python
from nupic.frameworks.opf.modelfactory import ModelFactory
from nupic.encoders import MultiEncoder
model_factory = ModelFactory(verbosity=0)
encoder = MultiEncoder()
encoder.addEncoder("position", position_encoder)
encoder.addEncoder("velocity", velocity_encoder)
model_params = {"inferenceType": "TemporalAnomaly",
"sensorParams": {
"timestampFieldName": "timestamp",
"encoders": {
"position": "position",
"velocity": "velocity"
}
},
"spEnable": True}
model = model_factory.create(model_params)
dataset = load_dataset("walking_patterns.csv")
model.enableInference({"predictedField": "position"})
for record in dataset:
result = model.run(record)
print("Anomaly score:", result.inferences["anomalyScore"])
future_data = generate_future_data()
for record in future_data:
result = model.run(record)
print("Predicted position:", result.inferences["multiStepBestPredictions"])
