From f65d30a798922644bf12c96bc2c58b84dee42b28 Mon Sep 17 00:00:00 2001
From: Manuel Spuhler <manuel.spuhler@chuv.ch>
Date: Tue, 21 May 2019 15:24:23 +0200
Subject: [PATCH] Exareme setup WIP
---
.../eu/hbp/mip/controllers/ExperimentApi.java | 5 +-
.../eu/hbp/mip/controllers/MethodsApi.java | 2 +-
.../java/eu/hbp/mip/model/Experiment.java | 204 +-----------------
.../eu/hbp/mip/model/ExperimentQuery.java | 9 +
4 files changed, 24 insertions(+), 196 deletions(-)
diff --git a/src/main/java/eu/hbp/mip/controllers/ExperimentApi.java b/src/main/java/eu/hbp/mip/controllers/ExperimentApi.java
index caa8ea97b..4f74bc820 100644
--- a/src/main/java/eu/hbp/mip/controllers/ExperimentApi.java
+++ b/src/main/java/eu/hbp/mip/controllers/ExperimentApi.java
@@ -76,11 +76,12 @@ public class ExperimentApi extends WokenClientController {
experiment.setName(expQuery.getName());
experiment.setCreatedBy(user);
experiment.setModel(modelRepository.findOne(expQuery.getModel()));
+ experiment.setSource(expQuery.getSource());
experimentRepository.save(experiment);
LOGGER.info("Experiment saved");
- if (!experiment.isExaremeAlgorithm()._1) {
+ if (experiment.getSource() != "exareme") {
sendExperiment(experiment);
} else {
String algoCode = expQuery.getAlgorithms().get(0).getCode();
@@ -286,7 +287,7 @@ public class ExperimentApi extends WokenClientController {
// >> Temporary: we should integrate exareme in a proper way in the future
// this runs in the background. For future optimization: use a thread pool
new Thread(() -> {
- String query = experiment.computeExaremeQuery(params);
+ String query = ""; //experiment.computeExaremeQuery(params);
String url = miningExaremeQueryUrl + "/" + algoCode;
// Results are stored in the experiment object
diff --git a/src/main/java/eu/hbp/mip/controllers/MethodsApi.java b/src/main/java/eu/hbp/mip/controllers/MethodsApi.java
index 29e69e325..21d3b9f2f 100644
--- a/src/main/java/eu/hbp/mip/controllers/MethodsApi.java
+++ b/src/main/java/eu/hbp/mip/controllers/MethodsApi.java
@@ -26,7 +26,7 @@ public class MethodsApi extends WokenClientController {
private static final Logger LOGGER = LoggerFactory.getLogger(MethodsApi.class);
private static final Gson gson = new Gson();
-d
+
@Value("#{'${services.exareme.algorithmsUrl:http://localhost:9090/mining/algorithms.json}'}")
private String exaremeAlgorithmsUrl;
diff --git a/src/main/java/eu/hbp/mip/model/Experiment.java b/src/main/java/eu/hbp/mip/model/Experiment.java
index 8f4dd0a34..c0a179909 100644
--- a/src/main/java/eu/hbp/mip/model/Experiment.java
+++ b/src/main/java/eu/hbp/mip/model/Experiment.java
@@ -19,7 +19,6 @@ import scala.collection.JavaConversions;
import javax.persistence.*;
import java.lang.reflect.Type;
import java.util.*;
-import scala.Tuple2;
/**
* Created by habfast on 21/04/16.
