Statistics

WebJar for vega-statistics

Statistical Machine Intelligence and Learning Engine

BioJava is an open-source project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

WebJar for simple-statistics

Datumbox is an open-source Machine Learning Framework written in Java which allows the rapid development of Machine Learning and Statistical applications.

Datastore SQL engine (DSQL) for Google appengine datastore. DSQL extends gae datastore in implementing local joins between datastore kinds as well as providing local filtering for unindexed properties. DSQL uses familiar sql-syntax. SQL joins are optimized using datastore statistics. It is assumed that datastore schema is designed like relational db. However parent/child relationships are supported. Also supported are special datatypes in package com.google.appengine.api.datastore like Email, Phonenumber, ...

Features to support gathering of statistics.

A library for gathering and reporting statistical information.

Random number generators, probability distributions, combinatorics and statistics for Java.

Metrics Integration for JCache, JSR 107 standard for caching. Uses the CacheStatisticsMXBean provided statistics.

org.wso2.carbon.event.statistics.ui represent the UI aspects of org.wso2.carbon.event.statistics bundle

52°North Iceland Statistics

Datumbox is an open-source Machine Learning Framework written in Java which allows the rapid development of Machine Learning and Statistical applications.

ASV Toolbox is a modular collection of tools for the exploration of written language data. They work either on word lists or text and solve several linguistic classification and clustering tasks. The topics covered contain language detection, POS-tagging, base form reduction, named entity recognition, and terminology extraction. On a more abstract level, the algorithms deal with various kinds of word similarity, using pattern based and statistical approaches. The collection can be used to work on large real world data sets as well as for studying the underlying algorithms. The ASV Toolbox can work on plain text files and connect to a MySQL database. While it is especially designed to work with corpora of the Leipzig Corpora Collection, it can easily be adapted to other sources.

Eclipse SCADA Statistic Information (Incubation)

openTCS-PlantOverview-Panel-Statistics

This feature contains the bundles required for Front-end Statistics functionality

org.wso2.carbon.event.statistics provides the back-end functionality

BioJava is an open-source project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

The addc-statistics library supplies classes for collecting statistics including counters, timers and accumulators and exposing these as MBeans.

BioJava is an open-source project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

Opencast is a media capture, processing, management and distribution system

Opencast is a media capture, processing, management and distribution system

Calculates summary statistics, optionally within zones defined by a zone image, for values in a data image

The Java Application Monitor (JAMon) is a free, simple, high performance, thread safe, Java API that allows developers to easily monitor production applications. 1) It contains the ability to monitor JDBC/SQL, web page requests, ejb's, log4j, interfaces and more. 2) It tracks aggregate stats for each sql statement, page request etc. and also lets you look at this information and more via the JAMon war. 3) You can also access JAMon statistics via the api

