Merge pull request #1 from HBPMedical/master

Merge latest HBPmedical/algorithm-repository to bldrvnlw fork

Guidelines.md

@@ -33,8 +33,8 @@ Step-by-Step Guidelines
 
 1.  **Go to** GitHub
 
-2.  **Clone** the *functions-repository* folder -
-    <https://github.com/LREN-CHUV/functions-repository>
+2.  **Clone** the *algorithm-repository* folder -
+    <https://github.com/LREN-CHUV/algorithm-repository>
 
 3.  **Go to** the root folder of your cloned project
 

README.md

@@ -1,10 +1,10 @@
-[![CHUV](https://img.shields.io/badge/CHUV-LREN-AF4C64.svg)](https://www.unil.ch/lren/en/home.html) [![Codacy Badge](https://api.codacy.com/project/badge/Grade/26aff9cefde9484c8c75794195fcf448)](https://www.codacy.com/app/hbp-mip/functions-repository?utm_source=github.com&utm_medium=referral&utm_content=HBPMedical/functions-repository&utm_campaign=Badge_Grade) [![CircleCI](https://circleci.com/gh/HBPMedical/functions-repository.svg?style=svg)](https://circleci.com/gh/HBPMedical/functions-repository)
+[![CHUV](https://img.shields.io/badge/CHUV-LREN-AF4C64.svg)](https://www.unil.ch/lren/en/home.html) [![Codacy Badge](https://api.codacy.com/project/badge/Grade/a170b1b08f81441f85c004480ddaac0f)](https://www.codacy.com/app/hbp-mip/algorithm-repository?utm_source=github.com&utm_medium=referral&utm_content=HBPMedical/algorithm-repository&utm_campaign=Badge_Grade) [![CircleCI](https://circleci.com/gh/HBPMedical/algorithm-repository.svg?style=svg)](https://circleci.com/gh/HBPMedical/algorithm-repository)
 
-# Functions repository
+# Algorithm repository
 
-This is the repository of functions for the [MIP](https://mip.humanbrainproject.eu).
+This is the repository of algorithms for the [MIP](https://mip.humanbrainproject.eu).
 
-Functions, written in their native language (R, Matlab, Python, Java...) are encapsulated in a Docker container that provides them with the runtime environment necessary to execute this function.
+Algorithms, written in their native language (R, Matlab, Python, Java...) are encapsulated in a Docker container that provides them with the runtime environment necessary to execute this function.
 
 The environment variables provided to the Docker container are used as parameters to the function or algorithm to execute.
 
@@ -14,4 +14,7 @@ Currently, we expect the Docker containers to be autonomous:
 * they should process the data, taking into account the parameters given as environment variables to the Docker container
 * they should store the results into the results database.
 
-The format of the results should be easily shared. We are using the [PFA format](http://dmg.org/pfa/) here in its YAML form. It will get translated to JSON automatically be the workflow application which provides web services which execute this Docker container.
+The format of the results should be easily shared.
+
+* For algorithms providing statistical analysis or machine learning, we require the results to be in [PFA format](http://dmg.org/pfa/) in its YAML or JSON form.
+* For algorithms providing visualisations, we support different formats, including Highcharts, Vis.js, PNG and SVG.

java-rapidminer-knn/.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.0
+current_version = 0.2.1
 commit = True
 tag = True
 tag_name = java-rapidminer-knn-{new_version}

java-rapidminer-knn/Dockerfile

@@ -1,4 +1,4 @@
-FROM hbpmip/java-base-build:3.5.0-jdk-8-6 as build-java-env
+FROM hbpmip/java-base-build:3.5.0-jdk-8-8 as build-java-env
 
 COPY pom.xml /project/pom.xml
 COPY src/ /project/src
@@ -7,17 +7,17 @@ COPY src/ /project/src
 RUN cp /usr/share/maven/ref/settings-docker.xml /root/.m2/settings.xml \
     && mvn package site
 
-FROM hbpmip/java-rapidminer:0.4.1
+FROM hbpmip/java-rapidminer:0.9.0
 
 MAINTAINER [email protected]
 
-ENV DOCKER_IMAGE=hbpmip/java-rapidminer-knn:0.1.0
-ENV JAVA_CLASSPATH=${JAVA_CLASSPATH}:/usr/share/jars/java-rapidminer-knn.jar
-ENV JAVA_ARGS=eu.hbp.mip.container.rapidminer.models.Knn
-ENV MODEL knn
-ENV FUNCTION java-rapidminer-knn
+ENV DOCKER_IMAGE=hbpmip/java-rapidminer-knn:0.2.1 \
+    JAVA_CLASSPATH=${JAVA_CLASSPATH}:/usr/share/jars/java-rapidminer-knn.jar \
+    JAVA_ARGS=/eu/humanbrainproject/mip/algorithms/rapidminer/knn/settings.properties \
+    MODEL="k-NN" \
+    FUNCTION=java-rapidminer-knn
 
