumberItem item2 = TestUtils.addItemTo(model, 4, useUpdatingItem);
- NumberItem affectedItem = TestUtils.addItemTo(model, 5, useUpdatingItem);
+ NumberItem item2 = TestUtils.addItemTo(root.getOpenHAB2Model(), 4, useUpdatingItem);
+ NumberItem affectedItem = TestUtils.addItemTo(root.getOpenHAB2Model(), 5, useUpdatingItem);
Rule ruleA = new Rule();
ruleA.addAction(new AddDoubleToStateAction(affectedItem, 2));
@@ -577,8 +577,8 @@ public class RulesTest {
ruleA.addAction(new TriggerRuleAction(ruleB));
- model.addRule(ruleA);
- model.addRule(ruleB);
+ root.addRule(ruleA);
+ root.addRule(ruleB);
ruleA.activateFor(item1);
ruleB.activateFor(item2);
@@ -653,7 +653,7 @@ public class RulesTest {
return message + " (Using " + name + ")";
}
- private StringItem addStringItem(Root model, String initialValue) {
+ private StringItem addStringItem(OpenHAB2Model model, String initialValue) {
StringItem item = new StringItem();
Group group = TestUtils.getDefaultGroup(model);
item.setID("item" + group.getNumItem());
diff --git a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/jastadd_test/core/TestRunner.java b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/jastadd_test/core/TestRunner.java
index 984fb21d95d17d02b3ef7c07d064c410e300afb2..6978df5cafeee586a7025fc1855d88b1b240a49b 100644
--- a/eraser-base/src/test/java/de/tudresden/inf/st/eraser/jastadd_test/core/TestRunner.java
+++ b/eraser-base/src/test/java/de/tudresden/inf/st/eraser/jastadd_test/core/TestRunner.java
@@ -30,6 +30,7 @@
package de.tudresden.inf.st.eraser.jastadd_test.core;
import beaver.Parser;
+import de.tudresden.inf.st.eraser.jastadd.model.OpenHAB2Model;
import de.tudresden.inf.st.eraser.jastadd.model.Root;
import de.tudresden.inf.st.eraser.util.ParserUtils;
@@ -67,9 +68,9 @@ public class TestRunner {
Result expected = config.expected;
// Parse input model
- Root model;
+ Root root;
try {
- model = parseModel(config);
+ root = parseModel(config);
} catch (Parser.Exception e) {
if (expected == Result.PARSE_FAILED) return;
// otherwise rethrow error
@@ -80,7 +81,7 @@ public class TestRunner {
fail("Parsing the model should have failed, but was successful!");
}
- if (model == null) {
+ if (root == null) {
fail("Parsing the model should have passed, but model was null!");
}
@@ -91,15 +92,15 @@ public class TestRunner {
return;
}
- printAndCompare(config, model);
+ printAndCompare(config, root);
}
- protected static void printAndCompare(TestConfiguration config, Root model) {
+ protected static void printAndCompare(TestConfiguration config, Root root) {
Result expected = config.expected;
// Print model.
String output;
try {
- output = printModel(model, config);
+ output = printModel(root, config);
} catch (Exception e) {
if (expected == Result.PRINT_FAILED) return;
// otherwise rethrow error
@@ -149,8 +150,8 @@ public class TestRunner {
return new File(testDir, "jastadd.err.expected");
}
- private static String printModel(Root model, TestConfiguration config) {
- return model.prettyPrint();
+ private static String printModel(Root root, TestConfiguration config) {
+ return root.prettyPrint();
}
/**
diff --git a/eraser-base/src/test/resources/log4j2-test.xml b/eraser-base/src/test/resources/log4j2-test.xml
index 5c534092d64e9c1834c2ba20208c057e2b56be16..b20ed4ecc82af01ce5278a8d9f0c1aa77a32f00b 100644
--- a/eraser-base/src/test/resources/log4j2-test.xml
+++ b/eraser-base/src/test/resources/log4j2-test.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser-test.log"
+ filePattern="logs/eraser-test-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
@@ -21,5 +21,14 @@
<Logger name="de.tudresden.inf.st.eraser.openhab2.mqtt" level="DEBUG" additivity="false">
<Appender-ref ref="Console"/>
</Logger>
+ <!-- Testcontainers reduce noise-->
+ <Logger name="org.testcontainers" level="INFO" additivity="false">
+ <Appender-ref ref="Console"/>
+ <AppenderRef ref="RollingFile"/>
+ </Logger>
+ <Logger name="com.github.dockerjava.core" level="INFO" additivity="false">
+ <Appender-ref ref="Console"/>
+ <AppenderRef ref="RollingFile"/>
+ </Logger>
</Loggers>
</Configuration>
diff --git a/eraser-base/src/test/resources/openhabtest/oh1/output.eraser b/eraser-base/src/test/resources/openhabtest/oh1/output.eraser
index c422840036be85ad9c3744a6fefc39ded481ee97..1844189cea3d085b031650470be0916f4943b21f 100644
--- a/eraser-base/src/test/resources/openhabtest/oh1/output.eraser
+++ b/eraser-base/src/test/resources/openhabtest/oh1/output.eraser
@@ -18,5 +18,3 @@ Color Item: id="wohnzimmer_item" label="Wohnzimmer" state="0,0,0" category="Ligh
Color Item: id="iris1_item" label="Iris 1" state="226,100,98" category="Lighting" ;
Group: id="all_dimmable_lamps" label="All dimmable lamps" items=["Go1_item"] aggregation="AVG" ;
Group: id="Unknown" items=["Rule_Switch", "Color_Manual_Slider", "watch_acceleration_x", "watch_acceleration_y", "watch_acceleration_z", "watch_rotation_x", "watch_rotation_y", "watch_rotation_z", "phone_rotation_x", "phone_rotation_y", "phone_rotation_z", "samsung_brightness", "skywriter_flick_item", "polar_brightness", "moto_360_brightness", "wohnzimmer_item", "iris1_item"] ;
-Mqtt: host="localhost" ;
-Influx: host="localhost" ;
diff --git a/eraser-base/src/test/resources/openhabtest/oh2/links.json b/eraser-base/src/test/resources/openhabtest/oh2/links.json
index 79e79442806b87513d8581eb877453873069ddbe..f881db063fd53906ab14e3fda79dbf4a5fac0d4b 100644
--- a/eraser-base/src/test/resources/openhabtest/oh2/links.json
+++ b/eraser-base/src/test/resources/openhabtest/oh2/links.json
@@ -142,7 +142,7 @@
{
"channelUID": "openlicht:polar-m600:342dfc32:rotation-y",
"configuration": {},
- "itemName": "watch_acceleration_y"
+ "itemName": "watch_rotation_y"
},
{
"channelUID": "openlicht:polar-m600:342dfc32:rotation-z",
diff --git a/eraser-base/src/test/resources/openhabtest/oh2/output.eraser b/eraser-base/src/test/resources/openhabtest/oh2/output.eraser
index c5e139935809383792596f6183ffe31514c8dbd0..e6354c12fa1e0a71edbe6eb77aafd9420c51069b 100644
--- a/eraser-base/src/test/resources/openhabtest/oh2/output.eraser
+++ b/eraser-base/src/test/resources/openhabtest/oh2/output.eraser
@@ -77,7 +77,7 @@ Channel: id="openlicht:polar-m600:342dfc32:activity" type="openlicht:activity-ty
Channel: id="openlicht:polar-m600:342dfc32:brightness" type="openlicht:brightness-type" links=["polar_brightness"] ;
Channel: id="openlicht:polar-m600:342dfc32:heart-rate" type="openlicht:heart-rate-type" ;
Channel: id="openlicht:polar-m600:342dfc32:rotation-x" type="openlicht:rotation-type" links=["watch_rotation_x"] ;
-Channel: id="openlicht:polar-m600:342dfc32:rotation-y" type="openlicht:rotation-type" links=["watch_acceleration_y"] ;
+Channel: id="openlicht:polar-m600:342dfc32:rotation-y" type="openlicht:rotation-type" links=["watch_rotation_y"] ;
Channel: id="openlicht:polar-m600:342dfc32:rotation-z" type="openlicht:rotation-type" links=["watch_rotation_z"] ;
Channel: id="openlicht:polar-m600:342dfc32:steps" type="openlicht:steps-type" ;
Channel: id="openlicht:samsung-s6:2ca84896:brightness" type="openlicht:brightness-type" links=["samsung_brightness"] ;
@@ -85,5 +85,3 @@ Channel: id="openlicht:samsung-s6:2ca84896:rotation-x" type="openlicht:rotation-
Channel: id="openlicht:samsung-s6:2ca84896:rotation-y" type="openlicht:rotation-type" links=["phone_rotation_y"] ;
Channel: id="openlicht:samsung-s6:2ca84896:rotation-z" type="openlicht:rotation-type" links=["phone_rotation_z"] ;
Channel: id="openlicht:skywriter-hat:e937d4f3:flick" type="openlicht:flick-type" links=["skywriter_flick_item"] ;
-Mqtt: host="localhost" ;
-Influx: host="localhost" ;
diff --git a/eraser-base/src/test/resources/tests/hostNonDefaultPort/Test.properties b/eraser-base/src/test/resources/tests/hostNonDefaultPort/Test.properties
new file mode 100644
index 0000000000000000000000000000000000000000..616a3deddd4decffd5d0e6e3db7bb8ce3873562a
--- /dev/null
+++ b/eraser-base/src/test/resources/tests/hostNonDefaultPort/Test.properties
@@ -0,0 +1 @@
+result=OUTPUT_PASS
diff --git a/eraser-base/src/test/resources/tests/hostNonDefaultPort/description b/eraser-base/src/test/resources/tests/hostNonDefaultPort/description
new file mode 100644
index 0000000000000000000000000000000000000000..bdaa31556a7a02ab764f16f5a5157676ce5126bf
--- /dev/null
+++ b/eraser-base/src/test/resources/tests/hostNonDefaultPort/description
@@ -0,0 +1 @@
+Test, if non-default ports in MQTT and Influx are working.
diff --git a/eraser-base/src/test/resources/tests/hostNonDefaultPort/input.eraser b/eraser-base/src/test/resources/tests/hostNonDefaultPort/input.eraser
new file mode 100644
index 0000000000000000000000000000000000000000..427f6137aa8058df0e264bb6ca8f200eb71dbd7d
--- /dev/null
+++ b/eraser-base/src/test/resources/tests/hostNonDefaultPort/input.eraser
@@ -0,0 +1,2 @@
+Influx: host="www.example.com:1234";
+Mqtt: host="localhost:9876";
diff --git a/eraser-base/src/test/resources/tests/hostNonDefaultPort/output.eraser b/eraser-base/src/test/resources/tests/hostNonDefaultPort/output.eraser
new file mode 100644
index 0000000000000000000000000000000000000000..73d8147fea0252ec1c95364ad6ad5449a829b1e6
--- /dev/null
+++ b/eraser-base/src/test/resources/tests/hostNonDefaultPort/output.eraser
@@ -0,0 +1,2 @@
+Mqtt: host="localhost:9876" ;
+Influx: host="www.example.com:1234" ;
diff --git a/eraser-base/src/test/resources/tests/ppc3/output.eraser b/eraser-base/src/test/resources/tests/ppc3/output.eraser
index e4b9707a84cc17f4901da3a68abf73c27eac58fc..b9a6d2f2a4301a35562946cc67ceca725d35e9e9 100644
--- a/eraser-base/src/test/resources/tests/ppc3/output.eraser
+++ b/eraser-base/src/test/resources/tests/ppc3/output.eraser
@@ -2,7 +2,7 @@ Color Item: id="color1" label="a Color Item" state="1,2,3" topic="item/hsb/color
Contact Item: id="contact1" label="a Contact Item" state="true" topic="item/bool/contact1/state" ;
Image Item: id="image1" label="an Image Item" state="def" topic="item/str/image1/state" ;
Location Item: id="location1" label="a Location Item" state="ghi" topic="item/str/location1/state" ;
-DateTime Item: id="datetime1" label="a DateTime Item" state="1970-01-18T20:43:35.826" topic="item/date/datetime1/state" ;
+DateTime Item: id="datetime1" label="a DateTime Item" state="1970-01-18T20:43:35.826Z" topic="item/date/datetime1/state" ;
Item: id="default1" label="a Default Item" state="pqr" topic="item/str/default1/state" ;
Dimmer Item: id="dimmer1" label="a Dimmer Item" state="123.0" topic="item/double/dimmer1/state" ;
Player Item: id="player1" label="a Player Item" state="jkl" topic="item/str/player1/state" ;
diff --git a/eraser-base/src/test/resources/tests/ppc4/input.eraser b/eraser-base/src/test/resources/tests/ppc4/input.eraser
index f363a8c8ebff9a763dbb34fbca6010bc43588faf..f5c7afff39c0a2d617f293076a86a794fa24263f 100644
--- a/eraser-base/src/test/resources/tests/ppc4/input.eraser
+++ b/eraser-base/src/test/resources/tests/ppc4/input.eraser
@@ -15,6 +15,7 @@ Location Item : id="location1" label="a Location Item" state="ghi" topic="item/s
Number Item : id="number1" label="a Number Item" state="456" topic="item/double/number1/state" controls=["string1"];
Player Item : id="player1" label="a Player Item" state="jkl" topic="item/str/player1/state";
RollerShutter Item : id="rollerShutter1" label="a RollerShutter Item" state="false" topic="item/str/rs1/state";
+Activity Item: id="activity";
String Item : id="string1" label="a String Item" state="mno" topic="item/str/string1/state";
Switch Item : id="switch1" label="a Switch Item" state="true" topic="item/bool/switch1/state" controls=["rollerShutter1"];
Item : id="default1" label="a Default Item" state="pqr" topic="item/str/default1/state";
diff --git a/eraser-base/src/test/resources/tests/ppc4/output.eraser b/eraser-base/src/test/resources/tests/ppc4/output.eraser
index 1231dc15e00cb468e6bb01da988501d1b0f26720..1b881dd0d5d11159a298a1c41b1d04d530353bd8 100644
--- a/eraser-base/src/test/resources/tests/ppc4/output.eraser
+++ b/eraser-base/src/test/resources/tests/ppc4/output.eraser
@@ -2,18 +2,19 @@ Color Item: id="color1" label="a Color Item" state="1,2,3" topic="item/hsb/color
Contact Item: id="contact1" label="a Contact Item" state="true" topic="item/bool/contact1/state" ;
Image Item: id="image1" label="an Image Item" state="def" topic="item/str/image1/state" ;
Location Item: id="location1" label="a Location Item" state="ghi" topic="item/str/location1/state" ;
-DateTime Item: id="datetime1" label="a DateTime Item" state="1970-01-18T20:43:35.826" topic="item/date/datetime1/state" ;
+DateTime Item: id="datetime1" label="a DateTime Item" state="1970-01-18T20:43:35.826Z" topic="item/date/datetime1/state" ;
Item: id="default1" label="a Default Item" state="pqr" topic="item/str/default1/state" ;
Dimmer Item: id="dimmer1" label="a Dimmer Item" state="123.0" topic="item/double/dimmer1/state" controls=["color1", "datetime1"] ;
Player Item: id="player1" label="a Player Item" state="jkl" topic="item/str/player1/state" ;
Number Item: id="number1" label="a Number Item" state="456.0" topic="item/double/number1/state" controls=["string1"] ;
RollerShutter Item: id="rollerShutter1" label="a RollerShutter Item" state="false" topic="item/str/rs1/state" ;
+Activity Item: id="activity" ;
String Item: id="string1" label="a String Item" state="mno" topic="item/str/string1/state" ;
Switch Item: id="switch1" label="a Switch Item" state="true" topic="item/bool/switch1/state" controls=["rollerShutter1"] ;
Group: id="my-first-group" items=["color1", "contact1", "image1", "location1"] aggregation="AND" ("ON", "OFF") ;
Group: id="my-second-group" items=["datetime1", "default1"] ;
Group: id="my-third-group" items=["dimmer1", "player1"] ;
Group: id="my-empty-group" ;
-Group: id="Unknown" items=["number1", "rollerShutter1", "string1", "switch1"] ;
+Group: id="Unknown" items=["number1", "rollerShutter1", "activity", "string1", "switch1"] ;
Mqtt: incoming="ppc3/" outgoing="oh2/in/" host="localhost" ;
Influx: host="localhost" ;
diff --git a/eraser-base/src/test/resources/tests/ppc5/description b/eraser-base/src/test/resources/tests/ppc5/description
index 8db9b9bceee597ada76ef353e2e683003efa6e8e..ff98c287292d9b2a62174084a242cf6e4d25c012 100644
--- a/eraser-base/src/test/resources/tests/ppc5/description
+++ b/eraser-base/src/test/resources/tests/ppc5/description
@@ -1 +1,2 @@
Complete feature-test, i.e., minimal and maximal many members set for each parseable non-terminal.
+Also test, if multi-line statements work.
diff --git a/eraser-base/src/test/resources/tests/ppc5/input.eraser b/eraser-base/src/test/resources/tests/ppc5/input.eraser
index 6cf47838d171c8c07e3919b42c05bc9ec8e80af6..21cc14bc796965aae71d2bca119f60b0cdf640c5 100644
--- a/eraser-base/src/test/resources/tests/ppc5/input.eraser
+++ b/eraser-base/src/test/resources/tests/ppc5/input.eraser
@@ -10,11 +10,15 @@ Group: id="min-group" ;
Group: items=["min-item", "max-item"] id="max-group" groups=["min-group"] aggregation="AND" ("one", "two") ;
Number Item: id="min-item" ; // state will be set to default value
-Switch Item: topic="items/max" controls=["min-item"] id="max-item" state="true" label="Item with all members set" category="not used" metaData={"one":"true", "zero":"false"} ;
+Switch Item: topic="items/max"
+ controls=["min-item"] id="max-item" state="true" label="Item with all members set" category="not used"
+ metaData={"one":"true", "zero":"false"} ;
// Parameters will get sorted alphabetically in output
Parameter: id="min-parameter" ;
-Parameter: label="Max Parameter" required id="max-parameter" type="Decimal" description="Parameter with all members set" default="should be a number" ;
+Parameter
+:
+label="Max Parameter" required id="max-parameter" type="Decimal" description="Parameter with all members set" default="should be a number" ;
ThingType: id="min-thing-type" ;
ThingType: id="max-thing-type" label="Max Thing Type" description="Thing type with all members set" parameters=["min-parameter", "max-parameter"] channelTypes=["min-channel-type", "max-channel-type-1", "max-channel-type-2"] ;
@@ -22,5 +26,10 @@ ThingType: id="max-thing-type" label="Max Thing Type" description="Thing type wi
Thing: type="min-thing-type" id="min-thing" ; // "type" must be set
Thing: id="max-thing" label="Max Thing" type="max-thing-type" channels=["min-channel", "max-channel"] ;
-Influx: ; // minimal Influx, most probably will fail?
