Documentation edits (#186)

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

* Edits supporting the modeling quide

---------

Co-authored-by: Shawn <[email protected]>

gcm/src/main/java/gov/hhs/aspr/ms/gcm/plugins/partitions/support/PartitionError.java

@@ -9,23 +9,30 @@
  */
 public enum PartitionError implements ContractError {
 
- PAST_LABEL_FAILURE("A labeler has failed to properly identify a person's past label from an event"),
- DUPLICATE_PARTITION("Duplicate partition key"), NON_DEGENERATE_PARTITION("Requires a degenerate partition"),
+ PAST_LABEL_FAILURE("A labeler has failed to properly identify a person's past label from an event"),//
+ DUPLICATE_PARTITION("Duplicate partition key"),//
+ NON_DEGENERATE_PARTITION("Requires a degenerate partition"),//
  INCOMPATIBLE_LABEL_SET("The label set is incompatible with the selected population partition definition"),
  MALFORMED_PARTITION_SAMPLE_WEIGHTING_FUNCTION(
- "Data used to form an enumerated distribution for partition sampling was malformed"),
+ "Data used to form an enumerated distribution for partition sampling was malformed"),//
  NULL_LABEL_SET_FUNCTION("Null labelset function"),
  RESERVED_PARTITION_TRIGGER(
- "An event class is being used to trigger refreshes as part of a partition that is reserved for the partition resolver"),
- NON_COMPARABLE_ATTRIBUTE("The attribute definition is not compatible with innequality comparisons"),
- NULL_EQUALITY_OPERATOR("Null equality operator"), NULL_LABEL_SET("Null label set"),
- NULL_PARTITION("Null partition"), NULL_PARTITION_PLUGIN("null partitions plugin"),
- NULL_PARTITION_PLUGIN_DATA("null partitions plugin date"), NULL_PARTITION_LABEL("Null partition label"),
- NULL_PARTITION_LABEL_DIMENSION("Null partition label dimension"), NULL_FILTER("Null filter"),
- NULL_PARTITION_KEY("Null population partition key"), NULL_POPULATION_PARTITION("Null population partition"),
- NULL_PARTITION_DATA_MANAGER("Null partition data manager"), NULL_PARTITION_SAMPLER("Null partition sampler"),
-
- UNKNOWN_POPULATION_PARTITION_KEY("No population partition found"), NULL_PERSON_DATA_VIEW("Null person data view");
+ "An event class is being used to trigger refreshes as part of a partition that is reserved for the partition resolver"),//
+ NON_COMPARABLE_ATTRIBUTE("The attribute definition is not compatible with innequality comparisons"),//
+ NULL_EQUALITY_OPERATOR("Null equality operator"),//
+ NULL_LABEL_SET("Null label set"),//
+ NULL_PARTITION("Null partition"),//
+ NULL_PARTITION_PLUGIN("null partitions plugin"),//
+ NULL_PARTITION_PLUGIN_DATA("null partitions plugin data"),//
+ NULL_PARTITION_LABEL("Null partition label"),//
+ NULL_PARTITION_LABEL_DIMENSION("Null partition label dimension"),//
+ NULL_FILTER("Null filter"),//
+ NULL_PARTITION_KEY("Null population partition key"),//
+ NULL_POPULATION_PARTITION("Null population partition"),// 
+ NULL_PARTITION_DATA_MANAGER("Null partition data manager"),//
+ NULL_PARTITION_SAMPLER("Null partition sampler"),//
+ UNKNOWN_POPULATION_PARTITION_KEY("No population partition found"),//
+ NULL_PERSON_DATA_VIEW("Null person data view");
 
  private final String description;
 

gcm/src/main/java/gov/hhs/aspr/ms/gcm/plugins/people/datamanagers/PeoplePluginData.java

@@ -217,7 +217,6 @@ private void ensureImmutability() {
 
  private Builder(Data data) {
  this.data = data;
-
  }
 
  /**

gcm/src/main/java/gov/hhs/aspr/ms/gcm/plugins/personproperties/datamanagers/PersonPropertiesDataManager.java

@@ -491,7 +491,11 @@ public double getPersonPropertyTime(final PersonId personId, final PersonPropert
  validatePersonExists(personId);
  validatePersonPropertyId(personPropertyId);
  validatePersonPropertyAssignmentTimesTracked(personPropertyId);
- return propertyTimes.get(personPropertyId).getValue(personId.getValue());
+ DoubleValueContainer doubleValueContainer = propertyTimes.get(personPropertyId);
+ if(doubleValueContainer == null) {
+ return propertyDefinitionTimes.get(personPropertyId);
+ }
+ return doubleValueContainer.getValue(personId.getValue());
  }
 
