Addition
Subtraction
Multiplication
Transpose A
Transpose B
Determinant A
Determinant B
Select the matrix operation to perform.
Calculation Results
Result:N/A
Formula Used:Select an operation and input matrix dimensions to see the formula.
Matrix Operation Visualization
Chart showing element-wise comparison or operation outcome.
Matrix Data
Matrix
Dimensions
Elements
Matrix A
N/A
N/A
Matrix B
N/A
N/A
Summary of input matrices and their dimensions.
What is a Matriz Calculator?
A Matriz Calculator is a specialized computational tool designed to perform various mathematical operations on matrices. Matrices, which are rectangular arrays of numbers, symbols, or expressions arranged in rows and columns, are fundamental in many fields including linear algebra, physics, engineering, computer graphics, economics, and statistics. A matriz calculator simplifies complex matrix manipulations, making them accessible and efficient for students, researchers, and professionals.
This tool is invaluable for anyone who needs to work with matrices, whether for solving systems of linear equations, performing transformations in geometry, analyzing data, or implementing algorithms in computer science. It eliminates the need for manual calculations, which are prone to errors and time-consuming, especially for larger matrices.
Who Should Use a Matriz Calculator?
Students: Learning linear algebra concepts, solving homework problems, and preparing for exams.
Engineers: Applying matrix methods in structural analysis, control systems, signal processing, and fluid dynamics.
Computer Scientists: Working with algorithms for machine learning, computer graphics, image processing, and data analysis.
Researchers: Utilizing matrix operations in statistical modeling, econometrics, and scientific simulations.
Financial Analysts: Employing matrices for portfolio optimization, risk management, and economic forecasting.
Common Misconceptions
Misconception: Matrix calculators are only for advanced mathematicians. Reality: While matrices are a core concept in advanced math, basic operations are taught early, and calculators make them accessible to beginners.
Misconception: All matrix operations are complex. Reality: Operations like addition, subtraction, and transposition are straightforward. Multiplication and finding determinants can be more involved, but calculators handle them easily.
Misconception: Calculators replace understanding. Reality: A good matriz calculator aids understanding by providing quick results and explanations, but conceptual knowledge is still crucial for effective application.
Matriz Calculator Formula and Mathematical Explanation
The specific formula used by a matriz calculator depends entirely on the selected operation. Here's a breakdown of common operations:
1. Matrix Addition/Subtraction
For two matrices A and B of the same dimensions (m x n), their sum (A + B) or difference (A – B) is a matrix C of the same dimensions, where each element Cij is the sum or difference of the corresponding elements of A and B.
Formula: Cij = Aij ± Bij
2. Matrix Multiplication
For matrix A (m x n) and matrix B (n x p), their product C = AB is a matrix of dimensions (m x p). The element Cij is calculated by taking the dot product of the i-th row of A and the j-th column of B.
Formula: Cij = Σk=1n (Aik * Bkj)
3. Matrix Transpose
The transpose of a matrix A (m x n), denoted as AT, is an n x m matrix where the rows of A become the columns of AT (and vice versa).
Formula: (AT)ij = Aji
4. Determinant
The determinant is a scalar value calculated from a square matrix. For a 2×2 matrix:
Formula (2×2): For A = [[a, b], [c, d]], det(A) = ad – bc
For larger matrices (3×3 and above), methods like cofactor expansion or row reduction are used, which are computationally intensive and best handled by a calculator.
Variable
Meaning
Unit
Typical Range
Aij, Bij
Element in the i-th row and j-th column of matrix A or B
Number (Integer, Decimal)
Depends on input; can be any real number
m, n, p
Dimensions of matrices (rows/columns)
Count
1 to 10 (for this calculator)
Cij
Resulting element in the i-th row and j-th column of the output matrix
Number (Integer, Decimal)
Depends on operation and input values
det(A)
Determinant of matrix A
Number (Scalar)
Can be any real number (positive, negative, or zero)
Practical Examples (Real-World Use Cases)
Example 1: Calculating Portfolio Returns
An investment firm manages two portfolios (Portfolio X and Portfolio Y) with three asset classes: Stocks, Bonds, and Real Estate. The current values of these assets in each portfolio are represented by Matrix A.
To find the total annual return for each portfolio, we perform matrix multiplication (A * B).
