Enhanced linear regression and maven updates

Added the ability to predict a result from a selected X value
Adding next value to stack is no longer the default - you need to use
the `add` parameter
Updated the following plugins:
  maven-compiler-plugin
  maven-surefire-plugin
  maven-shade-plugin
  exec-maven-plugin
Updated the following dependencies:
  fross libray
  jline-reader
  jline-terminal-jansi

Updated UserGuide for the Linear Regression command
Added enhanced lr tests

.classpath

@@ -13,9 +13,8 @@
 			<attribute name="maven.pomderived" value="true"/>
 		</attributes>
 	</classpathentry>
-	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/jdk">
+	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/JavaSE-11">
 		<attributes>
-			<attribute name="module" value="true"/>
 			<attribute name="maven.pomderived" value="true"/>
 		</attributes>
 	</classpathentry>

mdbook/src/Chapters/CalculatorCommands.md

@@ -21,7 +21,7 @@ These commands, like the others you'll read about later, are executed by typing
 |fact <br>factorial| **FACTORIAL**<br>Takes the factorial of `line1`. The factorial target number must be an integer, so if there is a decimal component, it will be dropped (not rounded) as with the `int` command|
 |f <br> flip | **FLIP SIGN**<br>Flip the sign on the top stack item (`line1`). This is effectively multiplying `line1` by `-1`|
 |int| **INTEGER**<br>Converts the top stack item (`line1`) to it's integer value.  This will discard the decimal portion regardless of it's value.  For example: `4.34` will result in `4` and `4.999` will also result in `4`. If rounding is desired, execute the `round` command prior to `int` (or create a user defined function)|
-|lr| **SIMPLE LINEAR REGRESSION**<br>[Linear regression](https://www.graphpad.com/guides/the-ultimate-guide-to-linear-regression) is used to model the relationship between two variables and create a line that can be used to estimate other values using a line-of-best-fit method. This implementation is for simple linear regression and will show you the formula, slope, y-intercept as well as add the next expected value to the top of the stack.<br><br>The values will be plotted from the bottom of the stack to the top (`line1`)(which is probably want you want).  If you need it the other way around, simply reverse the stack with the `reverse` or `rev` command prior to executing `lr`|
+|lr [add]<br>lr [x]| **SIMPLE LINEAR REGRESSION**<br>[Linear regression](https://www.graphpad.com/guides/the-ultimate-guide-to-linear-regression) is used to model the relationship between two variables and create a line that can be used to estimate other values using a line-of-best-fit method. This implementation is for simple linear regression, and will display the formula, slope, y-intercept as well as add the next expected value to the top of the stack.<br><br>If `add` (or just `a`) is entered, the next predicted value will be added to the top of the stack (`line1`). If a number is provided (`x`), the predicted `y` value will be displayed.  The `y` value is the result of the linear extrapolation at the `x` value. If both are added, the y value at the x location will be both calculated and added to the top of the stack (`line1`)<br><br>The values will be plotted from the bottom of the stack to the top (`line1`)(which is probably want you want).  If you need it the other way around, simply reverse the stack with the `reverse` or `rev` command prior to executing `lr`|
 |log|**LOGARITHM BASE e**<br>Calculates the [natural logarithm (base e)](https://en.wikipedia.org/wiki/Natural_logarithm). Please note that these are calculated as a `double` and therefore do not have unlimited precision|
 |log10|**LOGARITHM BASE 10**<br>Calculates the [base10 logarithm](https://en.wikipedia.org/wiki/Common_logarithm). Please note that these are calculated as a `double` and therefore do not have unlimited precision|
 |max|**MAXIMUM VALUE**<br>Copies the largest value in the top of the stack (`line1`)|

pom.xml

@@ -3,7 +3,7 @@
 
 	<groupId>org.fross</groupId>
 	<artifactId>rpncalc</artifactId>
-	<version>5.1.7</version>
+	<version>5.1.8</version>
 	<packaging>jar</packaging>
 
 	<name>rpncalc</name>
@@ -64,7 +64,7 @@
 				<!-- ========================================================================================== -->
 				<groupId>org.apache.maven.plugins</groupId>
 				<artifactId>maven-compiler-plugin</artifactId>
-				<version>3.11.0</version>
+				<version>3.12.1</version>
 				<configuration>
 					<release>${maven.compiler.release}</release>
 				</configuration>
@@ -77,7 +77,7 @@
 			<plugin>
 				<groupId>org.apache.maven.plugins</groupId>
 				<artifactId>maven-surefire-plugin</artifactId>
-				<version>3.1.0</version>
+				<version>3.2.5</version>
 			</plugin>
 
