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Karl Pettersson klpn

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klpn / pandoclinkerr
Created July 4, 2015 11:14
Pandoc link errors on OpenBSD
Linking dist/build/pandoc/pandoc ...
/home/karl/.cabal/lib/x86_64-openbsd-ghc-7.8.4/hslua-0.3.13/libHShslua-0.3.13.a(loslib.o): In function `luaopen_os':
(.text+0x38): warning: warning: tmpnam() possibly used unsafely; consider using mkstemp()
/home/karl/.cabal/lib/x86_64-openbsd-ghc-7.8.4/hslua-0.3.13/libHShslua-0.3.13.a(lobject.o): In function `luaO_chunkid':
(.text+0x145): warning: warning: strcpy() is almost always misused, please use strlcpy()
/home/karl/.cabal/lib/x86_64-openbsd-ghc-7.8.4/hslua-0.3.13/libHShslua-0.3.13.a(lmathlib.o): In function `luaopen_math':
(.text+0x367): warning: warning: rand() may return deterministic values, is that what you want?
/home/karl/.cabal/lib/x86_64-openbsd-ghc-7.8.4/hslua-0.3.13/libHShslua-0.3.13.a(lobject.o): In function `luaO_chunkid':
(.text+0x157): warning: warning: strcat() is almost always misused, please use strlcat()
/home/karl/.cabal/lib/x86_64-openbsd-ghc-7.8.4/cryptohash-0.11.6/libHScryptohash-0.11.6.a(sha512.o): In function `sha512_init_t':
@klpn
klpn / statswe.json
Created November 23, 2015 22:26
JSON to Statistics Sweden
{
"response": {
"format": "json-stat"
},
"query": [
{
"code": "Region",
"selection": {
"values": [
"25"
@klpn
klpn / svpred.jl
Created February 28, 2016 12:29
Prediction of Swedish mortality pattern using my MortParamsPlot
using MortParamsPlot, PyPlot
import YAML
obsyrs = 1999:2013
predyrs = 2018:5:2033
af = 0
ages = 35:5:95
country = 4290
circcomb = ["ihd";"circnonihd"]
predcauses = ["tum";circcomb]
@klpn
klpn / Masironi70.csv
Last active September 24, 2016 14:00
Connect Masironi (1970), https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/5309508/, with WHO mortality data (assume MySQL database set up according to my mortchartgen repo).
ctryname country totfat satfat suc m55mort f55mort
Jordan 3170 18.5 3.7 11 49 19
El Salvador 2190 19.5 5.5 51 28
Taiwan 3070 15.3 4.8 4.2 58 53
Philippines 3300 9.6 3.7 5.5 89 40
Guatemala 2250 15.1 4.1 115 84
Mexico 2310 24.8 7.9 122 65
Greece 4140 26.5 5.4 4.9 162 61
Japan 3160 14.5 3.4 7.3 165 92
Panama 2350 22.6 6.8 8.7 170 76
@klpn
klpn / cervc4290rate2.csv
Created October 16, 2016 08:14
Calculate life table for Swedish females 2013 with and without decrease cervical cancer mortality (data from Statistics Sweden, http://www.statistikdatabasen.scb.se/goto/sv/ssd/LivslangdEttariga, and WHO via mortchartgen).
We can make this file beautiful and searchable if this error is corrected: It looks like row 3 should actually have 36 columns, instead of 22. in line 2.
Year,Pop1,Pop2,Pop3,Pop4,Pop5,Pop6,Pop7,Pop8,Pop9,Pop10,Pop11,Pop12,Pop13,Pop14,Pop15,Pop16,Pop17,Pop18,Pop19,Pop20,Pop21,Pop22,Pop23,Pop24,Pop25,Pop26,Pop36sum,Pop222sum,Pop2325sum,Pop38mean,Pop914mean,Pop1518mean,Pop1920mean,Pop2122mean,List
1951,3.268342161613885e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.923816852635629e-05,2.2123893805309735e-05,2.982848620432513e-05,5.200594353640416e-05,8.46091861402095e-05,4.908522980812137e-05,8.060453400503778e-05,6.872852233676975e-05,6.93000693000693e-05,3.5842293906810036e-05,5.46448087431694e-05,0.00010416666666666667,4.464285714285714e-05,,,,0.0,3.260653831977091e-05,4.464285714285714e-05,0.0,2.053274867873255e-05,7.07568680725346e-05,5.2571181603439665e-05,7.940573770491804e-05,07A
1952,3.8315247790580604e-05,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,4.42282176028306e-06,0.0,3.637686431429611e-05,4.514672686230248e-05,5.167958656330749e-05,5.966587112171838e-05,0.00010048055919615553,8.91089108910891e-05,7.369614512471656e-05,7.407407407407407e-05,9.70873786407767e-05,6.
