ShapeLogic 1.0 with stream based rules released

Here are the release notes for ShapeLogic 1.0

Changes

• Rule for image processing have been migrated, previously they were implemented as goal driven tasks with sub tasks. Version 1.0 uses lazy streams which are simpler and more powerful.
• Letter match example now matches all polygons instead of just the first found.
• When running ShapeLogic as ImageJ plugin, it is now easy for users to define rules for matching in external Java files.
• New number matcher to demonstrate how to define rules for matching in an external Java file in 130 lines of code.
• Enabled use of Java 6 Scripting for rule database, which gives the user access to the 25 scripting languages that are supported
• ShapeLogic now has beta development status
• Many unit tests added for Lazy Stream library
• Fixed bugs in Lazy Stream library
• Fixed bugs in vectorizer

Lazy streams features

• Lazy streams can be named and defined based on other lazy streams
  
• They work similarly to UNIX pipes or calculation Legos
• They serve as your query construct, you can directly query them
• A stream can be wrapped around an Iterator
• A stream can be created from an input stream and a Calculation
  
• They can be instantiated lazily, so you can load calculation networks independently
  

The lazy stream worked very well with the letter match. It started out as a functional construct, but with the named streams they got a more declarative feel to them.

The Calculation in the stream is using the same signature as Neal Grafter's Java 7 closure prototype. This might make integration with Java 7 easier.

User defined rules for number match

The most significant change is that it has become a lot simpler for users to define rules. Here is the start of DigitStreamVectorizer_ the number matchre in 130 lines of code. Notice that there is barely any setup code. It is almost only rules, defined in a very simple format.

public class DigitStreamVectorizer_ extends StreamVectorizer_ {

@Override
public void matchSetup(ImageProcessor ip) {
 loadDigitStream();
}

public static void loadDigitStream() {
 LoadPolygonStreams.loadStreamsRequiredForLetterMatch();
 makeDigitStream();
 String[] digits = {"0", "1", "2", "3", "4", "5", "6", "7", "8", "9"};
LoadLetterStreams.makeLetterXOrStream(digits);
}

public static void makeDigitStream() {

 rule("0", HOLE_COUNT, "==", 1.);
 rule("0", T_JUNCTION_POINT_COUNT, "==", 0.);
 rule("0", END_POINT_COUNT, "==", 0.);
 rule("0", MULTI_LINE_COUNT, "==", 1.);
 rule("0", CURVE_ARCH_COUNT, ">", 0.);
 rule("0", HARD_CORNER_COUNT, "==", 0.);
 rule("0", SOFT_POINT_COUNT, ">", 0.);

 rule("1", HOLE_COUNT, "==", 0.);
 rule("1", T_JUNCTION_LEFT_POINT_COUNT, "==", 0.);
 rule("1", T_JUNCTION_RIGHT_POINT_COUNT, "==", 0.);
 rule("1", END_POINT_BOTTOM_POINT_COUNT, "==", 1.);
 rule("1", HORIZONTAL_LINE_COUNT, "==", 0.);
 rule("1", VERTICAL_LINE_COUNT, "==", 1.);
 rule("1", END_POINT_COUNT, "==", 2.);
 rule("1", MULTI_LINE_COUNT, "==", 0.);
 rule("1", SOFT_POINT_COUNT, "==", 0.);
 rule("1", ASPECT_RATIO, "<", 0.4);  

ShapeLogic's 3 different approaches to declarative programming

Here is a chronological listing of ShapeLogic's 3 different approaches declarative logic:

1. Declarative goal driven logic engine. From ShapeLogic 0.2.
2. Logic filter language. From ShapeLogic 0.8 The syntax and development of the logic language is better described in Logic language.
3. Lazy streams. From ShapeLogic 0.9.

Result of different approaches so far

For the letter matching example, the lazy stream approach has been both simpler and more powerful than the goal driven logic engine.

The Artificial Intelligence choice tree is built into the logical structure of goal driven logic engine, so this approach might work well when reasoning under uncertainty.

The logic filter language is used with both lazy streams and goal driven approach.

ShapeLogic is a toolkit, all 3 approaches are available with unit tests.

For now development is focused on the lazy stream approach.

