R version 3.6.1 (2019-07-05) -- "Action of the Toes" Copyright (C) 2019 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # R file to be executed by run runEddyProc.sh or reddy_runLocal.sh > > # stop("under construction, come back on 27th of June") > # setwd("/Net/Groups/BGI/services/REddyProcWeb/work/001") > # setwd("m:/services/REddyProcWeb/work/001") > # setwd("~/bgi/services/REddyProcWeb/work/debug") > > dumpfileBasename <- "RBatch_dump" > options(error = quote({ + dump.frames(dumpfileBasename,TRUE); stop(paste("dump in ",dumpfileBasename))})) > options(warn = 1) # print all warnings (instead of a summary at the end) > > # add REddyProc/Library as first library path, see readme in Library folder > .libPaths( c("../../Library", tail(.libPaths(),1)) ) > .libPaths() [1] "/Net/Groups/BGI/services/REddyProcWeb/Library" [2] "/Net/Groups/Services/LNX_Local64/SLES11/apps/R/R-3.6.1/lib64/R/library" > library(REddyProc) > > cat('Using REddyProc version ' + , paste(unlist(packageVersion("REddyProc")),collapse = "."),"\n") Using REddyProc version 1.2 > Sys.time() [1] "2020-10-21 16:47:10 CEST" > > source("../../R/readConfig.R") > configurationFileName = "post.dcf" > eddyProcConfiguration <- compileAndValidateEddyProcConfiguration(configurationFileName) Entries supplied by the web form: SiteID ustarFilter ustarFilterMethod "US-PFi" "YES" "RTw" ustarFilterSeasoning ustarFilterUncertainty isGapfilling "WithinYear" "NO" "YES" partitioningMethods.. partitioningMethods...1 Latitude "Reichstein05" "Lasslop10" "45.9749" Longitude Timezone temperatureVarName "-90.23273" "-6" "Tair" isRemoveUstarSuffix email fileIdentifier "TRUE" "bbutterworth@wisc.edu" "566346999" REddyProcWebRevision "75" > sourceFunctions(eddyProcConfiguration) > > time <- system.time( + # call as function for easier debugging with dump + retval <- processEddyData(eddyProcConfiguration = eddyProcConfiguration) + ) List of 18 $ siteId : Named chr "US-PFi" ..- attr(*, "names")= chr "SiteID" $ isToApplyUStarFiltering: Named logi TRUE ..- attr(*, "names")= chr "ustarFilter" $ isToApplyGapFilling : logi TRUE $ isToApplyPartitioning : logi TRUE $ temperatureDataVariable: Named chr "Tair" ..- attr(*, "names")= chr "temperatureVarName" $ debugFlags : chr "" $ isCatchingErrorsEnabled: logi TRUE $ useDevelopLibraryPath : logi FALSE $ isBootstrapUStar : logi FALSE $ partitioningMethods : chr [1:2] "Reichstein05" "Lasslop10" $ input_format : chr "onlinetool" $ output_format : chr "reddyproc12" $ figureFormat : chr "pdf" $ uStarSeasoning : Factor w/ 1 level "WithinYear": 1 ..- attr(*, "names")= chr "ustarFilterSeasoning" $ uStarMethod : Factor w/ 1 level "RTw": 1 ..- attr(*, "names")= chr "ustarFilterMethod" $ timezone : num -6 $ latitude : num 46 $ longitude : num -90.2 Loaded file input.txt with the following variables (units): *** Year(-) DoY(-) Hour(-) NEE(umolm-2s-1) LE(Wm-2) H(Wm-2) Rg(Wm-2) Tair(degC) Tsoil(degC) rH(%) Ustar(ms-1) Number of '-9999' convertered to NA: 15090 Converted time format 'YDH' to POSIX with column name 'DateTime'. 'data.frame': 5568 obs. of 12 variables: $ DateTime: POSIXct, format: "2019-06-20 00:30:00" "2019-06-20 01:00:00" ... $ Year : int 2019 2019 2019 2019 2019 2019 2019 2019 2019 2019 ... ..- attr(*, "varnames")= chr "Year" ..- attr(*, "units")= chr "-" $ DoY : int 171 171 171 171 171 171 171 171 171 171 ... ..- attr(*, "varnames")= chr "DoY" ..- attr(*, "units")= chr "-" $ Hour : num 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 ... ..- attr(*, "varnames")= chr "Hour" ..