smooth_ts {phenocamr}

Smooth a PhenoCam time series

Description

Smooths time series iteratively using a Akaike information criterion (AIC) to find an optimal smoothing parameter and curve.

Usage

smooth_ts(
  data,
  metrics = c("gcc_mean", "gcc_50", "gcc_75", "gcc_90", "rcc_mean", "rcc_50", "rcc_75",
    "rcc_90"),
  force = TRUE,
  internal = TRUE,
  out_dir = tempdir()
)

Arguments

data

a PhenoCam data file or data structure

metrics

which metrics to process, normally all default ones

force

TRUE / FALSE, force reprocessing?

internal

return a data structure if given a file on disk (TRUE / FALSE = default)

out_dir

output directory where to store data

Value

An PhenoCam data structure or file with optimally smoothed time series objects added to the original file. Smoothing is required for 'phenophase()' and 'transition_dates()' functions.

Examples

## Not run: 
# with defaults, outputting a data frame
# with smoothed values, overwriting the original

# download demo data (do not smooth)
download_phenocam(site = "harvard$",
                  veg_type = "DB",
                  roi_id = "1000",
                  frequency = "3",
                  smooth = FALSE)

# smooth the downloaded file (and overwrite the original)
smooth_ts(file.path(tempdir(),"harvard_DB_1000_3day.csv"))

# the function also works on a PhenoCam data frame
df <- read_phenocam(file.path(tempdir(),"harvard_DB_1000_3day.csv"))
df <- smooth_ts(df)

## End(Not run)