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data_generator.py

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+import numpy as np
+import pandas as pd
+
+def generate_multivariate_timeseries(n_samples=1500, n_features=5):
+    time = np.arange(n_samples)
+
+    data = {}
+    for i in range(n_features):
+        data[f"feature_{i+1}"] = (
+            np.sin(0.02 * time + i) +
+            np.cos(0.01 * time) +
+            np.random.normal(0, 0.1, n_samples)
+        )
+
+    df = pd.DataFrame(data)
+    df["target"] = (
+        df["feature_1"] * 0.4 +
+        df["feature_2"] * 0.3 +
+        df["feature_3"] * 0.2 +
+        np.random.normal(0, 0.05, n_samples)
+    )
+    return df
+
+if __name__ == "__main__":
+    df = generate_multivariate_timeseries()
+    df.to_csv("data.csv", index=False)
+    print("Data generated and saved as data.csv")