forked from kscience/kmath
Switch to multik-default
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@ -5,6 +5,7 @@
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package space.kscience.kmath.tensors
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import edu.mcgill.kaliningraph.power
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import org.jetbrains.kotlinx.multik.api.Multik
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import org.jetbrains.kotlinx.multik.api.linalg.dot
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import org.jetbrains.kotlinx.multik.api.math.exp
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@ -12,13 +13,12 @@ import org.jetbrains.kotlinx.multik.api.ndarray
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import org.jetbrains.kotlinx.multik.ndarray.operations.minus
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import org.jetbrains.kotlinx.multik.ndarray.operations.plus
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import org.jetbrains.kotlinx.multik.ndarray.operations.unaryMinus
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import space.kscience.kmath.multik.multikND
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import space.kscience.kmath.nd.one
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import space.kscience.kmath.operations.DoubleField
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fun main() {
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val a = Multik.ndarray(intArrayOf(1, 2, 3))
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fun main(): Unit = with(DoubleField.multikND) {
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val a = Multik.ndarray(intArrayOf(1, 2, 3)).asType<Double>().wrap()
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val b = Multik.ndarray(doubleArrayOf(1.0, 2.0, 3.0))
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2 + (-a) - 2
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a dot a
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a.exp()
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one(a.shape) - a + power()
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}
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@ -6,7 +6,7 @@ description = "JetBrains Multik connector"
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dependencies {
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api(project(":kmath-tensors"))
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api("org.jetbrains.kotlinx:multik-api:0.1.0")
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api("org.jetbrains.kotlinx:multik-default:0.1.0")
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}
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readme {
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@ -1,5 +1,7 @@
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package space.kscience.kmath.multik
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import org.jetbrains.kotlinx.multik.api.math.cos
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import org.jetbrains.kotlinx.multik.api.math.sin
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import org.jetbrains.kotlinx.multik.api.mk
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import org.jetbrains.kotlinx.multik.api.zeros
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import org.jetbrains.kotlinx.multik.ndarray.data.*
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@ -18,7 +20,7 @@ public open class MultikRingOpsND<T, A : Ring<T>> internal constructor(
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override val elementAlgebra: A
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) : RingOpsND<T, A> {
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public fun MutableMultiArray<T, DN>.wrap(): MultikTensor<T> = MultikTensor(this)
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public fun MutableMultiArray<T, *>.wrap(): MultikTensor<T> = MultikTensor(this.asDNArray())
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override fun structureND(shape: Shape, initializer: A.(IntArray) -> T): MultikTensor<T> {
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val res = mk.zeros<T, DN>(shape, type).asDNArray()
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