-Mqtt: ; // minimal MQTT, most probably will fail?
+Influx: ; // minimal Influx, most probably will fail in an actual system
+Mqtt: ; // minimal MQTT, most probably will fail in an actual system
+
+ML: activities = {
+ 0 : "an interesting activity",
+ 3: "rather boring activity"
+} ;
diff --git a/eraser-base/src/test/resources/tests/ppc5/output.eraser b/eraser-base/src/test/resources/tests/ppc5/output.eraser
index 1df79c3d8afdc7181f6334d546052122c949fe49..22f0869e0f35ece07c2aaf9b6dedbf6f11c4ae3b 100644
--- a/eraser-base/src/test/resources/tests/ppc5/output.eraser
+++ b/eraser-base/src/test/resources/tests/ppc5/output.eraser
@@ -13,5 +13,4 @@ Parameter: id="max-parameter" label="Max Parameter" description="Parameter with
Parameter: id="min-parameter" ;
Channel: id="max-channel" type="max-channel-type-1" links=["min-item", "max-item"] ;
Channel: id="min-channel" type="min-channel-type" ;
-Mqtt: ;
-Influx: ;
+ML: activities={0:"an interesting activity", 3:"rather boring activity"} ;
diff --git a/eraser.rest/build.gradle b/eraser.rest/build.gradle
index 0f7c52ef57d6d2c0100b9bb34e0473c5f4a05e6b..27a715637cd813a03182c27d332abedab4a02af0 100644
--- a/eraser.rest/build.gradle
+++ b/eraser.rest/build.gradle
@@ -23,15 +23,10 @@ sourceCompatibility = 1.8
dependencies {
compile project(':eraser-base')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
compile 'org.springframework.boot:spring-boot-starter-web'
- compile 'io.springfox:springfox-swagger2:2.9.2'
- compile 'io.springfox:springfox-swagger-ui:2.9.2'
+ compile group: 'io.springfox', name: 'springfox-swagger2', version: '2.9.2'
+ compile group: 'io.springfox', name: 'springfox-swagger-ui', version: '2.9.2'
testCompile 'org.springframework.boot:spring-boot-starter-test'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
sourceSets {
diff --git a/eraser.rest/src/main/resources/log4j2.xml b/eraser.rest/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/eraser.rest/src/main/resources/log4j2.xml
+++ b/eraser.rest/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/eraser.spark/build.gradle b/eraser.spark/build.gradle
index c5bdd901ca07fd6e2483c795e947a771488f11e2..fc14267292c11e5920e2bc3b7609a45a98d6ec6c 100644
--- a/eraser.spark/build.gradle
+++ b/eraser.spark/build.gradle
@@ -1,7 +1,7 @@
plugins {
id 'java'
id 'application'
- id 'io.franzbecker.gradle-lombok' version '1.14'
+ id 'io.franzbecker.gradle-lombok' version '3.0.0'
}
repositories {
@@ -12,13 +12,8 @@ sourceCompatibility = 1.8
dependencies {
compile project(':eraser-base')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- compile 'org.apache.logging.log4j:log4j-slf4j-impl:2.11.1'
- compile 'com.sparkjava:spark-core:2.8.0'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
+ compile group: 'org.apache.logging.log4j', name: 'log4j-slf4j-impl', version: '2.11.2'
+ compile group: 'com.sparkjava', name: 'spark-core', version: '2.9.0'
}
run {
diff --git a/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/Application.java b/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/Application.java
index 2602ca703f7cab2ba7fcf8ffc03158d6b65f591f..ae15f566876bb233706d34a9b563fa85af195244 100644
--- a/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/Application.java
+++ b/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/Application.java
@@ -9,7 +9,6 @@ import spark.Request;
import spark.Response;
import spark.Spark;
-import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
@@ -26,12 +25,12 @@ import java.util.stream.Collectors;
public class Application {
private static final Logger logger = LogManager.getLogger(Application.class);
- private final Root model;
+ private final Root root;
private final Lock lock;
private final Condition quitCondition;
- private Application(Root model, Lock lock, Condition quitCondition) {
- this.model = model;
+ private Application(Root root, Lock lock, Condition quitCondition) {
+ this.root = root;
this.lock = lock;
this.quitCondition = quitCondition;
}
@@ -43,19 +42,19 @@ public class Application {
Spark.path("/activity", () -> {
Spark.get("",
- (request, response) -> wrapActivityList(model.getMachineLearningRoot().getActivityList()),
+ (request, response) -> wrapActivityList(root.getMachineLearningRoot().getActivityList()),
mapper::writeValueAsString);
Spark.get("/current",
- (request, response) -> JavaUtils.ifPresentOrElseReturn(model.currentActivity(),
+ (request, response) -> JavaUtils.ifPresentOrElseReturn(root.currentActivity(),
this::wrapActivity,
() -> makeError(response, 204, "No activity recognized.")),
mapper::writeValueAsString);
Spark.put("/current", (request, response) -> {
logger.info("request body: '{}', params: '{}', length={}", request.body(), request.params(), request.contentLength());
- if (!model.getMachineLearningRoot().hasActivityRecognition()) {
+ if (!root.getMachineLearningRoot().hasActivityRecognition()) {
return makeError(response, 404, "No activity recognition model found");
}
- MachineLearningModel activityRecognition = model.getMachineLearningRoot().getActivityRecognition();
+ MachineLearningModel activityRecognition = root.getMachineLearningRoot().getActivityRecognition();
if (activityRecognition.canSetActivity()) {
activityRecognition.setActivity(Integer.valueOf(request.body()));
return "OK";
@@ -65,7 +64,7 @@ public class Application {
});
Spark.get("/:identifier",
(request, response) ->
- JavaUtils.ifPresentOrElseReturn(model.resolveActivity(paramAsInt(request, "identifier")),
+ JavaUtils.ifPresentOrElseReturn(root.resolveActivity(paramAsInt(request, "identifier")),
this::wrapActivity,
() -> makeError(response, 404, "No activity for identifier " + request.params("identifier"))),
mapper::writeValueAsString);
@@ -73,11 +72,11 @@ public class Application {
Spark.path("/events", () -> {
Spark.get("",
- (request, response) -> wrapChangeEventList(model.getMachineLearningRoot().getChangeEventList()),
+ (request, response) -> wrapChangeEventList(root.getMachineLearningRoot().getChangeEventList()),
mapper::writeValueAsString);
Spark.get("/:identifier",
(request, response) ->
- JavaUtils.ifPresentOrElseReturn(model.resolveChangeEvent(paramAsInt(request, "identifier")),
+ JavaUtils.ifPresentOrElseReturn(root.resolveChangeEvent(paramAsInt(request, "identifier")),
this::wrapChangeEvent,
() -> makeError(response, 404, "No event for identifier " + request.params("identifier"))),
mapper::writeValueAsString);
@@ -86,10 +85,10 @@ public class Application {
Spark.path("/model", () -> {
Spark.get("/full", (request, response) -> {
response.type("text/plain");
- return model.prettyPrint();
+ return root.prettyPrint();
});
Spark.get("/items",
- (request, response) -> wrapItemList(model.items()),
+ (request, response) -> wrapItemList(root.getOpenHAB2Model().items()),
mapper::writeValueAsString);
Spark.put("/items/:identifier/state", (request, response) -> {
logger.info("request body: '{}', params: '{}', length={}", request.body(), request.params(), request.contentLength());
@@ -124,13 +123,13 @@ public class Application {
}
private Object safeItemRoute(Request request, Response response, Function<Item, String> action) {
- return JavaUtils.ifPresentOrElseReturn(model.resolveItem(request.params("identifier")), action,
+ return JavaUtils.ifPresentOrElseReturn(root.getOpenHAB2Model().resolveItem(request.params("identifier")), action,
() -> makeError(response, 404, "Item '" + request.body() + "' not found"));
}
private String makeHistory(Item item, Response response) {
response.type("text/plain");
- InfluxAdapter influxAdapter = model.getInfluxRoot().influxAdapter();
+ InfluxAdapter influxAdapter = root.getInfluxRoot().influxAdapter();
influxAdapter.disableAsyncQuery();
List<? extends AbstractItemPoint> list;
if (item.asColorItem() != null) {
@@ -181,7 +180,9 @@ public class Application {
private SimpleItem wrapItem(Item item) {
return SimpleItem.of(item.getID(),
item.getLabel(),
- item.getTopic() != null ? item.getTopic().allParts() : null,
+ item.getTopic() != null ? item.getTopic().getTopicString() : null,
+ item.isFrozen(),
+ item.isSendState(),
item.getControllingList().stream().map(Item::getID).collect(Collectors.toList()),
wrapMetaData(item.getMetaDataList()));
}
diff --git a/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/DummyDataCreator.java b/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/DummyDataCreator.java
index 902f15bbd31fd7480bd413a239526b9576f68015..e548a6bc95012ba72675131395b9956f4a84466f 100644
--- a/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/DummyDataCreator.java
+++ b/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/DummyDataCreator.java
@@ -10,21 +10,21 @@ import de.tudresden.inf.st.eraser.util.JavaUtils;
*/
class DummyDataCreator {
- private final Root model;
+ private final Root root;
- DummyDataCreator(Root model) {
- this.model = model;
+ DummyDataCreator(Root root) {
+ this.root = root;
}
private void addDummyActivitiesToModel() {
- MachineLearningRoot mlRoot = model.getMachineLearningRoot();
+ MachineLearningRoot mlRoot = root.getMachineLearningRoot();
mlRoot.addActivity(new Activity(1, "Sitting in armchair"));
mlRoot.addActivity(new Activity(2, "Going to sleep"));
mlRoot.addActivity(new Activity(3, "Entering house"));
}
private void addDummyChangeEventsToModel() {
- MachineLearningRoot mlRoot = model.getMachineLearningRoot();
+ MachineLearningRoot mlRoot = root.getMachineLearningRoot();
Item iris1 = getOrCreateColorItem("iris1", "Hue Iris 1");
Item go1 = getOrCreateColorItem("go1", "Hue Go 1");
Item go2 = getOrCreateColorItem("go2", "Hue Go 2");
@@ -40,7 +40,7 @@ class DummyDataCreator {
}
private Item getOrCreateColorItem(String name, String label) {
- return model.resolveItem(name).orElseGet(() -> {
+ return root.getOpenHAB2Model().resolveItem(name).orElseGet(() -> {
ColorItem result = new ColorItem();
result.setID(name);
result.setLabel(label);
@@ -53,7 +53,7 @@ class DummyDataCreator {
private RecognitionEvent newRecognitionEvent(int identifier, long timestamp, int activityIdentifier, ChangedItem... changedItems) {
RecognitionEvent result = new RecognitionEvent();
- JavaUtils.ifPresentOrElse(model.resolveActivity(activityIdentifier), result::setActivity, () -> { throw new RuntimeException("No activity found for identifier " + activityIdentifier); });
+ JavaUtils.ifPresentOrElse(root.resolveActivity(activityIdentifier), result::setActivity, () -> { throw new RuntimeException("No activity found for identifier " + activityIdentifier); });
initChangeEvent(result, identifier, timestamp, changedItems);
return result;
}
diff --git a/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/SimpleItem.java b/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/SimpleItem.java
index 86007bae0cb6ea0366f48a7282341f86c75d8510..2eac624367215c547ef4cfe0058fdcce337062fa 100644
--- a/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/SimpleItem.java
+++ b/eraser.spark/src/main/java/de/tudresden/inf/st/eraser/spark/SimpleItem.java
@@ -15,6 +15,8 @@ public class SimpleItem {
public final String ID;
public final String label;
public final String topic;
+ public final boolean frozen;
+ public final boolean sendState;
public final List<String> controlling;
public final Map<String, String> metaData;
}
diff --git a/eraser.spark/src/main/resources/log4j2.xml b/eraser.spark/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/eraser.spark/src/main/resources/log4j2.xml
+++ b/eraser.spark/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/eraser.starter/build.gradle b/eraser.starter/build.gradle
index c0430b43501673b3ba4ab1b5ffce20d67789f99e..c6d86dcf9977de6e043e469e17726aa87224fb75 100644
--- a/eraser.starter/build.gradle
+++ b/eraser.starter/build.gradle
@@ -1,12 +1,16 @@
+plugins {
+ id 'java'
+ id 'application'
+ id 'distribution'
+ id 'io.github.http-builder-ng.http-plugin' version '0.1.1'
+}
+
repositories {
mavenCentral()
}
sourceCompatibility = 1.8
-apply plugin: 'java'
-apply plugin: 'application'
-
dependencies {
compile project(':eraser-base')
compile project(':eraser.spark')
@@ -15,14 +19,9 @@ dependencies {
compile project(':feedbackloop.plan')
compile project(':feedbackloop.execute')
compile project(':feedbackloop.learner')
- compile 'com.fasterxml.jackson.dataformat:jackson-dataformat-yaml:2.9.8'
- compile 'com.fasterxml.jackson.core:jackson-databind:2.9.8'
+ compile group: 'com.fasterxml.jackson.dataformat', name: 'jackson-dataformat-yaml', version: '2.9.8'
compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- compile 'net.sourceforge.argparse4j:argparse4j:0.8.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
+ compile group: 'net.sourceforge.argparse4j', name: 'argparse4j', version: '0.8.1'
}
run {
@@ -30,6 +29,20 @@ run {
standardInput = System.in
}
+import io.github.httpbuilderng.http.HttpTask
+
+task shutdown (type: HttpTask) {
+ group = 'application'
+ description = 'Shuts down a running eraser application'
+
+ config {
+ request.uri = 'http://localhost:4567'
+ }
+ post {
+ request.uri.path = '/system/exit'
+ }
+}
+
sourceSets {
main {
java {
@@ -37,3 +50,13 @@ sourceSets {
}
}
}
+
+distributions {
+ main {
+ contents {
+ from {
+ 'src/main/resources/starter.eraser'
+ }
+ }
+ }
+}
diff --git a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java
index 8971c806aa0331123e83720ad8906f2214d57faa..b263fd586f95781c26345076e7a3132472f20eab 100644
--- a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java
+++ b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/EraserStarter.java
@@ -8,26 +8,30 @@ import de.tudresden.inf.st.eraser.feedbackloop.api.Analyze;
import de.tudresden.inf.st.eraser.feedbackloop.api.Execute;
import de.tudresden.inf.st.eraser.feedbackloop.api.Learner;
import de.tudresden.inf.st.eraser.feedbackloop.api.Plan;
-import de.tudresden.inf.st.eraser.feedbackloop.api.model.Model;
+import de.tudresden.inf.st.eraser.feedbackloop.api.EncogModel;
import de.tudresden.inf.st.eraser.feedbackloop.execute.ExecuteImpl;
+import de.tudresden.inf.st.eraser.feedbackloop.learner.LearnerHelper;
import de.tudresden.inf.st.eraser.feedbackloop.learner.LearnerImpl;
import de.tudresden.inf.st.eraser.feedbackloop.plan.PlanImpl;
-import de.tudresden.inf.st.eraser.jastadd.model.DummyMachineLearningModel;
-import de.tudresden.inf.st.eraser.jastadd.model.InfluxAdapter;
-import de.tudresden.inf.st.eraser.jastadd.model.NeuralNetworkRoot;
-import de.tudresden.inf.st.eraser.jastadd.model.Root;
+import de.tudresden.inf.st.eraser.jastadd.model.*;
import de.tudresden.inf.st.eraser.openhab2.OpenHab2Importer;
import de.tudresden.inf.st.eraser.openhab2.mqtt.MQTTUpdater;
import de.tudresden.inf.st.eraser.spark.Application;
import de.tudresden.inf.st.eraser.util.JavaUtils;
import de.tudresden.inf.st.eraser.util.ParserUtils;
+import net.sourceforge.argparse4j.ArgumentParsers;
+import net.sourceforge.argparse4j.annotation.Arg;
+import net.sourceforge.argparse4j.inf.ArgumentParser;
+import net.sourceforge.argparse4j.inf.ArgumentParserException;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import java.io.File;
import java.io.IOException;
+import java.io.InputStream;
import java.net.MalformedURLException;
import java.net.URL;
+import java.util.Collections;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
@@ -44,13 +48,30 @@ import java.util.concurrent.locks.ReentrantLock;
*/
public class EraserStarter {
+ private static class CommandLineOptions {
+ @Arg(dest = "config_file")
+ String configFile;
+ }
+
private static final Logger logger = LogManager.getLogger(EraserStarter.class);
@SuppressWarnings("ResultOfMethodCallIgnored")
public static void main(String[] args) {
- logger.info("Starting ERASER");
+ ArgumentParser parser = ArgumentParsers.newFor("eraser").build()
+ .defaultHelp(true)
+ .description("Starts the knowledge-base of OpenLicht");
+ parser.addArgument("-f", "--config-file")
+ .help("Path to the configuration YAML file")
+ .setDefault("starter-setting.yaml");
+ CommandLineOptions commandLineOptions = new CommandLineOptions();
+ try {
+ parser.parseArgs(args, commandLineOptions);
+ } catch (ArgumentParserException e) {
+ parser.handleError(e);
+ System.exit(1);
+ }
ObjectMapper mapper = new ObjectMapper(new YAMLFactory());
- File settingsFile = new File("starter-setting.yaml");
+ File settingsFile = new File(commandLineOptions.configFile);
Setting settings;
try {
settings = mapper.readValue(settingsFile, Setting.class);
@@ -60,14 +81,17 @@ public class EraserStarter {
System.exit(1);
return;
}
+ logger.info("Starting ERASER");
boolean startRest = settings.rest.use;
- Root model;
+ Root root;
+ OpenHAB2Model model;
switch (settings.initModelWith) {
case openhab:
OpenHab2Importer importer = new OpenHab2Importer();
try {
model = importer.importFrom(new URL(settings.openhab.url));
+ root = model.getRoot();
} catch (MalformedURLException e) {
logger.error("Could not parse URL {}", settings.openhab.url);
logger.catching(e);
@@ -79,7 +103,8 @@ public class EraserStarter {
case load:
default:
try {
- model = ParserUtils.load(settings.load.file, EraserStarter.class);
+ root = ParserUtils.load(settings.load.realURL());
+ model = root.getOpenHAB2Model();
} catch (IOException | Parser.Exception e) {
logger.error("Problems parsing the given file {}", settings.load.file);
