From 6f1a0942d0dc987165433b003b167e5521b7aaad Mon Sep 17 00:00:00 2001 From: Christian Fournier Date: Tue, 25 Aug 2026 11:20:16 +0200 Subject: [PATCH 1/4] force float casting in plantgen extension fix phenT filling on explicit copy restore merge with dimT_user_table --- src/openalea/adel/plantgen/plantgen_core.py | 40 ++++++++++----------- src/openalea/adel/plantgen_extensions.py | 6 ++-- 2 files changed, 23 insertions(+), 23 deletions(-) diff --git a/src/openalea/adel/plantgen/plantgen_core.py b/src/openalea/adel/plantgen/plantgen_core.py index 582efa4c..832b39c7 100644 --- a/src/openalea/adel/plantgen/plantgen_core.py +++ b/src/openalea/adel/plantgen/plantgen_core.py @@ -365,10 +365,15 @@ def organs_dimensions( force=False, ) ) - dimT_tmp = _create_dimT_tmp(axeT_tmp, force=False) + dimT_tmp = _create_dimT_tmp(axeT_) + + # 3. merge dimT_tmp and dimT_user + dimT_tmp_merged = _merge_dimT_tmp_and_dimT_user( + dynT_, dimT_user, dimT_user_completeness, dimT_tmp + ) # 2. create dimT - dimT_ = _create_dimT(axeT_, dimT_tmp, dynT_, decimal_elongated_internode_number) + dimT_ = _create_dimT(axeT_, dimT_tmp_merged, dynT_, decimal_elongated_internode_number) return dimT_ @@ -2769,7 +2774,7 @@ def __call__(self, axeT_, dynT_, decimal_elongated_internode_number, force=True) for (id_cohort, N_phytomer_potential, id_phen), axeT_group in axeT_.groupby( ["id_cohort", "N_phytomer_potential", "id_phen"] ): - phenT_tmp_group = phenT_tmp_grouped.get_group(id_phen) + phenT_tmp_group = phenT_tmp_grouped.get_group(id_phen).copy() dynT_group = dynT_grouped.get_group((id_cohort, N_phytomer_potential)) dynT_row = dynT_group.loc[ dynT_group[ @@ -2867,9 +2872,7 @@ def __call__(self, axeT_, dynT_, decimal_elongated_internode_number, force=True) # ) # TODO: useful ? # compute TT_col_phytomer - self.phenT_tmp.loc[ - phenT_tmp_group.index, "TT_col_phytomer" - ] = phenT_tmp_group.loc[:, "TT_col_phytomer"].values[:] = ( + phenT_tmp_group["TT_col_phytomer"] = ( phenT_tmp_group["index_phytomer"].apply( _calculate_TT_col_phytomer, args=( @@ -2890,11 +2893,8 @@ def __call__(self, axeT_, dynT_, decimal_elongated_internode_number, force=True) # compute TT_em_phytomer first_leaf_indexes = phenT_tmp_group.index[0:2] - self.phenT_tmp.loc[ - first_leaf_indexes, "TT_em_phytomer" - ] = phenT_tmp_group.loc[first_leaf_indexes, "TT_em_phytomer"].values[ - : - ] = phenT_tmp_group.loc[ + phenT_tmp_group.loc[first_leaf_indexes, "TT_em_phytomer"] = \ + phenT_tmp_group.loc[ first_leaf_indexes, ["index_phytomer", "TT_col_phytomer"] ].apply( _calculate_TT_em_phytomer, @@ -2920,11 +2920,9 @@ def __call__(self, axeT_, dynT_, decimal_elongated_internode_number, force=True) phenT_tmp_group.index - phenT_tmp_group.index[0:2] ) if len(other_leaves_indexes) != 0: - self.phenT_tmp.loc[ + phenT_tmp_group.loc[ other_leaves_indexes, "TT_em_phytomer" ] = phenT_tmp_group.loc[ - other_leaves_indexes, "TT_em_phytomer" - ].values[:] = phenT_tmp_group.loc[ other_leaves_indexes, ["index_phytomer", "TT_col_phytomer"] ].apply( _calculate_TT_em_phytomer, @@ -2962,9 +2960,7 @@ def __call__(self, axeT_, dynT_, decimal_elongated_internode_number, force=True) a_cohort_before_start_MS_elongation_2, ) - self.phenT_tmp.loc[ - phenT_tmp_group.index, "TT_sen_phytomer" - ] = phenT_tmp_group.loc[:, "TT_sen_phytomer"].values[:] = ( + phenT_tmp_group["TT_sen_phytomer"] = ( phenT_tmp_group["index_phytomer"].apply( _calculate_TT_sen_phytomer, args=( @@ -2984,14 +2980,18 @@ def __call__(self, axeT_, dynT_, decimal_elongated_internode_number, force=True) ) # compute TT_del_phytomer - self.phenT_tmp.loc[ - phenT_tmp_group.index, "TT_del_phytomer" - ] = phenT_tmp_group.loc[:, "TT_del_phytomer"].values[:] = ( + phenT_tmp_group["TT_del_phytomer"] = ( _calculate_TT_del_phytomer( a_cohort_before_start_MS_elongation_1, phenT_tmp_group["TT_sen_phytomer"], ) ) + + # update phenT + self.phenT_tmp.loc[ + phenT_tmp_group.index, + phenT_tmp_group.columns + ] = phenT_tmp_group return self.phenT_tmp diff --git a/src/openalea/adel/plantgen_extensions.py b/src/openalea/adel/plantgen_extensions.py index 8875c82a..db4d8321 100644 --- a/src/openalea/adel/plantgen_extensions.py +++ b/src/openalea/adel/plantgen_extensions.py @@ -638,7 +638,7 @@ def fit_a(self, HS_since_flag, GL): return a, rmse def hs_t1(self, nff=None): - return self.hsfit.HSflag(nff) - self.n_elongated_internode + return float(self.hsfit.HSflag(nff)) - self.n_elongated_internode def dn_nff(self, nff=None): return 0.5 * (self.hs_t2(nff) - self.hs_t2()) @@ -647,7 +647,7 @@ def n1(self, nff=None): return self.GL_bolting + self.dn_nff(nff) def hs_t2(self, nff=None): - return self.hsfit.HSflag(nff) + return float(self.hsfit.HSflag(nff)) def n2(self, nff=None): return self.GL_flag + self.dn_nff(nff) @@ -1116,7 +1116,7 @@ def _dfc(x, y): for c in cardnff.loc[int(nff)].index: d[int(c)] = cardinalities( cohort_nff_modalities[int(nff)][int(c)], - int(cardnff.loc[int(nff), c]), + int(cardnff.loc[int(nff), c].values), ) cohort_nff_cardinalities[int(nff)] = d cohort_nff = { From 19cb37d254b656031d3738acf568db4e49f78e9c Mon Sep 17 00:00:00 2001 From: Christian Fournier Date: Tue, 25 Aug 2026 16:12:16 +0200 Subject: [PATCH 2/4] update and restore tes_Adel_Maxwell --- test/data/test_Adel_Maxwell_plante11/Adel.R | 486 +++-- .../Maxwell_reference_simulation.csv | 1698 +++++++---------- .../data/test_Adel_Maxwell_plante11/UseAdel.R | 126 +- .../data/test_Adel_Maxwell_plante11/setAdel.R | 124 +- test/test_Adel_Maxwell_plante11.py | 8 +- 5 files changed, 1207 insertions(+), 1235 deletions(-) diff --git a/test/data/test_Adel_Maxwell_plante11/Adel.R b/test/data/test_Adel_Maxwell_plante11/Adel.R index 6aaf967b..ec7c4bf8 100644 --- a/test/data/test_Adel_Maxwell_plante11/Adel.R +++ b/test/data/test_Adel_Maxwell_plante11/Adel.R @@ -1,5 +1,5 @@ # -# Ce fichier : Core Code modèle ADEL(cinetique, ssi...) sous R +# Ce fichier : Core Code modele ADEL(cinetique, ssi...) sous R # # Doc input et exemples sont dans docAdel.R # @@ -37,24 +37,66 @@ openapprox <- function(x,y,xout,extrapolate=TRUE) { res } # -#proportion Senesced as a function of Relative ssi and number from top -#TO DO add nf pour gerer pattern special si nf <4 & hasEar -psen <- function(rssi, nt, ssisenT, nf, hasEar=TRUE) { +#senescence pattern for leaf n on an axe bearing nf leaves +# +# 'old' adel model based on csv ssi2sen table +rssi_patternT <- function(n,nf,ssisenT,hasEar=TRUE) { ndelsen <- max(ssisenT$ndel) - ssisenT <- ssisenT[order(ssisenT$ndel),] - t1delsen <- ssisenT$dssit1 - ssisenT$ndel - t2delsen <- ssisenT$dssit2 - ssisenT$ndel - senrate <- ssisenT$rate - psen <- ifelse(rssi<=(-1),0,ifelse(rssi >= 0,1,rssi + 1)) - if (hasEar & nt < ndelsen) { - t0 <- max(nt-ndelsen, nt-nf) - t1 <- max(t1delsen[ndelsen-nt], t0) - t2 <- max(t2delsen[ndelsen-nt], t1) - psen <- openapprox(c(t0,t1,t2),c(0,senrate[ndelsen-nt]*(t1-t0),1),rssi,extrapolate=FALSE) + pattern <- list(t=c(-1, 0),p=c(0,1)) + if (hasEar & n > (nf - ndelsen)) { + idel <- n - (nf - ndelsen) + t0 <- -idel + t1 <- t0 + ssisenT$dssit1[idel] + t2 <- min(t0 + ssisenT$dssit2[idel],nf - n) + if (nf < ndelsen) { + t0 <- -nf + t1 <- min(nf - n, max(t1,t0))#nf - n is complete senescence of last leaf + t2 <- min(nf - n, max(t2,t1)) + } + p1 <- ssisenT$rate[idel] * (t1 - t0) + pattern <- list(t=c(t0,t1,t2),p=c(0,p1,1)) + } + pattern +} +# new model based on r1 and ndel only +# +#ssi table +ssi_table <- function(r1=.1, ndel=3) { + table <- matrix(0,ncol=ndel,nrow=ndel) + table[1,] <- c(rep(r1,ndel-1),1-(ndel-1)*r1) + for (i in 2:ndel) { + if ((ndel-i) >= 1) + table[i,1:(ndel-i)] <- r1 + table[i,ndel-i+2] <- 1 - sum(table[1:(i-1),(ndel-i+2)]) + table[i,ndel-i+1] <- 1 - sum(table[i,]) } - psen + table } - +# +rssi_pattern <- function(n,nf,hasEar=TRUE,pars=list(r1=0.07,ndelsen=3)) { + pattern <- list(t=c(-1, 0),p=c(0,1)) + ndel <- min(pars$ndelsen,nf) + if (ndel > 1 & hasEar & (nf - n) < pars$ndel) { + table <- ssi_table(r1=pars$r1,ndel=ndel) + t <- ((nf - ndel):nf) - n + p <- cumsum(c(0,table[nf - n + 1,])) + pattern <- list(t=t,p=p) + } + pattern +} +# +#proportion Senesced as a function of Relative ssi and number from top +#TO DO add nf pour gerer pattern special si nf <4 & hasEar +psen <- function(rssi, n, nf, hasEar=TRUE, pars = NULL) { + if ('ssisenT' %in% names(pars)) + pat <- rssi_patternT(n, nf, pars$ssisenT,hasEar) + else if ('ssipars' %in% names(pars)) + pat <- rssi_pattern(n,nf,hasEar,pars$ssipars) + else + pat <- rssi_pattern(n,nf,hasEar) + openapprox(pat$t, pat$p, rssi, extrapolate=FALSE) +} + # # kinL : Model for organ extension and leaf senescence # @@ -67,16 +109,19 @@ psen <- function(rssi, nt, ssisenT, nf, hasEar=TRUE) { # #plant are the parameters generated by setAdel # -kinL <- function(x,plant,pars=list("startLeaf" = -0.4, "endLeaf" = 1.6, "stemLeaf" = 1.2)) { +kinL <- function(x,plant,pars=list("leafDuration" = 2, "fracLeaf" = 0.2, "stemDuration" = 2 / 1.2, "dHS_col"=0.2, "dHS_en"=0.)) { #Model parameter - startLeaf <- pars$startLeaf - endLeaf <- pars$endLeaf - stemleaf <- pars$stemLeaf - startE <- endLeaf - endE <- startE + (endLeaf - startLeaf) / stemleaf + apparentLeafDuration <- (1 - pars$fracLeaf) * pars$leafDuration + dhslin <- apparentLeafDuration - pars$dHS_col# delay tip-hslin + startLeaf <- apparentLeafDuration - pars$leafDuration + endLeaf <- apparentLeafDuration + endLeaf1 <- apparentLeafDuration + startE <- endLeaf + pars$dHS_en + endE <- startE + pars$stemDuration #setting output naxe <- nrow(plant$axeT) nf <- plant$axeT$nf + hsf <- plant$axe$HS_final nx <- length(x) res <- vector("list",naxe) names(res) <- plant$axeT$axe @@ -87,46 +132,73 @@ kinL <- function(x,plant,pars=list("startLeaf" = -0.4, "endLeaf" = 1.6, "stemLea if (!is.na(xend)) xa[xa>=xend] <- xend ph <- openapprox(plant$pheno[[a]]$tip,plant$pheno[[a]]$n,xa) + hs <- ph - dhslin + phcol <- openapprox(plant$pheno[[a]]$col,plant$pheno[[a]]$n,xa) ssi <- openapprox(plant$pheno[[a]]$ssi,plant$pheno[[a]]$n,x) disp <- openapprox(plant$pheno[[a]]$disp,plant$pheno[[a]]$n,x) dim <- data.frame(plant$phytoT[,,a]) ped <- plant$pedT[[a]] - kin <- array(NA,c(nx,nf[a]+3,17),list(1:nx,1:(nf[a]+3),c("Ll","Gl","El","Lhem","Lhcol","xh","Lh","ht","Llvis","Glvis","Elvis","Llrolled","Glopen","Llsen","Glsen","Elsen","ntop"))) + kin <- array(NA,c(nx,nf[a]+3,24),list(1:nx,1:(nf[a]+3),c("Ll","Gl","El","Lhem","Lhcol","xh","Lh","ht","Llvis","Glvis","Elvis","Llrolled","Glopen","Llsen","Glsen","Elsen","ntop", "rph", "rssi", "rhs","exposition","lifetime", "age",'is_ligulated'))) nfa <- nf[a] for (i in 1:(nfa+3)) - kin[,i,c("Ll","Gl","El","Llsen","Glsen","Elsen")] <- 0 + kin[,i,c("Ll","Gl","El","Llsen","Glsen","Elsen","Llvis")] <- 0 for (i in seq(nf[a])) { #print(i) rph <- ph - i rssi <- ssi - i + kin[,i,"rph"] <- rph + kin[,i,"rssi"] <- rssi + kin[,i,"rhs"] <- hs - i + xtip <- openapprox(plant$pheno[[a]]$n,plant$pheno[[a]]$tip,i) + xssi <- openapprox(plant$pheno[[a]]$n,plant$pheno[[a]]$ssi,i) + kin[,i,"lifetime"] <- max(0,min(1, (x - xtip) / (xssi - xtip))) + kin[,i,"age"] <- x - xtip + kin[,i,"is_ligulated"] <- ifelse(rph > apparentLeafDuration, 1, 0) #longueur blade+sheath LGl <- approx(c(startLeaf,endLeaf),c(0,dim$Ll[i]+dim$Gl[i]),xout=rph,rule=2)$y + if (i ==1) + LGl <- approx(c(startLeaf,endLeaf1),c(0,dim$Ll[i]+dim$Gl[i]),xout=rph,rule=2)$y + El <- approx(c(startE,endE),c(0,dim$El[i]),xout=rph,rule=2)$y kin[,i,"Ll"] <- sapply(LGl,function(x) min(x,dim$Ll[i])) kin[,i,"Gl"] <- LGl - kin[,i,"Ll"] - kin[,i,"El"] <- approx(c(startE,endE),c(0,dim$El[i]),xout=rph,rule=2)$y - # hidden length of metamer at leaf emergence + kin[,i,"El"] <- El + # hidden length of metamer at leaf emergence (depends only on coordination rule) Lhem <- approx(c(startLeaf,endLeaf),c(0,dim$Ll[i]+dim$Gl[i]),xout=0,rule=2)$y + approx(c(startE,endE),c(0,dim$El[i]),xout=0,rule=2)$y - # hidden length of metamer at collar appearance + # hidden length of metamer at collar appearance (hypothesis: collar app = time at which blade is first completly visible) xcol <- openapprox(plant$pheno[[a]]$n,plant$pheno[[a]]$col,i) rphcol <- openapprox(plant$pheno[[a]]$tip,plant$pheno[[a]]$n,xcol) - i LGcol <- approx(c(startLeaf,endLeaf),c(0,dim$Ll[i]+dim$Gl[i]),xout=rphcol,rule=2)$y - Lhcol <- LGcol - min(LGcol,dim$Ll[i]) + approx(c(startE,endE),c(0,dim$El[i]),xout=rphcol,rule=2)$y - # relative progress in emergence - xh <- max(0, min(1, rph / rphcol)) + Ecol <- approx(c(startE,endE),c(0,dim$El[i]),xout=rphcol,rule=2)$y + Lhcol <- LGcol + Ecol - dim$Ll[i] + xh <- max(0, rph / rphcol) + Lh <- ifelse(xh <= 0, sum(kin[,i,c("Ll","Gl","El")]),Lhem + (Lhcol - Lhem) * min(xh, 1)) + # makes first phyto replace enclosing sheath after emergence + if (i == 1 & xh > 0) { + Lh <- 0 + } else if (xh > 1) { + Lhmat <- dim$Gl[i - 1] + Lh <- Lhcol + (Lhcol - Lhmat) * (xh - 1) + Lh <- ifelse(Lhmat < Lhcol, min(Lhmat, Lh), max(Lhmat, Lh)) + } + # kin[,i,"Lhem"] <- Lhem kin[,i,"Lhcol"] <- Lhcol kin[,i,"xh"] <- xh - kin[,i,"Lh"] <- ifelse(xh <= 0, sum(kin[,i,c("Ll","Gl","El")]),Lhem + (Lhcol - Lhem) * xh) + kin[,i,"Lh"] <- Lh + # Llvis is forced to be compatible with tip-col rates, Hcol/Glvis will be adjusted + kin[,i,"Llvis"] <- max(0,min(dim$Ll[i],LGl + El - Lh)) + if (dim$Ll[i] > 0) + kin[,i,"exposition"] <- kin[,i,"Llvis"] / dim$Ll[i] #senescence - kin[,i,"Llsen"] <- psen(rssi,nf[a]-i, plant$ssisenT, nf[a], plant$axeT$hasEar[a]) * kin[,i,"Ll"] - kin[,i,"Glsen"] <- psen(rssi - 2,nf[a]-i, plant$ssisenT, nf[a], plant$axeT$hasEar[a]) * kin[,i,"Gl"] + kin[,i,"Llsen"] <- psen(rssi, i, nf[a], plant$axeT$hasEar[a], plant) * kin[,i,"Ll"] + kin[,i,"Glsen"] <- psen(rssi - 2, i, nf[a], plant$axeT$hasEar[a], plant) * kin[,i,"Gl"] ## disparition feuille - kin[i <= disp,i,c("Ll","Llsen")] <- 0 + kin[i <= disp,i,c("Ll","Llsen","Llvis","Lh")] <- 0 kin[i <= (disp-1),i,c("Gl","Glsen")] <- 0 } #ear + peduncle elongation - + if (plant$axeT$hasEar[a]) { for (i in (nfa+2):(nfa+3)) kin[,i,"El"] <- ifelse(ph < (nfa + 1.6),0,dim$El[i]) @@ -136,14 +208,15 @@ kinL <- function(x,plant,pars=list("startLeaf" = -0.4, "endLeaf" = 1.6, "stemLea kin[,nfa+1,"El"] = 0 #senescence of stem + ear + awn + peduncle for (i in 1:(nfa+3)) - kin[,i,"Elsen"] <- ifelse(xa < ped$senPed,0,dim$El[i]) + kin[,i,"Elsen"] <- tryCatch(ifelse(xa < ped$senPed | length(dim$El[i]) <= 0,0,dim$El[i]), error = function(e) {stop(paste('plant:', plant$refp, 'axe', a, 'i', i));e}) } - ##disparition axe = longueurs nulles sauf pour entrenoeuds + ##TO DO disparition axe = longueurs nulles pour tout ce qui est sur des entrenoeuds allonges sauf pour entrenoeuds if (!is.na(plant$axeT$disp[a])) - kin[x > plant$axeT$disp[a],,c("Ll","Gl","Llsen","Glsen")] <- 0 + #kin[x > plant$axeT$disp[a],,c("Ll","Gl","Llsen","Glsen")] <- 0 + kin[x > plant$axeT$disp[a],,c("Ll","Gl","El","Llsen","Glsen","Elsen","Llvis","Lh")] <- 0 #rang depuis flag leaf for (d in seq(along=x)) - kin[d,,"ntop"] <- -(seq(nrow(kin[d,,])) - nfa) + kin[d,,"ntop"] <- -(seq(nrow(kin[d,,])) - nfa) res[[a]] <- kin } res @@ -156,17 +229,18 @@ kinL <- function(x,plant,pars=list("startLeaf" = -0.4, "endLeaf" = 1.6, "stemLea #hauteur du tube = depuis la base de l'entreneoud, pour chaque phyto # htube <- function(kin,ht0) { + nmax <- max(seq(nrow(kin))[kin$ntop >=0]) # hauteur base phyto stem <- cumsum(kin$El) - kin$El hcol <- stem + kin$Gl + kin$El + kin$Llrolled - kin$Glopen #ajout