Inputs for Calculator:
Matrix A Rows: 2
Matrix A Columns: 3
Matrix B Rows: 3
Matrix B Columns: 1
Operation: Multiplication
Matrix A Elements: [[100000, 50000, 25000], [150000, 75000, 30000]]
Matrix B Elements: [[8000, 4000, 6000]] (Note: Inputting as row for simplicity in some calculators, but conceptually it's a column vector)
Calculator Output:
Primary Result: Total Annual Return per Portfolio
[ 10,300 ] (Portfolio X Return: $10,300)
[ 15,900 ] (Portfolio Y Return: $15,900)
Interpretation: Portfolio X is projected to yield $10,300 annually, while Portfolio Y is projected to yield $15,900. This helps in comparing portfolio performance.
Example 2: Image Transformation in Computer Graphics
In computer graphics, transformations like scaling, rotation, and translation are often represented by matrices. Consider a 2D point P represented as a matrix.
Point P:
[ 5 ]
[ 3 ]
We want to scale this point by a factor of 2 in the x-direction and 1.5 in the y-direction using a scaling matrix S.
Scaling Matrix S:
[ 2.0 0.0 ]
[ 0.0 1.5 ]
To find the new coordinates P', we multiply the scaling matrix S by the point matrix P (S * P).
Inputs for Calculator:
Matrix A Rows: 2
Matrix A Columns: 2
Matrix B Rows: 2
Matrix B Columns: 1
Operation: Multiplication
Matrix A Elements: [[2, 0], [0, 1.5]]
Matrix B Elements: [[5], [3]]
Calculator Output:
Primary Result: Transformed Point Coordinates
[ 10.0 ]
[ 4.5 ]
Interpretation: The original point (5, 3) has been transformed to (10.0, 4.5) after applying the scaling transformation. This is a fundamental operation in rendering 2D graphics.
How to Use This Matriz Calculator
Our Matriz Calculator is designed for simplicity and accuracy. Follow these steps to get started:
Input Matrix Dimensions: Enter the number of rows and columns for both Matrix A and Matrix B in the respective fields. Ensure these dimensions are valid (between 1 and 10 for this calculator).
Select Operation: Choose the desired mathematical operation from the dropdown menu (Addition, Subtraction, Multiplication, Transpose, Determinant).
Enter Matrix Elements: Based on the dimensions you entered, the calculator will prompt you to input the individual elements for Matrix A and Matrix B. Enter the numerical values for each cell. For operations like addition or subtraction, the dimensions must match. For multiplication, the number of columns in Matrix A must equal the number of rows in Matrix B. For transpose and determinant, only one matrix is needed.
Calculate: Click the "Calculate" button.
Reading the Results
Primary Result: This is the main outcome of your calculation (e.g., the resulting matrix, the determinant value). It's highlighted for easy identification.
Intermediate Values: For complex operations, key intermediate steps or values might be displayed.
Formula Explanation: A brief description of the mathematical formula used for the selected operation is provided.
Chart: A visual representation of the data or operation outcome is shown. This could be element-wise comparisons or the structure of the resulting matrix.
Matrix Data Table: This table summarizes the dimensions and elements of your input matrices.
Decision-Making Guidance
Use the results to make informed decisions:
Compare Matrices: Use addition/subtraction results to see element-wise differences or similarities.
Analyze Transformations: Multiplication results can show how points or shapes change under transformations.
Solve Systems: Determinants are crucial for determining if a system of linear equations has a unique solution. A non-zero determinant usually implies a unique solution.
Data Analysis: Transposing matrices can help restructure data for different types of analysis.
Don't forget to use the "Copy Results" button to save your findings or share them easily.
Key Factors That Affect Matriz Calculator Results
While the calculator performs precise mathematical operations, several factors related to the input matrices and the chosen operation significantly influence the outcome:
Matrix Dimensions: This is the most critical factor. Addition and subtraction require identical dimensions. Multiplication has specific compatibility rules (columns of the first matrix must match rows of the second). Incorrect dimensions will lead to errors or invalid results.
Element Values: The actual numbers within the matrices directly determine the results. Large numbers can lead to large results, while small numbers or fractions will produce correspondingly scaled outputs. The sign of the elements is also crucial, especially in multiplication and determinant calculations.
Chosen Operation: Each operation (addition, multiplication, transpose, determinant) has a unique mathematical definition and produces a different type of output. Understanding the purpose of each operation is key to interpreting the results correctly.
