func main() {
demo(mat.MakeDenseMatrix([]float64{
25, 15, -5,
15, 18, 0,
-5, 0, 11,
}, 3, 3))
demo(mat.MakeDenseMatrix([]float64{
18, 22, 54, 42,
22, 70, 86, 62,
54, 86, 174, 134,
42, 62, 134, 106,
}, 4, 4))
}
func main() {
m1 := matrix.MakeDenseMatrix([]float64{1, 2, 3, 4, 5, 6}, 3, 2)
fmt.Println(m1)
fmt.Println(matrix.Transpose(m1))
res, _ := http.Get("http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv")
defer res.Body.Close()
reader := csv.NewReader(res.Body)
reader.Comma = ';'
//contents, _ := ioutil.ReadAll(res.Body)
testData := make([][]float64, 0)
for {
col, err := reader.Read()
if err == io.EOF {
break
}
//strings.Split(col, ";")
x := make([]float64, len(col))
for i := range col {
x[i], _ = strconv.ParseFloat(col[i], 64)
}
testData = append(testData, x)
}
ae := NewAutoEncoder()
ae.Train(testData[1])
}
func BenchmarkGoMatrixSvd(b *testing.B) {
for i := 0; i < b.N; i++ {
b.StopTimer()
test := randomMatrix3()
mat := matrix.MakeDenseMatrix(test[:], 3, 3)
b.StartTimer()
mat.SVD()
}
}
//Mints a new classifier.
func (KNN *KNNClassifier) New(name string, labels []string, numbers []float64, x int, y int) {
//Write in some error handling here
// if x != len(KNN.Labels) {
// return errors.New("KNN: There must be a label for each row")
// }
KNN.Data = *mat.MakeDenseMatrix(numbers, x, y)
KNN.Name = name
KNN.Labels = labels
}
func Reduct() int {
ret := 0
s := `[1 2 3;4 5 6]`
A, err := matrix.ParseMatlab(s)
Ar := matrix.MakeDenseMatrix([]float64{1, 2, 3, 4, 5, 6}, 2, 3)
fmt.Print(A)
fmt.Print(err)
fmt.Print(Ar)
return ret
}
func Test_3x3_times_3xN(t *testing.T) {
cols := 11
tests1 := randomMatrices(10000, 3, 3)
tests2 := randomMatrices(10000, 3, cols)
for i, test1 := range tests1 {
test2 := tests2[i]
// Compute our product.
tC_ := mult_3x3_3xN(cols, test1, test2)
tC := tmat(tC_[:])
// Now compute the "correct" product.
mat1 := matrix.MakeDenseMatrix(test1, 3, 3)
mat2 := matrix.MakeDenseMatrix(test2, 3, cols)
aC_, _ := mat1.TimesDense(mat2)
aC := tmat(aC_.Array())
if !tC.equal(aC) {
t.Fatalf("The product of\n%s\nand\n%s\nis\n%s\nbut we said\n%s\n",
tmat(test1), tmat(test2), aC, tC)
}
}
}
func TestCovariant(t *testing.T) {
cols := 11
tests1 := randomMatrices(10000, 3, cols)
tests2 := randomMatrices(10000, 3, cols)
for i, test1 := range tests1 {
test2 := tests2[i]
// Compute our covariant
tC_ := covariant_3x3(cols, test1, test2)
tC := tmat(tC_[:])
// Now compute the "correct" covariant.
mat1 := matrix.MakeDenseMatrix(test1, 3, cols)
mat2 := matrix.MakeDenseMatrix(test2, 3, cols)
aC_, _ := mat1.TimesDense(mat2.Transpose())
aC := tmat(aC_.Array())
if !tC.equal(aC) {
t.Fatalf("The covariant of\n%s\nand\n%s\nis\n%s\nbut we said\n%s\n",
tmat(test1), tmat(test2), aC, tC)
}
}
}
func main() {
//Parses the infamous Iris data.