  /**

gcm/src/main/java/gov/hhs/aspr/ms/gcm/plugins/personproperties/support/FunctionalPersonPropertyLabeler.java

@@ -0,0 +1,23 @@
+package gov.hhs.aspr.ms.gcm.plugins.personproperties.support;
+
+import java.util.function.Function;
+
+/**
+ * 
+ * A function-based implementor of PersonPropertyLabeler.
+ * 
+ */
+public class FunctionalPersonPropertyLabeler extends PersonPropertyLabeler {
+ private final Function<Object, Object> labelingFunction;
+
+ public FunctionalPersonPropertyLabeler(PersonPropertyId personPropertyId,
+ Function<Object, Object> labelingFunction) {
+ super(personPropertyId);
+ this.labelingFunction = labelingFunction;
+ }
+
+ @Override
+ protected Object getLabelFromValue(Object value) {
+ return labelingFunction.apply(value);
+ }
+}

tutorials/lessons/lesson_03_actors/src/main/resources/output/actors_lesson_3_output.txt

@@ -0,0 +1,6 @@
+/* start code_ref=actors_lesson_3_output|code_cap=Output from the single actor as it initializes.*/
+plugin being initialized -- we will add one actor
+actor being initialized
+my id = ActorId [id=0]
+time = 0.0
+/* end */

tutorials/lessons/lesson_04_data_managers/src/main/resources/output/data_managers_lesson_4_output.txt

@@ -0,0 +1,14 @@
+/* start code_ref=data_managers_lesson_4_output|code_cap=Output from the example actor and example data manager showing the alpha property initialization and subsequent evolution.*/
+ExampleDataManager is initialized
+Example Actor is initialized and will plan to set Alpha
+ExampleDataManager sets alpha = 8 at time = 0.0
+ExampleDataManager sets alpha = 9 at time = 1.0
+ExampleDataManager sets alpha = 10 at time = 2.0
+ExampleDataManager sets alpha = 11 at time = 3.0
+ExampleDataManager sets alpha = 12 at time = 4.0
+ExampleDataManager sets alpha = 13 at time = 5.0
+ExampleDataManager sets alpha = 14 at time = 6.0
+ExampleDataManager sets alpha = 15 at time = 7.0
+ExampleDataManager sets alpha = 16 at time = 8.0
+ExampleDataManager sets alpha = 17 at time = 9.0
+/* end */

tutorials/lessons/lesson_05_events/src/main/resources/output/events_lesson_5_output.txt

@@ -0,0 +1,17 @@
+/* start code_ref=events_lesson_5_output|code_cap=Output from Actors 2 and 3 as they observe changes to the alpha and beta properties.*/
+Actor2 observes event AlphaChangeEvent [previousAlpha=7, currentAlpha=8] at time = 1.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=8, currentAlpha=9] at time = 2.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=9, currentAlpha=10] at time = 3.0
+Actor3 observes event BetaChangeEvent [previousBeta=1.2345, currentBeta=2.469] at time = 3.5
+Actor2 observes event AlphaChangeEvent [previousAlpha=10, currentAlpha=11] at time = 4.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=11, currentAlpha=12] at time = 5.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=12, currentAlpha=13] at time = 6.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=13, currentAlpha=14] at time = 7.0
+Actor3 observes event BetaChangeEvent [previousBeta=2.469, currentBeta=4.938] at time = 7.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=14, currentAlpha=15] at time = 8.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=15, currentAlpha=16] at time = 9.0
+Actor2 observes event AlphaChangeEvent [previousAlpha=16, currentAlpha=17] at time = 10.0
+Actor3 observes event BetaChangeEvent [previousBeta=4.938, currentBeta=9.876] at time = 10.5
+Actor3 observes event BetaChangeEvent [previousBeta=9.876, currentBeta=19.752] at time = 14.0
+Actor3 observes event BetaChangeEvent [previousBeta=19.752, currentBeta=39.504] at time = 17.5
+/* end */

tutorials/lessons/lesson_06_plugin_dependencies/src/main/resources/output/plugin_dependencies_output.txt

