MazamaTimeSeries (version 0.3.0)

mts_combine: Combine multiple mts time series objects

Description

Create a combined mts from any number of mts objects or from a list of mts objects. The resulting mts object with contain all deviceDeploymentIDs found in any incoming mts and will have a regular time axis covering the the entire range of incoming data.

If incoming time ranges are non-contiguous, the resulting mts will have gaps filled with NA values.

An error is generated if the incoming mts objects have non-identical metadata for the same deviceDeploymentID unless replaceMeta = TRUE.

Usage

mts_combine(
  ...,
  replaceMeta = FALSE,
  overlapStrategy = c("replace all", "replace na")
)

Value

An mts time series object containing all time series found in the incoming mts objects. (A list with meta and data dataframes.)

Arguments

...

Any number of valid mts objects.

replaceMeta

Logical specifying whether to allow replacement of metadata associated with deviceDeploymentIDs.

overlapStrategy

Strategy to use when data found in time series overlaps.

Examples

library(MazamaTimeSeries)

ids1 <- example_mts$meta$deviceDeploymentID[1:5]
ids2 <- example_mts$meta$deviceDeploymentID[4:6]
ids3 <- example_mts$meta$deviceDeploymentID[8:10]

mts1 <-
  example_mts %>%
  mts_filterMeta(deviceDeploymentID %in% ids1) %>%
  mts_filterDate(20190701, 20190703)

mts2 <-
  example_mts %>%
  mts_filterMeta(deviceDeploymentID %in% ids2) %>%
  mts_filterDate(20190704, 20190706)

mts3 <-
  example_mts %>%
  mts_filterMeta(deviceDeploymentID %in% ids3) %>%
  mts_filterDate(20190705, 20190708)

mts <- mts_combine(mts1, mts2, mts3)

# Should have 1:6 + 8:10 = 9 meta records and the full date range
nrow(mts$meta)
range(mts$data$datetime)