data: add NEFSC-20230928 (harbor, dolphin)

r/R/internal.R

@@ -4,13 +4,15 @@ targets_internal <- list(
       towed$deployments,
       moored$deployments,
       glider$deployments,
-      nefsc_20230926$deployments
+      nefsc_20230926$deployments,
+      nefsc_20230928$deployments
     )
     detections <- bind_rows(
       towed$detections,
       moored$detections,
       glider$detections,
-      nefsc_20230926$detections
+      nefsc_20230926$detections,
+      nefsc_20230928$detections
     )
     list(
       deployments = deployments,

r/R/internal/nefsc-20230928.R

@@ -0,0 +1,186 @@
+# harbor porpoise, dolphins at moorings
+
+targets_nefsc_20230928 <- list(
+  tar_target(nefsc_20230928_metadata_file, "data/internal/NEFSC_20230928/NEFSC_2023-09-28_METADATA.csv", format = "file"),
+  tar_target(nefsc_20230928_metadata, {
+    x <- read_csv(nefsc_20230928_metadata_file, col_types = cols(.default = col_character())) %>%
+      remove_empty(which = "rows") %>%
+      clean_names()
+
+    x %>%
+      crossing(theme = c("harbor", "dolphin")) %>% 
+      transmute(
+        theme,
+        id = case_when(
+          unique_id == "NEFSC_MA-RI_202110_NS01_FPO" ~ "NEFSC_MA-RI_202110_NS01_FPOD",
+          TRUE ~ unique_id
+        ),
+        project,
+        site_id,
+        latitude = parse_number(latitude),
+        longitude = parse_number(longitude),
+
+        monitoring_start_datetime = ymd_hms(monitoring_start_datetime),
+        monitoring_end_datetime = ymd_hms(monitoring_end_datetime),
+
+        platform_type = tolower(platform_type),
+        platform_id = NA_character_,
+
+        water_depth_meters = parse_number(water_depth_meters),
+        recorder_depth_meters = parse_number(recorder_depth_meters),
+        instrument_type,
+        instrument_id,
+        sampling_rate_hz = parse_number(sampling_rate_hz),
+        soundfiles_timezone,
+        duty_cycle_seconds = NA_character_,
+        channel,
+
+        data_poc_name,
+        data_poc_affiliation,
+        data_poc_email,
+
+        submitter_name,
+        submitter_affiliation,
+        submitter_email,
+        submission_date = mdy(submission_date)
+
+        # species specific
+        # detection_method,
+        # protocol_reference,
+        # call_type,
+        # analyzed
+        # qc_data
+      )
+  }),
+  tar_target(nefsc_20230928_deployments, {
+    x <- nefsc_20230928_detections_raw %>% 
+      distinct(
+        theme, 
+        id = unique_id, 
+        analysis_sampling_rate_hz = parse_number(analysis_sampling_rate_hz), 
+        detection_method, 
+        protocol_reference, 
+        call_type = call_type_code, 
+        qc_data = qc_processing
+      ) %>% 
+      mutate(analyzed = TRUE)
+
+    # metadata includes three deployments with no detections
+    # nefsc_20230928_metadata %>% 
+    #   anti_join(x, by = c("theme", "id")) %>% 
+    #   distinct(id)
+
+    stopifnot(all(x$id %in% nefsc_20230928_metadata$id))
+
+    nefsc_20230928_metadata %>% 
+      inner_join(x, by = c("theme", "id"))
+  }),
+  tar_target(nefsc_20230928_detections_harbor_file, "data/internal/NEFSC_20230928/NEFSC_2023-09-28_HarborPorpoise_DETECTIONS.csv", format = "file"),
+  tar_target(nefsc_20230928_detections_harbor_raw, {
+    read_csv(nefsc_20230928_detections_harbor_file, col_types = cols(.default = col_character())) %>% 
+      remove_empty(which = "rows") %>% 
+      clean_names() %>% 
+      distinct()
+  }),
+  tar_target(nefsc_20230928_detections_dolphin_file, "data/internal/NEFSC_20230928/NEFSC_2023-09-28_Dolphin_DETECTIONS.csv", format = "file"),
+  tar_target(nefsc_20230928_detections_dolphin_raw, {
+    read_csv(nefsc_20230928_detections_dolphin_file, col_types = cols(.default = col_character())) %>% 
+      remove_empty(which = "rows") %>% 
+      clean_names() %>% 
+      distinct()
+  }),
+  tar_target(nefsc_20230928_detections_raw, {
+    bind_rows(