Order of Operations (for Multiplication): Matrix multiplication is not commutative, meaning A * B is generally not equal to B * A. The order in which you multiply matrices is crucial and depends on their dimensions and the desired outcome.
Square vs. Non-Square Matrices: Determinants can only be calculated for square matrices (number of rows equals number of columns). Operations like multiplication can involve non-square matrices, but the resulting dimensions depend on the input shapes.
Data Type and Precision: While this calculator handles standard numerical inputs, in advanced applications, the data type (integers, floating-point numbers) and the precision used can affect the accuracy of results, especially after many operations. Floating-point inaccuracies can accumulate.
Zero Values: The presence of zeros can simplify calculations significantly, particularly in multiplication (multiplying by zero yields zero) and determinant calculations (rows or columns of zeros often lead to a zero determinant).
Frequently Asked Questions (FAQ)
Q1: Can this calculator handle matrices larger than 10×10?
A: This specific calculator is designed for matrices up to 10×10 for performance and usability reasons. For larger matrices, specialized software like MATLAB, NumPy (Python), or R is recommended.
Q2: What happens if Matrix A and Matrix B have different dimensions for addition?
A: Matrix addition and subtraction are only defined for matrices of the exact same dimensions. If the dimensions don't match, the calculator will show an error, as the operation is mathematically impossible.
Q3: Is matrix multiplication always possible?
A: No. For A * B to be possible, the number of columns in matrix A must equal the number of rows in matrix B. If this condition isn't met, multiplication cannot be performed.
Q4: What does a determinant of zero mean?
A: A determinant of zero for a square matrix indicates that the matrix is singular. This implies that the matrix does not have an inverse, and the system of linear equations represented by the matrix has either no solution or infinitely many solutions.
Q5: How is the transpose of a matrix calculated?
A: The transpose operation simply swaps the rows and columns. The element at row 'i', column 'j' in the original matrix moves to row 'j', column 'i' in the transposed matrix.
Q6: Can I input non-numeric values?
A: This calculator is designed for numerical matrices. It expects numbers (integers or decimals) as input. Non-numeric input will likely result in errors.
Q7: What is the difference between a row vector and a column vector?
A: A row vector is a matrix with one row (e.g., 1xN), while a column vector is a matrix with one column (e.g., Nx1). They are used differently in matrix multiplication depending on whether you are applying a transformation to a point or calculating dot products.
Q8: Why is the chart sometimes not very informative for matrix operations?
A: Charts are best for visualizing relationships or trends. For operations like matrix multiplication resulting in a new matrix, a direct visualization can be complex. The chart here might show element comparisons or simplified representations. For deep analysis, examining the resulting matrix values is often more effective.
Related Tools and Internal Resources
Matriz Calculator Perform matrix operations like addition, subtraction, multiplication, and find determinants.
Linear Equation Solver Solve systems of linear equations using methods like Gaussian elimination.
Data Analysis Suite A collection of tools for statistical analysis and data visualization.
var matrixA = [];
var matrixB = [];
var resultMatrix = [];
var chartInstance = null;
function createMatrixInputs(rows, cols, matrixId) {
var container = document.getElementById(matrixId + '_inputs');
container.innerHTML = "; // Clear previous inputs
var matrix = [];
var tableHtml = '
' + matrixId.toUpperCase() + ' Elements
';
tableHtml += '
';
for (var i = 0; i < rows; i++) {
matrix[i] = [];
tableHtml += '
';
for (var j = 0; j < cols; j++) {
var inputId = matrixId + '_r' + i + '_c' + j;
matrix[i][j] = 0; // Initialize with 0
tableHtml += '
';
}
tableHtml += '
';
}
tableHtml += '