@@ -28,12 +27,6 @@ import scala.Tuple2;
@Table(name = "`experiment`")
public class Experiment {
- public static final String WP_K_MEANS = "K_MEANS";
- public static final String WP_LINEAR_REGRESSION = "WP_LINEAR_REGRESSION";
- public static final String WP_VARIABLES_HISTOGRAM = "WP_VARIABLES_HISTOGRAM";
- public static final String WP_REGRESSION_TREE = "PIPELINE_ISOUP_REGRESSION_TREE_SERIALIZER";
- public static final String WP_MODEL_TREE = "PIPELINE_ISOUP_MODEL_TREE_SERIALIZER";
-
private static final Logger LOGGER = LoggerFactory.getLogger(Experiment.class);
private static final Gson gson = new Gson();
@@ -89,6 +82,10 @@ public class Experiment {
@Expose
private boolean resultsViewed = false;
+ @Column(columnDefinition="TEXT")
+ @Expose
+ private String source;
+
public Experiment() {
/*
* Empty constructor is needed by Hibernate
@@ -137,159 +134,10 @@ public class Experiment {
validationsSeq, Option.empty());
}
- private String chainsParams(List<String> params, String operator) {
- StringBuilder sb = new StringBuilder();
- int i = 0;
- for (String s : params)
- {
- i++;
- sb.append(s);
- if (i < params.size()) {
- sb.append(operator);
- }
- }
- return sb.toString();
- }
-
- public String computeExaremeQuery(List<AlgorithmParam> params) {
- List<ExaremeQueryElement> queryElements = new LinkedList<>();
-
- // parameters
- String design = ""; // TODO: don't assign to a global
- String nobuckets = "";
-
- if (params != null) {
- for (AlgorithmParam p : params)
- {
- ExaremeQueryElement paramEl = new ExaremeQueryElement();
- paramEl.setName(p.getCode());
- paramEl.setDesc("");
- paramEl.setValue(p.getValue());
- queryElements.add(paramEl);
-
- if (p.getCode().equals("design")) {
- design = p.getValue();
- }
-
- if (p.getCode().equals("nobuckets")) {
- nobuckets = p.getValue();
- }
- }
- }
-
- List<String> variables = new ArrayList<>();
- List<String> covariables = new ArrayList<>();
- List<String> groupings = new ArrayList<>();
-
- for (Variable var : model.getQuery().getVariables()) { variables.add(var.getCode()); }
- for (Variable var : model.getQuery().getCovariables()) { covariables.add(var.getCode()); }
- for (Variable var : model.getQuery().getGrouping()) { groupings.add(var.getCode()); }
-
- // Set algorithm specific queries
- String algoName = this.isExaremeAlgorithm()._2;
- if (algoName.equals(WP_K_MEANS)) {
- // columns
- List<String> columns = variables;
- columns.addAll(covariables);
- columns.addAll(groupings);
-
- ExaremeQueryElement columnsEl = new ExaremeQueryElement();
- columnsEl.setName("columns");
- columnsEl.setDesc("");
- columnsEl.setValue(chainsParams(columns, ","));
- queryElements.add(columnsEl);
- } else if (algoName.equals(WP_LINEAR_REGRESSION)) {
- List<String> nominals = covariables.isEmpty() ? groupings : covariables;
- nominals.addAll(groupings);
-
- String operator = design.equals("factorial") ? "*" : "+";
-
- ExaremeQueryElement xEl = new ExaremeQueryElement();
- xEl.setName("x");
- xEl.setDesc("");
- xEl.setValue(chainsParams(nominals, operator));
- queryElements.add(xEl);
-
- ExaremeQueryElement yEl = new ExaremeQueryElement();
- yEl.setName("y");
- yEl.setDesc("");
- yEl.setValue(chainsParams(variables, ","));
- queryElements.add(yEl);
- } else if (algoName.equals(WP_VARIABLES_HISTOGRAM)) {
- List<String> column1 = variables;
- ExaremeQueryElement columnsEl = new ExaremeQueryElement();
- columnsEl.setName("column1");
- columnsEl.setDesc("");
- columnsEl.setValue(chainsParams(column1, ","));
- queryElements.add(columnsEl);
-
- List<String> column2 = covariables.isEmpty() ? groupings : covariables;
- ExaremeQueryElement columnsEl2 = new ExaremeQueryElement();
- columnsEl2.setName("column2");
- columnsEl2.setDesc("");
- columnsEl2.setValue(chainsParams(column2, ","));
- queryElements.add(columnsEl2);
-
- if (!nobuckets.isEmpty()) {
- ExaremeQueryElement columnsEl3 = new ExaremeQueryElement();
- columnsEl3.setName("nobuckets");
- columnsEl3.setDesc("");
- columnsEl3.setValue(nobuckets);
- queryElements.add(columnsEl3);
- }
- } else if (algoName.equals(WP_REGRESSION_TREE) || algoName.equals(WP_MODEL_TREE)) {
- List<String> target = variables;
- List<String> descriptive = covariables.isEmpty() ? groupings : covariables;
- descriptive.addAll(groupings);
-
- ExaremeQueryElement xEl = new ExaremeQueryElement();
