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Here comes (long-awaited) 0.4.0
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@@ -6,6 +6,8 @@ Here you can see the full list of changes between each viktor release.
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Version 0.4.0
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-------------
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Released on November 1st 2016
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- Fixed serialization of non-dense matrices.
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- Allowed slicing a `StridedVector` with custom `step`.
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- Replaced `Strided` prefix with `F64`.

README.md

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@@ -4,8 +4,7 @@ viktor [![Build Status](https://travis-ci.org/JetBrains-Research/viktor.svg?bran
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`viktor` implements a restricted subset of NumPy [ndarray] [ndarray] features in
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Kotlin. Here're some of the highlights:
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* A single core data type --- `F64Array` which is backed by either `F64Vector`
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or `F64Matrix`.
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* A single core data type --- `F64Array`, an n-dimensional primitive array.
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* Efficient vectorized operations, which are accelerated using SIMD whenever
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possible.
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* Semi-sweet syntax.
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```gradle
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repositories {
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maven {
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url 'https://dl.bintray.com/jetbrains-research/maven'
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}
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jCenter()
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}
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dependencies {
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compile 'org.jetbrains.bio:viktor:0.3.5'
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compile 'org.jetbrains.bio:viktor:0.4.0'
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}
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```
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[bintray]: https://bintray.com/jetbrains-research/maven/viktor/view
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You can do it with a one-liner
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```bash
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./gradlew clean assemble generatePomFileForMavenJavaPublication bintrayUpload
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./gradlew clean assemble test generatePomFileForMavenJavaPublication bintrayUpload
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```
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Make sure to set Bintray credentials (see API key section

src/main/kotlin/org/jetbrains/bio/viktor/Loader.kt

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@@ -69,8 +69,10 @@ internal object Loader {
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}
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} catch (e: Throwable) {
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System.err.println(listOf(
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"Native SIMD optimization of vector operations is not available.",
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"Fallback Kotlin implementation will be used instead.").joinToString("\n"))
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"Native SIMD optimization of array operations is not available.",
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"Fallback Kotlin implementation will be used instead.",
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"Build viktor for your system from source as described in " +
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"https://github.com/JetBrains-Research/viktor").joinToString("\n"))
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e.printStackTrace(System.err)
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}
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}

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