';
container.innerHTML = tableHtml;
return matrix;
}
function updateMatrixValue(matrixId, row, col) {
var inputElement = document.getElementById(matrixId + '_r' + row + '_c' + col);
var value = parseFloat(inputElement.value);
if (isNaN(value)) {
value = 0; // Default to 0 if input is not a number
}
if (matrixId === 'matrixA') {
matrixA[row][col] = value;
} else {
matrixB[row][col] = value;
}
// Optionally trigger recalculation if needed, or wait for button click
// calculateMatrix();
}
function populateMatrixFromInputs(matrixId, rows, cols) {
var matrix = [];
for (var i = 0; i < rows; i++) {
matrix[i] = [];
for (var j = 0; j < cols; j++) {
var inputElement = document.getElementById(matrixId + '_r' + i + '_c' + j);
var value = inputElement ? parseFloat(inputElement.value) : 0;
if (isNaN(value)) {
value = 0;
}
matrix[i][j] = value;
}
}
return matrix;
}
function displayMatrix(matrix, elementId) {
var container = document.getElementById(elementId);
if (!matrix || matrix.length === 0) {
container.innerHTML = "N/A";
return;
}
var html = '
';
for (var i = 0; i < matrix.length; i++) {
html += '
';
for (var j = 0; j < matrix[i].length; j++) {
html += '
' + matrix[i][j].toFixed(4) + '
'; // Format to 4 decimal places
}
html += '
';
}
html += '
';
container.innerHTML = html;
}
function displayIntermediateResults(results) {
var container = document.getElementById('intermediate-results');
container.innerHTML = ";
for (var key in results) {
var div = document.createElement('div');
div.className = 'result-item';
div.innerHTML = '' + key + ':' + results[key].toFixed(4) + '';
container.appendChild(div);
}
}
function setFormulaText(text) {
document.getElementById('formula-text').innerText = text;
}
function validateInputs() {
var errors = false;
var rowsA = parseInt(document.getElementById('matrixA_rows').value);
var colsA = parseInt(document.getElementById('matrixA_cols').value);
var rowsB = parseInt(document.getElementById('matrixB_rows').value);
var colsB = parseInt(document.getElementById('matrixB_cols').value);
var op = document.getElementById('operation').value;
// Clear previous errors
document.getElementById('matrixA_rows_error').innerText = ";
document.getElementById('matrixA_cols_error').innerText = ";
document.getElementById('matrixB_rows_error').innerText = ";
document.getElementById('matrixB_cols_error').innerText = ";
if (isNaN(rowsA) || rowsA 10) {
document.getElementById('matrixA_rows_error').innerText = 'Rows must be between 1 and 10.';
errors = true;
}
if (isNaN(colsA) || colsA 10) {
document.getElementById('matrixA_cols_error').innerText = 'Columns must be between 1 and 10.';
errors = true;
}
if (isNaN(rowsB) || rowsB 10) {
document.getElementById('matrixB_rows_error').innerText = 'Rows must be between 1 and 10.';
errors = true;
}
if (isNaN(colsB) || colsB 10) {
document.getElementById('matrixB_cols_error').innerText = 'Columns must be between 1 and 10.';
errors = true;
}
// Operation-specific validation
if (op === 'add' || op === 'subtract') {
if (rowsA !== rowsB || colsA !== colsB) {
if (rowsA !== rowsB) {
document.getElementById('matrixA_rows_error').innerText += ' Dimensions must match for Add/Subtract.';
document.getElementById('matrixB_rows_error').innerText += ' Dimensions must match for Add/Subtract.';
}
if (colsA !== colsB) {
document.getElementById('matrixA_cols_error').innerText += ' Dimensions must match for Add/Subtract.';
document.getElementById('matrixB_cols_error').innerText += ' Dimensions must match for Add/Subtract.';
}
errors = true;
}
} else if (op === 'multiply') {
if (colsA !== rowsB) {
document.getElementById('matrixA_cols_error').innerText += ' Columns of A must match Rows of B for Multiplication.';
document.getElementById('matrixB_rows_error').innerText += ' Columns of A must match Rows of B for Multiplication.';
errors = true;
}
} else if (op === 'determinantA' || op === 'determinantB') {
// Determinant requires square matrix
var targetMatrix = (op === 'determinantA') ? {rows: rowsA, cols: colsA} : {rows: rowsB, cols: colsB};
if (targetMatrix.rows !== targetMatrix.cols) {
var errorId = (op === 'determinantA') ? 'matrixA_rows_error' : 'matrixB_rows_error';
