Analytical Thinking Calculator

Please define at least one Option and one Criterion in the input tab.

'; return; } // 2. Build Table Header let tableHtml = ''; tableHtml += ''; criteria.forEach(crit => { tableHtml += ``; }); tableHtml += ''; // 3. Build Table Body with Input Fields options.forEach(opt => { tableHtml += ``; criteria.forEach(crit => { // Use unique IDs for each cell input: optId_critId const inputId = `${opt.id}_${crit.id}`; tableHtml += ``; }); tableHtml += ''; }); tableHtml += '

Option / Criterion (Weight)	${crit.name} (${crit.weight})
${opt.name}

'; matrixContainer.innerHTML = tableHtml; // 4. Navigate (if requested) if (shouldNavigate) { const scoringButton = document.querySelector('.tab-button[onclick*="scoring-tab"]'); if (scoringButton) { showTab('scoring-tab', scoringButton); } } } /** * Performs the core analytical calculation: Weighted Score = (Criterion Score / 10) * Weight * Note: Lower scores are better for 'cost' type criteria, which requires score inversion. */ function calculateMatrix() { // 1. Validate Scoring Matrix existence const matrixEl = document.getElementById('input-matrix'); if (!matrixEl) { alert("Please generate the scoring matrix first by configuring options and criteria."); return; } let results = []; let totalMaxScore = 0; // Maximum possible weighted score (for normalization if needed) // Calculate total max score for context (10 points * weight) criteria.forEach(crit => { totalMaxScore += crit.weight * 10; }); // 2. Iterate through Options (Rows) options.forEach(opt => { let totalWeightedScore = 0; let detailedScores = {}; let missingScores = false; // 3. Iterate through Criteria (Columns) criteria.forEach(crit => { const inputId = `${opt.id}_${crit.id}`; const inputEl = document.getElementById(inputId); if (!inputEl) { console.warn(`Input element missing for ${inputId}`); missingScores = true; return; } const rawValue = inputEl.value.trim().toUpperCase(); let score; let weightedScore = 0; if (rawValue === '' || rawValue === 'N/A') { score = 'N/A'; } else { score = parseFloat(rawValue); if (isNaN(score) || score < 1 || score > 10) { alert(`Invalid score for ${opt.name} / ${crit.name}. Must be 1-10 or N/A.`); missingScores = true; return; } // Analytical Inversion for 'Cost' Type Criteria (Lower score is better) let normalizedScore; if (crit.type === 'cost') { // Invert score: 10 is best, 1 is worst. New Score = 11 - Old Score. normalizedScore = 11 - score; } else { // Benefit: Higher score is better normalizedScore = score; } // Weighted Score Calculation weightedScore = normalizedScore * crit.weight; totalWeightedScore += weightedScore; } detailedScores[crit.id] = { rawScore: rawValue, weightedScore: weightedScore }; }); if (!missingScores) { results.push({ optionId: opt.id, optionName: opt.name, totalWeightedScore: totalWeightedScore, detailedScores: detailedScores }); } }); if (results.length === options.length) { // 4. Sort and Rank (Highest score is Rank 1) results.sort((a, b) => b.totalWeightedScore - a.totalWeightedScore); // 5. Render Dashboard renderRanking(results); renderDetailedMatrix(results, totalMaxScore); // 6. Navigate to Dashboard Tab calculateMatrixAndNavigate(); } } /** * Renders the final ranking list on the dashboard. */ function renderRanking(results) { const container = document.getElementById('ranking-container'); if (!container) return; let html = ''; results.forEach((res, index) => { const rankClass = index === 0 ? 'rank-1' : ''; html += ` `; }); container.innerHTML = html; } /** * Renders the detailed weighted matrix table. */ function renderDetailedMatrix(results, totalMaxScore) { const container = document.getElementById('detailed-matrix-container'); if (!container) return; let tableHtml = ''; tableHtml += ''; criteria.forEach(crit => { const typeLabel = crit.type === 'cost' ? ' (Cost/Inv)' : ' (Benefit)'; tableHtml += ``; }); tableHtml += ''; // Data Rows results.forEach((res) => { tableHtml += ``; let totalScoreDisplay = 0; criteria.forEach(crit => { const scoreData = res.detailedScores[crit.id]; let displayValue = 'N/A'; if (scoreData.rawScore !== 'N/A') { displayValue = `${scoreData.rawScore} * ${crit.weight} = ${scoreData.weightedScore.toFixed(0)}`; totalScoreDisplay += scoreData.weightedScore; } tableHtml += ``; }); // Total Weighted Score column tableHtml += ``; tableHtml += ''; }); // Total Weight Row (Footer) const totalWeight = criteria.reduce((sum, crit) => sum + crit.weight, 0); tableHtml += ``; tableHtml += '

Option / Criterion	${crit.name} Weight: ${crit.weight}${typeLabel}	Total Weighted Score
${res.optionName}	${displayValue}	${totalScoreDisplay.toFixed(0)}
Total Weights Sum:	${totalWeight}

'; container.innerHTML = tableHtml; } /** * Generates and downloads the PDF report of the Decision Matrix. (II.C) */ function downloadMatrixPdf() { // 1. Ensure Dashboard is active for print formatting const dashboardButton = document.querySelector('.tab-button[onclick*="dashboard-tab"]'); if (dashboardButton) { showTab('dashboard-tab', dashboardButton); } // 2. Set temporary title for PDF file name/header const originalTitle = document.title; document.title = `Analytical Decision Matrix Report - ${new Date().toLocaleDateString('en-US')}`; // 3. Trigger the browser's print/PDF dialog window.print(); // 4. Restore the original title after printing setTimeout(() => { document.title = originalTitle; }, 10); }