Tabular Data Processing

uses System.Data.Tabular;

// 1. Create a dataset representing sensor readings or predictions
var data := new TabularData;
data.AddColumn('Timestamp', [1000, 1010, 1020, 1030, 1040]);
data.AddColumn('Signal', [0.5, -1.2, 3.4, 2.1, -0.8]);
data.AddColumn('Actual', [0.6, 0.1, 3.0, 2.5, 0.1]);

PrintLn('<h3>Raw Sensor Data</h3>');
PrintLn(data.ExportToSeparated(['Timestamp', 'Signal', 'Actual']).Replace(#10, '<br>'));

// 2. Data Normalization (Min-Max Scaling)
// Calculate range metrics manually (as 'min'/'max' aggregates are not in this binary)
var signalVals := data.Evaluate(['"Signal"']);
var sMin := signalVals[0];
var sMax := signalVals[0];
for var v in signalVals do begin
   if v < sMin then sMin := v;
   if v > sMax then sMax := v;
end;
var sRange := sMax - sMin;

// Scale Signal to [0, 1] range: (Signal - Min) / Range
data.EvaluateNewColumn('Normalized', [ '"Signal"', sMin, '-', sRange, '/' ]);

// 3. Simple Linear Model + ReLU Activation
// Simulate a prediction: (Signal * 1.5) + 0.5, clamped to positive values via 'relu'
// In this engine, 'relu' is a fused binary operator that performs max(0, a + b)
data.EvaluateNewColumn('Prediction', [ '"Signal"', 1.5, '*', 0.5, 'relu' ]);

// 4. Error Analysis (SMAPE component)
// 'smape' opcode calculates abs(a-b) / (abs(a)+abs(b)) for each row
data.EvaluateNewColumn('ErrorRate', [ '"Prediction"', '"Actual"', 'smape' ]);

PrintLn('<h4>Processed Features & Predictions</h4>');
PrintLn(data.ExportToSeparated(['Timestamp', 'Normalized', 'Prediction', 'ErrorRate']).Replace(#10, '<br>'));

// 5. Aggregate Metrics
var avgError := data.EvaluateAggregate('sum', [ '"ErrorRate"' ]) / 5;

PrintLn('<h4>Summary Metrics</h4>');
PrintLn('<b>Mean SMAPE Error:</b> ' + Float(avgError).ToString(4));
PrintLn('<b>Peak Signal:</b> ' + Float(sMax).ToString(2));

// Note: While this example uses 5 rows for readability, TabularData 
// is designed to process millions of rows using these same JIT expressions.
try
   data.LockAndShare('GlobalAnalyticsCache');
except
   // Might already be shared
end;