document.getElementById(errorId).innerText += ' Determinant requires a square matrix.';
errors = true;
}
}
return !errors;
}
function calculateMatrix() {
if (!validateInputs()) {
document.getElementById('main-result-value').innerText = 'Invalid Input';
document.getElementById('intermediate-results').innerHTML = ";
updateTableAndChart([], [], "Invalid Input");
return;
}
var rowsA = parseInt(document.getElementById('matrixA_rows').value);
var colsA = parseInt(document.getElementById('matrixA_cols').value);
var rowsB = parseInt(document.getElementById('matrixB_rows').value);
var colsB = parseInt(document.getElementById('matrixB_cols').value);
var operation = document.getElementById('operation').value;
// Ensure matrices are created/updated based on current dimensions
matrixA = createMatrixInputs(rowsA, colsA, 'matrixA');
matrixB = createMatrixInputs(rowsB, colsB, 'matrixB');
// Populate matrices from the newly created inputs
matrixA = populateMatrixFromInputs('matrixA', rowsA, colsA);
matrixB = populateMatrixFromInputs('matrixB', rowsB, colsB);
var results = {};
var formula = "";
var mainResultText = "";
var chartData = { labels: [], series: [[], []] }; // Default chart data structure
if (operation === 'add') {
formula = "Cij = Aij + Bij";
setFormulaText("For matrices A and B of the same dimensions, the resulting matrix C has elements Cij = Aij + Bij.");
resultMatrix = [];
for (var i = 0; i < rowsA; i++) {
resultMatrix[i] = [];
for (var j = 0; j < colsA; j++) {
resultMatrix[i][j] = matrixA[i][j] + matrixB[i][j];
}
}
mainResultText = "Resulting Matrix (A + B)";
chartData = prepareChartDataForAddition(matrixA, matrixB, resultMatrix);
} else if (operation === 'subtract') {
formula = "Cij = Aij – Bij";
setFormulaText("For matrices A and B of the same dimensions, the resulting matrix C has elements Cij = Aij – Bij.");
resultMatrix = [];
for (var i = 0; i < rowsA; i++) {
resultMatrix[i] = [];
for (var j = 0; j < colsA; j++) {
resultMatrix[i][j] = matrixA[i][j] – matrixB[i][j];
}
}
mainResultText = "Resulting Matrix (A – B)";
chartData = prepareChartDataForSubtraction(matrixA, matrixB, resultMatrix);
} else if (operation === 'multiply') {
formula = "Cij = Σ (Aik * Bkj)";
setFormulaText("For matrix A (m x n) and matrix B (n x p), the resulting matrix C (m x p) has elements Cij calculated by the dot product of row i of A and column j of B.");
var resultRows = rowsA;
var resultCols = colsB;
resultMatrix = [];
for (var i = 0; i < resultRows; i++) {
resultMatrix[i] = [];
for (var j = 0; j < resultCols; j++) {
var sum = 0;
for (var k = 0; k < colsA; k++) {
sum += matrixA[i][k] * matrixB[k][j];
}
resultMatrix[i][j] = sum;
}
}
mainResultText = "Resulting Matrix (A * B)";
chartData = prepareChartDataForMultiplication(matrixA, matrixB, resultMatrix);
} else if (operation === 'transposeA') {
formula = "(A^T)ij = Aji";
setFormulaText("The transpose of matrix A (m x n) is a matrix A^T (n x m) where elements are swapped: (A^T)ij = Aji.");
resultMatrix = [];
for (var i = 0; i < colsA; i++) {
resultMatrix[i] = [];
for (var j = 0; j < rowsA; j++) {
resultMatrix[i][j] = matrixA[j][i];
}
}
mainResultText = "Transpose of Matrix A (A^T)";
// Transpose chart might compare original vs transposed elements
chartData = prepareChartDataForTranspose(matrixA, resultMatrix);
} else if (operation === 'transposeB') {
formula = "(B^T)ij = Bji";
setFormulaText("The transpose of matrix B (m x n) is a matrix B^T (n x m) where elements are swapped: (B^T)ij = Bji.");
resultMatrix = [];
for (var i = 0; i < colsB; i++) {
resultMatrix[i] = [];
for (var j = 0; j < rowsB; j++) {
resultMatrix[i][j] = matrixB[j][i];
}
}
mainResultText = "Transpose of Matrix B (B^T)";
chartData = prepareChartDataForTranspose(matrixB, resultMatrix);
} else if (operation === 'determinantA') {
formula = "det(A)";
setFormulaText("The determinant is a scalar value calculated from a square matrix. For 2×2: ad-bc. For larger matrices, cofactor expansion or row reduction is used.");
var det = calculateDeterminant(matrixA);
resultMatrix = []; // Determinant is a scalar, not a matrix
results['Determinant of A'] = det;
mainResultText = "Determinant of Matrix A";