@@ -0,0 +1,32 @@
+/* start code_ref=plugin_dependencies_output|code_cap=The output shows the combined reporting from actors and data managers as they report vaccination progress.*/
+Person 7 was vaccinated at time = 1.0
+Person 2 was vaccinated at time = 2.0
+Person 5 was vaccinated at time = 3.0
+Vaccination Data Manager is removing person 2 at time = 3.0
+Family Data Manager is removing person 2 at time = 3.0
+Person 6 was vaccinated at time = 4.0
+Vaccination Data Manager is removing person 1 at time = 4.0
+Family Data Manager is removing person 1 at time = 4.0
+Person 3 was vaccinated at time = 5.0
+Vaccination Data Manager is removing person 8 at time = 5.0
+Family Data Manager is removing person 8 at time = 5.0
+Failed to vaccinate Person 1 at time = 6.0
+Vaccination Data Manager is removing person 6 at time = 6.0
+Family Data Manager is removing person 6 at time = 6.0
+Person 0 was vaccinated at time = 7.0
+Vaccination Data Manager is removing person 7 at time = 7.0
+Family Data Manager is removing person 7 at time = 7.0
+Person 9 was vaccinated at time = 8.0
+Vaccination Data Manager is removing person 5 at time = 8.0
+Family Data Manager is removing person 5 at time = 8.0
+Failed to vaccinate Person 8 at time = 9.0
+Vaccination Data Manager is removing person 3 at time = 9.0
+Family Data Manager is removing person 3 at time = 9.0
+Person 4 was vaccinated at time = 10.0
+Vaccination Data Manager is removing person 4 at time = 10.0
+Family Data Manager is removing person 4 at time = 10.0
+Vaccination Data Manager is removing person 0 at time = 11.0
+Family Data Manager is removing person 0 at time = 11.0
+Vaccination Data Manager is removing person 9 at time = 12.0
+Family Data Manager is removing person 9 at time = 12.0
+/* end */

tutorials/lessons/lesson_08_plugin_data/src/main/java/gov/hhs/aspr/ms/gcm/lessons/plugins/disease/DiseasePluginData.java

@@ -121,7 +121,7 @@ public double getSymptomaticDays() {
  }
  /* end */
 
- /* start code_ref=plugin_data_clone_builder|code_cap=The disease plugin data creates a copy of its data an places it in the returned plugin data builder.*/
+ /* start code_ref=plugin_data_clone_builder|code_cap=The disease plugin data creates a copy of its data and places it in the returned plugin data builder.*/
  @Override
  public PluginDataBuilder getCloneBuilder() {
  return new Builder(new Data(data));

tutorials/lessons/lesson_09_experiments/src/main/java/gov/hhs/aspr/ms/gcm/lessons/Example_9_A.java

@@ -6,6 +6,7 @@
 import gov.hhs.aspr.ms.gcm.lessons.plugins.policy.PolicyPlugin;
 import gov.hhs.aspr.ms.gcm.lessons.plugins.policy.PolicyPluginData;
 import gov.hhs.aspr.ms.gcm.nucleus.Experiment;
+import gov.hhs.aspr.ms.gcm.nucleus.ExperimentStatusConsole;
 import gov.hhs.aspr.ms.gcm.nucleus.Plugin;
 
 /* start code_ref=experiments_example_9_A|code_cap=Example 9 replaces Example 8's use of the simulation with an experiment.*/
@@ -43,7 +44,8 @@ public static void main(String[] args) {
  .addPlugin(diseasePlugin)//
  .addPlugin(modelPlugin)//
  .addPlugin(policyPlugin)//
- .build()//
+ .addExperimentContextConsumer(ExperimentStatusConsole.builder().build())//
+ .build()// 
  .execute();
  }
 }

tutorials/lessons/lesson_09_experiments/src/main/resources/output/experiements_example_9_D_output_1.txt

@@ -0,0 +1,16 @@
+/* start code_ref=experiements_example_9_D_output_1|code_cap=The first two scenarios.*/
+Model Actor initializing
+ r0 = 1.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = false
+
+Model Actor initializing
+ r0 = 2.0
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = false
+
+/* end */

tutorials/lessons/lesson_09_experiments/src/main/resources/output/experiements_example_9_D_output_2.txt

@@ -0,0 +1,16 @@
+/* start code_ref=experiements_example_9_D_output_2|code_cap=The last two scenarios.*/
+Model Actor initializing
+ r0 = 2.0
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.1
+ distribute vaccine locally = true
+
+Model Actor initializing
+ r0 = 2.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.1
+ distribute vaccine locally = true
+
+/* end */

tutorials/lessons/lesson_09_experiments/src/main/resources/output/experiements_example_9_E_output.txt

@@ -0,0 +1,21 @@
+/* start code_ref=experiements_example_9_E_output|code_cap=The output from the four threads running the twelve scenarios is a bit jumbled and hard to follow. This will get resolved later with improved output handling.*/
+Model Actor initializing
+Model Actor initializing
+ r0 = 1.5
+Model Actor initializing
+Model Actor initializing
+ r0 = 1.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ r0 = 2.5
+ school closing infection rate = 0.05
+ asymptomatic days = 4.0
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ r0 = 2.0
+ school closing infection rate = 0.1
+ distribute vaccine locally = false
+
+... 
+
+/* end */

tutorials/lessons/lesson_09_experiments/src/main/resources/output/experiments_example_9_A_output.txt

