forked from kscience/kmath
Attributes modify->modified
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@ -83,8 +83,8 @@ public fun <A : Attribute<Unit>> Attributes.withAttribute(attribute: A): Attribu
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/**
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* Create a new [Attributes] by modifying the current one
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*/
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public fun <T> Attributes.modify(block: AttributesBuilder<T>.() -> Unit): Attributes = Attributes<T> {
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putAll(this@modify)
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public fun <T> Attributes.modified(block: AttributesBuilder<T>.() -> Unit): Attributes = Attributes<T> {
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putAll(this@modified)
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block()
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}
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@ -26,7 +26,7 @@ public fun <T, A : Any> MultivariateIntegrand<T>.withAttribute(
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public fun <T> MultivariateIntegrand<T>.withAttributes(
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block: AttributesBuilder<MultivariateIntegrand<T>>.() -> Unit,
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): MultivariateIntegrand<T> = withAttributes(attributes.modify(block))
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): MultivariateIntegrand<T> = withAttributes(attributes.modified(block))
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public inline fun <reified T : Any> MultivariateIntegrand(
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attributeBuilder: AttributesBuilder<MultivariateIntegrand<T>>.() -> Unit,
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@ -27,7 +27,7 @@ public fun <T, A : Any> UnivariateIntegrand<T>.withAttribute(
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public fun <T> UnivariateIntegrand<T>.withAttributes(
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block: AttributesBuilder<UnivariateIntegrand<T>>.() -> Unit,
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): UnivariateIntegrand<T> = withAttributes(attributes.modify(block))
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): UnivariateIntegrand<T> = withAttributes(attributes.modified(block))
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public inline fun <reified T : Any> UnivariateIntegrand(
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attributeBuilder: AttributesBuilder<UnivariateIntegrand<T>>.() -> Unit,
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@ -65,7 +65,7 @@ public fun <T> FunctionOptimization<T>.withAttributes(
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modifier: AttributesBuilder<FunctionOptimization<T>>.() -> Unit,
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): FunctionOptimization<T> = FunctionOptimization(
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expression,
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attributes.modify(modifier),
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attributes.modified(modifier),
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)
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/**
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@ -108,7 +108,7 @@ public fun XYOptimization(
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public fun XYFit.withAttributes(
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modifier: AttributesBuilder<XYFit>.() -> Unit,
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): XYFit = XYFit(data, model, attributes.modify(modifier), pointToCurveDistance, pointWeight, xSymbol)
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): XYFit = XYFit(data, model, attributes.modified(modifier), pointToCurveDistance, pointWeight, xSymbol)
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public suspend fun XYColumnarData<Double, Double, Double>.fitWith(
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optimizer: Optimizer<Double, XYFit>,
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@ -123,7 +123,7 @@ public suspend fun XYColumnarData<Double, Double, Double>.fitWith(
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val problem = XYFit(
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this,
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modelExpression,
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attributes.modify<XYFit> {
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attributes.modified<XYFit> {
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set(OptimizationStartPoint(), startingPoint)
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if (!hasAny<OptimizationLog>()) {
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set(OptimizationLog, Loggable.console)
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