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Merge pull request #54 from afsc-gap-products/dev
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Add gap_products queries and revert AI to SBW indicator
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@sean-rohan-NOAA
sean-rohan-NOAA authored May 18, 2024
2 parents 47938f5 + 8116263 commit c430070
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4 changes: 4 additions & 0 deletions .Rbuildignore
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Original file line number Diff line number Diff line change
Expand Up @@ -2,3 +2,7 @@
^\.Rproj\.user$
^doc$
^Meta$
analysis
archive
past_years
plots
35 changes: 11 additions & 24 deletions 0_update_condition_data.Rmd
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Expand Up @@ -114,17 +114,17 @@ ESP_SETTINGS <- list(ESP_SPECIES =
n_knots = c(400, 400,
400, 600,
750, 750),
fl_min = c(0, 421,
0, 461,
0, 461),
fl_max = c(420, 1e7,
460, 1e7,
460, 1e7))
fl_min = c(0, 504,
0, 581,
0, 581),
fl_max = c(503, 1e7,
580, 1e7,
580, 1e7))
)
```


# 1. Update stratum-biomass weighted condition inidicators
# 1. Update stratum-biomass weighted condition indicators

```{r get_ai, message=TRUE, warning=TRUE}
# Aleutian Islands
Expand Down Expand Up @@ -277,9 +277,7 @@ Update sysdata.rda with raw data for the condition indicator and write raw data
```{r save_to_sysdata, message=FALSE, warning=FALSE}
EBS_INDICATOR <- list(
FULL_REGION = as.data.frame(
# dplyr::full_join(
ebs_sbw$full_sbw) %>% #,
# ebs_vast_df)) %>%
ebs_sbw$full_sbw) |>
dplyr::filter(common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$EBS]),
STRATUM = as.data.frame(
dplyr::filter(
Expand All @@ -291,9 +289,7 @@ EBS_INDICATOR <- list(
NBS_INDICATOR <- list(
FULL_REGION = as.data.frame(
# dplyr::full_join(
nbs_sbw$full_sbw) %>% #,
# nbs_vast_df) %>%
nbs_sbw$full_sbw) |>
dplyr::filter(
common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$NBS]),
STRATUM = as.data.frame(
Expand All @@ -306,9 +302,7 @@ NBS_INDICATOR <- list(
GOA_INDICATOR <- list(
FULL_REGION = as.data.frame(
# dplyr::full_join(
goa_sbw$full_sbw) %>% #,
# goa_vast_df)) %>%
goa_sbw$full_sbw) |>
dplyr::filter(common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$GOA]),
STRATUM = as.data.frame(
dplyr::filter(
Expand All @@ -320,10 +314,7 @@ GOA_INDICATOR <- list(
AI_INDICATOR <- list(
FULL_REGION = as.data.frame(
# dplyr::full_join(
ai_sbw$full_sbw) %>% #,
# ai_vast_df)
# ) %>%
ai_sbw$full_sbw) |>
dplyr::filter(common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$AI]),
STRATUM = as.data.frame(
dplyr::filter(
Expand All @@ -335,22 +326,18 @@ AI_INDICATOR <- list(
PCOD_ESP <- list(
FULL_REGION_EBS = as.data.frame(
# dplyr::full_join(ebs_sbw$full_sbw, ebs_vast_df) %>%
dplyr::filter(ebs_sbw$full_sbw,
common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
FULL_REGION_GOA = as.data.frame(
# dplyr::full_join(goa_sbw$full_sbw, goa_vast_df) %>%
dplyr::filter(goa_sbw$full_sbw,
common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
FULL_REGION_AI = as.data.frame(
# dplyr::full_join(ai_sbw$full_sbw, ai_vast_df) %>%
dplyr::filter(ai_sbw$full_sbw,
common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
FULL_REGION_NBS = as.data.frame(
# dplyr::full_join(nbs_sbw$full_sbw, nbs_vast_df) %>%
dplyr::filter(
nbs_sbw$full_sbw, common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
Expand Down
253 changes: 253 additions & 0 deletions 0_update_indicator.R
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@@ -0,0 +1,253 @@
library(akfishcondition)

# Make ESR/ESP settings ----

ESR_SETTINGS <- list(ESR_SPECIES = data.frame(common_name = c(
