Fetches the code to generate results seen in the app
Arguments
- state
NCA state from
NCA_fetch_state()
Examples
library(ruminate)
# Module IDs
id = "NCA"
id_UD = "UD"
id_DW = "DW"
id_ASM = "ASM"
# We need session and input variables to be define
sess_res = NCA_test_mksession()
#> → 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: module isgood: TRUE
#> → UD: including file
#> → UD: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → UD: dest: file.path("config","report.docx")
#> → UD: including file
#> → UD: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → UD: dest: file.path("config","report.pptx")
#> → UD: including file
#> → UD: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → UD: dest: file.path("config","report.yaml")
#> → UD: State initialized
#> → UD: module checksum updated:897d952fecbc804999396a96f9df4b20
#> → UD: module isgood: TRUE
#> → DW: including file
#> → DW: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → DW: dest: file.path("config","report.docx")
#> → DW: including file
#> → DW: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → DW: dest: file.path("config","report.pptx")
#> → DW: including file
#> → DW: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → DW: dest: file.path("config","report.yaml")
#> → DW: State initialized
#> → DW: module checksum updated:5b0f0b05ee3ac7336a74c564bb6efdad
#> → DW: loading data view idx: 1
#> → DW: setting name: Observations
#> → DW: module checksum updated:1ac3e0afcc601f848943f92b854b3830
#> → DW: -> filter
#> → DW: module checksum updated:67aff6e926eba73b3ecb361d26624844
#> → DW: -> filter
#> → DW: module checksum updated:0234f6d458ef7487a3b2e991b2d0957b
#> → DW: -> mutate
#> → DW: module checksum updated:37d0958f042076b974fdd3f894157822
#> → DW: loading data view idx: 2
#> → DW: setting name: PK 3mg SD IV
#> → DW: module checksum updated:4e7ca05728d66df3adfcf87387f9543a
#> → DW: -> filter
#> → DW: module checksum updated:2d95bc56262f46b7f135dd33fc4722b3
#> → DW: -> filter
#> → DW: module checksum updated:b8a30837145926d2d9cc6f788c10b7ed
#> → DW: -> filter
#> → DW: module checksum updated:24b554ee8736ebc84979c896ac2e93c3
#> → DW: -> filter
#> → DW: module checksum updated:daad88263faf7cbf90871ed00a0dd275
#> → DW: loading data view idx: 3
#> → DW: setting name: PK 3mg SD IV (NCA)
#> → DW: module checksum updated:a7b3ea35cdba272682716aa4619d3983
#> → DW: -> filter
#> → DW: module checksum updated:e8d2f77c0bd731995d845ee8be623e22
#> → DW: -> filter
#> → DW: module checksum updated:24cc7b591ca756a0abf560fb5295e04d
#> → DW: -> filter
#> → DW: module checksum updated:f79ef26bdb4dac420c24650b9e96f721
#> → DW: loading data view idx: 4
#> → DW: setting name: PKPD 3mg SD IV (NCA)
#> → DW: module checksum updated:c737e8b3a28ba600a83ddf58a969c90a
#> → DW: -> filter
#> → DW: module checksum updated:4c0d054f8ec47ae97fd1c650d8ddad55
#> → DW: -> filter
#> → DW: module checksum updated:1e3d65ec1bd6ee5850d67bd2250e3223
#> → DW: -> filter
#> → DW: module checksum updated:1e3d65ec1bd6ee5850d67bd2250e3223
#> → DW: module isgood: TRUE
#> → NCA: including file
#> → NCA: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → NCA: dest: file.path("config","report.docx")
#> → NCA: including file
#> → NCA: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → NCA: dest: file.path("config","report.pptx")
#> → NCA: including file
#> → NCA: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → NCA: dest: file.path("config","report.yaml")
#> ✖ NCA: Parameter specified in YAML is not a valid PKNCA parameter: sparse_se
#> ✖ NCA: Parameter specified in YAML is not a valid PKNCA parameter: sparse_df
#> → NCA: including file
#> → NCA: source: file.path(system.file(package="onbrand"), "templates", "report.docx")
#> → NCA: dest: file.path("config","report.docx")
#> → NCA: including file
#> → NCA: source: file.path(system.file(package="onbrand"), "templates", "report.pptx")
#> → NCA: dest: file.path("config","report.pptx")
#> → NCA: including file
#> → NCA: source: file.path(system.file(package="onbrand"), "templates", "report.yaml")
#> → NCA: dest: file.path("config","report.yaml")
#> → NCA: State initialized
#> → NCA: State initialized
#> → NCA: loading element idx: 1
#> → NCA: -> setting name: PK Example
#> → NCA: -> notes found and set
#> → NCA: -> setting data source: DW_myDS_3
#> → NCA: NCA_add_int: append
#> → NCA: NCA_add_int: append
#> → NCA: added element idx: 1
#> → NCA: loading element idx: 2
#> → NCA: -> setting name: PK/PD Example
#> → NCA: -> notes found and set
#> → NCA: -> setting data source: DW_myDS_4
#> → NCA: NCA_add_int: append
#> → NCA: NCA_add_int: append
#> → NCA: added element idx: 2
#> → NCA: module isgood: TRUE
# Extracting the session and input variables
session = sess_res$session
input = sess_res$input
react_state = list()
# We also need configuration files
FM_yaml_file = system.file(package = "formods", "templates", "formods.yaml")
MOD_yaml_file = system.file(package = "ruminate", "templates", "NCA.yaml")
# Getting the current module state
state = NCA_fetch_state(id = id,
input = input,
session = session,
FM_yaml_file = FM_yaml_file,
MOD_yaml_file = MOD_yaml_file,
id_ASM = id_ASM,
id_UD = id_UD,
id_DW = id_DW,
react_state = react_state)
# Pulls out the active analysis
current_ana = NCA_fetch_current_ana(state)
# This will get the dataset associated with this analysis
ds = NCA_fetch_ana_ds(state, current_ana)
# After making changes you can update those in the state
state = NCA_set_current_ana(state, current_ana)
# You can use this to check the current analysis
current_ana = NCA_process_current_ana(state)
# This will pull out the code for the module
fc_res = NCA_fetch_code(state)
# This will use patterns defined for the site to detect
# columns. In this example we are detecting the id column:
id_col = NCA_find_col(
patterns = state[["MC"]][["detect_col"]][["id"]],
dscols = names(ds$DS))
#> Warning: Unknown or uninitialised column: `DS`.
# This creates a new analysis
state = NCA_new_ana(state)