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Merge pull request #244 from NEFSC/dev_branch
v2.2.0 Age Structure and v6681 Code Update
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,44 @@ | ||
| #Script to compare initial numbers weight between reference and run | ||
| library(ncdf4) | ||
| dev.init = nc_open('/net/work3/EDAB/atlantis/dev_branch/currentVersion/neus_init.nc') | ||
| master.init = nc_open('/net/work3/EDAB/atlantis/master_branch/currentVersion/neus_init.nc') | ||
| new.6536.init = nc_open(here::here('currentVersion','neus_init_rescale_age.nc')) | ||
| nre.6665.init = nc_open('/net/work3/EDAB/atlantis/Rob_proj/currentVersion/neus_init.nc') | ||
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| fgs.dev = read.csv('/net/work3/EDAB/atlantis/dev_branch/currentVersion/neus_groups.csv',as.is = T) | ||
| fgs.master = read.csv('/net/work3/EDAB/atlantis/master_branch/currentVersion/neus_groups.csv',as.is = T) | ||
| fgs.6536 = read.csv(here::here('currentVersion','neus_groups.csv'),as.is = T) | ||
| fgs.6665 = read.csv('/net/work3/EDAB/atlantis/Rob_proj/currentVersion/neus_groups.csv',as.is = T) | ||
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| vert.names = fgs.dev$Name[which(fgs.dev$NumCohorts >2)] | ||
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| out.df = data.frame(Name = vert.names, dev = NA,master = NA, new.6536 = NA, new.6665 = NA) | ||
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| i=1 | ||
| for(i in 1:length(vert.names)){ | ||
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| ncohort.dev = fgs.dev$NumCohorts[which(fgs.dev$Name == vert.names[i])] | ||
| ncohort.master = fgs.master$NumCohorts[which(fgs.master$Name == vert.names[i])] | ||
| ncohort.6536 = fgs.6536$NumCohorts[which(fgs.6536$Name == vert.names[i])] | ||
| ncohort.6665 = fgs.6665$NumCohorts[which(fgs.6665$Name == vert.names[i])] | ||
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| out.dev = lapply(1:ncohort.dev,function(x){ | ||
| return(sum(ncvar_get(dev.init,paste0(vert.names[i],x,'_Nums')),na.rm=T)) | ||
| }) | ||
| out.master = lapply(1:ncohort.master,function(x){ | ||
| return(sum(ncvar_get(master.init,paste0(vert.names[i],x,'_Nums')),na.rm=T)) | ||
| }) | ||
| out.6536 = lapply(1:ncohort.6536,function(x){ | ||
| return(sum(ncvar_get(new.6536.init,paste0(vert.names[i],x,'_Nums')),na.rm=T)) | ||
| }) | ||
| out.6665 = lapply(1:ncohort.6665,function(x){ | ||
| return(sum(ncvar_get(nre.6665.init,paste0(vert.names[i],x,'_Nums')),na.rm=T)) | ||
| }) | ||
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| out.df$dev[i] = sum(unlist(out.dev)) | ||
| out.df$master[i] = sum(unlist(out.master)) | ||
| out.df$new.6536[i] = sum(unlist(out.6536)) | ||
| out.df$new.6665[i] = sum(unlist(out.6665)) | ||
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| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,112 @@ | ||
| #Script to compare weight at age for species between reference data and run | ||
| #Determine if mum needs to be rescaled | ||
| library(ggplot2) | ||
| library(dplyr) | ||
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| #get run info | ||
| run.name = '6536_new_age_param_init_rescale_2' | ||
| run.dir = here::here('Atlantis_Runs',run.name,'') | ||
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| fgs = read.csv(here::here('currentVersion','neus_groups.csv'),as.is = T)%>% | ||
| select(Code,LongName,NumCohorts,NumAgeClassSize) | ||
| fgs.old = read.csv(here::here('diagnostics','neus_groups_v2_0_1.csv'),as.is = T)%>% | ||
| select(Code,LongName,NumCohorts,NumAgeClassSize) | ||
| fgs$spp.change= fgs.old$NumCohorts != fgs$NumCohorts | ||
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| #Read in reference survey length weigth age: indwt = kg, len = cm | ||
| ref.stats.survdat = readRDS(here::here('data','survey_lenagewgt.rds'))%>% | ||
| group_by(Code,AGE)%>% | ||
| summarise(LENGTH = mean(LENGTH,na.rm=T), | ||
| WEIGHT = mean(INDWT,na.rm=T))%>% | ||
| rename(ref.len = 'LENGTH', | ||
| ref.wgt = 'WEIGHT') | ||
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| ref.stats.fishbase = read.csv(here::here('diagnostics','fishbase_len_wgt_ref.csv'),as.is = T)%>% | ||
| mutate(ref.wgt = Weight_g/1000)%>% | ||
| rename(ref.len = 'Length', | ||
| AGE = 'Age')%>% | ||
| select(Code,AGE,ref.len,ref.wgt) | ||
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| ref.stats.all = ref.stats.survdat %>% | ||
| bind_rows(ref.stats.fishbase) | ||
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| ref.spp = unique(ref.stats.all$Code) | ||
| i=1 | ||
| ref.stats.spp.ls = list() | ||
| for(i in 1:length(ref.spp)){ | ||
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| fgs.match = which(fgs$Code == ref.spp[i]) | ||
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| spp.agecl = 1:fgs$NumCohorts[fgs.match] | ||
| spp.age = c(0,(1:fgs$NumCohorts[fgs.match])*fgs$NumAgeClassSize[fgs.match],Inf) | ||
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| ref.stats.spp = ref.stats.all %>% | ||
| filter(Code == ref.spp[i] & !is.na(AGE)) | ||
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| spp.age.match = cut(ref.stats.spp$AGE+1,spp.age,labels = F,right =F) | ||
| spp.age.match[spp.age.match>fgs$NumCohorts[fgs.match]] = fgs$NumCohorts[fgs.match] | ||
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| ref.stats.spp$agecl = spp.age.match | ||