"walleye pollock", "walleye pollock (100-250 mm)", "walleye pollock (>250 mm)", "Pacific cod",
"Pacific cod (juvenile)", "Pacific cod (adult)", "Atka mackerel", "arrowtooth flounder",
"flathead sole", "yellowfin sole", "northern rock sole", "southern rock sole", "Alaska plaice",
"Pacific ocean perch", "dusky rockfish", "northern rockfish", "Dover sole", "rex sole", "shortraker rockfish", "rougheye rockfish", "blackspotted rockfish", "sharpchin rockfish"),
species_code = c(21740, 21741, 21742, 21720, 21721, 21722, 21921, 10110, 10130,
10210, 10261, 10262, 10285, 30060, 30152, 30420, 10180, 10200, 30576, 30051, 30052, 30560),
AI = c(FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, FALSE, TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE),
GOA = c(FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, TRUE, TRUE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE),
EBS = c(FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE),
NBS = c(FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE)),
VAST_SETTINGS = data.frame(species_code = c(30420, 30060, 10262, 21720, 21740, 10110, 30152,
30420, 30060, 10262, 21720, 21740, 21921, 10110, 21741, 21742,
10130, 10210, 10285, 21740, 21720, 10110, 10261, 21741, 21742,
21740, 21720, 10210, 10285, 21741, 21742
),
region = c("GOA", "GOA", "GOA", "GOA", "GOA", "GOA", "GOA",
"AI", "AI", "AI", "AI", "AI", "AI", "AI", "AI", "AI",
"EBS", "EBS", "EBS", "EBS", "EBS", "EBS", "EBS", "EBS", "EBS",
"NBS", "NBS", "NBS", "NBS", "NBS", "NBS"),
ObsModel_1 = c(2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2, 2, 2, 2,
2, 2, 2, 2, 2, 2),
ObsModel_2 = c(1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1, 1, 1, 1),
ObsModel_3 = c(3, 3, 3, 3, 4, 4, 4,
3, 3, 3, 3, 4, 3, 4, 4, 4,
3, 3, 3, 4, 3, 4, 3, 4, 4,
4, 4, 3, 4, 4, 4),
ObsModel_4 = c(3, 3, 3, 3, 4, 4, 4,
3, 3, 3, 3, 4, 3, 4, 4, 4,
3, 3, 3, 4, 3, 4, 3, 4, 4,
4, 4, 3, 4, 4, 4),
fl_min = c(0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 100, 251,
0, 0, 0, 0, 0, 0, 0, 100, 251,
0, 0, 0, 0, 100, 251),
fl_max = c(1e7, 1e7, 1e7, 1e7, 1e7, 1e7, 1e7,
1e7, 1e7, 1e7, 1e7, 1e7, 1e7, 1e7, 250, 1e7,
1e7, 1e7, 1e7, 1e7, 1e7, 1e7, 1e7, 250, 1e7,
1e7, 1e7, 1e7, 1e7, 250, 1e7),
n_knots = c(400, 400, 400, 400, 400, 400, 400,
400, 600, 400, 400, 400, 400, 400, 400, 400,
400, 600, 400, 400, 750, 400, 400, 400, 400,
200, 200, 200, 200, 200, 200))
)

ESP_SETTINGS <- list(ESP_SPECIES =
data.frame(
common_name = c("Pacific cod (juvenile)", "Pacific cod (adult)"),
species_code = c(21721, 21722),
AI = c(TRUE, TRUE),
GOA = c(TRUE, TRUE),
EBS = c(TRUE, TRUE),
NBS = c(FALSE, FALSE)),
VAST_SETTINGS = data.frame(species_code = c(21721, 21722,
21721, 21722,
21721, 21722),
region = c("GOA", "GOA",
"AI", "AI",
"EBS", "EBS"),
ObsModel_1 = c(2, 2,
2, 2,
2, 2),
ObsModel_2 = c(1, 1,
1, 1,
1, 1),
ObsModel_3 = c(3, 3,
4, 4,
3, 3),
ObsModel_4 = c(3, 3,
4, 4,
3, 3),
n_knots = c(400, 400,
400, 600,
750, 750),
fl_min = c(0, 504,
0, 581,
0, 581),
fl_max = c(503, 1e7,
580, 1e7,
580, 1e7))
)

devtools::install()

# Get data ---

library(akfishcondition)

channel <- akfishcondition:::get_connected(schema = "AFSC")

akfishcondition::get_condition_data(channel = channel)


# Generate data visualizations ---

akfishcondition:::make_data_summary(dat_csv = here::here("data", "nbs_all_species.csv"), region = "NBS")
akfishcondition:::make_data_summary(dat_csv = here::here("data", "ebs_all_species.csv"), region = "EBS")
akfishcondition:::make_data_summary(dat_csv = here::here("data", "ai_all_species.csv"), region = "AI")
akfishcondition:::make_data_summary(dat_csv = here::here("data", "goa_all_species.csv"), region = "GOA")


