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nutrientes_perfiles_2021.R
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# Ricardo Gomez Reyes, 2021
# Visualising silicate profile
# Graficar perfiles de H4SiO4 para Atlántico N y S, Indico y Pacífico N y S
# A16N2013: 30oN y 6oS
# I09N_2016: 26 oS
# P16N2015 : 30oN y 17oSt
# (notar que los datos de 2015
# vienen en dos archivos)
# Graficar los 5 perfiles en la misma gráfica
# Graficar datos entre 0 y 5000 m de profundidad
# DEPTH METERS,
# SILCAT UMOL/KG
rm(list=ls())
library(tidyverse)
library(patchwork)
library(scales)
cols <- c('SECT_ID','GROUP', 'LATITUDE', 'LONGITUDE', 'CTDPRS', 'SILCAT', 'SALNTY', 'PHSPHT', 'OXYGEN', 'NITRAT',
'ALKALI', 'PH') # 'CO2',
files <- list.files(pattern = 'csv',
path = '~/Documents/DOCTORADO/CSV/', full.names = T)
x <- lapply(files, function(x) {
y <- read.csv(x, skip = 1, comment.char = "#", stringsAsFactors = F)
y <- data.frame(y, GROUP = basename(x))
y <- y %>% select_at(vars(-contains(c('FLAG', 'TMP'))))
# y <- y %>% select_at(vars(contains(cols))) # -contains('FLAG'), vars(contains(cols)
y <- y %>% rename_with(~ toupper(gsub("_SWS", "_TOT", .x, fixed = TRUE)))
return(y)})
x <- do.call(rbind, x) %>%
as_tibble() %>% drop_na()
x %>%
mutate(SECT_ID = as.factor(SECT_ID)) %>%
mutate(GROUP = str_replace_all(GROUP, '.csv$', '')) %>%
mutate(SECT_ID = str_replace_all(SECT_ID, '.[1-9]$', '')) %>%
mutate_if(is.character, function(x) {str_replace_all(x, ' ', '')}) %>%
mutate_at(vars(contains(cols[-c(1:2)])), as.double) -> x
# con respecto a la latitud
# A16N2013: 30N y 6S
# I09N_2016: 26 S
# P16N2015 : 30N y 17S
# eliminar 0.5 unidades de distancia
x %>%
filter(SECT_ID %in% 'A16N') %>%
filter(round(LATITUDE) == 30 | round(LATITUDE) == -6) -> A16N
A16N %>%
mutate(SECT_ID = ifelse(round(LATITUDE) == 30, 'A16N_30N', 'A16N_6S')) -> A16N
x %>%
filter(round(LATITUDE) == -26 &
SECT_ID %in% 'I09N' ) -> I09N
x %>%
filter(SECT_ID %in% 'P16N') %>%
filter(round(LATITUDE) == 30 | round(LATITUDE) == -17) -> P16N
P16N %>%
mutate(SECT_ID = ifelse(round(LATITUDE) == 30, 'P16N_30N', 'P16N_17S')) -> P16N
y <- rbind(A16N, I09N, P16N)
y %>%
mutate(ocean = '') %>%
mutate(ocean = ifelse(grepl('^A', SECT_ID), 'Atlantic',ocean )) %>%
mutate(ocean = ifelse(grepl('^I', SECT_ID), 'Indian',ocean )) %>%
mutate(ocean = ifelse(grepl('^P', SECT_ID), 'Pacific',ocean )) -> y
y %>%
mutate(CTDPRS = as.numeric(CTDPRS),
SILCAT = as.numeric(SILCAT)) %>%
filter(SILCAT > 0 & CTDPRS <= 5000) %>%
ggplot(aes(y = CTDPRS, x = SILCAT, color = ocean,
shape = SECT_ID)) +
geom_point(alpha = 0.7, size = 3) +
geom_line(orientation = 'y') +
# geom_path() +
scale_y_reverse() +
theme_bw(base_family = "GillSans", base_size = 18) +
scale_x_continuous(position = "top") +
theme(axis.text = element_text(size = 12, colour = 1),
axis.title = element_text(size = 14, colour = 1)) +