 			<!-- ========================================================================================== -->
@@ -87,7 +87,7 @@
 			<plugin>
 				<groupId>org.apache.maven.plugins</groupId>
 				<artifactId>maven-shade-plugin</artifactId>
-				<version>3.4.1</version>
+				<version>3.5.1</version>
 				<executions>
 					<execution>
 						<phase>package</phase>
@@ -182,7 +182,7 @@
 			<plugin>
 				<groupId>org.codehaus.mojo</groupId>
 				<artifactId>exec-maven-plugin</artifactId>
-				<version>3.1.0</version>
+				<version>3.1.1</version>
 				<executions>
 					<execution>
 						<id>chmod</id>
@@ -240,7 +240,7 @@
 		<dependency>
 			<groupId>org.fross</groupId>
 			<artifactId>library</artifactId>
-			<version>2023.12.03</version>
+			<version>2024.01.22</version>
 		</dependency>
 
 		<!-- https://mvnrepository.com/artifact/org.junit.jupiter/junit-jupiter -->
@@ -255,15 +255,15 @@
 		<dependency>
 			<groupId>org.jline</groupId>
 			<artifactId>jline-reader</artifactId>
-			<version>3.25.0</version>
+			<version>3.25.1</version>
 		</dependency>
 
 		<!-- https://mvnrepository.com/artifact/org.jline/jline-terminal-jansi -->
 		<!-- Needed to remove jline warning when app starts -->
 		<dependency>
 			<groupId>org.jline</groupId>
 			<artifactId>jline-terminal-jansi</artifactId>
-			<version>3.25.0</version>
+			<version>3.25.1</version>
 		</dependency>
 
 	</dependencies>

snap/snapcraft.yaml

@@ -1,5 +1,5 @@
 name: rpncalc
-version: '5.1.7'
+version: '5.1.8'
 summary: The command line Reverse Polish Notation (RPN) calculator
 description: |
   RPNCalc is an easy to use command line based Reverse Polish
@@ -50,7 +50,7 @@ parts:
       plugin: maven
       source: https://github.com/frossm/library.git
       source-type: git
-      source-tag: 'v2023.12.03'
+      source-tag: 'v2024.01.22'
       maven-parameters:
          - install
 

src/main/java/org/fross/rpncalc/CommandParser.java

@@ -163,7 +163,7 @@ public static void Parse(StackObj calcStack, StackObj calcStack2, String cmdInpu
 
 		// Linear Regression
 		case "lr":
-			StackCommands.cmdLinearRegression(calcStack);
+			StackCommands.cmdLinearRegression(calcStack, cmdInputParam);
 			break;
 
 		// Absolute Value

src/main/java/org/fross/rpncalc/Help.java

@@ -81,7 +81,7 @@ public static void Display() {
 		Output.printColorln(Ansi.Color.WHITE, " fact           Take a factorial of line1. Decimals will be dropped");
 		Output.printColorln(Ansi.Color.WHITE, " f              Flip the sign of the element at line1");
 		Output.printColorln(Ansi.Color.WHITE, " int            Convert line1 to an integer. No rounding is performed");
-		Output.printColorln(Ansi.Color.WHITE, " lr             Simple Linear regression. Calculate the next predicted value");
+		Output.printColorln(Ansi.Color.WHITE, " lr [add] [x]   Linear Regress. 'add' will add next value. x adds the y value at that x");
 		Output.printColorln(Ansi.Color.WHITE, " log | log10    Calculate the natural (base e) or base10 logarithm");
 		Output.printColorln(Ansi.Color.WHITE, " min | max      Add the minimum or maximum stack value to the stack");
 		Output.printColorln(Ansi.Color.WHITE, " median [keep]  Replace stack with median value. 'keep' will retain stack");

src/main/java/org/fross/rpncalc/StackCommands.java

@@ -406,13 +406,40 @@ public static void cmdInteger(StackObj calcStack) {
 	 * 
 	 * @param calcStack
 	 */
-	public static void cmdLinearRegression(StackObj calcStack) {
+	public static void cmdLinearRegression(StackObj calcStack, String args) {
+		boolean argAdd = false;
+		BigDecimal argX = new BigDecimal(calcStack.size());
+
 		// Ensure we have at least 2 values on the stack
 		if (calcStack.size() < 2) {
 			Output.printColorln(Ansi.Color.RED, "Error: There must be at least two items on the stack to calculate a linear regression");
 			return;
 		}
 
