Merge pull request #11 from scottsievert/pr/10

Pull request 10 merge

swix/swix.xcodeproj/project.pbxproj

@@ -208,6 +208,8 @@
 		D24A8549196D7D73009C18AC /* Project object */ = {
 			isa = PBXProject;
 			attributes = {
+				LastSwiftMigration = 0700;
+				LastSwiftUpdateCheck = 0700;
 				LastUpgradeCheck = 0600;
 				ORGANIZATIONNAME = com.scott;
 				TargetAttributes = {

swix/swix.xcodeproj/xcuserdata/scott.xcuserdatad/xcdebugger/Breakpoints_v2.xcbkptlist

@@ -26,11 +26,11 @@
             ignoreCount = "0"
             continueAfterRunningActions = "No"
             filePath = "swix/tests.swift"
-            timestampString = "437169242.142289"
+            timestampString = "459378664.414002"
             startingColumnNumber = "9223372036854775807"
             endingColumnNumber = "9223372036854775807"
-            startingLineNumber = "341"
-            endingLineNumber = "341"
+            startingLineNumber = "340"
+            endingLineNumber = "340"
             landmarkName = "functionTests()"
             landmarkType = "5">
          </BreakpointContent>
@@ -42,11 +42,11 @@
             ignoreCount = "0"
             continueAfterRunningActions = "No"
             filePath = "swix/main.swift"
-            timestampString = "430429795.929013"
+            timestampString = "459388981.990875"
             startingColumnNumber = "9223372036854775807"
             endingColumnNumber = "9223372036854775807"
-            startingLineNumber = "15"
-            endingLineNumber = "15">
+            startingLineNumber = "13"
+            endingLineNumber = "13">
          </BreakpointContent>
       </BreakpointProxy>
       <BreakpointProxy

swix/swix/main.swift

@@ -10,12 +10,5 @@
 import Foundation
 import Swift
 
-
-
 runTests()
-//SpeedTests()
-
-
-
-
-
+//SpeedTests()

swix/swix/speed.swift

@@ -19,13 +19,13 @@ class SpeedTests {
     }
 }
 func time(f:()->(), name:String="function"){
-    var start = NSDate()
+    let start = NSDate()
     f()
-    println(NSString(format:"\(name) time (s): %.4f", -1 * start.timeIntervalSinceNow))
+    print(NSString(format:"\(name) time (s): %.4f", -1 * start.timeIntervalSinceNow))
 }
 func pe1(){
-    var N = 1e6
-    var x = arange(N)
+    let N = 1e6
+    let x = arange(N)
     // seeing where that modulo is 0
     var i = argwhere((abs(x%3) < 1e-9) || (abs(x%5) < 1e-9))
     // println(sum(x[i]))
@@ -38,15 +38,15 @@ func pe10(){
     var top = (sqrt(N.double)).int
     for i in 2 ..< top{
         var max:Int = (N/i)
-        var j = arange(2, max.double) * i.double
+        var j = arange(2, max: max.double) * i.double
         primes[j] *= 0.0
     }
     // sum(primes) is the correct answer
 }
 func pe73(){
     var N = 1e3
     var i = arange(N)+1
-    var (n, d) = meshgrid(i, i)
+    var (n, d) = meshgrid(i, y: i)
 
     var f = (n / d).flat
     f = unique(f)
@@ -57,9 +57,9 @@ func pe73(){
 
 func soft_thresholding(){
     let N = 1e2.int
-    var j = linspace(-1, 1, num:N)
-    var (x, y) = meshgrid(j, j)
-    var z = pow(x, 2) + pow(y, 2)
+    var j = linspace(-1, max: 1, num:N)
+    var (x, y) = meshgrid(j, y: j)
+    var z = pow(x, power: 2) + pow(y, power: 2)
     var i = abs(z) < 0.5
     z[argwhere(i)] *= 0
     z[argwhere(1-i)] -= 0.5
@@ -68,7 +68,7 @@ func soft_thresholding(){
 
 
 func pi_approx(){
-    var N = 1e6
+    let N = 1e6
     var k = arange(N)
     var pi_approx = 1 / (2*k + 1)
     pi_approx[2*k[0..<(N/2).int]+1] *= -1