logger.catching(e);
@@ -89,9 +114,10 @@ public class EraserStarter {
}
// initialize activity recognition
+ MachineLearningRoot machineLearningRoot = root.getMachineLearningRoot();
if (settings.activity.dummy) {
logger.info("Using dummy activity recognition");
- model.getMachineLearningRoot().setActivityRecognition(DummyMachineLearningModel.createDefault());
+ machineLearningRoot.setActivityRecognition(DummyMachineLearningModel.createDefault());
} else {
logger.error("Reading activity recognition from file is not supported yet!");
// TODO
@@ -100,30 +126,46 @@ public class EraserStarter {
// initialize preference learning
if (settings.preference.dummy) {
logger.info("Using dummy preference learning");
- model.getMachineLearningRoot().setPreferenceLearning(DummyMachineLearningModel.createDefault());
+ machineLearningRoot.setPreferenceLearning(DummyMachineLearningModel.createDefault());
} else {
logger.info("Reading preference learning from file {}", settings.preference.file);
Learner learner = new LearnerImpl();
// there should be a method to load a model using an URL
- Model preference = learner.getTrainedModel(settings.preference.realURL(), settings.preference.id);
- NeuralNetworkRoot neuralNetwork = LearnerHelper.transform(preference);
- if (neuralNetwork == null) {
- logger.error("Could not create preference model, see possible previous errors.");
+ boolean loadingSuccessful = false;
+ try (InputStream input = settings.preference.realURL().openStream()) {
+ loadingSuccessful = learner.loadModelFromFile(input, settings.preference.id,
+ Collections.emptyList(), Collections.emptyList(), Collections.emptyList(), Collections.emptyList());
+ } catch (IOException e) {
+ logger.catching(e);
+ loadingSuccessful = false;
+ }
+// Model preference = learner.getTrainedModel(settings.preference.realURL(), settings.preference.id);
+ logger.debug("Loading of {} was {}", settings.preference.realURL(), loadingSuccessful ? "successful" : "failed");
+ if (loadingSuccessful) {
+ EncogModel preference = learner.getTrainedModel(settings.preference.id);
+ NeuralNetworkRoot neuralNetwork = LearnerHelper.transform(preference);
+ if (neuralNetwork == null) {
+ logger.error("Could not create preference model, see possible previous errors.");
+ } else {
+ machineLearningRoot.setPreferenceLearning(neuralNetwork);
+ neuralNetwork.setOutputApplication(zeroToThree -> 33 * zeroToThree);
+ JavaUtils.ifPresentOrElse(
+ model.resolveItem(settings.preference.affectedItem),
+ item -> neuralNetwork.getOutputLayer().setAffectedItem(item),
+ () -> logger.error("Output item not set from value '{}'", settings.preference.affectedItem));
+ }
} else {
- model.getMachineLearningRoot().setPreferenceLearning(neuralNetwork);
- neuralNetwork.connectItems(settings.preference.items);
- neuralNetwork.setOutputApplication(zeroToThree -> 33 * zeroToThree);
- JavaUtils.ifPresentOrElse(
- model.resolveItem(settings.preference.affectedItem),
- item -> neuralNetwork.getOutputLayer().setAffectedItem(item),
- () -> logger.error("Output item not set from value '{}'", settings.preference.affectedItem));
+ // loading was not successful
+ logger.warn("Falling back to dummy preference learning");
+ machineLearningRoot.setPreferenceLearning(DummyMachineLearningModel.createDefault());
}
}
- if (!model.getMachineLearningRoot().getActivityRecognition().check()) {
+ machineLearningRoot.getPreferenceLearning().connectItems(settings.preference.items);
+ if (!machineLearningRoot.getActivityRecognition().check()) {
logger.fatal("Invalid activity recognition!");
System.exit(1);
}
- if (!model.getMachineLearningRoot().getPreferenceLearning().check()) {
+ if (!machineLearningRoot.getPreferenceLearning().check()) {
logger.fatal("Invalid preference learning!");
System.exit(1);
}
@@ -142,9 +184,9 @@ public class EraserStarter {
analyze.setPlan(plan);
plan.setExecute(execute);
- analyze.setKnowledgeBase(model);
- plan.setKnowledgeBase(model);
- execute.setKnowledgeBase(model);
+ analyze.setKnowledgeBase(root);
+ plan.setKnowledgeBase(root);
+ execute.setKnowledgeBase(root);
analyze.startAsThread(1, TimeUnit.SECONDS);
} else {
@@ -154,7 +196,7 @@ public class EraserStarter {
if (settings.mqttUpdate) {
logger.info("Starting MQTT updater");
Thread t = new Thread(() -> {
- try (MQTTUpdater updater = new MQTTUpdater(model)) {
+ try (MQTTUpdater updater = new MQTTUpdater(root)) {
updater.start();
updater.waitUntilReady(5, TimeUnit.SECONDS);
lock.lock();
@@ -174,7 +216,7 @@ public class EraserStarter {
// start REST-API in new thread
logger.info("Starting REST server");
Thread t = new Thread(
- () -> Application.start(settings.rest.port, model, settings.rest.createDummyMLData, lock, quitCondition),
+ () -> Application.start(settings.rest.port, root, settings.rest.createDummyMLData, lock, quitCondition),
"REST-API");
t.setDaemon(true);
t.start();
@@ -208,7 +250,7 @@ public class EraserStarter {
if (analyze != null) {
analyze.stop();
}
- InfluxAdapter influxAdapter = model.getInfluxRoot().influxAdapter();
+ InfluxAdapter influxAdapter = root.getInfluxRoot().influxAdapter();
if (influxAdapter != null) {
try {
influxAdapter.close();
diff --git a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/LearnerHelper.java b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/LearnerHelper.java
deleted file mode 100644
index 34404713f0e3abc32cf87ebca43db783c9dc3288..0000000000000000000000000000000000000000
--- a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/LearnerHelper.java
+++ /dev/null
@@ -1,102 +0,0 @@
-package de.tudresden.inf.st.eraser.starter;
-
-import de.tudresden.inf.st.eraser.feedbackloop.api.model.Model;
-import de.tudresden.inf.st.eraser.jastadd.model.*;
-import org.apache.commons.math3.stat.StatUtils;
-import org.apache.logging.log4j.LogManager;
-import org.apache.logging.log4j.Logger;
-
-import java.util.ArrayList;
-import java.util.Arrays;
-
-/**
- * Transformation of a {@link Model} into a {@link MachineLearningModel}.
- *
- * @author rschoene - Initial contribution
- */
-class LearnerHelper {
-
- private static final Logger logger = LogManager.getLogger(LearnerHelper.class);
-
- // Activation Functions
- private static DoubleArrayDoubleFunction sigmoid = inputs -> Math.signum(Arrays.stream(inputs).sum());
- private static DoubleArrayDoubleFunction tanh = inputs -> Math.tanh(Arrays.stream(inputs).sum());
- private static DoubleArrayDoubleFunction function_one = inputs -> 1.0;
-
- static NeuralNetworkRoot transform(Model model) {
- NeuralNetworkRoot result = NeuralNetworkRoot.createEmpty();
- ArrayList<Double> weights = model.getWeights();
-
- // inputs
- int inputSum = model.getInputLayerNumber() + model.getInputBias();
- for (int i = 0; i < inputSum; ++i) {
- InputNeuron inputNeuron = new InputNeuron();
- result.addInputNeuron(inputNeuron);
- }
- InputNeuron bias = result.getInputNeuron(model.getInputBias());
-
- OutputLayer outputLayer = new OutputLayer();
- // output layer
- for (int i = 0; i < model.getOutputLayerNumber(); ++i) {
- OutputNeuron outputNeuron = new OutputNeuron();
- setActivationFunction(outputNeuron, model.getOutputActivationFunction());
- outputLayer.addOutputNeuron(outputNeuron);
- }
- result.setOutputLayer(outputLayer);
-
- // hidden layer
- int hiddenSum = model.gethiddenLayerNumber() + model.getHiddenBias();
- HiddenNeuron[] hiddenNeurons = new HiddenNeuron[hiddenSum];
- for (int i = 0; i < (hiddenNeurons.length); i++) {
- if (i == model.gethiddenLayerNumber()) {
- HiddenNeuron hiddenNeuron = new HiddenNeuron();
- hiddenNeuron.setActivationFormula(function_one);
- hiddenNeurons[i] = hiddenNeuron;
- result.addHiddenNeuron(hiddenNeuron);
- bias.connectTo(hiddenNeuron, 1.0);
- for (int out = 0; out < outputLayer.getNumOutputNeuron(); out++) {
- hiddenNeuron.connectTo(outputLayer.getOutputNeuron(out), weights.get(i + hiddenSum * out));
- }
- } else {
- HiddenNeuron hiddenNeuron = new HiddenNeuron();
- setActivationFunction(hiddenNeuron, model.getHiddenActivationFunction());
- hiddenNeurons[i] = hiddenNeuron;
- result.addHiddenNeuron(hiddenNeuron);
- for (int in = 0; in < inputSum; in++) {
- // TODO replace 4 and 5 with model-attributes
- result.getInputNeuron(in).connectTo(hiddenNeuron, weights.get((hiddenNeurons.length * 4 + in) + i * 5));
- }
- for (int out = 0; out < outputLayer.getNumOutputNeuron(); out++) {
- hiddenNeuron.connectTo(outputLayer.getOutputNeuron(out), weights.get(i + hiddenSum * out));
- }
- }
- }
- outputLayer.setCombinator(LearnerHelper::predictor);
- logger.info("Created model with {} input, {} hidden and {} output neurons",
- result.getNumInputNeuron(), result.getNumHiddenNeuron(), result.getOutputLayer().getNumOutputNeuron());
- return result;
- }
-
- private static void setActivationFunction(HiddenNeuron neuron, String functionName) {
- switch (functionName) {
- case "ActivationTANH": neuron.setActivationFormula(tanh); break;
- case "ActivationLinear": neuron.setActivationFormula(function_one);
- case "ActivationSigmoid": neuron.setActivationFormula(sigmoid); break;
- default: throw new IllegalArgumentException("Unknown function " + functionName);
- }
- }
-
- private static double predictor(double[] inputs) {
- int index = 0;
- double maxInput = StatUtils.max(inputs);
- for (int i = 0; i < inputs.length; i++) {
- if (inputs[i] == maxInput) {
- index = i;
- }
- }
- //outputs from learner
- final double[] outputs = new double[]{2.0, 1.0, 3.0, 0.0};
- return outputs[index];
- }
-
-}
diff --git a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java
index fb08ee7df0463a9d2feb56bc2bf9d3e8296df791..dacbb4287bb16d2f4fcdb5ba2e2cb4b67cf6406e 100644
--- a/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java
+++ b/eraser.starter/src/main/java/de/tudresden/inf/st/eraser/starter/Setting.java
@@ -1,6 +1,11 @@
package de.tudresden.inf.st.eraser.starter;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+
+import java.net.MalformedURLException;
import java.net.URL;
+import java.nio.file.Paths;
import java.util.List;
/**
@@ -10,6 +15,7 @@ import java.util.List;
*/
@SuppressWarnings("WeakerAccess")
class Setting {
+ private final static Logger logger = LogManager.getLogger(Setting.class);
public class Rest {
/** Start the REST server. Default: true. */
public boolean use = true;
@@ -20,9 +26,20 @@ class Setting {
}
public class FileContainer {
public String file;
+ /** Whether the file is external (not shipped with the JAR). Default: false. */
+ public boolean external = false;
/** Get the URL to the {@link #file} */
URL realURL() {
- return Setting.class.getClassLoader().getResource(file);
+ if (external) {
+ try {
+ return Paths.get(file).toUri().toURL();
+ } catch (MalformedURLException e) {
+ logger.catching(e);
+ return null;
+ }
+ } else {
+ return Setting.class.getClassLoader().getResource(file);
+ }
}
}
public class MLContainer extends FileContainer {
diff --git a/eraser.starter/src/main/resources/log4j2.xml b/eraser.starter/src/main/resources/log4j2.xml
index 2ff094e32bbda4cd215ebac36f65b4394d607cad..900e8c305d176e82d8f8a3c6beb1e96acfe186a8 100644
--- a/eraser.starter/src/main/resources/log4j2.xml
+++ b/eraser.starter/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/eraser.starter/src/main/resources/starter.eraser b/eraser.starter/src/main/resources/starter.eraser
index 8d08d97431d0ea2a3a99e019b2126f1e1d04adb5..25505fe24d64d3ed08ecdc0a3d741625b25e46ad 100644
--- a/eraser.starter/src/main/resources/starter.eraser
+++ b/eraser.starter/src/main/resources/starter.eraser
@@ -1,14 +1,28 @@
-Color Item: id="iris1_item" label="Iris 1" state="121,88,68" topic="iris1_item/state";
-Number Item: id="datetime_month" label="Month" state="1" topic="datetime/month";
-Number Item: id="datetime_day" label="Day" state="31" topic="datetime/day";
-Number Item: id="datetime_hour" label="Hour" state="13" topic="datetime/hour";
-Number Item: id="datetime_minute" label="Minute" state="37" topic="datetime/minute";
+Color Item: id="iris1_item" label="Iris 1" state="121,88,68" topic="iris1_item";
+Number Item: id="datetime_month" label="Month" state="1" topic="datetime_month";
+Number Item: id="datetime_day" label="Day" state="31" topic="datetime_day";
+Number Item: id="datetime_hour" label="Hour" state="13" topic="datetime_hour";
+Number Item: id="datetime_minute" label="Minute" state="37" topic="datetime_minute";
Number Item: id="bias" label="bias item" state="1" ;
+Activity Item: id="activity" ;
Group: id="Lights" items=["iris1_item"];
-Group: id="Datetime" items=["datetime-month", "datetime-day", "datetime-hour", "datetime-minute"];
+Group: id="Datetime" items=["datetime_month", "datetime_day", "datetime_hour", "datetime_minute"];
-Mqtt: incoming="oh2/out/" outgoing="oh2/in/" host="localhost" ;
+Mqtt: incoming="oh2/out/" outgoing="oh2/in/" host="localhost:2883" ;
//Mqtt: incoming="oh2/out/" outgoing="oh2/in/" host="192.168.1.250" ;
Influx: host="172.22.1.152" ;
+
+ML: activities={
+ 0: "Open door in empty room",
+ 1: "Door closed in empty room",
+ 2: "Open door with person in room",
+ 3: "Door closed with person in room",
+ 4: "Working",
+ 5: "Watch TV",
+ 6: "Reading",
+ 7: "Listening to music",
+ 8: "Going to sleep",
+ 9: "Wake up"
+} ;
diff --git a/eraser.starter/starter-setting.yaml b/eraser.starter/starter-setting.yaml
index 01d5ec91350e51e34e2073ee7dce2bc0470f64d9..f29763c43dfa4b789f872efc9eec88439930eff9 100644
--- a/eraser.starter/starter-setting.yaml
+++ b/eraser.starter/starter-setting.yaml
@@ -9,13 +9,18 @@ rest:
# Port of the REST server. Default: 4567.
port: 4567
# Add some dummy data for activities and events. Only effective when using the REST server. Default: false.
- createDummyMLData: true
+ createDummyMLData: false
# Initialize the knowledge base with a file.
# OpenHAB synchronization is done if MQTT url is set in the processed file
load:
# File to read in. Expected format = eraser
- file: starter.eraser
+# # Option 1: Use built-in file
+# file: starter.eraser
+# external: false
+ # Option 2: Use external file
+ file: src/main/resources/starter.eraser
+ external: true
# Model for activity recognition. If dummy is true, then the file parameter is ignored.
activity:
@@ -40,7 +45,7 @@ preference:
- datetime_day
- datetime_hour
- datetime_minute
- - bias
+# - activity
# Item to change with classification result
affectedItem: iris1_item
diff --git a/feedbackloop.analyze/build.gradle b/feedbackloop.analyze/build.gradle
index b59641cfc6d47d4dac802ed0387bdd38806b3004..077136f33bd04ccde2acb2cce23df7ba22c69c7a 100644
--- a/feedbackloop.analyze/build.gradle
+++ b/feedbackloop.analyze/build.gradle
@@ -9,11 +9,6 @@ apply plugin: 'java'
dependencies {
compile project(':eraser-base')
compile project(':feedbackloop.api')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
sourceSets {
diff --git a/feedbackloop.analyze/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/analyze/AnalyzeImpl.java b/feedbackloop.analyze/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/analyze/AnalyzeImpl.java
index f58867a0ade42cba5c3da2ac4668ece0ee56bf60..5e9f8cfb5476ae25219cebd704e17e2e2b78cb9d 100644
--- a/feedbackloop.analyze/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/analyze/AnalyzeImpl.java
+++ b/feedbackloop.analyze/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/analyze/AnalyzeImpl.java
@@ -45,7 +45,11 @@ public class AnalyzeImpl implements Analyze {
// new! inform plan!
logger.info("Found new activity '{}'", activity.getLabel());
mostRecentActivity = activity;
- informPlan(activity);
+ try {
+ informPlan(activity);
+ } catch (Exception e) {
+ logger.catching(e);
+ }
}
});
}
diff --git a/feedbackloop.analyze/src/main/resources/log4j2.xml b/feedbackloop.analyze/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.analyze/src/main/resources/log4j2.xml
+++ b/feedbackloop.analyze/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/feedbackloop.api/build.gradle b/feedbackloop.api/build.gradle
index 9403a7197373bc6fcaa2e68821261fbc264ee6d4..0039b3d515db9d781cbbdc37c25ab42fa23fa855 100644
--- a/feedbackloop.api/build.gradle
+++ b/feedbackloop.api/build.gradle
@@ -1,20 +1,18 @@
+plugins {
+ id 'java'
+ id 'io.franzbecker.gradle-lombok' version '3.0.0'
+}
+
repositories {
mavenCentral()
}
sourceCompatibility = 1.8
-apply plugin: 'java'
-
dependencies {
compile project(':eraser-base')
- compile project(':commons.color:')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
- compile 'org.encog:encog-core:3.4'
+ compile project(':commons.color')
+ compile group: 'org.encog', name: 'encog-core', version: '3.4'
}
sourceSets {
diff --git a/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/EncogModel.java b/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/EncogModel.java
new file mode 100644
index 0000000000000000000000000000000000000000..c0bc0336ea49e810ac5930c30600e271e65c6861
--- /dev/null
+++ b/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/EncogModel.java
@@ -0,0 +1,44 @@
+package de.tudresden.inf.st.eraser.feedbackloop.api;
+
+import lombok.Getter;
+import lombok.Setter;
+import org.encog.neural.networks.layers.Layer;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Objects;
+
+/**
+ *
+ * This class represents an object that contains all information of a trained neural network.
