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## Welcome to fluxtools!
## Version: 0.3.0
## To cite, run citation('fluxtools')
fluxtools is an R package that provides an interactive Shiny‐based QA/QC environment for data in the AmeriFlux BASE format. In just a few clicks, you can:
NA
and an R script for
reproducibilityThis vignette shows you how to install, launch, and use the main
Shiny app—run_flux_qaqc()
—and walks through a typical
workflow.
You can install fluxtools from CRAN, or directly from GitHub:
Load fluxtools and launch the QA/QC application:
library(fluxtools)
# Add the UTC offset for your flux tower site (e.g., UTC-5 for EST)
run_flux_qaqc(-5)
Example workflow
Upload: Select your AmeriFlux-style CSV (e.g.,
US_VT1_HH_202401010000_202501010000.csv
). Files can be up
to 100 MB
Choose Year(s): By default “all” is selected, but you can subset to specific years
Choose variables: TIMESTAMP_START
is on the x-axis by default. Change the y-axis to your variable of
interest (e.g., FC_1_1_1
). The generated R code focuses on
removing the y-axis variable
Select data: Use the box or lasso to select points. This populates the “Current” code box with something like:
Flag data and Accumulate code: With points still selected, click “Flag data.” Selected points turn orange, and code is appended to the “Accumulated” box, allowing multiple selections per session.
Unflag data: Use the box or lasso to de-select points and remove from the Accumulated code box.
Clear Selection: To reset all selections from the current y-variable, click “Clear Selection” to reset the current view.
Switch variables: Change y to any other variable
(e.g., SWC_1_1_1
) and select more points. Click “Flag data”
Code for both variables to appear:
df <- df %>%
mutate(
FC_1_1_1 = case_when(
TIMESTAMP_START == '202401261830' ~ NA_real_,
TIMESTAMP_START == '202401270530' ~ NA_real_,
…
TRUE ~ FC_1_1_1
)
)
df <- df %>%
mutate(
SWC_1_1_1 = case_when(
TIMESTAMP_START == '202403261130' ~ NA_real_,
TIMESTAMP_START == '202403270800' ~ NA_real_,
…
TRUE ~ SWC_1_1_1
)
)
Compare variables: Change to variables you would
like to compare (e.g., change y to TA_1_1_1
and x to
T_SONIC_1_1_1
). The app computes an R² via simple linear
regression. The top R² is based on points before removals, and once data
is selected, a second R² will pop up - calculating the linear regression
assuming the selected points have been removed
Highlight outliers: Use the slider to select ±σ residuals. Click “Select all ±σ outliers” to append them to the Accumulated code. Click “Clear ±σ outliers” to deselect and remove from the code box
Copy all: Click the Copy Icon to the right of the current or accumulated code box and paste into your own R script for documentation
Apply Removals: Click “Apply Removals” to remove
each selected data points, from the current y-variable, to replace
points with NA
in a new .csv (raw data is unaffected),
available using ‘export cleaned data’ and remove these values from
view
Reload original data: Make a mistake or want a fresh start? Click Reload original data to reload the .csv from above to start over
Export cleaned data: Download the cleaned .csv reflecting your confirmed removals. This button will download a zip file containing your .csv, reflecting changes from using the “apply removals” button, and includes a compiled R script with the R code for those removals.
Fluxtools is an independent project and is not affiliated with or endorsed by the AmeriFlux Network. “AmeriFlux” is a registered trademark of Lawrence Berkeley National Laboratory and is used here for identification purposes only.
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.