From f2a169d36e551fe86c44596ee17069faf5777e92 Mon Sep 17 00:00:00 2001
From: thierrychambert <thierry.chambert@gmail.com>
Date: Thu, 12 Aug 2021 13:41:04 +0200
Subject: [PATCH] minor corrections on simul functions
---
R/models.R | 12 ++++++------
man/run_simul.Rd | 6 +++---
man/run_simul_shiny.Rd | 4 ++--
run_analysis.R | 23 +++++------------------
4 files changed, 16 insertions(+), 29 deletions(-)
diff --git a/R/models.R b/R/models.R
index 744b7c3..66b1b34 100644
--- a/R/models.R
+++ b/R/models.R
@@ -133,9 +133,9 @@ M3_WithDD_noDemoStoch <- function(N1, s, f, h, DD_params){
## M3_WithDD_noDemoStoch
# Extract DD parameters from list
- rMAX = DD_params$rMAX
- K = DD_params$K
- theta = DD_params$theta
+ rMAX <- DD_params$rMAX
+ K <- DD_params$K
+ theta <- DD_params$theta
# Apply density dependence effect
lam_Nt <- 1 + rMAX*(1-(sum(N1)/K)^theta)
@@ -208,9 +208,9 @@ M4_WithDD_WithDemoStoch <- function(N1, s, f, h, DD_params){
## M4_WithDD_WithDemoStoch
# Extract DD parameters from list
- rMAX = DD_params$rMAX
- K = DD_params$K
- theta = DD_params$theta
+ rMAX <- DD_params$rMAX
+ K <- DD_params$K
+ theta <- DD_params$theta
# Apply density dependence effect
lam_Nt <- 1 + rMAX*(1-(sum(N1)/K)^theta)
diff --git a/man/run_simul.Rd b/man/run_simul.Rd
index e320bff..afb0db7 100644
--- a/man/run_simul.Rd
+++ b/man/run_simul.Rd
@@ -6,7 +6,7 @@
\usage{
run_simul(
nsim,
- cumuated_impacts,
+ cumulated_impacts,
fatalities_mean,
fatalities_se,
onset_time,
@@ -29,7 +29,7 @@ run_simul(
\arguments{
\item{nsim}{number of simulation}
-\item{cumuated_impacts}{Logical. If TRUE, we used the projection model for cumulated impacts.}
+\item{cumulated_impacts}{Logical. If TRUE, we used the projection model for cumulated impacts.}
\item{fatalities_mean}{a vector (numeric). Average number of fatalities, for each scenario.}
@@ -111,7 +111,7 @@ carrying_capacity = 1200
theta = 1
rMAX_species <- 0.15
-run_simul(nsim = 10, cumuated_impacts = FALSE,
+run_simul(nsim = 10, cumulated_impacts = FALSE,
fatalities_mean, fatalities_se, onset_time = NULL,
pop_size_mean, pop_size_se, pop_size_type,
pop_growth_mean, pop_growth_se,
diff --git a/man/run_simul_shiny.Rd b/man/run_simul_shiny.Rd
index 1e8bc33..37a56f7 100644
--- a/man/run_simul_shiny.Rd
+++ b/man/run_simul_shiny.Rd
@@ -8,7 +8,7 @@ the simulation progress bar in Shiny (incProgress function)}
\usage{
run_simul_shiny(
nsim,
- cumuated_impacts,
+ cumulated_impacts,
fatalities_mean,
fatalities_se,
onset_time,
@@ -31,7 +31,7 @@ run_simul_shiny(
\arguments{
\item{nsim}{number of simulation}
-\item{cumuated_impacts}{Logical. If TRUE, we used the projection model for cumulated impacts.}
+\item{cumulated_impacts}{Logical. If TRUE, we used the projection model for cumulated impacts.}
\item{fatalities_mean}{a vector (numeric). Average number of fatalities, for each scenario.}
diff --git a/run_analysis.R b/run_analysis.R
index ee7136d..e24bb75 100644
--- a/run_analysis.R
+++ b/run_analysis.R
@@ -1,6 +1,6 @@
rm(list = ls(all.names = TRUE))
graphics.off()
-
+library(popbio)
## Libraries
library(eolpop)
@@ -14,7 +14,7 @@ fatalities_se = c(0, 0.05, 0.05, 0.05)
pop_size_mean = 200
pop_size_se = 25
-pop_growth_mean = 1
+pop_growth_mean = 1.1
pop_growth_se = 0
survivals <- c(0.5, 0.7, 0.8, 0.95)
@@ -23,8 +23,8 @@ fecundities <- c(0, 0, 0.05, 0.55)
model_demo = NULL # M2_noDD_WithDemoStoch #M1_noDD_noDemoStoch #M4_WithDD_WithDemoStoch #M3_WithDD_noDemoStoch #
time_horzion = 50
coeff_var_environ = 0.10
-fatal_constant = "M"
-pop_size_type = "Npair"
+fatal_constant = "h"
+pop_size_type = "Ntotal"
cumulated_impacts = TRUE
@@ -60,7 +60,7 @@ vr_calibrated <- calibrate_params(inits = inits, f = fecundities, s = survivals,
s_calibrated <- head(vr_calibrated, length(survivals))
f_calibrated <- tail(vr_calibrated, length(fecundities))
-build_Leslie(s = s_calibrated, f = f_calibrated) %>% lambda
+lambda( build_Leslie(s = s_calibrated, f = f_calibrated) )
@@ -84,16 +84,3 @@ names(run0)
N <- run0$N ; dim(N)
plot_traj(N, xlab = "Annee", ylab = "Taille de population (totale)")
abline(h = K)
-
-colSums(N[,,,]) %>% max
-
-plot_impact(N, onset_year = onset_year , xlab = "Annee", ylab = "Impact relatif")
-
-
-N <- run0$N
-output <- get_metrics(N, cumuated_impacts = cumulated_impacts)
-output$scenario$Pext
-
-#plot_impact(N = N, xlab = "year", ylab = "pop size")
-#source("draws_histog.R")
-#draws_histog(draws = run0$lambdas, mu = pop_growth_mean, se = pop_growth_se)
--
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