Augmented Matrices Calculator

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Augmented Matrix Calculator

Enter the coefficients of your system of linear equations to form an augmented matrix and see its row-echelon form.

Matrix Dimensions

Matrix Coefficients

Result: Row-Echelon Form (Reduced)

Enter dimensions and coefficients above.

Understanding Augmented Matrices and Row-Echelon Form

An augmented matrix is a matrix formed by adding the columns of coefficients from a system of linear equations and the constant terms on the right-hand side of the equations. It's a compact way to represent a system of equations, making it easier to solve using matrix operations.

For a system of equations like:

a₁₁x₁ + a₁₂x₂ + ... + a₁nxn = b₁
a₂₁x₁ + a₂₂x₂ + ... + a₂nxn = b₂
...
am₁x₁ + am₂x₂ + ... + amnxn = bm

The corresponding augmented matrix is:

[ A | B ] =

[[a₁₁, a₁₂, ..., a₁n | b₁], [a₂₁, a₂₂, ..., a₂n | b₂], ..., [am₁, am₂, ..., amn | bm]]

Where A is the coefficient matrix and B is the column vector of constants.

Row-Echelon Form (REF) and Reduced Row-Echelon Form (RREF)

The goal of using an augmented matrix is often to solve the system. This is achieved by transforming the matrix into its Row-Echelon Form (REF) or, more commonly, Reduced Row-Echelon Form (RREF) using elementary row operations. These operations include:

  • Swapping two rows.
  • Multiplying a row by a non-zero scalar.
  • Adding a multiple of one row to another row.

A matrix is in RREF if it satisfies the following conditions:

  • All zero rows are at the bottom of the matrix.
  • The first non-zero entry (leading entry or pivot) in each non-zero row is 1.
  • Each leading 1 is the only non-zero entry in its column.
  • The leading 1 in any row is to the right of the leading 1 in the row above it.

How this Calculator Works

This calculator takes the dimensions of your augmented matrix (number of equations and number of coefficients + constants) and then allows you to input the individual elements. It then applies Gaussian elimination and back-substitution (or Gauss-Jordan elimination) using elementary row operations to transform the matrix into its Reduced Row-Echelon Form (RREF). The output displays this RREF matrix.

