Merge pull request kodecocodes#349 from taiheng/feature/swift3-kmeans

Migrate K-Means to Swift 3 Syntax

Author: kelvinlauKL

.travis.yml

@@ -25,7 +25,7 @@ script:
 # - xcodebuild test -project ./Heap/Tests/Tests.xcodeproj -scheme Tests
 - xcodebuild test -project ./Heap\ Sort/Tests/Tests.xcodeproj -scheme Tests
 - xcodebuild test -project ./Insertion\ Sort/Tests/Tests.xcodeproj -scheme Tests
-# - xcodebuild test -project ./K-Means/Tests/Tests.xcodeproj -scheme Tests
+- xcodebuild test -project ./K-Means/Tests/Tests.xcodeproj -scheme Tests
 # - xcodebuild test -project ./Linked\ List/Tests/Tests.xcodeproj -scheme Tests
 - xcodebuild test -project ./Longest\ Common\ Subsequence/Tests/Tests.xcodeproj -scheme Tests
 - xcodebuild test -project ./Minimum\ Spanning\ Tree\ \(Unweighted\)/Tests/Tests.xcodeproj -scheme Tests

K-Means/KMeans.swift

@@ -11,11 +11,11 @@ class KMeans<Label: Hashable> {
  self.numCenters = labels.count
  }
 
- private func indexOfNearestCenter(x: Vector, centers: [Vector]) -> Int {
+ private func indexOfNearestCenter(_ x: Vector, centers: [Vector]) -> Int {
  var nearestDist = DBL_MAX
  var minIndex = 0
 
- for (idx, center) in centers.enumerate() {
+ for (idx, center) in centers.enumerated() {
  let dist = x.distanceTo(center)
  if dist < nearestDist {
  minIndex = idx
@@ -25,16 +25,16 @@ class KMeans<Label: Hashable> {
  return minIndex
  }
 
- func trainCenters(points: [Vector], convergeDistance: Double) {
- let zeroVector = Vector([Double](count: points[0].length, repeatedValue: 0))
+ func trainCenters(_ points: [Vector], convergeDistance: Double) {
+ let zeroVector = Vector([Double](repeating: 0, count: points[0].length))
 
  // Randomly take k objects from the input data to make the initial centroids.
  var centers = reservoirSample(points, k: numCenters)
 
  var centerMoveDist = 0.0
  repeat {
  // This array keeps track of which data points belong to which centroids.
- var classification: [[Vector]] = .init(count: numCenters, repeatedValue: [])
+ var classification: [[Vector]] = .init(repeating: [], count: numCenters)
 
  // For each data point, find the centroid that it is closest to.
  for p in points {
@@ -45,7 +45,7 @@ class KMeans<Label: Hashable> {
  // Take the average of all the data points that belong to each centroid.
  // This moves the centroid to a new position.
  let newCenters = classification.map { assignedPoints in
- assignedPoints.reduce(zeroVector, combine: +) / Double(assignedPoints.count)
+ assignedPoints.reduce(zeroVector, +) / Double(assignedPoints.count)
  }
 
  // Find out how far each centroid moved since the last iteration. If it's
@@ -61,22 +61,22 @@ class KMeans<Label: Hashable> {
  centroids = centers
  }
 
- func fit(point: Vector) -> Label {
+ func fit(_ point: Vector) -> Label {
  assert(!centroids.isEmpty, "Exception: KMeans tried to fit on a non trained model.")
 
  let centroidIndex = indexOfNearestCenter(point, centers: centroids)
  return labels[centroidIndex]
  }
 
- func fit(points: [Vector]) -> [Label] {
+ func fit(_ points: [Vector]) -> [Label] {
  assert(!centroids.isEmpty, "Exception: KMeans tried to fit on a non trained model.")
 
  return points.map(fit)
  }
 }
 
 // Pick k random elements from samples
-func reservoirSample<T>(samples: [T], k: Int) -> [T] {
+func reservoirSample<T>(_ samples: [T], k: Int) -> [T] {
  var result = [T]()
 
  // Fill the result array with first k elements

K-Means/Tests/KMeansTests.swift

@@ -10,7 +10,7 @@ import Foundation
 import XCTest
 
 class KMeansTests: XCTestCase {
- func genPoints(numPoints: Int, numDimensions: Int) -> [Vector] {
+ func genPoints(_ numPoints: Int, numDimensions: Int) -> [Vector] {
  var points = [Vector]()
  for _ in 0..<numPoints {
  var data = [Double]()

