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Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle L_{Aeq} = 10 \log \int_{t_0}^{t_1} \frac{p_A^2(t)}{p_0^2} dt }
Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \textstyle L_{Aeq} = 10 \log \int_{t_0}^{t_1} \frac{p_A^2(t)}{p_0^2} dt }
Contents
Kuopio buildings on Google maps test
library(rgdal)
library(maptools)
library(RColorBrewer)
library(classInt)
library(OpasnetBaseUtils)
shp<-readOGR('PG:host=localhost user=postgres dbname=spatial_db','kuopio_house')
plotvar<-shp@data$ika
nclr<-8
plotclr<-brewer.pal(nclr,"BuPu")
class<-classIntervals(plotvar,nclr,style="quantile")
colcode<-findColours(class,plotclr)
epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")
proj4string(shp)<-("+init=epsg:3067")
shp2<-spTransform(shp,epsg4326String)
kmlname<-"Kuopio house data"
kmldescription<-"Random stuff about here"
icon<-"http://maps.google.com/mapfiles/kml/pal2/icon18.png"
name<-paste("ika value: ", shp2$ika)
description <- paste("<b>Value:</b>",shp2$ika,"<br><b>Description:</b>",shp2$kayttotark)
MyPointKML<-function(obj = NULL, kmlname = "", kmldescription = "", name = NULL, description = "", icon = "http://maps.google.com/mapfiles/kml/pal4/icon24.png",col=NULL)
{
if (is.null(obj))
return(list(header = c("<?xml version=\"1.0\" encoding=\"UTF-8\"?>",
"<kml xmlns=\"http://earth.google.com/kml/2.2\">",
"<Document>", paste("<name>", kmlname, "</name>",
sep = ""), paste("<description><![CDATA[", kmldescription,
"]]></description>", sep = "")), footer = c("</Document>",
"</kml>")))
if (class(obj) != "SpatialPointsDataFrame")
stop("obj must be of class 'SpatialPointsDataFrame' [package 'sp']")
if (is.null(name)) {
name = c()
for (i in 1:nrow(obj)) name <- append(name, paste("site",
i))
}
if (length(name) < nrow(obj)) {
if (length(name) > 1)
warning("kmlPoints: length(name) does not match nrow(obj). The first name will be replicated.")
name <- rep(name, nrow(obj))
}
if (length(description) < nrow(obj)) {
if (length(description) > 1)
warning("kmlPoints: length(description) does not match nrow(obj). The first description will be replicated.")
description <- rep(description, nrow(obj))
}
if (length(icon) < nrow(obj)) {
if (length(icon) > 1)
warning("kmlPoints: length(icon) does not match nrow(obj). Only the first one will be used.")
icon <- icon[1]
}
col2kmlcolor <- function(col) paste(rev(sapply(col2rgb(col, TRUE), function(x) sprintf("%02x", x))), collapse = "")
kml <- kmlStyle <- ""
kmlHeader <- c("<?xml version=\"1.0\" encoding=\"UTF-8\"?>","<kml xmlns=\"http://earth.google.com/kml/2.2\">", "<Document>")
kmlFooter <- c("</Document>", "</kml>")
#for (i in 1:nrow(obj)) {
for (i in 1:100) {
point <- obj[i, ]
pt_name = name[i]
pt_description = description[i]
pt_style <- paste("#style", ifelse(length(icon) == 1, 1, i), sep = "")
kml <- append(kml, "<Placemark>")
kml <- append(kml, paste(" <description><![CDATA[",pt_description, "]]></description>", sep = ""))
#kml <- append(kml, "<Style><IconStyle>")
#kml <- append(kml, paste("<color>", col2kmlcolor(col[i]), "</color>", sep =""))
#kml <- append(kml, paste(" <Icon><href>", icon, "</href></Icon>", sep = ""))
#kml <- append(kml, "<scale>0.300000</scale>")
#kml <- append(kml, "</IconStyle></Style>")
kml <- append(kml, " <Point>")
kml <- append(kml, " <coordinates>")
kml <- append(kml, paste(point@coords[1], point@coords[2], sep = ","))
kml <- append(kml, " </coordinates>")
kml <- append(kml, " </Point>")
