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Our current format for sending messages over UDP via classifier or regressor is not standardized. For example, the use of proportional control and/or probabilities drastically changes the format of our output message. This makes it difficult to create uniform methods for parsing this information. It would be just as easy to always send this info, but have some constant (e.g., -1000) that we send to signify that this option is disabled. If this gets fixed we can make the following improvements:
Remove num_classes parameters from ClassifierController
Potentially replace multiprocessing.Value string with multiprocessing.Value ints for each desired value (e.g., prediction, proportional control, etc.), which would be much more ideal. This may not be needed if we're happy with the performance we're getting currently.
Potentially remove output_format parameter from EMGClassifier and ClassifierController.
Our current format for sending messages over UDP via classifier or regressor is not standardized. For example, the use of proportional control and/or probabilities drastically changes the format of our output message. This makes it difficult to create uniform methods for parsing this information. It would be just as easy to always send this info, but have some constant (e.g., -1000) that we send to signify that this option is disabled. If this gets fixed we can make the following improvements:
num_classesparameters fromClassifierControllermultiprocessing.Valuestring withmultiprocessing.Valueints for each desired value (e.g., prediction, proportional control, etc.), which would be much more ideal. This may not be needed if we're happy with the performance we're getting currently.output_formatparameter fromEMGClassifierandClassifierController.SocketControllerto use shared memory instead ofmultiprocessing.Value(see SocketController Shared Memory #91)