In jkennel/transducer: Reads RBR files

knitr::opts_chunk$set(echo = FALSE)
library(transducer)
library(ggplot2)
library(data.table)
library(earthtide)
library(waterlevel)
library(knitr)
library(xtable)
library(patchwork)
library(here)
library(plotly)

Read meta data

meta_path <- '/media/jonathankennel/Seagate Expansion Drive/guelph_south/meta/'
w  <- unique(fread(file.path(meta_path, 'well_details.csv')))
xd <- unique(fread(file.path(meta_path, 'transducer_details.csv')))
ma <- unique(fread(file.path(meta_path, 'manual_wl.csv')))


w_elev <- unique(w[, list(well, port, elevation)])

xd <- w_elev[xd, on = c('well', 'port')]

ma <- w[ma, on = c('well', 'port')]
ma[, wl_elevation := elevation - value_manual]
ma[, datetime := as.POSIXct(datetime, tz = 'UTC')]


ggplot(ma[well == 'HBP-MPS4-20'], aes(x = datetime, y = wl_elevation, group = port, color = port)) + 
  geom_point()

Read Westbay

fn <- list.files('/media/jonathankennel/Seagate Expansion Drive/guelph_south', full.names = TRUE)
fn <- fn[tools::file_ext(fn) == 'csv']
wb  <- read_transducer(fn)
wb

Read Diver (MON)

# fn <- c('hbp-mps2-19 baro_200401123850_V9549.DAT', 'hbp-mps2-19 port 1_200401230820_X0311.MON')
# fn <- file.path('/media/jonathankennel/Seagate Expansion Drive/guelph_south/', fn)
# tmp <- read_transducer(fn)
# tmp[parameter == 'pressure', parameter := 'level']
# tmp <- tmp[parameter == 'level']
# 
# a <- tmp[, rbindlist(data), by = list(name = basename(file))]
# b <- dcast(a, datetime~name, value.var = 'value')
# setnames(b, c('datetime', 'baro', 'wl'))
# b[, wl := shift(wl *100, 60*5)]
# b[, elev := wl - baro]
# plot(baro~datetime, b[-c(1:500, .N:(.N-500))], type='l')
# par(new = TRUE)
# plot(wl~datetime, b[-c(1:500, .N:(.N-500))], type='l', col = 'blue')
# par(new = TRUE)
# plot(elev~datetime, b[-c(1:500, .N:(.N-500))], type='l', col = 'green')
# 
# 
# plot(elev~datetime, b[-c(1:10, .N:(.N-500))], type='l')
# plot(wl~datetime, b, type='l')
# ggplot(a, aes(x = datetime, y = value, group = name, color = name)) +
#   geom_line()




fn <- list.files('/media/jonathankennel/Seagate Expansion Drive/guelph_south', full.names = TRUE)
fn <- fn[tools::file_ext(fn) == 'DAT']
dv  <- read_transducer(fn)
fn <- list.files('/media/jonathankennel/Seagate Expansion Drive/guelph_south', full.names = TRUE)
nm <- xd[tools::file_ext(xd$path) == 'MON']$path
mf <- fn[basename(fn) %in% nm]
add  <- read_transducer(mf)
add[parameter %chin% c('water_head_toc_cl', 'pressure'), channel := 'level']
add[parameter %chin% c('water_head_toc_cl', 'pressure'), parameter := 'level']
add[parameter %chin% c('level'), units := 'cmh2o']
add$data <- lapply(add$data, function(x) {
  x$value <- x$value * 100
  x$datetime <- x$datetime +3600*5
  x
  })
class(dv[[1]]) <- 'character'
dv <- rbind(dv, add)


# dv <- xd[path %in% basename(fn)]
dv[, path := basename(file)]
dv <- dv[xd[, list(path, well, transducer_depth = depth, port, well_elevation = elevation, isbaro, timezone)], on = 'path', nomatch = 0]


dv <- dv[parameter == 'level']

dv <- dv[well == 'HBP-MPS4-20']


dv$data <- lapply(dv$data, function(x) {
  x$value <- x$value / 100
  x
  })

dv <- dv[, data := .(.(make_even_times(data[[1]], diff_time = dt))), by = 1:nrow(dv)]

dv <- westbay_to_elevation(dv, baro_port = 'Baro')
dv <- downsample_data(dv, time_interval = 300)


# gaps <- dv[, find_gaps(rbindlist(data)), by = list(name = paste(well, port))]
# tmp  <- dv[, make_regular(rbindlist(data), gaps), by = list(name = paste(well, port))]
# make_regular(dv, gaps)

dv <- trim_downloads(dv, n_vals = c(3600, 7200))
tmp <- dv[, rbindlist(data), by = list(well, port)]
tmp[is.na(value), wl_elevation := NA_real_]

tmp[, flag := 'Submerged']
tmp[value <= baro *1.009, flag := 'In air']

p1 <- ggplot(tmp[port != "Baro" & flag == 'Submerged'], 
             aes(x = datetime, y = wl_elevation, group = port, color = port)) + 
  ylab('Water level elevation (masl)') + 
  scale_color_brewer('Port Elevation', type = 'qual', palette = 'Set1') + 
  geom_line() + 
  # scale_y_continuous(limits = c(316, 319.5)) + 
  theme_bw()
ggplotly(p1)

p1 <- ggplot(tmp[port == "Baro"], 
             aes(x = datetime, y = baro, group = port, color = port)) + 
  ylab('Water level elevation (masl)') + 
  scale_color_brewer('Port Elevation', type = 'qual', palette = 'Set1') + 
  geom_line() + 
  theme_bw()
ggplotly(p1)


# dv[grep('hbp-mps2-19 port 1_200303114700_X0311.DAT', file)]


# 
# 
# 
# 
# y <- westbay_interpolate(y)

Read RBR (rsk)

fn <- list.files('/media/jonathankennel/Seagate Expansion Drive/guelph_south', full.names = TRUE)
fn <- fn[tools::file_ext(fn) == 'rsk']
rbr  <- read_transducer(fn)
rbr

Read Micron (xlsx)

fn <- list.files('/media/jonathankennel/Seagate Expansion Drive/guelph_south', full.names = TRUE)
fn <- fn[tools::file_ext(fn) == 'xlsx']
mu <- read_transducer(fn)
mu