jsta/watershed_ploading repository overview

# python
conda env create -f environment.yml
source activate pgml_ploading

# R
Rscript -e 'remotes::install_github("jsta/rinvest")'
Rscript -e 'rinvest::install_invest()'
Rscript -e 'install.packages("renv")'
Rscript -e 'install.packages(unique(renv::dependencies()$Package))'

# source utils script
source("scripts/99_utils.R")

site_no <- "05427718" # yahara at windsor
year    <- 2012

custom_params <- data.frame(
  median = c(k_param = 28.71, threshold_flow_accumulation = 98.56, load_fac = 2.43),  
  stringsAsFactors = FALSE
)

params <- ndr_params_default(custom_params)
run_ndr(params$median, site_no = site_no, year = year)

# see ndr_params_default()[c(12, 13, 14),]

# target load
read.csv("data/nwis/nwis.csv",
    colClasses = c("flow_station_id" = "character")) %>%
    dplyr::filter(flow_station_id == site_no) %>%
    pull(LOAD_A_00665) %>%
    round(2) # kg/yr

params <- params[c(12, 13, 14),]
parscale <- 1 / (params$median - as.numeric(scale(params$median)))

unlink("log.csv")
FME::modFit(run_ndr, 
    p = params$median, 
    lower = params$lower, upper = params$upper,
    site_no = site_no, year = year, 
    p_position = c(12, 13, 14),
    method = "Nelder-Mead", 
    control = list(parscale = parscale))

calibration_viz("log.csv")
calibration_viz("calibration/log_2012_05427718.csv")

make data
make -C calibration -f Makefile log_2012_05427718.csv
make calibration_local

Rscript -e 'testthat::test_dir("tests")'
Rscript -e 'testthat::test_file("tests/test-run_ndr.R")'