Introduction

I need to write a proper intro here, but this is just a placeholder to see if my long-neglected Hugo site is still going to compile and build properly.

For some reason, and I’m not sure that this is a new issue, the “home page preview” of the most recent posts really mangles any code chunks that show up in it.

Hawaiian Ocean Timeseries WireWalker data

library(oce)

## Loading required package: gsw

library(readr)
library(cmocean)

d <- read_csv('HOT297_data_L1_v1_0.csv.zip')

## Rows: 507302 Columns: 17

## ── Column specification ────────────────────────────────────────────────────────────────────────────────
## Delimiter: ","
## dbl  (16): latitude, longitude, depth, cast, pressure, temperature, conserva...
## dttm  (1): time
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

ww <- with(d,
           as.ctd(salinity=practical_salinity,
                  temperature=temperature,
                  pressure=pressure,
                  time=as.POSIXct(time, tz='UTC'),
                  latitude=latitude,
                  longitude=longitude,
                  station="HOT"))
ww <- oceSetData(ww, 'fluorescence', d$fluorescence)
ww <- oceSetData(ww, 'backscattering', d$backscattering)
ww <- oceSetData(ww, 'oxygen', d$oxygen)
ww <- oceSetData(ww, 'cdom', d$CDOM)
ww <- oceSetData(ww, 'par', d$PAR)
ww <- oceSetData(ww, 'sigmaTheta', swSigmaTheta(ww))
ww <- oceSetData(ww, 'N2', swN2(ww))

movingAverage <- function(x, n = 11, ...)
{
    f <- rep(1/n, n)
    stats::filter(x, f, ...)
}
prof <- ctdFindProfiles(ww, smoother=movingAverage, direction = 'ascending')
prof <- lapply(prof, \(x) oceSetMetadata(x, 'startTime', x[['time']][1]))
prof <- lapply(prof, \(x) {
    oceSetMetadata(x, 'startTime', x[['time']][1]) |>
        oceSetMetadata('latitude', x[['latitude']][1]) |>
        oceSetMetadata('longitude', x[['longitude']][1])
    })

t <- numberAsPOSIXct(sapply(prof, '[[', 'startTime'))
p <- seq(0.5, 400, 0.25)
profg <- lapply(prof, ctdDecimate, p=p)

make_arrays <- function(x) {
    t <- sapply(x, '[[', 'startTime')
    p <- x[[1]][['pressure']]
    N <- length(x)
    fields <- names(x[[1]]@data)
    out <- list()
    for (i in seq_along(fields)) {
        out[[i]] <- array(NA_real_, dim=c(length(t), length(p)))
    }
    names(out) <- fields
    for (i in 1:N) {
        for (f in fields) {
            out[[f]][i, ] <- x[[i]][[f]]
        }
    }
    return(out)
}

mat <- make_arrays(profg)

plot_field <- function(x, f, log=FALSE, ...) {
    imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy=TRUE, ...)
    contour(t, p, x$sigmaTheta, add=TRUE)
}

plot_field(mat, 'temperature', col=cmocean('thermal'))

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'salinity', col=cmocean('haline'))

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'sigmaTheta', col=cmocean('dense'))

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'N2', log=!TRUE, zlim=c(0, 0.5e-4))

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'oxygen', col=cmocean('oxy'))

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'fluorescence', col=cmocean('algae'))

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'cdom', log=TRUE)

## Warning in log(x[[f]]): NaNs produced

## Warning in log(x[[f]]): auto-decimating second index of large image by 3; use
## decimate=FALSE to prevent this

plot_field(mat, 'par', log=!TRUE)

## Warning in imagep(t, p, if (log) log(x[[f]]) else x[[f]], flipy = TRUE, :
## auto-decimating second index of large image by 3; use decimate=FALSE to prevent
## this

plot_field(mat, 'backscattering', log=TRUE)

## Warning in log(x[[f]]): NaNs produced

## Warning in log(x[[f]]): auto-decimating second index of large image by 3; use
## decimate=FALSE to prevent this