Reflect tp review for the matrix part

docs/DeveloperGuide.md

@@ -428,8 +428,9 @@ Below is an example usage scenario and how the `Matrix` feature behaves at each
 
 When user enters an input:
 ```
-Matrix. [1,2;3,4] .* [5,6;7,8]
+Matrix [1,2;3,4] .* [5,6;7,8]
 ```
+
 #### Calculator class
 
 step 1. `run()` function in `Calculator.class` firstly get `toDo` as the argument which is `[1,2;3,4] .* [5,6;7,8]` in the above example.

docs/UserGuide.md

@@ -108,7 +108,7 @@ This is the vertical shift: 0.0
 ### 2) Matrix Calculation: `Matrix`
 This feature accepts matrix equation and outputs calculation result.
 
-Format: `Matrix. [Matrix] [operator] [Matrix]`
+Format: `Matrix [Matrix] [operator] [Matrix]`
 
 * `[Matrix]` is the 2 dimensional matrix with integer elements. When you declare the matrix, you should follow the matrix format below:
   ```
@@ -129,10 +129,86 @@ Format: `Matrix. [Matrix] [operator] [Matrix]`
    * `+` : matrix addition
    * `-` : matrix subtraction
 
-Example input:
+#### Examples for the matrix multiplication
+
+Input:
+ ```
+ Matrix [1,2;3,4] .* [4,5;6,7]
+ ```
+
+Expected output:
+ ```
+ Result.
+     1. shape : 2 x 2
+     2. value : 
+         0) 16 19 
+         1) 36 43 
+ ```
+
+#### Examples for the matrix multiplication with transpose
+
+Input:
+ ```
+ Matrix [1,2;3,4] .* [4,5;6,7].T
  ```
- Matrix. [1,2;3,4] .* [4,5;6,7]
+
+output:
  ```
+ Result.
+     1. shape : 2 x 2
+     2. value : 
+         0) 14 20 
+         1) 32 46 
+ ```
+
+#### Examples for the matrix element wise product
+
+Input:
+ ```
+ Matrix [1,2;3,4] * [4,5;6,7]
+ ```
+
+output:
+ ```
+ Result.
+     1. shape : 2 x 2
+     2. value : 
+         0) 4 10 
+         1) 18 28 
+ ```
+
+#### Examples for the matrix addition
+
+Input:
+ ```
+ Matrix [1,2;3,4] + [4,5;6,7]
+ ```
+
+output:
+ ```
+ Result.
+     1. shape : 2 x 2
+     2. value : 
+         0) 5 7 
+         1) 9 11 
+ ```
+
+#### Examples for the matrix subtraction
+
+Input:
+ ```
+ Matrix [1,2;3,4] - [4,5;6,7]
+ ```
+
+output:
+ ```
+ Result.
+     1. shape : 2 x 2
+     2. value : 
+         0) -3 -3 
+         1) -3 -3 
+ ```
+
 ### 3) Store Notes: `Store`
 * Adds a new item to the Notes list.
 * Format: `Store <item description>`

src/main/java/seedu/badmaths/CommandHistory.java

@@ -19,6 +19,6 @@ public void displayHistory() {
         for (String command : historyCommand) {
             System.out.println(command);
         }
-        System.out.println();
+
     }
 }

src/main/java/seedu/badmaths/matrix/Calculate.java

@@ -12,7 +12,7 @@ public class Calculate {
     ExceptionPrinter ep = new ExceptionPrinter();
 
     // TODO : Implement exception related to tensor's shape mismatch
-    public Tensor2D mul(Tensor2D t1, Tensor2D t2){
+    public Tensor2D mul(Tensor2D t1, Tensor2D t2) {
         Shape t1Shape = t1.shape();
         Shape t2Shape = t2.shape();
 
@@ -22,25 +22,25 @@ public Tensor2D mul(Tensor2D t1, Tensor2D t2){
             Tensor2D t2T = t2.t();
             int[][] output = new int[t1Shape.row][t2Shape.column];
 
-            for(int i=0; i<t1Shape.row; i++){
-                for(int j=0; j<t2Shape.column; j++){
+            for(int i = 0; i < t1Shape.row; i++) {
+                for(int j = 0; j < t2Shape.column; j++) {
                     output[i][j] = 0;
 
-                    for(int k=0; k<t1Shape.column; k++){
+                    for(int k = 0; k < t1Shape.column; k++) {
                         output[i][j] += t1.get(i, k) * t2T.get(j, k);
                     }
                 }
             }
 
             return new Tensor2D(output);
-        }catch (ShapeMismatchException e){
+        } catch (ShapeMismatchException e) {
             ep.printShapeMismatchExceptionLog();
             return null;
         }
     }
 
     // TODO : Implement exception related to tensor's shape mismatch
-    public Tensor2D dot(Tensor2D t1, Tensor2D t2){
+    public Tensor2D dot(Tensor2D t1, Tensor2D t2) {
         Shape t1Shape = t1.shape();
         Shape t2Shape = t2.shape();
 
@@ -49,21 +49,21 @@ public Tensor2D dot(Tensor2D t1, Tensor2D t2){
 
