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Commit 1ada79c

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Replaced random & shuffle with versions from previous chapters; tuned wine and iris examples.
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  • Classic Computer Science Problems in Swift.playground/Pages/Chapter 7.xcplaygroundpage

1 file changed

+119
-82
lines changed

‎Classic Computer Science Problems in Swift.playground/Pages/Chapter 7.xcplaygroundpage/Contents.swift

Lines changed: 119 additions & 82 deletions
Original file line numberDiff line numberDiff line change
@@ -23,20 +23,42 @@ import Foundation
2323

2424
// MARK: Randomization & Statistical Helpers
2525

26+
struct Random {
27+
private static var seeded = false
28+
29+
// a random Double between *from* and *to*, assumes *from* < *to*
30+
static func double(from: Double, to: Double) -> Double {
31+
if !Random.seeded {
32+
srand48(time(nil))
33+
Random.seeded = true
34+
}
35+
36+
return (drand48() * (to - from)) + from
37+
}
38+
}
39+
2640
/// Create *number* of random Doubles between 0.0 and 1.0
2741
func randomWeights(number: Int) -> [Double] {
28-
return (0..<number).map{ _ in Math.randomFractional() }
42+
return (0..<number).map{ _ in Random.double(from:0.0, to:1.0) }
2943
}
3044

3145
/// Create *number* of random Doubles between 0.0 and *limit*
3246
func randomNums(number: Int, limit: Double) -> [Double] {
33-
return (0..<number).map{ _ in Math.randomTo(limit: limit) }
47+
return (0..<number).map{ _ in Random.double(from:0.0, to: limit) }
3448
}
3549

36-
/// primitive shuffle - not fisher yates... not uniform distribution
37-
extension Sequence where Iterator.Element : Comparable {
38-
var shuffled: [Self.Iterator.Element] {
39-
return sorted { _, _ in arc4random() % 2 == 0 }
50+
// A derivative of the Fisher-Yates algorithm to shuffle an array
51+
extension Array {
52+
public func shuffled() -> Array<Element> {
53+
var shuffledArray = self // value semantics (Array is Struct) makes this a copy
54+
if count < 2 { return shuffledArray } // already shuffled
55+
for i in (1..<count).reversed() { // count backwards
56+
let position = Int(arc4random_uniform(UInt32(i + 1))) // random to swap
57+
if i != position { // swap with the end, don't bother with selp swaps
58+
shuffledArray.swapAt(i, position)
59+
}
60+
}
61+
return shuffledArray
4062
}
4163
}
4264

@@ -106,36 +128,7 @@ public func sum(x: [Double]) -> Double {
106128
return result
107129
}
108130

109-
// MARK: Random Number Generation
110131

111-
// this struct & the randomFractional() function
112-
// based on http://stackoverflow.com/a/35919911/281461
113-
struct Math {
114-
private static var seeded = false
115-
116-
static func randomFractional() -> Double {
117-
118-
if !Math.seeded {
119-
let time = Int(NSDate().timeIntervalSinceReferenceDate)
120-
srand48(time)
121-
Math.seeded = true
122-
}
123-
124-
return drand48()
125-
}
126-
127-
// addition, just multiplies random number by *limit*
128-
static func randomTo(limit: Double) -> Double {
129-
130-
if !Math.seeded {
131-
let time = Int(NSDate().timeIntervalSinceReferenceDate)
132-
srand48(time)
133-
Math.seeded = true
134-
}
135-
136-
return drand48() * limit
137-
}
138-
}
139132

140133
/// An individual node in a layer
141134
class Neuron {
@@ -282,8 +275,7 @@ class Network {
282275

