Interactive Shiny application for exploration and
QA/QC of eddy covariance data.
Streamlines post-processing of eddy covariance datasets (e.g., after
EddyPro) to detect and remove outliers, enforce physical ranges, and
generate reproducible R code for AmeriFlux submissions.
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.
If you use fluxtools in your workflow, please cite:
Key, K. (2025). fluxtools (version 0.5.0) [Computer software]. Zenodo.
https://doi.org/10.5281/zenodo.15597159
#key-features
Interactive scatter
Choose TIMESTAMP_START (time) or any numeric variable for X; choose any
numeric variable for Y. Drag a box or lasso to flag points
Multi-year support
Upload up to ~1GB CSV (all years by default, or select one/more
years)
±σ outlier highlighting
Slider marks points beyond n standard deviations from a linear
fit; click Select ±σ outliers to add them
Accumulate & undo
Add selections to an accumulated list and remove them later if needed
Use Apply removals to commit NA changes, and Reload original data to
revert
Physical Range Module (PRM)
Clamp variables to physically reasonable ranges (AmeriFlux Technical
Note, Table A1) Out-of-range → NA. QC columns are ignored by PRM by
default Undo PRM reverts only PRM-applied changes
Reproducible outputs
Export a cleaned CSV (removed values set to NA) and an R script with the
exact transformations If PRM was applied, a summary table, audit
CSV, and a manual replay script are included
Dark/Light mode
Toggle theme on the fly
#installation
# From CRAN
install.packages("fluxtools")
# Newest version from GitHub
library(devtools)
devtools::install_github("kesondrakey/fluxtools")#quickstart
library(fluxtools)
# Launch the QA/QC Shiny app
run_fluxtools()#data-requirements - Input: AmeriFlux BASE (or Fluxnet) CSV - Must include TIMESTAMP_START (e.g., YYYYMMDDHHMM for 30-min or hourly data) - Missing values like -9999 are treated as NA
#how-it-works Timestamp Parsing & Time Zones #timestamp-parsing–time-zones - TIMESTAMP_START is parsed automatically - Viewer can display times with a fixed UTC±offset (no DST) - Selections, code, and exports are keyed to the original timestamp string. Underlying values and exported timestamps are preserved
Interactive QC & Selection #interactive-qc–selection - Box or lasso to select points - Click Flag Data to add selected points to the accumulated removal set - Click Unflag Data or Clear Selection to remove from the current set - Click Apply removals to set Y-values to NA_real_ (not reversible except through Reload original data)
Outlier Detection #outlier-detection - Fit a simple linear model between X and Y, compute residuals, and highlight points exceeding ±σ (user-controlled) - Select all ±σ outliers to add them to your accumulated code; clear ±σ outliers if needed
Time Slider (Inside / Outside) #time-slider-inside–outside - Adjustable time window on TIMESTAMP_START - Flag inside: add only points within the chosen time range - Flag outside: add all points except those within the chosen range - The slider snaps to your data cadence (30 min / 60 min) and supports multi-year files
Manual Range Filters #manual-range-filters - Define custom min/max for any variable - Flag values outside range to add out-of-bounds points to the accumulated set - Complements PRM by allowing site- or project-specific thresholds
Physical Range Module (PRM) #physical-range-module-prm’ - Available in the app or through fluxtools directly in R - Applies canonical physical bounds to variables (e.g., SWC, P, TA, CO2) using name-family matching (e.g., ^SWC($|_).) - Example: the “SWC” family refers to all variables starting with SWC (e.g., SWC_1_1_1, SWC_2_1_3) - Out-of-range values are set to NA and summarized with counts and percentages replaced - Apply to all variables or limit to selected families - Undo PRM reverts only the last PRM operation.
Example:
# View PRM rule table
get_prm_rules()
# Apply to all present families
res <- apply_prm(df)
res$data # clamped data
res$summary # per-column stats (min, max, n_replaced, pct_replaced)
# Apply to selected families
res2 <- apply_prm(df, include = c("SWC", "P"))PRM ranges (and name) were sourced from Ameriflux
Code Generation & Copy-All #code-generation–copy-all - The app continuously builds tidy dplyr code that sets selected Y-values to NA via case_when() - Switch between Current and Accumulated snippets; click Copy code to paste into your own scripts and version control
Export cleaned data: downloads a ZIP containing
raw_df.csv (original upload, unchanged)
fluxtools_processed_df_
fluxtools_removal_script.R (replays removals)
If PRM was applied:
prm_summary.csv (bounds + replacements)
prm_removed_values.csv (audit of values removed)
manual_prm_removed.R (cell-level replay)
Reload original data: restores the initial CSV to start over
browseVignettes("fluxtools")
# or
vignette("introduction", package = "fluxtools")If you use fluxtools in publications, please cite: > Key, K. (2025). fluxtools (version 0.4.0) [Computer software]. Zenodo. > https://doi.org/10.5281/zenodo.15597159
This package is free software, released under the GNU General Public License v3 (GPL-3). See the LICENSE file for details.
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.