swix/swix/swix/io.swift

@@ -9,37 +9,36 @@
 import Foundation
 
 // ndarray binary
-func write_binary(x:ndarray, #filename:String, prefix:String=S2_PREFIX){
-    var N = x.n
-    var data = NSData(bytes:!x, length:N*sizeof(Double))
+func write_binary(x:ndarray, filename:String, prefix:String=S2_PREFIX){
+    let N = x.n
+    let data = NSData(bytes:!x, length:N*sizeof(Double))
     data.writeToFile(prefix+"../"+filename, atomically: false)
 }
 func read_binary(filename:String, prefix:String=S2_PREFIX) -> ndarray{
-    var read = NSData(contentsOfFile: prefix+"../"+filename)
-    var l:Int! = read?.length
-    var sD:Int = sizeof(Double)
-    var count = (l.double / sD.double)
+    let read = NSData(contentsOfFile: prefix+"../"+filename)
+    let l:Int! = read?.length
+    let sD:Int = sizeof(Double)
+    let count = (l.double / sD.double)
 
-    var y = zeros(count.int)
+    let y = zeros(count.int)
     read?.getBytes(!y, length: count.int*sizeof(Double))
     return y
 }
 
 // matrix binary
-func write_binary(x:matrix, #filename:String, prefix:String=S2_PREFIX){
-    var y = concat(array(x.shape.0.double, x.shape.1.double), x.flat)
+func write_binary(x:matrix, filename:String, prefix:String=S2_PREFIX){
+    let y = concat(array(x.shape.0.double, x.shape.1.double), y: x.flat)
     write_binary(y, filename:filename, prefix:prefix)
 }
 func read_binary(filename:String, prefix:String=S2_PREFIX)->matrix{
     var a:ndarray = read_binary(filename, prefix:prefix)
-    var (w, h) = (a[0], a[1])
-    var b = reshape(a[2..<a.n], (w.int,h.int))
-    return b
+    let (w, h) = (a[0], a[1])
+    return reshape(a[2..<a.n], shape: (w.int,h.int))
 }
 
 
 // ndarray csv
-func write_csv(x:ndarray, #filename:String, prefix:String=S2_PREFIX){
+func write_csv(x:ndarray, filename:String, prefix:String=S2_PREFIX){
     // write the array to CSV
     var seperator=","
     var str = ""
@@ -48,21 +47,26 @@ func write_csv(x:ndarray, #filename:String, prefix:String=S2_PREFIX){
         str += String(format: "\(x[i])"+seperator)
     }
     str += "\n"
-    var error:NSError?
-    str.writeToFile(prefix+"../"+filename, atomically: false, encoding: NSUTF8StringEncoding, error: &error)
-    if let error=error{
-        println("File probably wasn't recognized \n\(error)")
+    do {
+        try str.writeToFile(prefix+"../"+filename, atomically: false, encoding: NSUTF8StringEncoding)
+    } catch {
+        Swift.print("File probably wasn't recognized")
     }
 
 }
 func read_csv(filename:String, prefix:String=S2_PREFIX) -> ndarray{
-    var x = String(contentsOfFile: prefix+"../"+filename, encoding: NSUTF8StringEncoding, error: nil)
+    var x: String?
+    do {
+        x = try String(contentsOfFile: prefix+"../"+filename, encoding: NSUTF8StringEncoding)
+    } catch _ {
+        x = nil
+    }
     var array:[Double] = []
     var columns:Int = 0
     var z = x!.componentsSeparatedByString(",")
     columns = 0
     for i in 0..<z.count{
-        var num = z[i]
+        let num = z[i]
         array.append(num.doubleValue)
         columns += 1
     }
@@ -73,13 +77,18 @@ func read_csv(filename:String, prefix:String=S2_PREFIX) -> ndarray{
 
