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Updated plots to only last seven days #43

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Merged
wilsonsj100 merged 1 commit into from
Dec 16, 2025
Merged

Updated plots to only last seven days #43

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Binary file added CB_checks/CB_Chk_20251216.pdf
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71 changes: 52 additions & 19 deletions current-data.qmd
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
---
author: "COMPASS workflows team"
params:
DROPBOX: "~/Dropbox/"
DROPBOX: "C:/Users/wilsonsj/Smithsonian Dropbox/Stephanie Wilson"
SITES: "CB"
date: now
date-format: "YYYY-MM-DD HH:mm:ssZ"
Expand All @@ -26,6 +26,7 @@ theme_set(theme_bw())
library(dplyr)
library(tidyr)
library(gt)
library(lubridate)

SITES <- params$SITES
PATH <- params$DROPBOX
Expand Down Expand Up @@ -260,8 +261,15 @@ if(nrow(sf) > 0) {
left_join(SF_METADATA, by = c("Site", "Logger", "Port")) ->
sf_long

for(site in unique(sf_long$Site)) {
p <- ggplot(filter(sf_long, Site == site), aes(TIMESTAMP, value, color = Tree)) +
sf_long_current <- sf_long %>%
filter(
TIMESTAMP >= Sys.time() - days(7),
TIMESTAMP <= Sys.time()
)

for(site in unique(sf_long_current$Site)) {
p <- ggplot(filter(sf_long_current, Site == site),
aes(TIMESTAMP, value, color = Tree)) +
facet_grid(. ~ Plot) +
ylab("Raw sapflow") +
geom_point(na.rm = TRUE) +
Expand All @@ -273,7 +281,7 @@ if(nrow(sf) > 0) {

```{r sf-table}
if(nrow(sf) > 0) {
sf_long %>%
sf_long_current %>%
group_by(Site, Plot) %>%
summarise(N_sensor = length(unique(Tree)),
Mean = mean(value, na.rm = TRUE),
Expand Down Expand Up @@ -319,8 +327,14 @@ if(nrow(teros) > 0) {
)) ->
teros_long

for(site in unique(teros_long$Site)) {
teros_site <- filter(teros_long, Site == site)
teros_long_current <- teros_long %>%
filter(
TIMESTAMP >= Sys.time() - days(7),
TIMESTAMP <= Sys.time()
)

for(site in unique(teros_long_current$Site)) {
teros_site <- filter(teros_long_current, Site == site)
p <- ggplot(teros_site, aes(TIMESTAMP, value, color = Depth_cm)) +
facet_grid(sensor_name ~ Plot, scales = "free") +
geom_point(na.rm = TRUE) +
Expand All @@ -333,7 +347,7 @@ if(nrow(teros) > 0) {

```{r teros-table}
if(nrow(teros) > 0) {
teros_long %>%
teros_long_current %>%
group_by(Site, Plot, sensor_name) %>%
summarise(N_sensor = length(unique(Port)),
Mean = mean(value, na.rm = TRUE),
Expand Down Expand Up @@ -423,19 +437,26 @@ troll_long %>%

# join is many-to-one: many names at a given timestamp
troll_long %>%
left_join(wl, by = c("Site", "Plot", "Instrument_ID", "TIMESTAMP"), relationship = "many-to-one") ->
left_join(wl, by = c("Site", "Plot", "Instrument_ID", "TIMESTAMP"),
relationship = "many-to-one") ->
troll_long

p <- ggplot(troll_long, aes(TIMESTAMP, water_level_cm, color = water_level_cm < -ground_to_sensor_cm)) +
troll_long_current <- troll_long %>%
filter(
TIMESTAMP >= Sys.time() - days(7),
TIMESTAMP <= Sys.time()
)

p <- ggplot(troll_long_current, aes(TIMESTAMP, water_level_cm, color = water_level_cm < -ground_to_sensor_cm)) +
facet_grid(Site ~ Plot, scales = "free") +
geom_point(na.rm = TRUE) +
scale_color_manual("WL below sensor", values = c("black", "red")) +
ggtitle("water_level_cm") +
theme(axis.text.x = element_text(angle = 90))
print(p)

for(nm in unique(troll_long$name)) {
x <- filter(troll_long, name == nm)
for(nm in unique(troll_long_current$name)) {
x <- filter(troll_long_current, name == nm)
p <- ggplot(x, aes(TIMESTAMP, value, color = water_level_cm < -ground_to_sensor_cm)) +
facet_grid(Site ~ Plot, scales = "free") +
ylab(nm) +
Expand All @@ -450,7 +471,7 @@ troll_long %>%

```{r troll-tables}
if(nrow(troll) > 0) {
troll_long %>%
troll_long_current %>%
group_by(Site, Plot, name) %>%
summarise(N_sensor = length(unique(Instrument_ID)),
Mean = mean(value, na.rm = TRUE),
Expand Down Expand Up @@ -510,9 +531,15 @@ if(nrow(redox) > 0) {
mutate(Depth_Rep = as.factor(paste(Depth, Rep, sep = "-"))) ->
redox_long

redox_long_current <- redox_long %>%
filter(
TIMESTAMP >= Sys.time() - days(7),
TIMESTAMP <= Sys.time()
)

for(site in unique(redox_long$Site)) {
redox_site <- filter(redox_long, Site == site)

for(site in unique(redox_long_current$Site)) {
redox_site <- filter(redox_long_current, Site == site)
p <- ggplot(redox_site, aes(TIMESTAMP, value, color = Depth_Rep)) +
facet_grid(which ~ Plot) +
geom_point(na.rm = TRUE) +
Expand All @@ -526,7 +553,7 @@ if(nrow(redox) > 0) {

```{r redox-table}
if(nrow(redox) > 0) {
redox_long %>%
redox_long_current %>%
group_by(Site, Plot) %>%
summarise(N_sensor = length(unique(number)),
Mean = mean(value, na.rm = TRUE),
Expand Down Expand Up @@ -558,8 +585,14 @@ if(nrow(exo) > 0) {
pivotstep() ->
exo_long

for(site in unique(exo_long$Site)) {
p <- ggplot(filter(exo_long, Site == site), aes(TIMESTAMP, value)) +
exo_long_current <- exo_long %>%
filter(
TIMESTAMP >= Sys.time() - days(7),
TIMESTAMP <= Sys.time()
)

for(site in unique(exo_long_current$Site)) {
p <- ggplot(filter(exo_long_current, Site == site), aes(TIMESTAMP, value)) +
facet_wrap(. ~ name, scales = "free") +
geom_point(na.rm = TRUE) +
ggtitle(site)
Expand All @@ -570,8 +603,8 @@ if(nrow(exo) > 0) {

```{r exo-tables}
if(nrow(exo) > 0) {
exo_long %>%
group_by(Site, Plot, name) %>%
exo_long_current %>%
group_by(Site, name) %>%
summarise(Mean = mean(value, na.rm = TRUE),
SD = sd(value, na.rm = TRUE),
Range = robust_range(value, 3),
Expand Down
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