# Calculate residual condition indicator ----

ai_sbw <- akfishcondition:::run_sbw_condition_multimodel(
region = "AI",
covariates_to_use = c('sex', 'stratum'),
min_n = 10)

goa_sbw <- akfishcondition:::run_sbw_condition_multimodel(
region = "GOA",
covariates_to_use = c('sex', 'stratum'),
min_n = 10)

ebs_sbw <- akfishcondition:::run_sbw_condition_multimodel(
region = "EBS",
covariates_to_use = c('sex', 'stratum'),
min_n = 10)

nbs_sbw <- akfishcondition:::run_sbw_condition_multimodel(
region = "NBS",
covariates_to_use = c('sex', 'stratum'),
min_n = 10)


# Add updated indicator to built-in data sets ----

EBS_INDICATOR <- list(
FULL_REGION = as.data.frame(
ebs_sbw$full_sbw) |>
dplyr::filter(common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$EBS]),
STRATUM = as.data.frame(
dplyr::filter(
ebs_sbw$stratum_sbw,
common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$EBS])
),
LAST_UPDATE = Sys.Date()
)

NBS_INDICATOR <- list(
FULL_REGION = as.data.frame(
nbs_sbw$full_sbw) |>
dplyr::filter(
common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$NBS]),
STRATUM = as.data.frame(
dplyr::filter(
nbs_sbw$stratum_sbw,
common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$EBS])
),
LAST_UPDATE = Sys.Date()
)

GOA_INDICATOR <- list(
FULL_REGION = as.data.frame(
goa_sbw$full_sbw) |>
dplyr::filter(common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$GOA]),
STRATUM = as.data.frame(
dplyr::filter(
goa_sbw$stratum_sbw,
common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$GOA])
),
LAST_UPDATE = Sys.Date()
)

AI_INDICATOR <- list(
FULL_REGION = as.data.frame(
ai_sbw$full_sbw) |>
dplyr::filter(common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$AI]),
STRATUM = as.data.frame(
dplyr::filter(
ai_sbw$stratum_sbw,
common_name %in% ESR_SETTINGS$ESR_SPECIES$common_name[ESR_SETTINGS$ESR_SPECIES$AI])
),
LAST_UPDATE = Sys.Date()
)

PCOD_ESP <- list(
FULL_REGION_EBS = as.data.frame(
dplyr::filter(ebs_sbw$full_sbw,
common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
FULL_REGION_GOA = as.data.frame(
dplyr::filter(goa_sbw$full_sbw,
common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
FULL_REGION_AI = as.data.frame(
dplyr::filter(ai_sbw$full_sbw,
common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
FULL_REGION_NBS = as.data.frame(
dplyr::filter(
nbs_sbw$full_sbw, common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
STRATUM_EBS = as.data.frame(
dplyr::filter(
ebs_sbw$stratum_sbw, common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
STRATUM_GOA = as.data.frame(
dplyr::filter(
goa_sbw$stratum_sbw, common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
STRATUM_AI = as.data.frame(
dplyr::filter(
ai_sbw$stratum_sbw, common_name %in% ESP_SETTINGS$ESP_SPECIES$common_name
)),
stratum_NBS = NA,
LAST_UPDATE = Sys.Date()
)

usethis::use_data(EBS_INDICATOR, overwrite = TRUE)
usethis::use_data(AI_INDICATOR, overwrite = TRUE)
usethis::use_data(GOA_INDICATOR, overwrite = TRUE)
usethis::use_data(NBS_INDICATOR, overwrite = TRUE)
usethis::use_data(PCOD_ESP, overwrite = TRUE)

save(
EBS_INDICATOR,
NBS_INDICATOR,
GOA_INDICATOR,
AI_INDICATOR,
PCOD_ESP,
ESR_SETTINGS,
ESP_SETTINGS,
file = here::here("R", "sysdata.rda")
)

AI_raw <- ai_sbw$input_data
GOA_raw <- goa_sbw$input_data
EBS_raw <- ebs_sbw$input_data
NBS_raw <- nbs_sbw$input_data

save(AI_raw,
GOA_raw,
EBS_raw,
NBS_raw,
file = here::here("inst", "extdata", "raw_lw_bio.rda"))

# Check update ----

library(akfishcondition)

print(akfishcondition::AI_INDICATOR$LAST_UPDATE)
print(akfishcondition::GOA_INDICATOR$LAST_UPDATE)
print(akfishcondition::EBS_INDICATOR$LAST_UPDATE)
print(akfishcondition::NBS_INDICATOR$LAST_UPDATE)
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