| ref.stats.spp.ls[[i]] = ref.stats.spp | ||
| } | ||
| ref.stats.all2 = bind_rows(ref.stats.spp.ls) | ||
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| #Get run length weight stats | ||
| run.wgt = readRDS(paste0(run.dir,'Post_Processed/Data/max_weight.rds'))%>% | ||
| group_by(species,agecl)%>% | ||
| summarise(maxMeanWeight = max(maxMeanWeight,na.rm=T)/1000) | ||
| run.len = readRDS(paste0(run.dir,'Post_Processed/Data/length_age.rds'))%>% | ||
| group_by(species,agecl)%>% | ||
| summarise(length = mean(atoutput,na.rm=T)) | ||
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| run.stats = run.wgt %>% | ||
| left_join(run.len)%>% | ||
| left_join(fgs,by = c(species = 'LongName'))%>% | ||
| # mutate(AGE = agecl * NumAgeClassSize)%>% | ||
| rename(run.wgt = 'maxMeanWeight', | ||
| run.len = 'length') | ||
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| #Combine and create scalar based on length and weight | ||
| combined.stats = run.stats%>% | ||
| left_join(ref.stats.all2)%>% | ||
| select(Code,species,spp.change,agecl,AGE,run.len,ref.len,run.wgt,ref.wgt)%>% | ||
| mutate(len.scale = ref.len / run.len, | ||
| wgt.scale = ref.wgt / run.wgt) | ||
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| mean.scale.wgt = combined.stats %>% | ||
| group_by(Code,spp.change,agecl)%>% | ||
| summarise(mum.scale = mean(wgt.scale,na.rm=T))%>% | ||
| # group_by(Code,spp.change)%>% | ||
| # summarise(mum.scale = mean(mum.scale,na.rm=T))%>% | ||
| filter(spp.change == T) | ||
| # filter(spp.change == T & is.na(mum.scale)) | ||
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| source(here::here('R','Calibration_Tools','edit_param_mum_age.R')) | ||
| mum.orig = get_param_mum_age(bio.prm = here::here('currentVersion','at_biology_rescale_mumC.prm')) | ||
| new.mum = mum.orig | ||
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| spp.names = sort(unique(mean.scale.wgt$Code)) | ||
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| j = 1 | ||
| for(j in 1:length(spp.names)){ | ||
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| which.mum = which(mum.orig$group == spp.names[j] ) | ||
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| mum.age.scale = filter(mean.scale.wgt,Code == spp.names[j]) %>% arrange(agecl) | ||
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| mean.scale = mean(mum.age.scale$mum.scale,na.rm=T) | ||
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| mum.scale.spp = mum.age.scale$mum.scale | ||
| mum.scale.spp[is.na(mum.scale.spp)] = mean.scale | ||
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| mum.orig.spp = as.numeric(mum.orig[which.mum,2:ncol(mum.orig)]) | ||
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| new.mum[which.mum,2:ncol(new.mum)] = signif(mum.orig.spp * mum.scale.spp,2) | ||
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| } | ||
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| edit_param_mum_age(bio.prm = here::here('currentVersion','at_biology_rescale_mumC.prm'), | ||
| single.group = F, | ||
| new.mum = new.mum, | ||
| overwrite = T) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,47 @@ | ||
| #Changes FSP parameter in at_biology.prm | ||
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| get_param_FSP = function(bio.prm, group.name = NA){ | ||
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| bio.lines = readLines(bio.prm) | ||
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| FSP.line = grep(paste0('^FSP_'),bio.lines) | ||
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| groups = sapply(bio.lines[FSP.line],function(x) return(strsplit(x,'\t| |_')[[1]][2]),USE.NAMES = F) | ||
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| group.vals = sapply(bio.lines[FSP.line],function(x) strsplit(x,' |\t')[[1]][2], USE.NAMES = F) | ||
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| if(is.na(group.name)){ | ||
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| return(data.frame(Code = groups, FSP = group.vals)) | ||
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| }else{ | ||
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| return(group.vals[which(groups == group.name)]) | ||
| } | ||
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| return(out.df) | ||
| } | ||
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| edit_param_FSP = function(bio.prm,group.name,value,unit = 'value',overwrite = F, new.file.name){ | ||
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| bio.lines = readLines(bio.prm) | ||
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| FSP.line = grep(paste0('FSP_',group.name),bio.lines) | ||
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| if(unit == 'value'){ | ||
| new.val = value | ||
| }else{ | ||
| old.val = as.numeric(strsplit(bio.lines[FSP.line],' |\t')[[1]][2]) | ||
| new.val = old.val * value | ||
| } | ||
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| bio.lines[FSP.line] = paste0('FSP_',group.name,' ',new.val) | ||
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| if(overwrite){ | ||
| writeLines(bio.lines, con = bio.prm) | ||
| }else{ | ||
| file.copy(bio.prm, new.file.name, overwrite = T) | ||
| writeLines(bio.lines, con = new.file.name ) | ||
| } | ||
| } |
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