Appends a new empty cohort to the CTS state object and makes this new cohort the active cohort.
Arguments
- state
CTS state from
CTS_fetch_state()
Value
CTS state object containing a new cohort and that
cohort is set as the current active cohort. See the help for
CTS_fetch_state() for ===ELEMENT== format.
Examples
# For more information see the Clinical Trial Simulation vignette:
# https://ruminate.ubiquity.tools/articles/clinical_trial_simulation.html
# None of this will work if rxode2 isn't installed:
# \donttest{
library(formods)
if( Sys.getenv("ruminate_rxfamily_found") == "TRUE"){
# This will populate the session variable with the model building (MB) module
sess_res = MB_test_mksession()
session = sess_res[["session"]]
id = "CTS"
id_ASM = "ASM"
id_MB = "MB"
input = list()
# Configuration files
FM_yaml_file = system.file(package = "formods", "templates", "formods.yaml")
MOD_yaml_file = system.file(package = "ruminate", "templates", "CTS.yaml")
state = CTS_fetch_state(id = id,
id_ASM = id_ASM,
id_MB = id_MB,
input = input,
session = session,
FM_yaml_file = FM_yaml_file,
MOD_yaml_file = MOD_yaml_file,
react_state = NULL)
# Fetch a list of the current element
current_ele = CTS_fetch_current_element(state)
# You can modify the element
current_ele[["element_name"]] = "A more descriptive name"
# Defining the source model
state[["CTS"]][["ui"]][["source_model"]] = "MB_obj_1_rx"
current_ele = CTS_change_source_model(state, current_ele)
# Single visit
current_ele[["ui"]][["visit_times"]] = "0"
current_ele[["ui"]][["cts_config_nsteps"]] = "5"
# Creating a dosing rule
state[["CTS"]][["ui"]][["rule_condition"]] = "time == 0"
state[["CTS"]][["ui"]][["rule_type"]] = "dose"
state[["CTS"]][["ui"]][["action_dosing_state"]] = "central"
state[["CTS"]][["ui"]][["action_dosing_values"]] = "c(1)"
state[["CTS"]][["ui"]][["action_dosing_times"]] = "c(0)"
state[["CTS"]][["ui"]][["action_dosing_durations"]] = "c(0)"
state[["CTS"]][["ui"]][["rule_name"]] = "Single_Dose"
# Adding the rule:
current_ele = CTS_add_rule(state, current_ele)
# Appending the plotting details as well
current_ele[["ui"]][["fpage"]] = "1"
current_ele[["ui"]][["dvcols"]] = "Cc"
# Reducing the number of subjects and steps to speed things up on CRAN
current_ele[["ui"]][["nsub"]] = "2"
current_ele[["ui"]][["cts_config_nsteps"]] = "5"
# Putting the element back in the state forcing code generation
state = CTS_set_current_element(
state = state,
element = current_ele)
# Now we pull out the current element, and simulate it
current_ele = CTS_fetch_current_element(state)
#current_ele = CTS_simulate_element(state, current_ele)
# Next we plot the element
current_ele = CTS_plot_element(state, current_ele)
# Now we save those results back into the state:
state = CTS_set_current_element(
state = state,
element = current_ele)
# This will extract the code for the current module
code = CTS_fetch_code(state)
code
# This will update the checksum of the module state
state = CTS_update_checksum(state)
# Access the datasets generated from simulations
ds = CTS_fetch_ds(state)
# CTS_add_covariate
state[["CTS"]][["ui"]][["covariate_value"]] = "70, .1"
state[["CTS"]][["ui"]][["covariate_type_selected"]] = "cont_lognormal"
state[["CTS"]][["ui"]][["selected_covariate"]] = "WT"
current_ele = CTS_add_covariate(state, current_ele)
# Creates a new empty element
state = CTS_new_element(state)
# Delete the current element
state = CTS_del_current_element(state)
}
#> → ASM: including file
#> → ASM: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → ASM: dest: file.path("config","report.docx")
#> → ASM: including file
#> → ASM: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → ASM: dest: file.path("config","report.pptx")
#> → ASM: including file
#> → ASM: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → ASM: dest: file.path("config","report.yaml")
#> → ASM: State initialized
#> → ASM: setting word placeholders:
#> → ASM: -> setting docx ph: HEADERLEFT = left header
#> → ASM: -> setting docx ph: HEADERRIGHT = right header
