Last updated: 2019-11-14
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Knit directory: BloomSail/
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html | d61a468 | jens-daniel-mueller | 2019-11-14 | Build site. |
html | f3277a5 | jens-daniel-mueller | 2019-11-08 | Build site. |
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html | 33e3659 | jens-daniel-mueller | 2019-10-22 | Build site. |
Rmd | efcafd1 | jens-daniel-mueller | 2019-10-22 | Added data base, merging, and RT determination |
html | 1595fe9 | jens-daniel-mueller | 2019-10-21 | Build site. |
Rmd | 4131b9c | jens-daniel-mueller | 2019-10-21 | finisehd read CTD and HydroC, created merging Rmd |
library(tidyverse)
library(lubridate)
library(zoo)
# library(dygraphs)
# library(xts)
# Load Sensor and HydroC data ---------------------------------------------
CTD <- read_csv(here::here("Data/_summarized_data_files",
"Tina_V_Sensor_Profiles_Transects.csv"),
col_types = list("pCO2" = col_double())) %>%
rename(pCO2_analog = pCO2)
HC <- read_csv(here::here("Data/_summarized_data_files", "Tina_V_HydroC.csv"))
# Time offset correction ----------------------------------------------
# Time offset was determined by comparing zeroing reads from Sensor and HC
# in the plots produced in the section Time stamp synchronzity below
# before applying this correction
CTD <- CTD %>%
mutate(day = yday(date_time),
date_time = if_else(day >= 206 & day <= 220,
date_time - 80, date_time - 10)) %>%
select(-day)
# Merge Sensor and HydroC data --------------------------------------------
df <- full_join(CTD, HC) %>%
arrange(date_time)
rm(HC, CTD)
CTD and auxillary recordings (15 sec measurment interval) are interpolated to HydroC time stamps (first 10 sec, than 1 sec measurement interval) when gaps between observations are not larger than 20. Thereafter, HydroC readings not falling in regular transects/profilings are removed, by removing rows with NA depth values. Furthermore, CTD readings without corresponding HydroC reading are removed, except during periods when HydroC was not operating.
# Interpolate Sensor data to HydroC timestamp
df <-
df %>%
mutate(dep = na.approx(dep, na.rm = FALSE, maxgap = 20),
sal = na.approx(sal, na.rm = FALSE, maxgap = 20),
tem = na.approx(tem, na.rm = FALSE, maxgap = 20),
pCO2_analog = na.approx(pCO2_analog, na.rm = FALSE, maxgap = 20),
pH = na.approx(pH, na.rm = FALSE, maxgap = 20),
V_pH = na.approx(V_pH, na.rm = FALSE, maxgap = 20),
O2 = na.approx(O2, na.rm = FALSE, maxgap = 20),
Chl = na.approx(Chl, na.rm = FALSE, maxgap = 20)) %>%
filter(!is.na(dep)) %>% #remove HC readings not falling in regular transects/profilings
fill(ID, type, station, cast) %>%
filter(!is.na(deployment) | is.na(pCO2_analog)) # removes CTD readings without corresponding HydroC reading, except during periods when HydroC was not operating
