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"