Запуск следующего кода из блога Тима Черча и получение этой ошибки. https://timchurches.github.io/blog/posts/2020-03-18-modelling-the-effects-of-public-health-interventions-on-covid-19-transmission-part-2/
Error in { : task 1 failed - "could not find function "init_status.icm""
Ошибка говорит о том, что не может найти функцию, но я вижу ее в функциях среды.
Если вы загружаете код и запускаете его, он работает для вас? Я пытаюсь заставить работать этот базовый сценарий и затем изменить параметры, чтобы использовать разные допущения для моделирования распространения covid-19 среди населения. Может кто-нибудь помочь, пожалуйста?
# Churches (2020, March 18). Tim Churches Health Data Science Blog: Modelling the effects of public health interventions on COVID-19 transmission using R - part 2. Retrieved from https://timchurches.github.io/blog/posts/2020-03-18-modelling-the-effects-of-public-health-interventions-on-covid-19-transmission-part-2/
library(tidyverse)
library(magrittr)
library(lubridate)
library(stringr)
library(tibble)
library(broom)
library(ggplot2)
library(gt)
library(knitr)
library(devtools)
library(DiagrammeR)
library(parallel)
library(foreach)
library(tictoc)
suppressMessages(library(EpiModel))
library(incidence)
library(earlyR)
tic("Time to complete")
source_files <- c("_icm.mod.init.seiqhrf.R", "_icm.mod.status.seiqhrf.R",
"_icm.mod.vital.seiqhrf.R", "_icm.control.seiqhrf.R", "_icm.utils.seiqhrf.R",
"_icm.saveout.seiqhrf.R", "_icm.icm.seiqhrf.R")
src_path <- paste0("./_posts/2020-03-18-modelling-the-effects-of-public-health-",
"interventions-on-covid-19-transmission-part-2/")
gist_url <- "https://gist.github.com/timchurches/92073d0ea75cfbd387f91f7c6e624bd7"
local_source <- FALSE
for (source_file in source_files) {
if (local_source) {
source(paste(src_path, source_file, sep = ""))
} else {
source_gist(gist_url, filename = source_file)
}
}
# function to set-up and run the baseline simulations
simulate <- function(# control.icm params
type = "SEIQHRF",
nsteps = 366,
nsims = 8,
ncores = 4,
prog.rand = FALSE,
rec.rand = FALSE,
fat.rand = TRUE,
quar.rand = FALSE,
hosp.rand = FALSE,
disch.rand = TRUE,
infection.FUN = infection.seiqhrf.icm,
recovery.FUN = progress.seiqhrf.icm,
departures.FUN = departures.seiqhrf.icm,
arrivals.FUN = arrivals.icm,
get_prev.FUN = get_prev.seiqhrf.icm,
# init.icm params
s.num = 9997,
e.num=0,
i.num = 3,
q.num=0,
h.num=0,
r.num = 0,
f.num = 0,
# param.icm params
inf.prob.e = 0.02,
act.rate.e = 10,
inf.prob.i = 0.05,
act.rate.i = 10,
inf.prob.q = 0.02,
act.rate.q = 2.5,
quar.rate = 1/30,
hosp.rate = 1/100,
disch.rate = 1/15,
prog.rate = 1/10,
prog.dist.scale = 5,
prog.dist.shape = 1.5,
rec.rate = 1/20,
rec.dist.scale = 35,
rec.dist.shape = 1.5,
fat.rate.base = 1/50,
hosp.cap = 40,
fat.rate.overcap = 1/25,
fat.tcoeff = 0.5,
vital = TRUE,
a.rate = (10.5/365)/1000,
a.prop.e = 0.01,
a.prop.i = 0.001,
a.prop.q = 0.01,
ds.rate = (7/365)/1000,
de.rate = (7/365)/1000,
di.rate = (7/365)/1000,
dq.rate = (7/365)/1000,
dh.rate = (20/365)/1000,
dr.rate = (7/365)/1000,
out="mean"
) {
control <- control.icm(type = type,
nsteps = nsteps,
nsims = nsims,
ncores = ncores,
prog.rand = prog.rand,
rec.rand = rec.rand,
infection.FUN = infection.FUN,
recovery.FUN = recovery.FUN,
arrivals.FUN = arrivals.FUN,
departures.FUN = departures.FUN,
get_prev.FUN = get_prev.FUN)
init <- init.icm(s.num = s.num,
e.num = e.num,
i.num = i.num,
q.num = q.num,
h.num = h.num,
r.num = r.num,
f.num = f.num)
param <- param.icm(inf.prob.e = inf.prob.e,
act.rate.e = act.rate.e,
inf.prob.i = inf.prob.i,
act.rate.i = act.rate.i,
inf.prob.q = inf.prob.q,
act.rate.q = act.rate.q,
quar.rate = quar.rate,
hosp.rate = hosp.rate,
disch.rate = disch.rate,
prog.rate = prog.rate,
prog.dist.scale = prog.dist.scale,
prog.dist.shape = prog.dist.shape,
rec.rate = rec.rate,
rec.dist.scale = rec.dist.scale,
rec.dist.shape = rec.dist.shape,
fat.rate.base = fat.rate.base,
hosp.cap = hosp.cap,
fat.rate.overcap = fat.rate.overcap,
fat.tcoeff = fat.tcoeff,
vital = vital,
a.rate = a.rate,
a.prop.e = a.prop.e,
a.prop.i = a.prop.i,
a.prop.q = a.prop.q,
ds.rate = ds.rate,
de.rate = de.rate,
di.rate = di.rate,
dq.rate = dq.rate,
dh.rate = dh.rate,
dr.rate = dr.rate)
sim <- icm.seiqhrf(param, init, control)
sim_df <- as.data.frame(sim, out=out)
return(list(sim=sim, df=sim_df))
}
baseline_sim <- simulate(ncores = 4)