update for widow rockfish

pfmc-assessments · Jan 15, 2025 · 4fe162b · 4fe162b
1 parent 1d05a26
commit 4fe162b
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Showing 3 changed files with 126 additions and 87 deletions.
diff --git a/data-raw/configuration.csv b/data-raw/configuration.csv
@@ -47,7 +47,7 @@
 "sharpchin rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_lognormal()","catch_weight ~ 0 + fyear + pass_scaled",-55,-475,33,Inf,-Inf,Inf,TRUE,200,"iid","off",FALSE
 "splitnose rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_gamma()","catch_weight ~ 0 + fyear + pass_scaled",-55,-700,-Inf,Inf,-Inf,Inf,TRUE,500,"iid","off",FALSE
 "stripetail rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_gamma()","catch_weight ~ 0 + fyear",-55,-500,-Inf,Inf,-Inf,Inf,TRUE,500,"off","iid",FALSE
-"widow rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_gamma()","catch_weight ~ 0 + fyear + pass_scaled",-55,-675,33.5,Inf,-Inf,Inf,TRUE,200,"iid","off",TRUE
+"widow rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_lognormal()","catch_weight ~ 0 + fyear + pass_scaled",-55,-500,33.5,Inf,-Inf,Inf,TRUE,200,"iid","off",TRUE
 "yelloweye rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_gamma()","catch_weight ~ 0 + fyear + pass_scaled",-55,-325,34.5,Inf,-Inf,Inf,TRUE,200,"off","off",TRUE
 "yellowtail rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","NWFSC.Combo","sdmTMB::delta_gamma()","catch_weight ~ 0 + fyear*split_mendocino + pass_scaled",-55,-425,33.5,Inf,-Inf,Inf,TRUE,400,"iid","off",TRUE
 "yellowtail rockfish","nwfscSurvey::pull_catch(common_name = species,survey=source)","Triennial","sdmTMB::delta_gamma()","catch_weight ~ 0 + fyear*split_mendocino",-55,-425,33.5,Inf,1980,Inf,TRUE,400,"iid","off",TRUE

diff --git a/data/configuration.rda b/data/configuration.rda
diff --git a/examples/2025_assessments.R b/examples/2025_assessments.R
@@ -1,36 +1,31 @@
+# Run with configuration file associated with
+# commit 1d05a26e09f99e003120a18d0171b7249ea00654
 library(dplyr)
 library(indexwc)
 
 savedir <- here::here("2025")
-
 configuration_all <- tibble::as_tibble(read.csv(
   file.path("data-raw", "configuration.csv")
 ))
 
 
-# Tweaking stuff for wcgbt widow index
-configuration_all[which(configuration_all$species == "widow rockfish" &
-                        configuration_all$source == "NWFSC.Combo"), "knots"] <- 50
-
-configuration_all[which(configuration_all$species == "widow rockfish" &
-                          configuration_all$source == "NWFSC.Combo"), "spatiotemporal2"] <- "iid"
-
-
 #===============================================================================
 # NWFSC Combo All default setting species
 #===============================================================================
 
 wcgbt_species_list <- c(
-  "sablefish",
   "chilipepper",
+  "rougheye rockfish",
+  "sablefish",
   "widow rockfish",
   "yelloweye rockfish",
-  "rougheye rockfish",
-  "rougheye and blackpotted rockfish"
+  "yellowtail rockfish"
 )
 
 configuration_sub <- configuration_all |>
-  dplyr::filter(source == "NWFSC.Combo", species %in% wcgbt_species_list)
+  dplyr::filter(source == "NWFSC.Combo",
+                species %in% wcgbt_species_list,
+                formula == "catch_weight ~ 0 + fyear + pass_scaled")
 
 for(sp in wcgbt_species_list){
   configuration <- configuration_sub |>
@@ -48,12 +43,7 @@ for(sp in wcgbt_species_list){
                                  depth <= min_depth, depth >= max_depth,
                                  latitude >= min_latitude, latitude <= max_latitude,
                                  year >= min_year, year <= max_year
-                               ) |>
-         dplyr::mutate(
-           split_mendocino = 1,
-           split_conception = 1,
-           split_monterey = 1,
-           split_state = 1))
+                               ))
       ) |>
       dplyr::ungroup()
 
