library(McMasterPandemic)
library(splines)
library(dplyr)
library(parallel)
L <- load(".ont_keep.RData")
print(unique(ont_all_sub$var))
ont_noICU <- dplyr::filter(ont_all_sub, var != "ICU")
params <- fix_pars(read_params("ICU1.csv"))
inputs <- expand.grid(spline_df=3:7,
## NA = no penalization
## penalization is *inversely* prop to SD of prior on spline params
spline_sd_pen=c(NA,0.001,0.01,0.1),
## NA = time
knot_quantile_var=c(NA,"H","report"))
## reduced version
## inputs <- expand.grid(spline_df=c(3,7)
## spline_sd_pen=c(NA,1),
## knot_quantile_var=c(NA,"hosp"))
## ?run with data with just hosp or with hosp & reports?
## ?run for NYC and Central NY
res_list <- mclapply(seq(nrow(inputs)),
function(i) {
cat(i,paste(inputs[i,],collapse=", "),"\n")
do.call(calibrate_comb,
c(nlist(params
, debug_plot=FALSE
, data=ont_noICU)
, inputs[i,]))
},
mc.cores=5
)
# rdsave(inputs, res_list)
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