From 938647b779c3e1b3692c236de98233fbe9c40b11 Mon Sep 17 00:00:00 2001
From: Eilert Tunheim <emtunhei@stud.ntnu.no>
Date: Thu, 19 May 2022 00:37:38 +0200
Subject: [PATCH] commented linechart class
---
.../GUI/LineChartFunctionality.java | 385 +++++-------------
1 file changed, 91 insertions(+), 294 deletions(-)
diff --git a/src/main/java/com/application/GUI/LineChartFunctionality.java b/src/main/java/com/application/GUI/LineChartFunctionality.java
index 93593a3..53bdb00 100644
--- a/src/main/java/com/application/GUI/LineChartFunctionality.java
+++ b/src/main/java/com/application/GUI/LineChartFunctionality.java
@@ -21,6 +21,12 @@ import java.util.*;
import static com.application.Main.*;
+/**
+ * This class handle all the GUI functionality and statistics calculations
+ *
+ * @author Eilert Tunheim, Karin Pettersen, Mads Arnesen
+ * @version 1.0.0
+ */
public class LineChartFunctionality {
private static LineChart<String, Number> lineChart;
@@ -39,6 +45,7 @@ public class LineChartFunctionality {
private static boolean printLiveData;
private static boolean printPreviousData;
+ // Constructor
public LineChartFunctionality() {
xAxis = new CategoryAxis();
yAxis = new NumberAxis();
@@ -63,7 +70,7 @@ public class LineChartFunctionality {
/**
- * Prints the graphs to the line chart
+ * Prints the selected graphs to the line chart
*
* Note: Something wrong when exceeding 8 series, think the next series choose a random series color
*/
@@ -107,15 +114,11 @@ public class LineChartFunctionality {
getMenuViewPreviousData().setSelected(true);
// If there are more than 5 series, adds 3 new empty series to keep the color scheme
- //int index = getLineChart().getData().size();
for (int i = 0; i < getPreviousData().size(); i++) {
int index = getLineChart().getData().size();
- //System.out.println(getPreviousData().size());
if (index % 8 == 0 ){
for (int j = 0; j < 3; j++) {
updateLineChart(new XYChart.Series<>());
- //index++;
- System.out.println("@@@@@@@");
}
}
updateLineChart(getPreviousData().get(i));
@@ -127,103 +130,102 @@ public class LineChartFunctionality {
}
-
+ /**
+ * This function calculates the confidence interval
+ *
+ * @param multiMap input containing the drying cycle data
+ * @param CIShadow input to indicate if the confidence interval shadow is stored or not
+ * @return a map containing the processed data
+ */
private static Map<Integer, ArrayList<Double>> statistics(Map<Integer, ArrayList<Double>> multiMap, boolean CIShadow){
- //System.out.println("\n\nMultimap: \n");
+ // Iterates through all the data
for (Map.Entry<Integer, ArrayList<Double>> entry : multiMap.entrySet()) {
- //System.out.printf("\nIndex: \t%s\t\t\tkWh: \t%s\n", entry.getKey(), entry.getValue());
-
- //System.out.println("entry: "+entry);
- //if(entry.getValue().size()>1){
- SummaryStatistics stats = new SummaryStatistics();
+ SummaryStatistics data = new SummaryStatistics();
for (double val : entry.getValue()) {
- stats.addValue(val);
+ data.addValue(val);
}
- //System.out.println("Stats: "+stats);
-
- // Calculate 95% confidence interval
- double ci = calcMeanCI(stats, Settings.CONFIDENCE_INTERVAL);
- //System.out.println(String.format("Mean: %f", stats.getMean()));
- double lower = stats.getMean() - ci;
- double upper = stats.getMean() + ci;
- //System.out.println(String.format("Confidence Interval "+ Settings.CONFIDENCE_INTERVAL*100+"%%: %f, %f", lower, upper));
+ // Calculate the confidence interval