@@ -79,80 +69,129 @@ for(sp in wcgbt_species_list){
   }
 }
 
-
 #===============================================================================
 # Yellowtail rockfish north - WCGBT
 #===============================================================================
-
+savedir <- "yellowtail_interaction"
 configuration <- configuration_all |>
-  dplyr::filter(species == "yellowtail rockfish")
-# Change the covariates to include a split at cape mendocino
-configuration$formula <- "catch_weight ~ 0 + fyear*split_mendocino + pass_scaled"
-
-data <- configuration |>
-  # Row by row ... do stuff then ungroup
-  dplyr::rowwise() |>
-  # Pull the data based on the function found in fxn column
-  dplyr::mutate(
-    data_raw = list(format_data(eval(parse(text = fxn)))),
-    data_filtered = list(data_raw |>
-                           dplyr::filter(
-                             depth <= min_depth, depth >= max_depth,
-                             latitude >= min_latitude, latitude <= max_latitude,
-                             year >= min_year, year <= max_year
-                           ) |>
-                           dplyr::mutate(split_mendocino = ifelse(latitude > 40.1666667, "N", "S")))
-  ) |>
-  dplyr::ungroup()
-
-# Confirm no data in the south in 2007:
-dplyr::filter(data$data_filtered[[1]], catch_weight > 0) |>
-  dplyr::group_by(split_mendocino, year) |>
-  dplyr::summarise(n = dplyr::n())
-
-# Find variables that aren't identifiable for presence-absence model
-lm <- lm(formula = as.formula(configuration$formula),
-         data = data$data_filtered[[1]])
-#not_identifiable <- names(which(is.na(coef(lm))))
-# Find variables that aren't identifiable for positive model
-lm_pos <- lm(formula = as.formula(configuration$formula),
-             data = dplyr::filter(data$data_filtered[[1]], catch_weight>0))
-pos_not_identifiable <- names(which(is.na(coef(lm_pos))))
-
-# Create variables to be not estimated/ mapped off
-coef_names <- names(coef(lm))
-.map_pos <- coef_names
-.map_pos[coef_names %in% pos_not_identifiable] <- NA
-.map_pos <- factor(.map_pos)
-.start_pos <- rep(0, length(coef_names))
-.start_pos[coef_names %in% pos_not_identifiable] <- -20
-
-best <- data |>
-  dplyr::mutate(
-    # Evaluate the call in family
-    family = purrr::map(family, .f = ~ eval(parse(text = .x))),
-    # Run the model on each row in data
-    results = purrr::pmap(
-      .l = list(
-        data = data_filtered,
-        formula = formula,
-        family = family,
-        anisotropy = anisotropy,
-        n_knots = knots,
-        share_range = share_range,
-        spatiotemporal = purrr::map2(spatiotemporal1, spatiotemporal2, list),
-        sdmtmb_control = list(
-          sdmTMB::sdmTMBcontrol(
-            map = list(b_j = .map_pos, b_j2 = .map_pos),
-            start = list(b_j = .start_pos, b_j2 = .start_pos),
-            newton_loops = 3
+  dplyr::filter(source == "NWFSC.Combo",
+                species == "yellowtail rockfish",
+                formula != "catch_weight ~ 0 + fyear + pass_scaled")
+
+for (run in 1:nrow(configuration)){
+  data <- configuration[run, ] |>
+    # Row by row ... do stuff then ungroup
+    dplyr::rowwise() |>
+    # Pull the data based on the function found in fxn column
+    dplyr::mutate(
+      data_raw = list(format_data(eval(parse(text = fxn)))),
+      data_filtered = list(data_raw |>
+                             dplyr::filter(
+                               depth <= min_depth, depth >= max_depth,
+                               latitude >= min_latitude, latitude <= max_latitude,
+                               year >= min_year, year <= max_year
+                             ) |>
+                             dplyr::mutate(split_mendocino = ifelse(latitude > 40.1666667, "N", "S")))
+    ) |>
+    dplyr::ungroup()
+
+  # Confirm no data in the south in 2007:
+  dplyr::filter(data$data_filtered[[1]], catch_weight > 0) |>
+    dplyr::group_by(split_mendocino, year) |>
+    dplyr::summarise(n = dplyr::n())
+
+  # Find variables that aren't identifiable for presence-absence model
+  lm <- lm(formula = as.formula(configuration$formula),
+           data = data$data_filtered[[1]])
+  #not_identifiable <- names(which(is.na(coef(lm))))
+  # Find variables that aren't identifiable for positive model
+  lm_pos <- lm(formula = as.formula(configuration$formula),
+               data = dplyr::filter(data$data_filtered[[1]], catch_weight>0))
+  pos_not_identifiable <- names(which(is.na(coef(lm_pos))))
+
+  # Create variables to be not estimated/ mapped off
+  coef_names <- names(coef(lm))
+  .map_pos <- coef_names
+  .map_pos[coef_names %in% pos_not_identifiable] <- NA
+  .map_pos <- factor(.map_pos)
+  .start_pos <- rep(0, length(coef_names))
+  .start_pos[coef_names %in% pos_not_identifiable] <- -20
+
+  best <- data |>
+    dplyr::mutate(
+      # Evaluate the call in family
+      family = purrr::map(family, .f = ~ eval(parse(text = .x))),
+      # Run the model on each row in data
+      results = purrr::pmap(
+        .l = list(
+          dir_main = savedir,
+          data = data_filtered,
+          formula = formula,
+          family = family,
+          anisotropy = anisotropy,
+          n_knots = knots,
+          share_range = share_range,
+          spatiotemporal = purrr::map2(spatiotemporal1, spatiotemporal2, list),
+          sdmtmb_control = list(
+            sdmTMB::sdmTMBcontrol(
+              map = list(b_j = .map_pos, b_j2 = .map_pos),
+              start = list(b_j = .start_pos, b_j2 = .start_pos),
+              newton_loops = 3
+            )
           )
-        )
-      ),
-      .f = indexwc::run_sdmtmb
+        ),
+        .f = indexwc::run_sdmtmb
+      )
     )
-  )
+}
 
