Include sapflux tree reassignment and fix valid_entries() sorting bug (…

…#98) * Fix two bugs in date-handling and data frame sorting; this ensures that valid_through entries are handled correctly * Account for C8->C19 reassignment in TEMPEST control ( #86 )
COMPASS-DOE · Jan 19, 2024 · 242e341 · 242e341
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commit 242e341
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Showing 3 changed files with 8 additions and 3 deletions.
diff --git a/synoptic/L1_normalize.qmd b/synoptic/L1_normalize.qmd
@@ -156,8 +156,9 @@ f <- function(fn, out_dir, design_table) {
  # (in helpers.R) to figure out which mappings should apply.
  message("\tChecking for multiple-match design links...")
  dat_retain <- valid_entries(objects = dat$loggernet_variable,
- times = ymd_hms(dat$TIMESTAMP, tz = "EST"),
+ times = substr(dat$TIMESTAMP, 1, 10), # isolate YYYY-MM-DD
  valid_through = dat$valid_through)
+
  message("\tDropping ", sum(!dat_retain), " out-of-date design links")
  dat <- dat[dat_retain,]
  dat$valid_through <- NULL

diff --git a/synoptic/data_TEST/design_table.csv b/synoptic/data_TEST/design_table.csv
@@ -1854,7 +1854,10 @@ TMP,PNNL_11,sapflow,Format,,,,
 TMP,PNNL_11,sapflow,RECORD,,,,
 TMP,PNNL_11,sapflow,Statname,,,,
 TMP,PNNL_11,sapflow,BattV_Avg,SF_BattV-TMP-C-11,,voltage,
-TMP,PNNL_11,sapflow,DiffVolt_Avg({1:6}),"SF-TMP-C-{C7,C19,C10,C11,C16,C18}",,sapflow_2.5cm,
+TMP,PNNL_11,sapflow,DiffVolt_Avg(1),SF-TMP-C-C7,,sapflow_2.5cm,
+TMP,PNNL_11,sapflow,DiffVolt_Avg(2),SF-TMP-C-C8,2022-06-03,sapflow_2.5cm,C8 (Tree 1436) died; reassigned to C19
+TMP,PNNL_11,sapflow,DiffVolt_Avg(2),SF-TMP-C-C19,,sapflow_2.5cm,C8 (Tree 1436) died; reassigned to C19
+TMP,PNNL_11,sapflow,DiffVolt_Avg({3:6}),"SF-TMP-C-{C10,C11,C16,C18}",,sapflow_2.5cm,
 TMP,PNNL_11,sapflow,DiffVolt_Avg(7),SF-TMP-C-C10D,,sapflow_5cm,
 TMP,PNNL_11,sapflow,DiffVolt_Avg({8:14}),,,,
 TMP,PNNL_11,sapflow,DiffVolt({1:14}),,,,

diff --git a/synoptic/helpers.R b/synoptic/helpers.R
@@ -291,14 +291,15 @@ valid_entries <- function(objects, times, valid_through) {
  past_valid_time <- times > valid_through
 
  # Create a data frame to aggregate and then merge, below
- x <- data.frame(obj = objects, time = times, vu = valid_through)
+ x <- data.frame(num = seq_along(objects), obj = objects, time = times, vu = valid_through)
  # Compute the minimum valid_through entry for each object and time that is
  # not past the valid_through point; this is the 'controlling' value
  y <- aggregate(vu ~ obj + time, data = x[!past_valid_time,], FUN = min)
  names(y)[3] <- "controlling"
 
  # Figure out controlling valid_through for each object/time
  z <- merge(x, y, all.x = TRUE)
+ z <- z[order(z$num),] # ensure in correct original order
  # An NA controlling entry means there is none
  valids <- z$vu == z$controlling
  valids[is.na(valids)] <- FALSE