Skip to content

Commit 11a2093

Browse files
westonslaughterwestonslaughter
authored
Merge pull request #159 from vlahm/master
just some cleanup
2 parents 401ada1 + cd16c63 commit 11a2093

11 files changed

Lines changed: 456 additions & 70 deletions

‎src/acquisition_master.R‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -264,7 +264,7 @@ ms_globals <- c(ls(all.names = TRUE), 'ms_globals')
264264

265265
dir.create('logs', showWarnings = FALSE)
266266

267-
# dmnrow = 20
267+
# dmnrow = 8
268268
# print(network_domain, n=50)
269269
for(dmnrow in 1:nrow(network_domain)){
270270

@@ -281,7 +281,7 @@ for(dmnrow in 1:nrow(network_domain)){
281281
# held_data = invalidate_tracked_data(network, domain, 'derive')
282282
# owrite_tracker(network, domain)
283283

284-
# held_data = invalidate_tracked_data(network, domain, 'munge', 'stream_chemistry')
284+
# held_data = invalidate_tracked_data(network, domain, 'munge', 'precipitation')
285285
# owrite_tracker(network, domain)
286286
# held_data = invalidate_tracked_data(network, domain, 'derive', 'stream_flux_inst')
287287
# owrite_tracker(network, domain)
@@ -303,7 +303,7 @@ for(dmnrow in 1:nrow(network_domain)){
303303
# prodname_filter = c('stream_chemistry'),
304304
domain = domain)
305305
ms_munge(network = network,
306-
# prodname_filter = c('discharge'),
306+
prodname_filter = c('stream_chemistry'),
307307
domain = domain)
308308
if(domain != 'mcmurdo'){
309309
sw(ms_delineate(network = network,

‎src/czo/network_helpers.R‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -115,9 +115,9 @@ populate_set_details <- function(tracker, prodname_ms, site_code, avail){
115115
s = sites,
116116
c = components)
117117

118-
email_err(msgs = update_msg,
119-
addrs = conf$report_emails,
120-
pw = conf$gmail_pw)
118+
#email_err(msgs = update_msg,
119+
# addrs = conf$report_emails,
120+
# pw = conf$gmail_pw)
121121
}
122122
}
123123