- attr(*, "units")= chr "-" $ NEE : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "NEE" ..- attr(*, "units")= chr "umolm-2s-1" $ LE : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "LE" ..- attr(*, "units")= chr "Wm-2" $ H : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "H" ..- attr(*, "units")= chr "Wm-2" $ Rg : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "Rg" ..- attr(*, "units")= chr "Wm-2" $ Tair : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "Tair" ..- attr(*, "units")= chr "degC" $ Tsoil : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "Tsoil" ..- attr(*, "units")= chr "degC" $ rH : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "rH" ..- attr(*, "units")= chr "%" $ Ustar : num NA NA NA NA NA NA NA NA NA NA ... ..- attr(*, "varnames")= chr "Ustar" ..- attr(*, "units")= chr "ms-1" [1] "Calculating VPD from rH and Tair." Warning in fCheckOutsideRange(cbind(RelHumidity_Percent = rH), "RelHumidity_Percent", : fCalcVPDfromRHandTair:::fCheckOutsideRange::: Variable outside (plausible) range in 1205 cases! Invalid values with 'RelHumidity_Percent < 0 | > 100': 100, 100, 101, 101, 101, 101, 101, 101, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 101, 101, 100, 100, 100, 101, 101, 101, 101, 101, 101, 101, 101, 101, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 102, 101, 101, 100, 100, 100, 101 ... Data variables picked for gap filling (dataVariablesToFill): NEE,LE,H,Rg,VPD,rH,Tair,Tsoil No additional columns picked to keep in processing Warning in fCheckOutsideRange(Data.F, VarName.V.s[v.i], c("<", 0), SubCallFunc.s) : sEddyProc.initialize:::fCheckColPlausibility:::fCheckOutsideRange::: Variable outside (plausible) range in 1212 cases! Invalid values with 'Rg < 0': -4.607, -3.595, -3.519, -3.327, -3.723, -2.862, -3.590, -2.970, -3.224, -3.170, -2.896, -3.037, -3.141, -2.785, -3.126, -2.797, -1.738, -1.542, -1.557, -1.444, -1.361, -1.362, -1.355, -0.885, -2.124, -1.336, -0.904, -0.714, -0.471, -0.584, -0.928, -0.863, -0.090, -0.291, -0.280, -0.434, -0.265, -0.023, -0.861, -1.118, -1.116, -1.351, -1.412, -1.653, -1.038, -0.843, -0.568, -2.351, -2.651, -2.962 ... Warning in fCheckOutsideRange(Data.F, VarName.V.s[v.i], c("<", 0), SubCallFunc.s) : sEddyProc.initialize:::fCheckColPlausibility:::fCheckOutsideRange::: Variable outside (plausible) range in 1205 cases! Invalid values with 'VPD < 0': -0.030, -0.065, -0.102, -0.124, -0.127, -0.185, -0.217, -0.222, -0.282, -0.359, -0.398, -0.388, -0.382, -0.381, -0.384, -0.388, -0.395, -0.392, -0.325, -0.230, -0.144, -0.029, -0.049, -0.051, -0.190, -0.126, -0.155, -0.165, -0.170, -0.170, -0.100, -0.117, -0.189, -0.265, -0.327, -0.273, -0.272, -0.319, -0.312, -0.305, -0.294, -0.305, -0.301, -0.264, -0.124, -0.145, -0.016, -0.063, -0.024, -0.130 ... New sEddyProc class for site 'US-PFi' [1] "------------- u* Threshold estimation ---------------" Warning in .estimateUStarSeason(...) : sEstUstarThreshold: too few finite records within season (n = 623) for 7 temperature classes. Need at least n = 700. Returning NA for this Season. Warning in .estimateUStarSeason(...) : sEstUstarThreshold: too few finite records within season (n = 379) for 7 temperature classes. Need at least n = 700. Returning NA for this Season. Estimated UStar threshold of: 0.24 by using controls: taClasses UstarClasses 7 20 swThr minRecordsWithinTemp 10 100 minRecordsWithinSeason minRecordsWithinYear 160 3000 isUsingOneBigSeasonOnFewRecords 1 aggregationMode seasonYear season uStar 2 year 2019 0.237375 [1] "------------- Gapfilling ---------------" Ustar filtering (u * Th_1 = 0.237375), marked 49% of the data as gap Initialized variable 'NEE' with 3500 real gaps for gap filling of all 5568 values (to estimate uncertainties). Full MDS algorithm for gap filling of 'NEE.Ustar_uStar_fqc_0' with LUT(Rg, VPD, Tair) and MDC. Look up table with window size of 7 days with Rg VPD Tair .......................................................2483 Look up table with window size of 14 days with Rg VPD Tair ..............................94 Look up table with window size of 7 days with Rg .............................322 Mean diurnal course with window size of 0 days: . ..........................552 Mean diurnal course with window size of 1 days: . .....................745 Mean diurnal course with window size of 2 days: . .............172 Look up table with window size of 21 days with Rg VPD Tair ............0 Look up table with window size of 28 days with Rg VPD Tair ............1 Look up table with window size of 35 days with Rg VPD Tair ...........4 Look up table with window size of 42 days with Rg VPD Tair ...........1 Look up table with window size of 49 days with Rg VPD Tair ...........0 Look up table with window size of 56 days with Rg VPD Tair ...........0 Look up table with window size of 63 days with Rg VPD Tair ...........0 Look up table with window size of 70 days with Rg VPD Tair ...........0 Look up table with window size of 14 days with Rg ...........0 Look up table with window size of 21 days with Rg ...........0 Look up table with window size of 28 days with Rg ...........0 Look up table with window size of 35 days with Rg ...........0 Look up table with window size of 42 days with Rg ...........0 Look up table with window size of 49 days with Rg ...........0 Look up table with window size of 56 days with Rg ...........0 Look up table with window size of 63 days with Rg ...........0 Look up table with window size of 70 days with Rg ...........0 Mean diurnal course with window size of 7 days: . ...........370 Mean diurnal course with window size of 14 days: . ........336 Mean diurnal course with window size of 21 days: . ....336 Mean diurnal course with window size of 28 days: . .152 Finished gap filling of 'NEE' in 7 seconds. Artificial gaps filled: 5568, real gaps filled: 3500, unfilled (long) gaps: 0. Initialized variable 'LE' with 2775 real gaps for gap filling of all 5568 values (to estimate uncertainties). Full MDS algorithm for gap filling of 'LE' with LUT(Rg, VPD, Tair) and MDC. Look up table with window size of 7 days with Rg VPD Tair .......................................................2516 Look up table with window size of 14 days with Rg VPD Tair ..............................78 Look up table with window size of 7 days with Rg .............................305 Mean diurnal course with window size of 0 days: . ..........................755 Mean diurnal course with window size of 1 days: . ...................643 Mean diurnal course with window size of 2 days: . ............112 Look up table with window size of 21 days with Rg VPD Tair ...........0 Look up table with window size of 28 days with Rg VPD Tair ...........1 Look up table with window size of 35 days with Rg VPD Tair ...........4 Look up table with window size of 42 days with Rg VPD Tair ...........1 Look up table with window size of 49 days with Rg VPD Tair ...........0 Look up table with window size of 56 days with Rg VPD Tair ...........0 Look up table with window size of 63 days with Rg VPD Tair ...........0 Look up table with window size of 70 days with Rg VPD Tair ...........0 Look up table with window size of 14 days with Rg ...........0 Look up table with window size of 21 days with Rg ...........0 Look up table with window size of 28 days with Rg ...........0 Look up table with window size of 35 days with Rg ...........0 Look up table with window size of 42 days with Rg ...........0 Look up table with window size of 49 days with Rg ...........0 Look up table with window size of 56 days with Rg ...........0 Look up table with window size of 63 days with Rg ...........0 Look up table with window size of 70 days with Rg ...........0 Mean diurnal course with window size of 7 days: . ...........344 Mean diurnal course with window size of 14 days: . ........336 Mean diurnal course with window size of 21 days: . ....336 Mean diurnal course with window size of 28 days: . .137 Finished gap filling of 'LE' in 7 seconds. Artificial gaps filled: 5568, real gaps filled: 2775, unfilled (long) gaps: 0. Initialized variable 'H' with 2188 real gaps for gap filling of all 5568 values (to estimate uncertainties). Full MDS algorithm for gap filling of 'H' with LUT(Rg, VPD, Tair) and MDC. Look up table with window size of 7 days with Rg VPD Tair .......................................................2874 Look up table with window size of 14 days with Rg VPD Tair ..........................22 Look up table with window size of 7 days with Rg ..........................11 Mean diurnal course with window size of 0 days: . ..........................870 Mean diurnal course with window size of 1 days: . .................659 Mean diurnal course with window size of 2 days: . ...........74 Look up table with window size of 21 days with Rg VPD Tair ..........0 Look up table with window size of 28 days with Rg VPD Tair ..........0 Look up table with window size of 35 days with Rg VPD Tair ..........0 Look up table with window size of 42 days with Rg VPD Tair ..........0 Look up table with window size of 49 days with Rg VPD Tair ..........0 Look up table with window size of 56 days with Rg VPD Tair ..........0 Look up table with window size of 63 days with Rg VPD Tair ..........0 Look up table with window size of 70 days with Rg VPD Tair ..........0 Look up table with window size of 14 days with Rg ..........0 Look up table with window size of 21 days with Rg ..........0 Look up table with window size of 28 days with Rg ..........0 Look up table with window size of 35 days with Rg ..........0 Look up table with window size of 42 days with Rg ..........0 Look up table with window size of 49 days with Rg ..........0 Look up table with window size of 56 days with Rg ..........0 Look up table with window size of 63 days with Rg ..........0 Look up table with window size of 70 days with Rg ..........0 Mean diurnal course with window size of 7 days: . ..........252 Mean diurnal course with window size of 14 days: . ........336 Mean diurnal course with window size of 21 days: . ....336 Mean diurnal course with window size of 28 days: . .134 Finished gap filling of 'H' in 6 seconds. Artificial gaps filled: 5568, real gaps filled: 2188, unfilled (long) gaps: 0. Initialized variable 'Rg' with 2660 real gaps for gap filling. Restriced MDS algorithm for gap filling of 'Rg' with no meteo conditions and hence only MDC. Mean diurnal course with window size of 0 days: . ..........................241 Mean diurnal course with window size of 1 days: . ........................1182 Mean diurnal course with