WS22337

if (!nzchar(system.file(package = "librarian"))) {
  install.packages("librarian")
}

librarian::shelf(
  quiet = TRUE,
  readr, here, fs, ggplot2, glue, "jiho/castr", dplyr, oce, patchwork, purrr, tidyr
)

source(here("R/cruise_load.R"))
cruise_df <- cruise_load(params$cruise_id)

tryCatch({
  plots <- list()
  
  for (station_name in unique(cruise_df$station)) {
    subset_df <- filter(cruise_df, station == station_name)
    plots[[station_name]] <- ggplot(subset_df, aes(x = time_elapsed)) +
      geom_point(aes(y = depth), color = "blue") +  # Plot depth in blue
      geom_line(aes(y = sea_water_pressure), color = "red") +  # Plot sea water pressure in red
      ggtitle(glue("{station_name}")) +
      theme(
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.text.x = element_blank(),
        axis.text.y = element_blank(),
        axis.ticks.x = element_blank(),
        axis.ticks.y = element_blank()
      )  # Remove individual axis titles and text
  }
  
  # drop nulls
  plots <- purrr::compact(plots)
  
  # Combine all plots into a grid
  combined_plot <- wrap_plots(plots) + 
    plot_layout(ncol = 4) +  # Adjust ncol to set number of columns in the grid
    plot_annotation(
      title = "Depth (blue) and Pressure (red)",
      subtitle = "Each panel represents a different station",
      caption = "Time Elapsed (x-axis) vs Depth & Pressure (y-axis)"
    ) +
    theme(
      plot.tag = element_text(size = 12, face = "bold"),
      plot.tag.position = "topleft",
      axis.title.x = element_text(margin = margin(t = 10)),
      axis.title.y = element_text(margin = margin(r = 10))
    )
  
  print(combined_plot)
}, error = function(er){
  print(er)
});

p <- ggplot(cruise_df, aes(x = time, y = depth, fill = station)) +
  geom_col() +  # This creates the bars
  # geom_text(aes(label = station), vjust = -0.3) +  # This adds labels to each bar, adjust vjust for position
  labs(x = "Time", y = "Depth", title = "Depth over Time by Station") +  # Set labels and title
  theme_minimal()  # Use a minimal theme
print(p)

ctd_load <- function(data, other_params = NULL) {
  
  # create csv into ctd object
  test_ctd <-
    as.ctd(
      salinity    = data$sea_water_salinity,
      temperature = data$sea_water_temperature,
      pressure    = data$sea_water_pressure,
      station     = data$station
    )
  
  # add additional columns to ctd object
  if (!is.null(other_params)) {
    for (param_name in other_params) {
      test_ctd <-
        oceSetData(
          object = test_ctd,
          name   = param_name,
          value  = data[[param_name]]
        )
    }
  }
  print(glue("{data$station[1]}:\t{length(test_ctd@data$scan)} scans"))


  return(test_ctd)
}

# Define other parameters to add
other_params <- c(
  "cruise_id", "station", "time", "time_elapsed", 
  "latitude", "longitude", "sea_water_electrical_conductivity", 
  "CDOM", "dissolved_oxygen","oxygen_saturation", "chlorophyll_concentration", 
  "chlorophyll_fluorescence", "photosynthetically_available_radiation", 
  "beam_attenuation","beam_transmission", "depth", "sea_water_sigma_t",
  "descent_rate", "sound_velocity","altimeter"
)

# Split data by station and create data list
ctd_FK <- cruise_df %>%
  split(.$station) %>%
  map(~ ctd_load(.x, other_params = other_params)) # ~ is a lambda(x)

