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Copy path_targets.R
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131 lines (97 loc) · 5.56 KB
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library("targets")
library("tarchetypes")
library("future")
library("future.callr")
plan(callr)
source("R/functions.R") # loads functions
# Set target-specific options such as packages.
tar_option_set(packages = c("dplyr", "data.table",
"ggplot2", "patchwork"))
# A List of target objects.
list(
#++++++++++++++++++++++++++++++++++++++
##### SIMULATION ######################
#++++++++++++++++++++++++++++++++++++++
# set simulation parameters when environment is shared among individuals
tar_target(s_param_TRUE, f_init_sim_param(X1_sto_shared=TRUE)),
# set simulation parameters when environment is not shared among individuals
tar_target(s_param_FALSE, f_init_sim_param(X1_sto_shared=FALSE)),
# simulate data with environment shared among individuals
tar_target(s_sim_TRUE, f_simulate_data(s_param_TRUE),
format="fst_dt",
resources = tar_resources(
fst = tar_resources_fst(compress = 100)
)),
# simulate data with environment not shared among individuals
tar_target(s_sim_FALSE, f_simulate_data(s_param_FALSE),
format="fst_dt",
resources = tar_resources(
fst = tar_resources_fst(compress = 100)
)),
####
# set simulation parameters when total duration is 1000 time steps
tar_target(s_param_large_NR, f_init_sim_param(Tmax=1000, NR=100, Nrep=1, VI=0.4, Vhsi=c(0, 0.4, 0.8), X1_sto_corr=c(0.8),
X1_lin_state=FALSE, X1_cyc_state=FALSE, X1_sto_shared=FALSE)),
# simulate data with total duration is 1000 time steps
tar_target(s_sim_large_NR, f_simulate_data(s_param_large_NR),
format="fst_dt",
resources = tar_resources(
fst = tar_resources_fst(compress = 100)
)),
#++++++++++++++++++++++++++++++++++++++
##### ANALYSIS ########################
#++++++++++++++++++++++++++++++++++++++
# fit models
tar_target(a_null, f_fit_lmer(rbind(s_sim_TRUE, s_sim_FALSE),
"null",
"Phenotype ~ 1 + (1|Individual)")),
##
tar_target(a_time_fix, f_fit_lmer(rbind(s_sim_TRUE, s_sim_FALSE),
"time_fix",
"Phenotype ~ 1 + Time + (1|Individual)")),
tar_target(a_time_ran, f_fit_lmer(rbind(s_sim_TRUE, s_sim_FALSE),
"time_ran",
"Phenotype ~ 1 + (1|Individual) + (1|Time)")),
tar_target(a_time_ind, f_fit_lmer(rbind(s_sim_TRUE, s_sim_FALSE),
"time_ind",
"Phenotype ~ 1 + (1|Individual) + (1|Time) + (1|Time:Individual)")),
##
tar_target(a_ar1, f_fit_glmmTMB(s_sim_TRUE,
"ar1",
"Phenotype ~ 1 + (1|Individual) + ar1(factor(Time)+0|Replicate)")),
tar_target(a_ar1_ind, f_fit_glmmTMB(s_sim_FALSE,
"ar1_ind",
"Phenotype ~ 1 + (1|Individual) + ar1(factor(Time)+0|Individual)")),
tar_target(a_ar1_ind_large_NR, f_fit_glmmTMB(s_sim_large_NR,
"ar1_ind",
"Phenotype ~ 1 + (1|Individual) + ar1(factor(Time)+0|Individual)")),
#++++++++++++++++++++++++++++++++++++++
##### RESULTS #########################
#++++++++++++++++++++++++++++++++++++++
tar_target(out_path, "./output"),
# make figures
tar_target(r_var_figs, f_variance_figs(data.table::rbindlist(list(a_null,
a_time_ran,
a_time_fix,
a_time_ind,
a_ar1,
a_ar1_ind),
fill=TRUE),
rbind(s_param_TRUE, s_param_FALSE),
out_path)),
tar_target(r_var_figs_all, f_variance_figs_all(data.table::rbindlist(list(a_null,
a_time_ran,
a_time_fix,
a_time_ind,
a_ar1,
a_ar1_ind),
fill=TRUE),
rbind(s_param_TRUE, s_param_FALSE),
out_path)),
tar_target(r_var_figs_alllarge_NR, f_variance_figs_all_large_NR(a_ar1_ind_large_NR,
s_param_large_NR,
out_path)),
tar_target(r_env_figs, f_environment_figs(out_path)),
tar_target(r_samp_figs, f_sampling_figs(out_path)),
tar_target(END, 0)
)