labs(x = expression(~H[4]~SiO[4]~(µmol~Kg^{-1})), y = expression(~Pressure~(dbar))) +
scale_shape_discrete(name = 'Coordinates') +
theme(legend.position = "none") -> p1
y %>%
mutate(CTDPRS = as.numeric(CTDPRS),
PHSPHT = as.numeric(PHSPHT)) %>%
filter(PHSPHT > 0 & CTDPRS <= 5000) %>%
ggplot(aes(y = CTDPRS, x = PHSPHT, color = ocean,
shape = SECT_ID)) +
geom_point(alpha = 0.7, size = 3) +
geom_line(orientation = 'y') +
# geom_path() +
scale_y_reverse() +
theme_bw(base_family = "GillSans", base_size = 18) +
scale_x_continuous(position = "top") +
theme(axis.text = element_text(size = 12, colour = 1),
axis.title = element_text(size = 14, colour = 1))+
labs(x = expression(~PO[4]~(µmol~Kg^{-1})), y = expression(~Pressure~(dbar))) +
scale_shape_discrete(name = 'Coordinates') +
theme(axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
legend.position = "right") -> p2
saveP <- p1+p2
saveP
# Pacific 32N profiling SILICATE and PHSPTH
library(scales)
x %>%
filter(SECT_ID %in% 'P16N') %>%
filter(round(LATITUDE) == 32) %>%
mutate_at(vars(c('SILCAT', 'PHSPHT', 'CTDPRS', 'SALNTY')), as.numeric) %>%
filter(PHSPHT > 0 & CTDPRS <= 5000) %>%
# mutate()
ggplot(data = ., aes(y = CTDPRS)) +
scale_y_reverse() +
geom_line(aes(x = PHSPHT), colour = 'red', orientation = 'y') +
geom_line(aes(x = SILCAT/50), color = 'blue', orientation = 'y') +
scale_x_continuous(expression(~PO[4]~(µmol~Kg^{-1})),
sec.axis = sec_axis(~.*50,
name = expression(~H[4]~SiO[4]~(µmol~Kg^{-1})))) +
theme_bw(base_family = "GillSans", base_size = 18) +
labs(y = expression(~Pressure~(dbar))) +
theme(axis.text.x.top = element_text(color = "blue"),
axis.text.x.bottom = element_text(color = "red"),
axis.ticks.x.top = element_line(color = "blue"),
axis.ticks.x.bottom = element_line(color = 'red'),
axis.title.x.top = element_text(color = "blue"),
axis.title.x.bottom = element_text(color = 'red')) -> p3
# facet nutrients
cols <- c('SILCAT', 'PHSPHT', 'NITRAT', 'OXYGEN', 'ALKALI', 'PH_TOT', 'SALNTY') # ,
# expression(~H[4]~SiO[4]~(µmol~Kg^{-1}))
nitrL <- quote(NO[3]~(µmol~L^{-1}))
fosL <- quote(PO[4]~(µmol~L^{-1}))
silL <- quote(H[4]~SiO[4]~(µmol~Kg^{-1}))
OxL <- quote(O[2]~(µmol~L^{-1}))
labels <- c(silL, fosL, nitrL, OxL, 'Alcalinidad', 'pH', 'Salinidad') # ,
y %>%
filter(CTDPRS <= 5000) %>%
pivot_longer(cols = cols, names_to = 'var') %>%
filter(value > 0) %>%
mutate(var = factor(var, levels = cols, labels = labels)) -> y_longer
y_longer %>% group_by(SECT_ID, var) %>% filter(value > mean(value))
# CTDPRS > 200 & CTDPRS <= 1000
y_longer %>%
mutate(depth = '') %>%
mutate(depth = ifelse(CTDPRS <= 200, '0-200',
ifelse(between(CTDPRS, 200, 1000), '200-1000',
ifelse(between(CTDPRS, 1000, 4000), '1000-4000',
ifelse(CTDPRS > 4000, '> 4000', depth))))) %>%
mutate(depth = factor(depth, levels = c('0-200', '200-1000', '1000-4000', '> 4000'))) %>%
# group_by(depth) %>% count() %>% pull(n) %>% sum() # sanity check
ggplot(aes(y = value, x = depth)) +