+ double confidenceInterval = calcMeanConfidenceInterval(data);
+ double lower = data.getMean() - confidenceInterval;
+ double upper = data.getMean() + confidenceInterval;
// Deletes entries if they are out of bounds with the confidence interval
entry.getValue().removeIf(value -> Double.compare(value, lower) < 0 || Double.compare(value, upper) > 0);
+ // Checks if the confidence interval shall be returned or not
if(CIShadow){
ArrayList<Double> lowerUpperBounds = new ArrayList<>();
lowerUpperBounds.add(lower);
lowerUpperBounds.add(upper);
multiMap.replace(entry.getKey(), lowerUpperBounds);
}
- //}
}
return multiMap;
}
- private static double calcMeanCI(SummaryStatistics stats, double level) {
+ /**
+ * This function calculates the confidence interval mean value
+ *
+ * @param data the data to base the calculation on
+ * @return returns the confidence interval mean value
+ */
+ private static double calcMeanConfidenceInterval(SummaryStatistics data) {
try {
- // Create T Distribution with N-1 degrees of freedom
- TDistribution tDist = new TDistribution(stats.getN() - 1);
- // Calculate critical value
- double critVal = tDist.inverseCumulativeProbability(1.0 - (1 - level) / 2);
- // Calculate confidence interval
- return critVal * stats.getStandardDeviation() / Math.sqrt(stats.getN());
+ // Create a T distribution
+ TDistribution tDistribution = new TDistribution(data.getN() - 1);
+ // Calculate the critical value
+ double criticalValue = tDistribution.inverseCumulativeProbability(1.0 - (1 - Settings.CONFIDENCE_INTERVAL) / 2);
+ // Calculate the confidence interval
+ return criticalValue * data.getStandardDeviation() / Math.sqrt(data.getN());
} catch (MathIllegalArgumentException e) {
return Double.NaN;
}
}
+ /**
+ * This function serves as the main function that controls all the functionality.
+ * This function takes the data inputted and plots it and calculates the statistics.
+ *
+ * @param userInput data regarding the drying cycles
+ * @throws Exception throws exception if an error occurs
+ */
+ public static void loadSingleSeries(Map<Integer, Map<String, Number>> userInput) throws Exception {
- public static LineChart<String, Number> loadSingleSeries(Map<Integer, Map<String, Number>> userInput) throws Exception {
+ // Clears the linechart if there are previous graphs plotted
clearLineChart();
-
+ // Defining a map to store data
Map<Integer, ArrayList<Double>> multiMap = new HashMap<>();
+ // Iterates through the data
for (Map.Entry<Integer, Map<String, Number>> entryKwh : userInput.entrySet()) {
Map data = entryKwh.getValue();
- //System.out.println(data.size());
- XYChart.Series<String, Number> newSeries = new XYChart.Series<String, Number>();
int index = 0;
for (Object entryData : data.entrySet()) {
- //System.out.println("data: \t"+entryData);
String entryString = entryData.toString();
String[] arr = entryString.split("=");
- String date = arr[0];
Double kwhValue = Double.parseDouble(arr[1]);
- //System.out.printf("Date: \t%s\t\t\tkWh: \t%s\n",date,kwhValue);
-
// Checks if the index already got an arraylist, if not one is created
multiMap.computeIfAbsent(index, k -> new ArrayList<Double>());
multiMap.get(index).add(kwhValue);
- // Connect the data to a series
- newSeries.getData().add(new XYChart.Data<String, Number>(String.valueOf(index), kwhValue));
index++;
}
- //allSeries.add(newSeries);
- //updateLineChart(newSeries);
- //lineChart.setOpacity(1);
}
- //System.out.println("Series size: "+allSeries.size());