@klpn
klpn / amplt.jl
Last active November 6, 2016 13:34
Calculate lifetime cancer risk in Sweden (using data from Statstics Sweden and National Board of Health and Welfare), built on the method defined by Sasieni et. al, (doi:10.1038/bjc.2011.250).
using LifeTable, DataFrames
function AmpLt(inframe, sex, rate = "inc")
age = inframe[1]
pop = inframe[2]
acd = inframe[3]
cd = inframe[4]
cc = inframe[5]
if rate == "inc"
ncol = cc
@klpn
klpn / allskinsv15.csv
Last active April 1, 2017 15:48
Create chart on incidence for all cancer and skin cancer vs age Sweden 2015, based on data from http://www.socialstyrelsen.se/statistik/statistikdatabas/cancer
age fall mall fskin mskin
0 0.0002006 0.0002459 0.0 0.0
5 9.22e-5 0.0001006 0.0 0.0
10 0.0001424 0.0001568 0.0 0.0
15 0.00022940000000000002 0.0002389 0.0 0.0
20 0.0003875 0.00036030000000000003 9.3e-6 0.0
25 0.0007676 0.0004501 9.2e-6 0.0
30 0.0011704 0.0007615 1.34e-5 0.0
35 0.0023091 0.0009373000000000001 2.02e-5 9.7e-6
40 0.0032355 0.0013991 3.74e-5 3.0299999999999998e-5
@klpn
klpn / meni.jl
Last active April 28, 2017 10:20
Create chart showing sum of hospitalized cases with meningococcal disease (ICD-10 A39 as main diagnosis) in Sweden over years, using data from The National Board of Health and Welfare
using DataFrames, PyPlot
m = readtable("meni9815.csv")
magg = aggregate(m, :Ålder, sum)
bar(magg[:Ålder], magg[:Kvinnor_sum], -2, align="edge", label = "Kvinnor")
bar(magg[:Ålder], magg[:Män_sum], 2, align="edge", label = "Män")
grid(1)
legend()
xlabel("Ålder")
ylabel("Antal (summa för ålder över år)")
title("Sjukhusvårdade meningokockinfektion Sverige 1998\u20132015")
@klpn
klpn / sedor.jl
Last active September 8, 2017 15:09
Analyze Swedish cause-of-death and population data (assumed to be in data/2017-9-10-4Amod.csv and data/mfsv16.csv) transformed to CSV files.
using DataFrames
deaths = readtable(normpath("data", "2017-9-10-4Amod.csv"))
ages = DataFrame(age = collect(0:20),
agest = [0;0;1;collect(5:5:90)],
age2 =[0;1;fill(2,3);fill(3,6);fill(4,4);fill(5,2);fill(6,4)])
ages2 = by(ages[:,[:agest, :age2]], :age2,
df -> DataFrame(agest=minimum(df[:agest])))
pop = DataFrame()
pop1 = readtable(normpath("data", "mfsv16.csv"))
@klpn
klpn / WordToPDFA.psm1
Last active July 30, 2018 08:13
Word to PDF/A conversion adapted for Archivematica
function ConvertTo-WordPDFA
{
Param(
[Parameter(Mandatory=$true,Position=0)][String]$dpath
)
$word_app = New-Object -ComObject Word.Application
$doc = $word_app.Documents.Open($dpath)
$dpath_dir = [System.IO.Path]::GetDirectoryName($dpath)
$dpath_base = [System.IO.Path]::GetFileNameWithoutExtension($dpath)
$pdf_fname = $dpath_base + ".pdf"