JSR 223 scripting surprise

I had put a lot of energy into making it easy to create a stream from a Scripting snippet in either Groovy, JRuby or JavaScript. This was clearly superior to text snippet rules defined using Apache Commons JEXL under the Declarative goal driven approach, but using the new Stream it turned out not to be necessary. The rules could easily be defined in plain Java. I still think that good integration with streams and Scripting from ShapeLogic might turn out to be useful.

Download ShapeLogic 1.0

-Sami Badawi
http://www.shapelogic.org

Lazy streams in mathematics and vision

ShapeLogic 0.9 contains new functional and declarative constructs

1. Lazy streams
2. Simplified and expanded lazy calculations

The functional and declarative construct of ShapeLogic can be used independently of the image processing code. It only requires a 200 KB jar file to use this in other application, and there is no dependency of third party jars.

ShapeLogic 0.9 letter recognition example is still using a different system for declarative programming. More on that later in this post.

To test lazy streams in pure form I tried them on the 10 first mathematical problems in Project Euler. I think that ShapeLogic streams provided for simple solutions to the mathematical problems.
However they are more verbose that say solutions in the Scala language:
http://scala-blogs.org/2007/12/project-euler-fun-in-scala.html

Solutions to a few of the Project Euler mathematical problems

Project Euler is a list of 178, mathematical problems, that can be solved by computers.

1 Add all the natural numbers below 1000 that are multiples of 3 or 5

NaturalNumberStream naturalNumberStream = new NaturalNumberStream(1,999);
ListFilterStream<Integer> filter = new BaseListFilterStream<Integer>(naturalNumberStream) {
public boolean evaluate(Integer object) {return object % 3 == 0 || object % 5 == 0;}
};
SumAccumulator accumulator = new SumAccumulator(filter);
System.out.println(accumulator.getValue());

2 Find the sum of all the even-valued terms in the Fibonacci sequence which do not exceed one million

BaseListStream1<Object,Integer>fibonacci = new BaseListStream1<Object,Integer>(){
{ _list.add(1); _list.add(2);}
public Integer invoke(Object input, int index) {return get(index-2) + get(index-1);}
};
ListFilterStream<Integer> filter = new BaseListFilterStream<Integer>(fibonacci) {
public boolean evaluate(Integer object) { return object % 2 == 0; }
};
SumAccumulator accumulator = new SumAccumulator(filter) {
{_inputElement = 0;}
public boolean hasNext(){ return _inputElement <= theNumber; }
};
System.out.println(accumulator.getValue());

More solutions to Project Euler

Here are the next 8 solutions:
10 first solutions to Project Euler in ShapeLogic
10 first solutions to Project Euler as Java unit tests

Comparison between streams and old declarative constructs

In ShapeLogic 0.8 a cornerstone in declarative programming was a goal driven system of tasks with sub tasks. The letter recognition example reads in a rule database and translated it into goals/tasks with sub tasks. Somewhat like the programming language Prolog.
In case of uncertainty the different choices would live in an artificial intelligence choice tree that is tied to the tree of tasks and sub tasks.

Integrating old declarative constructs with lazy streams

Based on what is needed in the current letter match example. It seems like the stream based approach is simpler and able to handle all the problem that the goal driven approach could.
I expect the stream approach to supersede the goal approach.
The rule database will be read and translated to streams. So the rule for the letter A would be translated into a filter that could filter a stream of polygons into a stream of polygons that represent the letter A.

Also currently the rules now are using JEXL to translate a text rule into something executable.
Example:
Rule for letter A: polygon.holeCount == 1.
In ShapeLogic 1.0, you should be able to use Java 6 Scripting, JSR 223, to be able to define these rules, in one of the 25 supported scripting languages. In ShapeLogic 0.9: Groovy, JRuby, and JavaScript was tested with streams, but not with the rule databases.

Using streams for concurrent programming

Streams can also support parallel or concurrent programming, which is important with the CPU intensive operations in image processing and computer vision. Especially with the advent of cheap multi processor machines.

Example: Find polygons in a stack of images

You define a lazy data stream for this and set a stream property
randomAccess = true
This indicates that individual elements can be calculated independently. The factory creating the stream could create a parallel version of the stream and assign each operation its own thread. Note that the result would be a stream of polygons for each image.