facet_grid(var~ocean, scales = 'free',
labeller = labeller(var = label_parsed)) +
stat_boxplot(geom ='errorbar', width = 0.15,
position = position_dodge(0.6)) +
geom_boxplot(width = 0.4, position = position_dodge(0.6)) +
stat_summary(fun=mean, geom="point", shape=23, size=1, color = 'red', position = position_dodge(0.6)) +
labs(y = '') +
theme_minimal() +
theme(strip.background = element_blank(),
axis.line.y = element_line(colour = "black"),
panel.border = element_blank()) -> psave
ggsave(psave, path = '~/Documents/DOCTORADO/', filename = 'facet_vars_box.png', width = 10, height = 10)
y_longer %>% group_by(GROUP, var, ocean) %>%
mutate(z = (value - mean(value))/sd(value) ) %>%
filter(!abs(z) > 3) -> y_longer
# group_by(var) %>%
# summarise(q = quantile(z)) %>%
# ggplot(aes(x=var, y = abs(q))) + geom_boxplot()
y_longer %>%
ggplot(aes(y = CTDPRS, x = value, shape = SECT_ID)) + #
geom_point(alpha = 0.7, size = 1.5) +
geom_line(orientation = 'y') +
# geom_path() +
scale_y_reverse() +
theme_bw(base_family = "GillSans", base_size = 18) +
scale_x_continuous(position = "bottom") +
theme(legend.position = "top",
strip.background = element_blank(),
axis.line.y = element_line(colour = "black"),
panel.border = element_blank()) +
labs(x = '', y = expression(~Profundidad~(dbar))) +
scale_shape_discrete(name = 'Coordenadas') +
facet_grid(ocean~var, scales = 'free_x', labeller = labeller(var = label_parsed)) -> p
ggsave(p, path = '~/Documents/DOCTORADO/', filename = 'facet_vars_depth.png', width = 20, height = 10)
#
#
# y_longer %>%
# ggplot(aes(y = value, x = SALNTY)) + #
# geom_point(alpha = 0.7, size = 1.5) +
# facet_grid(var~ocean, scales = 'free', labeller = labeller(var = label_parsed))
# Graficar a una misma escala, H4SiO4 y PO4 de la coordenada 32 N del Pacifico.
x %>%
filter(SECT_ID %in% 'P16N') %>%
filter(round(LATITUDE) == 32) %>%
mutate_at(vars(c('SILCAT', 'PHSPHT', 'CTDPRS', 'SALNTY')), as.numeric) %>%
filter(PHSPHT > 0 & CTDPRS <= 5000) %>%
# mutate()
ggplot(data = ., aes(y = CTDPRS)) +
scale_y_reverse() +
geom_line(aes(x = PHSPHT), colour = 'red', orientation = 'y') +
geom_line(aes(x = SILCAT/50), color = 'blue', orientation = 'y') +
scale_x_continuous(expression(~PO[4]~(µmol~Kg^{-1})),
sec.axis = sec_axis(~.*50,
name = expression(~H[4]~SiO[4]~(µmol~Kg^{-1})))) +
theme_bw(base_family = "GillSans", base_size = 18) +
labs(y = expression(~Profundidad~(dbar)),
caption = "Perfiles verticales de silicato y fosfato del Pacifico Norte (32°N)") +
theme(axis.text.x.top = element_text(color = "blue"),
axis.text.x.bottom = element_text(color = "red"),
axis.ticks.x.top = element_line(color = "blue"),
axis.ticks.x.bottom = element_line(color = 'red'),
axis.title.x.top = element_text(color = "blue"),
axis.title.x.bottom = element_text(color = 'red')) -> p3
ggsave(p3, path = '~/Documents/DOCTORADO/', filename = 'DSi_PO4_profiles.png', width = 5.5, height = 5.5)