## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 5 ) ## ----message=FALSE, warning=FALSE--------------------------------------------- library(IncidencePrevalence) library(visOmopResults) library(dplyr) library(ggplot2) library(stringr) cdm <- mockIncidencePrevalence( sampleSize = 100, earliestObservationStartDate = as.Date("2010-01-01"), latestObservationStartDate = as.Date("2010-01-01"), minDaysToObservationEnd = 364, maxDaysToObservationEnd = 364, outPre = 0.1 ) timings <- benchmarkIncidencePrevalence(cdm) timings |> glimpse() ## ----------------------------------------------------------------------------- visOmopTable(timings, hide = c( "variable_name", "variable_level", "strata_name", "strata_level" ), groupColumn = "task" ) ## ----------------------------------------------------------------------------- test_db <- IncidencePrevalenceBenchmarkResults |> filter(str_detect(cdm_name, "CPRD", negate = TRUE)) test_db |> glimpse() ## ----------------------------------------------------------------------------- visOmopTable(bind(timings, test_db), settingsColumn = "package_version", hide = c( "variable_name", "variable_level", "strata_name", "strata_level" ), groupColumn = "task" ) ## ----------------------------------------------------------------------------- real_db <- IncidencePrevalenceBenchmarkResults |> filter(str_detect(cdm_name, "CPRD")) visOmopTable(real_db, settingsColumn = "package_version", hide = c( "variable_name", "variable_level", "strata_name", "strata_level" ), groupColumn = "task" ) ## ----eval = FALSE------------------------------------------------------------- # library(CDMConnector) # library(IncidencePrevalence) # # cdm <- cdmFromCon("....") # timings <- benchmarkIncidencePrevalence(cdm) # exportSummarisedResult( # timings, # minCellCount = 5, # fileName = "results_{cdm_name}_{date}.csv", # path = getwd() # )