Ensemble averaging of adp objects is often necessary to reduce the uncertainty in velocity estimates from single pings. Many types of ADPs can be configured to perform the ensemble averaging during the data collection, due to memory limitations for long deployments. In cases where the instrument is not memory limited, it may be desirable to perform the ensemble averaging during post-processing, thereby reducing the overall size of the data set and decreasing the uncertainty of the velocity estimates (by averaging out Doppler noise).

adpEnsembleAverage(x, n = 5, leftover = FALSE, na.rm = TRUE, ...)

Arguments

x

an adp object.

n

number of pings to average together.

leftover

a logical value indicating how to proceed in cases where n does not divide evenly into the number of ensembles in x. If leftover is FALSE (the default) then any extra ensembles at the end of x are ignored. Otherwise, they are used to create a final ensemble in the returned value.

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds

...

extra arguments to be passed to the mean() function.

Value

A new adp object with ensembles averaged as specified. E.g. for an adp object with 100 pings and n=5 the number of rows of the data arrays will be reduced by a factor of 5.

See also

Examples

library(oce) data(adp) adpAvg <- adpEnsembleAverage(adp, n=2) plot(adpAvg)