-Sami Badawi

ShapeLogic 0.9 with lazy stream library released

Here are the release notes, I will soon describe the changes in more details.

This is the first release where ShapeLogic is moving beyond current parameters as a plugin library for ImageJ, currently only used in a letter recognition example. The improved system will be for declarative programming where the user can define rules in either a database or flat file. The focus will still be on image processing and computer vision, but the system will be more broadly applicable. There has been no new work on image processing or letter recognition in this release. ShapeLogic 1.0 will combine these new changes with the current image processing code.

Changes

• Introduce new functional, declarative and query constructs to Java
• Implement lazy streams like Haskell, Scala or Scheme
• These functional constructs are very lightweight and you only need one 200KB jar file to use it in other applications
• Test streams by solving the first 10 mathematical problems from Project Euler
• Enabled Java 6 Scripting for evaluating expressions.
  
• Tested with Groovy, JRuby, JavaScript, but should work with other supported Scripting languages, currently that are 25 of these. This makes it possible for users to add rule, formulas and queries in real time using text format. They can interact with a running Java application, which can be useful in science, finance or web applications.

-Sami Badawi

Lazy streams in Java, Groovy, JavaScript, JRuby

This is a follow up to my last blog: Functional constructs Java 7, Groovy, Commons

I have finished coding the first part of the lazy streams for ShapeLogic. They are going to be key for the declarative programming query interface to ShapeLogic. As a proof of concept I wanted to see how easy it would be to implement a lazy stream of Fibonacci numbers. So far I have tested my framework with definitions written in:

1. Groovy
2. JavaScript
3. JRuby
4. Java

It is essential that lazy streams are are easy to define so they can be put in a flat file or a database. I was very satisfied with the concise definitions of the Fibonacci streams in the different languages:

Lazy Fibonacci stream in Groovy

new FunctionStream("fibo","def fibo_FUNCTION_ = { fibo.get(it-2) + fibo.get(it-1) };",1,1);

fibo is the name the lazy stream has in the context / name space
fibo_FUNCTION_ it is a naming convention that the function that is use to create the stream has this name
1,1 is the first part of the lazy stream

Lazy Fibonacci stream in JRuby

new FunctionStream("fibo","jruby",null,"def fibo_FUNCTION_(it) return $fibo.get(it-2) + $fibo.get(it-1) end",1,1)

Lazy Fibonacci stream in JavaScript

new FunctionStream("fibo","javascript",null,"function fibo_FUNCTION_(it) { return parseInt(fibo.get(it-2) ) + parseInt(fibo.get(it-1))};",1,1);

Scripting using JSR 223

I added a formula language for users to an enterprise Java system a few years back using Antlr and BeanShell. JSR 223 is dramatically easier to work with, but there are still some problems.

The only scripting language that works out of the box with Java 6 is JavaScript. To get others to work you have to download jsr223-engines.zip from:
https://scripting.dev.java.net/servlets/ProjectDocumentList
For each language you want to use there is a engine jar file.
E.g. jruby-engine.jar.
They have to be on your path. So does the jar file implementing the language.

JSR 223 and Maven 2 problems

JSR 223 does not work well with Maven 2. The engine jar file does not reside in the Maven repository so you have to separately install them into you local Maven repository. Here is the command to install JRuby:
~/bin/maven-2.0.8/bin/mvn install:install-file -Dfile=jruby-engine.jar -DgroupId=org.jruby -DartifactId=jruby-engine -Dversion=1.0.1 -Dpackaging=jar

Scripting languages currently under JSR 223

beanshell, browserjs, ejs, freemarker, groovy, jacl, jaskell, java, javascript, jawk, jelly, jep, jexl, jruby, jst, judo, juel, jython, ognl, pnuts, scheme, sleep, velocity, xpath, xslt.
These languages should in theory work with ShapeLogic, without any additional code.

Other implementations of lazy streams

1. BaseStream: That is the abstract base class with most of the lazy stream functionality
2. IteratorStream: Generates elements using Java Iterator
3. TransformerStream: Generates elements using Java interface
4. FunctionStream: Generates elements using JRS 223 as described above
   

Next step for functional constructs for ShapeLogic

1. Filter that is easy to define in external text using scripting
2. Transformer transforming one lazy stream to the next
3. Query interface from where a result can be retrieved

-Sami Badawi