ht0,=>parcours hcol de 1 a n-1 - ht <- sapply(seq(along=hcol),function(i) max(c(ht0,hcol)[1:i])) - pmax(0,ht - stem) + hins <- sapply(seq(along=hcol),function(i) max(c(ht0,hcol)[1:i])) + Gt <- sapply(seq(along=hcol),function(i) min(nmax,which.max(c(ht0,hcol)[1:i]) - 1)) + ht <- pmax(0,hins - stem) + data.frame(hins=hins,ht=ht,Gt=Gt) } # -checktube <- function(kin,ht0=0) { - #try to accomodate tube length to emergence constrainst using rolling/opening - n <- max(seq(nrow(kin))[kin$ntop >=0]) +basetube <- function(kin,ht0=0) { # for first phytomer, try to accomodate for ht0 if first sheath is too short if (ht0 > kin$Gl[1] & kin$xh[1] > 0) { delta = ht0 - kin$Gl[1] @@ -177,9 +251,15 @@ checktube <- function(kin,ht0=0) { kin$ht[1] <- 0 kin$ht <- htube(kin,0) } + kin +} +# +checktube <- function(kin,ht0=0) { + n <- max(seq(nrow(kin))[kin$ntop >=0]) + #try to accomodate tube length to emergence constrainst using rolling/opening if (n >=2) for (i in 2:n) { - # for emerged collar, ht must be less than Lh + # for emerged collar, ht must be less than Lh if (kin$xh[i] >= 1) if (kin$ht[i] > kin$Lh[i]) { delta <- kin$ht[i] - kin$Lh[i] @@ -192,18 +272,18 @@ checktube <- function(kin,ht0=0) { dl = min(delta,kin$Gl[i-1]) kin$Glopen[i-1] <- dl } - #update tube + #update tube kin$ht <- htube(kin,0) } #for emegrning leaves ht must be as close to Lh as possible - if (kin$xh[i] > 0 & kin$xh[i] < 1) + if (kin$xh[i] > 0 & kin$xh[i] < 1) if (abs(kin$ht[i] - kin$Lh[i]) > 0) { delta <- kin$Lh[i] - kin$ht[i] if (delta > 0) #tube is too short kin$Llrolled[i-1] = min(delta,kin$Ll[i-1]) else kin$Glopen[i-1] = min(abs(delta),kin$Gl[i-1]+kin$Llrolled[i-1]) - #update tube + #update tube kin$ht <- htube(kin,0) } #for non-emerged leaves, Lh must be less than ht @@ -217,41 +297,88 @@ checktube <- function(kin,ht0=0) { kin } # +# compute whorl adjustements needed to make Lh match ht. +# +whorl <- function(kin) { + do.call('rbind',lapply(split(kin,kin$Gt),function(mat) { + res <- NULL + if (mat$Gt[1] > 0) { + delta <- mean((mat$Lh - mat$ht)[mat$xh > 0],na.rm=TRUE) + if (!is.na(delta)) + if (abs(delta) > 1e-6) + res <- data.frame(Gt=mat$Gt[1],delta=delta) + } + res + })) +} +# #Hmax : hauteur max axe si feuille verticale (pour calcul visibilite talles) # Hmax <- function(kin) { kin <- data.frame(kin) max(cumsum(kin$El)+kin$Gl+kin$Ll) } +# +# ms_pos : position of axis on main stem from axis_id.returns 0 for ms itself +ms_pos <- function(axeid) { + idpos <- strsplit(axeid,split=".",fixed=TRUE)[[1]][1] + if (idpos=="MS") + pos <- 0 + else + pos <- as.numeric(strsplit(idpos,split="T")[[1]][2]) + pos +} +# +# Construct whorl, compute rolling and visibility +# +visibility <- function(kin,ht0=0) { + #initialisation of rolling/opening + kin[,c("Llrolled","Glopen")] <- 0 + kin[,c('hins','ht','Gt')] <- htube(kin,ht0) + if (all(c("xh","Lh") %in% colnames(kin))) { + w <- whorl(kin) + if (length(w) > 0) + for (i in seq(nrow(w))) { + if (w$delta[i] < 0) { + kin$Glopen[w$Gt[i]] <- min(kin$Gl[i],-w$delta[i]) + } else { + kin$Llrolled[w$Gt[i]] <- min(w$delta[i],kin$Llvis[i]) + } + } + kin[,c('hins','ht','Gt')] <- htube(kin,ht0) + } + #kin$Llvis <- pmin(pmax(0,kin$Ll + kin$Gl + kin$El - kin$ht),kin$Ll) + kin$Glvis <- pmin(pmax(0,kin$Gl - kin$Glopen + kin$El - kin$ht),kin$Gl) + kin$Elvis <- pmin(pmax(0,kin$El - kin$ht),kin$El) + kin +} +# #model: kinlist is the output of kinL : all axes computed as ramification emerging from stem (no enclosing sheath). Length of the enclosing sheath is accomodated by rolling first blade if needed. # kinLvis <- function(kinlist,pars=NULL) { res <- kinlist - axes <- as.numeric(names(kinlist)) + axes <- names(kinlist) for (d in seq(dim(kinlist[[1]])[1])) { #Haxe <- sapply(kinlist,function(kinaxe) Hmax(kinaxe[d,,])) for (a in seq(kinlist)) { - kin <- data.frame(kinlist[[a]][d,,]) - #initialisation of rolling/opening - kin[,c("Llrolled","Glopen")] <- 0 + kin <- data.frame(kinlist[[a]][d,,c("ntop","Ll","Gl","El","Llvis","Lhem","Lhcol","xh","Lh","rph","rssi", "rhs")]) # calcul visibilite : talles doivent emerger du tube de la gaine axilante - if (axes[a] == 0) { - ht0 = max(kin$Lhem[1],kin$Gl[1]) - kin$ht <- htube(kin,ht0) - kin <- checktube(kin,ht0) + if (axes[a] == "MS") { + ht0 = kin$Lh[1] + kin <- visibility(kin,ht0) htbm <- kin$ht } else { - axil <- htbm[axes[a] + 1]# tiller a emerges from same tube as leaf a+1 on the bearing axe - kin$ht <- htube(kin,axil) - kin <- checktube(kin,axil) + # numero de la gaine axillante sur le bm + axilrank <- ms_pos(axes[a]) + axil <- htbm[axilrank + 1]# tiller a emerges from same tube as leaf a+1 on the bearing axe + kin <- visibility(kin,axil) } - #calcul Lvis res[[a]][d,,"ht"] <- kin$ht res[[a]][d,,"Llrolled"] <- kin$Llrolled - res[[a]][d,,"Glopen"] <- kin$Glopen - res[[a]][d,,"Llvis"] <- pmin(pmax(0,kin$Ll + kin$Gl + kin$El - kin$ht),kin$Ll) - res[[a]][d,,"Glvis"] <- pmin(pmax(0,kin$Gl + kin$El - kin$ht),kin$Gl) - res[[a]][d,,"Elvis"] <- pmin(pmax(0,kin$El - kin$ht),kin$El) + res[[a]][d,,"Glopen"] <- kin$Glopen + res[[a]][d,,"Llvis"] <- kin$Llvis + res[[a]][d,,"Glvis"] <- kin$Glvis + res[[a]][d,,"Elvis"] <- kin$Elvis } } res @@ -287,9 +414,82 @@ stemElements <- function(desc) { data.frame(metamer=metamer,elt=elt,dl=dl) } # -getdesc <- function(kinlist,plantlist,pars=list("senescence_leaf_shrink" = 0.5,"epsillon" = 1e-6, "dynamic_leaf_angle" = TRUE),t=1) { +# Compute inclinations of stem elements +# +axe_inclination <- function(dat, HS, ht, axename, incBase, dredT, start_incT=1, incT_rate=30,epsillon=1e-6) { + nbphy <- nrow(dat)#inclus ear,ped et awn + # Calcul des inclinaisons de tiges + # 1er phyto = entrenoeud a incT + Einc <- rep(0,nbphy) + Ginc <- rep(0,nbphy) + if (axename == "MS") { + incT <- incBase + } else { + if (HS > start_incT) { + incT <- max(3,min(incBase, incT_rate * (HS - start_incT))) + } else { + incT <- 3 + } + } + Einc[1] <- incT + if (axename != "MS" && incT <= 3) { #Do not represent basal part of first metamer for non inclining tillers + dat$Lv[1] = min(dat$Ll[1],max(0, dat$Ll[1] + dat$Gl[1] + dat$El[1] - ht)) + dat$Lr[1] = min(dat$Lv[1],dat$Lr[1]) + dat$Gv[1] = min(dat$Gl[1],max(0, dat$Gl[1] + dat$El[1] - ht)) + dat$Ev[1] = min(dat$El[1],max(0, dat$El[1] - ht)) + } + # redressement (if any) + if (dredT > 0 & sum(dat$Ev+dat$Gv) > epsillon) { + #distance inserton talle -> extremite stemElements + stem <- stemElements(dat) + alpha <- (90 - incT) * pi / 180 + hc <- cumsum(stem$dl) + dc <- hc * cos(alpha) + #phytomer a redresser + if (any(dc >= dredT)) { + nd <- min(which(dc >= dredT)) + #beta : angle entre l'horizontale et l'element nd pour que son extremite tombe a dredT + if (nd > 1) { + beta <- acos( (dredT - dc[nd - 1]) / (hc[nd] - hc[nd - 1]) ) + inc <- -(beta - alpha) / pi * 180 + if (stem$elt[nd] == "en") { + Einc[stem$metamer[nd]] <- inc + } else { + Ginc[stem$metamer[nd]] <- inc + } + if (nd < nrow(stem)) { + inc <- - (pi / 2 - beta) / pi * 180 + if (stem$elt[nd+1] == "en") { + Einc[stem$metamer[nd+1]] <- inc + } else { + Ginc[stem$metamer[nd+1]] <- inc + } + } + } else {#incT too large + beta <- acos(dredT / hc[1]) + Einc[1] <- (pi / 2 - beta) / pi * 180 + if (nrow(stem) > 1) { + inc <- -Einc[1] + if (stem$elt[2] == "en") { + Einc[stem$metamer[2]] <- inc + } else { + Ginc[stem$metamer[2]] <- inc + } + } + } + } + } + dat$Einc <- Einc + dat$Ginc <- Ginc + dat +} +# +getdesc <- function(kinlist,plantlist,pars=list("senescence_leaf_shrink" = 0.5,"epsillon" = 1e-6, "dynamic_leaf_angle" = TRUE, 'HSstart_inclination_tiller' = 1, 'rate_inclination_tiller' = 30, 'drop_empty'=TRUE),t=1) { epsillon = pars$epsillon fshrink = pars$senescence_leaf_shrink + start_incT = pars$HSstart_inclination_tiller + incT_rate = pars$rate_inclination_tiller + drop_empty = pars$drop_empty res <- NULL for (p in seq(kinlist)) { #print(p) @@ -297,14 +497,14 @@ getdesc <- function(kinlist,plantlist,pars=list("senescence_leaf_shrink" = 0.5," kin <- kinlist[[p]] plant <- plantlist[[p]] pldesc <- NULL - + for (a in seq(kin)) { #print(paste("axe",a)) axename <- names(kin)[a] - numaxe <- as.numeric(axename) - dat <- data.frame(kin[[a]][t,,c("Ll","Gl","El","Llvis","Glvis","Elvis","Llsen","Glsen","Elsen")]) + #numaxe <- as.numeric(axename) + dat <- data.frame(kin[[a]][t,,c("Ll","Gl","El","Llvis","Glvis","Elvis","Llsen","Glsen","Elsen","Llrolled")]) if (sum(dat) > epsillon | a == 1) {#do not represent empty tillers (BUT main stems are needed even if empty! ) - colnames(dat) <- c("Ll","Gl","El","Lv","Gv","Ev","Lsen","Gsen","Esen") + colnames(dat) <- c("Ll","Gl","El","Lv","Gv","Ev","Lsen","Gsen","Esen","Lr") # infos brutes de plant parameters datp <- data.frame(plant$phytoT[,,a]) dataxe <- plant$axeT[a,] @@ -312,67 +512,19 @@ getdesc <- function(kinlist,plantlist,pars=list("senescence_leaf_shrink" = 0.5," nbphy <- nrow(dat)#inclus ear,ped et awn datp <- datp[1:nbphy,] # Calcul des inclinaisons de tiges - # 1er phyto = entrenoeud a incT - Einc <- rep(0,nbphy) - Ginc <- rep(0,nbphy) - if (numaxe == 0) { - incT <- dataxe$incT + HS_axe <- kin[[a]][t,1,"rhs"] + 1 + if (axename =="MS") { + ht <- 0 } else { - en <- which(datp$El > epsillon) - if (length(en) > 0) { - firstEn <- min(en) - incT <- max(3,dataxe$incT * dat$El[firstEn] / datp$El[firstEn]) - } else { - incT <- 3 - } + axilrank <- ms_pos(axename) + ht <- kin$MS[t,axilrank+1,"ht"] # length of the tube the axe emerge from } - Einc[1] <- incT - # redressement (if any) - if (dataxe$dredT > 0 & sum(dat$Ev+dat$Gv) > epsillon) { - #distance inserton talle -> extremite stemElements - stem <- stemElements(dat) - alpha <- (90 - incT) * pi / 180 - hc <- cumsum(stem$dl) - dc <- hc * cos(alpha) - #phytomer a redresser - if (any(dc >= dataxe$dredT)) { - nd <- min(which(dc >= dataxe$dredT)) - #beta : angle entre l'horizontale et l'element nd pour que son extremite tombe a dredT - if (nd > 1) { - beta <- acos( (dataxe$dredT - dc[nd - 1]) / (hc[nd] - hc[nd - 1]) ) - inc <- -(beta - alpha) / pi * 180 - if (stem$elt[nd] == "en") { - Einc[stem$metamer[nd]] <- inc - } else { - Ginc[stem$metamer[nd]] <- inc - } - if (nd < nrow(stem)) { - inc <- - (pi / 2 - beta) / pi * 180 - if (stem$elt[nd] == "en") { - Einc[stem$metamer[nd+1]] <- inc - } else { - Ginc[stem$metamer[nd+1]] <- inc - } - } - } else {#incT too large - beta <- acos(dataxe$dredT / hc[1]) - Einc[1] <- (pi / 2 - beta) / pi * 180 - if (nrow(stem) > 1) { - inc <- -Einc[1] - if (stem$elt[2] == "en") { - Einc[stem$metamer[2]] <- inc - } else { - Ginc[stem$metamer[2]] <- inc - } - } - } - } - } + dat <- axe_inclination(dat, HS_axe, ht, axename, dataxe$incT, dataxe$dredT, start_incT, incT_rate) #azimuts : Attention new 21 fev 2011 : azimuts en relatif / phytomere precedent ! Laz <- datp$Azim Laz[1] <- dataxe$azT - + # control of blade basal inclination (to be moved in kinL?) Linc <- ifelse(datp$Ll > 0,dat$Lv / datp$Ll,1) # setup of Lindex (for Tino, no more needed) as a function of leaf stage @@ -383,15 +535,29 @@ getdesc <- function(kinlist,plantlist,pars=list("senescence_leaf_shrink" = 0.5," Epos <- c(rep(2,nbleaf),4,4,4) pogreen <- rep(1,nbphy) posen <- rep(2,nbphy) + rph <- kin[[a]][t,,"rph"] + rssi <- kin[[a]][t,,"rssi"] + rhs <- kin[[a]][t,,"rhs"] + exposition <- kin[[a]][t,,"exposition"] + lifetime <- kin[[a]][t,,"lifetime"] + age <- kin[[a]][t,,"age"] + is_ligulated <- kin[[a]][t,,"is_ligulated"] + mtype <- c(rep('vegetative',nbleaf),'peduncle','ear','awn') # pldesc <- rbind(pldesc, cbind(data.frame(refplant_id = rep(refp,nbphy), - axe_id = rep(a,nbphy), - axe=rep(as.numeric(axename),nbphy), + axe_id = rep(axename,nbphy), + ms_insertion=rep(ms_pos(axename),nbphy), + az_insertion = rep(dataxe$azTb,nbphy), + nff = dataxe$nf, + nff_end = dataxe$nf_end, + HS_final= dataxe$HS_final, + hasEar = dataxe$hasEar, numphy=1:nbphy, + ntop= dataxe$nf + 1 - (1:nbphy), L_shape=datp$Ll, Lw_shape=datp$Lw, - LsenShrink = fshrink, + LsenShrink = rep(fshrink,nbphy), LcType=datp$Lindex, LcIndex=datp$Lseed, Linc=Linc, @@ -399,32 +565,78 @@ getdesc <- function(kinlist,plantlist,pars=list("senescence_leaf_shrink" = 0.5," Lpo=pogreen, Lpos=posen, Gd=datp$Gd, - Ginc=Ginc, Gpo=pogreen, Gpos=posen, Ed=datp$Ed, - Einc=Einc, Epo=Epo, - Epos=Epos), + Epos=Epos, + rph=rph, + rssi=rssi, + rhs=rhs, + exposition=exposition, + lifetime=lifetime, + m_type=mtype, + age=age, + is_ligulated = is_ligulated +), dat)) } } - if (!is.null(pldesc)) + if (!is.null(pldesc)) { + if (drop_empty) { + # option allows filtering non growing metamers, + ms <- pldesc[pldesc$axe_id =='MS',] + tillers <- pldesc[pldesc$axe_id !='MS',] + #keep at least two row of MS to avoid degenerated one-line dataframe in python + lmetamer <- apply(na.omit(ms[,c('Ll','El','Gl')]),1,sum) + last <- 1 + if (sum(lmetamer) > 0) + last <- max(which(lmetamer > 0)) + pldesc <- ms[1:max(2,last),] + if (nrow(tillers) > 0) { + tillers <- do.call('rbind',lapply(split(tillers,tillers$axe_id, drop=TRUE), function(axdesc) { + lmetamer <- apply(na.omit(axdesc[,c('Ll','El','Gl')]),1,sum) + last <- 1 + if (sum(lmetamer) > 0) + last <- max(which(lmetamer > 0)) + axdesc[1:last,] + })) + pldesc <- rbind(pldesc,tillers) + } + } res <- rbind(res,cbind(plant=p,pldesc)) + } } - res } # # Checker for axe dynamics of the plants sampled at dates # -checkAxeDyn <- function(dates,plants) { +checkAxeDyn <- function(dates,plants, density=1) { em <- unlist(sapply(plants,function(p) p$axeT$emf1)) + end <- unlist(sapply(plants,function(p) p$axeT$end)) disp <- unlist(sapply(plants,function(p) p$axeT$disp)) + em_p <- unlist(sapply(plants,function(p) p$axeT$emf1[p$axeT$axe=='MS'])) + disp_p <- unlist(sapply(plants,function(p) p$axeT$disp[p$axeT$axe=='MS'])) disp[is.na(disp)] <- max(dates) + 1 - nbaxes <- sapply(dates,function(d) length(em[em <=d]) - length(disp[disp <= d])) - nbaxes + end[is.na(end)] <- max(dates) + 1 + disp_p[is.na(disp_p)] <- max(dates) + 1 + emited <- sapply(dates,function(d) length(em[em <=d])) + stoped <- sapply(dates,function(d) length(end[end <=d])) + disped <- sapply(dates,function(d) length(disp[disp <=d])) + emited_p <- sapply(dates,function(d) length(em_p[em_p<=d])) + disped_p <- sapply(dates,function(d) length(disp_p[disp_p<=d])) + nbaxes <- emited + nbaxes_growing <- emited - stoped + nbaxes_present <- emited - disped + nbpl <- emited_p - disped_p + nbpld <- length(plants) + data.frame(TT=dates, nbplants=nbpl/nbpld*density, nbaxes_emited=nbaxes/nbpld*density, nbaxes_growing=nbaxes_growing/nbpld*density, nbaxes_present=nbaxes_present/nbpld*density) } - - +# +getAxeT <- function(plants) do.call('rbind', mapply(function(idpl,pl) {df=pl$axeT;df$plant=idpl;df},seq(plants),plants,SIMPLIFY=FALSE)) +# +getPhenT <- function(plants, axe='MS') do.call('rbind', mapply(function(idpl,pl) {df=pl$pheno[[axe]];df$plant=idpl;df},seq(plants),plants,SIMPLIFY=FALSE)) +# +getPhytoT <- function(plants, axe='MS') do.call('rbind', mapply(function(idpl,pl) {df=data.frame(pl$phytoT[,,axe]);df$plant=idpl;df$axe=axe;df$n=seq(nrow(df));df},seq(plants),plants,SIMPLIFY=FALSE)) diff --git a/test/data/test_Adel_Maxwell_plante11/Maxwell_reference_simulation.csv b/test/data/test_Adel_Maxwell_plante11/Maxwell_reference_simulation.csv index 08e921d6..cd3ee83b 100644 --- a/test/data/test_Adel_Maxwell_plante11/Maxwell_reference_simulation.csv +++ b/test/data/test_Adel_Maxwell_plante11/Maxwell_reference_simulation.csv @@ -1,1022 +1,676 @@ -"TT","plant","refplant_id","axe_id","axe","numphy","L_shape","Lw_shape","LsenShrink","LcType","LcIndex","Linc","Laz","Lpo","Lpos","Gd","Ginc","Gpo","Gpos","Ed","Einc","Epo","Epos","Ll","Gl","El","Lv","Gv","Ev","Lsen","Gsen","Esen" -0,1,11,1,0,1,8.7,0.381001176,0.5,11,12,0.595690978525263,133.964603869244,1,2,0.4,0,1,2,0,2.8893505372107,1,2,5.18251151316979,0,0,5.18251151316979,0,0,0,0,0 -0,1,11,1,0,2,7.6000000022,0.372438537017125,0.5,10,87,0,176.471638712101,1,2,0.4,0,1,2,0,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,3,7.0333333347,0.452776836758985,0.5,9,68,0,191.090725371614,1,2,0.4,0,1,2,0,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,4,8.99999999213333,0.540027999650995,0.5,8,96,0,175.21046990063,1,2,0.4,0,1,2,0,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,5,10.34999999325,0.603818699681047,0.5,7,63,0,179.462403464131,1,2,0.4,0,1,2,0,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,6,10.500000005,0.75168550170082,0.5,6,89,0,182.986974762753,1,2,0.39999999823,0,1,2,0,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,7,11.5000000204,1.09184950060959,0.5,5,80,0,179.612478422932,1,2,0.045999999996,0,1,2,1.57599991010889e-10,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,8,16.6000000117,1.24424800029796,0.5,4,93,0,161.173056084663,1,2,0.044999999997,0,1,2,0.0393999999943,0,1,2,0,0,0,0,0,0,0,0,0 -0,1,11,1,0,9,20.4999999842,1.34356874993896,0.5,3,116,0,199.642399116419,1,2,0.044000000002,0,1,2,0.0375000000022,0,1,2,0,0,0,0,0,0,0,0,0 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Returns a list of string # -runAdel <- function(dates,plants,pars = list('senescence_leaf_shrink' = 0.5,'startLeaf' = -0.4, 'endLeaf' =1.6, 'stemLeaf' = 1.2,'epsillon' = 1e-6)) { +runAdel <- function(dates,plants,pars = list('senescence_leaf_shrink' = 0.5, 'leafDuration' = 2, 'fracLeaf' = 0.2, 'stemDuration' = 2 / 1.2, 'dHS_col'=0.2, 'dHS_en'=0.,'epsillon' = 1e-6, 'HSstart_inclination_tiller' = 1, 'rate_inclination_tiller' = 30,'drop_empty'=TRUE)) { out <- vector("list",length(dates)) #deals with python-flatten lists if ("axeT" %in% names(plants)) { @@ -17,52 +17,69 @@ runAdel <- function(dates,plants,pars = list('senescence_leaf_shrink' = 0.5,'sta desc <- getdesc(kinlist,plants,pars) #chn <- genString(desc,pars) if (!is.null(desc)) - out[[i]] <- cbind(date=dates[i],desc) + out[[i]] <- cbind(TT=dates[i],desc) } out } # #set Adel from parameters # -setAdeluser <- function(devT,geoLeaf,geoAxe,nplants,sample='random',seed=NULL,xy_db=NULL,sr_db=NULL) { +setAdeluser <- function(devT,geoLeaf,geoAxe,nplants,sample='random',seed=NULL,xy_db=NULL,sr_db=NULL, ssipars=NULL) { setAdel(devT$axeT,devT$dimT,devT$phenT,devT$earT,devT$ssisenT,geoLeaf,geoAxe,nplants,sample,seed,xy_db,sr_db) } # - #build devT from csv parameter files +#build devT from csv parameter files # -devTcsv <- function(axeTfile,dimTfile,phenTfile,earTfile=NULL,ssisenTfile=NULL,type=1) { +readCsv <- function(file,type=1) { reader <- get(ifelse(type==1,"read.csv","read.csv2")) - #type 1 : "." for decimal, "," for separator - #type 2: "," for decimal, ";" for separator - + #type 1 : "." for decimal, "," for separator + #type 2: "," for decimal, ";" for separator + data <- reader(file) + #filter empty columns + Filter(function(x)!all(is.na(x)), data) +} +# +devTcsv <- function(axeTfile,dimTfile,phenTfile,earTfile=NULL,ssisenTfile=NULL,type=1) { + #conversion nouvelle nomencalture #axeT - axeT <- reader(axeTfile) + axeT <- readCsv(axeTfile) + # nouvelle convention (kirby) id_axe + if ("axe" %in% colnames(axeT)) + axeT$axe <- ifelse(axeT$axe==0,"MS",paste("T",axeT$axe,sep="")) + # + #conversions nouveaux noms + conv <- c("plant","axe","nf","end","disp","dimIndex","phenIndex","earIndex","emf1","ligf1","senf1","dispf1") names(conv) <- c("id_plt","id_axis","N_phytomer","TT_stop_axis","TT_del_axis","id_dim","id_phen","id_ear","TT_em_phytomer1","TT_col_phytomer1","TT_sen_phytomer1","TT_del_phytomer1") if (all(conv %in% colnames(axeT))) colnames(axeT)[colnames(axeT) %in% conv] <- names(conv)[na.omit(match(colnames(axeT),conv))] else if (!all(names(conv) %in% colnames(axeT))) stop(paste("axeT : missing data: ",paste(names(conv)[!names(conv) %in% colnames(axeT)],collapse=" "))) + # force numeric conversion + numcols <- names(conv)[-grep('id_axis',names(conv))] + for (w in numcols) + axeT[,w] <- as.numeric(as.character(axeT[,w])) #dimT - dimT <- reader(dimTfile) + dimT <- readCsv(dimTfile, type) conv <- c("index","nrel","Ll","Lw","Gl","Gd","El","Ed") names(conv) <- c("id_dim","index_rel_phytomer","L_blade","W_blade","L_sheath","W_sheath","L_internode","W_internode") if (all(conv %in% colnames(dimT))) colnames(dimT)[colnames(dimT) %in% conv] <- names(conv)[na.omit(match(colnames(dimT),conv))] - else if (!all(names(conv) %in% colnames(dimT))) + else if (!all(names(conv[-grep('nrel',conv)]) %in% colnames(dimT))) stop(paste("dimT : missing data: ",paste(names(conv)[!names(conv) %in% colnames(dimT)],collapse=" "))) # phenT - phenT = reader(phenTfile) + phenT = readCsv(phenTfile, type) conv <- c("index","nrel","tip","col","ssi","disp") names(conv) <- c("id_phen","index_rel_phytomer","dTT_em_phytomer","dTT_col_phytomer","dTT_sen_phytomer","dTT_del_phytomer") if (all(conv %in% colnames(phenT))) colnames(phenT)[colnames(phenT) %in% conv] <- names(conv)[na.omit(match(colnames(phenT),conv))] - else if (!all(names(conv) %in% colnames(phenT))) + else if (!all(names(conv[-grep('nrel',conv)]) %in% colnames(phenT))) stop(paste("phenT : missing data: ",paste(names(conv)[!names(conv) %in% colnames(phenT)],collapse=" "))) + phenT <- phenT[!is.na(phenT$id_phen),] # earT if (!is.null(earTfile)) { - earT <- reader(earTfile) + earT <- readCsv(earTfile, type) conv <- c("index","em_ear","em_ped","end_gf","l_ped","d_ped","l_ear","Sp_ear","l_ear_awn") names(conv) <- c("id_ear","dTT_em_ear","dTT_em_peduncle","TT_z92","L_peduncle","W_peduncle","L_ear","A_ear","L_spike") if (all(conv %in% colnames(earT))) @@ -74,7 +91,7 @@ devTcsv <- function(axeTfile,dimTfile,phenTfile,earTfile=NULL,ssisenTfile=NULL,t earT <- NULL if (!is.null(ssisenTfile)) - ssisenT <- reader(ssisenTfile) + ssisenT <- readCsv(ssisenTfile, type) else ssisenT <- NULL list(axeT = axeT, @@ -84,33 +101,31 @@ devTcsv <- function(axeTfile,dimTfile,phenTfile,earTfile=NULL,ssisenTfile=NULL,t ssisenT = ssisenT) } # -readCsv <- function(file,type=1) { - reader <- get(ifelse(type==1,"read.csv","read.csv2")) - #type 1 : "." for decimal, "," for separator - #type 2: "," for decimal, ";" for separator - reader(file) -} -# # #geoAxe from parameter # -genGeoAxe <- function(azTM = 75,dazT = 5,incBmM = 2,dincBm = 2,incT = 60,dincT = 5,depMax = 7) { +genGeoAxe <- function(azTM = 75,dazT = 5,incBmM = 2,dincBm = 2,incT = 60,dincT = 5,depMax = 7,depMin = 1.5,dazTb=60) { list( azT = function(a) { - ifelse(a == 0, + ifelse(a == 'MS', runif(1) * 360,#plant azimuth azTM + (runif(1) - .5) * dazT) }, + azTb = function(a) { + ifelse(a == 'MS', + 0, + (runif(1) - .5) * dazTb) + }, incT = function(a) { - ifelse(a == 0, + ifelse(a == 'MS', incBmM + (runif(1) - .5) * dincBm, incT + (runif(1) - .5) * dincT) }, dredT = function(a) { #1.5 is an offset to avoid tiller superposed to mainstem - ifelse(a == 0, + ifelse(a == 'MS', 0, - 1.5 + runif(1) * (depMax-1.5)) + depMin + runif(1) * (depMax-depMin)) } ) } @@ -119,21 +134,23 @@ genGeoAxe <- function(azTM = 75,dazT = 5,incBmM = 2,dincBm = 2,incT = 60,dincT = # genGeoLeaf <- function(ntoplim = 4,dazTop = 60,dazBase = 30,topIndex=TRUE) { list( - Azim = function(a,n,ntop) { + Azim = function(a,n,nf) { + ntop = nf - n ifelse(ntop <= ntoplim, 180 + dazTop * (runif(1) - .5), 180 + dazBase * (runif(1) - .5)) }, - Lindex = function(a,n,ntop) { + Lindex = function(a,n,nf) { ifelse(topIndex, - ntop + 1, + nf - n + 1, n)} ) } # # Compute surfaces from lengths in canopy table # -leafSurface <- function(shape,scL,scW,from=0,to=1) { +leafSurface <- function(shape_db, shape_index, scL,scW,from=0,to=1) { + shape <- shape_db[[shape_index]] if (is.na(scL) | is.na(scW) | is.null(shape)) res <- NA else if (to <= from | scL == 0 | scW == 0) @@ -149,25 +166,52 @@ leafSurface <- function(shape,scL,scW,from=0,to=1) { # canL2canS <- function(canL,sr_db,leaf_shrink=NULL) { canS <- canL + canS$ntop <- canL$nff - canL$numphy + 1 if (all(canS$LcIndex <= 1)) {#leaf shape has not been set by setAdel print("canL2canS : can't compute Blade surfaces : SR data not connected to setAdel!!!") } else { - rg <- ifelse(is.na(canS$LcType) | canS$LcType == 0, 1,canS$LcType) - canS$SLl <- sapply(seq(nrow(canS)),function(x) leafSurface(sr_db[[rg[x]]],canS$Ll[x],canS$Lw[x])) - # - base <- canS$Ll - canS$Lsen - canS$Lv - top <- canS$Ll - canS$Lsen - canS$Slv <- sapply(seq(nrow(canS)),function(x) leafSurface(sr_db[[rg[x]]],canS$Ll[x],canS$Lw[x],base[x] / canS$Ll[x],top[x] / canS$Ll[x])) + rg <- ifelse(is.na(canS$LcType) | canS$LcType <= 0, 1,canS$LcType)#handle phytomers above nff (peduncle, ear, awn) for which Lindex = zero + shapes <- sr_db + Lref <- canS$L_shape + Lwref <- canS$Lw_shape + Lwsen <- canS$Lw_shape * canS$LsenShrink + # add some info on visibility + canS$Lvsen <- pmin(canS$Lv,canS$Lsen) + canS$Lvgreen <- canS$Lv - canS$Lvsen + canS$Gvsen <- pmin(canS$Gv,canS$Gsen) + canS$Gvgreen <- canS$Gv - canS$Gvsen + canS$Evsen <- pmin(canS$Ev,canS$Esen) + canS$Evgreen <- canS$Ev - canS$Evsen + # + #add info on distances base of axes -> col + g <- list(canS$plant,canS$axe_id) + canS <- unsplit(lapply(split(canS,g), function(dat) {dat$d_basecol <- cumsum(dat$El) + dat$Gl;dat}),g) + # + canS$S_shape <- sapply(seq(nrow(canS)),function(x) leafSurface(shapes, rg[x], Lref[x], Lwref[x])) + # + base <- 1 - (canS$Lvsen + canS$Lvgreen) / Lref + top <- 1 - canS$Lvsen / Lref + canS$Slvgreen <- sapply(seq(nrow(canS)),function(x) leafSurface(shapes, rg[x], Lref[x], Lwref[x], base[x], top[x])) + # + base <- 1 - canS$Lvsen / Lref + canS$Slvsen <- sapply(seq(nrow(canS)),function(x) leafSurface(shapes, rg[x], Lref[x], Lwsen[x], base[x], 1)) + # + canS$Slv <- canS$Slvgreen + canS$Slvsen + # + top <- 1 - canS$Lsen / Lref + Shgreen <- sapply(seq(nrow(canS)),function(x) leafSurface(shapes, rg[x], Lref[x], Lwref[x], 0, top[x])) + # + base <- 1 - canS$Lsen / Lref + canS$Slsen <- sapply(seq(nrow(canS)),function(x) leafSurface(shapes, rg[x], Lref[x], Lwsen[x], base[x], 1)) # - base <- canS$Ll - canS$Lsen - canS$SLsen <- sapply(seq(nrow(canS)),function(x) leafSurface(sr_db[[rg[x]]],canS$Ll[x],canS$Lw[x]*canS$LsenShrink[x],base[x] / canS$Ll[x],1)) + canS$SLl <- Shgreen + canS$Slsen } #names(res)[match(c("Ll","Lsen","Lv"),names(res))] <- c("SLl","SLsen","SLv") # - for (w in c("Gl","Gv","Gsen")) + for (w in c("Gl","Gv","Gsen","Gvsen","Gvgreen")) canS[[paste("S",w,sep="")]] <- canS[[w]] * pi * canS$Gd - for (w in c("El","Ev","Esen")) + for (w in c("El","Ev","Esen","Evsen","Evgreen")) canS[[paste("S",w,sep="")]] <- canS[[w]] * pi * canS$Ed canS } diff --git a/test/data/test_Adel_Maxwell_plante11/setAdel.R b/test/data/test_Adel_Maxwell_plante11/setAdel.R index d9909b1e..9374d667 100644 --- a/test/data/test_Adel_Maxwell_plante11/setAdel.R +++ b/test/data/test_Adel_Maxwell_plante11/setAdel.R @@ -17,6 +17,10 @@ openapprox <- function(x,y,xout,extrapolate=TRUE) { lastrate <- 0 firstrate <- 0 } + if (!is.finite(lastrate)) # last two x identical + lastrate <- diff(xy[twolast,2]) + if (!is.finite(firstrate)) # last two x identical + firstrate <- diff(xy[1:2,2]) extrax <- xout > xy[last,1] res[extrax] <- xy[last,2] + lastrate * (xout[extrax] - xy[last,1]) extrax <- xout < xy[1,1] @@ -46,37 +50,62 @@ setCanopy <- function(canT, nplants=1, randomize = TRUE, seed = NULL) { } # -predictDim <- function(dimT,index,nf) { +predictDim <- function(dimT,index,nf,nf_end) { res <- NULL if (!index %in% dimT$index) stop(paste("setAdel : dimIndex", index, "not found in dimTable")) else { - nout <- seq(nf)/nf dim <- dimT[dimT$index == index,] - out <- vector("list",ncol(dimT)-2) - names(out) <- colnames(dim)[-match(c('index','nrel'),colnames(dim))] - for (w in names(out)) - out[[w]] <- approx(dim$nrel,dim[,w],nout,rule=2)$y - res <- data.frame(do.call("cbind",out)) + if ('index_phytomer' %in% colnames(dimT)) {# index is absolute + headers <- c('index_phytomer', 'index', 'nrel') + headers <- headers[headers %in% colnames(dim)] + out <- vector("list",ncol(dimT) - length(headers)) + names(out) <- colnames(dim)[-match(headers,colnames(dim))] + for (w in names(out)) + out[[w]] <- c(dim[seq(nf_end),w], rep(0, nf - nf_end)) + res <- data.frame(do.call("cbind",out)) + } else {#index is relative to n phytomer potentiel + nout <- seq(nf)/nf + out <- vector("list",ncol(dimT)-2) + names(out) <- colnames(dim)[-match(c('index','nrel'),colnames(dim))] + for (w in names(out)) + out[[w]] <- approx(dim$nrel,dim[,w],nout,rule=2)$y + res <- data.frame(do.call("cbind",out)) + } } res } # -predictPhen <- function(phenT,index,nf,datesf1) { +predictPhen <- function(phenT,index,nf,datesf1,nf_end) { if (!"disp"%in%colnames(phenT)) - stop("Missing input for leaf desapearance in phenT (see docAdel.txt") + stop("setAdel: Missing input for leaf desapearance in phenT (see docAdel.txt") res <- NULL if (!index %in% phenT$index) - stop(paste("setAdel : phenIndex", index, "not found in phenTable")) + stop(paste("setAdel : phenIndex/id_phen", index, "not found in phenTable")) else { - nout <- c(0,seq(nf))/nf phen <- phenT[phenT$index == index,] - out <- vector("list",ncol(phenT) -2) - names(out) <- colnames(phen)[-match(c('index','nrel'),colnames(phen))] + headers <- c('index_phytomer', 'index', 'nrel') + headers <- headers[headers %in% colnames(phen)] + out <- vector("list",ncol(phen) - length(headers)) + names(out) <- colnames(phen)[-match(headers,colnames(phen))] names(datesf1) <- c("tip","col","ssi","disp") + # + if ('index_phytomer' %in% colnames(phen)) {# index is absolute + nin <- phen$index_phytomer + nout <- c(0,seq(nf)) + if (length(na.omit(phen$index_phytomer)) < 2) + stop(paste("setAdel : not enough data in phenTable for id_phen:",index)) + } else {#index is relative to n phytomer potentielnout <- c(0,seq(nf))/nf + nin <- phen$nrel + nout <- c(0,seq(nf))/nf + if (length(na.omit(phen$nrel)) < 2) + stop(paste("setAdel : not enough data in phenTable for id_phen:",index)) + } for (i in 1:4) { w <- names(out)[i] - out[[w]] <- openapprox(phen$nrel,phen[,w],nout) + datesf1[[w]] + if (length(na.omit(phen[,w])) < 2) + stop(paste("setAdel : not enough data in phenTable for id_phen:",index, 'column:', w)) + out[[w]] <- openapprox(nin,phen[,w],nout,extrapolate=FALSE) + datesf1[[w]] } res <- data.frame(cbind(n=c(0,seq(nf)),do.call("cbind",out))) } @@ -98,11 +127,22 @@ predictPed <- function(pheno,phyto,index,nf,earT) { #setAdel performs the dressing (geometry, tiller number ...) of plants from parameters and duplicate them for a given number of outputed plants # -setAdel <- function(axeT,dimT,phenT,earT,ssisenT,geoLeaf,geoAxe,nplants=1,sample='random',seed=NULL,xy_db=NULL,sr_db=NULL) { +#debug load defaults +#axeT=devT$axeT;dimT=devT$dimT;phenT=devT$phenT;earT=devT$earT;ssisenT=devT$ssisenT;nplants=1;sample='random';seed=NULL;xy_db=xydb;sr_db=srdb;ssipars=NULL +# +setAdel <- function(axeT,dimT,phenT,earT,ssisenT,geoLeaf,geoAxe,nplants=1,sample='random',seed=NULL,xy_db=NULL,sr_db=NULL,ssipars=NULL) { + # Handle semantic of nf, N_phytomer and N_phytomer_potentiel, that depend on the history of adel. + # + if ("nf"%in%colnames(axeT)) {#first version of adel: N_phytomer_potentiel = nf & N_phytomer = nf + colnames(axeT)[match("nf",colnames(axeT))] <- "N_phytomer_potentiel" + axeT <- cbind(axeT,N_phytomer = axeT$N_phytomer_potentiel) + } else if (!"N_phytomer_potentiel"%in%colnames(axeT)) {# old plantgen (before may 2015) + axeT <- cbind(axeT,N_phytomer_potentiel = axeT$N_phytomer) + } #prise en chage nouveaux noms - conv <- c("id_plt","id_axis","N_phytomer","TT_stop_axis","TT_del_axis","id_dim","id_phen","id_ear","TT_em_phytomer1","TT_col_phytomer1","TT_sen_phytomer1","TT_del_phytomer1") - names(conv) <- c("plant","axe","nf","end","disp","dimIndex","phenIndex","earIndex","emf1","ligf1","senf1","dispf1") + conv <- c("id_plt","id_axis","N_phytomer","N_phytomer_potentiel","TT_stop_axis","TT_del_axis","id_dim","id_phen","id_ear","TT_em_phytomer1","TT_col_phytomer1","TT_sen_phytomer1","TT_del_phytomer1") + names(conv) <- c("plant","axe","nf_end","nf","end","disp","dimIndex","phenIndex","earIndex","emf1","ligf1","senf1","dispf1") colnames(axeT)[colnames(axeT) %in% conv] <- names(conv)[na.omit(match(colnames(axeT),conv))] # conv <- c("id_dim","index_rel_phytomer","L_blade","W_blade","L_sheath","W_sheath","L_internode","W_internode") @@ -133,8 +173,9 @@ setAdel <- function(axeT,dimT,phenT,earT,ssisenT,geoLeaf,geoAxe,nplants=1,sample earT <- data.frame(index = 1,em_ear = 100, em_ped = 200, end_gf = 1000, l_ped = 0, d_ped = 0, l_ear = 0, Sp_ear = 0, l_ear_awn = 0) } - if (is.null(ssisenT)) - ssisenT <- data.frame(ndel=1:4,rate1=0.07,dssit1=c(0,1.2,2.5,3),dssit2=c(1.2,2.5,3.7,4)) + if (is.null(ssisenT)) + if (is.null(ssipars))#otherwise, use ssipars + ssisenT <- data.frame(ndel=1:4,rate1=0.07,dssit1=c(0,1.2,2.5,3),dssit2=c(1.2,2.5,3.7,4)) if (!"incB"%in%colnames(dimT)) dimT <- cbind(dimT,incB = -999,dincB = 0) @@ -143,49 +184,63 @@ setAdel <- function(axeT,dimT,phenT,earT,ssisenT,geoLeaf,geoAxe,nplants=1,sample useAzim <- TRUE dimT <- cbind(dimT,pAngle = -999,dpAngle = 0) } + + if (!"HS_final"%in%colnames(axeT)) + axeT <- cbind(axeT, HS_final = ifelse(is.na(axeT$end), 1, NA) * pmin(axeT$nf_end,axeT$nf)) + + + plantdb <- by(axeT,list(axeT$plant),function(x) { - if (! 