kml <- append(kml, "</Placemark>")
}
return(paste(paste(c(kmlHeader, kmlStyle, kml, kmlFooter), sep = "", collapse = "\n"), collapse="\n", sep = ""))
}
data <- MyPointKML(shp2,kmlname,kmldescription,name,description,icon,colcode)
google.show_kml_data_on_maps(data)
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GoogleMaps Sorvi MML TEST
library(OpasnetBaseUtils)
library(sorvi)
library(rgdal)
data(MML)
shp <- MML[["1_milj_Shape_etrs_shape"]][["kunta1_p"]]
#epsg3857String <- CRS("+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +a=6378137 +b=6378137 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs")
epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")
proj4string(shp)<-("+init=epsg:3047")
shp2<-spTransform(shp,epsg4326String)
out<-sapply(slot(shp2,"polygons"),function(x){kmlPolygon(x,name="nimi",col='#df0000aa',lwd=1,border='black',description="selite") })
data<-paste(
paste(kmlPolygon(kmlname="This will be layer name", kmldescription="<i>More info about layer here</i>")$header, collapse="\n"),
paste(unlist(out["style",]), collapse="\n"),
paste(unlist(out["content",]), collapse="\n"),
paste(kmlPolygon()$footer, collapse="\n"),
sep=''
)
google.show_kml_data_on_maps(data)
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GoogleMaps PostgreSQL test 2
library(rgdal)
library(maptools)
library(RColorBrewer)
library(classInt)
library(OpasnetBaseUtils)
shp<-readOGR('PG:host=localhost user=postgres dbname=spatial_db','watson_wkt')
plotvar<-shp@data$value_inhalation
nclr<-8
plotclr<-brewer.pal(nclr,"BuPu")
class<-classIntervals(plotvar,nclr,style="quantile")
colcode<-findColours(class,plotclr)
epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")
proj4string(shp)<-("+init=epsg:3035")
shp2<-spTransform(shp,epsg4326String)
out<-sapply(slot(shp2,"polygons"),function(x){kmlPolygon(x,name=as(shp2,"data.frame")[slot(x,"ID"),"country_code"],col=colcode[[((as.numeric(slot(x,"ID"))+1))]],lwd=1,border='black',description=paste("Value:",as(shp2,"data.frame")[slot(x,"ID"),"value_inhalation"])) })
data<-paste(
paste(kmlPolygon(kmlname="This will be layer name", kmldescription="<i>More info about layer here</i>")$header, collapse="\n"),
paste(unlist(out["style",]), collapse="\n"),
paste(unlist(out["content",]), collapse="\n"),
paste(kmlPolygon()$footer, collapse="\n"),
sep=''
)
google.show_kml_data_on_maps(data)
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GoogleMaps PostgreSQL test
library('OpasnetBaseUtils')
cat("<span style='font-size: 1.2em;font-weight:bold;'>PostgreSQL Test</span>\n")
google.show_data_on_maps()
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Opasnet.csv test
library(OpasnetBaseUtils)
csv <- opasnet.csv("2/25/Russian_elections_2011_results.csv")
print(csv[1:10,1:10])
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Opasnet.data and BUGS test
library(OpasnetBaseUtils)
pumps.model <- opasnet.data('c/cc/Test_bugs_model.txt')
library('rbugs')
data(pumps)
pumps.data <- list(t = pumps$t, x = pumps$x, N = nrow(pumps))
inits <- list(alpha = 1, beta = 1)
parameters <- c("theta", "alpha", "beta")
pumps.sim <- bugs.run(data = pumps.data, list(inits), parameters,pumps.model, n.chains = 1, n.iter = 1000)
## MCMC Analysis
library("coda")
pumps.mcmc <- as.mcmc(pumps.sim$chain1)
summary(pumps.mcmc)
effectiveSize(pumps.mcmc)
## End(Not run)
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# This code does not work. Should test the one in test wiki but i don't remember the location.
