添加施密特正交化函数

Author: YdrMaster

build.gradle.kts

@@ -8,7 +8,7 @@ plugins {
 }
 
 group = "org.mechdancer"
-version = "0.2.7-dev-3"
+version = "0.2.7-dev-4"
 
 repositories {
     mavenCentral()

src/main/kotlin/org/mechdancer/algebra/function/vector/Cauculate.kt

@@ -97,3 +97,18 @@ fun Vector.norm(n: Int = 2) =
         2                 -> length
         else              -> toList().sumByDouble { it.pow(n) }.pow(1.0 / n)
     } ?: .0
+
+/** 施密特正交化 */
+fun Sequence<Vector>.orthogonalize(): List<Vector> =
+    fold(mutableListOf<Vector>()) { result, v0 ->
+        result += sequence { yield(v0); for (v in result) yield(v * -(v0 dot v)) }.sum().normalize()
+        result
+    }
+
+/** 施密特正交化 */
+fun Iterable<Vector>.orthogonalize() =
+    asSequence().orthogonalize()
+
+/** 施密特正交化 */
+fun Array<Vector>.orthogonalize() =
+    asSequence().orthogonalize()

src/main/kotlin/org/mechdancer/algebra/function/vector/Copy.kt

@@ -38,8 +38,8 @@ fun Vector.copy(vararg change: Pair<Int, Number>): Vector {
  * Select some dimension of the vector, then copy them to a new vector
  * 从向量选取指定的维度组成新的向量
  */
-fun Vector.select(vararg indexes: Int): Vector =
-    toList().filterIndexed { i, _ -> i in indexes }.let(::ListVector)
+fun Vector.select(vararg indices: Int): Vector =
+    toList().filterIndexed { i, _ -> i in indices }.let(::ListVector)
 
 /**
  * Select a range of index of the dimensions, then copy them to a new vector

src/test/kotlin/org/mechdancer/algebra/vector/TestOrthogonalize.kt

@@ -0,0 +1,23 @@
+package org.mechdancer.algebra.vector
+
+import org.junit.Test
+import org.mechdancer.algebra.doubleEquals
+import org.mechdancer.algebra.function.vector.dot
+import org.mechdancer.algebra.function.vector.isNormalized
+import org.mechdancer.algebra.function.vector.orthogonalize
+import org.mechdancer.algebra.implement.vector.vector3D
+
+class TestOrthogonalize {
+    @Test
+    fun testOrthogonalize() {
+        val orthogonalized =
+            listOf(vector3D(1, 0, 0),
+                   vector3D(1, 2, 3),
+                   vector3D(5, 6, 7)
+            ).orthogonalize()
+        orthogonalized.forEachIndexed { i, v ->
+            assert(v.isNormalized())
+            for (j in 0 until i) assert(doubleEquals(.0, v dot orthogonalized[j]))
+        }
+    }
+}