Forecasted ${aibefm_model.baselineMetric}: $${forecastedValue.toFixed(2)} (${(percentageChange >=0 ? '+': '')}${percentageChange.toFixed(2)}%)

Baseline ${aibefm_model.baselineMetric}: $${aibefm_model.baselineValue.toFixed(2)}

`; contributionsList.innerHTML = ''; factorContributions.sort((a,b) => Math.abs(b.contribution) - Math.abs(a.contribution)); // Sort by magnitude factorContributions.forEach(c => { const item = document.createElement('div'); item.className = 'aibefm_factor_contribution_item'; item.innerHTML = `${c.name}: ${(c.contribution >=0 ? '+': '')}${c.contribution.toFixed(2)} pp`; contributionsList.appendChild(item); }); contributionsDiv.style.display = 'block'; document.getElementById('aibefm_downloadPdfButton').style.display = 'block'; } function aibefm_collectModelSetup() { aibefm_model.companyName = aibefm_getInputValue('aibefm_companyName'); aibefm_model.sector = aibefm_getInputValue('aibefm_sector'); aibefm_model.baselineMetric = aibefm_getInputValue('aibefm_baselineMetric'); aibefm_model.baselineValue = aibefm_getInputNumValue('aibefm_baselineValue', 0); aibefm_model.forecastPeriod = aibefm_getInputValue('aibefm_forecastPeriod'); // Factors are updated directly via their oninput events } // --- PDF Generation --- function aibefm_downloadPDF() { if (!aibefm_forecastOutput) { alert("Please generate a forecast first."); return; } if (typeof window.jspdf === 'undefined' || typeof window.jspdf.jsPDF === 'undefined') { alert('PDF library (jsPDF) is not loaded.'); return; } const { jsPDF: JSPDF } = window.jspdf; const doc = new JSPDF(); let y = 15; const m = 15; const cw = doc.internal.pageSize.getWidth() - (2 * m); const data = aibefm_forecastOutput; function addLine(text, size, style = 'normal', indent = 0, spacing = 2.5) { if (y > 270) { doc.addPage(); y = m; } doc.setFontSize(size); doc.setFont(undefined, style); const lines = doc.splitTextToSize(text, cw - indent); doc.text(lines, m + indent, y); y += (lines.length * (size * 0.35)) + spacing; } addLine(`Earnings Forecast: ${data.companyName || 'N/A'}`, 18, 'bold', 0, 5); addLine(`Sector: ${data.sector}, Period: ${data.forecastPeriod}`, 10); addLine(`Baseline ${data.baselineMetric}: $${data.baselineValue.toFixed(2)}`, 10); addLine(`Forecasted ${data.baselineMetric}: $${data.forecastedValue.toFixed(2)} (${(data.percentageChange >=0 ? '+': '')}${data.percentageChange.toFixed(2)}%)`, 12, 'bold', 0, 6); addLine("Influencing Factors & Settings:", 14, 'bold', 0, 4); data.factors.forEach(f => { let factorDesc = `- ${f.name || 'Unnamed'}: Type: ${f.type}, Impact: ${f.impactDirection}, Weight (Max Contrib.): ${f.weight}%`; if(f.type === 'numerical') factorDesc += `, Range: ${f.scaleMin}-${f.scaleMax}`; if(f.type === 'categorical') factorDesc += `, Cats: ${(f.categories||[]).join('/')}`; if(f.type === 'percentage') factorDesc += `, Input as % points`; factorDesc += `, Forecast Input Value: ${f.currentValue === null || f.currentValue === undefined ? 'N/A' : f.currentValue} ${f.unit || ''}`; addLine(factorDesc, 9, 'normal', 5, 1.5); }); y += 3; addLine("Factor Contributions to Forecast Change:", 14, 'bold', 0, 4); data.factorContributions.forEach(c => { addLine(`- ${c.name}: ${(c.contribution >=0 ? '+': '')}${c.contribution.toFixed(2)} percentage points`, 10, 'normal', 5, 2); }); addLine(`Note: This is a simulated forecast based on user-defined parameters. Max total impact from factors capped at +/-${aibefm_model.maxTotalImpactFromFactors}%.`, 8, 'italic', 0, 5); doc.save(`${(data.companyName || 'forecast').replace(/\s+/g, '_')}_earnings_forecast.pdf`); }