window size of 2 days: . ............178 Mean diurnal course with window size of 7 days: . ..........256 Mean diurnal course with window size of 14 days: . ........336 Mean diurnal course with window size of 21 days: . ....336 Mean diurnal course with window size of 28 days: . .131 Finished gap filling of 'Rg' in 0 seconds. Artificial gaps filled: 5568, real gaps filled: 2660, unfilled (long) gaps: 0. Initialized variable 'VPD' with 663 real gaps for gap filling. Limited MDS algorithm for gap filling of 'VPD' with LUT(Rg only) and MDC. Look up table with window size of 7 days with Rg ......0 Mean diurnal course with window size of 0 days: . ......72 Mean diurnal course with window size of 1 days: . .....541 Mean diurnal course with window size of 2 days: . 50 Finished gap filling of 'VPD' in 0 seconds. Artificial gaps filled: 5568, real gaps filled: 663, unfilled (long) gaps: 0. Initialized variable 'rH' with 663 real gaps for gap filling. Full MDS algorithm for gap filling of 'rH' with LUT(Rg, VPD, Tair) and MDC. Look up table with window size of 7 days with Rg VPD Tair ......0 Look up table with window size of 14 days with Rg VPD Tair ......0 Look up table with window size of 7 days with Rg ......0 Mean diurnal course with window size of 0 days: . ......72 Mean diurnal course with window size of 1 days: . .....541 Mean diurnal course with window size of 2 days: . 50 Finished gap filling of 'rH' in 0 seconds. Artificial gaps filled: 5568, real gaps filled: 663, unfilled (long) gaps: 0. Initialized variable 'Tair' with 663 real gaps for gap filling. Limited MDS algorithm for gap filling of 'Tair' with LUT(Rg only) and MDC. Look up table with window size of 7 days with Rg ......0 Mean diurnal course with window size of 0 days: . ......72 Mean diurnal course with window size of 1 days: . .....541 Mean diurnal course with window size of 2 days: . 50 Finished gap filling of 'Tair' in 0 seconds. Artificial gaps filled: 5568, real gaps filled: 663, unfilled (long) gaps: 0. Initialized variable 'Tsoil' with 1372 real gaps for gap filling. Full MDS algorithm for gap filling of 'Tsoil' with LUT(Rg, VPD, Tair) and MDC. Look up table with window size of 7 days with Rg VPD Tair .............323 Look up table with window size of 14 days with Rg VPD Tair ..........11 Look up table with window size of 7 days with Rg ..........2 Mean diurnal course with window size of 0 days: . ..........67 Mean diurnal course with window size of 1 days: . .........581 Mean diurnal course with window size of 2 days: . ...135 Look up table with window size of 21 days with Rg VPD Tair ..0 Look up table with window size of 28 days with Rg VPD Tair ..0 Look up table with window size of 35 days with Rg VPD Tair ..0 Look up table with window size of 42 days with Rg VPD Tair ..0 Look up table with window size of 49 days with Rg VPD Tair ..0 Look up table with window size of 56 days with Rg VPD Tair ..0 Look up table with window size of 63 days with Rg VPD Tair ..0 Look up table with window size of 70 days with Rg VPD Tair ..0 Look up table with window size of 14 days with Rg ..0 Look up table with window size of 21 days with Rg ..0 Look up table with window size of 28 days with Rg ..0 Look up table with window size of 35 days with Rg ..0 Look up table with window size of 42 days with Rg ..0 Look up table with window size of 49 days with Rg ..0 Look up table with window size of 56 days with Rg ..0 Look up table with window size of 63 days with Rg ..0 Look up table with window size of 70 days with Rg ..0 