- xEl.setName("target_attributes");
- xEl.setDesc("");
- xEl.setValue(chainsParams(target, ","));
- queryElements.add(xEl);
-
- ExaremeQueryElement yEl = new ExaremeQueryElement();
- yEl.setName("descriptive_attributes");
- yEl.setDesc("");
- yEl.setValue(chainsParams(descriptive, ","));
- queryElements.add(yEl);
- }
-
- // datasets
- StringBuilder datasets = new StringBuilder();
- List<Variable> trainingDatasets = model.getQuery().getTrainingDatasets();
- int j = 0;
- for (Variable var : trainingDatasets)
- {
- j++;
- datasets.append(var.getCode());
- if (j < trainingDatasets.size() ) {
- datasets.append(",");
- }
- }
-
- ExaremeQueryElement datasetsEl = new ExaremeQueryElement();
- datasetsEl.setName("dataset");
- datasetsEl.setDesc("");
- // datasetsEl.setValue("adni,ppmi,edsd,fbf,clm");
- datasetsEl.setValue(datasets.toString());
- queryElements.add(datasetsEl);
-
- // filter
- String filter = model.getQuery().getFilters();
- ExaremeQueryElement filterEl = new ExaremeQueryElement();
- filterEl.setName("filter");
- filterEl.setDesc("");
- filterEl.setValue(filter);
- queryElements.add(filterEl);
-
- return gson.toJson(queryElements);
- }
-
public JsonObject jsonify() {
JsonObject exp = gson.toJsonTree(this).getAsJsonObject();
JsonParser parser = new JsonParser();
- Tuple2<Boolean, String> isExaremeAlgorithm = this.isExaremeAlgorithm();
+ Boolean isExaremeAlgorithm = this.getSource() == "exareme";
if (this.algorithms != null)
{
@@ -308,7 +156,7 @@ public class Experiment {
if (this.result != null && !this.hasServerError) {
exp.remove("result");
- if (!isExaremeAlgorithm._1) {
+ if (!isExaremeAlgorithm) {
JsonElement jsonResult = parser.parse(this.result);
exp.add("result", jsonResult);
} else {
@@ -331,18 +179,6 @@ public class Experiment {
JsonObject jsonData = tryJson;
jsonObjectResult.add("data", jsonData);
- // add mime-type
- String algo = isExaremeAlgorithm._2;
- if (jsonData.get("Error") != null) {
- jsonObjectResult.add("type", new JsonPrimitive("text/plain+error"));
- } else if (algo.equals( WP_K_MEANS) || algo.equals( WP_VARIABLES_HISTOGRAM)) {
- jsonObjectResult.add("type", new JsonPrimitive("application/vnd.highcharts+json"));
- } else if (algo.equals(WP_LINEAR_REGRESSION)) {
- jsonObjectResult.add("type", new JsonPrimitive("application/vnd.dataresource+json"));
- } else if (algo.equals(WP_REGRESSION_TREE) || algo.equals(WP_MODEL_TREE)) {
- jsonObjectResult.add("type", new JsonPrimitive("application/vnd.visjs+javascript"));
- }
-
jsonArrayResult.add(jsonObjectResult);
exp.add("result", jsonArrayResult);
@@ -456,29 +292,11 @@ public class Experiment {
this.shared = shared;
}
- public Tuple2<Boolean, String> isExaremeAlgorithm() {
- Boolean isExareme = false;
- String algorithm = "";
-
- String algorithms = this.algorithms;
-
- if (algorithms.contains(WP_K_MEANS)) {
- isExareme = true;
- algorithm = WP_K_MEANS;
- } else if (algorithms.contains(WP_LINEAR_REGRESSION)) {
- isExareme = true;
- algorithm = WP_LINEAR_REGRESSION;
- } else if (algorithms.contains(WP_VARIABLES_HISTOGRAM)) {
- isExareme = true;
- algorithm = WP_VARIABLES_HISTOGRAM;
- } else if (algorithms.contains(WP_REGRESSION_TREE)) {
- isExareme = true;
- algorithm = WP_REGRESSION_TREE;
- } else if (algorithms.contains(WP_MODEL_TREE)) {
- isExareme = true;
- algorithm = WP_MODEL_TREE;
- }
+ public String getSource() {
+ return this.source;
+ }
- return new Tuple2<Boolean, String>(isExareme, algorithm);
+ public void setSource(String source) {
+ this.source = source;
}
}
diff --git a/src/main/java/eu/hbp/mip/model/ExperimentQuery.java b/src/main/java/eu/hbp/mip/model/ExperimentQuery.java
index 333751c43..2e7e6fd81 100644
--- a/src/main/java/eu/hbp/mip/model/ExperimentQuery.java
+++ b/src/main/java/eu/hbp/mip/model/ExperimentQuery.java
@@ -9,6 +9,7 @@ public class ExperimentQuery {
private String name;
private String model;
+ private String source;
private List<ExperimentValidator> validations;
private List<Algorithm> algorithms;
@@ -28,6 +29,14 @@ public class ExperimentQuery {
this.model = model;
}
+ public String getSource() {
+ return source;
+ }
+
+ public void setSource(String source) {
+ this.source = source;
+ }
+
public List<ExperimentValidator> getValidations() {
return validations;
}
--
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