cols, rows, _, labels, data := base.ParseCsv("datasets/randomdata.csv", 2, []int{0, 1})
newlabels := util.ConvertLabelsToFloat(labels)
//Initialises a new KNN classifier
knn := knnclass.KNNRegressor{}
knn.New("Testing", newlabels, data, rows, cols)
for {
//Creates a random array of N float64s between 0 and Y
randArray := util.RandomArray(2, 100)
//Initialises a vector with this array
random := mat.MakeDenseMatrix(randArray, 1, 2)
//Calculates the Euclidean distance and returns the most popular label
outcome, _ := knn.Predict(random, 3)
fmt.Println(outcome)
}
}
func main() {
//Parses the infamous Iris data.
cols, rows, _, labels, data := base.ParseCsv("datasets/iris.csv", 4, []int{0, 1, 2})
//Initialises a new KNN classifier
knn := knnclass.KNNClassifier{}
knn.C
knn.New("Testing", labels, data, rows, cols)
for {
//Creates a random array of N float64s between 0 and 7
randArray := util.RandomArray(3, 7)
//Initialises a vector with this array
random := mat.MakeDenseMatrix(randArray, 1, 3)
//Calculates the Euclidean distance and returns the most popular label
labels, _ := knn.Predict(random, 3)
fmt.Println(labels)
}
}
func TestSvd(t *testing.T) {
tests := randomMatrices3(10000)
for _, test := range tests {
// Compute our SVD.
tU_, tV_ := matrix3(test).svd()
tU, tV := tmat(tU_[:]), tmat(tV_[:])
// Now compute the "correct" SVD.
mat := matrix.MakeDenseMatrix(test[:], 3, 3)
U, _, V, _ := mat.SVD()
aU, aV := tmat(U.Array()), tmat(V.Array())
// Now compare them.
if !aU.equal(tU) {
t.Fatalf("With matrix\n%s\nU =\n%s\nbut we said\n%s\n",
tmat(test[:]), aU, tU)
}
if !aV.equal(tV) {
t.Fatalf("With matrix\n%s\n, V =\n%s\n, but we said\n%s\n",
tmat(test[:]), aV, tV)
}
}
}
// choleskyMatrix takes the array of floats provided by the JSON data, and
// converts it to a matrix.
// Receiver: SimulationData
// Params: none
// Returns: *goMatrix.DenseMatrix
func (s *SimulationData) choleskyMatrix() *goMatrix.DenseMatrix {
vals := s.CholeskyDecomposition
noOfVals := float64(len(vals))
noRows := int(math.Pow(noOfVals, 0.5))
return goMatrix.MakeDenseMatrix(vals, noRows, noRows)
}
func shiftMatrix(A *matrix.DenseMatrix, x int, y int) *matrix.DenseMatrix {
result := A
// fmt.Println("Shift x: ", x)
// fmt.Println("Shift y: ", y)
// A*shiftRightOrUp will shift A right
// shiftRightOrUp*A will shift A up
shiftRightOrUp := matrix.MakeDenseMatrix([]float64{
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
}, 15, 15)
// A*shiftLeftOrDown will shift A left
// shiftLeftOrDown*A will shift A down
shiftLeftOrDown := matrix.MakeDenseMatrix([]float64{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
}, 15, 15)
// fmt.Println("Start Matrix: ", result.String(), "\n\n")
if x < 0 {
for i := x; i < 0; i++ {
// fmt.Print("<")
result = matrix.Product(result, shiftLeftOrDown)
// fmt.Println("Shifted Matrix ", i, ": ", result.String(), "\n\n")
}
} else if x > 0 {
for i := 0; i < x; i++ {
// fmt.Print(">")
result = matrix.Product(result, shiftRightOrUp)
// fmt.Println("Shifted Matrix ", i, ": ", result.String(), "\n\n")
}
}
// fmt.Println()
if y < 0 {
for i := y; i < 0; i++ {
result = matrix.Product(shiftLeftOrDown, result)
// fmt.Println("Shifted Matrix ", i, ": ", result.String(), "\n\n")
}
} else if y > 0 {
for i := 0; i < y; i++ {
result = matrix.Product(shiftRightOrUp, result)
// fmt.Println("Shifted Matrix ", i, ": ", result.String(), "\n\n")
}
}
// fmt.Println("Shifted Matrix: ", result.String())
return result
}
func InitMatrices() {
singlePawnMove = matrix.MakeDenseMatrix([]float64{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
}, 15, 15)
singleRookMove = matrix.MakeDenseMatrix([]float64{
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
1, 1, 1, 1, 1, 1, 1, -1, 1, 1, 1, 1, 1, 1, 1,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
}, 15, 15)
singleKnightMove = matrix.MakeDenseMatrix([]float64{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
}, 15, 15)
singleBishopMove = matrix.MakeDenseMatrix([]float64{
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
}, 15, 15)
singleQueenMove = matrix.MakeDenseMatrix([]float64{
1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
1, 1, 1, 1, 1, 1, 1, -1, 1, 1, 1, 1, 1, 1, 1,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0,
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0,
1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1,
}, 15, 15)
singleKingMove = matrix.MakeDenseMatrix([]float64{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, -1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
}, 15, 15)
singlePuppyMove = matrix.MakeDenseMatrix([]float64{
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
}, 15, 15)
}
//Mints a new classifier.