+      harbor = nefsc_20230928_detections_harbor_raw,
+      dolphin = nefsc_20230928_detections_dolphin_raw,
+      .id = "theme"
+    ) %>% 
+      mutate(unique_id = str_replace(unique_id, "FPOD_Min_FPOD", "FPOD"))
+  }),
+  tar_target(nefsc_20230928_detections, {
+    nefsc_20230928_detections_raw %>% 
+      transmute(
+        theme,
+        id = unique_id,
+        species = NA_character_,
+        date = as_date(ymd_hms(analysis_period_start_datetime)),
+        presence = fct_recode(acoustic_presence, y = "D", n = "N")
+      ) %>%
+      arrange(theme, id, date)
+  }),
+  tar_target(nefsc_20230928, {
+    detections <- nefsc_20230928_detections %>% 
+      mutate(
+        locations = map(theme, ~ NULL)
+      )
+
+    analysis_periods <- detections %>%
+      group_by(id) %>%
+      summarise(
+        analysis_start_date = min(date),
+        analysis_end_date = max(date),
+        .groups = "drop"
+      )
+
+    deployments_analysis <- nefsc_20230928_deployments %>%
+      filter(!is.na(latitude), analyzed) %>%
+      left_join(analysis_periods, by = "id")
+
+    # qaqc: analysis period ---------------------------------------------------
+    # 
+    # deployments_analysis %>%
+    #   transmute(
+    #     id,
+    #     monitoring_start_date = as_date(monitoring_start_datetime),
+    #     monitoring_end_date = as_date(monitoring_end_datetime),
+    #     monitoring_n_days = as.numeric(monitoring_end_date - monitoring_start_date + 1),
+    #     analysis_start_date,
+    #     analysis_end_date,
+    #     analysis_n_days = as.numeric(analysis_end_date - analysis_start_date + 1),
+    #     delta_days = monitoring_n_days - analysis_n_days
+    #   ) %>%
+    #   left_join(
+    #     count(detections, id, name = "n_detections"),
+    #     by = "id"
+    #   ) %>%
+    #   view()
+
+    # summary -----------------------------------------------------------------
+
+    tabyl(detections, theme, presence)
+
+    # deployments geom --------------------------------------------------------
+
+    # no missing id, latitude, longitude
+    stopifnot(
+      all(
+        deployments_analysis %>%
+          distinct(id, latitude, longitude) %>%
+          complete.cases()
+      )
+    )
+
+    deployments_sf <- deployments_analysis %>%
+      bind_rows(filter(nefsc_20230928_deployments, !analyzed, !is.na(latitude))) %>% 
+      distinct(id, latitude, longitude) %>%
+      st_as_sf(coords = c("longitude", "latitude"), crs = 4326)
+
+    mapview::mapview(deployments_sf, legend = FALSE)
+
+    deployments <- deployments_sf %>%
+      left_join(
+        deployments_analysis %>%
+          bind_rows(filter(nefsc_20230928_deployments, !analyzed, !is.na(latitude))), 
+        by = "id"
+      ) %>%
+      mutate(deployment_type = "stationary") %>%
+      relocate(deployment_type, geometry, .after = last_col())
+
+    # export ------------------------------------------------------------------
+
+    list(
+      deployments = deployments,
+      detections = detections
+    )
+  })
+)

r/R/pacm.R

@@ -20,9 +20,11 @@ targets_pacm <- list(
           "Song & Social" = "HWMIX",
           "Pulse Train" = "MWPT",
           "Narrow band high frequency click" = "NBHF CLICKS",
+          "Narrow band high frequency click" = "NBHF",
           "Usual click" = "SPUSC",
           "30-80Hz downsweep" = "SWDS",
-          "Upcall" = "UPCALL"
+          "Upcall" = "UPCALL",
+          "Dolphin clicks" = "ODCLICK",
         )
       )
     detections_all <- map_df(all_datasets, ~ .x$detections)

r/_targets.R

@@ -41,6 +41,7 @@ list(
   targets_towed_detections,
   targets_towed,
   targets_nefsc_20230926,
+  targets_nefsc_20230928,
   targets_internal,
 
   targets_external,

src/lib/constants.js

@@ -49,6 +49,10 @@ export const themes = [
     id: 'harbor',
     label: 'Harbor Porpoise'
   },
+  {
+    id: 'dolphin',
+    label: 'Dolphin (Unidentified)'
+  },
   {
     divider: true
   },