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Updated dependencies:
MazamaCoreUtils 0.4.15 => 0.5.2
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()These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.