             int[][] output = new int[t1Shape.row][t1Shape.column];
 
-            for(int i=0; i<t1Shape.row; i++){
-                for(int j=0; j<t1Shape.column; j++){
+            for(int i = 0; i < t1Shape.row; i++) {
+                for(int j = 0; j < t1Shape.column; j++) {
                     output[i][j] = t1.get(i, j) * t2.get(i, j);
                 }
             }
 
             return new Tensor2D(output);
-        }catch (ShapeMismatchException e){
+        } catch (ShapeMismatchException e) {
             ep.printShapeMismatchExceptionLog();
             return null;
         }
     }
 
     // TODO : Implement exception related to tensor's shape mismatch
-    public Tensor2D add(Tensor2D t1, Tensor2D t2){
+    public Tensor2D add(Tensor2D t1, Tensor2D t2) {
         Shape t1Shape = t1.shape();
         Shape t2Shape = t2.shape();
 
@@ -72,20 +72,20 @@ public Tensor2D add(Tensor2D t1, Tensor2D t2){
 
             int[][] output = new int[t1Shape.row][t1Shape.column];
 
-            for(int i=0; i<t1Shape.row; i++){
-                for(int j=0; j<t1Shape.column; j++){
+            for(int i = 0; i < t1Shape.row; i++) {
+                for(int j = 0; j < t1Shape.column; j++) {
                     output[i][j] = t1.get(i, j) + t2.get(i, j);
                 }
             }
 
             return new Tensor2D(output);
-        }catch (ShapeMismatchException e){
+        } catch (ShapeMismatchException e) {
             ep.printShapeMismatchExceptionLog();
             return null;
         }
     }
 
-    public Tensor2D sub(Tensor2D t1, Tensor2D t2){
+    public Tensor2D sub(Tensor2D t1, Tensor2D t2) {
         Shape t1Shape = t1.shape();
         Shape t2Shape = t2.shape();
 
@@ -94,14 +94,14 @@ public Tensor2D sub(Tensor2D t1, Tensor2D t2){
 
             int[][] output = new int[t1Shape.row][t1Shape.column];
 
-            for(int i=0; i<t1Shape.row; i++){
-                for(int j=0; j<t1Shape.column; j++){
+            for(int i = 0; i < t1Shape.row; i++) {
+                for(int j = 0; j < t1Shape.column; j++) {
                     output[i][j] = t1.get(i, j) - t2.get(i, j);
                 }
             }
 
             return new Tensor2D(output);
-        }catch (ShapeMismatchException e){
+        } catch (ShapeMismatchException e) {
             ep.printShapeMismatchExceptionLog();
             return null;
         }

src/main/java/seedu/badmaths/matrix/Calculator.java

@@ -6,7 +6,7 @@
 public class Calculator {
     Logger logger = Logger.getLogger("matrix");
 
-    public void run(String toDo){
+    public void run(String toDo) {
         logger.log(Level.INFO, "Start to open calculator.");
 
         Ui ui = new Ui();

src/main/java/seedu/badmaths/matrix/Execute.java

@@ -1,7 +1,7 @@
 package seedu.badmaths.matrix;
 
 public class Execute {
-    public Tensor2D executeMul(String command){
+    public Tensor2D executeMul(String command) {
         Calculate c = new Calculate();
 
         String[] operator = command.split("\\.\\*");
@@ -16,7 +16,7 @@ public Tensor2D executeMul(String command){
         return result;
     }
 
-    public Tensor2D executeDot(String command){
+    public Tensor2D executeDot(String command) {
         Calculate c = new Calculate();
 
         String[] operator = command.split("\\*");
@@ -31,7 +31,7 @@ public Tensor2D executeDot(String command){
         return result;
     }
 
-    public Tensor2D executeAdd(String command){
+    public Tensor2D executeAdd(String command) {
         Calculate c = new Calculate();
 
         String[] operator = command.split("\\+");
@@ -46,7 +46,7 @@ public Tensor2D executeAdd(String command){
         return result;
     }
 
-    public Tensor2D executeSub(String command){
+    public Tensor2D executeSub(String command) {
         Calculate c = new Calculate();
 
         String[] operator = command.split("-");
@@ -61,12 +61,12 @@ public Tensor2D executeSub(String command){
         return result;
     }
 
-    public Tensor2D executeTranspose(String command){
+    public Tensor2D executeTranspose(String command) {
         String operator;
-        if(command.contains(".T")){