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. ## Dependency The library is available on maven central using: * group-id = `au.com.dius.pact.consumer` * artifact-id = `java8` * version-id = `4.1.x` # A Lambda DSL for Pact This is an extension for the pact DSL provided by [consumer](../consumer). The difference between the default pact DSL and this lambda DSL is, as the name suggests, the usage of lambdas. The use of lambdas makes the code much cleaner. ## Why a new DSL implementation? The lambda DSL solves the following two main issues. Both are visible in the following code sample: ```java new PactDslJsonArray() .array() # open an array .stringValue("a1") # choose the method that is valid for arrays .stringValue("a2") # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .numberValue(1) # choose the method that is valid for arrays .numberValue(2) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .object() # now we work with an object .stringValue("foo", "Foo") # choose the method that is valid for objects .closeObject() # close the object and we're back in the array .closeArray() # close the array ``` ### The existing DSL is quite error-prone Methods may only be called in certain states. For example `object()` may only be called when you're currently working on an array whereas `object(name)` is only allowed to be called when working on an object. But both of the methods are available. You'll find out at runtime if you're using the correct method. Finally, the need for opening and closing objects and arrays makes usage cumbersome. The lambda DSL has no ambiguous methods and there's no need to close objects and arrays as all the work on such an object is wrapped in a lamda call. ### The existing DSL is hard to read When formatting your source code with an IDE the code becomes hard to read as there's no indentation possible. Of course, you could do it by hand but we want auto formatting! Auto formatting works great for the new DSL! ```java array.object((o) -> { o.stringValue("foo", "Foo"); # an attribute o.stringValue("bar", "Bar"); # an attribute o.object("tar", (tarObject) -> { # an attribute with a nested object tarObject.stringValue("a", "A"); # attribute of the nested object tarObject.stringValue("b", "B"); # attribute of the nested object }) }); ``` ## Installation ### Maven ``` <dependency> <groupId>au.com.dius.pact.consumer</groupId> <artifactId>java8</artifactId> <version>${pact.version}</version> </dependency> ``` ## Usage Start with a static import of `LambdaDsl`. This class contains factory methods for the lambda dsl extension. When you come accross the `body()` method of `PactDslWithProvider` builder start using the new extensions. The call to `LambdaDsl` replaces the call to instance `new PactDslJsonArray()` and `new PactDslJsonBody()` of the pact library. ```java io.pactfoundation.consumer.dsl.LambdaDsl.* ``` ### Response body as json array ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonArray; ... PactDslWithProvider builder = ... builder.given("some state") .uponReceiving("a request") .path("/my-app/my-service") .method("GET") .willRespondWith() .status(200) .body(newJsonArray((a) -> { a.stringValue("a1"); a.stringValue("a2"); }).build()); ``` ### Response body as json object ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonBody; ... PactDslWithProvider builder = ... builder.given("some state") .uponReceiving("a request") .path("/my-app/my-service") .method("GET") .willRespondWith() .status(200) .body(newJsonBody((o) -> { o.stringValue("foo", "Foo"); o.stringValue("bar", "Bar"); }).build()); ``` ### Examples #### Simple Json object When creating simple json structures the difference between the two approaches isn't big. ##### JSON ```json { "bar": "Bar", "foo": "Foo" } ``` ##### Pact DSL ```java new PactDslJsonBody() .stringValue("foo", "Foo") .stringValue("bar", "Bar") ``` ##### Lambda DSL ```java newJsonBody((o) -> { o.stringValue("foo", "Foo"); o.stringValue("bar", "Bar"); }).build(); ``` #### An array of arrays When we come to more complex constructs with arrays and nested objects the beauty of lambdas become visible! ##### JSON ```json [ ["a1", "a2"], [1, 2], [{"foo": "Foo"}] ] ``` ##### Pact DSL ```java new PactDslJsonArray() .array() .stringValue("a1") .stringValue("a2") .closeArray() .array() .numberValue(1) .numberValue(2) .closeArray() .array() .object() .stringValue("foo", "Foo") .closeObject() .closeArray(); ``` ##### Lambda DSL ```java newJsonArray((rootArray) -> { rootArray.array((a) -> a.stringValue("a1").stringValue("a2")); rootArray.array((a) -> a.numberValue(1).numberValue(2)); rootArray.array((a) -> a.object((o) -> o.stringValue("foo", "Foo"))); }).build(); ``` ##### Kotlin Lambda DSL ```kotlin newJsonArray { newArray { stringValue("a1") stringValue("a2") } newArray { numberValue(1) numberValue(2) } newArray { newObject { stringValue("foo", "Foo") } } } ``` # Test Analytics We are tracking anonymous analytics to gather important usage statistics like JVM version and operating system. To disable tracking, set the 'pact_do_not_track' system property or environment variable to 'true'.

AVOS Cloud Android SDK

Generic Repository: Statistics

OpenDaylight is leading the transformation to Open Software Defined Networking (SDN). For more information, please see https://www.opendaylight.org

52°North SOS - OGC Statistics

Datumbox is an open-source Machine Learning Framework written in Java which allows the rapid development of Machine Learning and Statistical applications.

Datumbox is an open-source Machine Learning Framework written in Java which allows the rapid development of Machine Learning and Statistical applications.

A prometheus metrics handler to log statistic info on the server

DKPro Statistics is a collection of open-licensed statistical tools, currently including inter-rater agreement, correlation, and significance measures.

Datumbox is an open-source Machine Learning Framework written in Java which allows the rapid development of Machine Learning and Statistical applications.

Configuration files for openflowjava statistics

The Apache Commons Math project is a library of lightweight, self-contained mathematics and statistics components addressing the most common practical problems not immediately available in the Java programming language or commons-lang.

BioJava is an open-source project dedicated to providing a Java framework for processing biological data. It provides analytical and statistical routines, parsers for common file formats and allows the manipulation of sequences and 3D structures. The goal of the biojava project is to facilitate rapid application development for bioinformatics.

Features to support gathering of statistics.

Fedora Repository Statistics API interfaces and classes

52°North iceland statistics extension for IP-based geolocation

A Java package that provides routines for various statistical distributions.

Garmadon is a java event logs collector for hadoop and frameworks

MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.

openTCS-Kernel-Extension-Statistics

WSO2 is an open source application development software company focused on providing service-oriented architecture solutions for professional developers.

52°North SOS - OGC Statistics

kotlin-gradle-statistics

Sdmx Connectors for Statistical Software

This feature contains the core bundles required for BAM Agent Service Statistics Server functionality