SpherWave (version 1.2.2)

sw.plot: Plot of Observation, Network Design, Field, SW Coefficient, Decomposition or Reconstruction Result

Description

This function performs plotting of observation, network design, field, SW coefficients, decomposition or reconstruction result.

Usage

sw.plot(sw = NULL, z = NULL, latlon = NULL, latlim = NULL,  lonlim = NULL, type = "field", nlevel = 256, pch = NULL,  cex = NULL, ...)

Arguments

sw

sbf or swd object

z

observations, network design labels or reconstruction

latlon

grid points of observation sites in degree

latlim

range of latitudes in degree

lonlim

range of longitudes in degree

type

specifies the type "obs", "network", "field", "swcoeff", "decom" or "recon"

nlevel

number of color levels used in legend strip

pch

either an integer specifying a symbol or a single character to be used as the default in plotting points

cex

a numerical value giving the amount by which plotting text and symbols should be scaled relative to the default

...

the usual arguments to the image function or plot function

Details

This function plots spherical wavelet results. Possible types are

`"obs"' for observations `"network"' for network design `"field"' for field `"swcoeff"' for spherical wavelet coefficients `"decom"' for decomposition results `"recon"' for reconstruction result. For `sw', sbf or swd object must be provided. For sbf object, type `"obs"', `"network"', `"field"' are possible whereas all types are possible for swd object. Or specify `z' and `latlon' without `sw'.

Examples

### Observations of year 1967
data(temperature)
names(temperature)

# Temperatures on 939 weather stations of year 1967    
temp67 <- temperature$obs[temperature$year == 1967] 
# Locations of 939 weather stations    
latlon <- temperature$latlon[temperature$year == 1967, ]

### Draw the temperature data
sw.plot(z=temp67, latlon=latlon, type="obs")

### Network design by BUD
data(netlab)
sw.plot(z=netlab, latlon=latlon, type="network")

### SBF representation of the observations
#eta <- c(0.961,0.923,0.852,0.723,0.506)
#out.pls <- sbf(obs=temp67, latlon=latlon, netlab=netlab, eta=eta,
#    method="pls", grid.size=c(50, 100), lambda=0.89)
# observation
#sw.plot(out.pls, type="obs")
# network design
#sw.plot(out.pls, type="network")
# field 
#sw.plot(out.pls, type="field")  

### Decomposition
#out.dpls <- swd(out.pls)
# observation
#sw.plot(out.dpls, type="obs")
# network design
#sw.plot(out.dpls, type="network")   
# SBF representation of the observations
#sw.plot(out.dpls, type="field")
# sw coefficient
#sw.plot(out.dpls, type="swcoeff")
# decomposition result
#sw.plot(out.dpls, type="decom")

# Thresholding  
#out.univ <- swthresh(out.dpls, policy="universal", by.level=TRUE, 
#    type="hard", nthresh=4)  
#par(oma=c(0,0,3.5,0))
#sw.plot(out.univ, type="decom") 
#mtext("Decomposition & Threshold", side = 3, outer = TRUE, 
#    cex = 1.2, line = 1)

# Reconstruction
#out.rec <- swr(out.univ)
#sw.plot(z=out.rec, type="recon", xlab="", ylab="")