The On-board Artificial Intelligence Research (OnAIR) Platform is a framework that enables AI algorithms written in Python to interact with NASA's cFS. It is intended to explore research concepts in autonomous operations in a simulated environment.
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Improve ease-of-use for Telemetry Metadata file #108
Currently, all OnAIR configurations require a Telemetry metadata file, defining the telemetry headers and a variety of testing parameters per telemetry type in a json table. While this works for the smaller test-type data functions used so far, users may be discouraged if they need to manually create an entry for all columns in their data as that number grows.
As discussed in last week's meeting, it seems like the easiest solution is to implement functionality to generate a Telemetry Metadata file if none is given, using user provided headers. For CSV's, we could simply use the header row if one exists. The Redis case is more difficult; perhaps dictionary or database keys could be used.
Currently, all OnAIR configurations require a Telemetry metadata file, defining the telemetry headers and a variety of testing parameters per telemetry type in a json table. While this works for the smaller test-type data functions used so far, users may be discouraged if they need to manually create an entry for all columns in their data as that number grows.
As discussed in last week's meeting, it seems like the easiest solution is to implement functionality to generate a Telemetry Metadata file if none is given, using user provided headers. For CSV's, we could simply use the header row if one exists. The Redis case is more difficult; perhaps dictionary or database keys could be used.