 // matrix csv
 func read_csv(filename:String, prefix:String=S2_PREFIX) -> matrix{
-    var x = String(contentsOfFile: prefix+"../"+filename, encoding: NSUTF8StringEncoding, error: nil)
+    var x: String?
+    do {
+        x = try String(contentsOfFile: prefix+"../"+filename, encoding: NSUTF8StringEncoding)
+    } catch _ {
+        x = nil
+    }
     var y = x!.componentsSeparatedByString("\n")
-    var rows = y.count-1
+    let rows = y.count-1
     var array:[Double] = []
     var columns:Int = 0
     for i in 0..<rows{
-        var z = y[i].componentsSeparatedByString(",")
+        let z = y[i].componentsSeparatedByString(",")
         columns = 0
         for num in z{
             array.append(num.doubleValue)
@@ -90,7 +99,7 @@ func read_csv(filename:String, prefix:String=S2_PREFIX) -> matrix{
     done.flat.grid = array
     return done
 }
-func write_csv(x:matrix, #filename:String, prefix:String=S2_PREFIX){
+func write_csv(x:matrix, filename:String, prefix:String=S2_PREFIX){
     var seperator=","
     var str = ""
     for i in 0..<x.shape.0{
@@ -100,10 +109,10 @@ func write_csv(x:matrix, #filename:String, prefix:String=S2_PREFIX){
         }
         str += "\n"
     }
-    var error:NSError?
-    str.writeToFile(prefix+"../"+filename, atomically: false, encoding: NSUTF8StringEncoding, error: &error)
-    if let error=error{
-        println("File probably wasn't recognized \n\(error)")
+    do {
+        try str.writeToFile(prefix+"../"+filename, atomically: false, encoding: NSUTF8StringEncoding)
+    } catch {
+        Swift.print("File probably wasn't recognized")
     }
 }
 

swix/swix/swix/machine_learning/machine_learning.swift

@@ -32,7 +32,7 @@ class SVM {
         // svm_type: C_SVC, ONE_CLASS, NU_SVC, NU_SVR
 
         // careful: NU_SVR and SIGMOID throws an exception error
-        self.cvsvm.setParams(svm_type.nsstring, kernel:kernel_type.nsstring, nu:nu.cfloat)
+        self.cvsvm.setParams(svm_type.nsstring as String, kernel:kernel_type.nsstring as String, nu:nu.cfloat)
     }
     func train(responses: matrix, _ targets: ndarray){
         // convert matrix2d to NSArray
@@ -42,11 +42,11 @@ class SVM {
     }
     func predict(response: ndarray) -> Double{
         assert(self.N == response.count, "Sizes of input arguments do not match: predict.count != trained.count. The varianbles you're trying to predict a result from must match variables you trained off of.")
-        var tp = self.cvsvm.predict(!response, n:self.N.cint)
+        let tp = self.cvsvm.predict(!response, n:self.N.cint)
         return tp.double
     }
     func predict(responses: matrix) -> ndarray{
-        var y = zeros(responses.shape.0)
+        let y = zeros(responses.shape.0)
         assert(self.N == responses.shape.1, "Sizes must match")
         self.cvsvm.predict(!responses, into:!y, m:responses.shape.0.cint, n:responses.shape.1.cint);
         return y
@@ -75,7 +75,7 @@ class kNearestNeighbors{
     func predict(x: ndarray, k: Int) -> Double{
         assert(self.N == x.count, "Sizes of input arguments do not match: predict.count != trained.count. The varianbles you're trying to predict a result from must match variables you trained off of.")
         assert(k <= 32, "k <= 32 for performance reasons enforced by OpenCV.")
-        var result = self.knn.predict(!x, n:x.n.cint, k:k.cint)
+        let result = self.knn.predict(!x, n:x.n.cint, k:k.cint)
         return result.double;
     }
 }

swix/swix/swix/matrix/m-complex-math.swift

@@ -11,16 +11,16 @@ import Swift
 import Accelerate
 
 func rank(x:matrix)->Double{
-    var (u, S, v) = svd(x, compute_uv:false)
-    var m:Double = (x.shape.0 < x.shape.1 ? x.shape.1 : x.shape.0).double
-    var tol = S.max() * m * DOUBLE_EPSILON
+    let (_, S, _) = svd(x, compute_uv:false)
+    let m:Double = (x.shape.0 < x.shape.1 ? x.shape.1 : x.shape.0).double
+    let tol = S.max() * m * DOUBLE_EPSILON
     return sum(S > tol)
 }
 func dot(x: matrix, y: matrix) -> matrix{
-    var (Mx, Nx) = x.shape
-    var (My, Ny) = y.shape
+    let (Mx, Nx) = x.shape
+    let (My, Ny) = y.shape
     assert(Nx == My, "Matrix sizes not compatible for dot product")
-    var z = zeros((Mx, Ny))
+    let z = zeros((Mx, Ny))
     cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
         Mx.cint, Ny.cint, Nx.cint, 1.0,
         !x, Nx.cint,
@@ -29,44 +29,44 @@ func dot(x: matrix, y: matrix) -> matrix{
     return z
 }
 func svd(x: matrix, compute_uv:Bool=true) -> (matrix, ndarray, matrix){
-    var (m, n) = x.shape
-    var nS = m < n ? m : n // number singular values
-    var sigma = zeros(nS)
-    var vt = zeros((n,n))
+    let (m, n) = x.shape
+    let nS = m < n ? m : n // number singular values
+    let sigma = zeros(nS)
+    let vt = zeros((n,n))
     var u = zeros((m,m))
 