document.getElementById('primary-result').style.display = 'block'; // Show primary result for scalar
document.getElementById('intermediate-results').innerHTML = ''; // Clear intermediate results if any
updateTableAndChart([], [], "Determinant Calculation"); // Clear matrix display
updateChart([], [], "Determinant Value", det); // Update chart for scalar value
return; // Exit early for scalar result
} else if (operation === 'determinantB') {
formula = "det(B)";
setFormulaText("The determinant is a scalar value calculated from a square matrix. For 2×2: ad-bc. For larger matrices, cofactor expansion or row reduction is used.");
var det = calculateDeterminant(matrixB);
resultMatrix = []; // Determinant is a scalar
results['Determinant of B'] = det;
mainResultText = "Determinant of Matrix B";
document.getElementById('primary-result').style.display = 'block';
document.getElementById('intermediate-results').innerHTML = '';
updateTableAndChart([], [], "Determinant Calculation");
updateChart([], [], "Determinant Value", det);
return; // Exit early for scalar result
}
// Display results
document.getElementById('main-result-value').innerText = mainResultText;
displayMatrix(resultMatrix, 'results-container'); // Display the resulting matrix
displayIntermediateResults(results);
updateTableAndChart(matrixA, matrixB, operation);
updateChart(chartData.labels, chartData.series, operation, null); // Pass null for scalar value
}
// Helper function to calculate determinant recursively
function calculateDeterminant(matrix) {
var n = matrix.length;
if (n === 1) {
return matrix[0][0];
}
if (n === 2) {
return matrix[0][0] * matrix[1][1] – matrix[0][1] * matrix[1][0];
}
var det = 0;
for (var j = 0; j < n; j++) {
var subMatrix = [];
for (var i = 1; i < n; i++) {
subMatrix[i – 1] = [];
for (var k = 0; k 0 && series[0].length > 0) {
// Chart for matrix operations
var datasets = [];
var colors = ['rgba(0, 74, 153, 0.7)', 'rgba(40, 167, 69, 0.7)'];
var borderColors = ['rgba(0, 74, 153, 1)', 'rgba(40, 167, 69, 1)'];
for (var i = 0; i < series.length; i++) {
datasets.push({
label: 'Series ' + (i + 1),
data: series[i],
backgroundColor: colors[i % colors.length],
borderColor: borderColors[i % borderColors.length],
borderWidth: 1
});
}
chartInstance = new Chart(ctx, {
type: 'bar', // Default to bar chart, can be changed
data: {
labels: labels,
datasets: datasets
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
title: {
display: true,
text: 'Matrix Operation Visualization: ' + operationName
},
legend: {
position: 'top',
}
},
scales: {
y: {
beginAtZero: true
}
}
}
});
document.getElementById('chart-caption').innerText = 'Bar chart comparing elements or results for ' + operationName + '.';
} else {
document.getElementById('chart-caption').innerText = 'No data available for chart.';
}
}
// Chart Data Preparation Functions
function prepareChartDataForAddition(matA, matB, matC) {
var labels = [];
var series = [[], [], []]; // A, B, C
var maxDim = Math.max(matA.length, matA[0].length);
for (var i = 0; i < matA.length; i++) {
for (var j = 0; j < matA[i].length; j++) {
var label = 'A' + (i + 1) + ',' + (j + 1);
labels.push(label);
series[0].push(matA[i][j]);
series[1].push(matB[i][j]);
series[2].push(matC[i][j]);
}
}
return { labels: labels, series: series };
}
function prepareChartDataForSubtraction(matA, matB, matC) {
var labels = [];
var series = [[], [], []]; // A, B, C (Difference)
var maxDim = Math.max(matA.length, matA[0].length);
for (var i = 0; i < matA.length; i++) {
for (var j = 0; j < matA[i].length; j++) {
var label = 'A' + (i + 1) + ',' + (j + 1);
labels.push(label);
series[0].push(matA[i][j]);
series[1].push(matB[i][j]);
series[2].push(matC[i][j]); // C is A-B
}
}
return { labels: labels, series: series };
}
function prepareChartDataForMultiplication(matA, matB, matC) {
var labels = [];
var series = [[], []]; // Can represent rows of A vs columns of B, or elements of C
// For simplicity, let's show elements of the resulting matrix C
for (var i = 0; i < matC.length; i++) {
for (var j = 0; j < matC[i].length; j++) {
var label = 'C' + (i + 1) + ',' + (j + 1);
labels.push(label);
series[0].push(matC[i][j]);
}
}
// If we want to show A and B contributions, it gets complex.
