Changes between Version 4 and Version 5 of udg/ecoms/RPackage/examples/drift

Timestamp:

Sep 4, 2014 12:21:14 PM (8 years ago)

Author:

juaco

Comment:

--

udg/ecoms/RPackage/examples/drift

@@ -36 +36 @@
 
 {{{#!text/R
-> # The library sp needs to be installed to do this example:
-> require(sp)
-Loading required package: sp
-> # Matrix of anomalies between lead month and reference 
-> aux.mat <- matrix(ncol = length(cfs.list), nrow = length(ref$xyCoords$x)*length(ref$xyCoords$y))
-> for (i in 1:length(cfs.list)) {
-+       mm.field <- apply(cfs.list[[i]]$Data, MARGIN = c(3,2), FUN = mean, na.rm = TRUE)
-+       aux.mat[ ,i] <- mm.field - ref.field
-+ }
-> # 2D coordinates
-> xy <- expand.grid(ref$xyCoords$x, ref$xyCoords$y)
-> # This step ensures regularity of the CFS grid, which is not perfectly regular:
-> xy.coords <- coordinates(points2grid(points = SpatialPoints(xy), tolerance = .003))
-> # Now we create a data.frame with the coordinates X-Y in the first two columns and the mean anomalies in the next 6 columns:
-> df <- cbind.data.frame(xy.coords, aux.mat)
-> names(df) <- c("x","y",paste("LeadMonth_",1:6, sep = ""))
-> str(df)
+# The library sp needs to be installed to do this example:
+require(sp)
+# Matrix of anomalies between lead month and reference 
+aux.mat <- sapply(1:length(cfs.list), function(i) {apply(cfs.list[[i]]$Data, MARGIN = c(3,2), FUN = mean, na.rm = TRUE) - ref.field})
+# 2D coordinates
+xy <- expand.grid(ref$xyCoords$x, ref$xyCoords$y)
+# This step ensures regularity of the CFS grid, which is not perfectly regular:
+xy.coords <- coordinates(points2grid(points = SpatialPoints(xy), tolerance = .003))
+# Now we create a data.frame with the coordinates X-Y in the first two columns and the mean anomalies in the next 6 columns:
+df <- cbind.data.frame(xy.coords, aux.mat)
+names(df) <- c("x","y",paste("LeadMonth_",1:6, sep = ""))
+str(df)
 'data.frame':   55 obs. of  8 variables:
  $ x          : num  -10.31 -9.38 -8.44 -7.5 -6.56 ...
@@ -62 +57 @@
  $ LeadMonth_5: num  -1.212 -0.986 -0.682 -0.587 -0.584 ...
  $ LeadMonth_6: num  -1.314 -0.732 -0.32 -0.5 -0.98 ...
-> coordinates(df) <- c(1,2)
-> gridded(df) <- TRUE
-> class(df)
+coordinates(df) <- c(1,2)
+gridded(df) <- TRUE
+class(df)
+}}}
+
+Which returns the new spatial object class:
+
+{{{
 [1] "SpatialPixelsDataFrame"
 attr(,"package")
@@ -73 +73 @@
 
 {{{#!text/R
-> load(url("http://meteo.unican.es/work/downscaler/aux/wlines.rda"), verbose = TRUE)
-Loading objects:
-  wlines
-> l1 <- list("sp.lines", wlines)
-> spplot(df, as.table = TRUE, col.regions = colorRampPalette(c("blue","white","red")), at = seq(-5.25,5.25,.25), scales = list(draw = TRUE), sp.layout = list(l1))
+load(url("http://meteo.unican.es/work/downscaler/aux/wlines.rda"), verbose = TRUE)
+l1 <- list("sp.lines", wlines)
+spplot(df, as.table = TRUE, col.regions = colorRampPalette(c("blue","white","red")), at = seq(-5.25,5.25,.25), scales = list(draw = TRUE), sp.layout = list(l1))
 }}}
 
@@ -88 +86 @@
 
 {{{#!text/R
-> barplot(colMeans(df@data), names.arg = abbreviate(names(df)), xlab = "lead month", ylab = "anomaly (ºC)")
-> title(main = "Mean forecast bias w.r.t. the lead-month 0 initialization")
-> mtext("Member 1")
+barplot(colMeans(df@data), names.arg = abbreviate(names(df)), xlab = "lead month", ylab = "anomaly (ºC)")
+title(main = "Mean forecast bias w.r.t. the lead-month 0 initialization")
+mtext("Member 1")
 }}}