intentionally leaking DataHandler abstraction

kate/data_handler.go

@@ -13,8 +13,8 @@ import (
 
 //DataHandler is a wrapper that packages the required data for running backtesting simulation.
 type DataHandler struct {
-	counter, windowSize int
-	prices              []DataPoint
+	Counter, WindowSize int
+	Prices              []DataPoint
 }
 
 //Position is the representation of a traded position
@@ -43,29 +43,29 @@ var csvColumns = []string{"open", "high", "low", "close", "volume"}
 //newDataHandler creates and initializes a DataHandler with pricing data and executes the required setup
 func newDataHandler(prices []DataPoint, windowSize int) *DataHandler {
 	return &DataHandler{
-		windowSize: windowSize,
-		prices:     prices,
-		counter:    windowSize,
+		WindowSize: windowSize,
+		Prices:     prices,
+		Counter:    windowSize,
 	}
 }
 
 //NextValues returns AggregatedDataPoints with the next values in the stream of datapoints (containing the lastest windowSize of values).
 //a nil return denotes the end for the stream
 func (handler *DataHandler) nextValues() *AggregatedDataPoints {
-	if handler.counter < len(handler.prices) {
+	if handler.Counter < len(handler.Prices) {
 		data := &AggregatedDataPoints{
-			datapoints: handler.prices[handler.counter-handler.windowSize : handler.counter],
+			datapoints: handler.Prices[handler.Counter-handler.WindowSize : handler.Counter],
 		}
-		handler.counter++
+		handler.Counter++
 		return data
 	}
 	return nil
 }
 
 //SetWindow defines the range of values that will be avaliable on each step through the data points
 func (handler *DataHandler) SetWindow(windowSize int) {
-	handler.windowSize = windowSize
-	handler.counter = windowSize
+	handler.WindowSize = windowSize
+	handler.Counter = windowSize
 }
 
 //PricesFromCSV reads all csv data in the OHLCV format to the DataHandler and returns if a error occurred

kate/data_handler_test.go

@@ -12,8 +12,8 @@ import (
 func TestLoadCSVData(t *testing.T) {
 	handler, _ := PricesFromCSV("../testdata/simple_example.csv")
 
-	if len(handler.prices) != 100 {
-		t.Errorf("The amount of prices is %v the expected amount is 100", len(handler.prices))
+	if len(handler.Prices) != 100 {
+		t.Errorf("The amount of prices is %v the expected amount is 100", len(handler.Prices))
 	}
 
 	firstPrice := DataPoint{
@@ -23,8 +23,8 @@ func TestLoadCSVData(t *testing.T) {
 		close:  746.95,
 		volume: 1045532,
 	}
-	if !reflect.DeepEqual(handler.prices[0], firstPrice) {
-		t.Errorf("The first price in the csv is %v the expected was %v", handler.prices[0], firstPrice)
+	if !reflect.DeepEqual(handler.Prices[0], firstPrice) {
+		t.Errorf("The first price in the csv is %v the expected was %v", handler.Prices[0], firstPrice)
 	}
 
 	lastPrice := DataPoint{
@@ -35,8 +35,8 @@ func TestLoadCSVData(t *testing.T) {
 		volume: 80597,
 	}
 
-	if !reflect.DeepEqual(handler.prices[len(handler.prices)-1], lastPrice) {
-		t.Errorf("The last price in the csv is %v the expected was %v", handler.prices[len(handler.prices)-1], lastPrice)
+	if !reflect.DeepEqual(handler.Prices[len(handler.Prices)-1], lastPrice) {
+		t.Errorf("The last price in the csv is %v the expected was %v", handler.Prices[len(handler.Prices)-1], lastPrice)
 	}
 
 	middlePrice := DataPoint{
@@ -46,8 +46,8 @@ func TestLoadCSVData(t *testing.T) {
 		close:  746.45,
 		volume: 5306,
 	}
-	if !reflect.DeepEqual(handler.prices[66], middlePrice) {
-		t.Errorf("The middle price in the csv is %v the expected was %v", handler.prices[66], middlePrice)
+	if !reflect.DeepEqual(handler.Prices[66], middlePrice) {
+		t.Errorf("The middle price in the csv is %v the expected was %v", handler.Prices[66], middlePrice)
 	}
 
 }

kate/statistics.go

@@ -40,7 +40,7 @@ func (bt *Backtester) calculateStatistics(initialBalance float64) *Statistics {
 		TotalTrades:     len(tradeHistory),
 		WinRate:         float64(wins) / float64(len(tradeHistory)),
 		MaxDrawdown:     (peakProfit - bottomProfit) / peakProfit,
-		TotalDataPoints: len(bt.dataHandler.prices),
+		TotalDataPoints: len(bt.dataHandler.Prices),
 	}
 
 	stats.SharpeRatio = sharpe(stats.NetProfit, 0.0, stdDev(balanceHistory))