+ *
+ * For now: weights and the {@link Layer}s
+ *
+ * @author Bierzyns - initial contribution
+ * */
+@Getter
+@Setter
+public class EncogModel {
+ /**
+ * todo
+ */
+ private String modelType;
+ private List<Double> weights;
+ private List<Layer> layers;
+
+ public EncogModel(String model) {
+ modelType = model;
+ }
+
+ public Layer getInputLayer() {
+ return Objects.requireNonNull(layers, "Layers not set yet").get(0);
+ }
+
+ public Layer getOutputLayer() {
+ return Objects.requireNonNull(layers, "Layers not set yet").get(layers.size() - 1);
+ }
+
+ public List<Layer> getHiddenLayers() {
+ return Objects.requireNonNull(layers, "Layers not set yet").subList(1, layers.size() - 1);
+ }
+}
diff --git a/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/Learner.java b/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/Learner.java
index 5ee02c57f3ff5a1353c0a50d5f94055e5b9eabe4..a08a6fc2a444b4a30fd4f234acfd4449c075d444 100644
--- a/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/Learner.java
+++ b/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/Learner.java
@@ -1,15 +1,18 @@
package de.tudresden.inf.st.eraser.feedbackloop.api;
+import java.io.File;
+import java.io.InputStream;
import java.net.URL;
-import java.util.ArrayList;
+import java.util.List;
+
+import org.encog.util.arrayutil.NormalizedField;
-import de.tudresden.inf.st.eraser.feedbackloop.api.model.Model;
import de.tudresden.inf.st.eraser.jastadd.model.Root;
/**
*
- * Learner which handles the training and retraining of algorithms
- * and models used for activity recognition, preference learning and data pre-processing.
+ * Learner which handles the training and retraining of neural networks
+ * and models used for activity recognition and preference learning.
*
* @author Bierzyns - initial contribution
*
@@ -19,50 +22,114 @@ public interface Learner {
void setKnowledgeBase(Root knowledgeBase);
/**
- * Method for loading data set, which used for initial training. This method exists only for development purposes.
+ * Method for loading data set, which used for initial training. This method exists only for development purposes. The csvFolderPath
+ * variable should be set to ensure that the data is read from the correct place.
*
- * @param dataSetName - name of data set that is loaded from the data set folder e.g. data1.arff (Weka)
+ * @param dataSetName - name of data set that is loaded from the data set folder e.g. data1.csv
+ * @param targetColumns - number of the columns that contain label of the corresponding csv data set
* @param modelID - ID of the model that will be trained with this data set
* @return true - data set loading was successful
* */
- boolean loadDataSet(String dataSetName, int modelID);
+ boolean loadDataSet(String dataSetName, List<Integer> targetColumns, int modelID);
+
+ /**
+ * Method for loading a neural network from a file.
+ * Please note that the normalizer are note loaded file , because it is assumed that the mins and maxes are saved anyway in the meta data of the data sets or items.
+ *
+ * @param file file to load the model from
+ * @param modelID - ID of the BasicNetwork.
+ * @param inputMaxes - list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins - list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes - list that contains max values of all output columns (results) e.g. brigthness 100 for preference learning
+ * @param targetMins - list that contains min values of all output columns (results) e.g. brigthness 0 for preference learning
+ * @return true - model loading was successful
+ * */
+ boolean loadModelFromFile(File file, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins);
+
+ /**
+ * Method for loading a neural network from an input stream.
+ * Please note that the normalizer are note loaded file , because it is assumed that the mins and maxes are saved anyway in the meta data of the data sets or items.
+ *
+ * @param input stream to load the model from
+ * @param modelID - ID of the BasicNetwork.
+ * @param inputMaxes - list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins - list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes - list that contains max values of all output columns (results) e.g. brigthness 100 for preference learning
+ * @param targetMins - list that contains min values of all output columns (results) e.g. brigthness 0 for preference learning
+ * @return true - model loading was successful
+ * */
+ boolean loadModelFromFile(InputStream input, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins);
/**
* Method for the initial training of algorithms and models. That uses external data set for training.
*
- * @param modelID - ID of model that will be trained
+ * @param inputCount - number of neurons in the input layer [here to simplify code reading]
+ * @param outputCount - number of neurons in the output layer [here to simplify code reading]
+ * @param hiddenCount -number of hidden layers in the network
+ * @param hiddenNeuronCount - number of neurons in the hidden layers for now
+ * @param modelID - ID of the BasicNetwork.
+ * @param inputMaxes - list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins - list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes - list that contains max values of all output columns (results) e.g. brigthness 100 for preference learning
+ * @param targetMins - list that contains min values of all output columns (results) e.g. brigthness 0 for preference learning
+ *
* @return true - training of the model was successful started
* */
- boolean train(int modelID);
+ boolean train(int inputCount, int outputCount, int hiddenCount, int hiddenNeuronCount, int modelID,
+ List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins);
/**
- * Method for the initial training of algorithms and models. That uses data set provided by Knowledge Base. Format of Data?
+ * Method for the initial training of algorithms and models. That uses data set provided by Knowledge Base.
*
- * @param set - data set on which the training is based on
- * @param modelID - ID of model that will be trained
+ * @param data - data set on which the training is based on
+ * @param inputCount - number of neurons in the input layer [here to simplify code reading]
+ * @param outputCount - number of neurons in the output layer [here to simplify code reading]
+ * @param hiddenCount - number of hidden layers in the network
+ * @param hiddenNeuronCount - number of neurons in the hidden layers for now
+ * @param modelID - ID of the BasicNetwork.
+ * @param inputMaxes - list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins - list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes - list that contains max values of all output columns (results) e.g. brigthness 100 for preference learning
+ * @param targetMins - list that contains min values of all output columns (results) e.g. brigthness 0 for preference learning
* @return true - training of the model was successful started
* */
- boolean train(ArrayList<Integer> set, int modelID);
+ boolean train(double[][] data, int inputCount, int outputCount, int hiddenCount, int hiddenNeuronCount, int modelID,
+ List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins, List<Integer> targetColumns);
/**
- * Method for adapting existing models. Format of new data?
+ * Method for adapting existing models.
*
- * @param set - data set on which the retraining is based on
+ * @param data - data set on which the retraining is based on
+ * @param targetColumns - number of the columns thta contain labels/target
* @param modelID - ID of the model that will be retrained
* @return true - retraining of model was started successfully
* */
- boolean reTrain(ArrayList<Integer> set, int modelID);
+ boolean reTrain(double[][] data, List<Integer> targetColumns, int modelID);
/**
* Method for getting the information about an trained model.
*
- * @param modelID - ID of the model of which information are requested from
- * @return Model - Object that contains the information of the requested model
+ * @param modelID - ID of the model of which information is requested from
+ * @return Model - Object that contains the information of the requested model
* */
- Model getTrainedModel(int modelID);
-
- Model getTrainedModel(URL url, int modelID);
+ EncogModel getTrainedModel(int modelID);
- ArrayList<Double> getNormalizer(int modelID, ArrayList<Integer> list);
+ @Deprecated
+ EncogModel getTrainedModel(URL url, int modelID);
+
+ /**
+ *
+ * Method for getting normalizer of a model for a specific column/input.
+ *
+ * @param modelID - ID of the model of which normalizer is requested from
+ * @param columnNr - number of columns the normalizer can be used for
+ *
+ * @return {@link NormalizedField} - the normalizer
+ * */
+ NormalizedField getNormalizerInput(int modelID, int columnNr);
}
diff --git a/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/model/Model.java b/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/model/Model.java
deleted file mode 100644
index 2b24c4267addb456b63eee9afc16b061c738c9c9..0000000000000000000000000000000000000000
--- a/feedbackloop.api/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/api/model/Model.java
+++ /dev/null
@@ -1,106 +0,0 @@
-package de.tudresden.inf.st.eraser.feedbackloop.api.model;
-
-import java.text.Normalizer;
-import java.util.ArrayList;
-import org.encog.ml.data.versatile.NormalizationHelper;
-
-/**
- *
- * This class represents an object that contains all information of a trained model.
- *
- * @author Bierzyns - initial contribution
- * */
-public class Model {
- /**
- * todo
- */
-
- private String modelType;
- private ArrayList weights;
-
- private Integer inputLayerNumber;
- private Integer hiddenLayerNumber;
- private Integer outputLayerNumber;
-
- private String inputActivationFunction;
- private String hiddenActivationFunction;
- private String outputActivationFunction;
-
- private Integer inputBiasNumber;
- private Integer hiddenBiasNumber;
- private NormalizationHelper helper;
-
- public Model(String model) {
-
- modelType=model;
- }
- /**
- * Getter for model type.
- *
- * @return modelType - Possible results: NN or DT
- * */
-
- public String getModelType(){return this.modelType;}
-
- public ArrayList<Double> getWeights(){
- return this.weights;
- }
-
- public void setWeights(ArrayList<Double> weights){
- this.weights=weights;
- }
-
- public void setInputLayerNumber(int Number){this.inputLayerNumber=Number;}
- public int getInputLayerNumber(){
- return this.inputLayerNumber;
- }
-
- public void setHiddenLayerNumber(int Number){this.hiddenLayerNumber=Number;}
- public int gethiddenLayerNumber(){
- return this.hiddenLayerNumber;
- }
-
- public void setOutputLayerNumber(int Number){this.outputLayerNumber=Number;}
- public int getOutputLayerNumber(){
- return this.outputLayerNumber;
- }
- public void setInputActivationFunction(String function){
- this.inputActivationFunction=function;
- }
- public String getInputActivationFunction(){
- return this.inputActivationFunction;
- }
- public void setHiddenActivationFunction(String function){
- this.hiddenActivationFunction=function;
- }
- public String getHiddenActivationFunction(){
- return this.hiddenActivationFunction;
- }
- public void setOutputActivationFunction(String function){
- this.outputActivationFunction=function;
- }
- public String getOutputActivationFunction(){
- return this.outputActivationFunction;
- }
-
- public void setInputBias(int Number){
- this.inputBiasNumber=Number;
- }
- public int getInputBias(){
- return this.inputBiasNumber;
- }
-
- public void setHiddenBias(int Number){
- this.hiddenBiasNumber=Number;
- }
-
- public int getHiddenBias(){
- return this.hiddenBiasNumber;
- }
- //public void setNormalizer(NormalizationHelper helper){
- //this.helper=helper;
- //}
- //public NormalizationHelper getNormalizer(){
- //return this.helper;
- //}
-}
diff --git a/feedbackloop.api/src/main/resources/log4j2.xml b/feedbackloop.api/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.api/src/main/resources/log4j2.xml
+++ b/feedbackloop.api/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/feedbackloop.execute/build.gradle b/feedbackloop.execute/build.gradle
index b59641cfc6d47d4dac802ed0387bdd38806b3004..077136f33bd04ccde2acb2cce23df7ba22c69c7a 100644
--- a/feedbackloop.execute/build.gradle
+++ b/feedbackloop.execute/build.gradle
@@ -9,11 +9,6 @@ apply plugin: 'java'
dependencies {
compile project(':eraser-base')
compile project(':feedbackloop.api')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
sourceSets {
diff --git a/feedbackloop.execute/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImpl.java b/feedbackloop.execute/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImpl.java
index 1fa433ad425df55e2d9c44b66c396786cddea84e..80d2346312445914306e6c224d1f9de1b766cf6d 100644
--- a/feedbackloop.execute/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImpl.java
+++ b/feedbackloop.execute/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImpl.java
@@ -61,7 +61,7 @@ public class ExecuteImpl implements Execute {
}
private void resolveOrLogError(String itemId, Consumer<? super Item> consumer) {
- Optional<Item> optionalItem = knowledgeBase.resolveItem(itemId);
+ Optional<Item> optionalItem = knowledgeBase.getOpenHAB2Model().resolveItem(itemId);
if (!optionalItem.isPresent()) {
logger.warn("Could not resolve '{}' as an item.", itemId);
}
diff --git a/feedbackloop.execute/src/main/resources/log4j2.xml b/feedbackloop.execute/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.execute/src/main/resources/log4j2.xml
+++ b/feedbackloop.execute/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/feedbackloop.execute/src/test/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImplTest.java b/feedbackloop.execute/src/test/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImplTest.java
index 66823f1459c45fccc007815b3004527b62159be6..f3f79ac72847b1c8c251c96a6d011014479f7115 100644
--- a/feedbackloop.execute/src/test/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImplTest.java
+++ b/feedbackloop.execute/src/test/java/de/tudresden/inf/st/eraser/feedbackloop/execute/ExecuteImplTest.java
@@ -21,7 +21,7 @@ public class ExecuteImplTest {
@Test
public void testColorControlledByOneNumber() {
ModelAndItem mai = TestUtils.createModelAndItem(0);
- Root model = mai.model;
+ OpenHAB2Model model = mai.model;
NumberItem numberItem = mai.item;
ColorItem lamp = new ColorItem();
@@ -33,7 +33,7 @@ public class ExecuteImplTest {
numberItem.addControlling(lamp);
Execute execute = new ExecuteImpl();
- execute.setKnowledgeBase(model);
+ execute.setKnowledgeBase(model.getRoot());
Assert.assertEquals(0, numberItem.getState(), DELTA);
Assert.assertEquals(TupleHSB.of(0, 0, 0), lamp.getState());
@@ -47,7 +47,7 @@ public class ExecuteImplTest {
@Test
public void testColorControlledByOneBoolean() {
- Root model = TestUtils.createModelAndItem(0).model;
+ OpenHAB2Model model = TestUtils.createModelAndItem(0).model;
ItemWithBooleanState button = new SwitchItem();
button.setID("button");
@@ -64,7 +64,7 @@ public class ExecuteImplTest {
button.addControlling(lamp);
Execute execute = new ExecuteImpl();
- execute.setKnowledgeBase(model);
+ execute.setKnowledgeBase(model.getRoot());
Assert.assertFalse(button.getState());
Assert.assertEquals(TupleHSB.of(0, 0, 0), lamp.getState());
@@ -79,7 +79,7 @@ public class ExecuteImplTest {
@Test
public void testColorControlledByMany() {
ModelAndItem mai = TestUtils.createModelAndItem(0);
- Root model = mai.model;
+ OpenHAB2Model model = mai.model;
NumberItem numberItem = mai.item;
Group g = TestUtils.getDefaultGroup(model);
@@ -108,7 +108,7 @@ public class ExecuteImplTest {
lamp.addControlledBy(colorItem);
Execute execute = new ExecuteImpl();
- execute.setKnowledgeBase(model);
+ execute.setKnowledgeBase(model.getRoot());
Assert.assertEquals(0, numberItem.getState(), DELTA);
Assert.assertEquals("0", stringItem.getState());
diff --git a/feedbackloop.learner/build.gradle b/feedbackloop.learner/build.gradle
index c3303f2d9f2835666f08b8ee7748a9c8d100e7eb..ea041e50cc38e90c333527bf039567860b29f7a8 100644
--- a/feedbackloop.learner/build.gradle
+++ b/feedbackloop.learner/build.gradle
@@ -10,12 +10,7 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
compile project(':feedbackloop.api')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
- compile 'org.encog:encog-core:3.4'
+ compile group: 'org.encog', name: 'encog-core', version: '3.4'
}
run {
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Dataset.java b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Dataset.java
new file mode 100644
index 0000000000000000000000000000000000000000..0b09cbd2c73a753fa2de5b74b8bbe509e8e75a36
--- /dev/null
+++ b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Dataset.java
@@ -0,0 +1,36 @@
+package de.tudresden.inf.st.eraser.feedbackloop.learner;
+
+import org.encog.util.csv.ReadCSV;
+
+import java.util.List;
+
+/**
+ * This class is an representation of a data set in csv format.
+ * The data is saved and made accessible by {@link ReadCSV} and the numbers of the target columns is saved as meta-data.
+ *
+ * @author Bierzyns - initial contribution
+ *
+ * */
+public class Dataset {
+
+ private final ReadCSV csv;
+ private final List<Integer> targetColumns;
+
+ public Dataset(ReadCSV csv, List<Integer> targetColumns) {
+ this.csv = csv;
+ this.targetColumns = targetColumns;
+ }
+
+ public int getColumnCount() {
+ return csv.getColumnCount();
+ }
+
+ public List<Integer> getTargetColumns() {
+ return targetColumns;
+ }
+
+ public ReadCSV getCsv() {
+ return csv;
+ }
+
+}
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerHelper.java b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerHelper.java
new file mode 100644
index 0000000000000000000000000000000000000000..f23b58105b78ea6b84a3f11211e843eb28f2cf13
--- /dev/null
+++ b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerHelper.java
@@ -0,0 +1,150 @@
+package de.tudresden.inf.st.eraser.feedbackloop.learner;
+
+import de.tudresden.inf.st.eraser.feedbackloop.api.EncogModel;
+import de.tudresden.inf.st.eraser.jastadd.model.*;
+import org.apache.commons.math3.stat.StatUtils;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+import org.encog.engine.network.activation.ActivationFunction;
+import org.encog.engine.network.activation.ActivationLinear;
+import org.encog.engine.network.activation.ActivationSigmoid;
+import org.encog.engine.network.activation.ActivationTANH;
+import org.encog.neural.networks.layers.Layer;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.stream.Collectors;
+
+/**
+ * Transformation of a {@link EncogModel} into a {@link NeuralNetworkRoot}.