283276
/// for generalized results that require classification
284277
/// this function will return the correct number of trials
285-
/// and the percentge correct out of the total
286-
/// See the unit tests for some examples
278+
/// and the percentage correct out of the total
287279
func validate<T: Equatable>(inputs:[[Double]], expecteds:[T], interpretOutput: ([Double]) -> T) -> (correct: Int, total: Int, percentage: Double) {
288280
var correct = 0
289281
for (input, expected) in zip(inputs, expecteds) {
@@ -295,75 +287,120 @@ class Network {
295287
let percentage = Double(correct) / Double(inputs.count)
296288
return (correct, inputs.count, percentage)
297289
}
298-
299-
// for when result is a single neuron
300-
func validate(inputs:[[Double]], expecteds:[Double], accuracy: Double) -> (correct: Int, total: Int, percentage: Double) {
301-
var correct = 0
302-
for (input, expected) in zip(inputs, expecteds) {
303-
let result = outputs(input: input)[0]
304-
if abs(expected - result) < accuracy {
305-
correct += 1
306-
}
307-
}
308-
let percentage = Double(correct) / Double(inputs.count)
309-
return (correct, inputs.count, percentage)
310-
}
311290
}
312291

313-
var network: Network = Network(layerStructure: [13,7,3], learningRate: 7.0)
314-
// for training
315-
var wineParameters: [[Double]] = [[Double]]()
316-
var wineClassifications: [[Double]] = [[Double]]()
317-
// for testing/validation
318-
var wineSamples: [[Double]] = [[Double]]()
319-
var wineCultivars: [Int] = [Int]()
292+
/// Wine Test
293+
294+
//var network: Network = Network(layerStructure: [13,7,3], learningRate: 7.0)
295+
//// for training
296+
//var wineParameters: [[Double]] = [[Double]]()
297+
//var wineClassifications: [[Double]] = [[Double]]()
298+
//// for testing/validation
299+
//var wineSamples: [[Double]] = [[Double]]()
300+
//var wineCultivars: [Int] = [Int]()
301+
//
302+
//func parseWineCSV() {
303+
// let myBundle = Bundle.main
304+
// let urlpath = myBundle.path(forResource: "wine", ofType: "csv")
305+
// let url = URL(fileURLWithPath: urlpath!)
306+
// let csv = try! String.init(contentsOf: url)
307+
// let lines = csv.components(separatedBy: "\n")
308+
//
309+
// let shuffledLines = lines.shuffled()
310+
// for line in shuffledLines {
311+
// if line == "" { continue }
312+
// let items = line.components(separatedBy: ",")
313+
// let parameters = items[1...13].map{ Double(0ドル)! }
314+
// wineParameters.append(parameters)
315+
// let species = Int(items[0])!
316+
// if species == 1 {
317+
// wineClassifications.append([1.0, 0.0, 0.0])
318+
// } else if species == 2 {
319+
// wineClassifications.append([0.0, 1.0, 0.0])
320+
// } else {
321+
// wineClassifications.append([0.0, 0.0, 1.0])
322+
// }
323+
// wineCultivars.append(species)
324+
// }
325+
// normalizeByColumnMax(dataset: &wineParameters)
326+
// wineSamples = Array(wineParameters.dropFirst(150))
327+
// wineCultivars = Array(wineCultivars.dropFirst(150))
328+
// wineParameters = Array(wineParameters.dropLast(28))
329+
//}
330+
//
331+
//func interpretOutput(output: [Double]) -> Int {
332+
// if output.max()! == output[0] {
333+
// return 1
334+
// } else if output.max()! == output[1] {
335+
// return 2
336+
// } else {
337+
// return 3
338+
// }
339+
//}
340+
//
341+
//parseWineCSV()
342+
//// train over entire data set 5 times
343+
//for _ in 0..<5 {
344+
// network.train(inputs: wineParameters, expecteds: wineClassifications, printError: false)
345+
//}
346+
//
347+
//let results = network.validate(inputs: wineSamples, expecteds: wineCultivars, interpretOutput: interpretOutput)
348+
//print("\(results.correct) correct of \(results.total) = \(results.percentage * 100)%")
349+
350+
var network: Network = Network(layerStructure: [4,5,3], learningRate: 0.3)
351+
var irisParameters: [[Double]] = [[Double]]()
352+
var irisClassifications: [[Double]] = [[Double]]()
353+
var irisSpecies: [String] = [String]()
320354