Mean diurnal course with window size of 7 days: . ..253 Finished gap filling of 'Tsoil' in 1 seconds. Artificial gaps filled: 5568, real gaps filled: 1372, unfilled (long) gaps: 0. Saved plot to: ./US-PFi_2019_FP_NEE.pdf Saved plot to: ./US-PFi_2019_Flux_NEE.pdf Saved plot to: ./US-PFi_2019_FP_LE.pdf Saved plot to: ./US-PFi_2019_Flux_LE.pdf Saved plot to: ./US-PFi_2019_FP_H.pdf Saved plot to: ./US-PFi_2019_Flux_H.pdf Saved plot to: ./US-PFi_2019_FP_Rg.pdf Saved plot to: ./US-PFi_2019_Flux_Rg.pdf Saved plot to: ./US-PFi_2019_FP_VPD.pdf Saved plot to: ./US-PFi_2019_Flux_VPD.pdf Saved plot to: ./US-PFi_2019_FP_rH.pdf Saved plot to: ./US-PFi_2019_Flux_rH.pdf Saved plot to: ./US-PFi_2019_FP_Tair.pdf Saved plot to: ./US-PFi_2019_Flux_Tair.pdf Saved plot to: ./US-PFi_2019_FP_Tsoil.pdf Saved plot to: ./US-PFi_2019_Flux_Tsoil.pdf Saved plot to: ./US-PFi_2019_FP_NEE_uStar_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_NEE_uStar_f.pdf Saved plot to: ./US-PFi_2019_DSumU_NEE_uStar_f.pdf Saved plot to: ./US-PFi_2019_Flux_NEE_uStar_f.pdf Saved plot to: ./US-PFi_2019_FP_LE_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_LE_f.pdf Saved plot to: ./US-PFi_2019_DSumU_LE_f.pdf Saved plot to: ./US-PFi_2019_Flux_LE_f.pdf Saved plot to: ./US-PFi_2019_FP_H_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_H_f.pdf Saved plot to: ./US-PFi_2019_DSumU_H_f.pdf Saved plot to: ./US-PFi_2019_Flux_H_f.pdf Saved plot to: ./US-PFi_2019_FP_Rg_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_Rg_f.pdf Saved plot to: ./US-PFi_2019_DSum_Rg_f.pdf Saved plot to: ./US-PFi_2019_Flux_Rg_f.pdf Saved plot to: ./US-PFi_2019_FP_VPD_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_VPD_f.pdf Saved plot to: ./US-PFi_2019_DSum_VPD_f.pdf Saved plot to: ./US-PFi_2019_Flux_VPD_f.pdf Saved plot to: ./US-PFi_2019_FP_rH_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_rH_f.pdf Saved plot to: ./US-PFi_2019_DSum_rH_f.pdf Saved plot to: ./US-PFi_2019_Flux_rH_f.pdf Saved plot to: ./US-PFi_2019_FP_Tair_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_Tair_f.pdf Saved plot to: ./US-PFi_2019_DSum_Tair_f.pdf Saved plot to: ./US-PFi_2019_Flux_Tair_f.pdf Saved plot to: ./US-PFi_2019_FP_Tsoil_f.pdf Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: January! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: February! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: March! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: April! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: May! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month, Legend = F) : .sPlotDiurnalCycleM::: No data available for month: November! Warning in .self$.sPlotDiurnalCycleM(Var, QFVar, QFValue, Month) : .sPlotDiurnalCycleM::: No data available for month: December! Saved plot to: ./US-PFi_2019_DC_Tsoil_f.pdf Saved plot to: ./US-PFi_2019_DSum_Tsoil_f.pdf Saved plot to: ./US-PFi_2019_Flux_Tsoil_f.pdf [1] "------------- Flux Partitioning ---------------" Warning in fCheckOutsideRange(Data.F, VarName.V.s[v.i], c("<", 0), SubCallFunc.s) : sMRFluxPartition:::fCheckColPlausibility:::fCheckOutsideRange::: Variable outside (plausible) range in 1212 cases! Invalid values with 'Rg < 0': -4.607, -3.595, -3.519, -3.327, -3.723, -2.862, -3.590, -2.970, -3.224, -3.170, -2.896, -3.037, -3.141, -2.785, -3.126, -2.797, -1.738, -1.542, -1.557, -1.444, -1.361, -1.362, -1.355, -0.885, -2.124, -1.336, -0.904, -0.714, -0.471, -0.584, -0.928, -0.863, -0.090, -0.291, -0.280, -0.434, -0.265, -0.023, -0.861, -1.118, -1.116, -1.351, -1.412, -1.653, -1.038, -0.843, -0.568, -2.351, -2.651, -2.962 ... Start flux partitioning for variable NEE_uStar_f with temperature Tair_f. Estimate of the temperature sensitivity E_0 from short term data: 129.38. Regression of reference temperature R_ref for 24 periods. Start daytime flux partitioning for variable NEE_uStar_f with temperature Tair_f. Warning in fCheckOutsideRange(Data.F, VarName.V.s[v.i], c("<", 0), SubCallFunc.s) : sGLFluxPartition:::fCheckColPlausibility:::fCheckOutsideRange::: Variable outside (plausible) range in 1225 cases! Invalid values with 'VPD_f < 0': -0.030, -0.065, -0.102, -0.124, -0.127, -0.185, -0.217, -0.222, -0.282, -0.359, -0.398, -0.388, -0.382, -0.381, -0.384, -0.388, -0.395, -0.392, -0.325, -0.230, -0.144, -0.029, -0.049, -0.051, -0.190, -0.126, -0.155, -0.165, -0.170, -0.170, -0.100, -0.117, -0.189, -0.265, -0.327, -0.273, -0.272, -0.319, -0.312, -0.305, -0.294, -0.305, -0.301, -0.264, -0.124, -0.145, -0.016, -0.063, -0.024, -0.130 ... Warning in fCheckOutsideRange(Data.F, VarName.V.s[v.i], c("<", 0), SubCallFunc.s) : sGLFluxPartition:::fCheckColPlausibility:::fCheckOutsideRange::: Variable outside (plausible) range in 2105 cases! Invalid values with 'Rg_f < 0': -1.78, -1.75, -1.80, -1.72, -1.65, -1.66, -1.33, -1.24, -2.06, -1.93, -1.83, -1.69, -1.69, -1.74, -1.69, -1.64, -1.64, -1.55, -1.45, -1.43, -1.11, -0.76, -1.89, -1.80, -1.74, -1.66, -1.69, -1.75, -1.72, -1.67, -1.66, -1.58, -1.49, -1.47, -1.14, -2.43, -3.75, -3.41, -3.40, -3.29, -3.27, -3.16, -3.17, -3.06, -3.09, -3.01, -3.00, -2.98, -2.32, -1.75 ... Estimating temperature sensitivity from night time NEE , 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113 increase window size to 24, 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113 increase window size to 48, 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113 Smoothing temperature sensitivity estimates Estimating respiration at reference temperature for smoothed temperature sensitivity from night time NEE , 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113 Estimating light response curve parameters from day time NEE , 1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 101, 103, 105, 107, 109, 111, 113 Warning: `select_()` is deprecated as of dplyr 0.7.0. Please use `select()` instead. This warning is displayed once every 8 hours. Call `lifecycle::last_warnings()` to see where this warning was generated. Saved plot to: ./US-PFi_2019_FP_Reco_uStar.pdf Saved plot to: ./US-PFi_2019_FP_GPP_uStar_f.pdf Saved plot to: ./US-PFi_2019_FP_Reco_DT_uStar.pdf Saved plot to: ./US-PFi_2019_FP_GPP_DT_uStar.pdf Number of NA convertered to '-9999': 225263 Wrote tab separated textfile: output.txt > > # done in shell script > print("converting generated output pdf files to png format for display on results page.") [1] "converting generated output pdf files to png format for display on results page." > > # write logEntry that will be appended by to reddy_jobs_out.txt by reddy_bjobs.sh > logEntry <- paste( time["user.self"], retval$mode, retval$inputSize, sep = "," ) > cat( logEntry, file = "logEntry.txt") > > # if error occured make sure to exit with error code. > if(length(retval$err)){ + fDump <- function(retval, eddyProcConfiguration) + stop("First caught error: ", retval$err) # does not quite but only dump + fDump(retval, eddyProcConfiguration) + } > if (file.exists(paste0(dumpfileBasename,".rda"))) { + quit(save = "no", status = 1L) + } > > > > > proc.time() user system elapsed 38.822 0.124 39.062