xde_scaling_eir

xde_scalling_eir  function:
A change of terms<- model$outputs$orbits$terms[[1]] changed to model$outputs$orbits$terms

R/scaling.R

@@ -18,7 +18,7 @@ xde_scaling_eir = function(model, N=25){
     model$EIRpar$eir <- aEIR[i]/365
     model <- ramp.xds::xds_solve_cohort(model, A=10, da=1)
     XH <- model$outputs$orbits$XH[[1]]
-    terms <- model$outputs$orbits$terms[[1]]
+    terms <- model$outputs$orbits$terms
     pr_t = tail(XH$true_pr, 365); pr[i] = mean(pr_t)
     ni_t = tail(XH$ni, 365);  ni[i]= mean(ni_t)
     eir_t = tail(terms$EIR, 365); eir[i] = mean(eir_t)

vignettes/Scaling.R

@@ -1,11 +1,10 @@
 ## -----------------------------------------------------------------------------
 library(ramp.xds)
-library(deSolve)
-library(rootSolve)
 library(ramp.work)
+library(deSolve)
 
 ## ----echo=F-------------------------------------------------------------------
-devtools::load_all()
+#devtools::load_all()
 
 ## ----Fsin---------------------------------------------------------------------
 tt <- seq(0, 730, by=5) 
@@ -51,54 +50,3 @@ plot_eirpr(sis)
 with(sis$outputs$eirpr, points(aeir, pr, pch = 15))
 with(preir_i, points(365*eir, pr, pch = 19, col = "red"))
 
-## -----------------------------------------------------------------------------
-sis0 <- xds_setup_cohort(Xname = "SIS", F_season = Fsin)
-xde_scaling_eir(sis0, 25) -> sis0
-
-## -----------------------------------------------------------------------------
-clrs = turbo(25)
-with(sis$outputs$eirpr, plot(aeir, pr, type = "l", log = "x", xaxt= "n", xlab = "aEIR", ylab = "PR"))
-axis(1, 10^(-1:3), c(0.1, 1, 10, 100, 1000))
-lines(sis$outputs$eirpr$aeir, sis0$outputs$eirpr$pr, col = "tomato", lwd=2) 
-
-with(sis0$outputs$eirpr, points(aeir, pr, col = clrs))
-with(sis0$outputs$eirpr, lines(scaling[[5]]$aeir, scaling[[5]]$pr, col = clrs[5]))
-with(sis0$outputs$eirpr, lines(scaling[[10]]$aeir, scaling[[10]]$pr, col = clrs[10]))
-with(sis0$outputs$eirpr, lines(scaling[[15]]$aeir, scaling[[15]]$pr, col = clrs[15]))
-with(sis0$outputs$eirpr, lines(scaling[[20]]$aeir, scaling[[20]]$pr, col = clrs[20]))
-
-## ----eval=F-------------------------------------------------------------------
-#  sip = xds_setup_cohort(Xname = "SIP", F_season=Fsin)
-#  sip$Xpar[[1]]$eta = 1/40
-#  xde_scaling_eir(sip, 25) -> sip
-
-## ----eval=F-------------------------------------------------------------------
-#  sip1 = setup_exposure_nb(sip, 1/50)
-#  xde_scaling_eir(sip1, 25) -> sip1
-
-## ----eval=F-------------------------------------------------------------------
-#  with(sis$outputs$eirpr, plot(aeir, pr, type = "l", log = "x", xaxt= "n", xlab = "aEIR", ylab = "PR"))
-#  axis(1, 10^(-1:3), c(0.1, 1, 10, 100, 1000))
-#  with(sip$outputs$eirpr, lines(aeir, pr, col = "darkorange"))
-#  with(sip1$outputs$eirpr, lines(aeir, pr, col = "brown"))
-
-## -----------------------------------------------------------------------------
-sis4 <- setup_exposure_nb(sis, 1/50)
-xde_scaling_eir(sis4, 25) -> sis4
-
-## -----------------------------------------------------------------------------
-with(sis$outputs$eirpr, plot(aeir, pr, type = "l", log = "x", xaxt= "n", xlab = "aEIR", ylab = "PR"))
-axis(1, 10^(-1:3), c(0.1, 1, 10, 100, 1000))
-#with(sis2$outputs$eir, lines(aeir, pr, col = "blue"))
-#with(sis3$outputs$eir, lines(aeir, pr, col = "purple"))
-with(sis4$outputs$eir, lines(aeir, pr, col = "darkblue"))
-
-## -----------------------------------------------------------------------------
-sis5 <- setup_travel_static(sis, delta = 1/5/365)
-xde_scaling_eir(sis5, 25) -> sis5
-
-## -----------------------------------------------------------------------------
-with(sis$outputs$eirpr, plot(aeir, pr, type = "l", log = "x", xaxt= "n", xlab = "aEIR", ylab = "PR"))
-axis(1, 10^(-1:3), c(0.1, 1, 10, 100, 1000))
-with(sis5$outputs$eir, lines(aeir, pr, col = "darkgreen")) 
-