// Let's stick to showing the result matrix C for now.
return { labels: labels, series: [series[0]] }; // Only one series for result matrix C
}
function prepareChartDataForTranspose(originalMat, transposedMat) {
var labels = [];
var series = [[], []]; // Original, Transposed
var maxDim = Math.max(originalMat.length, originalMat[0].length);
for (var i = 0; i < originalMat.length; i++) {
for (var j = 0; j < originalMat[i].length; j++) {
var label = 'Orig' + (i + 1) + ',' + (j + 1);
labels.push(label);
series[0].push(originalMat[i][j]);
}
}
for (var i = 0; i < transposedMat.length; i++) {
for (var j = 0; j < transposedMat[i].length; j++) {
// Use transposed indices for labels if needed, or reuse original labels
var label = 'Trans' + (i + 1) + ',' + (j + 1);
// Ensure labels align if dimensions change significantly
if (i < labels.length) labels[i] = label; // Overwrite if possible
series[1].push(transposedMat[i][j]);
}
}
// Adjust labels if dimensions differ greatly
if (transposedMat.length !== originalMat.length || transposedMat[0].length !== originalMat[0].length) {
labels = [];
for (var i = 0; i < transposedMat.length; i++) {
for (var j = 0; j 0) {
tableA_dims.innerText = matA.length + 'x' + matA[0].length;
tableA_elements.innerText = JSON.stringify(matA);
} else {
tableA_dims.innerText = 'N/A';
tableA_elements.innerText = 'N/A';
}
if (matB && matB.length > 0) {
tableB_dims.innerText = matB.length + 'x' + matB[0].length;
tableB_elements.innerText = JSON.stringify(matB);
} else {
tableB_dims.innerText = 'N/A';
tableB_elements.innerText = 'N/A';
}
}
function resetCalculator() {
document.getElementById('matrixA_rows').value = 2;
document.getElementById('matrixA_cols').value = 2;
document.getElementById('matrixB_rows').value = 2;
document.getElementById('matrixB_cols').value = 2;
document.getElementById('operation').value = 'add';
// Clear error messages
document.getElementById('matrixA_rows_error').innerText = ";
document.getElementById('matrixA_cols_error').innerText = ";
document.getElementById('matrixB_rows_error').innerText = ";
document.getElementById('matrixB_cols_error').innerText = ";
// Recreate inputs and clear matrices
matrixA = createMatrixInputs(2, 2, 'matrixA');
matrixB = createMatrixInputs(2, 2, 'matrixB');
resultMatrix = [];
document.getElementById('main-result-value').innerText = 'N/A';
document.getElementById('intermediate-results').innerHTML = ";
document.getElementById('formula-text').innerText = 'Select an operation and input matrix dimensions to see the formula.';
updateTableAndChart([], [], "Reset");
// Clear chart
if (chartInstance) {
chartInstance.destroy();
chartInstance = null;
}
document.getElementById('matrixChart').getContext('2d').clearRect(0, 0, canvas.width, canvas.height);
document.getElementById('chart-caption').innerText = 'Chart will appear after calculation.';
}
function copyResults() {
var mainResult = document.getElementById('main-result-value').innerText;
var intermediateResults = document.getElementById('intermediate-results').innerText;
var formula = document.getElementById('formula-text').innerText;
var matrixAText = document.getElementById('tableA_elements').innerText;
var matrixBText = document.getElementById('tableB_elements').innerText;
var resultMatrixText = "N/A";
if (resultMatrix && resultMatrix.length > 0) {
resultMatrixText = JSON.stringify(resultMatrix);
} else if (document.getElementById('main-result-value').innerText.includes("Determinant")) {
resultMatrixText = document.getElementById('main-result-value').innerText.split(': ')[1]; // Extract scalar value
}
var textToCopy = "— Matriz Calculator Results —\n\n";
textToCopy += "Operation: " + document.getElementById('operation').value + "\n";
textToCopy += "Matrix A: " + matrixAText + "\n";
textToCopy += "Matrix B: " + matrixBText + "\n\n";
textToCopy += "Main Result: " + mainResult + "\n";
if (resultMatrixText !== "N/A") {
textToCopy += "Result Matrix/Value: " + resultMatrixText + "\n";
}
textToCopy += "Intermediate Values:\n" + intermediateResults.replace(/:\s*/g, ': ') + "\n\n"; // Format intermediate results better