+ *
+ * @author rschoene - Initial contribution
+ */
+public class LearnerHelper {
+
+ private static final Logger logger = LogManager.getLogger(LearnerHelper.class);
+
+ // Activation Functions
+ private static DoubleArrayDoubleFunction sigmoid = inputs -> Math.signum(Arrays.stream(inputs).sum());
+ private static DoubleArrayDoubleFunction tanh = inputs -> Math.tanh(Arrays.stream(inputs).sum());
+ private static DoubleArrayDoubleFunction function_one = inputs -> 1.0;
+
+ public static NeuralNetworkRoot transform(EncogModel encogModel) {
+ NeuralNetworkRoot result = NeuralNetworkRoot.createEmpty();
+ List<Double> weights = encogModel.getWeights();
+ logger.debug("Got {} weights", weights.size());
+
+ List<List<Neuron>> allNeurons = new ArrayList<>();
+ // inputs
+ Layer inputLayer = encogModel.getInputLayer();
+ reportLayer("input", inputLayer);
+ List<Neuron> inputNeurons = new ArrayList<>();
+ for (int i = 0; i < nonBiasNeuronCount(inputLayer); ++i) {
+ InputNeuron inputNeuron = new InputNeuron();
+ result.addInputNeuron(inputNeuron);
+ inputNeurons.add(inputNeuron);
+ }
+ addBiasIfNeeded(inputLayer, result.getHiddenNeuronList(), inputNeurons);
+ allNeurons.add(inputNeurons);
+
+ // hidden layer
+ List<Neuron> currentNeurons;
+ for (Layer hiddenLayer : encogModel.getHiddenLayers()) {
+ reportLayer("one hidden", hiddenLayer);
+ currentNeurons = new ArrayList<>();
+ allNeurons.add(currentNeurons);
+ for (int i = 0; i < nonBiasNeuronCount(hiddenLayer); ++i) {
+ HiddenNeuron hiddenNeuron = new HiddenNeuron();
+ setActivationFunction(hiddenNeuron, hiddenLayer.getActivationFunction());
+ result.addHiddenNeuron(hiddenNeuron);
+ currentNeurons.add(hiddenNeuron);
+ }
+ addBiasIfNeeded(hiddenLayer, result.getHiddenNeuronList(), currentNeurons);
+ }
+
+ // output layer
+ OutputLayer outputLayer = new OutputLayer();
+ Layer modelOutputLayer = encogModel.getOutputLayer();
+ reportLayer("output", modelOutputLayer);
+ List<Neuron> outputNeurons = new ArrayList<>();
+ for (int i = 0; i < nonBiasNeuronCount(modelOutputLayer); ++i) {
+ OutputNeuron outputNeuron = new OutputNeuron();
+ setActivationFunction(outputNeuron, modelOutputLayer.getActivationFunction());
+ outputLayer.addOutputNeuron(outputNeuron);
+ outputNeurons.add(outputNeuron);
+ }
+ result.setOutputLayer(outputLayer);
+ allNeurons.add(outputNeurons);
+ logger.debug("Created a total of {} neurons",
+ allNeurons.stream()
+ .map(list -> Integer.toString(list.size()))
+ .collect(Collectors.joining("+")));
+
+ // set weights from back to front, and from top to bottom
+ int weightIndex = 0;
+ for (int layer = allNeurons.size() - 1; layer > 0; --layer) {
+ List<Neuron> rightList = allNeurons.get(layer);
+ List<Neuron> leftList = allNeurons.get(layer - 1);
+ for (int rightIndex = 0; rightIndex < rightList.size(); rightIndex++) {
+ for (int leftIndex = 0; leftIndex < leftList.size(); leftIndex++) {
+ if (rightList.get(rightIndex) instanceof BiasNeuron) {
+ continue;
+ }
+ leftList.get(leftIndex).connectTo(rightList.get(rightIndex), weights.get(weightIndex++));
+ }
+ }
+ }
+ if (weightIndex != weights.size()) {
+ logger.error("No all weights used (only {} of {}). Loaded wrong model!", weightIndex, weights.size());
+ }
+
+ outputLayer.setCombinator(LearnerHelper::predictor);
+ logger.info("Created model with {} input, {} hidden and {} output neurons",
+ result.getNumInputNeuron(), result.getNumHiddenNeuron(), result.getOutputLayer().getNumOutputNeuron());
+ return result;
+ }
+
+ private static void addBiasIfNeeded(Layer layer, JastAddList<HiddenNeuron> neuronList, List<Neuron> localNeuronList) {
+ if (layer.hasBias()) {
+ BiasNeuron bias = new BiasNeuron();
+ neuronList.add(bias);
+ localNeuronList.add(bias);
+ }
+ }
+
+ private static int nonBiasNeuronCount(Layer layer) {
+ return layer.getNeuronCount() - (layer.hasBias() ? 1 : 0);
+ }
+
+ private static void reportLayer(String name, Layer layer) {
+ logger.debug("{} layer has {} neurons {}",
+ name, layer.getNeuronCount(), layer.hasBias() ? "(including bias)" : "");
+ }
+
+ private static void setActivationFunction(HiddenNeuron neuron, ActivationFunction function) {
+ if (function instanceof ActivationTANH) {
+ neuron.setActivationFormula(tanh);
+ } else if (function instanceof ActivationLinear) {
+ neuron.setActivationFormula(function_one);
+ } else if (function instanceof ActivationSigmoid) {
+ neuron.setActivationFormula(sigmoid);
+ } else {
+ throw new IllegalArgumentException("Unknown activation function " + function.getClass().getName());
+ }
+ }
+
+ private static double predictor(double[] inputs) {
+ int index = 0;
+ double maxInput = StatUtils.max(inputs);
+ for (int i = 0; i < inputs.length; i++) {
+ if (inputs[i] == maxInput) {
+ index = i;
+ }
+ }
+ //outputs from learner
+ final double[] outputs = new double[]{2.0, 1.0, 3.0, 0.0};
+ return outputs[index];
+ }
+
+}
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerImpl.java b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerImpl.java
index c9d79dbba376b13554a881bfc9dc3fc2df0f0849..83edf6b7f195d9be6420369d4590955c42449735 100644
--- a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerImpl.java
+++ b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/LearnerImpl.java
@@ -1,335 +1,230 @@
package de.tudresden.inf.st.eraser.feedbackloop.learner;
-import java.io.*;
-import java.net.URL;
-import java.util.ArrayList;
-
+import de.tudresden.inf.st.eraser.feedbackloop.api.EncogModel;
import de.tudresden.inf.st.eraser.feedbackloop.api.Learner;
-import de.tudresden.inf.st.eraser.feedbackloop.api.model.Model;
-import de.tudresden.inf.st.eraser.jastadd.model.*;
-
-import org.apache.commons.math3.stat.StatUtils;
+import de.tudresden.inf.st.eraser.jastadd.model.Root;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
-import org.encog.Encog;
-import org.encog.ml.MLClassification;
-import org.encog.ml.data.MLData;
+import org.encog.neural.flat.FlatNetwork;
+import org.encog.neural.networks.BasicNetwork;
+import org.encog.neural.networks.layers.BasicLayer;
+import org.encog.neural.networks.layers.Layer;
+import org.encog.util.arrayutil.NormalizedField;
import org.encog.util.csv.CSVFormat;
import org.encog.util.csv.ReadCSV;
-import org.encog.util.simple.EncogUtility;
-
-import org.encog.ml.data.versatile.NormalizationHelper;
-import org.encog.ml.data.versatile.VersatileMLDataSet;
-import org.encog.ml.data.versatile.columns.ColumnDefinition;
-import org.encog.ml.data.versatile.columns.ColumnType;
-import org.encog.ml.data.versatile.sources.VersatileDataSource;
-import org.encog.ml.data.versatile.sources.CSVDataSource;
-import org.encog.ml.factory.MLMethodFactory;
-import org.encog.ml.model.EncogModel;
-import org.encog.ConsoleStatusReportable;
-import org.encog.ml.MLRegression;
-
-import java.util.Arrays;
-import static org.encog.persist.EncogDirectoryPersistence.*;
-
import java.io.File;
-import java.util.List;
+import java.io.InputStream;
+import java.net.URL;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+import java.util.*;
/**
* Implementation of the Learner.
*
* @author Bierzyns - Initial contribution
*/
-public class LearnerImpl implements Learner{
- /**
- * todo
- */
-
- private Root knowledgeBase;
- private Logger logger = LogManager.getLogger(LearnerImpl.class);
- private String saveFile="src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/";
- private String loadFile;
-
-
- @Override
- public void setKnowledgeBase(Root knowledgeBase) {
- this.knowledgeBase = knowledgeBase;
- }
-
- /**
- * todo
- * @param dataSetName - name of data set that is loaded from the data set folder e.g. data1.arff (Weka)
- * @param modelID - ID of the model that will be trained with this data set
- * @return
- */
-
- @Override
- public boolean loadDataSet(String dataSetName, int modelID) {
- loadFile = saveFile + dataSetName;
- return false;
- }
-
- /**
- * todo
- * @param modelID - ID of model that will be trained
- * @return
- */
-
- @Override
- public boolean train(int modelID) {
- // Method for the initial training of algorithms and models. That uses external data set for training.
-
- int modelId= modelID;
- String File = loadFile;
- String savefile = saveFile + modelID+".eg";
- File file = new File(File);
- VersatileDataSource source = new CSVDataSource(file, false, CSVFormat.DECIMAL_POINT);
- VersatileMLDataSet data = new VersatileMLDataSet(source);
- data.defineSourceColumn("monat", 0, ColumnType.continuous);
- data.defineSourceColumn("day", 1, ColumnType.continuous);
- data.defineSourceColumn("hour", 2, ColumnType.continuous);
- data.defineSourceColumn("minute", 3, ColumnType.continuous);
- ColumnDefinition outputColumn = data.defineSourceColumn("labels", 4, ColumnType.nominal);
- data.analyze();
- data.defineSingleOutputOthersInput(outputColumn);
- EncogModel model = new EncogModel(data);
- model.selectMethod(data, MLMethodFactory.TYPE_FEEDFORWARD);
- data.normalize();
- model.holdBackValidation(0.3, true, 1001);
- model.selectTrainingType(data);
- MLRegression bestMethod = (MLRegression)model.crossvalidate(5, true);
- NormalizationHelper helper = data.getNormHelper();
- // save network...
- //to delete
- saveObject(new File(savefile), bestMethod);
- Encog.getInstance().shutdown();
-
- return true;
- }
-
- /**
- * todo
- * @param set - data set on which the training is based on
- * @param modelID - ID of model that will be trained
- * @return
- */
-
- @Override
- public boolean train(ArrayList<Integer> set, int modelID) {
- // 1. convert the set into csv data list
- try{
- convertFromArraystoCSV(set, modelID, false);}
- catch(IOException e) {
- e.printStackTrace();
- }
- // 2. load the csv data and data normalize
- String datasetName = String.valueOf(modelID)+".csv";
- loadDataSet(datasetName,modelID);
- // 3. data train and save the Encog model
- train(modelID);
- logger.info("model"+modelID+"has been trained");
- return true;
- }
-
- /**
- * todo
- * @param set - data set on which the retraining is based on
- * @param modelID - ID of the model that will be retrained
- * @return
- */
-
- @Override
- public boolean reTrain(ArrayList<Integer> set, int modelID) {
- // 1. add new data set to the existing data set
- logger.info("model"+modelID+" will be retrained");
- try{
- convertFromArraystoCSV(set, modelID, true);}
- catch(IOException e) {
- e.printStackTrace();
- }
- // 2. data normalize again
- String datasetName = String.valueOf(modelID)+".csv";
- loadDataSet(datasetName,modelID);
- // 3. get new Encog model and save it with the modelID
- train(modelID);
- logger.info("model"+modelID+" has been retrained");
- return true;
- }
-
- /**
- * todo
- * @param modelID - ID of the model of which information are requested from
- * @return
- */
- @Override
- public Model getTrainedModel(int modelID) {
- String file = saveFile + String.valueOf(modelID) + ".eg";
- try (BufferedReader br = new BufferedReader(new FileReader(file))) {
- return getTrainedModel(br, modelID);
- } catch (IOException e) {
- logger.catching(e);
- return null;
- }
- }
-
- @Override
- public Model getTrainedModel(URL url, int modelID) {
- try (BufferedReader br = new BufferedReader(new InputStreamReader(url.openStream()))) {
- return getTrainedModel(br, modelID);
- } catch (IOException e) {
- logger.catching(e);
- return null;
- }
- }
-
- private Model getTrainedModel(BufferedReader reader, int modelID) {
- //TODO
- // read from Encog model file
- //model infos: 1. neutral network type, how many layers, how many neutrons in each layer, weights,
- // activation functions, normalize infos max min ...
- Model model=new Model("NN");
- Integer k = 0;
- ArrayList<Double> weights=new ArrayList<Double>();
- String st;
- String[] split_st;
- String st_part;
- String[] split_st_part;
- try{
- while ((st = reader.readLine()) != null){
-
- if(st.contains("weights")){
- split_st = st.split("=");
- st_part=split_st[1];
- split_st_part=st_part.split(",");
- for (int i = 0; i < (split_st_part.length); i++){
- weights.add(Double.valueOf(split_st_part[i]));
- model.setWeights(weights);
- }
- }
- //layerCounts=4,8,5
- if(st.contains("layerFeedCounts")){
- split_st = st.split("=");
- st_part=split_st[1];
- split_st_part=st_part.split(",");
- if(split_st_part.length==3) {
- int inputLayerNumber=Integer.valueOf(split_st_part[2]);
- int hiddenLayerNumber=Integer.valueOf(split_st_part[1]);
- int outputLayerNumber=Integer.valueOf(split_st_part[0]);
- model.setInputLayerNumber(inputLayerNumber);
- model.setHiddenLayerNumber(hiddenLayerNumber);
- model.setOutputLayerNumber(outputLayerNumber);
- }else{logger.info("oh my god Neutral Network is more than 3 layers");}
- }
- if(st.contains("org")){
- split_st = st.split("\\.");
- st_part=split_st[split_st.length-1];
- split_st_part=st_part.split("\"");
- if(k == 0){
- model.setOutputActivationFunction(split_st_part[0]);
- } else if (k == 1){
- model.setHiddenActivationFunction(split_st_part[0]);
- } else if(k == 2){
- model.setInputActivationFunction(split_st_part[0]);
- }
- k += 1;
- }
- if(st.contains("biasActivation")){
- split_st = st.split("=");
- st_part=split_st[1];
- split_st_part=st_part.split(",");
- if(split_st_part.length==3) {
- int inputBiasNumber=Integer.valueOf(split_st_part[2]);
- int hiddenBiasNumber=Integer.valueOf(split_st_part[1]);
- model.setInputBias(inputBiasNumber);
- model.setHiddenBias(hiddenBiasNumber);
- }else{logger.info("oh my god Neutral Network is more than 3 layers");}
-
- }
- }
- }
- catch(IOException e) {
- e.printStackTrace();
- }
-
- //NormalizationHelper helper= getNormalizer(modelID);
- //model.setNormalizer(helper);
- return model;
- }
-
- /**
- *
- * @param modelID
- * @return
- */
- public ArrayList<Double> getNormalizer(int modelID, ArrayList<Integer> list){
- String File;
- int model_id= modelID;
- if(model_id == 1){
- File=saveFile + "initial_data.csv";
- }else {
- File=saveFile + model_id+".csv";
- }
- File file = new File(File);
- VersatileDataSource source = new CSVDataSource(file, false, CSVFormat.DECIMAL_POINT);
- VersatileMLDataSet data = new VersatileMLDataSet(source);
- data.defineSourceColumn("monat", 0, ColumnType.continuous);
- data.defineSourceColumn("day", 1, ColumnType.continuous);
- data.defineSourceColumn("hour", 2, ColumnType.continuous);
- data.defineSourceColumn("minute", 3, ColumnType.continuous);
- ColumnDefinition outputColumn = data.defineSourceColumn("labels", 4, ColumnType.nominal);
- data.analyze();
- data.defineSingleOutputOthersInput(outputColumn);
- EncogModel model = new EncogModel(data);
- model.selectMethod(data, MLMethodFactory.TYPE_FEEDFORWARD);
- data.normalize();
- NormalizationHelper helper = data.getNormHelper();
-
- ArrayList<Integer> list3 = list;
- String[] line = new String[4];
- MLData input = helper.allocateInputVector();
- line[0] = String.valueOf(list3.get(0));
- line[1] = String.valueOf(list3.get(1));
- line[2] = String.valueOf(list3.get(2));
- line[3] = String.valueOf(list3.get(3));
- helper.normalizeInputVector(line,input.getData(),false);
-
- String helperstr=helper.toString();
- String [] split=helperstr.split(";");
- String [] finalStr = split[split.length-1].replace("]","").replace("[","").
