/// <summary>
/// Generate data for each sensor and store it in the observations input.
/// NOTE: At the moment, this is only called during training or when using a DemonstrationRecorder;
/// during inference the Sensors are used to write directly to the Tensor data. This will likely change in the
/// future to be controlled by the type of brain being used.
/// </summary>
/// <param name="sensors"> List of ISensors that will be used to generate the data.</param>
/// <param name="buffer"> A float array that will be used as buffer when generating the observations. Must
/// be at least the same length as the total number of uncompressed floats in the observations</param>
/// <param name="adapter"> The WriteAdapter that will be used to write the ISensor data to the observations</param>
/// <param name="observations"> A list of observations outputs. This argument will be modified by this method.</param>//
public static void GenerateSensorData(List <ISensor> sensors, float[] buffer, WriteAdapter adapter, List <Observation> observations)
{
int floatsWritten = 0;
// Generate data for all Sensors
for (var i = 0; i < sensors.Count; i++)
{
var sensor = sensors[i];
if (sensor.GetCompressionType() == SensorCompressionType.None)
{
// TODO handle in communicator code instead
adapter.SetTarget(buffer, sensor.GetObservationShape(), floatsWritten);
var numFloats = sensor.Write(adapter);
var floatObs = new Observation
{
FloatData = new ArraySegment <float>(buffer, floatsWritten, numFloats),
Shape = sensor.GetObservationShape(),
CompressionType = sensor.GetCompressionType()
};
observations.Add(floatObs);
floatsWritten += numFloats;
}
else
{
var compressedObs = new Observation
{
CompressedData = sensor.GetCompressedObservation(),
Shape = sensor.GetObservationShape(),
CompressionType = sensor.GetCompressionType()
};
observations.Add(compressedObs);
}
}
}