.10:    4 scans
.12:    4962 scans
.16:    2698 scans
.18:    4697 scans
.2: 2713 scans
.21:    6113 scans
.30:    4387 scans
.31:    4676 scans
.33:    3281 scans
.41:    2893 scans
.45:    2880 scans
.47:    3017 scans
.49:    2726 scans
.51:    2659 scans
.53:    2406 scans
.54:    78 scans
.55:    211 scans
.56:    3467 scans
.57:    2588 scans
.57_1:  2549 scans
.57_2:  3849 scans
.57_3:  3622 scans
.58:    3810 scans
.60:    3419 scans
.64:    2 scans
.65:    4961 scans
.68:    4392 scans
.7: 2492 scans
.9: 4702 scans
.9_5:   9073 scans
.AMI1:  3392 scans
.AMI2:  3942 scans
.AMI3:  4782 scans
.AMI4:  5058 scans
.AMI5:  4625 scans
.AMI6:  5327 scans
.AMI7:  5106 scans
.AMI8:  6270 scans
.AMI9:  6002 scans
.BG1:   3746 scans
.BG2:   3374 scans
.BG3:   4823 scans
.BG4:   4014 scans
.CAL1:  1591 scans
.CAL2:  3132 scans
.CAL3:  3192 scans
.CAL4:  3959 scans
.CAL5:  4531 scans
.CAL6:  4384 scans
.CW1:   3 scans
.CW2:   2768 scans
.CW3:   3104 scans
.CW4:   3878 scans
.GP5:   4680 scans
.KW1:   3458 scans
.KW2:   3771 scans
.KW4:   4397 scans
.L1:    2946 scans
.L3:    4914 scans
.L5:    6961 scans
.L7:    5775 scans
.L9:    5180 scans
.MR:    5551 scans
.RP1:   2990 scans
.RP2:   3154 scans
.RP3:   3810 scans
.RP4:   4376 scans
.TB1:   2848 scans
.TB10:  5350 scans
.TB2:   3141 scans
.TB3:   4004 scans
.TB4:   4058 scans
.TB5:   5301 scans
.V1:    3901 scans
.V2:    3752 scans
.V3:    3774 scans
.V4:    3651 scans
.V5:    5442 scans
.V6:    4826 scans
.V7:    4717 scans
.V8:    5135 scans
.V9:    5212 scans
.WS:    5575 scans

for (i in seq(ctd_FK)){
  cast <- ctd_FK[[i]]  # 1 is selecting only the first sublist
  # print(i)
  print(glue("=== station: {cast@metadata$station[1]}"))
  print(glue("# scans: {length(cast@data$scan)}"))
  plotScan(cast)
}