- split(",");
- System.out.println("helperstr:"+ finalStr[0]);
-
- String inputStr=input.toString();
- String str=inputStr.replace("[BasicMLData:","").replace("]","");
- String [] split1 = str.split(",");
- ArrayList<Double> normalizedInputandOuput = new ArrayList<Double> (Arrays.asList(Double.valueOf(split1[0]),
- Double.valueOf(split1[1]), Double.valueOf(split1[2]),Double.valueOf(split1[3]), Double.valueOf(finalStr[0]),
- Double.valueOf(finalStr[1]),Double.valueOf(finalStr[2]), Double.valueOf(finalStr[3])));
- return normalizedInputandOuput;
- }
- /**
- * @param list history values/new values from the system
- * @param modelID ML Model ID
- * @param initial if false, writer will append from the last word of the file
- * @throws IOException
- */
- public void convertFromArraystoCSV(ArrayList<Integer> list, int modelID, boolean initial)throws IOException{
- //create a csv data for store the arrays
- String File = saveFile+ String.valueOf(modelID) + ".csv";
- FileWriter writer= new FileWriter(File, initial);
- for (int i = 0; i < (list.size()/5); i++) {
- writer.append(String.valueOf(list.get(0+i*5)));
- writer.append(',');
- writer.append(String.valueOf(list.get(1+i*5)));
- writer.append(',');
- writer.append(String.valueOf(list.get(2+i*5)));
- writer.append(',');
- writer.append(String.valueOf(list.get(3+i*5)));
- writer.append(',');
- writer.append(String.valueOf(list.get(4+i*5)));
- writer.append('\n');
+public class LearnerImpl implements Learner {
+
+
+ private Root knowledgeBase;
+ private static final Logger logger = LogManager.getLogger(LearnerImpl.class);
+ private Path csvFolderPath = Paths.get("src", "main", "resources");
+ private String modelFolderPath = ".";
+ private CSVFormat format = new CSVFormat('.', ',');
+ private Map<Integer, Dataset> datasets = new HashMap<>();
+ private Map<Integer, Network> models = new HashMap<>();
+
+
+ @Override
+ public void setKnowledgeBase(Root knowledgeBase) {
+ this.knowledgeBase = knowledgeBase;
+ }
+
+ public void setCsvFolderPath(String csvFolderPath) {
+ this.csvFolderPath = Paths.get(csvFolderPath);
+ }
+
+ public void setModelFolderPath(String modelFolderPath) {
+ this.modelFolderPath = modelFolderPath;
+ }
+
+ @Override
+ public boolean loadDataSet(String dataSetName, List<Integer> targetColumns, int modelID) {
+ Path realDataSetPath = csvFolderPath.resolve(dataSetName);
+ logger.debug("Load data set from file {}", realDataSetPath);
+ try {
+ Dataset set = new Dataset(new ReadCSV(realDataSetPath.toFile().getAbsoluteFile(), false, format), targetColumns);
+ datasets.put(modelID, set);
+ } catch (Exception e) {
+ e.printStackTrace();
+ return false;
+ }
+ return true;
+ }
+
+ @Override
+ public boolean loadModelFromFile(File file, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+ logger.debug("Load model from file {}", file);
+ models.put(modelID, new Network(file.getAbsolutePath(), modelID, inputMaxes, inputMins, targetMaxes, targetMins));
+ return true;
+ }
+
+ @Override
+ public boolean loadModelFromFile(InputStream input, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+ logger.debug("Load model from input stream");
+ models.put(modelID, new Network(input, modelID, inputMaxes, inputMins, targetMaxes, targetMins));
+ return true;
+ }
+
+ @Override
+ public boolean train(int inputCount, int outputCount, int hiddenCount, int hiddenNeuronCount, int modelID,
+ List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+ // Method for the initial training of algorithms and models. That uses external data set for training.
+
+ if (datasets.get(modelID) != null) {
+ Dataset set = datasets.get(modelID);
+
+ ReadCSV csv = set.getCsv();
+
+ Network model = new Network(inputCount, outputCount, hiddenCount, hiddenNeuronCount, modelID, inputMaxes,
+ inputMins, targetMaxes, targetMins);
+
+ ArrayList<Double> input = new ArrayList<>();
+ ArrayList<Double> target = new ArrayList<>();
+
+ while (csv.next()) {
+ logger.debug("Train next csv row");
+ for (int i = 0; i < csv.getColumnCount(); i++) {
+ int col_nr = i + 1;
+ if (set.getTargetColumns().contains(col_nr)) {
+ target.add(csv.getDouble(i));
+ } else {
+ input.add(csv.getDouble(i));
+ }
}
- writer.close();
- }
+
+ model.train(input, target);
+ input.clear();
+ target.clear();
+ }
+
+ models.put(modelID, model);
+ model.saveModel(modelFolderPath);
+
+ return true;
+ }
+ return false;
+ }
+
+ @Override
+ public boolean train(double[][] data, int inputCount, int outputCount, int hiddenCount, int hiddenNeuronCount, int modelID,
+ List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins, List<Integer> targetColumns) {
+
+ Network model = new Network(inputCount, outputCount, hiddenCount, hiddenNeuronCount, modelID, inputMaxes,
+ inputMins, targetMaxes, targetMins);
+
+ return reTrainModel(model, data, targetColumns, modelID);
+ }
+
+
+ @Override
+ public boolean reTrain(double[][] data, List<Integer> targetColumns, int modelID) {
+
+ Network model = models.get(modelID);
+
+ return reTrainModel(model, data, targetColumns, modelID);
+ }
+
+ private boolean reTrainModel(Network model, double[][] data, List<Integer> targetColumns, int modelID) {
+ List<Double> input = new ArrayList<>();
+ List<Double> target = new ArrayList<>();
+
+ for (int i = 0; i < data.length; i++) {
+
+ for (int j = 0; j < data[0].length; j++) {
+ int col_nr = j + 1;
+ if (targetColumns.contains(col_nr)) {
+ target.add(data[i][j]);
+ } else {
+ input.add(data[i][j]);
+ }
+
+ model.train(input, target);
+ input.clear();
+ target.clear();
+ }
+
+ }
+
+ models.put(modelID, model);
+ model.saveModel(modelFolderPath);
+
+ return true;
+ }
+
+
+ @Override
+ public EncogModel getTrainedModel(int modelID) {
+ return fillModel(modelID);
+ }
+
+ @Override
+ public EncogModel getTrainedModel(URL url, int modelID) {
+ return fillModel(modelID);
+ }
+
+ private EncogModel fillModel(int modelID) {
+ EncogModel encogModel = new EncogModel("NN");
+ BasicNetwork nn = models.get(modelID).getNetwork();
+
+ ArrayList<Double> weightsList = new ArrayList<>();
+ String weights = nn.dumpWeights();
+ String[] split = weights.split(",");
+
+ for (int i = 0; i < (split.length); i++) {
+ weightsList.add(Double.valueOf(split[i]));
+ }
+
+ encogModel.setWeights(weightsList);
+
+ // do not use getLayers() because it is not restored immediately on load from file
+ FlatNetwork flat = nn.getFlat();
+ List<Layer> layers = new ArrayList<>(flat.getLayerCounts().length);
+ logger.debug("layer counts: {}", Arrays.toString(flat.getLayerCounts()));
+ for (int j = 0; j < flat.getLayerCounts().length; j++) {
+// boolean hasBias = j != 0 && j != flat.getLayerCounts().length - 1;
+ boolean hasBias = flat.getLayerCounts()[j] != flat.getLayerFeedCounts()[j];
+ Layer l = new BasicLayer(flat.getActivationFunctions()[j], hasBias, flat.getLayerCounts()[j]);
+ l.setBiasActivation(flat.getBiasActivation()[j]);
+ layers.add(0, l);
+ }
+
+ encogModel.setLayers(layers);
+
+ return encogModel;
+ }
+
+
+ /**
+ * @param modelID
+ * @return
+ */
+ public NormalizedField getNormalizerInput(int modelID, int columnNr) {
+ return models.get(modelID).getNormalizersIn().get(columnNr);
+ }
+
+ /**
+ * @param modelID
+ * @return
+ */
+ public NormalizedField getNormalizerTar(int modelID, int columnNr) {
+ return models.get(modelID).getNormalizersTar().get(columnNr);
+ }
+
}
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Main.java b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Main.java
index e94f6706ac57ecef13c75a384f20325866cf6884..0f82201e8bcffb278656fb821d6efb3e55008791 100644
--- a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Main.java
+++ b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Main.java
@@ -1,75 +1,95 @@
package de.tudresden.inf.st.eraser.feedbackloop.learner;
import de.tudresden.inf.st.eraser.feedbackloop.api.Learner;
-import de.tudresden.inf.st.eraser.feedbackloop.api.model.*;
+import de.tudresden.inf.st.eraser.feedbackloop.api.EncogModel;
import de.tudresden.inf.st.eraser.jastadd.model.*;
import org.apache.commons.math3.stat.StatUtils;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
-import org.encog.ml.data.MLData;
-import org.encog.ml.data.versatile.NormalizationHelper;
+import java.io.File;
+import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.Arrays;
+import java.util.Collections;
import java.util.List;
-import java.util.concurrent.TimeUnit;
import java.util.function.Function;
-import java.util.stream.Collectors;
+@SuppressWarnings("unused")
public class Main {
private static final Logger logger = LogManager.getLogger(Main.class);
- private static ArrayList<Integer> list1;
- private static ArrayList<Integer> list2;
+ private static class InitialDataConfig {
+ static List<Integer> inputMins = Arrays.asList(
+ 7, // min month
+ 1, // min day
+ 10, // min hour
+ 1 // min minute
+ );
+ static List<Integer> inputMaxes = Arrays.asList(
+ 9, // max month
+ 31, // max day
+ 21, // max hour
+ 60 // max minute
+ );
+ static List<Integer> targetMins = Collections.singletonList(0);
+ static List<Integer> targetMaxes = Collections.singletonList(3);
+ static String csv_filename = "initial_data.csv";
+ static String encog_filename = Paths.get("src", "main", "resources").toFile().getAbsolutePath() + "/";
+ static int inputCount = 4;
+ static int outputCount = 1;
+ static int hiddenCount = 0;
+ static int hiddenNeuronCount = 7;
+ static List<Integer> targetColumns = Collections.singletonList(4);
+ }
public static void main(String[] args) {
+// loadFromCsv();
+ loadFromEncog();
+ }
+ private static void loadFromCsv() {
Learner learner = new LearnerImpl();
- //learner.loadDataSet("initial_data.csv",1);
- //learner.train(1);
-
- Model model = learner.getTrainedModel(1);
-
- ArrayList<Double> weights = model.getWeights();
- int inputLayerNumber = model.getInputLayerNumber();
- int inputBiasNumber = model.getInputBias();
- int hiddenLayerNumber = model.gethiddenLayerNumber();
- int hiddenBiasNumber = model.getHiddenBias();
- int outputLayerNumber = model.getOutputLayerNumber();
- String inputActivation = model.getInputActivationFunction();
- String hiddenActivation = model.getHiddenActivationFunction();
- String outputActivation = model.getOutputActivationFunction();
-
- logger.info("Model Typ is: " + model.getModelType());
- logger.info("Model Weights are: " + model.getWeights());
- logger.info("Model input normal neutrons: " + model.getInputLayerNumber());
- logger.info("Model input bias neutron: " + model.getInputBias());
- logger.info("Model hidden normal neutrons: " + model.gethiddenLayerNumber());
- logger.info("Model hidden bias neutron: " + model.getHiddenBias());
- logger.info("Model output neutrons: " + model.getOutputLayerNumber());
- logger.info("Model input activation function: " + model.getInputActivationFunction());
- logger.info("Model hidden activation function: " + model.getHiddenActivationFunction());
- logger.info("Model output activation function: " + model.getOutputActivationFunction());
- //logger.info("Normalizer helper: " + helper);
-
-
- //TODO create NN eraser Model
- //input from system ??? how to get them?
- ArrayList<Integer> list3 = new ArrayList<Integer>(Arrays.asList(7, 20, 12, 13, 2));
-
- //ArrayList<Integer> list3 = new ArrayList<Integer>(Arrays.asList(7,24,14,38,2));
- //normalize the input data
- ArrayList<Double> normalizedInputandOutput = learner.getNormalizer(1, list3);
- createBrightnessNetwork(weights, inputBiasNumber, hiddenLayerNumber, hiddenBiasNumber, normalizedInputandOutput);
+ learner.loadDataSet(InitialDataConfig.csv_filename, InitialDataConfig.targetColumns,1);
+ learner.train(
+ InitialDataConfig.inputCount, InitialDataConfig.outputCount, InitialDataConfig.hiddenCount,
+ InitialDataConfig.hiddenNeuronCount, 1, InitialDataConfig.inputMaxes, InitialDataConfig.inputMins,
+ InitialDataConfig.targetMaxes, InitialDataConfig.targetMins);
+
+ printModel(learner.getTrainedModel(1));
+ }
+
+ private static void loadFromEncog() {
+ Learner learner = new LearnerImpl();
+ learner.loadModelFromFile(
+ new File(InitialDataConfig.encog_filename), 1,
+ InitialDataConfig.inputMaxes, InitialDataConfig.inputMins,
+ InitialDataConfig.targetMaxes, InitialDataConfig.targetMins);
+ printModel(learner.getTrainedModel(1));
+ NeuralNetworkRoot eraserModel = LearnerHelper.transform(learner.getTrainedModel(1));
+ }
+
+ private static void printModel(EncogModel encogModel) {
+ logger.info("Model Type is: " + encogModel.getModelType());
+ logger.info("Model Weights are: " + encogModel.getWeights());
+ logger.info("Model layers are: " + encogModel.getLayers());
+// logger.info("Model input normal neutrons: " + model.getInputLayerNumber());
+// logger.info("Model input bias neutron: " + model.getInputBias());
+// logger.info("Model hidden normal neutrons: " + model.gethiddenLayerNumber());
+// logger.info("Model hidden bias neutron: " + model.getHiddenBias());
+// logger.info("Model output neutrons: " + model.getOutputLayerNumber());
+// logger.info("Model input activation function: " + model.getInputActivationFunction());
+// logger.info("Model hidden activation function: " + model.getHiddenActivationFunction());
+// logger.info("Model output activation function: " + model.getOutputActivationFunction());
}
//(ArrayList<Integer> list3
private static Root createModel(ArrayList<Double> normalizedInputs, int inputBiasNumber) {
//create KB Model
- Root model = Root.createEmptyRoot();
+ Root root = Root.createEmptyRoot();
Group group = new Group();
group.setID("Group1");
- model.addGroup(group);
+ root.getOpenHAB2Model().addGroup(group);
NumberItem monthItem = new NumberItem();
monthItem.setState(normalizedInputs.get(0));
@@ -102,7 +122,7 @@ public class Main {
group.addItem(dayItem);
group.addItem(hourItem);
group.addItem(minuteItem);
- return model;
+ return root;
}
/**
@@ -110,7 +130,8 @@ public class Main {
*/
private static void createBrightnessNetwork(ArrayList<Double> all_weights, int inputBiasNumber, int hiddenlayernumber,
int hiddenlayerbias, ArrayList<Double> normalizedInputsandOutput) {
- Root model = createModel(normalizedInputsandOutput, inputBiasNumber);
+ Root root = createModel(normalizedInputsandOutput, inputBiasNumber);
+ OpenHAB2Model model = root.getOpenHAB2Model();
Item monthItem = model.resolveItem("month").orElseThrow(
() -> new RuntimeException("Month not found"));
Item dayItem = model.resolveItem("day").orElseThrow(
@@ -200,8 +221,8 @@ public class Main {
hiddenNeuron.connectTo(output3, weights.get(i + hiddenSum * 3));
}
}
- model.getMachineLearningRoot().setPreferenceLearning(nn);
- System.out.println(model.prettyPrint());
+ root.getMachineLearningRoot().setPreferenceLearning(nn);
+ System.out.println(root.prettyPrint());
List<String> output = new ArrayList<>();
Function<DoubleNumber, String> leafToString = classification -> Double.toString(classification.number);
@@ -235,4 +256,4 @@ public class Main {
//outputs:
//[BasicMLData:0.36743405976714366,-0.6610085416169492,-0.9999999998849812,-0.9999999224507112]
- }
\ No newline at end of file
+ }
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Network.java b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Network.java
new file mode 100644
index 0000000000000000000000000000000000000000..e3467c7fda1544befee165d0316f11e9b35e8d27
--- /dev/null
+++ b/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/Network.java
@@ -0,0 +1,202 @@
+package de.tudresden.inf.st.eraser.feedbackloop.learner;
+
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.InputStream;
+import java.util.ArrayList;
+import java.util.List;
+
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+import org.encog.engine.network.activation.ActivationSigmoid;
+import org.encog.ml.data.MLDataSet;
+import org.encog.ml.data.basic.BasicMLDataSet;
+import org.encog.ml.train.MLTrain;
+import org.encog.neural.networks.BasicNetwork;
+import org.encog.neural.networks.layers.BasicLayer;
+import org.encog.neural.networks.training.propagation.back.Backpropagation;
+import org.encog.persist.EncogDirectoryPersistence;
+import org.encog.util.arrayutil.NormalizationAction;
+import org.encog.util.arrayutil.NormalizedField;
+import org.encog.util.simple.EncogUtility;
+
+/**
+ * Network class serves as interface to encog BasicNetwork and holdsfunctions for handling the BasicNetwork (training, input, output and inference)
+ *
+ * @author Bierzynski - initial contribution
+ */
+public class Network {
+ private static final Logger logger = LogManager.getLogger(Network.class);
+ private BasicNetwork network;
+ private int modelID;
+ private ArrayList<NormalizedField> normalizersIn;
+ private ArrayList<NormalizedField> normalizersTar;
+
+ /**
+ * Constructor for when the neural network is created from data.
+ *
+ * @param inputCount number of neurons in the input layer
+ * @param outputCount number of neurons in the output layer
+ * @param hiddenCount number of hidden layers in the network
+ * @param hiddenNeuronCount number of neurons in the hidden layers for now
+ * @param modelID ID of the BasicNetwork.
+ * @param inputMaxes list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes list that contains max values of all output columns (results) e.g. brightness 100 for preference learning
+ * @param targetMins list that contains min values of all output columns (results) e.g. brightness 0 for preference learning
+ */
+ public Network(int inputCount, int outputCount, int hiddenCount, int hiddenNeuronCount, int modelID,
+ List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+
+ normalizersIn = new ArrayList<>();
+ normalizersTar = new ArrayList<>();
+ this.modelID = modelID;
+
+ network = new BasicNetwork();
+
+ network.addLayer(new BasicLayer(null, true, inputCount));
+
+ for (int i = 0; i < hiddenCount; i++) {
+ network.addLayer(new BasicLayer(new ActivationSigmoid(), true, hiddenNeuronCount));
+ }
+
+ network.addLayer(new BasicLayer(new ActivationSigmoid(), false, outputCount));
+ network.getStructure().finalizeStructure();
+ network.reset();
+
+ addNormalizer(inputMaxes, inputMins, normalizersIn);
+ addNormalizer(targetMaxes, targetMins, normalizersTar);
+ }
+
+ private void addNormalizer(List<Integer> maxes, List<Integer> mins, ArrayList<NormalizedField> normalizers) {
+ for (int j = 0; j < maxes.size(); j++) {
+ NormalizedField normalizer = new NormalizedField("in_" + j, NormalizationAction.Normalize,
+ maxes.get(j), mins.get(j));
+ normalizers.add(normalizer);
+ }
+ }
+
+ /**
+ * Constructor for when the neural network is loaded from a file.
