transfer from old repo

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Andreas Gammelgaard Damsbo 2026-08-19 09:27:27 +02:00
commit 277e2b8cf3
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# Sample data set is generated with rownames and colnames
ds <- do.call(cbind,lapply(1:133,function(i){
sample(c(1,2,3,4,5,rep(NA,12)),size=17)
}))
rownames(ds) <- letters[seq_len(nrow(ds))]
colnames(ds) <- paste0("sub",seq_len(ncol(ds)))
# df[as.character(as.matrix(ds))==0] <- 17
# Clearing NAs and applying the max cost instead
# ds[is.na(ds)] <- 17
# I believe this would actually be the organic data set
df <- data.frame("ID"=colnames(ds),t(ds))
openxlsx::write.xlsx(df,"assign_sample.xlsx")
write.csv(df,"assign_sample.csv",na = "",row.names = FALSE)
df[as.matrix(df)==0] <- 17
assigned <- df |>
group_assignment(cap_classes = rep(8, 17),excess_space = 1)
df |> group_assignment()
assigned$`Group assignment`
assigned$`Cost evaluation` |> assignment_plot(1:5)
pre_grouped <- data.frame("ID"=sample(df$ID,10),"group"=sample(1:17,10))
ds <- df
assigned <- df |>
group_assignment(excess_space = 1.05,
pre_assign = pre_grouped)
lengths(assigned[[1]])
#
# ds <- read.csv("assign_sample.csv")
#
# ls <- read.csv("assign_sample.csv") |> group_assignment(cap_classes = 8, excess_space = 1)
#
# ls |> assignment_plot()
#
# lst <- ls
#
# "[["(ls,4) |> head(10)
# View(ls$export)
#
# pre_grouped <- data.frame("ID"=sample(ds$ID,10),"group"=sample(1:17,10))
# write.csv(pre_grouped,"pre_grouped.csv",row.names = FALSE)
#
# assigned <- ds |>
# group_assignment(excess_space = 1.05,
# pre_assign = pre_grouped)
# ls <-
# read.csv("assign_sample.csv") |> group_assignment(
# cap_classes = 8,
# excess_space = 1,
# pre_assign = read.csv("pre_grouped.csv")
# )

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## IPTO import
library(readxl)
# Not possible to link to online file, and so the downloaded file is used.
dt<-read_xlsx("/Users/au301842/OneDrive/Research/PhD/Vejledning/IPTO_AGD.xlsx")
# To-dos
# - Export to calendar
# - Naming according to category
# - Dates and duration from file
# - Limit import to relevant rows/columns

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BEGIN:VCALENDAR
PRODID:ATFutures/calendar
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
SUMMARY:Neuro JC: Anne [Claus Simonsen]
DTSTART:20230117T090000
DTEND:20230117T100000
UID:ical-8975bd20-da0d-476e-ad8b-bc93c11992d2
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Camilla [Morten Stilund]
DTSTART:20230221T090000
DTEND:20230221T100000
UID:ical-6fcb55e3-9ebc-40dd-a59e-1c40d89f1ac7
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Andreas [Janne Mortensen]
DTSTART:20230321T090000
DTEND:20230321T100000
UID:ical-3748aed7-6f7a-4eba-8425-88a649ed6a01
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Mette [Claus Simonsen]
DTSTART:20230418T090000
DTEND:20230418T100000
UID:ical-95a5dd9d-60a5-46ee-a635-dd9ee79161e3
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Sigrid [Janne Mortensen]
DTSTART:20230523T090000
DTEND:20230523T100000
UID:ical-40881f9c-cd1b-4356-9915-557f8f89c405
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Anders [Henning Andersen]
DTSTART:20230613T090000
DTEND:20230613T100000
UID:ical-786215da-b996-4136-b6a0-81c17c8a0590
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Sine [Claus Simonsen]
DTSTART:20230815T090000
DTEND:20230815T100000
UID:ical-d97439f6-f519-4199-9ecb-11e45b7acc65
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Helga [Henning Andersen]
DTSTART:20230912T090000
DTEND:20230912T100000
UID:ical-71c1f62e-03e7-46b8-87ca-c915b80a56e1
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Thomas [Claus Simonsen]
DTSTART:20231003T090000
DTEND:20231003T100000
UID:ical-02cd6933-1db7-4be5-aa70-e1655733370e
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Marie [Claus Simonsen]
DTSTART:20231031T090000
DTEND:20231031T100000
UID:ical-9ea63131-b8d9-40a2-b2f6-c1a86721c81d
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Jesper [Henning Andersen]
DTSTART:20231121T090000
DTEND:20231121T100000
UID:ical-17bf89ac-dbd4-4d2e-8da8-e99963f740a1
END:VEVENT
BEGIN:VEVENT
SUMMARY:Neuro JC: Josefine [Henning Andersen]
DTSTART:20231219T090000
DTEND:20231219T100000
UID:ical-4a14e2ba-9fd3-4c90-b427-2d014aa5d6e7
END:VEVENT
END:VCALENDAR

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# NOTER
#
# .ics uploades til git, herefter muligt at abbonere.
source("/Users/au301842/stRoke/R/write_ical.R")
library(dplyr)
df <-
readODS::read_ods("./side projects/jc2023.ods")
output <- "./side projects/jc_cal.ics"
df |> mutate(
dato.clean = lubridate::dmy(paste0(
`Dato `, "/", format(Sys.Date(), format = "%Y")
)),
title = paste0("Neuro JC: ", `Ansvarlig `, " [", `Vejleder `, "]"),
start = "09:00:00",
end = "10:00:00",
place = "J119"
) |>
write_ical(date = "dato.clean") |>
calendar::ic_write(file = output)

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# ------------------------------------------------------------------------------
# Setup
# ------------------------------------------------------------------------------
token=names(suppressWarnings(read.csv("/Users/au301842/pss_redcap_token.csv",colClasses = "character")))
uri="https://redcap.au.dk/api/"
library(REDCapR)
library(gtsummary)
source("https://raw.githubusercontent.com/agdamsbo/daDoctoR/master/R/dob_extract_cpr_function.R")
library(lubridate)
# ------------------------------------------------------------------------------
# Data download
# ------------------------------------------------------------------------------
dta <- redcap_read_oneshot(
redcap_uri = uri,
token = token,
forms = "baggrund"
)$data
dta<-dta[!is.na(dta$debut),]
# ------------------------------------------------------------------------------
# Table 1
# ------------------------------------------------------------------------------
vars<-c("kon","age","nihss_acute","diagnosis","psg_performed","interview")
# Mangler tilpassede analyser til NIHSS
dta[dta$record_id %in% 12:26,] |>
tbl_summary(missing = "ifany",
include = all_of(vars),
missing_text="(Missing)"#,
#label = lab_sel(labels_all,tbl1_vars)
)|>
add_n()|>
as_gt() |>
# modify with gt functions
gt::tab_header("Baseline Characteristics") |>
gt::tab_options(
table.font.size = "small",
data_row.padding = gt::px(1))
skimr::skim(dta[dta$record_id %in% 12:26,]) |> gt::gt()

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## treatment_quality