add lab 2

Author: eeholmes

Labs/Week 3/ESA lab/Data_Images/LCR-chinook-regions.png

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+# Create data files
+library(rCAX)
+library(tidyr)
+columbia.river <- NULL
+for(i in c(17, 20, 15, 11, 2)){
+esuname <- rCAX:::caxesu[i]
+a <- rcax_hli("NOSA", type="colnames")
+tab <- rcax_hli("NOSA", flist = list(esu_dps = esuname))
+# find the pops with no data and remove
+tab <- tab %>% 
+  subset((datastatus == "Final" | datastatus == "Reviewed") & bestvalue=="Yes")
+if(i == 17 | i == 20) tab$value <- tab$tsaij else tab$value <- tab$tsaej
+aa <- tab %>% 
+  group_by(esapopname, run) %>% 
+  summarize(n = sum(value!= "" & value!="0" & majorpopgroup != ""))
+bad <- aa[which(aa$n==0),]
+aa <- tab %>% 
+  group_by(esapopname, run) %>% 
+  summarize(n = any(duplicated(spawningyear)))
+df <- tab %>% 
+  subset(!(esapopname %in% bad$esapopname & run %in% bad$run)) %>%
+  mutate(value = as.numeric(value))
+
+# get the min and max years in data
+years <- min(df$spawningyear[!is.na(df$value)]):max(df$spawningyear[!is.na(df$value)])
+# fill out the missing years with NAs
+df <- df %>%
+  select(species, esu_dps, majorpopgroup, esapopname, commonpopname, spawningyear, value, run) %>% 
+  group_by(species, esu_dps, majorpopgroup, esapopname, commonpopname, run) %>% 
+  complete(spawningyear=years, fill=list(value=NA))
+
+# Deal with pops with multiple data
+if(any(aa$n)){
+  cat(aa$esapopname[aa$n], "has duplicated years\n")
+  df <- df %>% ungroup() %>%
+    group_by(species, esu_dps, majorpopgroup, esapopname, run, spawningyear) %>%
+    summarize(value = mean(value, na.rm = TRUE,
+              commonpopname = commonpopname[1]))
+}
+if(i == 17 | i == 20) df$value_type <- "tsaij" else df$value_type <- "tsaej"
+columbia.river <- bind_rows(columbia.river, df)
+}
+columbia.river <- columbia.river %>% subset(species != "") %>% ungroup()
+save(columbia.river, file = file.path("Lab-2", "Data_Images/columbia-river.rda"))
+
+unique(lower.columbia.river$esu_dps)
+df <- lower.columbia.river %>% subset(species == "Steelhead" & run == "Winter")
+ggplot(df, aes(x=spawningyear, y=log(value), color=majorpopgroup)) + 
+  geom_point(size=0.2) + 
+  theme(strip.text.x = element_text(size = 2)) +
+  theme(axis.text.x = element_text(size = 5, angle = 90)) +
+  facet_wrap(~esapopname)

Labs/Week 3/ESA lab/Data_Images/LCR-coho-regions.png

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+# Create data files
+# remotes:::install_github("nwfsc-cb/rCAX@*release")
+library(rCAX)
+library(tidyr)
+x <-  rCAX:::caxesu
+valid_esu <- which(!str_detect(x, "XN") & !str_detect(x,"N/A"))
+esa.salmon <- NULL
+for(i in valid_esu){
+esuname <- rCAX:::caxesu[i]
+print(esuname)
+a <- rcax_hli("NOSA", type="colnames")
+tab <- rcax_hli("NOSA", flist = list(esu_dps = esuname))
+# error no data
+if (!is.data.frame(tab)) next
+# find the pops with no data and remove
+tab <- tab %>% 
+  subset((datastatus == "Final" | datastatus == "Reviewed") & bestvalue=="Yes")
+if(tab$tsaej[1]=="") tab$value <- tab$tsaij else tab$value <- tab$tsaej
+aa <- tab %>% 
+  group_by(esapopname, run) %>% 
+  summarize(n = sum(value!= "" & value!="0" & majorpopgroup != ""))
+bad <- aa[which(aa$n==0),]
+aa <- tab %>% 
+  group_by(esapopname, run) %>% 
+  summarize(n = any(duplicated(spawningyear)))
+df <- tab %>% 
+  subset(!(esapopname %in% bad$esapopname & run %in% bad$run)) %>%
+  mutate(value = as.numeric(value))
+
+# get the min and max years in data
+years <- min(df$spawningyear[!is.na(df$value)]):max(df$spawningyear[!is.na(df$value)])
+# fill out the missing years with NAs
+df <- df %>%
+  select(species, esu_dps, majorpopgroup, esapopname, commonpopname, spawningyear, value, run) %>% 
+  group_by(species, esu_dps, majorpopgroup, esapopname, commonpopname, run) %>% 
+  complete(spawningyear=years, fill=list(value=NA))
+
+# Deal with pops with multiple data
+if(any(aa$n)){
+  cat(aa$esapopname[aa$n], "has duplicated years\n")
+  df <- df %>% ungroup() %>%
+    group_by(species, esu_dps, majorpopgroup, esapopname, run, spawningyear) %>%
+    summarize(value = mean(value, na.rm = TRUE,
+              commonpopname = commonpopname[1]))
+}
+#if(i == 17 | i == 20) df$value_type <- "tsaij" else df$value_type <- "tsaej"
+esa.salmon <- bind_rows(esa.salmon, df)
+}
+esa.salmon <- esa.salmon %>% subset(species != "") %>% ungroup()
+save(esa.salmon, file = file.path("Lab-2", "Data_Images/esa-salmon.rda"))
+
+unique(esa.salmon$esu_dps)
+df <- esa.salmon %>% subset(species == "Steelhead" & run == "Winter")
+ggplot(df, aes(x=spawningyear, y=log(value), color=majorpopgroup)) + 
+  geom_point(size=0.2) + 
+  theme(strip.text.x = element_text(size = 2)) +
+  theme(axis.text.x = element_text(size = 5, angle = 90)) +
+  facet_wrap(~esapopname)