func (KNN *KNNRegressor) New(name string, labels []float64, numbers []float64, x int, y int) {
KNN.Data = *mat.MakeDenseMatrix(numbers, x, y)
KNN.Name = name
KNN.Labels = labels
}
package main
import (
"fmt"
matrix "github.com/skelterjohn/go.matrix"
"math"
)
var relation = []float64{4, 1, 1, 0}
var relation_mat = matrix.MakeDenseMatrix(relation, 2, 2)
var initial_seq_values = []float64{8, 2}
var init_mat = matrix.MakeDenseMatrix(initial_seq_values, 2, 1)
var dict = make(map[float64]*matrix.DenseMatrix, 0)
var pow = []float64{1, -1}
/*************************************************************************
function calculate_even_fib_until:
Input: limit Integer
Output:
Computes the Even_Fibanacci_Series elements F(n) and F(n+1) where:
F(n) < limit
F(n+1) >= limit
> Even_Fibanacci_Series:
It is the series formed by even elements of Fibonacci Series:
2, 8, 34, 144, 610, ...
It has a recurrence relation which be derived easily:
|4, 1| * | F(n) | = |F(n+1)|
|1, 0| |F(n-1)| | F(n) |
func getOptions() {
reader := bufio.NewReader(os.Stdin)
// Get the piece choice
for {
fmt.Println("Choose a Piece:")
fmt.Println(" Pawn")
fmt.Println(" Rook")
fmt.Println(" Knight")
fmt.Println(" Bishop")
fmt.Println(" Queen")
fmt.Println(" King")
fmt.Println(" Puppy\n")
fmt.Print(":: ")
text, _ := reader.ReadString('\n')
text = strings.ToLower(text)
text = strings.TrimSpace(text)
if text == "pawn" {
piece = boards.Pawn
break
} else if text == "rook" {
piece = boards.Rook
break
} else if text == "knight" {
piece = boards.Knight
break
} else if text == "bishop" {
piece = boards.Bishop
break
} else if text == "queen" {
piece = boards.Queen
break
} else if text == "king" {
piece = boards.King
break
} else if text == "puppy" {
piece = boards.Puppy
break
} else {
fmt.Println("Invalid Piece")
}
}
for {
fmt.Print("\nStart Position {a-h}{1-8}: ")
text, _ := reader.ReadString('\n')
text = strings.ToLower(text)
text = strings.TrimSpace(text)
if len(text) > 2 {
fmt.Println("Invalid Location")
continue
}
if strings.HasPrefix(text, "a") {
startX = 1
} else if strings.HasPrefix(text, "b") {
startX = 2
} else if strings.HasPrefix(text, "c") {
startX = 3
} else if strings.HasPrefix(text, "d") {
startX = 4
} else if strings.HasPrefix(text, "e") {
startX = 5
} else if strings.HasPrefix(text, "f") {
startX = 6
} else if strings.HasPrefix(text, "g") {
startX = 7
} else if strings.HasPrefix(text, "h") {
startX = 8
} else {
fmt.Println("Invalid Location")
continue
}
if strings.HasSuffix(text, "1") {
startY = 1
break
} else if strings.HasSuffix(text, "2") {
startY = 2
break
} else if strings.HasSuffix(text, "3") {
startY = 3
break
} else if strings.HasSuffix(text, "4") {
startY = 4
break
} else if strings.HasSuffix(text, "5") {