+ * Please note that the normalizer are note loaded file , because it is assumed that the mins and maxes are saved anyway in the meta data of the data sets or items.
+ *
+ * @param path path to the save folder of the model files e.g. C:\models\
+ * @param modelID ID of the BasicNetwork.
+ * @param inputMaxes list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes list that contains max values of all output columns (results) e.g. brightness 100 for preference learning
+ * @param targetMins list that contains min values of all output columns (results) e.g. brightness 0 for preference learning
+ */
+ public Network(String path, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+ this(() -> (BasicNetwork) EncogDirectoryPersistence.loadObject(new File(path, "NN_" + modelID)), modelID, inputMaxes, inputMins, targetMaxes, targetMins);
+ }
+
+ /**
+ * Constructor for when the neural network is loaded from an input stream.
+ * Please note that the normalizer are note loaded file , because it is assumed that the mins and maxes are saved anyway in the meta data of the data sets or items.
+ *
+ * @param input stream to load the model from
+ * @param modelID ID of the BasicNetwork.
+ * @param inputMaxes list that contains max values of all input columns (sensors) e.g. light intensity 100
+ * @param inputMins list that contains min values of all input columns (sensors) e.g. light intensity 0
+ * @param targetMaxes list that contains max values of all output columns (results) e.g. brightness 100 for preference learning
+ * @param targetMins list that contains min values of all output columns (results) e.g. brightness 0 for preference learning
+ */
+ public Network(InputStream input, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+ this(() -> (BasicNetwork) EncogDirectoryPersistence.loadObject(input), modelID, inputMaxes, inputMins, targetMaxes, targetMins);
+ }
+
+ private Network(LoadEncogModel loader, int modelID, List<Integer> inputMaxes, List<Integer> inputMins, List<Integer> targetMaxes,
+ List<Integer> targetMins) {
+ this.modelID = modelID;
+
+ normalizersIn = new ArrayList<>();
+ normalizersTar = new ArrayList<>();
+
+ network = loader.load();
+
+ addNormalizer(inputMaxes, inputMins, normalizersIn);
+ addNormalizer(targetMaxes, targetMins, normalizersTar);
+ }
+
+ @FunctionalInterface
+ interface LoadEncogModel {
+ BasicNetwork load();
+ }
+
+ /**
+ * Method to save the trained {@link BasicNetwork} to a file.
+ * File name is always NN_modelID
+ *
+ * @param savePath path to the folder in which the model file should be placed
+ */
+ public void saveModel(String savePath) {
+ EncogDirectoryPersistence.saveObject(new File(savePath + "NN_" + modelID), network);
+ }
+
+ /**
+ * Method for training the {@link BasicNetwork}.
+ * One row training is implemented here for now to optimize preference learning.
+ *
+ * @param input input part of the data row which should be used for training
+ * @param target target/output part of the data row which should be used for training
+ */
+ public void train(List<Double> input, List<Double> target) {
+ double[][] INPUT = new double[1][input.size()];
+ double[][] IDEAL = new double[1][target.size()];
+
+ for (int i = 0; i < input.size(); i++) {
+ INPUT[0][i] = normalizersIn.get(i).normalize(input.get(i));
+ }
+
+ for (int j = 0; j < target.size(); j++) {
+ IDEAL[0][j] = normalizersTar.get(j).normalize(target.get(j));
+ }
+
+ MLDataSet trainingSet = new BasicMLDataSet(INPUT, IDEAL);
+ MLTrain train = new Backpropagation(network, trainingSet, 3.5, 0.3);
+
+ do {
+ train.iteration();
+ } while (train.getError() > 0.005);
+
+ train.finishTraining();
+ }
+
+ /**
+ * Method that uses the {@link BasicNetwork} to predict/classify/.. something based on an input.
+ *
+ * @param inputVector data that should be processed
+ */
+ public double[] computeResult(List<Double> inputVector) {
+ double[] output = new double[normalizersTar.size()];
+ double[] input = new double[inputVector.size()];
+
+ for (int i = 0; i < inputVector.size(); i++) {
+ input[i] = normalizersIn.get(i).normalize(inputVector.get(i));
+ }
+
+ network.compute(input, output);
+
+ for (int j = 0; j < normalizersTar.size(); j++) {
+ output[j] = normalizersTar.get(j).deNormalize(output[j]);
+ }
+
+ return output;
+ }
+
+ public BasicNetwork getNetwork() {
+ return network;
+ }
+
+ public ArrayList<NormalizedField> getNormalizersIn() {
+ return normalizersIn;
+ }
+
+ public ArrayList<NormalizedField> getNormalizersTar() {
+ return normalizersTar;
+ }
+}
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/1.eg b/feedbackloop.learner/src/main/resources/1.eg
similarity index 100%
rename from feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/1.eg
rename to feedbackloop.learner/src/main/resources/1.eg
diff --git a/feedbackloop.learner/src/main/resources/NN_1 b/feedbackloop.learner/src/main/resources/NN_1
new file mode 120000
index 0000000000000000000000000000000000000000..c47a1c155ec39abc4357baa43dbafad60eb2988a
--- /dev/null
+++ b/feedbackloop.learner/src/main/resources/NN_1
@@ -0,0 +1 @@
+1.eg
\ No newline at end of file
diff --git a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/initial_data.csv b/feedbackloop.learner/src/main/resources/initial_data.csv
similarity index 92%
rename from feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/initial_data.csv
rename to feedbackloop.learner/src/main/resources/initial_data.csv
index a1e263194d3ee4f95c64c3eff3b5123fb2246cf5..12c125ce2bbdc9ec6bb9762f05f6a83c3b863bb0 100644
--- a/feedbackloop.learner/src/main/java/de/tudresden/inf/st/eraser/feedbackloop/learner/initial_data.csv
+++ b/feedbackloop.learner/src/main/resources/initial_data.csv
@@ -1,418 +1,418 @@
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+8,3,13,31,2
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+8,4,13,20,2
+8,4,18,27,3
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+8,5,18,33,3
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+8,9,13,32,2
+8,9,13,32,2
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+8,9,15,8,2
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+8,12,12,27,1
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+8,12,13,53,2
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+8,13,13,16,1
+8,13,13,16,1
+8,13,14,14,2
+8,13,14,14,2
+8,13,16,11,3
+8,13,17,18,3
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+8,14,13,7,1
+8,14,13,7,1
+8,14,13,7,1
+8,14,13,7,2
+8,14,13,7,2
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+8,15,14,5,2
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+8,16,13,40,2
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+8,17,13,34,1
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+8,22,12,4,2
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+8,22,13,51,2
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+8,23,13,42,1
+8,23,17,32,3
+8,23,19,28,3
+8,23,20,27,3
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+8,25,13,34,1
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+8,26,18,41,3
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+8,27,13,41,2
+8,27,13,41,2
+8,27,13,41,2
+8,27,17,42,3
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+8,28,11,9,1
+8,28,12,14,0
+8,28,12,14,1
+8,28,12,14,0
+8,28,15,3,2
+8,28,15,3,2
+8,28,16,31,3
+8,28,17,40,3
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+8,30,13,32,1
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+8,31,14,31,2
+8,31,14,31,2
+8,31,14,31,2
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+9,2,13,44,1
+9,2,13,44,1
+9,2,14,49,2
+9,2,14,49,2
+9,2,14,49,2
+9,2,16,6,3
+9,2,16,6,3
+9,2,17,2,3
+9,3,16,9,3
+9,3,17,35,3
+9,3,17,36,3
+9,4,12,57,1
+9,4,12,57,1
+9,4,15,8,3
+9,4,15,34,3
+9,4,16,26,3
+9,4,16,26,3
+9,4,18,37,3
+9,4,18,37,3
+9,4,18,37,3
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+9,6,11,18,0
+9,6,12,54,1
+9,6,12,54,1
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+9,6,14,21,2
+9,6,19,20,3
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+9,8,12,1,0
+9,8,12,1,0
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+9,17,11,10,0
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+9,17,12,43,1
+9,17,12,43,1
+9,17,13,32,1
+9,17,13,32,1
+9,17,14,5,1
+9,17,14,5,2
+9,17,14,6,2
+9,17,15,7,3
+9,17,15,49,3
+9,17,15,49,3
+9,17,18,12,3
+9,17,18,13,3
diff --git a/feedbackloop.learner/src/main/resources/log4j2.xml b/feedbackloop.learner/src/main/resources/log4j2.xml
index 481178a66aaaf356ef87241bf07871f4e808c3ee..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.learner/src/main/resources/log4j2.xml
+++ b/feedbackloop.learner/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
@@ -19,4 +19,4 @@
<AppenderRef ref="RollingFile"/>
</Root>
</Loggers>
-</Configuration>
\ No newline at end of file
+</Configuration>
diff --git a/feedbackloop.main/build.gradle b/feedbackloop.main/build.gradle
index 2287b7b94c161ad8a3268ca9d751e1c1e2137e88..c5a11eda0213af9b519a5c8df62de30e8dc6b059 100644
--- a/feedbackloop.main/build.gradle
+++ b/feedbackloop.main/build.gradle
@@ -14,11 +14,6 @@ dependencies {
compile project(':feedbackloop.analyze')
compile project(':feedbackloop.plan')
compile project(':feedbackloop.execute')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
run {
diff --git a/feedbackloop.main/src/main/resources/log4j2.xml b/feedbackloop.main/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.main/src/main/resources/log4j2.xml
+++ b/feedbackloop.main/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/feedbackloop.monitor/build.gradle b/feedbackloop.monitor/build.gradle
index 77b9513097ddb84f3d1e003489bade769e38c4a7..6b73819fad70219d9bb7465e0b3c903352bc76d7 100644
--- a/feedbackloop.monitor/build.gradle
+++ b/feedbackloop.monitor/build.gradle
@@ -10,11 +10,6 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
compile project(':feedbackloop.api')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
run {
diff --git a/feedbackloop.monitor/src/main/resources/log4j2.xml b/feedbackloop.monitor/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.monitor/src/main/resources/log4j2.xml
+++ b/feedbackloop.monitor/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/feedbackloop.plan/build.gradle b/feedbackloop.plan/build.gradle
index 2a9ac05f8f3beb83fab66354c598d27ca84bb4b7..81156210881de5442bc7d1f79e3dcefdf51c042a 100644
--- a/feedbackloop.plan/build.gradle
+++ b/feedbackloop.plan/build.gradle
@@ -10,11 +10,6 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
compile project(':feedbackloop.api')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
run {
diff --git a/feedbackloop.plan/src/main/resources/log4j2.xml b/feedbackloop.plan/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/feedbackloop.plan/src/main/resources/log4j2.xml
+++ b/feedbackloop.plan/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/influx_test/build.gradle b/influx_test/build.gradle
index fcb387f503c0960fee15af9ffbc5913d536bcb07..ead9dcee7f559d5c2ae9a472c8c09096692af3b2 100644
--- a/influx_test/build.gradle
+++ b/influx_test/build.gradle
@@ -9,13 +9,7 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- compile 'org.influxdb:influxdb-java:2.14'
-
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
+ compile group: 'org.influxdb', name: 'influxdb-java', version: '2.15'
}
run {
diff --git a/influx_test/src/main/resources/log4j2.xml b/influx_test/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/influx_test/src/main/resources/log4j2.xml
+++ b/influx_test/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/integration/build.gradle b/integration/build.gradle
index 47be63191b320dce8ea7c0673b15943a1496b634..584eb25249ba3c44c928d77ac7a9368d0890daad 100644
--- a/integration/build.gradle
+++ b/integration/build.gradle
@@ -19,7 +19,4 @@ run {
dependencies {
compile project(':eraser-base')
compile project(':openhab-mock')
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
}
diff --git a/integration/src/main/java/de/tudresden/inf/st/eraser/integration/IntegrationMain.java b/integration/src/main/java/de/tudresden/inf/st/eraser/integration/IntegrationMain.java
index a7ca2904072ea46e0a0243fd7bc47328729a55c4..3418238f3572595c4a9640369767a1d34d037920 100644
--- a/integration/src/main/java/de/tudresden/inf/st/eraser/integration/IntegrationMain.java
+++ b/integration/src/main/java/de/tudresden/inf/st/eraser/integration/IntegrationMain.java
@@ -79,17 +79,14 @@ public class IntegrationMain {
logger.info("Start!");
Root model = Main.importFromFile();
// Root model = importFromLocalFile();
- logger.debug("Got model: {}", model.description());
+ logger.debug("Got model: {}", model.getOpenHAB2Model().description());
MqttRoot mqttRoot = new MqttRoot();
mqttRoot.setHostByName("localhost");
mqttRoot.setIncomingPrefix("oh2/out/");
- MqttTopic irisTopic = new MqttTopic();
- irisTopic.setPart("iris1_item");
MqttTopic irisStateTopic = new MqttTopic();
- irisStateTopic.setPart("state");
- irisTopic.addSubTopic(irisStateTopic);
+ irisStateTopic.setTopicString("iris1_item/state");
Item iris = null;
- for (Item item : model.items()) {
+ for (Item item : model.getOpenHAB2Model().items()) {
if (item.getID().equals("iris1_item")) {
iris = item;
break;
@@ -99,8 +96,7 @@ public class IntegrationMain {
logger.error("Could not find iris1. Exiting");
return;
}
- irisStateTopic.setItem(iris);
- mqttRoot.addTopic(irisTopic);
+ irisStateTopic.addItem(iris);
model.setMqttRoot(mqttRoot);
// JsonSerializer.write(model, "src/main/resources/openhab2-data.json");
JsonSerializer.write(model, "openhab2-data.json");
diff --git a/ml_test/build.gradle b/ml_test/build.gradle
index 241f853811b83bf6161c9e98efc0a22ec1ba64f2..2d500200789d52e56de89a77d453c6af7ae6d49b 100644
--- a/ml_test/build.gradle
+++ b/ml_test/build.gradle
@@ -9,11 +9,6 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
run {
diff --git a/ml_test/src/main/java/de/tudresden/inf/st/eraser/ml_test/Main.java b/ml_test/src/main/java/de/tudresden/inf/st/eraser/ml_test/Main.java
index d17b6c97dc647e9faebfb1fd1ca9b4450fef4725..59c156853782b8e58010d24393e7c14c73ffefb8 100644
--- a/ml_test/src/main/java/de/tudresden/inf/st/eraser/ml_test/Main.java
+++ b/ml_test/src/main/java/de/tudresden/inf/st/eraser/ml_test/Main.java
@@ -23,15 +23,15 @@ public class Main {
}
private static Root createModel() {
- Root model = Root.createEmptyRoot();
+ Root root = Root.createEmptyRoot();
Group group = new Group();
group.setID("Group1");
- model.addGroup(group);
+ root.getOpenHAB2Model().addGroup(group);
Item activityItem = newItem("activity", "Recognized activity", false, 8);
Item brightnessItem = newItem("brightness", "Measured brightness", false, 5);
group.addItem(activityItem);
group.addItem(brightnessItem);
- return model;
+ return root;
}
private static NumberItem newItem(String id, String label, boolean defaultSendState, int initialState) {
@@ -70,7 +70,7 @@ public class Main {
}
}
logger.info("Classification results: {}", results);
- logger.info("Took {}ms", String.join("ms, ", times.stream().map(l -> Long.toString(l)).collect(Collectors.toList())));
+ logger.info("Took {}ms", times.stream().map(l -> Long.toString(l)).collect(Collectors.joining("ms, ")));
logger.info("Took on average: {}ms",
Arrays.stream(times.toArray(new Long[0])).mapToLong(l -> l).average().orElse(-1));
logger.info("Took on median: {}ms",
@@ -78,30 +78,36 @@ public class Main {
.skip((REPETITIONS-1)/2).limit(2-REPETITIONS%2).average().orElse(Double.NaN));
}
- /**
- * Purpose: Create a neural network with 3 layers (2 + 10 + 1 neurons)
- * Sigmoid function for all layers, combinator of output is identity function
- */
- private static void createAndTestBrightnessNetwork() {
- /*
- - Helligkeit NN:
- - arbeitet momentan mit Zonen und nicht mit einzelnen Lampen
- - 3 Layers
- - Input Layer hat Neuronen (Aktivitätsnummer, Wert vom Helligkeitssensor)
- - Hidden Layer hat 10 Neuronen
- - Output Layer hat 1 Neuron ( Helligkeitswert)
- - Aktivierungsfunktion: Sigmoidfunktion <- selbe für alle Layers
- */
- Root model = createModel();
- Item activityItem = model.resolveItem("activity").orElseThrow(
+ private static class PreparationResult {
+ OutputLayer outputLayer;
+ DoubleArrayDoubleFunction sigmoid;
+ InputNeuron activity;
+ InputNeuron brightness;
+ NeuralNetworkRoot nn;
+ HiddenNeuron[] hiddenNeurons;
+
+ PreparationResult(OutputLayer outputLayer, DoubleArrayDoubleFunction sigmoid, InputNeuron activity,
+ InputNeuron brightness, NeuralNetworkRoot nn, HiddenNeuron[] hiddenNeurons) {
+ this.outputLayer = outputLayer;