+        if(command.contains(".T")) {
             operator = command.replace(".T", "");
             return Parser.parseMatrix(operator).t();
-        }else{
+        } else {
             return Parser.parseMatrix(command);
         }
     }

src/main/java/seedu/badmaths/matrix/Parser.java

@@ -16,15 +16,15 @@ public Tensor2D parse(String command) {
         try {
             check.checkUnknownOperator(command);
 
-            if(command.contains("+")){
-                type = CalType.ADD;
-            }else if(command.contains("-")){
-                type = CalType.SUB;
-            }else if(command.contains(".*")){
-                type = CalType.MUL;
-            }else if(command.contains("*")){
-                type = CalType.DOT;
-            }else{
+            if(command.contains("+")) {
+                type = CalType.ADDITION;
+            } else if(command.contains("-")) {
+                type = CalType.SUBTRACTION;
+            } else if(command.contains(".*")) {
+                type = CalType.MULTIPLICATION;
+            } else if(command.contains("*")) {
+                type = CalType.ELEMENT_WISE_DOT_PRODUCT;
+            } else {
                 type = CalType.UNKNOWN;
             }
 
@@ -36,25 +36,25 @@ public Tensor2D parse(String command) {
             Calculate c = new Calculate();
             Execute e = new Execute();
 
-            switch(type){
-            case ADD:
+            switch(type) {
+            case ADDITION:
                 result = e.executeAdd(command);
                 break;
-            case SUB:
+            case SUBTRACTION:
                 result = e.executeSub(command);
                 break;
-            case MUL:
+            case MULTIPLICATION:
                 result = e.executeMul(command);
                 break;
-            case DOT:
+            case ELEMENT_WISE_DOT_PRODUCT:
                 result = e.executeDot(command);
                 break;
             default:
                 break;
             }
 
             return result;
-        }catch (UnknownOperatorException e){
+        } catch (UnknownOperatorException e) {
             ep.printUnknownOperatorExceptionLog();
             return null;
         }
@@ -78,8 +78,8 @@ public static Tensor2D parseMatrix(String command) {
         assert rowNum == 1 || colNum == rows[1].split(",").length;
 
         tensor = new int[rowNum][colNum];
-        for(int i=0; i<rowNum; i++){
-            for(int j=0; j<colNum; j++){
+        for(int i = 0; i < rowNum; i++) {
+            for(int j = 0; j < colNum; j++) {
                 column = rows[i].split(",");
                 tensor[i][j] = Integer.parseInt(column[j]);
             }
@@ -89,6 +89,6 @@ public static Tensor2D parseMatrix(String command) {
     }
 
     enum CalType {
-        ADD, SUB, MUL, DOT, UNKNOWN
+        ADDITION, SUBTRACTION, MULTIPLICATION, ELEMENT_WISE_DOT_PRODUCT, UNKNOWN
     }
 }

src/main/java/seedu/badmaths/matrix/Shape.java

@@ -4,7 +4,7 @@ public class Shape {
     protected int row;
     protected int column;
 
-    public Shape(int row, int column){
+    public Shape(int row, int column) {
         this.row = row;
         this.column = column;
     }

src/main/java/seedu/badmaths/matrix/Tensor2D.java

@@ -35,8 +35,8 @@ public Tensor2D t(){
 
         int[][] transposeTensor = new int[column][row];
 
-        for(int i=0; i<column; i++){
-            for(int j=0; j<row; j++){
+        for(int i = 0; i < column; i++) {
+            for(int j = 0; j < row; j++) {
                 transposeTensor[i][j] = tensor[j][i];
             }
         }
@@ -53,9 +53,9 @@ public String toString() {
         str.append("    1. shape : ").append(row).append(" x ").append(column).append("\n");
         str.append("    2. value : \n");
 
-        for(int i=0; i<row; i++){
+        for(int i = 0; i < row; i++) {
             str.append("        ").append(i).append(") ");
-            for(int j=0; j<column; j++){
+            for(int j = 0; j < column; j++){
                 str.append(tensor[i][j]).append(" ");
             }
             str.append("\n");