**Omnia sunt Communia! » R-english**, and kindly contributed to R-bloggers)

The version 0.22 of `solaR` includes a new method, `mergesolaR`. It is designed to merge daily time series of several `solaR` objects.

For example, we can obtain the daily irradiation of the whole set of meteorological stations of Madrid (Spain) and use this information to calculate the productivity of a grid connected PV system. It is possible to complete this process with the `lapply` function. Therefore, we obtain a list of `ProdGCPV` objects:

EstMadrid <- subset(RedEstaciones, NomProv=='Madrid') nEstMadrid <- nrow(EstMadrid) namesMadrid <- EstMadrid$NomEst prodMadrid <- lapply(1:nEstMadrid, function(x){try(prodGCPV(lat=41, modeRad='mapa', mapa=list(prov=28, est=x, start='01/01/2009', end='31/12/2010')) )}) names(prodMadrid) <- namesMadrid okMadrid <- lapply(prodMadrid, class)!='try-error' prodMadrid <- prodMadrid[okMadrid]

In order to prevent from the erroneous behaviour of some stations, the code includes the use of `try`.

Now it’s time for `mergesolaR`. Since we have a list of objects, `do.call` can solve the problem:

YfMadrid <- do.call(mergesolaR, prodMadrid)

The `mergesolaR` for a set of `ProdGCPV` objects merges the daily time series of the `Yf` variable of each object. The result is a multivariate `zoo` object which can be displayed (for example) with the `horizonplot` function.

Previously, the row mean is substracted from each column in order to show the deviation of each meteorological station from the daily mean of the set of stations.

horizonplot(YfMadrid-rowMeans(YfMadrid), origin=0, scales=list(y=list(relation='same')), colorkey=TRUE)

Besides, the function `TargetDiagram` is an alternative tool to show the behaviour of

the set of meteorological stations:

TargetDiagram(YfMadrid, end=as.POSIXct('2010-12-31'), ndays=c(10, 20, 30, 40, 50, 60))

**leave a comment**for the author, please follow the link and comment on their blog:

**Omnia sunt Communia! » R-english**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...