K-Means/Tests/Tests.xcodeproj/project.pbxproj

@@ -85,10 +85,11 @@
 isa = PBXProject;
 attributes = {
 LastSwiftUpdateCheck = 0720;
-LastUpgradeCheck = 0730;
+LastUpgradeCheck = 0820;
 TargetAttributes = {
 B80894DF1C852D100018730E = {
 CreatedOnToolsVersion = 7.2.1;
+LastSwiftMigration = 0820;
 };
 };
 };
@@ -136,14 +137,49 @@
 B80894D91C852CDC0018730E /* Debug */ = {
 isa = XCBuildConfiguration;
 buildSettings = {
+CLANG_WARN_BOOL_CONVERSION = YES;
+CLANG_WARN_CONSTANT_CONVERSION = YES;
+CLANG_WARN_EMPTY_BODY = YES;
+CLANG_WARN_ENUM_CONVERSION = YES;
+CLANG_WARN_INFINITE_RECURSION = YES;
+CLANG_WARN_INT_CONVERSION = YES;
+CLANG_WARN_SUSPICIOUS_MOVE = YES;
+CLANG_WARN_UNREACHABLE_CODE = YES;
+CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
+ENABLE_STRICT_OBJC_MSGSEND = YES;
 ENABLE_TESTABILITY = YES;
+GCC_NO_COMMON_BLOCKS = YES;
+GCC_WARN_64_TO_32_BIT_CONVERSION = YES;
+GCC_WARN_ABOUT_RETURN_TYPE = YES;
+GCC_WARN_UNDECLARED_SELECTOR = YES;
+GCC_WARN_UNINITIALIZED_AUTOS = YES;
+GCC_WARN_UNUSED_FUNCTION = YES;
+GCC_WARN_UNUSED_VARIABLE = YES;
 ONLY_ACTIVE_ARCH = YES;
 };
 name = Debug;
 };
 B80894DA1C852CDC0018730E /* Release */ = {
 isa = XCBuildConfiguration;
 buildSettings = {
+CLANG_WARN_BOOL_CONVERSION = YES;
+CLANG_WARN_CONSTANT_CONVERSION = YES;
+CLANG_WARN_EMPTY_BODY = YES;
+CLANG_WARN_ENUM_CONVERSION = YES;
+CLANG_WARN_INFINITE_RECURSION = YES;
+CLANG_WARN_INT_CONVERSION = YES;
+CLANG_WARN_SUSPICIOUS_MOVE = YES;
+CLANG_WARN_UNREACHABLE_CODE = YES;
+CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
+ENABLE_STRICT_OBJC_MSGSEND = YES;
+GCC_NO_COMMON_BLOCKS = YES;
+GCC_WARN_64_TO_32_BIT_CONVERSION = YES;
+GCC_WARN_ABOUT_RETURN_TYPE = YES;
+GCC_WARN_UNDECLARED_SELECTOR = YES;
+GCC_WARN_UNINITIALIZED_AUTOS = YES;
+GCC_WARN_UNUSED_FUNCTION = YES;
+GCC_WARN_UNUSED_VARIABLE = YES;
+SWIFT_OPTIMIZATION_LEVEL = "-Owholemodule";
 };
 name = Release;
 };
@@ -193,6 +229,7 @@
 PRODUCT_NAME = "$(TARGET_NAME)";
 SDKROOT = macosx;
 SWIFT_OPTIMIZATION_LEVEL = "-Onone";
+SWIFT_VERSION = 3.0;
 };
 name = Debug;
 };
@@ -234,6 +271,7 @@
 PRODUCT_BUNDLE_IDENTIFIER = com.alvahouse322.Tests;
 PRODUCT_NAME = "$(TARGET_NAME)";
 SDKROOT = macosx;
+SWIFT_VERSION = 3.0;
 };
 name = Release;
 };

K-Means/Tests/Tests.xcodeproj/xcshareddata/xcschemes/Tests.xcscheme

@@ -1,6 +1,6 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <Scheme
- LastUpgradeVersion = "0730"
+ LastUpgradeVersion = "0820"
  version = "1.3">
  <BuildAction
  parallelizeBuildables = "YES"

K-Means/Tests/Vector.swift

@@ -13,7 +13,7 @@ struct Vector: CustomStringConvertible, Equatable {
  return "Vector (\(data)"
  }
 
- func distanceTo(other: Vector) -> Double {
+ func distanceTo(_ other: Vector) -> Double {
  var result = 0.0
  for idx in 0..<length {
  result += pow(data[idx] - other.data[idx], 2.0)
@@ -39,7 +39,7 @@ func + (left: Vector, right: Vector) -> Vector {
  return Vector(results)
 }
 
-func += (inout left: Vector, right: Vector) {
+func += (left: inout Vector, right: Vector) {
  left = left + right
 }
 
@@ -51,18 +51,18 @@ func - (left: Vector, right: Vector) -> Vector {
  return Vector(results)
 }
 
-func -= (inout left: Vector, right: Vector) {
+func -= (left: inout Vector, right: Vector) {
  left = left - right
 }
 
 func / (left: Vector, right: Double) -> Vector {
- var results = [Double](count: left.length, repeatedValue: 0)
- for (idx, value) in left.data.enumerate() {
+ var results = [Double](repeating: 0, count: left.length)
+ for (idx, value) in left.data.enumerated() {
  results[idx] = value / right
  }
  return Vector(results)
 }
 
-func /= (inout left: Vector, right: Double) {
+func /= (left: inout Vector, right: Double) {
  left = left / right
 }