-
-
-
// Finds the end datapoint at the end of each graph
int numberOfGraphs = 0;
+ // Defines lists to store data
ArrayList<Double> dataArraylistXAxis = new ArrayList<>();
ArrayList<Double> dataArraylistYAxis = new ArrayList<>();
-
Map<Integer, ArrayList<Double>> endOfGraphPointsXAxis = new HashMap<>();
Map<Integer, ArrayList<Double>> endOfGraphPointsYAxis = new HashMap<>();
+ // Iterates through the data
for (int i = 0; i < multiMap.size(); i++) {
ArrayList<Double> list = multiMap.get(i);
for (int j = 0; j < list.size(); j++) {
@@ -231,11 +233,8 @@ public class LineChartFunctionality {
numberOfGraphs = list.size();
}
if (list.size() < numberOfGraphs) {
-
dataArraylistXAxis.add((double) i);
dataArraylistYAxis.add(multiMap.get(i).get(j));
- //System.out.println(tempList);
-
numberOfGraphs = list.size();
}
}
@@ -243,56 +242,33 @@ public class LineChartFunctionality {
dataArraylistXAxis.add((double) multiMap.size());
dataArraylistYAxis.add(multiMap.get(multiMap.size()-1).get(0));
- //System.out.println(dataArraylistYAxis);
-
-
endOfGraphPointsXAxis.put(0,dataArraylistXAxis);
endOfGraphPointsYAxis.put(0,dataArraylistYAxis);
- System.out.println(endOfGraphPointsXAxis);
- System.out.println(endOfGraphPointsYAxis);
-
Map<Integer, ArrayList<Double>> endOfGraphPointsConfidenceXAxis = statistics(endOfGraphPointsXAxis,false);
Map<Integer, ArrayList<Double>> endOfGraphPointsConfidenceYaxis = statistics(endOfGraphPointsYAxis,false);
- System.out.println("X-axis:"+ endOfGraphPointsConfidenceXAxis);
- System.out.println("X-axis size: "+ endOfGraphPointsConfidenceXAxis.size());
- System.out.println("------------");
- System.out.println("Y-axis:"+ endOfGraphPointsConfidenceYaxis);
- System.out.println("Y-axis size: "+ endOfGraphPointsConfidenceYaxis.size());
- System.out.println("------------");
-
-
+ // X-axis
dataPointsXAxis = 0;
for (Map.Entry<Integer, ArrayList<Double>> entry : endOfGraphPointsConfidenceXAxis.entrySet()) {
- System.out.println("Arraylist: "+ entry.getValue());
for (int i = 0; i < entry.getValue().size(); i++) {
- System.out.println("End of graphs: "+ entry.getValue().get(i));
dataPointsXAxis += entry.getValue().get(i);
}
}
dataPointsXAxis = dataPointsXAxis /endOfGraphPointsConfidenceXAxis.get(0).size();
- System.out.println("Datapoints: " + dataPointsXAxis);
-
+ // Y-axis
dataPointsYAxis = 0;
for (Map.Entry<Integer, ArrayList<Double>> entry : endOfGraphPointsConfidenceYaxis.entrySet()) {
- System.out.println("Arraylist: "+ entry.getValue());
for (int i = 0; i < entry.getValue().size(); i++) {
- System.out.println("End of graphs: "+ entry.getValue().get(i));
dataPointsYAxis += entry.getValue().get(i);
}
}
dataPointsYAxis = dataPointsYAxis /endOfGraphPointsConfidenceYaxis.get(0).size();
- System.out.println("Datapoints Y-axis: " + dataPointsYAxis);
-
-
// Stores the data from the confidence interval in a new map
Map<Integer, ArrayList<Double>> confidenceIntervalData = statistics(multiMap,false);
- //getNonLinearRegression(confidenceIntervalData);
-
// Checks the max size for the arraylists needed for the data array later
int jMaxSize = 0;
for (int i = 0; i < confidenceIntervalData.size(); i++) {
@@ -301,23 +277,20 @@ public class LineChartFunctionality {
}
}
-
- // Defines an array to be used for the regression
+ // Defines an array to be used for the linear regression
double[][] data = new double[confidenceIntervalData.size()*jMaxSize][2];
int index = 0;