321-
func parseWineCSV() {
355+
func parseIrisCSV() {
322356
let myBundle = Bundle.main
323-
let urlpath = myBundle.path(forResource: "wine", ofType: "csv")
357+
let urlpath = myBundle.path(forResource: "iris", ofType: "csv")
324358
let url = URL(fileURLWithPath: urlpath!)
325359
let csv = try! String.init(contentsOf: url)
326360
let lines = csv.components(separatedBy: "\n")
327361

328-
let shuffledLines = lines.shuffled
362+
let shuffledLines = lines.shuffled()
329363
for line in shuffledLines {
330364
if line == "" { continue }
331365
let items = line.components(separatedBy: ",")
332-
let parameters = items[1...13].map{ Double(0ドル)! }
333-
wineParameters.append(parameters)
334-
let species = Int(items[0])!
335-
if species == 1 {
336-
wineClassifications.append([1.0, 0.0, 0.0])
337-
} else if species == 2 {
338-
wineClassifications.append([0.0, 1.0, 0.0])
366+
let parameters = items[0...3].map{ Double(0ドル)! }
367+
irisParameters.append(parameters)
368+
let species = items[4]
369+
if species == "Iris-setosa" {
370+
irisClassifications.append([1.0, 0.0, 0.0])
371+
} else if species == "Iris-versicolor" {
372+
irisClassifications.append([0.0, 1.0, 0.0])
339373
} else {
340-
wineClassifications.append([0.0, 0.0, 1.0])
374+
irisClassifications.append([0.0, 0.0, 1.0])
341375
}
342-
wineCultivars.append(species)
376+
irisSpecies.append(species)
343377
}
344-
normalizeByColumnMax(dataset: &wineParameters)
345-
wineSamples = Array(wineParameters.dropFirst(150))
346-
wineCultivars = Array(wineCultivars.dropFirst(150))
347-
wineParameters = Array(wineParameters.dropLast(28))
378+
normalizeByColumnMax(dataset: &irisParameters)
348379
}
349380

350-
func interpretOutput(output: [Double]) -> Int {
381+
func interpretOutput(output: [Double]) -> String {
351382
if output.max()! == output[0] {
352-
return 1
383+
return "Iris-setosa"
353384
} else if output.max()! == output[1] {
354-
return 2
385+
return "Iris-versicolor"
355386
} else {
356-
return 3
387+
return "Iris-virginica"
357388
}
358389
}
359390

360-
parseWineCSV()
361-
// train over entire data set 5 times
362-
for _ in 0..<5 {
363-
network.train(inputs: wineParameters, expecteds: wineClassifications, printError: false)
391+
// Put setup code here. This method is called before the invocation of each test method in the class.
392+
parseIrisCSV()
393+
// train over first 140 irises in data set 20 times
394+
let trainers = Array(irisParameters[0..<140])
395+
let trainersCorrects = Array(irisClassifications[0..<140])
396+
for _ in 0..<20 {
397+
network.train(inputs: trainers, expecteds: trainersCorrects, printError: false)
364398
}
365399

366-
let results = network.validate(inputs: wineSamples, expecteds: wineCultivars, interpretOutput: interpretOutput)
400+
// test over the last 10 of the irses in the data set
401+
let testers = Array(irisParameters[140..<150])
402+
let testersCorrects = Array(irisSpecies[140..<150])
403+
let results = network.validate(inputs: testers, expecteds: testersCorrects, interpretOutput: interpretOutput)
367404
print("\(results.correct) correct of \(results.total) = \(results.percentage * 100)%")
368405

369406
//: [Next](@next)

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