Convert data frame of parameters to list
Arguments
- pardf
tibbledata frame with tabular representation of hydrograph separation parameters as returned bygr_to_pardf().
Value
list of lists of hydrograph separation parameters as returned in params attribute by gr_separate() with debug = TRUE.
Examples
library(grwat)
data(spas) # example Spas-Zagorye data is included with grwat package
head(spas)
#> # A tibble: 6 × 4
#> Date Q Temp Prec
#> <date> <dbl> <dbl> <dbl>
#> 1 1956-01-01 5.18 -6.46 0.453
#> 2 1956-01-02 5.18 -11.4 0.825
#> 3 1956-01-03 5.44 -10.7 0.26
#> 4 1956-01-04 5.44 -8.05 0.397
#> 5 1956-01-05 5.44 -11.7 0.102
#> 6 1956-01-06 5.58 -20.1 0.032
# separate
sep = gr_separate(spas, params = gr_get_params(reg = 'center'))
#> grwat: data frame is correct
#> grwat: parameters list and types are OK
# Visualize
gr_plot_sep(sep, c(1978, 1989))
# Debug mode gives access to additional information
sep_debug = gr_separate(spas,
params = gr_get_params(reg = 'center'),
debug = TRUE)
#> grwat: data frame is correct
#> grwat: parameters list and types are OK
#> Warning: grwat: 1974 years were not separated. Check the input data for possible errors. Use gr_get_gaps() and gr_fill_gaps() functions to detect and fill missing data.
#> Warning: grwat: 2002, 2014, 2019 years were processed with jittered parameters
# a vector of years with jittered params
jit = attributes(sep_debug)$jittered
print(jit)
#> [1] 2002 2014 2019
# actual params used for each year
parlist = attributes(sep_debug)$params
# tweak parameters for selected year
parlist[['1989']]$grad1 = 3
parlist[['1989']]$grad2 = 6
# tabular representation of parameters
partab = gr_to_pardf(parlist)
head(partab)
#> # A tibble: 6 × 40
#> year winmon grad1 grad2 gratio spmon1 spmon2 sprisedays1 sprisedays2 spdays
#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1956 11 1.7 5 400 2 5 8 10 30
#> 2 1957 11 1.7 5 400 2 5 8 10 30
#> 3 1958 11 1.7 5 400 2 5 8 10 30
#> 4 1959 11 1.7 5 400 2 5 8 10 30
#> 5 1960 11 1.7 5 400 2 5 8 10 30
#> 6 1961 11 1.7 5 400 2 5 8 10 30
#> # ℹ 30 more variables: sprise <dbl>, spratio <dbl>, sprecdays <dbl>,
#> # spcomp <dbl>, precdays <dbl>, frostdays <dbl>, windays <dbl>,
#> # floodprec <dbl>, floodtemp <dbl>, frosttemp <dbl>, wintemp <dbl>,
#> # signratio1 <dbl>, signratio2 <dbl>, floodratio <dbl>, gaplen <dbl>,
#> # snowtemp <dbl>, gradabs <dbl>, mntmode <dbl>, mntgrad <dbl>,
#> # mntavgdays <dbl>, mntratiodays <dbl>, mntratio <dbl>, niter <dbl>, a <dbl>,
#> # k <dbl>, C <dbl>, aq <dbl>, padding <dbl>, passes <dbl>, filter <chr>
partab |>
dplyr::filter(year == 1989) |>
head()
#> # A tibble: 1 × 40
#> year winmon grad1 grad2 gratio spmon1 spmon2 sprisedays1 sprisedays2 spdays
#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1989 11 3 6 400 2 5 8 10 30
#> # ℹ 30 more variables: sprise <dbl>, spratio <dbl>, sprecdays <dbl>,
#> # spcomp <dbl>, precdays <dbl>, frostdays <dbl>, windays <dbl>,
#> # floodprec <dbl>, floodtemp <dbl>, frosttemp <dbl>, wintemp <dbl>,
#> # signratio1 <dbl>, signratio2 <dbl>, floodratio <dbl>, gaplen <dbl>,
#> # snowtemp <dbl>, gradabs <dbl>, mntmode <dbl>, mntgrad <dbl>,
#> # mntavgdays <dbl>, mntratiodays <dbl>, mntratio <dbl>, niter <dbl>, a <dbl>,
#> # k <dbl>, C <dbl>, aq <dbl>, padding <dbl>, passes <dbl>, filter <chr>
parlist_back = gr_from_pardf(partab)
head(parlist_back[['1989']])
#> $winmon
#> [1] 11
#>
#> $grad1
#> [1] 3
#>
#> $grad2
#> [1] 6
#>
#> $gratio
#> [1] 400
#>
#> $spmon1
#> [1] 2
#>
#> $spmon2
#> [1] 5
#>