=== station: .10
# scans: 4

=== station: .12
# scans: 4962

=== station: .16
# scans: 2698

=== station: .18
# scans: 4697

=== station: .2
# scans: 2713

=== station: .21
# scans: 6113

=== station: .30
# scans: 4387

=== station: .31
# scans: 4676

=== station: .33
# scans: 3281

=== station: .41
# scans: 2893

=== station: .45
# scans: 2880

=== station: .47
# scans: 3017

=== station: .49
# scans: 2726

=== station: .51
# scans: 2659

=== station: .53
# scans: 2406

=== station: .54
# scans: 78

=== station: .55
# scans: 211

=== station: .56
# scans: 3467

=== station: .57
# scans: 2588

=== station: .57_1
# scans: 2549

=== station: .57_2
# scans: 3849

=== station: .57_3
# scans: 3622

=== station: .58
# scans: 3810

=== station: .60
# scans: 3419

=== station: .64
# scans: 2

=== station: .65
# scans: 4961

=== station: .68
# scans: 4392

=== station: .7
# scans: 2492

=== station: .9
# scans: 4702

=== station: .9_5
# scans: 9073

=== station: .AMI1
# scans: 3392

=== station: .AMI2
# scans: 3942

=== station: .AMI3
# scans: 4782

=== station: .AMI4
# scans: 5058

=== station: .AMI5
# scans: 4625

=== station: .AMI6
# scans: 5327

=== station: .AMI7
# scans: 5106

=== station: .AMI8
# scans: 6270

=== station: .AMI9
# scans: 6002

=== station: .BG1
# scans: 3746

=== station: .BG2
# scans: 3374

=== station: .BG3
# scans: 4823

=== station: .BG4
# scans: 4014

=== station: .CAL1
# scans: 1591

=== station: .CAL2
# scans: 3132

=== station: .CAL3
# scans: 3192

=== station: .CAL4
# scans: 3959

=== station: .CAL5
# scans: 4531

=== station: .CAL6
# scans: 4384

=== station: .CW1
# scans: 3

=== station: .CW2
# scans: 2768

=== station: .CW3
# scans: 3104

=== station: .CW4
# scans: 3878

=== station: .GP5
# scans: 4680

=== station: .KW1
# scans: 3458

=== station: .KW2
# scans: 3771

=== station: .KW4
# scans: 4397

=== station: .L1
# scans: 2946

=== station: .L3
# scans: 4914

=== station: .L5
# scans: 6961

=== station: .L7
# scans: 5775

=== station: .L9
# scans: 5180

=== station: .MR
# scans: 5551

=== station: .RP1
# scans: 2990

=== station: .RP2
# scans: 3154

=== station: .RP3
# scans: 3810

=== station: .RP4
# scans: 4376

=== station: .TB1
# scans: 2848

=== station: .TB10
# scans: 5350

=== station: .TB2
# scans: 3141

=== station: .TB3
# scans: 4004

=== station: .TB4
# scans: 4058

=== station: .TB5
# scans: 5301

=== station: .V1
# scans: 3901

=== station: .V2
# scans: 3752

=== station: .V3
# scans: 3774

=== station: .V4
# scans: 3651

=== station: .V5
# scans: 5442

=== station: .V6
# scans: 4826

=== station: .V7
# scans: 4717

=== station: .V8
# scans: 5135

=== station: .V9
# scans: 5212

=== station: .WS
# scans: 5575

for (i in seq(ctd_FK)){
  cast <- ctd_FK[[i]]  # 1 is selecting only the first sublist
  tryCatch({
    plot(ctdDecimate(ctdTrim(cast)))
  }, error = function(e){
    print(e)
  })
}

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4962' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2698' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4697' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2713' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 6113' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4387' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4676' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3281' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2893' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2880' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3017' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2726' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2659' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2406' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3467' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2588' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2549' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3849' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3622' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3810' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3419' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4392' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2492' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4702' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 9073' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3392' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3942' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4782' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5058' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4625' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5327' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5106' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 6270' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 6002' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3746' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3374' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4823' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4014' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3132' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3192' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3959' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4531' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4384' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2768' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3104' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3878' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4680' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3458' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3771' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4397' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2946' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4914' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 6961' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5775' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5180' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5551' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2990' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3154' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3810' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4376' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 2848' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5350' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3141' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4004' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4058' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5301' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3901' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3752' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3774' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 3651' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5442' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4826' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 4717' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5135' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5212' in coercion to 'logical(1)'>

<simpleError in !is.null(x@metadata$station) && !is.na(x@metadata$station): 'length = 5575' in coercion to 'logical(1)'>

# Loop through each CTD cast
for (i in seq(ctd_FK)){
  cast <- ctd_FK[[i]]  # Assuming each sublist contains only one relevant CTD object
  tryCatch({
    # Extract metadata for station name and cruise ID
    station_name <- cast@metadata$station[1]
    cruise_id <- cast@data$cruise_id[1]

    # Generate a title with station name and cruise ID
    overall_title <- glue::glue("Station: {station_name}, Cruise ID: {cruise_id}")

    # Set margins: increase the outer margin for the title
    par(oma = c(0, 0, 3, 0))  # Top outer margin increased for title

    # Plotting function with specific parameters
    oce::plot(
      x = ctdDecimate(ctdTrim(cast)),
      which = c(
        "sea_water_electrical_conductivity",
        "descent_rate", "sound_velocity",
        "sea_water_sigma_t","altimeter"
      ),
      main = ""  # No main title for individual subplots
    )

    # Place a single overall title at the top of the plot frame
    mtext(overall_title, side = 3, line = 1, outer = TRUE, cex = 1.5)

    # Reset outer margins to default
    par(oma = c(0, 0, 0, 0))

  }, error = function(e) {
    print(e$message)  # Print any errors that occur during plotting
  })
}

[1] "need finite 'xlim' values"

[1] "need finite 'xlim' values"

