Nothing
#clearing the workspace
rm(list=ls())
graphics.off()
options(show.error.locations = TRUE)
# If we are in a stand alone ubiquity distribution we run
# from there otherwise we try to load the package
if(file.exists(file.path('library', 'r_general', 'ubiquity.R'))){
source(file.path('library', 'r_general', 'ubiquity.R'))
} else {
library(ubiquity) }
# flowctl = 'previous estimate as guess';
# flowctl = 'plot guess';
# flowctl = 'plot previous estimate';
flowctl = 'estimate';
archive_results = TRUE
analysis_name = 'parent_metabolite_nm_data';
# For documentation explaining how to modify the commands below
# See the "R Workflow" section at the link below:
# http://presentation.ubiquity.grok.tv
# Rebuilding the system (R scripts and compiling C code)
cfg = build_system(output_directory = file.path(".", "output"),
temporary_directory = file.path(".", "transient"))
# set name | Description
# -------------------------------------------------------
# default | Original Estimates
# The following will estimate a subset of the parameters:
pnames = c('Vp',
'Vt',
'CLp',
'Q',
'slope_parent',
'slope_metabolite');
cfg = system_select_set(cfg, "default", pnames)
# Specify the output times used for smooth profiles
cfg=system_set_option(cfg, group = "simulation",
option = "output_times",
linspace(0,50,100))
# Loading Datasets
#
cfg = system_load_data(cfg, dsname = "nm_pm_data",
data_file = "nm_data.csv")
# Defining the cohorts
#
# Clearing all of the cohorts
cfg = system_clear_cohorts(cfg);
# Only including the 10 and 30 mpk doses
filter = list()
filter$DOSE = c(10, 30)
# Mapping information:
OBSMAP = list()
OBSMAP$PT = list(variance = 'slope_parent*PRED^2',
CMT = 1,
output = 'Cpblood',
missing = -1 )
OBSMAP$MT = list(variance = 'slope_metabolite*PRED^2',
CMT = 2,
output = 'Cmblood',
missing = -1 )
INPUTMAP = list()
INPUTMAP$bolus$Mpb$CMT_NUM = 1
cfg = system_define_cohorts_nm(cfg,
DS = 'nm_pm_data',
col_ID = 'ID',
col_CMT = 'CMT',
col_DV = 'DV',
col_TIME = 'TIME',
col_AMT = 'AMT',
col_RATE = 'RATE',
col_EVID = 'EVID',
col_GROUP= 'DOSE',
filter = filter,
INPUTS = INPUTMAP,
OBS = OBSMAP)
# #----------------------------------------------------------
# # performing estimation or loading guess/previous results
pest = system_estimate_parameters(cfg,
flowctl = flowctl,
analysis_name = analysis_name,
archive_results = archive_results)
# Simulating the system at the estimates
erp = system_simulate_estimation_results(pest = pest, cfg = cfg)
plot_opts = c()
plot_opts$outputs$MT$yscale = 'log'
plot_opts$outputs$MT$ylabel = 'Metabolite'
#plot_opts$outputs$MT$ylim = c(1, 100)
plot_opts$outputs$MT$xlabel = 'Time (hours)'
plot_opts$outputs$PT$yscale = 'log'
plot_opts$outputs$PT$ylabel = 'Parent'
plot_opts$outputs$PT$xlabel = 'Time (hours)'
# Plotting the simulated results at the estimates
# These figures will be placed in output/
system_plot_cohorts(erp, plot_opts, cfg, analysis_name=analysis_name)
#-------------------------------------------------------
# Writing the results to a PowerPoint report
# cfg = system_rpt_read_template(cfg, template="PowerPoint")
# cfg = system_rpt_estimation(cfg=cfg, analysis_name=analysis_name)
# system_rpt_save_report(cfg=cfg, output_file=file.path("output",paste(analysis_name, "-report.pptx", sep="")))
#-------------------------------------------------------
# Writing the results to a Word report
# cfg = system_rpt_read_template(cfg, template="Word")
# cfg = system_rpt_estimation(cfg=cfg, analysis_name=analysis_name)
# system_rpt_save_report(cfg=cfg, output_file=file.path("output",paste(analysis_name, "-report.docx", sep="")))
#-------------------------------------------------------
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