Minor documentation update
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README.md
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README.md
@ -6,15 +6,29 @@ and `scipy` it is modular and has a lightweight core.
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* **Algebra**
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* Mathematical operation entities like rings, spaces and fields with (**TODO** add example to wiki)
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* Basic linear algebra operations (summs products, etc) backed by `Space` API.
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* Basic linear algebra operations (sums products, etc) backed by `Space` API.
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* [In progress] advanced linear algebra operations like matrix inversions.
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* **Array-like structures** Full support of numpy-like ndarray including mixed ariphmetic operations and function operations
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* **Array-like structures** Full support of numpy-like ndarray including mixed arithmetic operations and function operations
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on arrays and numbers just like it works in python (with benefit of static type checking).
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## Planned features
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* **Common mathematics** It is planned to gradually wrap most parts of [Apache commons-math](http://commons.apache.org/proper/commons-math/)
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library in kotlin code and maybe rewrite some parts to better suite kotlin programming paradigm. There is no fixed priority list for that. Feel free
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to submit a future request if you want something to be done first.
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* **Expressions** Expressions are one of the ultimate goals of kmath. It is planned to be able to write some mathematical
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expression once an then apply it to different types of objects by providing different context. Exception could be used
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for a wide variety of purposes from high performance calculations to code generation.
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* **Messaging** A mathematical notation to support multilanguage and multinod communication for mathematical tasks.
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## Multi-platform support
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KMath is developed as a multi-platform library, which means that most of interfaces are declared in common module.
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Implementation is also done in common module wherever it is possible. In some cases features are delegated to
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platform even if they could be done in common module because of platform performance optimization.
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platform even if they could be done in common module because of platform performance optimization.
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Currently the main focus of development is the JVM platform, contribution of implementations for Kotlin - Native and
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Kotlin - JS is welcome.
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## Performance
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The calculation performance is one of major goals of KMath in the future, but in some cases it is not possible to achieve
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@ -3,6 +3,8 @@ package scientifik.kmath.operations
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/**
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* The generic mathematics elements which is able to store its context
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* @param T the self type of the element
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* @param S the type of mathematical context for this element
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*/
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interface MathElement<T, S>{
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/**
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