# Time stamp synchronzity -------------------------------------------------
#
# df <- df %>%
# mutate(day = yday(date_time))
#
# for (dayID in unique(df$day)) {
#
# df %>%
# filter(day == dayID) %>%
# ggplot()+
# geom_point(aes(date_time, pCO2, col="HC"))+
# geom_point(aes(date_time, dep, col="dep"))+
# geom_point(aes(date_time, pH, col="pH"))+
# geom_point(aes(date_time, pCO2_analog, col="Sensor_int"))
#
# ggsave(here::here("/Plots/TinaV/Sensor/HydroC_diagnostics/Timing/day",
# paste(dayID,"_day_HydroC_merged.jpg", sep="")),
# width = 10, height = 4)
# }
#
#
# for (depID in unique(df$deployment)) {
#
# df_dep <- df %>%
# filter(deployment == depID, Zero == 1)
#
# for (zerID in unique(df_dep$Zero_ID)) {
#
# df_dep %>%
# filter(Zero_ID == zerID) %>%
# ggplot()+
# geom_point(aes(date_time, pCO2, col="HC"))+
# geom_point(aes(date_time, pCO2_analog, col="Sensor_int"))
#
# ggsave(here::here("/Plots/TinaV/Sensor/HydroC_diagnostics/Timing/Zeroing",
# paste(depID,"_deployment_",zerID,"_Zero_ID_HydroC.jpg", sep="")),
# width = 10, height = 4)
#
# }
# }
write_csv(df, here::here("Data/_merged_data_files", "BloomSail_CTD_HydroC.csv"))
HC <-
read_csv2(here::here("Data/TinaV/Sensor/HydroC-pCO2/corrected_Contros",
"parameter&pCO2s(method 43).txt"),
col_names = c("date_time", "Zero", "Flush", "p_NDIR",
"p_in", "T_control", "T_gas", "%rH_gas",
"Signal_raw", "Signal_ref", "T_sensor",
"pCO2", "Runtime", "nr.ave")) %>%
mutate(Flush = as.factor(as.character(Flush)),
Zero = as.factor(as.character(Zero)))
df %>%
filter(!is.na(pCO2)) %>%
ggplot()+
geom_path(aes(date_time, pCO2, col = "HydroC, drift corrected"))+
geom_path(aes(date_time, pCO2_analog, col = "analog CTD"))+
scale_color_brewer(palette = "Set1", name = "pCO2 record")+
labs(y=expression(pCO[2]~(µatm)), x="")+
facet_wrap(~ID, scales = "free_x", ncol = 1)
# ts <- xts(cbind(df$pCO2, df$dep), order.by = df$date_time)
# names(ts) <- c("pCO2", "Depth")
#
# ts %>%
# dygraph() %>%
# dyRangeSelector() %>% #dateWindow = c("2012-01-01", "2016-12-31")
# dySeries("pCO2", label = "pCO2") %>%
# dySeries("Depth", axis = 'y2', label = "Depth") %>%
# dyAxis("y", label = "pCO2 [µatm]") %>%
# dyAxis("y2", label = "Depth [m]") %>%
# dyOptions(drawPoints = TRUE, pointSize = 1)
sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] zoo_1.8-6 lubridate_1.7.4 forcats_0.4.0 stringr_1.4.0
[5] dplyr_0.8.3 purrr_0.3.3 readr_1.3.1 tidyr_1.0.0
[9] tibble_2.1.3 ggplot2_3.2.1 tidyverse_1.2.1
loaded via a namespace (and not attached):
[1] tidyselect_0.2.5 xfun_0.10 haven_2.1.1
[4] lattice_0.20-35 colorspace_1.4-1 vctrs_0.2.0
[7] generics_0.0.2 htmltools_0.4.0 yaml_2.2.0
[10] utf8_1.1.4 rlang_0.4.1 pillar_1.4.2
[13] glue_1.3.1 withr_2.1.2 RColorBrewer_1.1-2
[16] modelr_0.1.5 readxl_1.3.1 lifecycle_0.1.0
[19] munsell_0.5.0 gtable_0.3.0 workflowr_1.4.0
[22] cellranger_1.1.0 rvest_0.3.4 evaluate_0.14
[25] labeling_0.3 knitr_1.25 fansi_0.4.0
[28] highr_0.8 broom_0.5.2 Rcpp_1.0.2
[31] scales_1.0.0 backports_1.1.5 jsonlite_1.6
[34] fs_1.3.1 hms_0.5.1 digest_0.6.22
[37] stringi_1.4.3 grid_3.5.0 rprojroot_1.3-2
[40] here_0.1 cli_1.1.0 tools_3.5.0
[43] magrittr_1.5 lazyeval_0.2.2 crayon_1.3.4
[46] whisker_0.4 pkgconfig_2.0.3 zeallot_0.1.0
[49] ellipsis_0.3.0 xml2_1.2.2 assertthat_0.2.1
[52] rmarkdown_1.16 httr_1.4.1 rstudioapi_0.10
[55] R6_2.4.0 nlme_3.1-137 git2r_0.26.1
[58] compiler_3.5.0