[1] "need finite 'xlim' values"

[1] "need finite 'xlim' values"

[1] "need finite 'xlim' values"

[1] "need finite 'xlim' values"

[1] "unknown xtype value (\"4.829499\")"

# Loop through each CTD cast
for (i in seq(ctd_FK)){
  cast <- ctd_FK[[i]]  # Assuming each sublist contains only one relevant CTD object
  tryCatch({
    # Extract metadata for station name and cruise ID
    station_name <- cast@metadata$station[1]
    cruise_id <- cast@data$cruise_id[1]

    # Generate a title with station name and cruise ID
    overall_title <- glue::glue("Station: {station_name}, Cruise ID: {cruise_id}")

    # Set margins: increase the outer margin for the title
    par(oma = c(0, 0, 3, 0))  # Top outer margin increased for title

    # Plotting function with specific parameters
    oce::plot(
      x = ctdDecimate(ctdTrim(cast)),
      which = c(
        "CDOM", "dissolved_oxygen",
        "oxygen_saturation",
        "chlorophyll_concentration", "chlorophyll_fluorescence"
      ),
      main = ""  # No main title for individual subplots
    )

    # Place a single overall title at the top of the plot frame
    mtext(overall_title, side = 3, line = 1, outer = TRUE, cex = 1.5)

    # Reset outer margins to default
    par(oma = c(0, 0, 0, 0))

  }, error = function(e) {
    print(e$message)  # Print any errors that occur during plotting
  })
}

[1] "need finite 'xlim' values"

[1] "need finite 'xlim' values"

[1] "unknown xtype value (\"1.6407\")"

# Loop through each CTD cast
for (i in seq(ctd_FK)){
  cast <- ctd_FK[[i]]  # Assuming each sublist contains only one relevant CTD object
  tryCatch({
    # Extract metadata for station name and cruise ID
    station_name <- cast@metadata$station[1]
    cruise_id <- cast@data$cruise_id[1]

    # Generate a title with station name and cruise ID
    overall_title <- glue::glue("Station: {station_name}, Cruise ID: {cruise_id}")

    # Set margins: increase the outer margin for the title
    par(oma = c(0, 0, 3, 0))  # Top outer margin increased for title

    # Plotting function with specific parameters
    oce::plot(
      x = ctdDecimate(ctdTrim(cast)),
      which = c(
        "photosynthetically_available_radiation",
        "beam_attenuation","beam_transmission"
      ),
      main = ""  # No main title for individual subplots
    )

    # Place a single overall title at the top of the plot frame
    mtext(overall_title, side = 3, line = 1, outer = TRUE, cex = 1.5)

    # Reset outer margins to default
    par(oma = c(0, 0, 0, 0))

  }, error = function(e) {
    print(e$message)  # Print any errors that occur during plotting
  })
}

[1] "need finite 'xlim' values"

[1] "unknown xtype value (\"0.098924\")"

combined_df <- data.frame()
for (i in seq(ctd_FK)){
  tryCatch({
    cast <- ctd_FK[[i]]  # 1 is selecting only the first sublist
    
    # print(class(cast))
    # clean cast 
    trimmed_cast <- ctdTrim(cast)
    decimated_cast <- ctdDecimate(trimmed_cast, p = 0.5)  # binned to 0.5 m
    
    # convert to df
    cast_df <- as.data.frame(decimated_cast@data)
    
    # Add metadata
    # assumes station ID and cruise ID the same for all & just uses 1st one
    cast_df <- mutate(
      cast_df,
      station = cast@data$station[1],
      cruise_id = cast@data$cruise_id[1]
    )
  
    # drop NA rows left by cleaning
    cast_df <- subset(cast_df, !is.na(scan))
    
    # Append the data to the combined dataframe
    combined_df <- rbind(combined_df, cast_df)
  }, error = function(e){
    print(glue("error in cast {cast@metadata$station[1]}"))
    print(e)
  })
}
# Save to CSV
file_path <- here(glue("data/cleaned/{cruise_id}.csv"))
write.csv(combined_df, file_path, row.names = FALSE)