rtop (version 0.5-10)

netProp-deprecated: Propagate values along a river network. This function does not work as intended for several cases, including the example. It is therefore deprecated and will be completely removed in one of the next versions.

Description

Pass values along a river network when the river network has more segments than the prediction polygons.

Usage

netProp(network, from = "FROMJCT", to = "TOJCT", pred = "pred", 
        iprint = 1)

Arguments

network

object of class SpatialLinesDataFrame describing the river network

from

name of the column giving the endpoint ID of each line segment

to

name of the column giving the start ID of each line segment

pred

name of column with predictions

iprint

if iprint >= 1 the function will give some information about the convergence of the value propagation. Use iprint = 0 to suppress this output.

Value

The function will propagate the predictions upwards along the river network. The result is a SpatialLinesDataFrame with predictions for all line segments, which can easier be plotted.

Examples

# NOT RUN {
library(rgdal)
rpath = system.file("extdata",package="rtop")
observations = readOGR(rpath,"observations")
predictionLocations = readOGR(rpath,"predictionLocations")
observations$obs = observations$QSUMMER/observations$AREASQKM

# Setting some parameters 
params = list(geoDist = TRUE, rresol = 25, cloud = FALSE, model = "Sph")
# Build an object
rtopObj = createRtopObject(observations,predictionLocations, 
              formulaString = obs~1, params = params)
# Fit a variogram (function also creates it)
rtopObj = rtopFitVariogram(rtopObj)
# Check the variogram fit
rtopObj = checkVario(rtopObj, cloud = TRUE, identify = TRUE)
# Predicting at prediction locations
rtopObj = rtopKrige(rtopObj)
# Cross-validation
rtopObj = rtopKrige(rtopObj,cv=TRUE)
cor(rtopObj$predictions$observed, rtopObj$predictions$var1.pred)

rnet = readOGR(".", "rnet")
pred = rtopObj$predictions
rnet$pred = 
    pred$var1.pred[match(rnet$TOJCT, pred$JCTID)]

# will only plot for a few discontinous river segments
spplot(rnet, "pred", col.regions = bpy.colors())
rnet = netProp(rnet)
# will show a prediction for all segments
spplot(rnet, "pred", col.regions = bpy.colors())

 
# }