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params.index = 'testfile2.txt'

Channel
    .fromPath(params.index)
    .splitCsv(header:true, sep:"\t")
    .map{ row-> tuple(row.head1, row.head2, row.head4) }
    .into { samples_ch }

process transform {
  input:

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head1	head2	head3	head4
line.00	afsd	col3	another-00
line.01	afsd	col3	another-01
line.02	afsd	col3	another-02
line.03	afsd	col3	another-03
leene.04	afsd	col3	another-04
line.05	afsd	col3	another-05
leene.06	afsd	col3	another-06
loone.07	afsd	col3	another-07
loone.08	afsd	col3	another-08

k-hench

library(tidyverse)

# allele section -----------------
# available base pairs
BS <- c('A','T','C','G')
# sample random base pair
bs <- function(n,replace = TRUE,...) sample(x = BS, size = n, replace = replace, ...)
# sample a possible alternative allele for a single given base pair
alt_bs_1 <- function(bs){
  stopifnot(length(bs)==1)

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library(tidyverse)
library(grid)

raw <- tibble(x = letters[1:5], y = x)
filter <- function(x, y) x <= y
data_tri <- purrr::cross_df(raw,.filter = filter) %>% mutate(val = rnorm(length(.$x)))

plot_tri <- ggplot(data = data_tri, aes(x = x, y = y, fill = val)) +
  coord_equal()+
  geom_tile() +

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library(tidyverse)

export_2_latex <- function(table, name){
  table %>% 
    mutate(`\\\\\\hline` = '\\\\') %>% 
    write_delim(.,path = '.tmp.tex',delim = '&')
  # clean last column
  n <- names(table) %>% length()
  
  # open latex table 

k-hench

/*typo replace {into ; not ","}*/
Channel
  .from( [[1, "ind"], [2, "may"], [3, "nig"], [4, "pue"], [5, "uni"], [6, "gem"]] )
  .into{ bel_spec1_ch; bel_spec2_ch }

Channel.from("test1", "test2" ).collect().set{vcf_loc_pair1}

bel_pairs_ch = Channel
  .from( "test1" )
  .join( vcf_loc_pair1 )

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pts <- strata_coordinates( arapat, as.SpatialPoints = TRUE )
stamen_bb <- function(bb){
  bt <- pts@bbox %>% 
    as_tibble()
  
  c(left = bt$min[1],
    bottom = bt$min[2],
    right = bt$max[1],
    top = bt$max[2])
}

k-hench

---
title: "fit_growth_curve"
author: "Kosmas Hench"
date: "5/24/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(DT)

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library(tidyverse)

### nuber of reruns ###
nsims <- 10000


## parameter table defining the parameter space --------------------
params <- tibble(param_name = c("NNIG", "NPUE", "NANC", "TDIV", "TMIG",  "MIGRPROBN2P", "MIGRPROBP2N"),
                 log10min   = c(rep(3,3), 1, 1, rep(-5, 2)),
                 log10max   = c(rep(log10(2.5e5), 3), rep(4, 2), rep(-2, 2)),