-COPY --from=build-java-env /project/target/java-rapidminer-knn.jar /usr/share/jars/java-rapidminer-knn.jar
+COPY --from=build-java-env /project/target/knn.jar /usr/share/jars/java-rapidminer-knn.jar
 COPY --from=build-java-env /project/target/site/ /var/www/html/
 COPY src/ /src/
 
@@ -27,9 +27,9 @@ RUN chown -R compute:compute /src/ \
 LABEL org.label-schema.build-date=$BUILD_DATE \
       org.label-schema.name="hbpmip/java-rapidminer-knn" \
       org.label-schema.description="KNN algorithm" \
-      org.label-schema.url="https://github.com/LREN-CHUV/functions-repository" \
+      org.label-schema.url="https://github.com/LREN-CHUV/algorithm-repository" \
       org.label-schema.vcs-type="git" \
-      org.label-schema.vcs-url="https://github.com/LREN-CHUV/functions-repository.git" \
+      org.label-schema.vcs-url="https://github.com/LREN-CHUV/algorithm-repository.git" \
       org.label-schema.vcs-ref=$VCS_REF \
       org.label-schema.version="$VERSION" \
       org.label-schema.vendor="LREN CHUV" \

java-rapidminer-knn/README.md

@@ -1,13 +1,13 @@
-[![DockerHub](https://img.shields.io/badge/docker-hbpmip%2Fjava--rapidminer--knn-008bb8.svg)](https://hub.docker.com/r/hbpmip/java-rapidminer-knn/) [![ImageVersion](https://images.microbadger.com/badges/version/hbpmip/java-rapidminer-knn.svg)](https://hub.docker.com/r/hbpmip/java-rapidminer-knn/tags "hbpmip/java-rapidminer-knn image tags") [![ImageLayers](https://images.microbadger.com/badges/image/hbpmip/java-rapidminer-knn.svg)](https://microbadger.com/#/images/hbpmip/java-rapidminer-knn "hbpmip/java-rapidminer-knn on microbadger")
+[![CHUV](https://img.shields.io/badge/CHUV-LREN-AF4C64.svg)](https://www.unil.ch/lren/en/home.html) [![DockerHub](https://img.shields.io/badge/docker-hbpmip%2Fjava--rapidminer--knn-008bb8.svg)](https://hub.docker.com/r/hbpmip/java-rapidminer-knn/) [![ImageVersion](https://images.microbadger.com/badges/version/hbpmip/java-rapidminer-knn.svg)](https://hub.docker.com/r/hbpmip/java-rapidminer-knn/tags "hbpmip/java-rapidminer-knn image tags") [![](https://images.microbadger.com/badges/version/hbpmip/java-rapidminer-knn.svg)](https://microbadger.com/images/hbpmip/java-rapidminer-knn "Get your own version badge on microbadger.com") [![ImageLayers](https://images.microbadger.com/badges/image/hbpmip/java-rapidminer-knn.svg)](https://microbadger.com/#/images/hbpmip/java-rapidminer-knn "hbpmip/java-rapidminer-knn on microbadger")
 
 # java-rapidminer-knn
 
-Implementation of the KNN algorithm using RapidMiner
+Implementation of the [KNN](https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm) algorithm using RapidMiner
 
 ## Usage
 
 ```
-  docker run --rm --env [list of environment variables] hbpmip/java-rapidminer-knn:0.0.1 compute
+  docker run --rm --env [list of environment variables] hbpmip/java-rapidminer-knn:0.2.1 compute
 
 ```
 
@@ -26,16 +26,16 @@ where the environment variables are:
 * PARAM_variables: Name of the target variable (only one variable is supported for KNN)
 * PARAM_covariables: List of covariables
 * PARAM_query: Query selecting the variables and covariables to feed into the algorithm for training.
-* PARAM_MODEL_k: Number of class labels to search for.
+* MODEL_PARAM_k (or PARAM_MODEL_k for compatibility): Number of class labels to search for.
 
 ## Development process
 
 The goal of this project is to create a Docker image containing the full R environment capable of:
 
 1. Read parameters from the environment and connect to a database
 2. Query the database and prepare the data
-3. Run the algorithm (here, a linear regression)
-4. Format the results into a format that can be easily shared. We are using the [PFA format](http://dmg.org/pfa/) here in its YAML form. It will get translated to JSON automatically be the workflow application which provides web services which execute this Docker container.
+3. Run the algorithm (here, KNN)
+4. Format the results into a format that can be easily shared. We are using the [PFA format](http://dmg.org/pfa/) here in its JSON form.
 5. Save the results into the result database.
 
 The Docker image should contain the binaries and resources that this algorithm depends on.
@@ -48,8 +48,9 @@ The main build script, it packages this project into a Docker image and performs
 It requires [captain](https://github.com/harbur/captain) and [Docker engine](https://www.docker.com/) to run. If you cannot install captain on your platform, you may use the following commands to build the project:
 
 ```
-  docker build -t hbpmip/r-linear-regression .
-  ./tests/test.sh
+  captain build
+  # or
+  docker build -t hbpmip/java-rapidminer-knn .
 ```
 
 ### `./tests/test.sh`