‎src/dev/investigate_pchem_sample_regimes.R‎

Lines changed: 179 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,179 @@
1+
library(ggplot2)
2+
3+
#pchem
4+
d = load_product('precip_chemistry', 'macrosheds_dataset')
5+
doms = distinct(d, domain) %>% pull()
6+
7+
for(dom in doms){
8+
9+
dd = filter(d, domain == !!dom)
10+
11+
dd = dd %>%
12+
# filter(ms_interp == 0) %>%
13+
mutate(val = drop_errors(val)) %>%
14+
select(-ms_status, -network) %>%
15+
arrange(domain, site_code, datetime)
16+
17+
gg = dd %>%
18+
mutate(val = ifelse(ms_interp == 0, val, -10)) %>%
19+
filter(datetime > max(dd$datetime) - 60 * 60 * 24 * 100) %>%
20+
ggplot() +
21+
geom_line(aes(x = datetime, y = val, color = var)) +
22+
labs(title = dom) +
23+
facet_wrap(vars(site_code))
24+
print(gg)
25+
readLines(n=1)
26+
27+
gg = dd %>%
28+
filter(datetime > max(dd$datetime) - 60 * 60 * 24 * 100) %>%
29+
ggplot() +
30+
geom_line(aes(x = datetime, y = val, color = var)) +
31+
labs(title = dom) +
32+
facet_wrap(vars(site_code))
33+
print(gg)
34+
readLines(n=1)
35+
36+
gg = dd %>%
37+
mutate(val = ifelse(ms_interp == 0, val, -10)) %>%
38+
filter(datetime > max(dd$datetime) - 2 * 60 * 60 * 24 * 365) %>%
39+
ggplot() +
40+
geom_line(aes(x = datetime, y = val, color = var)) +
41+
labs(title = dom) +
42+
facet_wrap(vars(site_code))
43+
print(gg)
44+
# filter(dd, site_code == 'WS78', datetime > as.Date('2015-07-01'), datetime < as.Date('2015-10-01'), var == 'GN_TP') %>%
45+
# ggplot()+geom_point(aes(datetime, val, color = var))
46+
readLines(n=1)
47+
48+
gg = dd %>%
49+
filter(datetime > max(dd$datetime) - 2 * 60 * 60 * 24 * 365) %>%
50+
ggplot() +
51+
geom_line(aes(x = datetime, y = val, color = var)) +
52+
labs(title = dom) +
53+
facet_wrap(vars(site_code))
54+
print(gg)
55+
readLines(n=1)
56+
57+
# gg = dd %>%
58+
# # mutate(val = ifelse(ms_interp == 1, NA_real_, val)) %>%
59+
# ggplot() +
60+
# geom_line(aes(x = datetime, y = val, color = var)) +
61+
# labs(title = dom) +
62+
# facet_wrap(vars(site_code))
63+
# print(gg)
64+
# readLines(n=1)
65+
}
66+
67+
#precip
68+
d = load_product('precipitation', 'macrosheds_dataset')
69+
doms = distinct(d, domain) %>% pull()
70+
71+
for(dom in doms){
72+
73+
dd = filter(d, domain == !!dom)
74+
75+
dd = dd %>%
76+
# filter(ms_interp == 0) %>%
77+
mutate(val = drop_errors(val)) %>%
78+
select(-ms_status, -network) %>%
79+
arrange(domain, site_code, datetime)
80+
81+
# gg = dd %>%
82+
# mutate(val = ifelse(ms_interp == 0, val, -10)) %>%
83+
# filter(datetime > max(dd$datetime) - 60 * 60 * 24 * 100) %>%
84+
# ggplot() +
85+
# geom_line(aes(x = datetime, y = val)) +
86+
# labs(title = dom) +
87+
# facet_wrap(vars(site_code))
88+
# print(gg)
89+
# readLines(n=1)
90+
#
91+
# gg = dd %>%
92+
# filter(datetime > max(dd$datetime) - 60 * 60 * 24 * 100) %>%
93+
# ggplot() +
94+
# geom_line(aes(x = datetime, y = val)) +
95+
# labs(title = dom) +
96+
# facet_wrap(vars(site_code))
97+
# print(gg)
98+
# readLines(n=1)
99+
#
100+
# gg = dd %>%
101+
# mutate(val = ifelse(ms_interp == 0, val, -10)) %>%
102+
# filter(datetime > max(dd$datetime) - 2 * 60 * 60 * 24 * 365) %>%
103+
# ggplot() +
104+
# geom_line(aes(x = datetime, y = val)) +
105+
# labs(title = dom) +
106+
# facet_wrap(vars(site_code))
107+
# print(gg)
108+
# readLines(n=1)
109+
110+
print(dom)
111+
qqq = filter(dd, datetime > max(dd$datetime) - 2 * 60 * 60 * 24 * 365)
112+
print(paste(sum(is.na(qqq$val)), nrow(qqq)))
113+
114+
gg = dd %>%
115+
filter(datetime > max(dd$datetime) - 2 * 60 * 60 * 24 * 365) %>%
116+
ggplot() +
117+
geom_line(aes(x = datetime, y = val)) +
118+
labs(title = dom) +
119+
facet_wrap(vars(site_code))
120+
print(gg)
121+
# readLines(n=1)
122+
#
123+
# ggsave(glue('~/git/macrosheds/data_acquisition/plots/precip_coverage/{dom}.png'))
124+
}
125+
126+
127+
#investigate konza
128+
bb = read_csv('data/lter/konza/raw/precipitation__4/sitename_NA/APT011.csv') %>%
129+
mutate(ppt = as.numeric(ppt))
130+
bb %>%
131+
mutate(RecDate = as.Date(RecDate, format = '%d/%m/%Y')) %>%
132+
group_by(watershed) %>%
133+
summarize(n_recs = n(), mindate = min(RecDate, na.rm=T), maxdate = max(RecDate, na.rm=T))
134+
135+
bb %>%
136+
filter(! is.na(RecDate),
137+
duplicated(RecDate)) %>%
138+
mutate(RecDate = as.Date(RecDate, format = '%d/%m/%Y')) %>%
139+
arrange(watershed, RecDate) %>%
140+
ggplot() +
141+
geom_line(aes(x=RecDate, y=ppt)) +
142+
facet_wrap(vars(watershed))
143+
144+
bb %>%
145+
filter(! is.na(RecDate),
146+
duplicated(RecDate)) %>%
147+
mutate(RecDate = as.Date(RecDate, format = '%d/%m/%Y')) %>%
148+
filter(RecDate > as.Date('2020-01-01')) %>%
149+
arrange(watershed, RecDate) %>%
150+
ggplot() +
151+
geom_point(aes(x=RecDate, y=ppt)) +
152+
facet_wrap(vars(watershed))
153+
154+
155+
dd2 = dd %>%
156+
filter(site_code == 'N01B') %>%
157+
mutate(date = as.Date(datetime)) %>%
158+
select(date, val)
159+
bb2 = bb %>%
160+
filter(! is.na(RecDate),
161+
duplicated(RecDate)) %>%
162+
mutate(RecDate = as.Date(RecDate, format = '%d/%m/%Y')) %>%
163+
filter(RecDate > as.Date('2020-01-01')) %>%
164+
arrange(watershed, RecDate) %>%
165+
filter(watershed == 'K01B') %>%
166+
select(RecDate, ppt, Comments) %>%
167+
full_join(dd2, by = c('RecDate' = 'date')) %>%
168+
filter(if_any(c(ppt, val), ~!is.na(.))) %>%
169+
filter(RecDate > as.Date('2020-01-01')) %>%
170+
arrange(RecDate) %>%
171+
mutate(Comments = ifelse(! is.na(Comments), 'blue', 'black'))
172+
plot(bb2$RecDate, bb2$ppt, col=bb2$Comments)
173+
lines(bb2$RecDate, bb2$val, col = 'red')
174+
bb3 = filter(bb2, RecDate > as.Date('2021-01-01'))
175+
176+
png('~/Desktop/konza_precip.png')
177+
plot(bb3$RecDate, bb3$ppt, col=bb3$Comments)
178+
lines(bb3$RecDate, bb3$val, col = 'red')
179+
dev.off()