@@ -0,0 +1,13 @@
+/* start code_ref=experiments_example_9_A_output|code_cap=The output of the experiment version is the same as the simulation since the experiment contains exactly one scenario.*/
+Model Actor initializing
+ r0 = 1.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+1 of 1 scenario, 100% complete. Expected experiment completion in 0:00:00
+Experiment completion of 1 scenario in 0:00:00:
+ SUCCEDED : 1
+end of experiment status console
+/* end */

tutorials/lessons/lesson_09_experiments/src/main/resources/output/experiments_output.txt

@@ -0,0 +1,44 @@
+/* start code_ref=experiments_output|code_cap=The model actor writes output for each of the five scenarios corresponding to the five values of the R0 dimension.*/
+Model Actor initializing
+ r0 = 0.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+Model Actor initializing
+ r0 = 0.75
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+Model Actor initializing
+ r0 = 1.0
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+Model Actor initializing
+ r0 = 1.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+Model Actor initializing
+ r0 = 2.0
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+Model Actor initializing
+ r0 = 2.5
+ asymptomatic days = 4.0
+ symptomatic days = 12.0
+ school closing infection rate = 0.05
+ distribute vaccine locally = true
+
+/* end */

tutorials/lessons/lesson_10_output/src/main/java/gov/hhs/aspr/ms/gcm/lessons/Example_10_B.java

@@ -1,3 +1,4 @@
+
 package gov.hhs.aspr.ms.gcm.lessons;
 
 import java.util.ArrayList;

tutorials/lessons/lesson_10_output/src/main/java/gov/hhs/aspr/ms/gcm/lessons/OutputConsumer_D.java

@@ -5,7 +5,7 @@
 
 import gov.hhs.aspr.ms.gcm.nucleus.ExperimentContext;
 
-/* start code_ref=output_consumer_D|code_cap=Output consumer D demonstrates that the meta data collected from the dimensions is available from the experiment context. Thus output can be associated with the scenario's meta data.*/
+/* start code_ref=output_consumer_D|code_cap=OutputConsumer_D demonstrates that the meta data collected from the dimensions is available from the experiment context. Thus output can be associated with the scenario's meta data.*/
 public class OutputConsumer_D implements Consumer<ExperimentContext> {
 
  @Override

tutorials/lessons/lesson_10_output/src/main/resources/output/output_consumer_B_output.txt

@@ -0,0 +1,33 @@
+/* start code_ref=output_consumer_B_output|code_cap=The output is still a bit scrambled, but each row now has the relevant scenario id.*/
+scenario 1: Model Actor initializing
+scenario 2: Model Actor initializing
+scenario 3: Model Actor initializing
+scenario 0: Model Actor initializing
+scenario 3: r0 = 1.5
+scenario 0: r0 = 1.5
+scenario 2: r0 = 2.5
+scenario 2: asymptomatic days = 4.0
+scenario 1: r0 = 2.0
+scenario 2: symptomatic days = 12.0
+scenario 1: asymptomatic days = 4.0
+scenario 0: asymptomatic days = 4.0
+scenario 2: school closing infection rate = 0.05
+scenario 3: asymptomatic days = 4.0
+scenario 2: distribute vaccine locally = false
+scenario 0: symptomatic days = 12.0
+scenario 1: symptomatic days = 12.0
+scenario 0: school closing infection rate = 0.05
+scenario 1: school closing infection rate = 0.05
+scenario 3: symptomatic days = 12.0
+scenario 3: school closing infection rate = 0.1
+scenario 1: distribute vaccine locally = false
+scenario 0: distribute vaccine locally = false
+scenario 3: distribute vaccine locally = false
+scenario 5: Model Actor initializing
+scenario 4: Model Actor initializing
+scenario 5: r0 = 2.5
+scenario 4: r0 = 2.0
+
+...
+
+/* end */

tutorials/lessons/lesson_10_output/src/main/resources/output/output_consumer_C_output_1.txt

@@ -0,0 +1,20 @@
+/* start code_ref=output_consumer_C_output_1|code_cap=The first output lines for OutputConsumer_C.*/
+
+the experiment is open
+scenario 0 is open
+scenario 1 is open
+scenario 2 is open
+scenario 3 is open
+scenario 0: Model Actor initializing
+scenario 2: Model Actor initializing
+scenario 1: Model Actor initializing
+scenario 2: r0 = 2.5
+scenario 3: Model Actor initializing
+scenario 2: asymptomatic days = 4.0
+scenario 1: r0 = 2.0
+scenario 0: r0 = 1.5
+scenario 2: symptomatic days = 12.0
+
+...
+
+/* end */