- //System.out.println(confidenceIntervalData);
for (int i = 0; i < confidenceIntervalData.size(); i++) {
-
ArrayList<Double> list = confidenceIntervalData.get(i);
-
- for (int j = 0; j < list.size(); j++) {
+ for (Double aDouble : list) {
data[index][0] = i;
- data[index][1] = list.get(j);
+ data[index][1] = aDouble;
index++;
}
}
+ // Adds the data to the confidence interval shadow
getRegressionSeriesConfidenceInterval().getData().clear();
Map<Integer, ArrayList<Double>> confidenceIntervalShadow = statistics(multiMap,true);
for ( Map.Entry<Integer, ArrayList<Double>> entry : confidenceIntervalShadow.entrySet()) {
@@ -327,59 +300,14 @@ public class LineChartFunctionality {
}
}
- System.out.println(data.length);
- //System.out.println(data[12][1]);
-
+ // Does the linear regression
SimpleRegression simpleRegression = new SimpleRegression();
-
simpleRegression.addData(data);
- //simpleRegression.regress();
-
-
- for (double[] datum : data) {
- //System.out.println("");
- for (double v : datum) {
- //System.out.println("Data: "+v);
- }
- }
-
- //updateLineChart(liveDataSeries);
-
-
- //XYChart.Series<String, Number> regressionSeries = new XYChart.Series<String, Number>();
+ // Does the logistic regression
getRegressionSeries().getData().clear();
for (int i = 0; i <= getDataPointsXAxis(); i++) {
- // Connect the data to a series
- //System.out.println(simpleRegression.predict(i));
- //regressionSeries.getData().add(new XYChart.Data<String, Number>(String.valueOf(i), simpleRegression.predict(i)));
- /*
- regressionSeries.getData().add(new XYChart.Data<String, Number>(
- String.valueOf(i),
- getNonLinearRegression(
- confidenceIntervalData,
- getDataPointsYAxis(),
- //simpleRegression.getIntercept(),
- simpleRegression.getSlope(),
- //simpleRegression.getIntercept()
- getDataPointsYAxis(),
- i,
- getDataPointsXAxis()
- )));
-
- */
-
- /*
- regressionSeries.getData().add(new XYChart.Data<String, Number>(
- String.valueOf(i),
- getCubicNonLinearRegression(confidenceIntervalData,i)
- ));
-
- */
-
-
-
getRegressionSeries().getData().add(new XYChart.Data<String, Number>(
String.valueOf(i),
getNonLinearRegression(
@@ -389,21 +317,14 @@ public class LineChartFunctionality {
i,
getDataPointsXAxis()
)));
-
-
}
- //updateLineChart(getRegressionSeries());
- //lineChart.setOpacity(1);
-
-
+ // Adds the previous data to series
getPreviousData().clear();
for (Map.Entry<Integer, Map<String, Number>> entryKwh : userInput.entrySet()) {
- //System.out.println(data.size());
XYChart.Series<String, Number> newSeries = new XYChart.Series<String, Number>();
index = 0;
for (Object entryData : entryKwh.getValue().entrySet()) {
- //System.out.println("data: \t"+entryData);
String entryString = entryData.toString();
Double kwhValue = Double.parseDouble(entryString.split("=")[1]);
@@ -412,36 +333,17 @@ public class LineChartFunctionality {
index++;
}
addPreviousData(newSeries);
- //allSeries.add(newSeries);
- //updateLineChart(newSeries);
- //lineChart.setOpacity(1);
}
-
-
-
-
- System.out.println("Get R: " + simpleRegression.getR());
- System.out.println("Get getRSquare: " + simpleRegression.getRSquare());
- System.out.println("Get getRegressionSumSquares: " + simpleRegression.getRegressionSumSquares());
-
- System.out.println("Get N: " + simpleRegression.getN());
-
- // and then you can predict the time at a given temperature value
- System.out.println("Predicted Time: " + simpleRegression.predict(35));
-