0 %in% x$axe) + if (! "MS" %in% x$axe) stop(paste("No main stem found for plant",x$plant[1],", Check axeT table")) x}) #sampling nplants in the database if (sample == 'random') plnb <- ceiling(runif(nplants) * length(unique(axeT$plant))) - else - plnb <- rep(seq(plantdb),lenght.out=nplants)[1:nplants] + else + plnb <- rep(seq(plantdb),length.out=nplants) # out <- vector("list",nplants) names(out) <- names(plantdb)[plnb] for (p in seq(out)) { + #print(p) #axeTable from axeT and geoAxe or dimT if azim/azdev in colums pT <- plantdb[[plnb[p]]] axeTable <- data.frame(axe = pT$axe, nf = pT$nf, + nf_end = pT$nf_end, emf1 = pT$emf1, end = pT$end, disp = pT$disp, azT = sapply(pT$axe,geoAxe$azT), + azTb = sapply(pT$axe,geoAxe$azTb), incT = sapply(pT$axe,geoAxe$incT), dredT = sapply(pT$axe,geoAxe$dredT), - hasEar = !is.na(pT$earIndex) + hasEar = is.na(pT$end), + HS_final = pT$HS_final ) - #phytoT from dimT and geoleaf + #phytoT and leafT from dimT and geoleaf nomsdim <- c("Ll","Lw","Gl","Gd","El","Ed","pAngle","dpAngle","incB","dincB") #row = phytomer number + 3 (peduncle, ear, awns) nfM <- max(pT$nf) + 3 + if (! all(is.finite(c(nfM,nrow(pT))))) + stop("setAdel: Can't create phytoT array") phytoT <- array(NA,dim=c(nfM,length(nomsdim)+3,nrow(pT)),dimnames=list(seq(nfM),c(nomsdim,"Azim","Lindex","Lseed"),pT$axe)) for (a in seq(nrow(pT))) { nf <- pT$nf[a] - pred <- predictDim(dimT,pT$dimIndex[a],nf)[,nomsdim] + nf_end <- pT$nf_end[a] + idaxe <- pT$axe[a] + pred <- predictDim(dimT,pT$dimIndex[a],nf, nf_end)[,nomsdim] if (!is.null(pred)) phytoT[seq(nf),nomsdim,a] <- unlist(pred) phytoT[seq(nf),"incB",a] <- phytoT[seq(nf),"incB",a] + (runif(nf) - .5) * phytoT[seq(nf),"dincB",a] if (useAzim) - phytoT[seq(nf),"Azim",a] <- sapply(seq(nf),function(n) geoLeaf$Azim(a,n,nf-n)) + phytoT[seq(nf),"Azim",a] <- sapply(seq(nf),function(n) geoLeaf$Azim(idaxe,n,nf)) else phytoT[seq(nf),"Azim",a] <- phytoT[seq(nf),"pAngle",a] + (runif(nf) - .5) * phytoT[seq(nf),"dpAngle",a] # - lindex <- sapply(seq(nf),function(n) geoLeaf$Lindex(a,n,nf-n)) + lindex <- sapply(seq(nf),function(n) geoLeaf$Lindex(idaxe,n,nf)) lseed <- runif(nf) if (is.null(xy_db)) { phytoT[seq(nf),"Lindex",a] <- lindex @@ -194,14 +249,17 @@ setAdel <- function(axeT,dimT,phenT,earT,ssisenT,geoLeaf,geoAxe,nplants=1,sample else { lindex <- sapply(lindex,function(x) ifelse(x %in% seq(xy_db),x,seq(xy_db)[which.min(abs(x - seq(xy_db)))])) lindex <- sapply(lindex,function(x) ifelse(x %in% seq(sr_db),x,seq(sr_db)[which.min(abs(x - seq(sr_db)))])) + # uses R-style indexing convention for lindex and lseed : they vary from 1 to length(object_list) phytoT[seq(nf),"Lindex",a] <- lindex - phytoT[seq(nf),"Lseed",a] <- sapply(seq(lseed),function(x) round(lseed[x] * length(xy_db[[lindex[x]]]))) + phytoT[seq(nf),"Lseed",a] <- sapply(seq(lseed),function(x) {index = round(lseed[x] * length(xy_db[[lindex[x]]])); ifelse(index==0,1,index)}) } # phytoT[(nf+1):(nf+3),,a] <- 0 + phytoT[(nf+1):(nf+3),c('Lindex', 'Lseed'),a] <- -999 if (!is.na(pT$earIndex[a])) { phytoT[(nf+1):(nf+2),"El",a] <- unlist(earT[pT$earIndex[a],c("l_ped","l_ear")]) - phytoT[nf+3,"El",a] <- unlist(earT[pT$earIndex[a],"l_ear_awn"] - earT[pT$earIndex[a],"l_ear"]) + if (earT[pT$earIndex[a],"l_ear_awn"] > earT[pT$earIndex[a],"l_ear"]) + phytoT[nf+3,"El",a] <- unlist(earT[pT$earIndex[a],"l_ear_awn"] - earT[pT$earIndex[a],"l_ear"]) phytoT[nf+1,"Ed",a] <- unlist(earT[pT$earIndex[a],"d_ped"]) if (earT[pT$earIndex[a],"l_ear"] > 0) phytoT[(nf+2):(nf+3),"Ed",a] <- unlist(earT[pT$earIndex[a],"Sp_ear"]/earT[pT$earIndex[a],"l_ear"]) @@ -213,15 +271,17 @@ setAdel <- function(axeT,dimT,phenT,earT,ssisenT,geoLeaf,geoAxe,nplants=1,sample if (!"dispf1"%in%colnames(pT)) print("Missing input for leaf desapearance in axeT (see docAdel.txt") for (a in seq(nrow(pT))) - phenoT[[a]] <- predictPhen(phenT,pT$phenIndex[a],pT$nf[a],pT[a,c("emf1","ligf1","senf1","dispf1")]) + phenoT[[a]] <- predictPhen(phenT,pT$phenIndex[a],pT$nf[a],pT[a,c("emf1","ligf1","senf1","dispf1")], pT$nf_end[a]) # date of start and end of peduncle elongation pedT <- vector("list",nrow(pT)) names(pedT) <- pT$axe for (a in seq(nrow(pT))) if (!is.na(pT$earIndex[a])) pedT[[a]] <- predictPed(phenoT[[a]],phytoT[,,a],pT$earIndex[a],pT$nf[a],earT) - - out[[p]] <- list(refp=names(out)[p],axeT = axeTable,phytoT=phytoT,pheno=phenoT,pedT = pedT,ssisenT=ssisenT) + if (!is.null(ssisenT)) + out[[p]] <- list(refp=names(out)[p],axeT = axeTable,phytoT=phytoT,pheno=phenoT,pedT = pedT,ssisenT=ssisenT) + else + out[[p]] <- list(refp=names(out)[p],axeT = axeTable,phytoT=phytoT,pheno=phenoT,pedT = pedT,ssipars=ssipars) } out } diff --git a/test/test_Adel_Maxwell_plante11.py b/test/test_Adel_Maxwell_plante11.py index ce661bee..21cae2f9 100644 --- a/test/test_Adel_Maxwell_plante11.py +++ b/test/test_Adel_Maxwell_plante11.py @@ -1,6 +1,7 @@ """Test stability of Adel for simulating a reference plant (Maxwell, plant 11, pareameterised by M. Abichou/B.Andrieu, EGC Grignon""" -import pathlib +from pathlib import Path from functools import reduce +import numpy as np from openalea.adel.AdelR import devCsv, setAdel, RunAdel, genGeoLeaf, genGeoAxe, \ csvAsDict @@ -10,7 +11,8 @@ @pytest_r_skip def test_organ_length(): - dir = str(pathlib.Path(__file__).parent.resolve() / "data" / "test_Adel_Maxwell_plante11/Maxwell_") + datadir = Path(__file__).parent if '__file__' in globals() else Path(".") + dir = str(datadir.resolve() / "data" / "test_Adel_Maxwell_plante11/Maxwell_") sufix = "_plante11.csv" axeTpath = dir + "axeT" + sufix dimTpath = dir + "dimT" + sufix @@ -39,4 +41,4 @@ def test_organ_length(): ): sim = reduce(lambda x, y: x + y, (t[k].tolist() for t in cantables)) exp = expected[k] - # np.testing.assert_allclose(sim,exp) + np.testing.assert_allclose(sim,exp) From 7f655a2f669ad146441d33a10e1a6c338c99865b Mon Sep 17 00:00:00 2001 From: Christian Fournier Date: Tue, 25 Aug 2026 16:12:51 +0200 Subject: [PATCH 3/4] Fix ear diparition --- src/openalea/adel/AdelR.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/openalea/adel/AdelR.py b/src/openalea/adel/AdelR.py index 97430d36..cc0129d4 100644 --- a/src/openalea/adel/AdelR.py +++ b/src/openalea/adel/AdelR.py @@ -406,7 +406,7 @@ def _devCsv(axeTfn, dimTfn, phenTfn, earTfn=None, ssi2senTfn=None): def devCsv(axeTfn, dimTfn, phenTfn, earTfn=None, ssi2senTfn=None): """Import development parameters for adel from csv files and/or pandas dataframes""" return RdflistAsdicts( - _devCsv(axeTfn, dimTfn, phenTfn, earTfn=None, ssi2senTfn=None) + _devCsv(axeTfn, dimTfn, phenTfn, earTfn=earTfn, ssi2senTfn=ssi2senTfn) ) From 5ff2e9e310339d308116faad3d73f0da4d6786c9 Mon Sep 17 00:00:00 2001 From: Christian Fournier Date: Wed, 26 Aug 2026 11:56:22 +0200 Subject: [PATCH 4/4] restore test_plantgen.py --- conda/meta.yaml | 2 +- src/openalea/adel/plantgen/plantgen_core.py | 15 +- .../adel/plantgen/plantgen_interface.py | 2 +- .../test_plantgen/default/HS_GL_SSI_T.csv | 72000 +++++++-------- test/data/test_plantgen/default/axeT.csv | 40 +- .../test_plantgen/default/cardinalityT.csv | 18 +- test/data/test_plantgen/default/dimT.csv | 128 +- test/data/test_plantgen/default/dynT.csv | 16 +- test/data/test_plantgen/default/phenT.csv | 149 +- test/data/test_plantgen/default/phenT_abs.csv | 149 +- .../test_plantgen/default/phenT_first.csv | 21 +- .../data/test_plantgen/default/tilleringT.csv | 6 +- .../test_plantgen/full_full/HS_GL_SSI_T.csv | 75000 +++++++--------- test/data/test_plantgen/full_full/axeT.csv | 40 +- .../test_plantgen/full_full/cardinalityT.csv | 18 +- test/data/test_plantgen/full_full/dimT.csv | 143 +- test/data/test_plantgen/full_full/dynT.csv | 16 +- test/data/test_plantgen/full_full/phenT.csv | 166 +- .../test_plantgen/full_full/phenT_abs.csv | 166 +- .../test_plantgen/full_full/phenT_first.csv | 23 +- .../test_plantgen/full_full/tilleringT.csv | 6 +- .../test_plantgen/min_min/HS_GL_SSI_T.csv | 72000 +++++++-------- test/data/test_plantgen/min_min/axeT.csv | 40 +- .../test_plantgen/min_min/cardinalityT.csv | 18 +- test/data/test_plantgen/min_min/dimT.csv | 153 +- test/data/test_plantgen/min_min/dynT.csv | 16 +- test/data/test_plantgen/min_min/phenT.csv | 177 +- test/data/test_plantgen/min_min/phenT_abs.csv | 177 +- .../test_plantgen/min_min/phenT_first.csv | 24 +- .../data/test_plantgen/min_min/tilleringT.csv | 6 +- .../test_plantgen/short_short/HS_GL_SSI_T.csv | 72000 +++++++-------- test/data/test_plantgen/short_short/axeT.csv | 40 +- .../short_short/cardinalityT.csv | 18 +- test/data/test_plantgen/short_short/dimT.csv | 144 +- test/data/test_plantgen/short_short/dynT.csv | 16 +- test/data/test_plantgen/short_short/phenT.csv | 167 +- .../test_plantgen/short_short/phenT_abs.csv | 167 +- .../test_plantgen/short_short/phenT_first.csv | 23 +- .../test_plantgen/short_short/tilleringT.csv | 6 +- ...{bck_test_plantgen.py => test_plantgen.py} | 17 +- 40 files changed, 139130 insertions(+), 154203 deletions(-) rename test/{bck_test_plantgen.py => test_plantgen.py} (95%) diff --git a/conda/meta.yaml b/conda/meta.yaml index a070de32..0b8109a3 100644 --- a/conda/meta.yaml +++ b/conda/meta.yaml @@ -45,7 +45,7 @@ test: - test/data/** commands: - cd test - - pytest -v --ignore=test_povray.py --ignore=test_dataflow.py --ignore=test_plantgen.py + - pytest -v --ignore=test_povray.py --ignore=test_dataflow.py about: home: {{ home }} diff --git a/src/openalea/adel/plantgen/plantgen_core.py b/src/openalea/adel/plantgen/plantgen_core.py index 832b39c7..bfcd2576 100644 --- a/src/openalea/adel/plantgen/plantgen_core.py +++ b/src/openalea/adel/plantgen/plantgen_core.py @@ -835,12 +835,21 @@ def _gen_id_dim_list(id_cohort_series, N_phytomer_series, id_ear_series): """Generate the *id_dim* column.""" is_ear = pd.Series(0, index=id_ear_series.index) is_ear[id_ear_series.dropna().index] = 1 - zfilled_array = np.core.defchararray.zfill(np.char.mod("%d", N_phytomer_series), 2) + + zfilled_array = np.char.zfill( + np.char.mod("%d", N_phytomer_series), 2 + ) + id_cohort_str_array = np.char.mod("%d", id_cohort_series) - id_dim_array = np.core.defchararray.add(id_cohort_str_array, zfilled_array) - id_dim_array = np.core.defchararray.add( + + id_dim_array = np.char.add( + id_cohort_str_array, zfilled_array + ) + + id_dim_array = np.char.add( id_dim_array, np.char.mod("%d", is_ear) ).astype(int) + return id_dim_array.tolist() diff --git a/src/openalea/adel/plantgen/plantgen_interface.py b/src/openalea/adel/plantgen/plantgen_interface.py index b40284dc..918ffb79 100644 --- a/src/openalea/adel/plantgen/plantgen_interface.py +++ b/src/openalea/adel/plantgen/plantgen_interface.py @@ -172,7 +172,7 @@ def gen_adel_input_data( ) ) - if sum(MS_leaves_number_probabilities.values()) != 1.0: + if not np.isclose(sum(MS_leaves_number_probabilities.values()), 1.0): raise tools.InputError( "the sum of the probabilities defined in MS_leaves_number_probabilities is not equal to 1.0" ) diff --git a/test/data/test_plantgen/default/HS_GL_SSI_T.csv b/test/data/test_plantgen/default/HS_GL_SSI_T.csv index a742ad8f..1e453043 100644 --- a/test/data/test_plantgen/default/HS_GL_SSI_T.csv +++ b/test/data/test_plantgen/default/HS_GL_SSI_T.csv @@ -1,36001 +1,36001 @@ id_phen,TT,HS,GL,SSI -1101,0,0.0069995570,0.0069995570,0.0000000000 -1101,1,0.0160781006,0.0160781006,0.0000000000 -1101,2,0.0251566441,0.0251566441,0.0000000000 -1101,3,0.0342351876,0.0342351876,0.0000000000 -1101,4,0.0433137311,0.0433137311,0.0000000000 -1101,5,0.0523922746,0.0523922746,0.0000000000 -1101,6,0.0614708181,0.0614708181,0.0000000000 -1101,7,0.0705493617,0.0705493617,0.0000000000 -1101,8,0.0796279052,0.0796279052,0.0000000000 -1101,9,0.0887064487,0.0887064487,0.0000000000 -1101,10,0.0977849922,0.0977849922,0.0000000000 -1101,11,0.1068635357,0.1068635357,0.0000000000 -1101,12,0.1159420792,0.1159420792,0.0000000000 -1101,13,0.1250206227,0.1250206227,0.0000000000 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b/test/data/test_plantgen/default/cardinalityT.csv index 0efdeb10..b1e99827 100644 --- a/test/data/test_plantgen/default/cardinalityT.csv +++ b/test/data/test_plantgen/default/cardinalityT.csv @@ -1,10 +1,10 @@ id_cohort,id_axis,theoretical_cohort_cardinality,simulated_cohort_cardinality,theoretical_axis_cardinality,simulated_axis_cardinality -1,MS,5.0000000000,5,5.0000000000,5 -3,T0,0.0000000000,0,0.0000000000,0 -4,T1,4.5000000000,4,4.5000000000,4 -5,T2,4.8350000000,5,4.8350000000,5 -6,T1.0,6.6953150000,6,2.6103150000,2 -6,T3,6.6953150000,6,4.0850000000,4 -7,T1.1,0.9651115500,0,0.2651850000,0 -7,T2.0,0.9651115500,0,0.2849265500,0 -7,T4,0.9651115500,0,0.4150000000,0 +1,MS,5.0000000,5.0000000,5.0000000,5.0000000 +3,T0,0.0000000,0.0000000,0.0000000,0.0000000 +4,T1,4.5000000,4.0000000,4.5000000,4.0000000 +5,T2,4.8350000,5.0000000,4.8350000,5.0000000 +6,T1.0,6.6953150,6.0000000,2.6103150,2.0000000 +6,T3,6.6953150,6.0000000,4.0850000,4.0000000 +7,T1.1,0.9651116,0.0000000,0.2651850,0.0000000 +7,T2.0,0.9651116,0.0000000,0.2849266,0.0000000 +7,T4,0.9651116,0.0000000,0.4150000,0.0000000 diff --git