kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/CMIntegrator.kt

@@ -3,6 +3,7 @@ package space.kscience.kmath.commons.integration
 import org.apache.commons.math3.analysis.integration.IterativeLegendreGaussIntegrator
 import org.apache.commons.math3.analysis.integration.SimpsonIntegrator
 import space.kscience.kmath.integration.*
+import space.kscience.kmath.misc.UnstableKMathAPI
 
 /**
  * Integration wrapper for Common-maths UnivariateIntegrator
@@ -18,7 +19,7 @@ public class CMIntegrator(
     public class MinIterations(public val value: Int) : IntegrandFeature
     public class MaxIterations(public val value: Int) : IntegrandFeature
 
-    override fun evaluate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
+    override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
         val integrator = integratorBuilder(integrand)
         val maxCalls = integrand.getFeature<IntegrandMaxCalls>()?.maxCalls ?: defaultMaxCalls
         val remainingCalls = maxCalls - integrand.calls
@@ -74,4 +75,18 @@ public class CMIntegrator(
                 )
             }
     }
-}
+}
+
+@UnstableKMathAPI
+public var MutableList<IntegrandFeature>.targetAbsoluteAccuracy: Double?
+    get() = filterIsInstance<CMIntegrator.TargetAbsoluteAccuracy>().lastOrNull()?.value
+    set(value){
+        value?.let { add(CMIntegrator.TargetAbsoluteAccuracy(value))}
+    }
+
+@UnstableKMathAPI
+public var MutableList<IntegrandFeature>.targetRelativeAccuracy: Double?
+    get() = filterIsInstance<CMIntegrator.TargetRelativeAccuracy>().lastOrNull()?.value
+    set(value){
+        value?.let { add(CMIntegrator.TargetRelativeAccuracy(value))}
+    }

kmath-commons/src/main/kotlin/space/kscience/kmath/commons/integration/GaussRuleIntegrator.kt

@@ -27,7 +27,7 @@ public class GaussRuleIntegrator(
     private var type: GaussRule = GaussRule.LEGANDRE,
 ) : UnivariateIntegrator<Double> {
 
-    override fun evaluate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
+    override fun integrate(integrand: UnivariateIntegrand<Double>): UnivariateIntegrand<Double> {
         val range = integrand.getFeature<IntegrationRange<Double>>()?.range
             ?: error("Integration range is not provided")
         val integrator: GaussIntegrator = getIntegrator(range)
@@ -87,7 +87,7 @@ public class GaussRuleIntegrator(
             numPoints: Int = 100,
             type: GaussRule = GaussRule.LEGANDRE,
             function: (Double) -> Double,
-        ): Double = GaussRuleIntegrator(numPoints, type).evaluate(
+        ): Double = GaussRuleIntegrator(numPoints, type).integrate(
             UnivariateIntegrand(function, IntegrationRange(range))
         ).value!!
     }

kmath-commons/src/main/kotlin/space/kscience/kmath/commons/optimization/CMOptimizationProblem.kt

@@ -19,7 +19,7 @@ import kotlin.reflect.KClass
 public operator fun PointValuePair.component1(): DoubleArray = point
 public operator fun PointValuePair.component2(): Double = value
 
-public class CMOptimizationProblem(override val symbols: List<Symbol>, ) :
+public class CMOptimizationProblem(override val symbols: List<Symbol>) :
     OptimizationProblem<Double>, SymbolIndexer, OptimizationFeature {
     private val optimizationData: HashMap<KClass<out OptimizationData>, OptimizationData> = HashMap()
     private var optimizatorBuilder: (() -> MultivariateOptimizer)? = null

kmath-commons/src/test/kotlin/space/kscience/kmath/commons/integration/IntegrationTest.kt

@@ -21,8 +21,8 @@ internal class IntegrationTest {
     @Test
     fun customSimpson() {
         val res = CMIntegrator.simpson().integrate(0.0..PI, function) {
-            add(CMIntegrator.TargetRelativeAccuracy(1e-4))
-            add(CMIntegrator.TargetAbsoluteAccuracy(1e-4))
+            targetRelativeAccuracy = 1e-4
+            targetAbsoluteAccuracy = 1e-4
         }
         assertTrue { abs(res - 2) < 1e-3 }
         assertTrue { abs(res - 2) > 1e-12 }

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/Integrator.kt

@@ -7,5 +7,5 @@ public interface Integrator<I: Integrand> {
     /**
      * Run one integration pass and return a new [Integrand] with a new set of features
      */
-    public fun evaluate(integrand: I): I
+    public fun integrate(integrand: I): I
 }

kmath-functions/src/commonMain/kotlin/space/kscience/kmath/integration/UnivariateIntegrand.kt

@@ -39,7 +39,7 @@ public fun UnivariateIntegrator<Double>.integrate(
     range: ClosedRange<Double>,
     vararg features: IntegrandFeature,
     function: (Double) -> Double,
-): Double = evaluate(
+): Double = integrate(
     UnivariateIntegrand(function, IntegrationRange(range), *features)
 ).value ?: error("Unexpected: no value after integration.")
 
@@ -58,7 +58,7 @@ public fun UnivariateIntegrator<Double>.integrate(
         featureBuilder()
         add(IntegrationRange(range))
     }
-    return evaluate(
+    return integrate(
         UnivariateIntegrand(function, *features.toTypedArray())
     ).value ?: error("Unexpected: no value after integration.")
 }