+#===============================================================================
+# Widow rockfish - WCGBT
+#===============================================================================
+savedir <- "2025"
+configuration <- configuration_all |>
+  dplyr::filter(source == "NWFSC.Combo",
+                species == "widow rockfish")
+
+for (run in 1:nrow(configuration)){
+  data <- configuration[run, ] |>
+    # Row by row ... do stuff then ungroup
+    dplyr::rowwise() |>
+    # Pull the data based on the function found in fxn column
+    dplyr::mutate(
+      data_raw = list(format_data(eval(parse(text = fxn)))),
+      data_filtered = list(data_raw |>
+                             dplyr::filter(
+                               depth <= min_depth, depth >= max_depth,
+                               latitude >= min_latitude, latitude <= max_latitude,
+                               year >= min_year, year <= max_year
+                             ))
+    ) |>
+    dplyr::ungroup()
+
+  best <- data |>
+    dplyr::mutate(
+      # Evaluate the call in family
+      family = purrr::map(family, .f = ~ eval(parse(text = .x))),
+      # Run the model on each row in data
+      results = purrr::pmap(
+        .l = list(
+          dir_main = savedir,
+          data = data_filtered,
+          formula = formula,
+          family = family,
+          anisotropy = anisotropy,
+          n_knots = knots,
+          share_range = share_range,
+          spatiotemporal = purrr::map2(spatiotemporal1, spatiotemporal2, list)#,
+          #priors = list(sdmTMB::sdmTMBpriors(
+          #  matern_s = sdmTMB::pc_matern(range_gt = 10, sigma_lt = 5)
+          #))
+        ),
+        .f = indexwc::run_sdmtmb
+      )
+    )
+}
 
 #===============================================================================
 # NWFSC Slope