a/test/data/test_plantgen/default/dimT.csv b/test/data/test_plantgen/default/dimT.csv index caa10b76..a799f0b4 100644 --- a/test/data/test_plantgen/default/dimT.csv +++ b/test/data/test_plantgen/default/dimT.csv @@ -1,63 +1,67 @@ id_dim,index_phytomer,index_relative_to_MS_phytomer,L_blade,W_blade,L_sheath,W_sheath,L_internode,W_internode -1101,1,1.0000000000,9.4314366157,0.3794920246,3.0092091273,0.1580000000,0.0000000000,0.0000000000 -1101,2,2.0000000000,8.7440604620,0.3537366191,2.4376216914,0.1830000000,0.0000000000,0.0000000000 -1101,3,3.0000000000,8.9140967350,0.4869079092,3.2219424862,0.2090000000,0.0000000000,0.0000000000 -1101,4,4.0000000000,9.8754805895,0.6797122089,4.6377507170,0.2340000000,0.0000000000,0.0000000000 -1101,5,5.0000000000,11.5685474964,0.8619637784,6.1867727273,0.2590000000,0.0000000000,0.0000000000 -1101,6,6.0000000000,13.8148688517,0.9925848242,7.5968819991,0.2840000000,0.0000000000,0.0000000000 -1101,7,7.0000000000,16.1574691976,1.0596054989,8.8220991529,0.3554000000,0.0000000000,0.1471788083 -1101,8,8.0000000000,17.6664250586,1.0801639012,10.0425919478,0.3554000000,5.8130096000,0.1832777967 -1101,9,9.0000000000,16.7098453915,1.1005060758,11.6646752811,0.3554000000,10.7295214750,0.2048666915 -1101,10,10.0000000000,10.6902336487,1.1959860140,14.3208111888,0.3554000000,15.3470000000,0.2119454926 -1111,1,1.0000000000,9.4460000000,0.3800000000,2.8430000000,0.1580000000,0.0000000000,0.0000000000 -1111,2,2.0000000000,9.2670000000,0.3740000000,2.9310000000,0.1830000000,0.0000000000,0.0000000000 -1111,3,3.0000000000,8.0290000000,0.4450000000,3.2440000000,0.2090000000,0.0000000000,0.0000000000 -1111,4,4.0000000000,9.6650000000,0.5790000000,3.8940000000,0.2340000000,0.0000000000,0.0000000000 -1111,5,5.0000000000,11.2600000000,0.7500000000,4.4820000000,0.2590000000,0.0000000000,0.0000000000 -1111,6,6.0000000000,12.3280000000,0.9860000000,6.8130000000,0.2840000000,0.0000000000,0.0000000000 -1111,7,7.0000000000,14.0730000000,1.0200000000,8.8920000000,0.3100000000,1.5530000000,0.0000000000 -1111,8,8.0000000000,17.2530000000,1.0600000000,9.5800000000,0.3350000000,4.4470000000,0.0640000000 -1111,9,9.0000000000,17.7470000000,1.0800000000,10.1170000000,0.3600000000,6.4270000000,0.1340000000 -1111,10,10.0000000000,16.2640000000,1.1000000000,11.0730000000,0.3860000000,11.3000000000,0.1920000000 -1111,11,11.0000000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.3000000000 -4081,1,3.6724000000,9.0340000000,0.3800000000,3.3130000000,0.1580000000,0.0000000000,0.0000000000 -4081,2,4.6724000000,10.0340000000,0.4830000000,4.2440000000,0.1860000000,0.0000000000,0.0000000000 -4081,3,5.6724000000,11.6570000000,0.5850000000,5.8890000000,0.2150000000,0.0000000000,0.0000000000 -4081,4,6.6724000000,13.7490000000,0.6880000000,7.8120000000,0.2430000000,0.0000000000,0.0000000000 -4081,5,7.6724000000,15.9440000000,0.7900000000,9.3620000000,0.2720000000,3.7510000000,0.0000000000 -4081,6,8.6724000000,17.5290000000,0.8930000000,10.1150000000,0.3000000000,5.4060000000,0.0640000000 -4081,7,9.6724000000,17.2860000000,0.9950000000,10.5300000000,0.3290000000,9.2090000000,0.1820000000 -4081,8,10.6724000000,13.3150000000,1.0980000000,12.8040000000,0.3570000000,14.7330000000,0.3000000000 -6061,1,5.0086000000,6.5000000000,0.3800000000,5.5009652173,0.3162595280,0.0000000000,0.0000000000 -6061,2,6.0086000000,11.1134718671,0.5334960000,6.8640743929,0.3557395280,0.0000000000,0.0000000000 -6061,3,7.0086000000,14.2481874253,0.6869920000,8.0688770572,0.3691871988,1.6084847972,0.1475511164 -6061,4,8.0086000000,16.9702666443,0.8404880000,9.1516642834,0.3691871988,4.4570980603,0.1835253180 -6061,5,9.0086000000,18.0464227732,0.9939840000,10.3031886831,0.3691871988,6.4565350120,0.2049894260 -6061,6,10.0086000000,16.0814281565,1.1474800000,11.8686644064,0.3691871988,11.3490720523,0.2119434403 -5030,1,4.3405000000,5.7525000000,0.3443560000,4.0305293483,0.2626919202,0.0000000000,0.0000000000 -5030,2,5.3405000000,8.4774429807,0.6921011880,5.2806343513,0.2984686962,0.0000000000,0.0000000000 -5030,3,6.3405000000,11.2023859614,1.0398463760,6.4453526438,0.3342454722,0.0000000000,0.0000000000 -5040,1,4.3405000000,5.7525000000,0.3443560000,4.0305293483,0.2626919202,0.0000000000,0.0000000000 -5040,2,5.3405000000,8.4774429807,0.5761861253,5.2806343513,0.2984686962,0.0000000000,0.0000000000 -5040,3,6.3405000000,11.2023859614,0.8080162507,6.4453526438,0.3342454722,0.0000000000,0.0000000000 -5040,4,7.3405000000,13.4572280132,1.0398463760,7.4654735833,0.3345574395,2.8216172755,0.1459885530 -5050,1,4.3405000000,5.7525000000,0.3443560000,4.0305293483,0.2626919202,0.0000000000,0.0000000000 -5050,2,5.3405000000,8.4774429807,0.5182285940,5.2806343513,0.2984686962,0.0000000000,0.0000000000 -5050,3,6.3405000000,11.2023859614,0.6921011880,6.4453526438,0.3342454722,0.0000000000,0.0000000000 -5050,4,7.3405000000,13.4572280132,0.8659737820,7.4654735833,0.3345574395,2.8216172755,0.1459885530 -5050,5,8.3405000000,15.5757141597,1.0398463760,8.4184849890,0.3345574395,4.3154065965,0.1742242058 -6040,1,5.0086000000,5.7525000000,0.3443560000,4.8683542173,0.2865943843,0.0000000000,0.0000000000 -6040,2,6.0086000000,9.8354226024,0.5761861253,6.0747058377,0.3223711603,0.0000000000,0.0000000000 -6040,3,7.0086000000,12.6096458714,0.8080162507,7.1409561956,0.3345574395,1.4235090455,0.1337108217 -6040,4,8.0086000000,15.0186859802,1.0398463760,8.0992228908,0.3345574395,3.9445317834,0.1663106432 -6050,1,5.0086000000,5.7525000000,0.3443560000,4.8683542173,0.2865943843,0.0000000000,0.0000000000 -6050,2,6.0086000000,9.8354226024,0.5182285940,6.0747058377,0.3223711603,0.0000000000,0.0000000000 -6050,3,7.0086000000,12.6096458714,0.6921011880,7.1409561956,0.3345574395,1.4235090455,0.1337108217 -6050,4,8.0086000000,15.0186859802,0.8659737820,8.0992228908,0.3345574395,3.9445317834,0.1663106432 -6050,5,9.0086000000,15.9710841543,1.0398463760,9.1183219845,0.3345574395,5.7140334857,0.1857614178 -6060,1,5.0086000000,5.7525000000,0.3443560000,4.8683542173,0.2865943843,0.0000000000,0.0000000000 -6060,2,6.0086000000,9.8354226024,0.4834540752,6.0747058377,0.3223711603,0.0000000000,0.0000000000 -6060,3,7.0086000000,12.6096458714,0.6225521504,7.1409561956,0.3345574395,1.4235090455,0.1337108217 -6060,4,8.0086000000,15.0186859802,0.7616502256,8.0992228908,0.3345574395,3.9445317834,0.1663106432 -6060,5,9.0086000000,15.9710841543,0.9007483008,9.1183219845,0.3345574395,5.7140334857,0.1857614178 -6060,6,10.0086000000,14.2320639185,1.0398463760,10.5037679997,0.3345574395,10.0439287663,0.1920631456 +1111,1,1.0000000,9.4460000,0.3800000,2.8430000,0.1580000,0.0000000,0.0000000 +1111,2,2.0000000,9.2670000,0.3740000,2.9310000,0.1830000,0.0000000,0.0000000 +1111,3,3.0000000,8.0290000,0.4450000,3.2440000,0.2090000,0.0000000,0.0000000 +1111,4,4.0000000,9.6650000,0.5790000,3.8940000,0.2340000,0.0000000,0.0000000 +1111,5,5.0000000,11.2600000,0.7500000,4.4820000,0.2590000,0.0000000,0.0000000 +1111,6,6.0000000,12.3280000,0.9860000,6.8130000,0.2840000,0.0000000,0.0000000 +1111,7,7.0000000,14.0730000,1.0200000,8.8920000,0.3100000,1.5530000,0.0000000 +1111,8,8.0000000,17.2530000,1.0600000,9.5800000,0.3350000,4.4470000,0.0640000 +1111,9,9.0000000,17.7470000,1.0800000,10.1170000,0.3600000,6.4270000,0.1340000 +1111,10,10.0000000,16.2640000,1.1000000,11.0730000,0.3860000,11.3000000,0.1920000 +1111,11,11.0000000,10.7360000,1.2000000,14.7200000,0.3860000,15.3470000,0.3000000 +4081,1,3.6724000,9.0340000,0.3800000,3.3130000,0.1580000,0.0000000,0.0000000 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+6071,6,10.0086000,14.9950000,1.0630000,11.7240000,0.3480000,13.3760000,0.3000000 +6071,7,11.0086000,10.7360000,1.2000000,14.7200000,0.3860000,15.3470000,0.5360000 +4070,1,3.6724000,5.7525000,0.3443560,3.2392219,0.2387895,0.0000000,0.0000000 +4070,2,4.6724000,7.7973321,0.4602711,4.4456348,0.2745662,0.0000000,0.0000000 +4070,3,5.6724000,9.8421641,0.5761861,5.6823919,0.3103430,0.0000000,0.0000000 +4070,4,6.6724000,11.8210565,0.6921012,6.7989543,0.3345574,0.0000000,0.1197973 +4070,5,7.6724000,14.2835677,0.8080163,7.7814817,0.3345574,3.5387599,0.1568178 +4070,6,8.6724000,15.9086211,0.9239313,8.7528321,0.3345574,4.8603373,0.1806893 +4070,7,9.6724000,15.1560185,1.0398464,9.9725619,0.3345574,8.3720541,0.1914117 +5030,1,4.3405000,5.7525000,0.3443560,4.0305293,0.2626919,0.0000000,0.0000000 +5030,2,5.3405000,8.4774430,0.6921012,5.2806344,0.2984687,0.0000000,0.0000000 +5030,3,6.3405000,11.2023860,1.0398464,6.4453526,0.3342455,0.0000000,0.0000000 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+6060,1,5.0086000,5.7525000,0.3443560,4.8683542,0.2865944,0.0000000,0.0000000 +6060,2,6.0086000,9.8354226,0.4834541,6.0747058,0.3223712,0.0000000,0.0000000 +6060,3,7.0086000,12.6096459,0.6225522,7.1409562,0.3345574,1.4235090,0.1337108 +6060,4,8.0086000,15.0186860,0.7616502,8.0992229,0.3345574,3.9445318,0.1663106 +6060,5,9.0086000,15.9710842,0.9007483,9.1183220,0.3345574,5.7140335,0.1857614 +6060,6,10.0086000,14.2320639,1.0398464,10.5037680,0.3345574,10.0439288,0.1920631 diff --git a/test/data/test_plantgen/default/dynT.csv b/test/data/test_plantgen/default/dynT.csv index 201b4596..7448552c 100644 --- a/test/data/test_plantgen/default/dynT.csv +++ b/test/data/test_plantgen/default/dynT.csv @@ -1,11 +1,7 @@ id_axis,id_cohort,cardinality,N_phytomer_potential,a_cohort,TT_hs_0,TT_hs_break,TT_flag_ligulation,dTT_MS_cohort,n0,n1,n2,t0,t1,hs_t1,a,c,RMSE_gl -MS,1,4,11,0.0100000000,-0.7710000000,NA,1078.0000000000,0.0000000000,4.8720000000,3.2430000000,5.8000000000,486.4290000000,699.2290000000,7.0000000000,-0.0000000052,-0.0038096898,0.1689122432 -MS,1,1,10,0.0090785435,-0.7710000000,NA,1100.7272727273,-20.0000000000,4.4290909091,2.9481818182,5.2727272727,487.0925986116,660.1279636364,6.0000000000,-0.0000000047,-0.0034633543,0.1689122432 -T1,4,4,8,0.0100000000,246.1010000000,NA,1148.0000000000,70.0000000000,3.8015861379,3.2430000000,4.9300000000,626.2596137876,769.2290000000,5.2312800000,-0.0000000044,-0.0032382363,0.1689122432 -T1.0,6,1,7,0.0080000000,334.4150000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,739.7900000000,3.6385120000,-0.0000000044,-0.0032382363,0.1689122432 -T1.0,6,1,6,0.0073747672,334.4150000000,NA,1148.0000000000,70.0000000000,NA,3.2430000000,4.9300000000,NA,774.1576925000,3.2066520400,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,2,7,0.0110000000,446.0520000000,NA,1158.0000000000,80.0000000000,NA,3.2430000000,4.9300000000,NA,740.8701818182,3.6649470000,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,2,8,0.0109297382,446.0520000000,NA,1178.0000000000,100.0000000000,NA,3.2430000000,4.9300000000,NA,742.7654205000,3.8601321405,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,1,6,0.0086711718,446.0520000000,NA,1138.0000000000,60.0000000000,NA,3.2430000000,4.9300000000,NA,820.0498940000,2.7156115777,-0.0000000044,-0.0032382363,0.1689122432 -T3,6,3,7,0.0080000000,334.4150000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,739.7900000000,3.6385120000,-0.0000000044,-0.0032382363,0.1689122432 -T3,6,1,6,0.0073747672,334.4150000000,NA,1148.0000000000,70.0000000000,NA,3.2430000000,4.9300000000,NA,774.1576925000,3.2066520400,-0.0000000044,-0.0032382363,0.1689122432 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--- a/test/data/test_plantgen/default/phenT.csv +++ b/test/data/test_plantgen/default/phenT.csv @@ -1,73 +1,78 @@ id_phen,index_phytomer,dTT_em_phytomer,dTT_col_phytomer,dTT_sen_phytomer,dTT_del_phytomer -1101,0,-110.1498272727,-110.1498272727,-56.6991067999,-56.6991067999 -1101,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 -1101,2,44.0599309091,110.1498272727,56.6991067999,56.6991067999 -1101,3,154.2097581818,220.2996545455,113.3982135998,113.3982135998 -1101,4,264.3595854545,330.4494818182,365.6824760121,365.6824760121 -1101,5,374.5094127273,440.5993090909,635.0309797910,635.0309797910 -1101,6,484.6592400000,550.7491363636,878.8237918574,878.8237918574 -1101,7,594.8090672727,660.8989636364,1049.6389044123,1049.6389044123 -1101,8,704.9588945455,771.0487909091,1176.5993088683,2125.7588127703 -1101,9,815.1087218182,881.1986181818,1278.0279132833,2125.7588127703 -1101,10,925.2585490909,991.3484454545,1363.0982658465,2125.7588127703 -1111,0,-100.0000000000,-100.0000000000,-56.6409369178,-56.6409369178 -1111,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 -1111,2,40.0000000000,100.0000000000,56.6409369178,56.6409369178 -1111,3,140.0000000000,200.0000000000,113.2818738355,113.2818738355 -1111,4,240.0000000000,300.0000000000,230.9462615287,230.9462615287 -1111,5,340.0000000000,400.0000000000,535.8200176390,535.8200176390 -1111,6,440.0000000000,500.0000000000,734.1167723419,734.1167723419 -1111,7,540.0000000000,600.0000000000,925.7808825809,2156.9300630822 -1111,8,640.0000000000,700.0000000000,1065.5959615205,2156.9300630822 -1111,9,740.0000000000,800.0000000000,1174.5836973376,2156.9300630822 -1111,10,840.0000000000,900.0000000000,1264.3361225686,2156.9300630822 -1111,11,940.0000000000,1000.0000000000,1341.0927616130,2156.9300630822 -4081,0,-100.0000000000,-100.0000000000,-71.9060626332,-71.9060626332 -4081,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 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+6071.0000000,1,0.0000000,0.0000000,0.0000000,0.0000000 +6071.0000000,2,50.0000000,125.0000000,205.1732717,205.1732717 +6071.0000000,3,175.0000000,250.0000000,444.3980997,444.3980997 +6071.0000000,4,300.0000000,375.0000000,643.4930436,1638.9254623 +6071.0000000,5,425.0000000,500.0000000,785.7525203,1638.9254623 +6071.0000000,6,550.0000000,625.0000000,896.5710506,1638.9254623 +6071.0000000,7,675.0000000,750.0000000,988.0881605,1638.9254623 diff --git a/test/data/test_plantgen/default/phenT_abs.csv b/test/data/test_plantgen/default/phenT_abs.csv index 0e34c695..4c1db724 100644 --- a/test/data/test_plantgen/default/phenT_abs.csv +++ b/test/data/test_plantgen/default/phenT_abs.csv @@ -1,73 +1,78 @@ id_phen,index_phytomer,TT_em_phytomer,TT_col_phytomer,TT_sen_phytomer,TT_del_phytomer -1101,0,-132.9507927273,-22.8009654545,487.0925986116,817.5420804298 -1101,1,-22.8009654545,87.3488618182,543.7917054115,874.2411872297 -1101,2,21.2589654545,197.4986890909,600.4908122114,930.9402940296 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+6071.0000000,7,984.4150000,1184.4150000,1974.1626982,3000.0000000 diff --git a/test/data/test_plantgen/default/phenT_first.csv b/test/data/test_plantgen/default/phenT_first.csv index b3be5b71..0a41c454 100644 --- a/test/data/test_plantgen/default/phenT_first.csv +++ b/test/data/test_plantgen/default/phenT_first.csv @@ -1,11 +1,12 @@ id_phen,index_phytomer,TT_em_phytomer,TT_col_phytomer,TT_sen_phytomer,TT_del_phytomer -1101,1,-22.8009654545,87.3488618182,543.7917054115,874.2411872297 -1111,1,-20.7710000000,79.2290000000,543.0699369178,843.0699369178 -4081,1,226.1010000000,326.1010000000,698.1656764208,998.1656764208 -5030,1,324.5797787234,519.2468000000,884.5356418355,1159.0161418355 -5040,1,325.3556750484,518.7792727273,884.6372572658,1157.3645299931 -5050,1,325.3556750484,518.7792727273,884.6372572658,1157.3645299931 -6040,1,168.4575531915,434.4150000000,986.0745376953,1361.0745376953 -6050,1,168.4575531915,434.4150000000,986.0745376953,1361.0745376953 -6060,1,168.4575531915,434.4150000000,986.0745376953,1361.0745376953 -6061,1,307.2955000000,442.8930000000,1123.5430266121,1530.3355266121 +1111.0000000,1,-20.7710000,79.2290000,543.0699369,843.0699369 +4070.0000000,1,113.3350426,326.1010000,698.1656764,998.1656764 +4081.0000000,1,226.1010000,326.1010000,698.1656764,998.1656764 +5030.0000000,1,325.3556750,518.7792727,884.6372573,1157.3645300 +5040.0000000,1,324.5797787,519.2468000,884.5356418,1159.0161418 +5050.0000000,1,324.5797787,519.2468000,884.5356418,1159.0161418 +5060.0000000,1,325.3556750,518.7792727,884.6372573,1157.3645300 +6040.0000000,1,168.4575532,434.4150000,986.0745377,1361.0745377 +6050.0000000,1,168.4575532,434.4150000,986.0745377,1361.0745377 +6060.0000000,1,168.4575532,434.4150000,986.0745377,1361.0745377 +6071.0000000,1,309.4150000,434.4150000,986.0745377,1361.0745377 diff --git a/test/data/test_plantgen/default/tilleringT.csv b/test/data/test_plantgen/default/tilleringT.csv index 0db47d0b..ea84544d 100644 --- a/test/data/test_plantgen/default/tilleringT.csv +++ b/test/data/test_plantgen/default/tilleringT.csv @@ -1,4 +1,4 @@ TT,axes_density --20.7710000000,12.0000000000 -689.8990000000,48.0000000000 -1126.3990000000,25.0000000000 +-20.7710000,12.0000000 +689.8990000,48.0000000 +1126.3990000,25.0000000 diff --git a/test/data/test_plantgen/full_full/HS_GL_SSI_T.csv b/test/data/test_plantgen/full_full/HS_GL_SSI_T.csv index 95598959..36fca39d 100644 --- a/test/data/test_plantgen/full_full/HS_GL_SSI_T.csv +++ b/test/data/test_plantgen/full_full/HS_GL_SSI_T.csv @@ -1,42001 +1,33001 @@ id_phen,TT,HS,GL,SSI -1101,0,0.0069390000,0.0069390000,0.0000000000 -1101,1,0.0159390000,0.0159390000,0.0000000000 -1101,2,0.0249390000,0.0249390000,0.0000000000 -1101,3,0.0339390000,0.0339390000,0.0000000000 -1101,4,0.0429390000,0.0429390000,0.0000000000 -1101,5,0.0519390000,0.0519390000,0.0000000000 -1101,6,0.0609390000,0.0609390000,0.0000000000 -1101,7,0.0699390000,0.0699390000,0.0000000000 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-1,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,220.3585678176,331.4696789287,727.5658401151,1060.8991734484 -1,5,T2,7,5,4.0394800000,850.0000000000,1450.0000000000,5050,5050,NA,434.4670037525,534.4670037525,955.8172622613,1255.8172622613 -1,6,T1.0,7,5,4.4366800000,889.0000000000,1489.0000000000,6050,6050,NA,314.6061198110,439.6061198110,991.2656575063,1366.2656575063 -1,6,T3,7,5,4.7886800000,933.0000000000,1533.0000000000,6050,6050,NA,314.6061198110,439.6061198110,991.2656575063,1366.2656575063 -2,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-20.8647013463,79.1352986537,542.9762355715,842.9762355715 -2,5,T2,7,4,3.6894800000,815.0000000000,1415.0000000000,5040,5040,NA,428.5770128908,528.5770128908,949.9272713997,1249.9272713997 -2,6,T3,7,7,7.0000000000,NA,NA,6071,6071,1.0000000000,298.4634485447,423.4634485447,975.1229862399,1350.1229862399 -3,1,MS,10,10,10.0000000000,NA,NA,1101,1101,1.0000000000,-17.7117854975,93.3993256136,553.8153733783,887.1487067116 -3,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,215.9765970127,327.0877081238,723.1838693102,1056.5172026435 -3,5,T2,6,3,2.7394800000,720.0000000000,1320.0000000000,5030,5030,NA,419.7431363242,519.7431363242,941.0933948331,1241.0933948331 -3,6,T1.0,6,4,3.0648426409,750.0000000000,1350.0000000000,6040,6040,NA,296.9771456044,439.8342884616,1168.4028927801,1596.9743213515 -3,6,T3,6,6,6.0000000000,NA,NA,6061,6061,1.0000000000,296.9771456044,439.8342884616,1168.4028927801,1596.9743213515 -4,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-14.2565954121,85.7434045879,549.5843415057,849.5843415057 -4,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,234.1047003119,345.2158114230,741.3119726094,1074.6453059427 -4,5,T2,8,3,2.6834280000,690.0000000000,1290.0000000000,5030,5030,NA,423.8658048942,514.7748958033,880.6328803418,1153.3601530691 -5,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-33.9480200986,66.0519799014,529.8929168192,829.8929168192 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+5.0000000,1.0000000,MS,11.0000000,11.0000000,11.0000000,NA,NA,1111.0000000,1111.0000000,1.0000000,-33.9480201,66.0519799,529.8929168,829.8929168 +5.0000000,4.0000000,T1,8.0000000,5.0000000,4.5350910,750.0000000,1350.0000000,4050.0000000,4050.0000000,NA,227.1403965,338.2515076,734.3476688,1067.6810021 +5.0000000,5.0000000,T2,8.0000000,3.0000000,2.6834280,690.0000000,1290.0000000,5030.0000000,5030.0000000,NA,420.3569697,511.2660606,877.1240451,1149.8513179 +5.0000000,6.0000000,T3,7.0000000,4.0000000,3.0846800,720.0000000,1320.0000000,6040.0000000,6040.0000000,NA,298.9379999,423.9379999,975.5975376,1350.5975376 diff --git a/test/data/test_plantgen/full_full/cardinalityT.csv b/test/data/test_plantgen/full_full/cardinalityT.csv index 0efdeb10..b1e99827 100644 --- a/test/data/test_plantgen/full_full/cardinalityT.csv +++ b/test/data/test_plantgen/full_full/cardinalityT.csv @@ -1,10 +1,10 @@ id_cohort,id_axis,theoretical_cohort_cardinality,simulated_cohort_cardinality,theoretical_axis_cardinality,simulated_axis_cardinality -1,MS,5.0000000000,5,5.0000000000,5 -3,T0,0.0000000000,0,0.0000000000,0 -4,T1,4.5000000000,4,4.5000000000,4 -5,T2,4.8350000000,5,4.8350000000,5 -6,T1.0,6.6953150000,6,2.6103150000,2 -6,T3,6.6953150000,6,4.0850000000,4 -7,T1.1,0.9651115500,0,0.2651850000,0 -7,T2.0,0.9651115500,0,0.2849265500,0 -7,T4,0.9651115500,0,0.4150000000,0 +1,MS,5.0000000,5.0000000,5.0000000,5.0000000 +3,T0,0.0000000,0.0000000,0.0000000,0.0000000 +4,T1,4.5000000,4.0000000,4.5000000,4.0000000 +5,T2,4.8350000,5.0000000,4.8350000,5.0000000 +6,T1.0,6.6953150,6.0000000,2.6103150,2.0000000 +6,T3,6.6953150,6.0000000,4.0850000,4.0000000 +7,T1.1,0.9651116,0.0000000,0.2651850,0.0000000 +7,T2.0,0.9651116,0.0000000,0.2849266,0.0000000 +7,T4,0.9651116,0.0000000,0.4150000,0.0000000 diff --git a/test/data/test_plantgen/full_full/dimT.csv b/test/data/test_plantgen/full_full/dimT.csv index 40533d2e..eaf29889 100644 --- a/test/data/test_plantgen/full_full/dimT.csv +++ b/test/data/test_plantgen/full_full/dimT.csv @@ -1,78 +1,67 @@ id_dim,index_phytomer,index_relative_to_MS_phytomer,L_blade,W_blade,L_sheath,W_sheath,L_internode,W_internode -1101,1,1.0000000000,9.6110000000,0.3800000000,2.7710000000,0.1580000000,0.0000000000,0.0000000000 -1101,2,2.0000000000,8.7880000000,0.4710000000,3.0660000000,0.1830000000,0.0000000000,0.0000000000 -1101,3,3.0000000000,8.8390000000,0.5620000000,3.1650000000,0.2090000000,0.0000000000,0.0000000000 -1101,4,4.0000000000,9.6880000000,0.6540000000,3.9030000000,0.2340000000,0.0000000000,0.0000000000 -1101,5,5.0000000000,11.2810000000,0.7450000000,5.5120000000,0.2590000000,0.0000000000,0.0000000000 -1101,6,6.0000000000,13.4670000000,0.8360000000,7.5750000000,0.2850000000,0.0000000000,0.0000000000 -1101,7,7.0000000000,15.8400000000,0.9270000000,9.3020000000,0.3100000000,3.6320000000,0.0000000000 -1101,8,8.0000000000,17.5520000000,1.0180000000,10.1260000000,0.3350000000,5.4620000000,0.0640000000 -1101,9,9.0000000000,17.0900000000,1.1090000000,10.6190000000,0.3600000000,9.7870000000,0.1820000000 -1101,10,10.0000000000,12.0130000000,1.2000000000,13.7350000000,0.3860000000,15.2320000000,0.3000000000 -1111,1,1.0000000000,9.4460000000,0.3800000000,2.8430000000,0.1580000000,0.0000000000,0.0000000000 -1111,2,2.0000000000,9.2670000000,0.3740000000,2.9310000000,0.1830000000,0.0000000000,0.0000000000 -1111,3,3.0000000000,8.0290000000,0.4450000000,3.2440000000,0.2090000000,0.0000000000,0.0000000000 -1111,4,4.0000000000,9.6650000000,0.5790000000,3.8940000000,0.2340000000,0.0000000000,0.0000000000 -1111,5,5.0000000000,11.2600000000,0.7500000000,4.4820000000,0.2590000000,0.0000000000,0.0000000000 -1111,6,6.0000000000,12.3280000000,0.9860000000,6.8130000000,0.2840000000,0.0000000000,0.0000000000 -1111,7,7.0000000000,14.0730000000,1.0200000000,8.8920000000,0.3100000000,1.5530000000,0.0000000000 -1111,8,8.0000000000,17.2530000000,1.0600000000,9.5800000000,0.3350000000,4.4470000000,0.0640000000 -1111,9,9.0000000000,17.7470000000,1.0800000000,10.1170000000,0.3600000000,6.4270000000,0.1340000000 -1111,10,10.0000000000,16.2640000000,1.1000000000,11.0730000000,0.3860000000,11.3000000000,0.1920000000 -1111,11,11.0000000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.3000000000 -4081,1,3.6724000000,8.9860000000,0.3800000000,3.2740000000,0.1580000000,0.0000000000,0.0000000000 -4081,2,4.6724000000,10.1010000000,0.4970000000,4.3110000000,0.1910000000,0.0000000000,0.0000000000 -4081,3,5.6724000000,11.9960000000,0.6150000000,6.2230000000,0.2230000000,0.0000000000,0.0000000000 -4081,4,6.6724000000,14.4210000000,0.7320000000,8.3450000000,0.2560000000,0.0000000000,0.0000000000 -4081,5,7.6724000000,16.7490000000,0.8490000000,9.7820000000,0.2880000000,4.4820000000,0.0640000000 -4081,6,8.6724000000,17.7250000000,0.9660000000,10.2970000000,0.3210000000,7.0560000000,0.1820000000 -4081,7,9.6724000000,15.1650000000,1.0830000000,11.6240000000,0.3530000000,13.1830000000,0.3000000000 -4081,8,10.6724000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.4180000000 -6061,1,5.0086000000,9.6090000000,0.3800000000,3.8270000000,0.1580000000,0.0000000000,0.0000000000 -6061,2,6.0086000000,11.7250000000,0.5440000000,5.9570000000,0.2040000000,0.0000000000,0.0000000000 -6061,3,7.0086000000,14.6950000000,0.7080000000,8.5480000000,0.2490000000,1.5600000000,0.0000000000 -6061,4,8.0086000000,17.3210000000,0.8720000000,10.0300000000,0.2950000000,5.0450000000,0.0640000000 -6061,5,9.0086000000,16.8780000000,1.0360000000,10.7180000000,0.3400000000,10.3270000000,0.3000000000 -6061,6,10.0086000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.5360000000 -6071,1,5.0086000000,9.7440000000,0.3800000000,3.9570000000,0.1580000000,0.0000000000,0.0000000000 -6071,2,6.0086000000,11.5750000000,0.5170000000,5.8070000000,0.1960000000,0.0000000000,0.0000000000 -6071,3,7.0086000000,14.0730000000,0.6540000000,8.0750000000,0.2340000000,0.0000000000,0.0000000000 -6071,4,8.0086000000,16.5880000000,0.7900000000,9.7050000000,0.2720000000,4.3510000000,0.0000000000 -6071,5,9.0086000000,17.7320000000,0.9270000000,10.2870000000,0.3100000000,6.9440000000,0.0640000000 -6071,6,10.0086000000,14.9950000000,1.0630000000,11.7240000000,0.3480000000,13.3760000000,0.3000000000 -6071,7,11.0086000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.5360000000 -4080,1,3.6724000000,5.7525000000,0.3443560000,3.2392218853,0.2387894562,0.0000000000,0.0000000000 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--- a/test/data/test_plantgen/full_full/dynT.csv +++ b/test/data/test_plantgen/full_full/dynT.csv @@ -1,11 +1,7 @@ id_axis,id_cohort,cardinality,N_phytomer_potential,a_cohort,TT_hs_0,TT_hs_break,TT_flag_ligulation,dTT_MS_cohort,n0,n1,n2,t0,t1,hs_t1,a,c,RMSE_gl -MS,1,4,11,0.0100000000,-0.7710000000,NA,1078.0000000000,0.0000000000,4.8720000000,3.2430000000,5.8000000000,486.4290000000,699.2290000000,7.0000000000,-0.0000000052,-0.0038096898,0.1689122432 -MS,1,1,10,0.0090000000,-0.7710000000,NA,1078.0000000000,0.0000000000,4.4290000000,2.9480000000,5.2730000000,491.3401111111,665.8956666667,6.0000000000,-0.0000000047,-0.0034635335,0.1689122432 -T1,4,4,8,0.0090000000,246.1010000000,NA,1148.0000000000,70.0000000000,3.6268560488,3.2430000000,4.9300000000,649.0850054173,769.2290000000,4.7081520000,-0.0000000044,-0.0032382363,0.1689122432 -T1.0,6,1,7,0.0080000000,334.4150000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,739.7900000000,3.6385120000,-0.0000000044,-0.0032382363,0.1689122432 -T1.0,6,1,6,0.0073747672,334.4150000000,NA,1148.0000000000,70.0000000000,NA,3.2430000000,4.9300000000,NA,774.1576925000,3.2066520400,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,2,7,0.0100000000,446.0520000000,NA,1158.0000000000,80.0000000000,NA,3.2430000000,4.9300000000,NA,770.3520000000,3.3317700000,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,2,8,0.0110000000,446.0520000000,NA,1158.0000000000,80.0000000000,NA,3.2430000000,4.9300000000,NA,740.8701818182,3.6649470000,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,1,6,0.0100000000,446.0520000000,NA,1158.0000000000,80.0000000000,NA,3.2430000000,4.9300000000,NA,770.3520000000,3.3317700000,-0.0000000044,-0.0032382363,0.1689122432 -T3,6,3,7,0.0080000000,334.4150000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,739.7900000000,3.6385120000,-0.0000000044,-0.0032382363,0.1689122432 -T3,6,1,6,0.0070000000,334.4150000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,797.7007142857,3.1836980000,-0.0000000044,-0.0032382363,0.1689122432 +MS,1,5,11,0.0100000,-0.7710000,NA,1078.0000000,0.0000000,4.8720000,3.2430000,5.8000000,486.4290000,699.2290000,7.0000000,-0.0000000,-0.0038097,0.1689122 +T1,4,4,8,0.0090000,246.1010000,NA,1148.0000000,70.0000000,3.6268560,3.2430000,4.9300000,649.0850054,769.2290000,4.7081520,-0.0000000,-0.0032382,0.1689122 +T1.0,6,2,7,0.0080000,334.4150000,NA,1168.0000000,90.0000000,NA,3.2430000,4.9300000,NA,739.7900000,3.6385120,-0.0000000,-0.0032382,0.1689122 +T2,5,3,7,0.0100000,446.0520000,NA,1158.0000000,80.0000000,NA,3.2430000,4.9300000,NA,770.3520000,3.3317700,-0.0000000,-0.0032382,0.1689122 +T2,5,2,8,0.0110000,446.0520000,NA,1158.0000000,80.0000000,NA,3.2430000,4.9300000,NA,740.8701818,3.6649470,-0.0000000,-0.0032382,0.1689122 +T3,6,4,7,0.0080000,334.4150000,NA,1168.0000000,90.0000000,NA,3.2430000,4.9300000,NA,739.7900000,3.6385120,-0.0000000,-0.0032382,0.1689122 diff --git a/test/data/test_plantgen/full_full/phenT.csv b/test/data/test_plantgen/full_full/phenT.csv index f9328416..c22d89d7 100644 --- a/test/data/test_plantgen/full_full/phenT.csv +++ b/test/data/test_plantgen/full_full/phenT.csv @@ -1,90 +1,78 @@ id_phen,index_phytomer,dTT_em_phytomer,dTT_col_phytomer,dTT_sen_phytomer,dTT_del_phytomer -1101,0,-111.1111111111,-111.1111111111,-57.1938255424,-57.1938255424 -1101,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 -1101,2,44.4444444444,111.1111111111,57.1938255424,57.1938255424 -1101,3,155.5555555556,222.2222222222,114.3876510849,114.3876510849 -1101,4,266.6666666667,333.3333333333,399.6537298773,399.6537298773 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--git a/test/data/test_plantgen/full_full/phenT_first.csv b/test/data/test_plantgen/full_full/phenT_first.csv index 8830f0f9..d41d256e 100644 --- a/test/data/test_plantgen/full_full/phenT_first.csv +++ b/test/data/test_plantgen/full_full/phenT_first.csv @@ -1,13 +1,12 @@ id_phen,index_phytomer,TT_em_phytomer,TT_col_phytomer,TT_sen_phytomer,TT_del_phytomer -1101,1,-22.9932222222,88.1178888889,548.5339366536,881.8672699869 -1111,1,-20.7710000000,79.2290000000,543.0699369178,843.0699369178 -4080,1,98.5832695035,334.9898888889,731.0860500753,1064.4193834086 -4081,1,223.8787777778,334.9898888889,731.0860500753,1064.4193834086 -5030,1,325.3556750484,518.7792727273,884.6372572658,1157.3645299931 -5040,1,325.3556750484,518.7792727273,884.6372572658,1157.3645299931 -5050,1,313.2860425532,526.0520000000,947.4022585089,1247.4022585089 -6040,1,144.7493465046,448.7007142857,1177.2693186042,1605.8407471757 -6050,1,168.4575531915,434.4150000000,986.0745376953,1361.0745376953 -6060,1,168.4575531915,434.4150000000,986.0745376953,1361.0745376953 -6061,1,305.8435714286,448.7007142857,1177.2693186042,1605.8407471757 -6071,1,309.4150000000,434.4150000000,986.0745376953,1361.0745376953 +1111.0000000,1,-20.7710000,79.2290000,543.0699369,843.0699369 +4050.0000000,1,98.5832695,334.9898889,731.0860501,1064.4193834 +4081.0000000,1,223.8787778,334.9898889,731.0860501,1064.4193834 +5030.0000000,1,325.3556750,518.7792727,884.6372573,1157.3645300 +5040.0000000,1,313.2860426,526.0520000,947.4022585,1247.4022585 +5050.0000000,1,313.2860426,526.0520000,947.4022585,1247.4022585 +5081.0000000,1,427.8701818,518.7792727,884.6372573,1157.3645300 +6040.0000000,1,168.4575532,434.4150000,986.0745377,1361.0745377 +6050.0000000,1,168.4575532,434.4150000,986.0745377,1361.0745377 +6060.0000000,1,168.4575532,434.4150000,986.0745377,1361.0745377 +6071.0000000,1,309.4150000,434.4150000,986.0745377,1361.0745377 diff --git a/test/data/test_plantgen/full_full/tilleringT.csv b/test/data/test_plantgen/full_full/tilleringT.csv index 0db47d0b..ea84544d 100644 --- a/test/data/test_plantgen/full_full/tilleringT.csv +++ b/test/data/test_plantgen/full_full/tilleringT.csv @@ -1,4 +1,4 @@ TT,axes_density --20.7710000000,12.0000000000 -689.8990000000,48.0000000000 -1126.3990000000,25.0000000000 +-20.7710000,12.0000000 +689.8990000,48.0000000 +1126.3990000,25.0000000 diff --git a/test/data/test_plantgen/min_min/HS_GL_SSI_T.csv b/test/data/test_plantgen/min_min/HS_GL_SSI_T.csv index e0edfa16..b2dc91e4 100644 --- a/test/data/test_plantgen/min_min/HS_GL_SSI_T.csv +++ b/test/data/test_plantgen/min_min/HS_GL_SSI_T.csv @@ -1,36001 +1,36001 @@ id_phen,TT,HS,GL,SSI -1101,0,0.0069995570,0.0069995570,0.0000000000 -1101,1,0.0160781006,0.0160781006,0.0000000000 -1101,2,0.0251566441,0.0251566441,0.0000000000 -1101,3,0.0342351876,0.0342351876,0.0000000000 -1101,4,0.0433137311,0.0433137311,0.0000000000 -1101,5,0.0523922746,0.0523922746,0.0000000000 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-1,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-34.2382270273,65.7617729727,529.6027098905,829.6027098905 -1,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,223.2003795456,335.5467545456,733.3764298336,1070.4155548336 -1,5,T2,7,6,5.1222526768,933.0000000000,1533.0000000000,5060,5060,NA,305.3473444464,425.1717730178,935.3812955651,1294.8545812793 -1,6,T1.0,7,4,3.9868876824,850.0000000000,1450.0000000000,6040,6040,NA,412.5041700273,518.0428843131,967.4241804973,1284.0403233545 -1,6,T3,7,5,4.3564203251,889.0000000000,1489.0000000000,6050,6050,NA,412.5041700273,518.0428843131,967.4241804973,1284.0403233545 -2,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-20.8647013463,79.1352986537,542.9762355715,842.9762355715 -2,5,T2,7,7,7.0000000000,NA,NA,5071,5071,1.0000000000,298.2896965535,418.1141251249,928.3236476722,1287.7969333865 -2,6,T3,7,4,3.6552558235,815.0000000000,1415.0000000000,6040,6040,NA,398.8747558626,504.4134701483,953.7947663326,1270.4109091897 -3,1,MS,10,10,10.0000000000,NA,NA,1101,1101,1.0000000000,-17.5652213677,92.5846059050,549.0274494983,879.4769313165 -3,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,218.7696927280,331.1160677280,728.9457430160,1065.9848680160 -3,5,T2,6,6,6.0000000000,NA,NA,5061,5061,1.0000000000,283.3274422988,419.7892756322,-1152921504606846464.0000000000,-1152921504606846080.0000000000 -3,6,T1.0,6,3,2.4272348217,720.0000000000,1320.0000000000,6030,6030,NA,397.4368210752,517.2319877419,1118.5600607497,1477.9455607497 -3,6,T3,6,3,2.6776622874,750.0000000000,1350.0000000000,6030,6030,NA,397.4368210752,517.2319877419,1118.5600607497,1477.9455607497 -4,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-14.2565954121,85.7434045879,549.5843415057,849.5843415057 -4,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,237.0993329497,349.4457079497,747.2753832376,1084.3145082376 -4,5,T2,8,4,3.4539685201,690.0000000000,1290.0000000000,5040,5040,NA,293.0313161839,400.3776911839,772.6456831628,1094.6848081628 -5,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-33.9480200986,66.0519799014,529.8929168192,829.8929168192 -5,4,T1,8,8,7.2612133680,1065.0000000000,1665.0000000000,4080,4080,NA,230.0576043228,342.4039793228,740.2336546107,1077.2727796107 -5,5,T2,8,7,6.2113974505,986.0000000000,1586.0000000000,5070,5070,NA,288.8880480474,396.2344230474,768.5024150264,1090.5415400264 -5,6,T3,7,4,3.3425743566,782.0000000000,1382.0000000000,6040,6040,NA,399.2754241928,504.8141384785,954.1954346628,1270.8115775199 +1.0000000,1.0000000,MS,11.0000000,11.0000000,11.0000000,NA,NA,1111.0000000,1111.0000000,1.0000000,-34.2382270,65.7617730,529.6027099,829.6027099 +1.0000000,4.0000000,T1,8.0000000,8.0000000,8.0000000,NA,NA,4081.0000000,4081.0000000,1.0000000,223.2003795,335.5467545,733.3764298,1070.4155548 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+4.0000000,4.0000000,T1,8.0000000,8.0000000,8.0000000,NA,NA,4081.0000000,4081.0000000,1.0000000,237.0993329,349.4457079,747.2753832,1084.3145082 +4.0000000,5.0000000,T2,8.0000000,8.0000000,8.0000000,NA,NA,5081.0000000,5081.0000000,1.0000000,293.0313162,400.3776912,772.6456832,1094.6848082 +5.0000000,1.0000000,MS,11.0000000,11.0000000,11.0000000,NA,NA,1111.0000000,1111.0000000,1.0000000,-33.9480201,66.0519799,529.8929168,829.8929168 +5.0000000,4.0000000,T1,8.0000000,5.0000000,4.4573846,750.0000000,1350.0000000,4050.0000000,4050.0000000,NA,230.0576043,342.4039793,740.2336546,1077.2727796 +5.0000000,5.0000000,T2,8.0000000,4.0000000,3.7334377,720.0000000,1320.0000000,5040.0000000,5040.0000000,NA,288.8880480,396.2344230,768.5024150,1090.5415400 +5.0000000,6.0000000,T3,7.0000000,3.0000000,2.4708563,690.0000000,1290.0000000,6030.0000000,6030.0000000,NA,399.2754242,504.8141385,954.1954347,1270.8115775 diff --git a/test/data/test_plantgen/min_min/cardinalityT.csv b/test/data/test_plantgen/min_min/cardinalityT.csv index 0efdeb10..b1e99827 100644 --- a/test/data/test_plantgen/min_min/cardinalityT.csv +++ b/test/data/test_plantgen/min_min/cardinalityT.csv @@ -1,10 +1,10 @@ id_cohort,id_axis,theoretical_cohort_cardinality,simulated_cohort_cardinality,theoretical_axis_cardinality,simulated_axis_cardinality -1,MS,5.0000000000,5,5.0000000000,5 -3,T0,0.0000000000,0,0.0000000000,0 -4,T1,4.5000000000,4,4.5000000000,4 -5,T2,4.8350000000,5,4.8350000000,5 -6,T1.0,6.6953150000,6,2.6103150000,2 -6,T3,6.6953150000,6,4.0850000000,4 -7,T1.1,0.9651115500,0,0.2651850000,0 -7,T2.0,0.9651115500,0,0.2849265500,0 -7,T4,0.9651115500,0,0.4150000000,0 +1,MS,5.0000000,5.0000000,5.0000000,5.0000000 +3,T0,0.0000000,0.0000000,0.0000000,0.0000000 +4,T1,4.5000000,4.0000000,4.5000000,4.0000000 +5,T2,4.8350000,5.0000000,4.8350000,5.0000000 +6,T1.0,6.6953150,6.0000000,2.6103150,2.0000000 +6,T3,6.6953150,6.0000000,4.0850000,4.0000000 +7,T1.1,0.9651116,0.0000000,0.2651850,0.0000000 +7,T2.0,0.9651116,0.0000000,0.2849266,0.0000000 +7,T4,0.9651116,0.0000000,0.4150000,0.0000000 diff --git a/test/data/test_plantgen/min_min/dimT.csv b/test/data/test_plantgen/min_min/dimT.csv index a21c8b24..fcf11a32 100644 --- a/test/data/test_plantgen/min_min/dimT.csv +++ b/test/data/test_plantgen/min_min/dimT.csv @@ -1,80 +1,75 @@ id_dim,index_phytomer,index_relative_to_MS_phytomer,L_blade,W_blade,L_sheath,W_sheath,L_internode,W_internode -1101,1,1.0000000000,9.4314366157,0.3794920246,3.0092091273,0.1580000000,0.0000000000,0.0000000000 -1101,2,2.0000000000,8.7440604620,0.3537366191,2.4376216914,0.1830000000,0.0000000000,0.0000000000 -1101,3,3.0000000000,8.9140967350,0.4869079092,3.2219424862,0.2090000000,0.0000000000,0.0000000000 -1101,4,4.0000000000,9.8754805895,0.6797122089,4.6377507170,0.2340000000,0.0000000000,0.0000000000 -1101,5,5.0000000000,11.5685474964,0.8619637784,6.1867727273,0.2590000000,0.0000000000,0.0000000000 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+6060,6,10.0086000,14.2320639,1.0398464,10.5037680,0.3345574,10.0439288,0.1920631 diff --git a/test/data/test_plantgen/min_min/dynT.csv b/test/data/test_plantgen/min_min/dynT.csv index 15ee1d5a..792d9aa9 100644 --- a/test/data/test_plantgen/min_min/dynT.csv +++ b/test/data/test_plantgen/min_min/dynT.csv @@ -1,11 +1,7 @@ id_axis,id_cohort,cardinality,N_phytomer_potential,a_cohort,TT_hs_0,TT_hs_break,TT_flag_ligulation,dTT_MS_cohort,n0,n1,n2,t0,t1,hs_t1,a,c,RMSE_gl -MS,1,4,11,0.0100000000,-0.7710000000,NA,1078.0000000000,0.0000000000,4.8720000000,3.2430000000,5.8000000000,486.4290000000,699.2290000000,7.0000000000,-0.0000000052,-0.0038096898,0.1689122432 -MS,1,1,10,0.0090785435,-0.7710000000,NA,1100.7272727273,-20.0000000000,4.4290909091,2.9481818182,5.2727272727,487.0925986116,660.1279636364,6.0000000000,-0.0000000047,-0.0034633543,0.1689122432 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-T2,5,1,6,0.0073280563,319.2290000000,NA,1138.0000000000,60.0000000000,NA,3.2430000000,4.9300000000,NA,761.7747255000,3.2243447802,-0.0000000044,-0.0032382363,0.1689122432 -T3,6,3,7,0.0094751960,429.2290000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,771.4910504286,3.4110705482,-0.0000000044,-0.0032382363,0.1689122432 -T3,6,1,6,0.0083475822,429.2290000000,NA,1148.0000000000,70.0000000000,NA,3.2430000000,4.9300000000,NA,817.7247255000,2.8381779454,-0.0000000044,-0.0032382363,0.1689122432 +MS,1,5,11,0.0100000,-0.7710000,NA,1078.0000000,0.0000000,4.8720000,3.2430000,5.8000000,486.4290000,699.2290000,7.0000000,-0.0000000,-0.0038097,0.1689122 +T1,4,4,8,0.0089010,249.2290000,NA,1148.0000000,70.0000000,3.5955441,3.2430000,4.9300000,653.1753510,769.2290000,4.6285428,-0.0000000,-0.0032382,0.1689122 +T1.0,6,2,7,0.0094752,429.2290000,NA,1168.0000000,90.0000000,NA,3.2430000,4.9300000,NA,771.4910504,3.4110705,-0.0000000,-0.0032382,0.1689122 +T2,5,3,7,0.0083455,319.2290000,NA,1158.0000000,80.0000000,NA,3.2430000,4.9300000,NA,707.8196219,3.8389501,-0.0000000,-0.0032382,0.1689122 +T2,5,2,8,0.0093156,319.2290000,NA,1178.0000000,100.0000000,3.3769435,3.2430000,4.9300000,681.7316481,799.2290000,4.4715064,-0.0000000,-0.0032382,0.1689122 +T3,6,4,7,0.0094752,429.2290000,NA,1168.0000000,90.0000000,NA,3.2430000,4.9300000,NA,771.4910504,3.4110705,-0.0000000,-0.0032382,0.1689122 diff --git a/test/data/test_plantgen/min_min/phenT.csv b/test/data/test_plantgen/min_min/phenT.csv index be1b2937..57f4c19f 100644 --- a/test/data/test_plantgen/min_min/phenT.csv +++ b/test/data/test_plantgen/min_min/phenT.csv @@ -1,92 +1,87 @@ id_phen,index_phytomer,dTT_em_phytomer,dTT_col_phytomer,dTT_sen_phytomer,dTT_del_phytomer -1101,0,-110.1498272727,-110.1498272727,-56.6991067999,-56.6991067999 -1101,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 -1101,2,44.0599309091,110.1498272727,56.6991067999,56.6991067999 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-1111,6,440.0000000000,500.0000000000,734.1167723419,734.1167723419 -1111,7,540.0000000000,600.0000000000,925.7808825809,2156.9300630822 -1111,8,640.0000000000,700.0000000000,1065.5959615205,2156.9300630822 -1111,9,740.0000000000,800.0000000000,1174.5836973376,2156.9300630822 -1111,10,840.0000000000,900.0000000000,1264.3361225686,2156.9300630822 -1111,11,940.0000000000,1000.0000000000,1341.0927616130,2156.9300630822 -4080,0,-112.3463750000,-112.3463750000,-83.7604243254,-83.7604243254 -4080,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 -4080,2,-31.0745292553,112.3463750000,170.4615195490,170.4615195490 -4080,3,81.2718457447,224.6927500000,395.3238608229,395.3238608229 -4080,4,240.9734301576,384.3943344129,673.5368621841,673.5368621841 -4080,5,480.0082705831,623.4291748385,872.6318061179,1926.0250997121 -4080,6,719.0431110087,862.4640152640,1014.8912829424,1926.0250997121 -4080,7,958.0779514342,1101.4988556895,1125.7098132577,1926.0250997121 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b/test/data/test_plantgen/min_min/phenT_first.csv index 28d54150..5f08a24b 100644 --- a/test/data/test_plantgen/min_min/phenT_first.csv +++ b/test/data/test_plantgen/min_min/phenT_first.csv @@ -1,13 +1,13 @@ id_phen,index_phytomer,TT_em_phytomer,TT_col_phytomer,TT_sen_phytomer,TT_del_phytomer -1101,1,-22.8009654545,87.3488618182,543.7917054115,874.2411872297 -1111,1,-20.7710000000,79.2290000000,543.0699369178,843.0699369178 -4080,1,100.0712595745,339.1061000000,736.9357752879,1073.9749002879 -4081,1,226.7597250000,339.1061000000,736.9357752879,1073.9749002879 -5040,1,176.7095574468,405.1061000000,777.3740919790,1099.4132169790 -5060,1,160.1429501520,415.0885428571,925.2980654044,1284.7713511187 -5061,1,291.9366333333,428.3984666667,-1152921504606846464.0000000000,-1152921504606846080.0000000000 -5070,1,176.7095574468,405.1061000000,777.3740919790,1099.4132169790 -5071,1,295.2641142857,415.0885428571,925.2980654044,1284.7713511187 -6030,1,270.1818000000,525.0651333333,1126.3932063411,1485.7787063411 -6040,1,289.1095155015,513.6599714286,963.0412676128,1279.6574104700 -6050,1,289.1095155015,513.6599714286,963.0412676128,1279.6574104700 +1111.0000000,1,-20.7710000,79.2290000,543.0699369,843.0699369 +4050.0000000,1,100.0712596,339.1061000,736.9357753,1073.9749003 +4081.0000000,1,226.7597250,339.1061000,736.9357753,1073.9749003 +5040.0000000,1,176.7095574,405.1061000,777.3740920,1099.4132170 +5060.0000000,1,160.1429502,415.0885429,925.2980654,1284.7713511 +5070.0000000,1,160.1429502,415.0885429,925.2980654,1284.7713511 +5071.0000000,1,295.2641143,415.0885429,925.2980654,1284.7713511 +5081.0000000,1,297.7597250,405.1061000,777.3740920,1099.4132170 +6030.0000000,1,289.1095155,513.6599714,963.0412676,1279.6574105 +6040.0000000,1,289.1095155,513.6599714,963.0412676,1279.6574105 +6050.0000000,1,289.1095155,513.6599714,963.0412676,1279.6574105 +6060.0000000,1,289.1095155,513.6599714,963.0412676,1279.6574105 diff --git a/test/data/test_plantgen/min_min/tilleringT.csv b/test/data/test_plantgen/min_min/tilleringT.csv index 0db47d0b..ea84544d 100644 --- a/test/data/test_plantgen/min_min/tilleringT.csv +++ b/test/data/test_plantgen/min_min/tilleringT.csv @@ -1,4 +1,4 @@ TT,axes_density --20.7710000000,12.0000000000 -689.8990000000,48.0000000000 -1126.3990000000,25.0000000000 +-20.7710000,12.0000000 +689.8990000,48.0000000 +1126.3990000,25.0000000 diff --git a/test/data/test_plantgen/short_short/HS_GL_SSI_T.csv b/test/data/test_plantgen/short_short/HS_GL_SSI_T.csv index a858acaa..ae67b7b0 100644 --- a/test/data/test_plantgen/short_short/HS_GL_SSI_T.csv +++ b/test/data/test_plantgen/short_short/HS_GL_SSI_T.csv @@ -1,39001 +1,33001 @@ id_phen,TT,HS,GL,SSI -1101,0,0.0069995570,0.0069995570,0.0000000000 -1101,1,0.0160781006,0.0160781006,0.0000000000 -1101,2,0.0251566441,0.0251566441,0.0000000000 -1101,3,0.0342351876,0.0342351876,0.0000000000 -1101,4,0.0433137311,0.0433137311,0.0000000000 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+6071,2992,7.0000000,0.0000000,7.0000000 +6071,2993,7.0000000,0.0000000,7.0000000 +6071,2994,7.0000000,0.0000000,7.0000000 +6071,2995,7.0000000,0.0000000,7.0000000 +6071,2996,7.0000000,0.0000000,7.0000000 +6071,2997,7.0000000,0.0000000,7.0000000 +6071,2998,7.0000000,0.0000000,7.0000000 +6071,2999,7.0000000,0.0000000,7.0000000 diff --git a/test/data/test_plantgen/short_short/axeT.csv b/test/data/test_plantgen/short_short/axeT.csv index bb7ead01..bd322997 100644 --- a/test/data/test_plantgen/short_short/axeT.csv +++ b/test/data/test_plantgen/short_short/axeT.csv @@ -1,21 +1,21 @@ id_plt,id_cohort,id_axis,N_phytomer_potential,N_phytomer,HS_final,TT_stop_axis,TT_del_axis,id_dim,id_phen,id_ear,TT_em_phytomer1,TT_col_phytomer1,TT_sen_phytomer1,TT_del_phytomer1 -1,1,MS,11,11,11.0000000000,NA,NA,1111,1111,1.0000000000,-34.2382270273,65.7617729727,529.6027098905,829.6027098905 -1,4,T1,8,8,8.0000000000,NA,NA,4081,4081,1.0000000000,222.9328110358,322.9328110358,694.9974874567,994.9974874567 