     var xx = zeros_like(x)
     xx.flat = x.flat
     xx = xx.T
-    var c_uv:CInt = compute_uv==true ? 1 : 0
+    let c_uv:CInt = compute_uv==true ? 1 : 0
     svd_objc(!xx, m.cint, n.cint, !sigma, !vt, !u, c_uv)
 
     // to get the svd result to match Python
-    var v = transpose(vt)
+    let v = transpose(vt)
     u = transpose(u)
 
     return (u, sigma, v)
 }
 func pinv(x:matrix)->matrix{
     var (u, s, v) = svd(x)
-    var m = u.shape.0
-    var n = v.shape.1
-    var ma = m < n ? n : m
-    var cutoff = DOUBLE_EPSILON * ma.double * max(s)
-    var i = s > cutoff
-    var ipos = argwhere(i)
+    let m = u.shape.0
+    let n = v.shape.1
+    let ma = m < n ? n : m
+    let cutoff = DOUBLE_EPSILON * ma.double * max(s)
+    let i = s > cutoff
+    let ipos = argwhere(i)
     s[ipos] = 1 / s[ipos]
-    var ineg = argwhere(1-i)
+    let ineg = argwhere(1-i)
     s[ineg] = zeros_like(ineg)
     var z = zeros((n, m))
     z["diag"] = s
-    var res = v.T.dot(z).dot(u.T)
+    let res = v.T.dot(z).dot(u.T)
     return res
 }
 func inv(x: matrix) -> matrix{
     assert(x.shape.0 == x.shape.1, "To take an inverse of a matrix, the matrix must be square. If you want the inverse of a rectangular matrix, use psuedoinverse.")
-    var y = x.copy()
-    var (M, N) = x.shape
+    let y = x.copy()
+    let (M, N) = x.shape
 
     var ipiv:Array<__CLPK_integer> = Array(count:M*M, repeatedValue:0)
     var lwork:__CLPK_integer = __CLPK_integer(N*N)
@@ -79,31 +79,28 @@ func inv(x: matrix) -> matrix{
     return y
 }
 func solve(A: matrix, b: ndarray) -> ndarray{
-    var (m, n) = A.shape
+    let (m, n) = A.shape
     assert(b.n == m, "Ax = b, A.rows == b.n. Sizes must match which makes sense mathematically")
     assert(n == m, "Matrix must be square -- dictated by OpenCV")
-    var x = zeros(n)
+    let x = zeros(n)
     CVWrapper.solve(!A, b:!b, x:!x, m:m.cint, n:n.cint)
     return x
 }
 func eig(x: matrix)->ndarray{
     // matrix, value, vectors
-    var (m, n) = x.shape
+    let (m, n) = x.shape
     assert(m == n, "Input must be square")
 
-    var value_real = zeros(m)
-    var value_imag = zeros(n)
+    let value_real = zeros(m)
+    let value_imag = zeros(n)
     var vector = zeros((n,n))
 
-    var y = x.copy()
-
     var work:[Double] = Array(count:n*n, repeatedValue:0.0)
     var lwork = __CLPK_integer(4 * n)
     var info = __CLPK_integer(1)
 
     // don't compute right or left eigenvectors
-    var job = "N"
-    var ccharOptional = job.cStringUsingEncoding(NSUTF8StringEncoding)?[0]  // CChar?
+    let job = "N"
     var jobvl = (job.cStringUsingEncoding(NSUTF8StringEncoding)?[0])!
     var jobvr = (job.cStringUsingEncoding(NSUTF8StringEncoding)?[0])!