I noticed something strange today while reading a test signal from the SendData.py example. When I load the data using xdf.py, the effective_sr field in the EEG info is 1.2646483766719545e-05. However, the first timestamp is 430654.7832216, the last timestamp is 430686.9530195 giving an actual effective sampling rate of 1/((x[-1] - x[0])/len(x)) = 76.37954923109451. I recorded for about 30 seconds on a local machine and all the clock offsets appear to be correct (the time of the offset progresses every 5 seconds, and the value is a very small number).
I noticed something strange today while reading a test signal from the SendData.py example. When I load the data using xdf.py, the effective_sr field in the EEG info is 1.2646483766719545e-05. However, the first timestamp is 430654.7832216, the last timestamp is 430686.9530195 giving an actual effective sampling rate of 1/((x[-1] - x[0])/len(x)) = 76.37954923109451. I recorded for about 30 seconds on a local machine and all the clock offsets appear to be correct (the time of the offset progresses every 5 seconds, and the value is a very small number).