106 lines
5.9 KiB
Markdown
106 lines
5.9 KiB
Markdown
[](https://confluence.jetbrains.com/display/ALL/JetBrains+on+GitHub)
|
|
[](https://zenodo.org/badge/latestdoi/129486382)
|
|
|
|
[](https://search.maven.org/search?q=g:%22space.kscience%22)
|
|
[](https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven/space/kscience/)
|
|
|
|
# KMath
|
|
|
|
Could be pronounced as `key-math`. The **K**otlin **Math**ematics library was initially intended as a Kotlin-based
|
|
analog to Python's NumPy library. Later we found that kotlin is much more flexible language and allows superior
|
|
architecture designs. In contrast to `numpy` and `scipy` it is modular and has a lightweight core. The `numpy`-like
|
|
experience could be achieved with [kmath-for-real](/kmath-for-real) extension module.
|
|
|
|
[Documentation site (**WIP**)](https://mipt-npm.github.io/kmath/)
|
|
|
|
## Publications and talks
|
|
|
|
* [A conceptual article about context-oriented design](https://proandroiddev.com/an-introduction-context-oriented-programming-in-kotlin-2e79d316b0a2)
|
|
* [Another article about context-oriented design](https://proandroiddev.com/diving-deeper-into-context-oriented-programming-in-kotlin-3ecb4ec38814)
|
|
* [ACAT 2019 conference paper](https://aip.scitation.org/doi/abs/10.1063/1.5130103)
|
|
|
|
# Goal
|
|
|
|
* Provide a flexible and powerful API to work with mathematics abstractions in Kotlin-multiplatform (JVM, JS and Native)
|
|
.
|
|
* Provide basic multiplatform implementations for those abstractions (without significant performance optimization).
|
|
* Provide bindings and wrappers with those abstractions for popular optimized platform libraries.
|
|
|
|
## Non-goals
|
|
|
|
* Be like NumPy. It was the idea at the beginning, but we decided that we can do better in API.
|
|
* Provide the best performance out of the box. We have specialized libraries for that. Need only API wrappers for them.
|
|
* Cover all cases as immediately and in one bundle. We will modularize everything and add new features gradually.
|
|
* Provide specialized behavior in the core. API is made generic on purpose, so one needs to specialize for types, like
|
|
for `Double` in the core. For that we will have specialization modules like `kmath-for-real`, which will give better
|
|
experience for those, who want to work with specific types.
|
|
|
|
## Features and stability
|
|
|
|
KMath is a modular library. Different modules provide different features with different API stability guarantees. All
|
|
core modules are released with the same version, but with different API change policy. The features are described in
|
|
module definitions below. The module stability could have the following levels:
|
|
|
|
* **PROTOTYPE**. On this level there are no compatibility guarantees. All methods and classes form those modules could
|
|
break any moment. You can still use it, but be sure to fix the specific version.
|
|
* **EXPERIMENTAL**. The general API is decided, but some changes could be made. Volatile API is marked
|
|
with `@UnstableKMathAPI` or other stability warning annotations.
|
|
* **DEVELOPMENT**. API breaking generally follows semantic versioning ideology. There could be changes in minor
|
|
versions, but not in patch versions. API is protected
|
|
with [binary-compatibility-validator](https://github.com/Kotlin/binary-compatibility-validator) tool.
|
|
* **STABLE**. The API stabilized. Breaking changes are allowed only in major releases.
|
|
|
|
## Modules
|
|
|
|
${modules}
|
|
|
|
## Multi-platform support
|
|
|
|
KMath is developed as a multi-platform library, which means that most of the interfaces are declared in the
|
|
[common source sets](/kmath-core/src/commonMain) and implemented there wherever it is possible. In some cases, features
|
|
are delegated to platform-specific implementations even if they could be provided in the common module for performance
|
|
reasons. Currently, the Kotlin/JVM is the primary platform, however Kotlin/Native and Kotlin/JS contributions and
|
|
feedback are also welcome.
|
|
|
|
## Performance
|
|
|
|
Calculation performance is one of major goals of KMath in the future, but in some cases it is impossible to achieve both
|
|
performance and flexibility.
|
|
|
|
We expect to focus on creating convenient universal API first and then work on increasing performance for specific
|
|
cases. We expect the worst KMath benchmarks will perform better than native Python, but worse than optimized
|
|
native/SciPy (mostly due to boxing operations on primitive numbers). The best performance of optimized parts could be
|
|
better than SciPy.
|
|
|
|
## Requirements
|
|
|
|
KMath currently relies on JDK 11 for compilation and execution of Kotlin-JVM part. We recommend to use GraalVM-CE 11 for
|
|
execution to get better performance.
|
|
|
|
### Repositories
|
|
|
|
Release and development artifacts are accessible from mipt-npm [Space](https://www.jetbrains.com/space/)
|
|
repository `https://maven.pkg.jetbrains.space/mipt-npm/p/sci/maven` (see documentation of
|
|
[Kotlin Multiplatform](https://kotlinlang.org/docs/reference/multiplatform.html) for more details). The repository could
|
|
be reached through [repo.kotlin.link](https://repo.kotlin.link) proxy:
|
|
|
|
```kotlin
|
|
repositories {
|
|
maven("https://repo.kotlin.link")
|
|
}
|
|
|
|
dependencies {
|
|
api("${group}:kmath-core:$version")
|
|
// api("${group}:kmath-core-jvm:$version") for jvm-specific version
|
|
}
|
|
```
|
|
|
|
Gradle `6.0+` is required for multiplatform artifacts.
|
|
|
|
## Contributing
|
|
|
|
The project requires a lot of additional work. The most important thing we need is a feedback about what features are
|
|
required the most. Feel free to create feature requests. We are also welcome to code contributions, especially in issues
|
|
marked with
|
|
[waiting for a hero](https://github.com/mipt-npm/kmath/labels/waiting%20for%20a%20hero) label.
|