romunov

# this is what i have so far

require(TMB)

rak <- read.table("./data/master_all_r3.txt", dec = ".", header = TRUE, sep = "\t")

# prepare the data
rakdat <- na.omit(rak[, c("vrsta", "tw", "ETS_t_1000")])
xvar <- rakdat[, "tw"]
yvar <- rakdat[, "ETS_t_1000"]

romunov

subsetGenData <- function(x) {  
  mp <- droplevels(other(x)$metadata)
  iksips <- other(x)$xy
  
  pet <- df2genind(X = genind2df(x, sep = "/"), sep = "/", ind.names = indNames(x),
                   loc.names = locNames(x))
  pet@other$metadata <- mp
  pet@other$xy <- iksips
  pet
  }

romunov

 library(dplyr)

my.db <- src_sqlite("my_db.sqlite3", create = TRUE)
# creates an empty file
library(nycflights13)

# link to flights table
flights.db <- copy_to(my.db, flights, temporary = FALSE, 
                        indexes = list(c("year", "month", "day"), "carrier", "tailnum"))

romunov

```R
---
title: "Analiza - CRO"
author: "Teo"
date: "Sunday, February 15, 2015"
output: html_document
---

```{r}
library(ggplot2)

romunov

Imagine having a population where age of individuals is known. I would like to sample from this population individuals by age according to a parametric distribution (e.g. X ~ Poisson(1.82)). In other words, I would like to remove a known number of individuals from each class, where class sizes follows a Poisson distribution.

Is there a more elegant way?

ma <- 10 # max age
ss <- 50 # sample size
l <- 1.82 # lambda in Poisson distribution

set.seed(357)

romunov

I'm trying to install adegenet package using install_github(), but I get a few errors. I'm able to install the package if I build and install the package from console. For the latter output see below. I'm using 64-bit Windows 7. I wonder to what can we attribute the discrepancy between these two ways of installing a package?

Installation through devtools (fail)

> install_github("thibautjombart/adegenet/pkg")
Downloading github repo thibautjombart/adegenet@master
Installing adegenet
"C:/PROGRA~1/R/R-31~1.2/bin/x64/R" --vanilla CMD INSTALL  \
  "C:/Users/romunov/AppData/Local/Temp/RtmpSo6w8C/devtools15882f7c4022/thibautjombart-adegenet-8cca9e1/pkg"  \
  --library="C:/Users/romunov/Documents/R/win-library/3.1" --install-tests 

romunov

# -*- coding: utf-8 -*-
import simuPOP as sim
import numpy as np
import random
from math import exp
#from scipy.stats import poisson # for poisson pmf

popHR = 2000
popSI = 1000
population_size = popHR + popSI

romunov

# this example demostrantes that two individuals are not migrated from VSP [1, 1] to subpopulation 0
import simuPOP as sim
import numpy as np

pop = sim.Population(size = [100, 100], loci = 3, infoFields = ["age", "migrate_to"])
sim.initInfo(pop = pop, values = np.random.negative_binomial(n = 3, p = 0.4, size = 20), infoFields = "age")
sim.initSex(pop, maleProp = 0.5)

pop.setVirtualSplitter(sim.ProductSplitter(splitters = [
    sim.SexSplitter(),

romunov

# -*- coding: utf-8 -*-
import simuPOP as sim
import numpy as np
from simuPOP.utils import viewVars

pop = sim.Population(size = [550, 400], loci = 10, infoFields = ["age", "migrate_to"], subPopNames = ["croatia", "slovenia"])
sim.initInfo(pop = pop, values = np.random.choice([1, 2, 3, 4, 5], replace = True, size = 200), infoFields = "age")
sim.initGenotype(pop = pop, prop = [0.1]*10)
sim.initSex(pop, maleProp = 0.5)

romunov

def splitCalcMerge(pop, param):
    # Calculate population sizes to help with splitting (see below).
    pop_size_croatia = pop.subPopSize(0)
    pop_size_slovenia = pop.subPopSize(1)
    pop_sizes = {"1":pop_size_croatia, "3":pop_size_slovenia}

    # Split population into two. First subpopulation is the main one minus the
    # sample size (ss).
    sim.splitSubPops(pop = pop, subPops = 0, sizes = [pop_size_croatia - param["croatia"], param["croatia"]])
    sim.splitSubPops(pop = pop, subPops = 2, sizes = [pop_size_slovenia - param["slovenia"], param["slovenia"]])