- // You can also get the slope and intercept from your data
- System.out.println("Alpha! = " + simpleRegression.getSlope());
- System.out.println("intercept = " + simpleRegression.getIntercept());
-
- //simpleRegression.add
-
getTimeLeft(0);
-
printGraphs();
-
- return getLineChart();
}
+ /**
+ * This function loads the live data and plots the data in the graph
+ *
+ * @param userInput the input parameter for the live data
+ * @throws Exception throws an exception if an error occur
+ */
public static void loadLiveData(Map<String, Number> userInput) throws Exception {
// Clears any data already there
@@ -466,6 +368,13 @@ public class LineChartFunctionality {
}
}
+ /**
+ * Finds the difference between two dates
+ *
+ * @param start_date input parameter for the first date
+ * @param end_date input parameter for the second date
+ * @return returns the differnce in minutes
+ */
private static long findDifference(String start_date, String end_date) {
// Defining a simple date format
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
@@ -487,11 +396,19 @@ public class LineChartFunctionality {
return 0;
}
+ /**
+ * This function calculates the remaining time of the current drying cycle
+ *
+ * @param liveData input parameter for the data to base the calculations on
+ */
public static void getTimeLeft(int liveData){
+
+ // Defines variables
int minutes = 0;
int hours = 0;
if(liveData == 0) {
+ // There are 10 minutes between each datapoint
minutes = getDataPointsXAxis()*10;
} else {
@@ -512,135 +429,22 @@ public class LineChartFunctionality {
}
- public static double getNonLinearRegression(Map<Integer, ArrayList<Double>> confidenceIntervalData, double y0, double alpha, double j, double n) {
- //return Math.exp(intercept+slope*i)/(1+Math.exp(intercept+slope*i));
-
-
- double beta = 0.0;
- //double n = confidenceIntervalData.size();
- for (Map.Entry<Integer, ArrayList<Double>> entry : confidenceIntervalData.entrySet()) {
- for (int i = 0; i < entry.getValue().size(); i++) {
- if(beta < entry.getValue().get(i)){
- beta = entry.getValue().get(i);
- }
- }
- }
-
- beta = getDataPointsYAxis()+y0;
- //System.out.println("Beta: " +beta);
- //System.out.println("y0: "+y0);
-
-
- //System.out.println("maxYValue: " + maxYValue);
- //System.out.println("j*n: "+j/n);
-
- //double p_t = (((beta * y0))/(y0 +((beta- y0)*Math.exp(-alpha*j/n/(ADJUST_REGRESSION)))))-y0; //Beste til nå
- double p_t = (((beta * y0))/(y0 +((beta- y0)*Math.exp(-alpha*j/n/((alpha/10))))))-y0; //Beste til nå
- //double p_t = (((beta * y0))/(y0 +((beta- y0)*Math.exp(-alpha*(j-n)))))-y0; //Beste til nå
-
-
- /*
- System.out.println("---------------------------");
- System.out.println("y0: " + y0);
- System.out.println("Alpha: " + alpha);
- System.out.println("Beta: " + beta);
- //System.out.println(p_t);
-
- */
-
-
-
- return p_t;
-
- }
-
-
/**
- * Third degree cubic non-linear regression
+ * This function handles the logistic regression
*
- * n =
- *
- * sumT1 =
- * sumT2 =
- * sumT3 =
- * sumT4 =
- *
- * sumY =
- * sumYxT1=
- * sumYxT2 =
- * @param confidenceIntervalData Data to process
- * @return
+ * @param confidenceIntervalData the input parameter for the data to base the regression on
+ * @param y0 the input parameter for the intercept from the linear regression
+ * @param alpha the input parameter for the slope value from the linear regression
+ * @param j the input parameter for current x-axis datapoint to predict the value for