startY = 5
break
} else if strings.HasSuffix(text, "6") {
startY = 6
break
} else if strings.HasSuffix(text, "7") {
startY = 7
break
} else if strings.HasSuffix(text, "8") {
startY = 8
break
}
fmt.Println("Invalid Location")
}
for {
fmt.Print("\nGoal Position {a-h}{1-8}: ")
text, _ := reader.ReadString('\n')
text = strings.ToLower(text)
text = strings.TrimSpace(text)
if len(text) > 2 {
fmt.Println("Invalid Location")
continue
}
if strings.HasPrefix(text, "a") {
goalX = 1
} else if strings.HasPrefix(text, "b") {
goalX = 2
} else if strings.HasPrefix(text, "c") {
goalX = 3
} else if strings.HasPrefix(text, "d") {
goalX = 4
} else if strings.HasPrefix(text, "e") {
goalX = 5
} else if strings.HasPrefix(text, "f") {
goalX = 6
} else if strings.HasPrefix(text, "g") {
goalX = 7
} else if strings.HasPrefix(text, "h") {
goalX = 8
} else {
fmt.Println("Invalid Location")
continue
}
if strings.HasSuffix(text, "1") {
goalY = 1
break
} else if strings.HasSuffix(text, "2") {
goalY = 2
break
} else if strings.HasSuffix(text, "3") {
goalY = 3
break
} else if strings.HasSuffix(text, "4") {
goalY = 4
break
} else if strings.HasSuffix(text, "5") {
goalY = 5
break
} else if strings.HasSuffix(text, "6") {
goalY = 6
break
} else if strings.HasSuffix(text, "7") {
goalY = 7
break
} else if strings.HasSuffix(text, "8") {
goalY = 8
break
}
fmt.Println("Invalid Location")
}
for {
fmt.Print("\nLength of Trajectories: ")
text, _ := reader.ReadString('\n')
text = strings.TrimSpace(text)
var err error
maxLength, err = strconv.Atoi(text)
if err == nil && maxLength > 0 {
break
}
fmt.Println("Length must be a positive integer")
}
fmt.Println("\nEnter Holes {a-h}{1-8}")
fmt.Println("Enter anything else to continue")
boards.HoleBoard = matrix.MakeDenseMatrix(make([]float64, 225, 225), 15, 15)
for {
fmt.Print(":: ")
text, _ := reader.ReadString('\n')
text = strings.TrimSpace(text)
if len(text) > 2 {
break
}
var x int
var y int
if strings.HasPrefix(text, "a") {
x = 0
} else if strings.HasPrefix(text, "b") {
x = 1
} else if strings.HasPrefix(text, "c") {
x = 2
} else if strings.HasPrefix(text, "d") {
x = 3
} else if strings.HasPrefix(text, "e") {
x = 4
} else if strings.HasPrefix(text, "f") {
x = 5
} else if strings.HasPrefix(text, "g") {
x = 6
} else if strings.HasPrefix(text, "h") {
x = 7
} else {
break
}
if strings.HasSuffix(text, "1") {
y = 14
} else if strings.HasSuffix(text, "2") {
y = 13
} else if strings.HasSuffix(text, "3") {
y = 12
} else if strings.HasSuffix(text, "4") {
y = 11
} else if strings.HasSuffix(text, "5") {
y = 10
} else if strings.HasSuffix(text, "6") {
y = 9
} else if strings.HasSuffix(text, "7") {
y = 8
} else if strings.HasSuffix(text, "8") {
y = 7
} else {
break
}
boards.HoleBoard.Set(y, x, 500)
}
}