+ this.sigmoid = sigmoid;
+ this.activity = activity;
+ this.brightness = brightness;
+ this.nn = nn;
+ this.hiddenNeurons = hiddenNeurons;
+ }
+ }
+
+ private static PreparationResult prepareNetwork() {
+ Root root = createModel();
+ Item activityItem = root.getOpenHAB2Model().resolveItem("activity").orElseThrow(
() -> new RuntimeException("Activity not found"));
- Item brightnessItem = model.resolveItem("brightness").orElseThrow(
+ Item brightnessItem = root.getOpenHAB2Model().resolveItem("brightness").orElseThrow(
() -> new RuntimeException("Brightness not found"));
NeuralNetworkRoot nn = new NeuralNetworkRoot();
DoubleArrayDoubleFunction sigmoid = inputs -> Math.signum(Arrays.stream(inputs).sum());
- // input layer
+ // input layer (2 neurons)
InputNeuron activity = new InputNeuron();
activity.setItem(activityItem);
InputNeuron brightness = new InputNeuron();
@@ -109,31 +115,50 @@ public class Main {
nn.addInputNeuron(activity);
nn.addInputNeuron(brightness);
- // output layer
OutputLayer outputLayer = new OutputLayer();
- OutputNeuron output = new OutputNeuron();
- output.setLabel("Brightness_Output");
- output.setActivationFormula(sigmoid);
- outputLayer.addOutputNeuron(output);
- // we just have one output neuron, thus use IdentityFunction
- outputLayer.setCombinator(inputs -> inputs[0]);
nn.setOutputLayer(outputLayer);
- // hidden layer
+ // hidden layer (10 neurons)
HiddenNeuron[] hiddenNeurons = new HiddenNeuron[10];
- for (int i = 0; i < hiddenNeurons.length; i++) {
+ for (int hiddenIndex = 0; hiddenIndex < hiddenNeurons.length; hiddenIndex++) {
HiddenNeuron hiddenNeuron = new HiddenNeuron();
hiddenNeuron.setActivationFormula(sigmoid);
- hiddenNeurons[i] = hiddenNeuron;
nn.addHiddenNeuron(hiddenNeuron);
activity.connectTo(hiddenNeuron, 1.0/2.0);
brightness.connectTo(hiddenNeuron, 1.0/2.0);
- hiddenNeuron.connectTo(output, 1.0/hiddenNeurons.length);
}
+ root.getMachineLearningRoot().setPreferenceLearning(nn);
- model.getMachineLearningRoot().setPreferenceLearning(nn);
+ return new PreparationResult(outputLayer, sigmoid, activity, brightness, nn, hiddenNeurons);
+ }
- classifyTimed(nn, NeuralNetworkRoot::classify,
+ /**
+ * Purpose: Create a neural network with 3 layers (2 + 10 + 1 neurons)
+ * Sigmoid function for all layers, combinator of output is identity function
+ */
+ private static void createAndTestBrightnessNetwork() {
+ /*
+ - Helligkeit NN:
+ - arbeitet momentan mit Zonen und nicht mit einzelnen Lampen
+ - 3 Layers
+ - Input Layer hat Neuronen (Aktivitätsnummer, Wert vom Helligkeitssensor)
+ - Hidden Layer hat 10 Neuronen
+ - Output Layer hat 1 Neuron ( Helligkeitswert)
+ - Aktivierungsfunktion: Sigmoidfunktion <- selbe für alle Layers
+ */
+ PreparationResult pr = prepareNetwork();
+ OutputNeuron output = new OutputNeuron();
+ output.setLabel("Brightness_Output");
+ output.setActivationFormula(pr.sigmoid);
+ pr.outputLayer.addOutputNeuron(output);
+ // we just have one output neuron, thus use IdentityFunction
+ pr.outputLayer.setCombinator(inputs -> inputs[0]);
+
+ for (HiddenNeuron hiddenNeuron : pr.hiddenNeurons) {
+ hiddenNeuron.connectTo(output, 1.0/pr.hiddenNeurons.length);
+ }
+
+ classifyTimed(pr.nn, NeuralNetworkRoot::classify,
classification -> Double.toString(classification.number));
}
@@ -142,52 +167,23 @@ public class Main {
* Sigmoid function for all layers, combinator creates RGB value in hex form
*/
private static void createAndTestColorNetwork() {
- Root model = createModel();
- Item activityItem = model.resolveItem("activity").orElseThrow(
- () -> new RuntimeException("Activity not found"));
- Item brightnessItem = model.resolveItem("brightness").orElseThrow(
- () -> new RuntimeException("Brightness not found"));
- NeuralNetworkRoot nn = new NeuralNetworkRoot();
-
- DoubleArrayDoubleFunction sigmoid = inputs -> Math.signum(Arrays.stream(inputs).sum());
-
- // input layer (2 neurons)
- InputNeuron activity = new InputNeuron();
- activity.setItem(activityItem);
- InputNeuron brightness = new InputNeuron();
- brightness.setItem(brightnessItem);
- nn.addInputNeuron(activity);
- nn.addInputNeuron(brightness);
-
- // output layer (3 neurons)
- OutputLayer outputLayer = new OutputLayer();
+ PreparationResult pr = prepareNetwork();
for (int i = 0; i < 3; i++) {
OutputNeuron output = new OutputNeuron();
output.setLabel("Brightness_Output_" + i);
output.setActivationFormula(inputs -> Arrays.stream(inputs).sum());
- outputLayer.addOutputNeuron(output);
+ pr.outputLayer.addOutputNeuron(output);
}
// we have three output neurons, combine them to a double value (representing RGB)
- outputLayer.setCombinator(inputs -> 65536 * Math.ceil(255.0 * inputs[0]) + 256 * Math.ceil(255.0 * inputs[1]) + Math.ceil(255.0 * inputs[0]));
- nn.setOutputLayer(outputLayer);
+ pr.outputLayer.setCombinator(inputs -> 65536 * Math.ceil(255.0 * inputs[0]) + 256 * Math.ceil(255.0 * inputs[1]) + Math.ceil(255.0 * inputs[0]));
- // hidden layer (10 neurons)
- HiddenNeuron[] hiddenNeurons = new HiddenNeuron[10];
- for (int hiddenIndex = 0; hiddenIndex < hiddenNeurons.length; hiddenIndex++) {
- HiddenNeuron hiddenNeuron = new HiddenNeuron();
- hiddenNeuron.setActivationFormula(sigmoid);
- hiddenNeurons[hiddenIndex] = hiddenNeuron;
- nn.addHiddenNeuron(hiddenNeuron);
- activity.connectTo(hiddenNeuron, 1.0/2.0);
- brightness.connectTo(hiddenNeuron, 1.0/2.0);
- for (int outputIndex = 0; outputIndex < outputLayer.getNumOutputNeuron(); outputIndex++) {
- hiddenNeuron.connectTo(outputLayer.getOutputNeuron(outputIndex), random.nextDouble() * 1.0/hiddenNeurons.length);
+ for (HiddenNeuron hiddenNeuron : pr.hiddenNeurons) {
+ for (int outputIndex = 0; outputIndex < pr.outputLayer.getNumOutputNeuron(); outputIndex++) {
+ hiddenNeuron.connectTo(pr.outputLayer.getOutputNeuron(outputIndex), random.nextDouble() * 1.0/pr.hiddenNeurons.length);
}
}
- model.getMachineLearningRoot().setPreferenceLearning(nn);
-
- classifyTimed(nn, NeuralNetworkRoot::classify,
+ classifyTimed(pr.nn, NeuralNetworkRoot::classify,
classification -> Double.toHexString(classification.number));
// long before = System.nanoTime();
diff --git a/ml_test/src/main/resources/log4j2.xml b/ml_test/src/main/resources/log4j2.xml
index a5132e32502bf95c14ac0e6e50c2185325643ca7..686c2a889038bd7e7d89928939edfd09a5f15a94 100644
--- a/ml_test/src/main/resources/log4j2.xml
+++ b/ml_test/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/openhab-mock/build.gradle b/openhab-mock/build.gradle
index 94017c3d7308df49f404a1c49203b807fa4a5ef7..4de21c3b36c9d837c46aaf3245c86ad2b717d91a 100644
--- a/openhab-mock/build.gradle
+++ b/openhab-mock/build.gradle
@@ -19,9 +19,5 @@ run {
dependencies {
compile project(':eraser-base')
compile project(':commons.color')
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- compile 'com.opencsv:opencsv:3.8'
- compile 'org.apache.commons:commons-math3:3.6.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
+ compile group: 'com.opencsv', name: 'opencsv', version: '3.8'
}
diff --git a/openhab-mock/src/main/resources/log4j2.xml b/openhab-mock/src/main/resources/log4j2.xml
index 89799a2f09ba34d288e610d960b3ed6348213105..18175a02521156259c8789745fb849fa893302e9 100644
--- a/openhab-mock/src/main/resources/log4j2.xml
+++ b/openhab-mock/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/org.openhab.action.machinelearn/build.gradle b/org.openhab.action.machinelearn/build.gradle
index 12d6d1e875fee2da8bb334ebcf14e95d9e3c66af..0ca194823aeeff40aa1de7f6da6c61896ff63e5b 100644
--- a/org.openhab.action.machinelearn/build.gradle
+++ b/org.openhab.action.machinelearn/build.gradle
@@ -5,31 +5,16 @@ repositories {
sourceCompatibility = 1.8
apply plugin: 'java'
-//apply plugin: 'application'
dependencies {
compile files('lib/weka.jar')
compile project(':stub.org.openhab.core.scriptengine.action')
-// compile 'org.apache.commons:commons-lang3:3.8.1'
-// compile group: 'org.eclipse.jdt', name: 'org.eclipse.jdt.annotation', version: '2.0.0'
-// compile 'org.openhab.core.library.types'
-// compile 'org.openhab.core.scriptengine.action'
compile group: 'org.osgi', name: 'org.osgi.framework', version: '1.9.0'
compile group: 'org.osgi', name: 'org.osgi.service.cm', version: '1.6.0'
compile group: 'org.osgi', name: 'org.osgi.service.component', version: '1.4.0'
compile group: 'org.slf4j', name: 'slf4j-api', version: '1.7.25'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
-//run {
-// mainClassName = 'de.tudresden.inf.st.eraser.skywriter_hue_integration.Main'
-// standardInput = System.in
-// if (project.hasProperty("appArgs")) {
-// args Eval.me(appArgs)
-// }
-//}
-
sourceSets {
main {
java {
diff --git a/org.openlicht.action.reinforcementlearning/build.gradle b/org.openlicht.action.reinforcementlearning/build.gradle
index 54e1daf916b41766a9c4dc961e365040744ff608..66417e5da744784dfcb590357db19eaa1ce14bd6 100644
--- a/org.openlicht.action.reinforcementlearning/build.gradle
+++ b/org.openlicht.action.reinforcementlearning/build.gradle
@@ -10,16 +10,11 @@ apply plugin: 'java'
dependencies {
compile files('lib/encog-core-3.4.jar')
compile project(':stub.org.openhab.core.scriptengine.action')
- compile 'org.apache.commons:commons-lang3:3.8.1'
compile group: 'org.eclipse.jdt', name: 'org.eclipse.jdt.annotation', version: '2.2.200'
-// compile 'org.openhab.core.library.types'
-// compile 'org.openhab.core.scriptengine.action'
compile group: 'org.osgi', name: 'org.osgi.framework', version: '1.9.0'
compile group: 'org.osgi', name: 'org.osgi.service.cm', version: '1.6.0'
compile group: 'org.osgi', name: 'org.osgi.service.component', version: '1.4.0'
compile group: 'org.slf4j', name: 'slf4j-api', version: '1.7.25'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
sourceSets {
diff --git a/project-template/build.gradle b/project-template/build.gradle
index 9cb094bf6e4b76641f50f823f9f526b8c8ba7657..09e63423457a9994046774fcc0d5bf657b04db01 100644
--- a/project-template/build.gradle
+++ b/project-template/build.gradle
@@ -10,8 +10,8 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
+ compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.2'
+ compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.2'
testCompile group: 'junit', name: 'junit', version: '4.12'
testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
diff --git a/project-template/src/main/resources/log4j2.xml b/project-template/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/project-template/src/main/resources/log4j2.xml
+++ b/project-template/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/skywriter-hue-integration/build.gradle b/skywriter-hue-integration/build.gradle
index ab64e3d71e5b0b3c4e5939b2ffa387718e05a242..37bb2da071e8fe7cce1f769168cf33cddced3e32 100644
--- a/skywriter-hue-integration/build.gradle
+++ b/skywriter-hue-integration/build.gradle
@@ -10,11 +10,6 @@ apply plugin: 'application'
dependencies {
compile project(':eraser-base')
compile project(':commons.color')
- compile group: 'com.fasterxml.jackson.core', name: 'jackson-databind', version: '2.9.8'
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
}
run {
diff --git a/skywriter-hue-integration/src/main/java/de/tudresden/inf/st/eraser/skywriter_hue_integration/Main.java b/skywriter-hue-integration/src/main/java/de/tudresden/inf/st/eraser/skywriter_hue_integration/Main.java
index f6769cb625d1b914f54f6f377500166e61c1f9a9..3f64c8cdd3c530d8a287a0d3ce0d140f449c5921 100644
--- a/skywriter-hue-integration/src/main/java/de/tudresden/inf/st/eraser/skywriter_hue_integration/Main.java
+++ b/skywriter-hue-integration/src/main/java/de/tudresden/inf/st/eraser/skywriter_hue_integration/Main.java
@@ -3,10 +3,7 @@ package de.tudresden.inf.st.eraser.skywriter_hue_integration;
import beaver.Parser;
import de.tudresden.inf.st.eraser.commons.color.ColorUtils;
import de.tudresden.inf.st.eraser.commons.color.ColorUtils.RGBvalues;
-import de.tudresden.inf.st.eraser.jastadd.model.Item;
-import de.tudresden.inf.st.eraser.jastadd.model.Root;
-import de.tudresden.inf.st.eraser.jastadd.model.Rule;
-import de.tudresden.inf.st.eraser.jastadd.model.SetStateFromItemsAction;
+import de.tudresden.inf.st.eraser.jastadd.model.*;
import de.tudresden.inf.st.eraser.openhab2.mqtt.MQTTUpdater;
import de.tudresden.inf.st.eraser.util.ParserUtils;
import org.apache.logging.log4j.LogManager;
@@ -39,7 +36,8 @@ public class Main {
@SuppressWarnings("ResultOfMethodCallIgnored")
public static void main(String[] args) throws IOException, Parser.Exception {
// use openHAB-eraser-connection to update hue (automatically done)
- Root model = ParserUtils.load("skywriter-hue.eraser", Main.class);
+ Root root = ParserUtils.load("skywriter-hue.eraser", Main.class);
+ OpenHAB2Model model = root.getOpenHAB2Model();
Item irisItem = model.resolveItem("iris1_item").orElseThrow(() ->
new NoSuchElementException("Iris1_item not found"));
Item skywriter1_x = model.resolveItem("skywriter1_x").orElseThrow(() ->
@@ -48,10 +46,10 @@ public class Main {
new NoSuchElementException("Skywriter1 y not found"));
Item skywriter1_xyz = model.resolveItem("skywriter1_xyz").orElseThrow(() ->
new NoSuchElementException("Skywriter1 xyz not found"));
- System.out.println(model.prettyPrint());
+ System.out.println(root.prettyPrint());
// define rule to switch color, based on xyz-to-rgb-to-hsb mapping
Rule mapXYtoIrisState = new Rule();
- model.addRule(mapXYtoIrisState);
+ root.addRule(mapXYtoIrisState);
mapXYtoIrisState.activateFor(skywriter1_xyz);
// mapXYtoIrisState.addEventFor(skywriter1_y, "y changed");
SetStateFromItemsAction action = new SetStateFromItemsAction();
@@ -64,7 +62,7 @@ public class Main {
Lock abortLock = new ReentrantLock();
Condition abortCondition = abortLock.newCondition();
Thread readFromOpenHABThread = new Thread(() -> {
- try (MQTTUpdater updater = new MQTTUpdater(model)) {
+ try (MQTTUpdater updater = new MQTTUpdater(root)) {
updater.start();
if (!updater.waitUntilReady(3, TimeUnit.SECONDS)) {
logger.error("openHAB reader not ready. Aborting.");
@@ -84,7 +82,7 @@ public class Main {
}
});
if (USE_READ_FROM_OPENHAB || SEND_TO_OPENHAB) {
- model.getMqttRoot().setHostByName(MQTT_HOST);
+ root.getMqttRoot().setHostByName(MQTT_HOST);
}
if (USE_READ_FROM_OPENHAB) {
readFromOpenHABThread.start();
@@ -124,7 +122,7 @@ public class Main {
}
// wait for user to press enter
- System.out.println("Press [Enter] to quit updating the model.");
+ System.out.println("Press [Enter] to quit updating the root.");
System.in.read();
// and then cancel the threads
diff --git a/skywriter-hue-integration/src/main/resources/log4j2.xml b/skywriter-hue-integration/src/main/resources/log4j2.xml
index 5c534092d64e9c1834c2ba20208c057e2b56be16..5d1091ea995c881e5985a0cfc925a952ff50d0bc 100644
--- a/skywriter-hue-integration/src/main/resources/log4j2.xml
+++ b/skywriter-hue-integration/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>
diff --git a/stub.org.openhab.core.scriptengine.action/build.gradle b/stub.org.openhab.core.scriptengine.action/build.gradle
index e2b54c7a70609c315c5b529678bdfb6cc2d8b461..2f5043786a9064ac0c84ffe10ab32a6d01940398 100644
--- a/stub.org.openhab.core.scriptengine.action/build.gradle
+++ b/stub.org.openhab.core.scriptengine.action/build.gradle
@@ -6,13 +6,6 @@ sourceCompatibility = 1.8
apply plugin: 'java'
-dependencies {
- compile group: 'org.apache.logging.log4j', name: 'log4j-api', version: '2.11.1'
- compile group: 'org.apache.logging.log4j', name: 'log4j-core', version: '2.11.1'
- testCompile group: 'junit', name: 'junit', version: '4.12'
- testCompile group: 'org.hamcrest', name: 'hamcrest-junit', version: '2.0.0.0'
-}
-
sourceSets {
main {
java {
diff --git a/stub.org.openhab.core.scriptengine.action/src/main/resources/log4j2.xml b/stub.org.openhab.core.scriptengine.action/src/main/resources/log4j2.xml
index 0594576fac98ba859e411597c90c8e3d989378bd..867ec439d0a32dcb5f8b3e2d0c7485d7d8da418c 100644
--- a/stub.org.openhab.core.scriptengine.action/src/main/resources/log4j2.xml
+++ b/stub.org.openhab.core.scriptengine.action/src/main/resources/log4j2.xml
@@ -4,8 +4,8 @@
<Console name="Console">
<PatternLayout pattern="%highlight{%d{HH:mm:ss.SSS} %-5level} %c{1.} - %msg%n"/>
</Console>
- <RollingFile name="RollingFile" fileName="logs/jastadd-mquat.log"
- filePattern="logs/jastadd-mquat-%i.log">
+ <RollingFile name="RollingFile" fileName="logs/eraser.log"
+ filePattern="logs/eraser-%i.log">
<PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %logger{36} - %msg%n"/>
<Policies>
<OnStartupTriggeringPolicy/>