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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 + 444444 + \beta + \omega }

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File:aditro.PNG

File:Kuvatiedostonmitähäan.jpg

<display_map type="terrain"> 62.904602, 27.647781 62.891918, 27.680013 </display_map>

<mfanonymousfilelist></mfanonymousfilelist>

Sandbox: Difference between revisions(kg)

Obs	Make	Result	Description
1	Lata	100
2	Toyota	88	Toijota

[show] This page is a knowledge crystal of subtype variable. The page identifier is Op_en1390
Moderator:Ehac (see all)
Upload data {{#opasnet_base_link:Op_en1390}}

mitä tapahtuu!

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 + 8884444}

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 }

Live Code Test

Breaks: 10 20 35 50 + Show code- Hide code hist(faithful$eruptions, probability = TRUE, breaks = as.numeric(breaks), xlab = "Duration (minutes)", main = "Geyser eruption duration")

Sotkanet

+ Show code- Hide code library(OpasnetUtils) library(OpasnetUtilsExt) # collect makes a data.frame out of the list object from Sotkanet # x is the input data # name is the name for the column # single is a logical whether there is only a single entry in the x data. collect <- function(x, name, single = FALSE) { out <- data.frame() if(single) {out <- data.frame(temp1 = x$id, temp2 = x$title$fi) } else { for(i in 1:length(x)) { out <- rbind(out, data.frame(temp1 = x[[i]]$id, temp2 = x[[i]]$title$fi)) } } colnames(out) <- c(name, paste(name, "Result", sep="")) return(out) } a <- sotkanet.indicators() # print(a) b <- sotkanet.indicators(127) b <- collect(b, "indicator", TRUE) # print(xtable(b), type = 'html') d <- sotkanet.regions() d <- collect(d, "region") # print(xtable(d), type = 'html') e <- sotkanet.data(indicator=127,years=c(2011,2010),genders='female') e <- merge(b, e) e <- merge(d, e) oprint(e)

Objects save test

+ Show code- Hide code library(OpasnetUtils) x <- stats::runif(20) y <- list(a = 1, b = TRUE, c = "Jeah baby jeah!") objects.store(x, y, verbose=TRUE)

Giving tables via user interface

test: - paste table here - Cancel + Show code- Hide code library(OpasnetUtils) oprint(test)

ovariable merge testing

+ Show code- Hide code library(OpasnetUtils) aa <- new("ovariable", output = data.frame(dummy=NA)) bb <- new("ovariable", output = data.frame(a=1:4)) #cc <- new("ovariable", output = data.frame(a=1:4)) cc <- '' test <- Ovariable( name='test', dependencies = data.frame( Name = c("aa", "bb", "cc"), Ident = c(NA, NA, NA) ), formula = function(dependencies, ...) { ComputeDependencies(dependencies, ...) out <- merge(aa, bb) return(out) } ) oprint(test)

Static GoogleMaps test

+ Show code- Hide code #code goes here library(RgoogleMaps) library(rgdal) library(maptools) library(RColorBrewer) library(classInt) library(OpasnetUtils) library(OpasnetUtilsExt) shp<-readOGR('PG:host=localhost user=postgres dbname=spatial_db','kuopio_house') plotvar<-shp@data$ika nclr<-8 plotclr<-brewer.pal(nclr,"Spectral") class<-classIntervals(plotvar,nclr,style="quantile") colcode<-findColours(class,plotclr) epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") proj4string(shp)<-("+init=epsg:3067") shp2<-spTransform(shp,epsg4326String) #get marker information first 10 points mymarkers<-cbind.data.frame(lat=c(shp2@coords[,2]),lon=c(shp2@coords[,1]),color=colcode); #get the bounding box: bb <- qbbox(lat = mymarkers[,"lat"], lon = mymarkers[,"lon"]) #MyMap function without the "file destination" parameter MyRmap<-function (lonR, latR, center, size = c(640, 640), MINIMUMSIZE = FALSE, RETURNIMAGE = TRUE, GRAYSCALE = FALSE, NEWMAP = TRUE, zoom, verbose = 1, ...) { if (missing(zoom)) zoom <- min(MaxZoom(latR, lonR, size)) if (missing(center)) { lat.center <- mean(latR) lon.center <- mean(lonR) } else { lat.center <- center[1] lon.center <- center[2] } if (MINIMUMSIZE) { ll <- LatLon2XY(latR[1], lonR[1], zoom) ur <- LatLon2XY(latR[2], lonR[2], zoom) cr <- LatLon2XY(lat.center, lon.center, zoom) ll.Rcoords <- Tile2R(ll, cr) ur.Rcoords <- Tile2R(ur, cr) if (verbose > 1) { cat("ll:") print(ll) print(ll.Rcoords) cat("ur:") print(ur) print(ur.Rcoords) cat("cr:") print(cr) } size[1] <- 2 * max(c(ceiling(abs(ll.Rcoords$X)), ceiling(abs(ur.Rcoords$X)))) + 1 size[2] <- 2 * max(c(ceiling(abs(ll.Rcoords$Y)), ceiling(abs(ur.Rcoords$Y)))) + 1 if (verbose) cat("new size: ", size, "\n") } return(GetMap(center = c(lat.center, lon.center), zoom = zoom, size = size, RETURNIMAGE = RETURNIMAGE, GRAYSCALE = GRAYSCALE, verbose = verbose, ...)) } MyMap<-MyRmap(bb$lonR,bb$latR,maptype="mobile") PlotOnStaticMap(MyMap) PlotOnStaticMap(MyMap,lat=mymarkers[,"lat"],lon=mymarkers[,"lon"],pch=19,cex=0.3,col=colcode,add=T) legend("topleft", legend=names(attr(colcode, "table")),title="Ika", fill=attr(colcode, "palette"), cex=1.0, bty="y",bg="white")