+		// Process the arguments
+		try {
+			// If any arguments were supplied
+			if (!args.isEmpty()) {
+				// Loop through each option and process it
+				for (String a : args.split("\\s")) {
+					// Look for a string that starts with 'a'
+					if (a.toLowerCase().startsWith("a")) {
+						argAdd = true;
+						Output.debugPrintln("Setting LR ADD flag");
+						continue;
+					} else {
+						argX = new BigDecimal(a).subtract(BigDecimal.ONE);
+						Output.debugPrintln("Setting LR 'x' value to : " + argX.toString());
+						continue;
+					}
+				}
+			}
+
+		} catch (Exception ex) {
+			Output.printColorln(Ansi.Color.RED, "ERROR: Acceptable linear regression options are 'add' or a number");
+			return;
+		}
+
 		// X is the number of stack items
 		BigDecimal n = new BigDecimal(String.valueOf(calcStack.size()));
 		BigDecimal sumX = BigDecimal.ZERO;		// X values are the stack numbers
@@ -464,31 +491,34 @@ public static void cmdLinearRegression(StackObj calcStack) {
 		BigDecimal b = b_top.divide(b_bottom, MathContext.DECIMAL128);
 
 		// Output details if debug is enabled
-		Output.debugPrintln("n:     " + n.toPlainString());
-		Output.debugPrintln("sumX:  " + sumX.toPlainString());
-		Output.debugPrintln("sumY:  " + sumY.toPlainString());
-		Output.debugPrintln("sumXY: " + sumXY.toPlainString());
-		Output.debugPrintln("sumX2: " + sumX2.toPlainString());
-		Output.debugPrintln("sumY2: " + sumY2.toPlainString());
-		Output.debugPrintln("a:     " + a.toPlainString());
-		Output.debugPrintln("b:     " + b.toPlainString());
+		Output.debugPrintln("n:         " + n.toPlainString());
+		Output.debugPrintln("sumX:      " + sumX.toPlainString());
+		Output.debugPrintln("sumY:      " + sumY.toPlainString());
+		Output.debugPrintln("sumXY:     " + sumXY.toPlainString());
+		Output.debugPrintln("sumX2:     " + sumX2.toPlainString());
+		Output.debugPrintln("sumY2:     " + sumY2.toPlainString());
+		Output.debugPrintln("a:         " + a.toPlainString());
+		Output.debugPrintln("b:         " + b.toPlainString());
+		Output.debugPrintln("NextValue: " + argX.toPlainString() + " (one less than displayed)");
 
 		// Rounded values are just for the display
-		BigDecimal nextValue = a.add(b.multiply(n.add(BigDecimal.ONE)));
+		BigDecimal nextValue = a.add(b.multiply(argX.add(BigDecimal.ONE)));
 		BigDecimal aRounded = a.setScale(4, RoundingMode.HALF_UP);
 		BigDecimal bRounded = b.setScale(4, RoundingMode.HALF_UP);
 		BigDecimal nextValueRounded = nextValue.setScale(4, RoundingMode.HALF_UP);
 
 		// Display the LR formula
 		Output.printColorln(Ansi.Color.CYAN, "Slope Equation: y = " + bRounded + "x + " + aRounded);
 		Output.printColorln(Ansi.Color.CYAN, "Slope: " + bRounded + "   Y-Intercept: " + aRounded);
-		Output.printColorln(Ansi.Color.CYAN, "Predicted next value (" + nextValueRounded + ") added to the top of the stack");
-
-		// Save current calcStack to the undoStack
-		calcStack.saveUndo();
+		Output.printColorln(Ansi.Color.CYAN, "Predicted value at x = " + argX.add(BigDecimal.ONE) + ": " + nextValueRounded);
 
-		// Add the next predicted value to the stack
-		calcStack.push(nextValue);
+		// Add the next predicted value to the stack if 'add' was selected
+		if (argAdd) {
+			// Save current calcStack to the undoStack
+			calcStack.saveUndo();
+
+			calcStack.push(nextValue);
+		}
 
