looking at eof calculations

Author: atyrell3

data-raw/scripts/eof_investigation.R

@@ -3,14 +3,112 @@ gb_area <- ecodata::epu_sf |>
   sf::st_area() /
   1e6 # convert to km2
 
-ecodata::ppr |>
+new_ppr <- ecodata::ppr |>
   dplyr::filter(EPU == "GB", Var == "Ryther" | Var == "PP") |>
   dplyr::select(-Units) |>
   tidyr::pivot_wider(names_from = Var, values_from = Value) |>
   dplyr::mutate(
-    total_energy_required = (Ryther * gb_area) |> units::drop_units(),
-    ratio = total_energy_required / PP
-  ) |>
+    total_fish = (Ryther * gb_area) |> units::drop_units(),
+    ppr = (total_fish / 9) * (1 / 0.15)^2.5,
+    ratio = ppr / PP
+  )
+
+new_ppr |>
+  ggplot2::ggplot(ggplot2::aes(x = Time, y = ratio)) +
+  ggplot2::geom_point() +
+  ggplot2::geom_line() +
+  ggplot2::theme_bw()
+
+# compare to pp from annual_chl_pp
+
+ecodata::plot_annual_chl_pp(
+  report = "NewEngland",
+  EPU = "GB",
+  varName = "pp",
+  plottype = "total"
+)
+
+fix <- dplyr::filter(
+  dplyr::mutate(
+    ecodata::annual_chl_pp,
+    Time = as.integer(gsub("A_", "", Time))
+  ),
+  EPU == "GB",
+  Var == "PPD_ANNUAL_MTON"
+)
+
+ppr <- ecodata::ppr |>
+  dplyr::filter(EPU == "GB", Var == "PP")
+
+combined_pp <- tibble::tibble(
+  Time = c(
+    fix$Time,
+    ppr |>
+      dplyr::pull(Time)
+  ),
+  pp = c(
+    fix$Value,
+    ppr |>
+      dplyr::pull(Value)
+  ),
+  source = c(
+    rep("annual_chl_pp", nrow(fix)),
+    rep(
+      "ppr",
+      length(
+        ppr |>
+          dplyr::pull(Time)
+      )
+    )
+  )
+)
+
+combined_pp |>
+  ggplot2::ggplot(ggplot2::aes(x = Time, y = pp, color = source)) +
+  ggplot2::geom_point() +
+  ggplot2::geom_line() +
+  ggplot2::theme_bw()
+
+# compare catch in ppr to ecodata::comdat
+
+ecodata::comdat |>
+  dplyr::filter(Var == "Landings", EPU == "GB") |>
+  ggplot2::ggplot(ggplot2::aes(x = Time, y = Value)) +
+  ggplot2::geom_point() +
+  ggplot2::geom_line() +
+  ggplot2::theme_bw() +
+  ggplot2::geom_point(
+    data = new_ppr,
+    ggplot2::aes(y = total_fish),
+    color = "red"
+  )
+
+reconstructed_ppr <- dplyr::full_join(
+  ecodata::comdat |>
+    dplyr::filter(Var == "Landings", EPU == "GB") |>
+    dplyr::select(Time, Value) |>
+    dplyr::mutate(Var = "Landings"),
+  ecodata::annual_chl_pp |>
+    dplyr::filter(EPU == "GB", Var == "PPD_ANNUAL_MTON") |>
+    dplyr::select(Time, Value) |>
+    dplyr::mutate(
+      Var = "PPD_ANNUAL_MTON",
+      Time = as.integer(gsub("A_", "", Time))
+    )
+) |>
+  tidyr::pivot_wider(names_from = Var, values_from = Value) |>
+  dplyr::mutate(
+    ppr = (Landings / 9) * (1 / 0.15)^2.5,
+    # fill in missing pp
+    PPD_ANNUAL_MTON = ifelse(
+      is.na(PPD_ANNUAL_MTON),
+      mean(PPD_ANNUAL_MTON, na.rm = TRUE),
+      PPD_ANNUAL_MTON
+    ),
+    ratio = ppr / PPD_ANNUAL_MTON
+  )
+
+reconstructed_ppr |>
   ggplot2::ggplot(ggplot2::aes(x = Time, y = ratio)) +
   ggplot2::geom_point() +
   ggplot2::geom_line() +