Algorithm Theoretical Basis for "Average Algorithm"
Averages multiple observatory data for the same channel. Used mainly to average disturbance data in order to find the general disturbance in the magnetic field. The algorithm takes data from multiple observatories with the same channel and returns a stream of the averaged data.
The averaging function is used to smooth out the plots and find a combined disturbance of the magnetic field that encompasses the Earth. This can be used to determine the overall effect of magnetic storms over a large area. The algorithm is also used to average the Solar Quiet response to find the daily change in the magnetic field. The algorithm can be used to find the average of any channel over multiple observation stations.
Multiple data streams are averaged using a numpy function (numpy.mean) that takes multiple ndarrays as an argument and averages them into one array. A latitude correction can be applied based on the different observation locations. The correction is really just a weighting value based on a 0-1 scale in order to put more validity in some stations.
The averaging function can be called from geomag.py and stating the '--algorithm average' option or by calling the average.py script which automatically chooses the averaging option to the algorithm. Only one channel at a time can be run through the algorithm. Any input that geomag.py can handle can be used such as the edge server or a file url input this is also true for any output.