expand states and values to include
expand_stateval_testing(
x,
method = c("eigvec", "untested", "spread"),
params = NULL,
add_accum = TRUE
)state vector
method for distributing values across new (expanded) states
parameters
add N and P (neg/pos test) accumulator categories?
Other classic_macpan:
add_d_log(),
add_updated_vaxrate(),
aggregate_agecats(),
calibrate_comb(),
calibrate(),
check_age_cat_compatibility(),
check_contact_rate_setting(),
col_multiply(),
condense_age(),
condense_params_vax(),
condense_state(),
condense_vax(),
dev_is_tikz(),
do_step(),
expand_params_age(),
expand_params_desc_age(),
expand_params_desc_variant(),
expand_params_desc_vax(),
expand_params_mistry(),
expand_params_variant(),
expand_params_vax(),
expand_state_age(),
expand_state_vax(),
fix_pars(),
fix_stored(),
forecast_ensemble(),
forecast_sim(),
getData(),
get_GI_moments(),
get_Gbar(),
get_R0(),
get_doses_per_day(),
get_evec(),
get_kernel_moments(),
get_opt_pars(),
get_r(),
invlink_trans(),
make_betavec(),
make_beta(),
make_jac(),
make_ratemat(),
make_state(),
make_test_wtsvec(),
make_vaxrate(),
mk_Nvec(),
mk_agecats(),
mk_contact_rate_setting(),
mk_mistry_Nvec(),
mk_pmat(),
mk_vaxcats(),
mle_fun(),
non_expanded_states,
rExp(),
read_params(),
repair_names_age(),
restore(),
run_sim_ageify(),
run_sim_break(),
run_sim_loglin(),
run_sim_mobility(),
run_sim_range(),
run_sim(),
show_ratemat(),
testify(),
texify(),
trans_state_vars(),
update_contact_rate_setting(),
update_foi(),
update_params_mistry(),
vis_model(),
write_params()
pp <- read_params("PHAC_testify.csv")
s <- make_state(params=pp)
#> Warning: CHECK: may not be working properly for testify?
expand_stateval_testing(s, params=pp)
#> already testified, skipping
#> S_u S_p S_n S_t E_u E_p E_n E_t Ia_u Ia_p Ia_n
#> 999196 0 799 0 3 0 0 0 1 0 0
#> Ia_t Ip_u Ip_p Ip_n Ip_t Im_u Im_p Im_n Im_t Is_u Is_p
#> 0 0 0 0 0 1 0 0 0 0 0
#> Is_n Is_t H_u H_p H_n H_t H2_u H2_p H2_n H2_t ICUs_u
#> 0 0 0 0 0 0 0 0 0 0 0
#> ICUs_p ICUs_n ICUs_t ICUd_u ICUd_p ICUd_n ICUd_t R_u R_p R_n R_t
#> 0 0 0 0 0 0 0 0 0 0 0
#> D X V N P
#> 0 0 0 0 0
#> attr(,"epi_cat")
#> [1] "S" "E" "Ia" "Ip" "Im" "Is" "H" "H2" "ICUs" "ICUd"
#> [11] "D" "R" "X" "V"
#> attr(,"class")
#> [1] "state_pansim"
expand_stateval_testing(s, method="untested")
#> already testified, skipping
#> S_u S_p S_n S_t E_u E_p E_n E_t Ia_u Ia_p Ia_n
#> 999196 0 799 0 3 0 0 0 1 0 0
#> Ia_t Ip_u Ip_p Ip_n Ip_t Im_u Im_p Im_n Im_t Is_u Is_p
#> 0 0 0 0 0 1 0 0 0 0 0
#> Is_n Is_t H_u H_p H_n H_t H2_u H2_p H2_n H2_t ICUs_u
#> 0 0 0 0 0 0 0 0 0 0 0
#> ICUs_p ICUs_n ICUs_t ICUd_u ICUd_p ICUd_n ICUd_t R_u R_p R_n R_t
#> 0 0 0 0 0 0 0 0 0 0 0
#> D X V N P
#> 0 0 0 0 0
#> attr(,"epi_cat")
#> [1] "S" "E" "Ia" "Ip" "Im" "Is" "H" "H2" "ICUs" "ICUd"
#> [11] "D" "R" "X" "V"
#> attr(,"class")
#> [1] "state_pansim"