compute_monthly_mean {neonSoilFlux}

Function to compute monthly means for a given month of NEON data.

Description

Given a NEON measurement data frame calculate the monthly mean values across all horizontal and vertical locations. Based off code from Zoey Werbin.

Usage

compute_monthly_mean(
  NEON_data,
  position_columns = c("horizontalPosition", "verticalPosition")
)

Arguments

NEON_data

Required. Input vector of neon measurements for a month

position_columns

Optional. Do we group by horizontalPosition, verticalPosition, and? Default is both. Added this option in case we just want to average across a given dimension.

Value

A data frame that reports for each horiztonal and vertical position the computed mean and standard deviation from sampling (similar to a bootstrap method) as well as the sample mean and sample standard deviation

Author(s)

John Zobitz [e-mail]

References

Zoey Werbin (@zoey-rw): original author https://github.com/zoey-rw/microbialForecasts/blob/caa7b1a8aa8a131a5ff9340f1562cd3a3cb6667b/data_construction/covariate_prep/soil_moisture/clean_NEON_sensor_moisture_data.r

Examples

# Download the NEON data directly - here this would be soil moisture
NEON_moist_30m_orig <- neonUtilities::loadByProduct(
  dpID = "DP1.00094.001",
  site = "WREF",
  startdate = "2022-06",
  enddate = "2022-06",
  timeIndex = "30",
  package = "expanded",
  check.size = FALSE,
  include.provisional = TRUE
)


# Then correct the swc
site_swc <- swc_correct(NEON_moist_30m_orig, "WREF","2022-06")

# Select the columns and the time frequency
time_frequency <- "30_minute"
column_selectors <- c("Mean", "Minimum", "Maximum", "ExpUncert", "StdErMean")

    swc <- site_swc |>
    purrr::pluck(paste0("SWS_",time_frequency)) |>
    dplyr::select(tidyselect::all_of(c("domainID","siteID",
    "horizontalPosition","verticalPosition","startDateTime","VSWCFinalQF")),
    tidyselect::matches(stringr::str_c("VSWC",column_selectors)))

  # Determine a data frame of the different horizontal and vertical positions
  swc_positions <- site_swc |>
  purrr::pluck(paste0("sensor_positions_","00094"))

  # Add on the positions for swc
  swc <- determine_position(swc_positions,swc)