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+5.0000000,1.0000000,MS,11.0000000,11.0000000,11.0000000,NA,NA,1111.0000000,1111.0000000,1.0000000,-33.9480201,66.0519799,529.8929168,829.8929168 +5.0000000,4.0000000,T1,8.0000000,6.0000000,5.0389900,750.0000000,1350.0000000,4060.0000000,4060.0000000,NA,229.0364568,329.0364568,701.1011332,1001.1011332 +5.0000000,5.0000000,T2,8.0000000,3.0000000,2.6662878,690.0000000,1290.0000000,5030.0000000,5030.0000000,NA,420.1917892,511.6852892,876.9741310,1151.4546310 +5.0000000,6.0000000,T3,7.0000000,4.0000000,3.0846800,720.0000000,1320.0000000,6040.0000000,6040.0000000,NA,298.9379999,423.9379999,975.5975376,1350.5975376 diff --git a/test/data/test_plantgen/short_short/cardinalityT.csv b/test/data/test_plantgen/short_short/cardinalityT.csv index 0efdeb10..b1e99827 100644 --- a/test/data/test_plantgen/short_short/cardinalityT.csv +++ b/test/data/test_plantgen/short_short/cardinalityT.csv @@ -1,10 +1,10 @@ id_cohort,id_axis,theoretical_cohort_cardinality,simulated_cohort_cardinality,theoretical_axis_cardinality,simulated_axis_cardinality -1,MS,5.0000000000,5,5.0000000000,5 -3,T0,0.0000000000,0,0.0000000000,0 -4,T1,4.5000000000,4,4.5000000000,4 -5,T2,4.8350000000,5,4.8350000000,5 -6,T1.0,6.6953150000,6,2.6103150000,2 -6,T3,6.6953150000,6,4.0850000000,4 -7,T1.1,0.9651115500,0,0.2651850000,0 -7,T2.0,0.9651115500,0,0.2849265500,0 -7,T4,0.9651115500,0,0.4150000000,0 +1,MS,5.0000000,5.0000000,5.0000000,5.0000000 +3,T0,0.0000000,0.0000000,0.0000000,0.0000000 +4,T1,4.5000000,4.0000000,4.5000000,4.0000000 +5,T2,4.8350000,5.0000000,4.8350000,5.0000000 +6,T1.0,6.6953150,6.0000000,2.6103150,2.0000000 +6,T3,6.6953150,6.0000000,4.0850000,4.0000000 +7,T1.1,0.9651116,0.0000000,0.2651850,0.0000000 +7,T2.0,0.9651116,0.0000000,0.2849266,0.0000000 +7,T4,0.9651116,0.0000000,0.4150000,0.0000000 diff --git a/test/data/test_plantgen/short_short/dimT.csv b/test/data/test_plantgen/short_short/dimT.csv index e6dc2e1f..8771bf42 100644 --- a/test/data/test_plantgen/short_short/dimT.csv +++ b/test/data/test_plantgen/short_short/dimT.csv @@ -1,78 +1,68 @@ id_dim,index_phytomer,index_relative_to_MS_phytomer,L_blade,W_blade,L_sheath,W_sheath,L_internode,W_internode -1101,1,1.0000000000,9.4314366157,0.3794920246,3.0092091273,0.1580000000,0.0000000000,0.0000000000 -1101,2,2.0000000000,8.7440604620,0.3537366191,2.4376216914,0.1830000000,0.0000000000,0.0000000000 -1101,3,3.0000000000,8.9140967350,0.4869079092,3.2219424862,0.2090000000,0.0000000000,0.0000000000 -1101,4,4.0000000000,9.8754805895,0.6797122089,4.6377507170,0.2340000000,0.0000000000,0.0000000000 -1101,5,5.0000000000,11.5685474964,0.8619637784,6.1867727273,0.2590000000,0.0000000000,0.0000000000 -1101,6,6.0000000000,13.8148688517,0.9925848242,7.5968819991,0.2840000000,0.0000000000,0.0000000000 -1101,7,7.0000000000,16.1574691976,1.0596054989,8.8220991529,0.3554000000,0.0000000000,0.1471788083 -1101,8,8.0000000000,17.6664250586,1.0801639012,10.0425919478,0.3554000000,5.8130096000,0.1832777967 -1101,9,9.0000000000,16.7098453915,1.1005060758,11.6646752811,0.3554000000,10.7295214750,0.2048666915 -1101,10,10.0000000000,10.6902336487,1.1959860140,14.3208111888,0.3554000000,15.3470000000,0.2119454926 -1111,1,1.0000000000,9.4460000000,0.3800000000,2.8430000000,0.1580000000,0.0000000000,0.0000000000 -1111,2,2.0000000000,9.2670000000,0.3740000000,2.9310000000,0.1830000000,0.0000000000,0.0000000000 -1111,3,3.0000000000,8.0290000000,0.4450000000,3.2440000000,0.2090000000,0.0000000000,0.0000000000 -1111,4,4.0000000000,9.6650000000,0.5790000000,3.8940000000,0.2340000000,0.0000000000,0.0000000000 -1111,5,5.0000000000,11.2600000000,0.7500000000,4.4820000000,0.2590000000,0.0000000000,0.0000000000 -1111,6,6.0000000000,12.3280000000,0.9860000000,6.8130000000,0.2840000000,0.0000000000,0.0000000000 -1111,7,7.0000000000,14.0730000000,1.0200000000,8.8920000000,0.3100000000,1.5530000000,0.0000000000 -1111,8,8.0000000000,17.2530000000,1.0600000000,9.5800000000,0.3350000000,4.4470000000,0.0640000000 -1111,9,9.0000000000,17.7470000000,1.0800000000,10.1170000000,0.3600000000,6.4270000000,0.1340000000 -1111,10,10.0000000000,16.2640000000,1.1000000000,11.0730000000,0.3860000000,11.3000000000,0.1920000000 -1111,11,11.0000000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.3000000000 -4081,1,3.6724000000,9.0340000000,0.3800000000,3.3130000000,0.1580000000,0.0000000000,0.0000000000 -4081,2,4.6724000000,10.0340000000,0.4830000000,4.2440000000,0.1860000000,0.0000000000,0.0000000000 -4081,3,5.6724000000,11.6570000000,0.5850000000,5.8890000000,0.2150000000,0.0000000000,0.0000000000 -4081,4,6.6724000000,13.7490000000,0.6880000000,7.8120000000,0.2430000000,0.0000000000,0.0000000000 -4081,5,7.6724000000,15.9440000000,0.7900000000,9.3620000000,0.2720000000,3.7510000000,0.0000000000 -4081,6,8.6724000000,17.5290000000,0.8930000000,10.1150000000,0.3000000000,5.4060000000,0.0640000000 -4081,7,9.6724000000,17.2860000000,0.9950000000,10.5300000000,0.3290000000,9.2090000000,0.1820000000 -4081,8,10.6724000000,13.3150000000,1.0980000000,12.8040000000,0.3570000000,14.7330000000,0.3000000000 -6061,1,5.0086000000,6.5000000000,0.3800000000,5.5009652173,0.3162595280,0.0000000000,0.0000000000 -6061,2,6.0086000000,11.1134718671,0.5334960000,6.8640743929,0.3557395280,0.0000000000,0.0000000000 -6061,3,7.0086000000,14.2481874253,0.6869920000,8.0688770572,0.3691871988,1.6084847972,0.1475511164 -6061,4,8.0086000000,16.9702666443,0.8404880000,9.1516642834,0.3691871988,4.4570980603,0.1835253180 -6061,5,9.0086000000,18.0464227732,0.9939840000,10.3031886831,0.3691871988,6.4565350120,0.2049894260 -6061,6,10.0086000000,16.0814281565,1.1474800000,11.8686644064,0.3691871988,11.3490720523,0.2119434403 -6071,1,5.0086000000,9.7440000000,0.3800000000,3.9570000000,0.1580000000,0.0000000000,0.0000000000 -6071,2,6.0086000000,11.5750000000,0.5170000000,5.8070000000,0.1960000000,0.0000000000,0.0000000000 -6071,3,7.0086000000,14.0730000000,0.6540000000,8.0750000000,0.2340000000,0.0000000000,0.0000000000 -6071,4,8.0086000000,16.5880000000,0.7900000000,9.7050000000,0.2720000000,4.3510000000,0.0000000000 -6071,5,9.0086000000,17.7320000000,0.9270000000,10.2870000000,0.3100000000,6.9440000000,0.0640000000 -6071,6,10.0086000000,14.9950000000,1.0630000000,11.7240000000,0.3480000000,13.3760000000,0.3000000000 -6071,7,11.0086000000,10.7360000000,1.2000000000,14.7200000000,0.3860000000,15.3470000000,0.5360000000 -4080,1,3.6724000000,5.7525000000,0.3443560000,3.2392218853,0.2387894562,0.0000000000,0.0000000000 -4080,2,4.6724000000,7.7973320569,0.4437117680,4.4456347515,0.2745662322,0.0000000000,0.0000000000 -4080,3,5.6724000000,9.8421641137,0.5430675360,5.6823918576,0.3103430082,0.0000000000,0.0000000000 -4080,4,6.6724000000,11.8210564680,0.6424233040,6.7989543192,0.3345574395,0.0000000000,0.1197972856 -4080,5,7.6724000000,14.2835677104,0.7417790720,7.7814817133,0.3345574395,3.5387599257,0.1568178167 -4080,6,8.6724000000,15.9086211272,0.8411348400,8.7528320784,0.3345574395,4.8603373153,0.1806893009 -4080,7,9.6724000000,15.1560185128,0.9404906080,9.9725619145,0.3345574395,8.3720541330,0.1914117382 -4080,8,10.6724000000,11.3940141615,1.0398463760,11.8369261833,0.3345574395,12.9645784549,0.1889851286 -5030,1,4.3405000000,5.7525000000,0.3443560000,4.0305293483,0.2626919202,0.0000000000,0.0000000000 -5030,2,5.3405000000,8.4774429807,0.6921011880,5.2806343513,0.2984686962,0.0000000000,0.0000000000 -5030,3,6.3405000000,11.2023859614,1.0398463760,6.4453526438,0.3342454722,0.0000000000,0.0000000000 -5040,1,4.3405000000,5.7525000000,0.3443560000,4.0305293483,0.2626919202,0.0000000000,0.0000000000 -5040,2,5.3405000000,8.4774429807,0.5761861253,5.2806343513,0.2984686962,0.0000000000,0.0000000000 -5040,3,6.3405000000,11.2023859614,0.8080162507,6.4453526438,0.3342454722,0.0000000000,0.0000000000 -5040,4,7.3405000000,13.4572280132,1.0398463760,7.4654735833,0.3345574395,2.8216172755,0.1459885530 -5050,1,4.3405000000,5.7525000000,0.3443560000,4.0305293483,0.2626919202,0.0000000000,0.0000000000 -5050,2,5.3405000000,8.4774429807,0.5182285940,5.2806343513,0.2984686962,0.0000000000,0.0000000000 -5050,3,6.3405000000,11.2023859614,0.6921011880,6.4453526438,0.3342454722,0.0000000000,0.0000000000 -5050,4,7.3405000000,13.4572280132,0.8659737820,7.4654735833,0.3345574395,2.8216172755,0.1459885530 -5050,5,8.3405000000,15.5757141597,1.0398463760,8.4184849890,0.3345574395,4.3154065965,0.1742242058 -6040,1,5.0086000000,5.7525000000,0.3443560000,4.8683542173,0.2865943843,0.0000000000,0.0000000000 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a/test/data/test_plantgen/short_short/dynT.csv b/test/data/test_plantgen/short_short/dynT.csv index 201b4596..7448552c 100644 --- a/test/data/test_plantgen/short_short/dynT.csv +++ b/test/data/test_plantgen/short_short/dynT.csv @@ -1,11 +1,7 @@ id_axis,id_cohort,cardinality,N_phytomer_potential,a_cohort,TT_hs_0,TT_hs_break,TT_flag_ligulation,dTT_MS_cohort,n0,n1,n2,t0,t1,hs_t1,a,c,RMSE_gl -MS,1,4,11,0.0100000000,-0.7710000000,NA,1078.0000000000,0.0000000000,4.8720000000,3.2430000000,5.8000000000,486.4290000000,699.2290000000,7.0000000000,-0.0000000052,-0.0038096898,0.1689122432 -MS,1,1,10,0.0090785435,-0.7710000000,NA,1100.7272727273,-20.0000000000,4.4290909091,2.9481818182,5.2727272727,487.0925986116,660.1279636364,6.0000000000,-0.0000000047,-0.0034633543,0.1689122432 -T1,4,4,8,0.0100000000,246.1010000000,NA,1148.0000000000,70.0000000000,3.8015861379,3.2430000000,4.9300000000,626.2596137876,769.2290000000,5.2312800000,-0.0000000044,-0.0032382363,0.1689122432 -T1.0,6,1,7,0.0080000000,334.4150000000,NA,1168.0000000000,90.0000000000,NA,3.2430000000,4.9300000000,NA,739.7900000000,3.6385120000,-0.0000000044,-0.0032382363,0.1689122432 -T1.0,6,1,6,0.0073747672,334.4150000000,NA,1148.0000000000,70.0000000000,NA,3.2430000000,4.9300000000,NA,774.1576925000,3.2066520400,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,2,7,0.0110000000,446.0520000000,NA,1158.0000000000,80.0000000000,NA,3.2430000000,4.9300000000,NA,740.8701818182,3.6649470000,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,2,8,0.0109297382,446.0520000000,NA,1178.0000000000,100.0000000000,NA,3.2430000000,4.9300000000,NA,742.7654205000,3.8601321405,-0.0000000044,-0.0032382363,0.1689122432 -T2,5,1,6,0.0086711718,446.0520000000,NA,1138.0000000000,60.0000000000,NA,3.2430000000,4.9300000000,NA,820.0498940000,2.7156115777,-0.0000000044,-0.0032382363,0.1689122432 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+T2,5,2,8,0.0109297,446.0520000,NA,1178.0000000,100.0000000,NA,3.2430000,4.9300000,NA,742.7654205,3.8601321,-0.0000000,-0.0032382,0.1689122 +T3,6,4,7,0.0080000,334.4150000,NA,1168.0000000,90.0000000,NA,3.2430000,4.9300000,NA,739.7900000,3.6385120,-0.0000000,-0.0032382,0.1689122 diff --git a/test/data/test_plantgen/short_short/phenT.csv b/test/data/test_plantgen/short_short/phenT.csv index 9cc0dff3..67705b02 100644 --- a/test/data/test_plantgen/short_short/phenT.csv +++ b/test/data/test_plantgen/short_short/phenT.csv @@ -1,90 +1,79 @@ id_phen,index_phytomer,dTT_em_phytomer,dTT_col_phytomer,dTT_sen_phytomer,dTT_del_phytomer -1101,0,-110.1498272727,-110.1498272727,-56.6991067999,-56.6991067999 -1101,1,0.0000000000,0.0000000000,0.0000000000,0.0000000000 -1101,2,44.0599309091,110.1498272727,56.6991067999,56.6991067999 -1101,3,154.2097581818,220.2996545455,113.3982135998,113.3982135998 -1101,4,264.3595854545,330.4494818182,365.6824760121,365.6824760121 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+6071.0000000,6,859.4150000,1059.4150000,1882.6455883,3000.0000000 +6071.0000000,7,984.4150000,1184.4150000,1974.1626982,3000.0000000 diff --git a/test/data/test_plantgen/short_short/phenT_first.csv b/test/data/test_plantgen/short_short/phenT_first.csv index 857deb0b..1d57195d 100644 --- a/test/data/test_plantgen/short_short/phenT_first.csv +++ b/test/data/test_plantgen/short_short/phenT_first.csv @@ -1,13 +1,12 @@ id_phen,index_phytomer,TT_em_phytomer,TT_col_phytomer,TT_sen_phytomer,TT_del_phytomer -1101,1,-22.8009654545,87.3488618182,543.7917054115,874.2411872297 -1111,1,-20.7710000000,79.2290000000,543.0699369178,843.0699369178 -4080,1,113.3350425532,326.1010000000,698.1656764208,998.1656764208 -4081,1,226.1010000000,326.1010000000,698.1656764208,998.1656764208 -5030,1,324.5797787234,519.2468000000,884.5356418355,1159.0161418355 -5040,1,324.5797787234,519.2468000000,884.5356418355,1159.0161418355 -5050,1,325.3556750484,518.7792727273,884.6372572658,1157.3645299931 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+6071.0000000,1,309.4150000,434.4150000,986.0745377,1361.0745377 diff --git a/test/data/test_plantgen/short_short/tilleringT.csv b/test/data/test_plantgen/short_short/tilleringT.csv index 0db47d0b..ea84544d 100644 --- a/test/data/test_plantgen/short_short/tilleringT.csv +++ b/test/data/test_plantgen/short_short/tilleringT.csv @@ -1,4 +1,4 @@ TT,axes_density --20.7710000000,12.0000000000 -689.8990000000,48.0000000000 -1126.3990000000,25.0000000000 +-20.7710000,12.0000000 +689.8990000,48.0000000 +1126.3990000,25.0000000 diff --git a/test/bck_test_plantgen.py b/test/test_plantgen.py similarity index 95% rename from test/bck_test_plantgen.py rename to test/test_plantgen.py index 178f2eab..15a93c31 100644 --- a/test/bck_test_plantgen.py +++ b/test/test_plantgen.py @@ -3,7 +3,7 @@ from openalea.adel.plantgen import params, tools, plantgen_interface, plantgen_core import numpy as np import pandas -from pathlib import Path as path +from pathlib import Path import tempfile @@ -33,7 +33,7 @@ ears_density = 25 GL_number = {1117.0: 5.6, 1212.1: 5.4, 1368.7: 4.9, 1686.8: 2.4, 1880.0: 0.0} delais_TT_stop_del_axis = 600 -TT_hs_break = np.NaN # linear mode +TT_hs_break = np.nan # linear mode TT_flag_ligulation = { "MS": 1078.0, "T1": 1148.0, @@ -42,21 +42,21 @@ "T4": 1178.0, } number_of_ears = plants_number * ears_density / float(plants_density) - -expected_results_dir = path(__file__).parent.resolve() / path("data/test_plantgen") +this_dir = Path(__file__).parent if '__file__' in globals() else Path(".") +expected_results_dir = this_dir.resolve() / "data" / "test_plantgen" default_expected_results_dir = expected_results_dir.joinpath("default") min_min_expected_results_dir = expected_results_dir.joinpath("min_min") short_short_expected_results_dir = expected_results_dir.joinpath("short_short") full_full_expected_results_dir = expected_results_dir.joinpath("full_full") -tmp_results_directory = path(tempfile.mkdtemp(suffix="_plantgen_results")) +tmp_results_directory = Path(tempfile.mkdtemp(suffix="_plantgen_results")) default_results = tmp_results_directory.joinpath("default") if not default_results.exists(): default_results.mkdir() relative_tolerance = 10e-3 absolute_tolerance = 10e-3 -OUTPUTS_PRECISION = 10 +OUTPUTS_PRECISION = 7 FLOAT_FORMAT = "%.{}f".format(OUTPUTS_PRECISION) @@ -125,7 +125,10 @@ def test_phenology_functions(): ) print("The results have been saved to %s" % test_table_filepath) assert len(dynT_) == len(expected_dynT) - assert dynT_["id_axis"] == expected_dynT["id_axis"] + pandas.testing.assert_series_equal( + dynT_["id_axis"], + expected_dynT["id_axis"] + ) dynT_ = dynT_.drop("id_axis", axis=1) expected_dynT = expected_dynT.drop(["id_axis"], axis=1) np.testing.assert_allclose(