‎src/dev/krycklan_stream_chem_investigate.R‎

Lines changed: 37 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,37 @@
1+
#this code is useful after cast_and_reflag (not exactly as-is)
2+
3+
zz %>%
4+
select(-`pCO2 µatm`) %>%
5+
mutate(across(-c(Date, SiteID), as.numeric)) %>%
6+
pivot_longer(cols = -c(Date, SiteID), names_to = 'var', values_to = 'val') %>%
7+
ggplot()+
8+
geom_line(aes(Date, val, color=var))+
9+
facet_wrap(.~SiteID, scales = 'free')+
10+
theme(legend.position="none")
11+
d %>%
12+
ggplot()+
13+
geom_line(aes(datetime, val, color=var))+
14+
facet_wrap(.~site_code, scales = 'free')+
15+
theme(legend.position="none")
16+
17+
zz %>%
18+
filter(SiteID == 54) %>%
19+
# filter(Date > as.Date('2019-01-01'), Date < as.Date('2019-05-01')) %>%
20+
select(-`pCO2 µatm`) %>%
21+
select(Date, SiteID, `Ag µg/l`) %>%
22+
mutate(across(-c(Date, SiteID), as.numeric)) %>%
23+
pivot_longer(cols = -c(Date, SiteID), names_to = 'var', values_to = 'val') %>%
24+
ggplot()+
25+
geom_line(aes(Date, val, color=var))+
26+
facet_wrap(.~SiteID, scales = 'free')+
27+
theme(legend.position="none")
28+
d %>%
29+
mutate(val = drop_errors(val)) %>%
30+
filter(site_code == 'Site54') %>%
31+
mutate(val = val * 1000) %>%
32+
filter(var=='GN_Ag') %>%
33+
# filter(datetime > as.Date('2019-01-01'), datetime < as.Date('2019-05-01'), var == 'GN_Ag')
34+
ggplot()+
35+
geom_line(aes(datetime, val, color=var))+
36+
facet_wrap(.~site_code, scales = 'free')+
37+
theme(legend.position="none")

0 commit comments

Comments
 (0)