Minor documentation updates.
Updated dependencies:
MazamaCoreUtils 0.4.15 => 0.5.2
All mts_~() functions that return an mts
object now return an empty mts when an empty mts is
used as input. This prevents breaks in the middle of pipelines so that
“emptiness” only needs to be checked at the end.
All sts_~() functions that return an sts
object now return an empty sts when an empty sts is
used as input.
mts_pull() to get columns of data from
mts$meta or mts$data.mts_setTimeAxis() so that always retains the
original timezone associated with mts$data$datetime."US/Hawaii" from
the codebase.mts_filterDatetime() in favor of
mts_setTimeAxis() which is more general.mts_slice_head() and
mts_slice_tail().mts_setTimeAxis() to modify mts time spans.includeEnd argument to
mts/sts_filterDatetime().mts_select() with
duplicate deviceDeploymentIDs.mts_select() with
deviceDeploymentIDs not found in mts.mts_arrange() to order time series based on
values of a mts$meta column.mts_filterDate() and
mts_filterDatetime() when a POSIXct value is
encountered with no timezone information. This can happen when using
lubridate::now().mts_collapse() so that it now handles
metadata columns of class POSIXct.mts_trim() to remove all data records with only
missing data.mts_combine() with an
overlapStrategy argument. With
overlapStrategy = "replace all", values from later
timeseries (including NA) always replace values from
earlier timeseries. With overlapStrategy = "replace na",
values from later timeseries only replace NA values in
earlier timeseries.Carmel_Valley to match the latest version of
the AirMonitor package.Camp_Fire dataset from the
AirMonitor package.mts_selectWhere() to select time series based on
data values.mts/sts_filterMeta() to return an empty
mts/sts object if an empty mts/sts object is passed
in. Previous behavior was to stop with an error message. The new
behavior allows multiple filtering steps to be piped together without
having to check for an empty mts/sts at each step. Now you can
check once at the end of the pipeline..sample(),
.findOutliers().mts_sample().sts_summarize().example_raws dataset.Version 0.2 of the package is ready for operational use.
sts_join()
withsts_combine().mts_collapse().trimEmptyDays argument to
mts_trimDate().mts_collapse().monitor_isValid().mts_distance() to
mts_getDistance().monitorID
references.replaceMeta argument to
mts_combine().mts_summarize().mts_combine().mts_collapse(), mts_distance() and
mts_select().mts_filter() to mts_filterData()
to be more explicittimeInfo() and supporting functions.Carmel_Valley example dataset.~_filterDate().sts_from~() functions.mts_combine().mts_filter~() equivalents to
sts_filter~() functions.sts_isValid() and
mts_isValid().sts format:
sts_fromTidyDF()sts_fromCSV()sts functions.sts and
mts objects.sts functions:
sts_filter()sts_filterDate()sts_filterDatetime()sts_join()sts_toTidyDF()sts_trimDate()
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