 	}
 

src/test/java/org/fross/rpncalc/StackCommandsTest.java

@@ -570,7 +570,7 @@ void testCmdInteger() {
 
 	/**
 	 * Testing the linear regression results
-	 * 
+	 * Reference for testing:  https://www.socscistatistics.com/tests/regression/default.aspx
 	 */
 	@Test
 	void testCmdLinearRegression() {
@@ -584,7 +584,7 @@ void testCmdLinearRegression() {
 		stk.push(20.00);
 		stk.push(10.00);
 		stk.push(35.00);
-		StackCommands.cmdLinearRegression(stk);
+		StackCommands.cmdLinearRegression(stk, "a");
 		StackCommands.cmdRound(stk, "4");
 		assertEquals(8, stk.size());
 		assertEquals(27.7143, stk.pop().doubleValue());
@@ -601,7 +601,7 @@ void testCmdLinearRegression() {
 		stk.push(11.11);
 		stk.push(22.22);
 		stk.push(3.0);
-		StackCommands.cmdLinearRegression(stk);
+		StackCommands.cmdLinearRegression(stk, "a");
 		StackCommands.cmdRound(stk, "6");
 		assertEquals(11, stk.size());
 		assertEquals(16.671333, stk.pop().doubleValue());
@@ -618,7 +618,7 @@ void testCmdLinearRegression() {
 		stk.push(-34.88);
 		stk.push(40.99);
 		stk.push(3.00);
-		StackCommands.cmdLinearRegression(stk);
+		StackCommands.cmdLinearRegression(stk, "a");
 		StackCommands.cmdRound(stk, "6");
 		assertEquals(11, stk.size());
 		assertEquals(4.271333, stk.pop().doubleValue());
@@ -629,7 +629,7 @@ void testCmdLinearRegression() {
 		for (int i = 0; i < testValues.length; i++) {
 			stk.push(testValues[i]);
 		}
-		StackCommands.cmdLinearRegression(stk);
+		StackCommands.cmdLinearRegression(stk, "a");
 		StackCommands.cmdRound(stk, "7");
 		assertEquals(48.9842105, stk.pop().doubleValue());
 
@@ -639,7 +639,7 @@ void testCmdLinearRegression() {
 		for (int i = 0; i < testValues1.length; i++) {
 			stk.push(testValues1[i]);
 		}
-		StackCommands.cmdLinearRegression(stk);
+		StackCommands.cmdLinearRegression(stk, "a");
 		StackCommands.cmdRound(stk, "9");
 		assertEquals(17, stk.size());
 		assertEquals(-9.101980055, stk.pop().doubleValue());
@@ -652,10 +652,45 @@ void testCmdLinearRegression() {
 			stk.push(testValues2[i]);
 		}
 		assertEquals(12, stk.size());
-		StackCommands.cmdLinearRegression(stk);
+		StackCommands.cmdLinearRegression(stk, "a");
 		StackCommands.cmdRound(stk, "9");
 		assertEquals("47498562223075895424.242424242", stk.peek().toEngineeringString());
 		assertEquals(13, stk.size());
+
+		// Test #7 - Custom X values
+		stk.clear();
+		Double[] testValues3 = { 29.0, 41.0, 8.0, 18.0, 22.0, 99.0, 32.0, 15.0, 31.0, 3.0, 72.0, 12.0, 60.0, 32.0, 54.0, 45.0, 34.0, 76.0, 5.0, 67.0 };
+		for (int i = 0; i < testValues3.length; i++) {
+			stk.push(testValues3[i]);
+		}
+		StackCommands.cmdLinearRegression(stk, "30 a");
+		StackCommands.cmdRound(stk, "4");
+		assertEquals(58.6135, stk.pop().doubleValue());
+		assertEquals(20, stk.size());
+
+		// Test #8 - Custom X values
+		stk.clear();
+		Double[] testValues4 = { 19.0, 41.0, 8.0, 18.0, 12.0, -99.0, 32.0, 15.0, 31.0, 3.0, 72.0, 12.0, 60.0, 32.0, 54.0, 45.0, 34.0, 76.0, 5.0, 67.0 };
+		for (int i = 0; i < testValues4.length; i++) {
+			stk.push(testValues4[i]);
+		}
+		StackCommands.cmdLinearRegression(stk, "22 a");
+		StackCommands.cmdRound(stk, "4");
+		assertEquals(57.1564, stk.pop().doubleValue());
+		assertEquals(20, stk.size());
+
+		// Test #9 - Custom X values
+		stk.clear();
+		Double[] testValues5 = { 29.0, 41.0, 8.0, 18.0, 22.0, -99.0, 32.0, 15.0, 31.0, 3.0, 72.0, 12.0, -60.0, 32.0, 54.0, 45.0, 14.0, 76.0, 5.0, 44.0 };
+		for (int i = 0; i < testValues5.length; i++) {
+			stk.push(testValues5[i]);
+		}
+		StackCommands.cmdLinearRegression(stk, "45 a");
+		StackCommands.cmdRound(stk, "4");
+		assertEquals(69.1932, stk.pop().doubleValue());
+		assertEquals(20, stk.size());
+
+
 	}
 
 	/**