library(rjags)
N <- 1000
x <- rnorm(N, 0, 5)
example.bug <- "model {
for (i in 1:N) {
x[i] ~ dnorm(mu, tau)
}
mu ~ dnorm(0, .0001)
tau <- pow(sigma, -2)
sigma ~ dunif(0, 100)
}"
jags.model
jags <- jags.model(example1.bug,
data = list('x' = x,
'N' = N),
n.chains = 4,
n.adapt = 100)
update(jags, 1000)
jags.samples(jags,
c('mu', 'tau'),
1000)
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Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \alpha 444 + 9999 / 123}
Hello
- this works
Bluebox
- works
- ok
R-tools code include example
cat("Above should be included code\n")
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library(OpasnetBaseUtils)
library(ggplot2)
library(xtable)
saanto.siemenet <- op_baseGetData("opasnet_base", "Op_fi2633")[,-c(1,2,7)] # Jatropan siementen saanto viljelystä
saanto.öljy <- op_baseGetData("opasnet_base", "Op_fi2634")[,-c(1,2,5)] # Öljyn saanto jatropan siemenistä
saanto.diesel <- op_baseGetData("opasnet_base", "Op_fi2632")[,-c(1,2,5)] # Biodieselin saanto jatropaöljystä
viljelyala <- op_baseGetData("opasnet_base", "Op_fi2642")[,-c(1,2)] # Jatropan viljelyalueet
päästö.ilmasto <- op_baseGetData("opasnet_base", "Op_fi2547")[,-c(1,2)] # Jatropan viljelyn ilmastovaikutukset
päästö.sosiaali <- op_baseGetData("opasnet_base", "Op_fi2552")[,-c(1,2)] # Jatropan viljelyn sosiaaliset vaikutukset
päästö.ekosyst <- op_baseGetData("opasnet_base", "Op_fi2548")[,-c(1,2)] # Jatropan viljelyn ekosysteemivaikutukset
P <- op_baseGetData("opasnet_base", "Op_fi2539")[,-c(1,2,7)] # Jatropan käyttö bioenergian lähteenä
colnames(saanto.siemenet)[4] <- "siemenet"
colnames(saanto.öljy)[2] <- "öljy"
colnames(saanto.diesel)[2] <- "diesel"
saanto <- merge(saanto.siemenet, saanto.öljy)
saanto <- merge(saanto, saanto.diesel)
saanto[,9] <- saanto$siemenet * saanto$öljy * saanto$diesel * ala
colnames(saanto)[9] <- "saanto (kg/a)"
P <- PTable(P, n)
saanto <- merge(P, saanto)
if(length(divisions)>1) divisions <- as.list(saanto[, divisions]) else divisions <- saanto[, divisions]
out1 <- as.data.frame(as.table(tapply(saanto[, 10], divisions, mean)))
out1 <- dropall(out1[!is.na(out1$Freq), ])
print(xtable(out1), type = 'html')
out2 <- as.data.frame(as.table(tapply(saanto[, 10], list(saanto[, divisions2], saanto$obs), mean)))
out2 <- dropall(out2[!is.na(out2$Freq), ])
out2[1:10, ]
ggplot(out2, aes(x = Freq, weight = 1, fill = Var1)) +geom_density()
## Jostain syystä vain osa kuvista piirtyy oikein, riippuen mitä parametreja valitaan. En ymmärrä syytä.
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######################################
## dropall pudottaa data.framesta pois kaikki faktorien sellaiset levelit, joita ei käytetä.
## parametrit: x = data.frame
dropall <- function(x){
isFac <- NULL
for (i in 1:dim(x)[2]){isFac[i] = is.factor(x[ , i])}
for (i in 1:length(isFac)){
x[, i] <- x[, i][ , drop = TRUE]
}
return(x)
}
########################################
#########################################
## PTable muuntaa arvioinnin todennäköisyystaulun sopivaan muotoon arviointia varten.
## Parametrit: P = todennäköisyystaulu Opasnet-kannasta kaivettuna.
## n = iteraatioiden lukumäärä Monte Carlossa
## Todennäköisyystaulun sarakkeiden on oltava: Muuttuja, Selite, Lokaatio, P
## Tuotteena on Monte Carloa varten tehty taulu, jonka sarakkeina ovat
## n (iteraatio) ja kaikki todennäköisyystaulussa olleet selitteet, joiden riveille on arvottu
## lokaatiot niiden todennäköisyyksien mukaisesti, jotka todennäköisyystaulussa oli annettu.
PTable <- function(P, n) {
Pt <- unique(P[,c("Muuttuja", "Selite")])
Pt <- data.frame(Muuttuja = rep(Pt$Muuttuja, n), Selite = rep(Pt$Selite, n), obs = rep(1:n, each = nrow(Pt)), P = runif(n*nrow(Pt), 0, 1))
for(i in 2:nrow(P)){P$Result[i] <- P$Result[i] + ifelse(P$Muuttuja[i] == P$Muuttuja[i-1] & P$Selite[i] == P$Selite[i-1], P$Result[i-1], 0)}
P <- merge(P, Pt)
P <- P[P$P <= P$Result, ]
Pt <- as.data.frame(as.table(tapply(P$Result, as.list(P[, c("Muuttuja", "Selite", "obs")]), min)))
colnames(Pt) <- c("Muuttuja", "Selite", "obs", "Result")
Pt <- Pt[!is.na(P$Result), ]
P <- merge(P, Pt)
P <- P[, !colnames(P) %in% c("Result", "P", "Muuttuja")]
P <- reshape(P, idvar = "obs", timevar = "Selite", v.names = "Lokaatio", direction = "wide")
colnames(P) <- ifelse(substr(colnames(P), 1, 9) == "Lokaatio.", substr(colnames(P), 10,30), colnames(P))
return(P)
}
######################################
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Rectangle area test
# The area of the rect is width * height |
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