textToCopy += "Formula Used: " + formula + "\n";
// Use a temporary textarea for copying
var textArea = document.createElement("textarea");
textArea.value = textToCopy;
textArea.style.position = "fixed";
textArea.style.left = "-9999px";
document.body.appendChild(textArea);
textArea.focus();
textArea.select();
try {
var successful = document.execCommand('copy');
var msg = successful ? 'Results copied to clipboard!' : 'Failed to copy results.';
// Optionally show a temporary message to the user
alert(msg);
} catch (err) {
alert('Failed to copy results. Please copy manually.');
}
document.body.removeChild(textArea);
}
// Initial setup
document.addEventListener('DOMContentLoaded', function() {
// Load initial matrix inputs based on default values
var initialRowsA = parseInt(document.getElementById('matrixA_rows').value);
var initialColsA = parseInt(document.getElementById('matrixA_cols').value);
var initialRowsB = parseInt(document.getElementById('matrixB_rows').value);
var initialColsB = parseInt(document.getElementById('matrixB_cols').value);
matrixA = createMatrixInputs(initialRowsA, initialColsA, 'matrixA');
matrixB = createMatrixInputs(initialRowsB, initialColsB, 'matrixB');
// Populate matrices with initial values from inputs
matrixA = populateMatrixFromInputs('matrixA', initialRowsA, initialColsA);
matrixB = populateMatrixFromInputs('matrixB', initialRowsB, initialColsB);
// Set initial table and chart captions
document.getElementById('chart-caption').innerText = 'Chart will appear after calculation.';
updateTableAndChart(matrixA, matrixB, "Initial Load");
// Add event listeners for dimension changes to update inputs dynamically
document.getElementById('matrixA_rows').addEventListener('change', function() { updateMatrixInputsDynamically('matrixA'); });
document.getElementById('matrixA_cols').addEventListener('change', function() { updateMatrixInputsDynamically('matrixA'); });
document.getElementById('matrixB_rows').addEventListener('change', function() { updateMatrixInputsDynamically('matrixB'); });
document.getElementById('matrixB_cols').addEventListener('change', function() { updateMatrixInputsDynamically('matrixB'); });
// Add event listener for operation change to potentially update visibility or validation logic
document.getElementById('operation').addEventListener('change', function() {
validateInputs(); // Re-validate when operation changes
});
});
function updateMatrixInputsDynamically(matrixId) {
var rows = parseInt(document.getElementById(matrixId + '_rows').value);
var cols = parseInt(document.getElementById(matrixId + '_cols').value);
// Validate dimensions before creating inputs
if (isNaN(rows) || rows 10 || isNaN(cols) || cols 10) {
// Errors are handled by validateInputs, just prevent creation
return;
}
var currentMatrix = createMatrixInputs(rows, cols, matrixId);
// Try to preserve existing values if possible
var prevMatrix = (matrixId === 'matrixA') ? matrixA : matrixB;
if (prevMatrix && prevMatrix.length > 0) {
for (var i = 0; i < rows; i++) {
for (var j = 0; j < cols; j++) {
if (i < prevMatrix.length && j < prevMatrix[i].length) {
currentMatrix[i][j] = prevMatrix[i][j];
document.getElementById(matrixId + '_r' + i + '_c' + j).value = prevMatrix[i][j];
}
}
}
}
// Update the global matrix variable
if (matrixId === 'matrixA') matrixA = currentMatrix;
else matrixB = currentMatrix;
// Update table display
updateTableAndChart(matrixA, matrixB, "Dimension Change");
}
// — Chart.js Integration —
// Ensure Chart.js is loaded. In a real WordPress setup, you'd enqueue this script.
// For this single HTML file, we assume it's available or include it via CDN.
// For this example, we'll assume Chart.js is loaded via CDN in the or before this script.
// If not, you'd need to add:
// Placeholder for Chart.js library if not included externally
if (typeof Chart === 'undefined') {
console.error("Chart.js library not found. Please include it via CDN or enqueue it.");
// You might want to disable the chart section or show a message
}