+ * @param n the input parameter for the total number of points along the x-axis
+ * @return the predicted value at a given point
*/
- public static double getCubicNonLinearRegression(Map<Integer, ArrayList<Double>> confidenceIntervalData, int index){
-
- double n = confidenceIntervalData.size();
- //double n = getDataPointsYAxis();
- //System.out.println(n);
-
- double sumT1 = 0;
- double sumT2 = 0;
- double sumT3 = 0;
- double sumT4 = 0;
-
- double sumY = 0;
- double sumYxT1 = 0;
- double sumYxT2 = 0;
-
-
-
- for (Map.Entry<Integer, ArrayList<Double>> entry : confidenceIntervalData.entrySet()) {
-
- sumT1 += entry.getKey();
- sumT2 += Math.pow(entry.getKey(),2);
- sumT3 += Math.pow(entry.getKey(),3);
- sumT4 += Math.pow(entry.getKey(),4);
-
- for (int j = 0; j < entry.getValue().size(); j++) {
-
- sumY += entry.getValue().get(j);
- sumYxT1 += entry.getValue().get(j) * entry.getKey();
- sumYxT2 += entry.getValue().get(j) * Math.pow(entry.getKey(), 2);
- }
- }
-
-
-
-
-/*
- for (Map.Entry<Integer, ArrayList<Double>> entry : confidenceIntervalData.entrySet()) {
-
-
-
- for (int j = 0; j < entry.getValue().size(); j++) {
-
- sumT1 += Math.pow(entry.getValue().get(j), 1);
- sumT2 += Math.pow(entry.getValue().get(j), 2);
- sumT3 += Math.pow(entry.getValue().get(j), 3);
- sumT4 += Math.pow(entry.getValue().get(j), 4);
-
- sumY += entry.getKey();
- sumYxT1 += entry.getKey() * entry.getValue().get(j);
- sumYxT2 += entry.getKey() * Math.pow(entry.getValue().get(j), 2);
- }
- }
-
- */
-
-
-
- DoubleMatrix firstMatrix = new DoubleMatrix(new double[][]{{n,sumT1,sumT2},{sumT1,sumT2,sumT3},{sumT2,sumT3,sumT4}});
- DoubleMatrix secondMatrix = new DoubleMatrix( new double[]{sumY, sumYxT1, sumYxT2});
-
-
- DoubleMatrix solvedMatrix = Solve.solve(firstMatrix,secondMatrix);
- //System.out.println(solvedMatrix);
-
- //return ((solvedMatrix.get(0)) + (solvedMatrix.get(1) * index) + (solvedMatrix.get(2) * Math.pow(index, 2)));
- //return ((solvedMatrix.get(1) * index) + (solvedMatrix.get(2) * Math.pow(index, 2)))*(-1);
- return ((solvedMatrix.get(1) * index) + (solvedMatrix.get(2) * Math.pow(index, 2)));
-
+ public static double getNonLinearRegression(Map<Integer, ArrayList<Double>> confidenceIntervalData, double y0, double alpha, double j, double n) {
+ double beta = getDataPointsYAxis()+y0;
+ return (((beta * y0))/(y0 +((beta- y0)*Math.exp(-alpha*j/n/((alpha/10))))))-y0;
}
+
public static int getDataPointsXAxis() {
return dataPointsXAxis;
}
@@ -661,10 +465,8 @@ public class LineChartFunctionality {
return liveDataSeries;
}
- public static void setRegressionSeries(XYChart.Series<String, Number> regressionSeries) {
- LineChartFunctionality.regressionSeries = regressionSeries;
- }
+ // Getters and setters
public static XYChart.Series<String, Number> getRegressionSeries() {
return regressionSeries;
}
@@ -713,10 +515,6 @@ public class LineChartFunctionality {
return regressionSeriesConfidenceInterval;
}
- public static void setRegressionSeriesConfidenceInterval(XYChart.Series<String, Number> regressionSeriesConfidenceInterval) {
- LineChartFunctionality.regressionSeriesConfidenceInterval = regressionSeriesConfidenceInterval;
- }
-
public static LineChart<String, Number> getLineChart() {
return lineChart;
}
@@ -729,6 +527,5 @@ public class LineChartFunctionality {
public static void clearLineChart() {
getLineChart().getData().clear();
- //lineChart.getData().
}
}
--
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