Kuopio buildings on Google maps test

Building minimum age: + Show code- Hide code library(rgdal) library(maptools) library(RColorBrewer) library(classInt) library(OpasnetUtils) library(OpasnetUtilsExt) library(RODBC) shp <- spatial_db_query(paste('SELECT * FROM kuopio_house WHERE ika >= ',age,';',sep='')) coordinates(shp)=c("y_koord","x_koord") #shp<-readOGR('PG:host=localhost user=postgres dbname=spatial_db','kuopio_house') plotvar<-shp@data$ika nclr<-8 plotclr<-brewer.pal(nclr,"BuPu") class<-classIntervals(plotvar,nclr,style="quantile") colcode<-findColours(class,plotclr) epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") proj4string(shp)<-("+init=epsg:3067") shp2<-spTransform(shp,epsg4326String) kmlname<-"Kuopio house data" kmldescription<-"Random stuff about here" icon<-"http://maps.google.com/mapfiles/kml/pal2/icon18.png" name<-paste("Value: ",shp2$ika) description <- paste("<b>Ikä:</b>",shp2$ika,"<br><b>Rakennustunnus:</b>",shp2$rakennustunnus) 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)) } 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)) { 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)

GoogleMaps Sorvi MML TEST

+ Show code- Hide code library(OpasnetUtils) library(OpasnetUtilsExt) 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)

GoogleMaps PostgreSQL test 2

+ Show code- Hide code library(rgdal) library(maptools) library(RColorBrewer) library(classInt) library(OpasnetUtils) library(OpasnetUtilsExt) 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)

GoogleMaps PostgreSQL test

+ Show code- Hide code library(OpasnetUtils) library(OpasnetUtilsExt) cat("PostgreSQL Test\n") google.show_data_on_maps() google.show_data_on_maps(table='kuopio_house',database='spatial_db',fields=c('ika','ika','the_geom'))

Opasnet.csv test

+ Show code- Hide code library(OpasnetUtils) csv <- opasnet.csv("2/25/Russian_elections_2011_results.csv") print(csv[1:10,1:10])

Opasnet.data and BUGS test

+ Show code- Hide code library(OpasnetUtils) 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)

+ Show code- Hide code # 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)

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

+ Show code- Hide code cat("Above should be included code\n")

Jatropan viljelyala (ha): n: Mitkä tekijät halua eritellä tuloksessa?: Katalyytin määrä Ikä Kastelu Käytetty puristin Minkä yhden tekijän halua eritellä kuvaajassa?: Katalyytin määrä Ikä Kastelu Käytetty puristin + Show code- Hide code library(OpasnetUtils) 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.

+ Show code- Hide code ###################################### ## 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) } ######################################

Rectangle area test

width: Rect height: + Show code- Hide code # The area of the rect is width * height

MassHEIS test

Moved to MassHEIS.

MassHEIS test multilayer NOT WORKING YET

+ Show code- Hide code library(OpasnetUtils) library(OpasnetUtilsExt) library(ggplot2) library(rgdal) library(maptools) library(RColorBrewer) library(classInt) library(raster) data <- MassHEIS.data() # Plot the data coordinates(data)=c("longitude","latitude") proj4string(data)<-("+init=epsg:4326") epsg4326String <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") shp<-spTransform(data,epsg4326String) start <- min(shp$anmean) end <- max(shp$anmean) rasters = list() years = c(2000,2001,2002) for(y in 1:length(years)) { #Create blank raster rast<-raster() s <- shp[(shp$Year == years[y]),] #Set raster extent to that of point data extent(rast)<-extent(s) #Choose number of columns and rows ncol(rast) <- 64 nrow(rast) <- 64 #Rasterize point data rasters[[y]] <- rasterize(s, rast, s$anmean, fun=mean) } steps <- approx(c(start,end),n=6)$y colors <- rev(rainbow(length(steps), start=0, end=0.50)) par(mfrow=c(6,1), mar=c(3,1,0,1), cex=1.5) colorstrip <- function(colors, labels) { count <- length(colors) m <- matrix(1:count, count, 1) image(m, col=colors, ylab="", axes=FALSE) axis(1,approx(c(0, 1), n=length(labels))$y, labels) } cat("<span style='font-size: 1.2em;font-weight:bold;'>Massachusetts annual mean PM 2.5 microns</span>\n") colorstrip(colors, steps) #Plot data s <- stack(rasters) names(s) <- c('z2000','z2001','z2002') print(s) google.show_raster_on_maps(s, col=colors, style="height:500px;")