Use Cases

  • Solving systems of linear equations.
  • Determining if a system has a unique solution, no solution, or infinitely many solutions.
  • Finding the inverse of a matrix (by augmenting with an identity matrix).
  • Calculating the rank of a matrix.
  • Working with linear algebra concepts in various fields like engineering, physics, computer graphics, and economics.
// Function to generate input fields for the matrix function generateMatrixInputs() { var numRows = parseInt(document.getElementById("rows").value); var numCols = parseInt(document.getElementById("cols").value); var matrixInputsDiv = document.getElementById("matrix-inputs"); matrixInputsDiv.innerHTML = "; // Clear previous inputs if (isNaN(numRows) || isNaN(numCols) || numRows < 1 || numCols 10 || numCols > 11) { document.getElementById("error-message").innerText = "Please enter valid dimensions (Rows: 1-10, Columns: 2-11)."; return; } document.getElementById("error-message").innerText = ""; // Clear error message var table = document.createElement('table'); table.style.width = '100%'; table.style.borderCollapse = 'collapse'; for (var i = 0; i < numRows; i++) { var row = table.insertRow(); for (var j = 0; j < numCols; j++) { var cell = row.insertCell(); var input = document.createElement('input'); input.type = 'number'; input.step = 'any'; // Allow decimals input.className = 'matrix-element'; input.setAttribute('data-row', i); input.setAttribute('data-col', j); input.placeholder = 'a' + (i + 1) + (j + 1); input.style.width = '95%'; // Adjust width to fit cell padding input.style.padding = '8px'; input.style.margin = '2px'; input.style.border = '1px solid #ddd'; input.style.borderRadius = '4px'; input.style.textAlign = 'center'; // Add separator line visually if (j === numCols – 2) { input.style.borderRight = '2px solid #004a99'; input.style.marginRight = '5px'; } cell.appendChild(input); } cell.style.paddingRight = '10px'; // Add padding to separate last column } matrixInputsDiv.appendChild(table); } // Function to get the matrix from input fields function getMatrixFromInputs() { var numRows = parseInt(document.getElementById("rows").value); var numCols = parseInt(document.getElementById("cols").value); var matrix = []; for (var i = 0; i < numRows; i++) { matrix[i] = []; for (var j = 0; j < numCols; j++) { var input = document.querySelector('input[data-row="' + i + '"][data-col="' + j + '"]'); var value = parseFloat(input.value); // Handle empty inputs as 0, but check for NaN after parseFloat if (isNaN(value)) { matrix[i][j] = 0; } else { matrix[i][j] = value; } } } return matrix; } // Function to display the matrix in the result area function displayMatrix(matrix, elementId) { var resultDiv = document.getElementById(elementId); var numRows = matrix.length; if (numRows === 0) { resultDiv.innerHTML = 'Matrix is empty.'; return; } var numCols = matrix[0].length; var table = document.createElement('table'); table.style.width = '100%'; table.style.borderCollapse = 'collapse'; table.style.margin = '10px auto'; for (var i = 0; i < numRows; i++) { var row = table.insertRow(); for (var j = 0; j < numCols; j++) { var cell = row.insertCell(); var value = matrix[i][j]; // Format numbers for better readability, especially small/large numbers if (Math.abs(value) < 1e-9) { // Treat very small numbers as zero value = 0; } else { value = parseFloat(value.toFixed(6)); // Limit decimal places } cell.textContent = value; cell.style.padding = '10px'; cell.style.border = '1px solid #eee'; cell.style.textAlign = 'center'; if (j === numCols – 2) { cell.style.borderRight = '2px solid #004a99'; } } } resultDiv.innerHTML = ''; // Clear previous content resultDiv.appendChild(table); } // Gauss-Jordan Elimination to find RREF function calculateRREF() { var errorMessageDiv = document.getElementById("error-message"); errorMessageDiv.innerText = ""; // Clear previous errors var resultDiv = document.getElementById("result"); resultDiv.innerHTML = 'Calculating…'; var numRows = parseInt(document.getElementById("rows").value); var numCols = parseInt(document.getElementById("cols").value); if (isNaN(numRows) || isNaN(numCols) || numRows < 1 || numCols 10 || numCols > 11) { errorMessageDiv.innerText = "Invalid dimensions. Rows: 1-10, Columns: 2-11."; resultDiv.innerHTML = 'Enter dimensions and coefficients.'; return; } var matrix = getMatrixFromInputs(); var epsilon = 1e-10; // Tolerance for floating point comparisons var lead = 0; // Current pivot column for (var r = 0; r = numCols) { break; } var i = r; // Find a row with a non-zero entry in the current pivot column while (Math.abs(matrix[i][lead]) < epsilon) { i++; if (i === numRows) { // Reached end of rows for this column i = r; lead++; if (lead === numCols) { // Reached end of columns, break outer loop lead = -1; // Sentinel value to indicate completion break; } } } if (lead === -1) break; // Exit outer loop if all columns processed // Swap rows if necessary to bring the pivot element to the current row var temp = matrix[i]; matrix[i] = matrix[r]; matrix[r] = temp; // Normalize the pivot row (make the pivot element 1) var pivotValue = matrix[r][lead]; for (var j = 0; j < numCols; j++) { matrix[r][j] /= pivotValue; } // Eliminate other entries in the pivot column for (var i = 0; i < numRows; i++) { if (i !== r) { var factor = matrix[i][lead]; for (var j = 0; j < numCols; j++) { matrix[i][j] -= factor * matrix[r][j]; } } } lead++; // Move to the next column for the next pivot } // Clean up near-zero values to improve display for (var r = 0; r < numRows; r++) { for (var c = 0; c < numCols; c++) { if (Math.abs(matrix[r][c]) < epsilon) { matrix[r][c] = 0; } } } displayMatrix(matrix, "result"); } // Initial generation of matrix inputs on page load window.onload = generateMatrixInputs;

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