romunov

""" The task is to write comments (after ## ??) on every instance and describe it with the phrase is-a and has-a.
For further reference, please see ex41. """


## Animal is-a object (yes, sort of cinfusing) look at the extra credit
class Animal(object):
	pass 

## ?? Class Dog is-a Animal that has-a __init__that takes self and name as parameters
class Dog(Animal):

romunov

"""
Off the shelf way to skip already processed entities

This scripts processes files, remembers which files have been already
processed and skips them on the next run.
"""
import glob
import os
import shelve

romunov

naloga <-data.frame("U308"=c(8.23, 8.78, 9.90, 10.90, 17.88, 29.00, 44.17, 83.01))
naloga$Leto <- seq(from=2000, to=1999+length(naloga$U308))

fit <- lm(log(U308) ~ Leto, data=naloga)

ggplot(naloga, aes(x = Leto, y = U308)) +
  geom_point() +
  ylab("Cena funta urana U308 v $") +
  geom_function(fun = function(x) exp(coef(fit)[1]) * (exp(coef(fit)[2])^(x)), col="black", lty=2, size=0.3)

romunov

library(adegenet)

data(H3N2)

dapc1 <- dapc(H3N2, pop=H3N2$other$epid, n.pca=30,n.da=6)

custom.cols <- rep(c("red", "blue"), times = c(1000,903))

scatter(dapc1, col = custom.cols)

romunov

# http://www.neilmclatchie.com/using-r-shading-area-under-a-distribution/
stp <- 0.01  # "resolution"
left.limit <- -6
right.limit <- 6

plot(
  x = NA,
  type = "n",
  lwd = 2,
  lty = 1,

romunov

# Use case:
# You have a weekly dataset and some variable for that week, i.e.

# week value year
#    1   528 2019
#    2   503 2019
#    3   493 2019
#    4   487 2019
#    5   526 2019
#    6   523 2019

romunov

xy <- read.table(text = "date               | lon          | lat          | trip | distancetocoast
2014-06-11 19:02:00 | -58,3508585  | -51,88438373 | 1    | 2236.067977
                 2014-06-12 01:02:00 | -58,35589725 | -51,88349529 | 1    | 1000
                 2014-06-12 13:02:00 | -58,27224941 | -51,91903677 | 1    | 7211,102551
                 2014-06-12 19:02:00 | -58,27974654 | -51,90535003 | 1    | 5830,951895
                 2014-06-13 01:02:00 | -58,32331901 | -51,89410464 | 1    | 3605,551275
                 2014-06-13 07:02:00 | -58,35833139 | -51,88809227 | 1    | 1414,213562
                 2014-06-13 13:02:00 | -58,35617673 | -51,88156281 | 1    | 1000
                 2014-06-13 19:02:00 | -58,34055711 | -51,89002367 | 1    | 2236,067977
                 2014-06-14 01:02:00 | -58,34982536 | -51,8715761  | 2    | 1000

romunov

require(xts)

dailyip=readRDS(gzcon(url("https://dl.dropboxusercontent.com/s/kfxg1vi1s6hv6cg/dailyip.rds")))
dailyrx=readRDS(gzcon(url("https://dl.dropboxusercontent.com/s/of47enf79ugkq8c/dailyrx.rds")))

populate = function(x) { 
  if(unique(is.na(x))=='TRUE') return(x)
  naseries=cbind(x,NA)[,2]
  where=which(x<(yy))[1]
  if(!is.na(where)) return(na.locf(cbind(x[1:where],naseries)[,1]))

romunov

library(raster)
library(microbenchmark)

logo <- stack(system.file("external/rlogo.grd", package="raster")) 
la <- as.array(logo)

microbenchmark(vanilla = mean(logo), 
               overlay = overlay(logo, fun = mean), times = 50, calc(logo, fun = mean), 
               rasterapply = {raster(apply(la, MARGIN = c(1,2), FUN = mean))}, 
               norasterapply = {apply(la, MARGIN = c(1,2), FUN = mean)})

romunov

library(scrbook)

scrPID.um2  <- function (n, X, y, M, mmax, obsmod = c("pois", "bern"), niters, 
          npics, xlims, ylims, inits, delta) 
{
  obsmod <- match.arg(obsmod)
  J <- nrow(n)
  K <- ncol(n)
  S <- inits$S
  D <- e2dist(S, X)