#> → ASM: -> setting docx ph: FOOTERLEFT = left footer
#> → ASM: module isgood: TRUE
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → MB: dest: file.path("config","report.docx")
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → MB: dest: file.path("config","report.pptx")
#> → MB: including file
#> → MB: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → MB: dest: file.path("config","report.yaml")
#> ! MB: User-defined model: /Users/jmh/projects/ruminate/github/ruminate/docs/reference/user_model.R not found (skipping)
#> ! MB: User-defined model: /Users/jmh/projects/ruminate/github/ruminate/docs/reference/user_model.ctl not found (skipping)
#> → MB: module checksum updated:f7de2055542d3ff1b085fafc2d30a1f8
#> → MB: State initialized
#> → MB: loading model idx: 1
#>
#>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → MB: model checksum updated: 356adbad3e99169aaba00aaff95b2f48
#> → MB: module checksum updated:8cba155181ff9a3b5583276f6e335aee
#>
#>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → MB: model checksum updated: 30f867afc2dc4dac7ec1c947705c65d2
#> → MB: module checksum updated:e5684358eda4614020f57c89fcea6743
#> → MB: -> setting name: One compartment model
#> → MB: -> setting time scale: hours
#> → MB: -> setting base from: user
#> → MB: -> setting catalog selection:
#> → MB: -> setting base model id: manual
#> → MB: -> setting base model name: manual
#> → MB: model checksum updated: 99e85c2692aa4568c77d1c7b4e9f1e00
#> → MB: module checksum updated:68171d09207703be13f58820e735abc7
#> → MB: added element idx: 1
#> → MB: loading model idx: 2
#>
#>
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → MB: model checksum updated: 83cc6f4b6685a13ba75b9a254d094177
#> → MB: module checksum updated:0d7180b93d24bcf17f50fe719c8d74d5
#> → MB: -> setting name: PK Biomarker
#> → MB: -> setting time scale: days
#> → MB: -> setting base from: user
#> → MB: -> setting catalog selection:
#> → MB: -> setting base model id: manual
#> → MB: -> setting base model name: manual
#> → MB: model checksum updated: d489021cdc4044b6c6883b9b956f3c91
#> → MB: module checksum updated:8bed779770ca9296ef4a2dd64a813bd3
#> → MB: added element idx: 2
#> → MB: module isgood: TRUE
#> → CTS: including file
#> → CTS: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → CTS: dest: file.path("config","report.docx")
#> → CTS: including file
#> → CTS: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → CTS: dest: file.path("config","report.pptx")
#> → CTS: including file
#> → CTS: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → CTS: dest: file.path("config","report.yaml")
#> → CTS: source model change detected
#> → CTS: > covariates reset
#> → CTS: cohort checksum updated: fcf9410fd3c1c077da2e74e9e0a07045
#> → CTS: module checksum updated: 3b67defe76aebf4bd5c02b46d7fc57cf
#> → CTS: State initialized
#> → CTS: add rule success
#> → CTS: rule added
#> → CTS: cohort checksum updated: cf4297378856448df8be3a0d29be7278
#> → CTS: module checksum updated: febe9fb07ca1f2409fc063e95f00e43f
#> → CTS: CTS_plot_element()
#> → CTS: # Plotting timecourse
#> → CTS: CTS_obj_1_fgtc =
#> → CTS: plot_sr_tc(sro = CTS_obj_1_simres,
#> → CTS: xcol = "time",
#> → CTS: xlab_str = "Time",
#> → CTS: fncol = 4,
#> → CTS: fnrow = 2,
#> → CTS: dvcols = "Cc",
#> → CTS: fpage = 1)
#> → CTS:
#> → CTS: # Plotting events
#> → CTS: CTS_obj_1_fgev =
#> → CTS: plot_sr_ev(sro = CTS_obj_1_simres,
#> → CTS: xcol = "time",
#> → CTS: xlab_str = "Time",
#> → CTS: fncol = 4,
#> → CTS: fnrow = 2,
#> → CTS: evplot = 1,
#> → CTS: fpage = 1)
#> → CTS: No simulation available, you need to run the simulation first.
#> → CTS: cohort checksum updated: 6e5ca8819ecd18db134d1d5d83b79040
#> → CTS: module checksum updated: bfa7c135ddad0e4191d836c4a850fa3e
#> → CTS: source model change detected
#> → CTS: > covariates reset
#> → CTS: cohort checksum updated: 822f5bb40f42d783512400c4ec3c41bf
#> → CTS: module checksum updated: 952574a668fcdbac1fd7f6c60f64ee52
# }