Comments (2)
Post questions and/or plot/statistics here!
from daynight-q10.
# we start with `dat` which holds timestamp, location, soil respiration
# e.g. one site, one week, hourly data = 24 * 7 = 168 rows
dat %>%
# figure out what sm file each observation needs to draw from
mutate(filename = compute_filename(timestamp)) %>% # takes 168 unique timestamps -> 3 unique filenames
# we don't want to duplicate effort, so `distinct()`
distinct(lat, lon, filename) %>% # after this we have only three rows!
# for each filename, extract all the lat/lon s.m. data we need
group_by(filename) %>%
mutate(sm = get_sm_data(lat, lon, filename)) %>% # still have three rows
# after this right_join, we're going to end up with EXACTLY the same number of rows we started with!
right_join(dat, by = c("filename", "lat", "lon")) ->
dat
from daynight-q10.
Related Issues (15)
- First steps HOT 5
- Weeks 5-6 HOT 1
- Small R2 Values HOT 1
- Visualizations HOT 8
- Next steps in Q10 work HOT 15
- SMOS File Download HOT 7
- Reading grib data HOT 4
- Code Efficiency HOT 5
- Additional Graphs HOT 2
- Progress? HOT 3
- Check the percentage of Rh also reported Ts HOT 3
- calc_q10 function HOT 2
- Colin - weeks 3 and 4 HOT 8
- More on calculating Q10
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