Check results for 'BARD'

using R version 2.10.0 Patched (2009-11-03 r50304)
using session charset: UTF-8
checking for file 'BARD/DESCRIPTION' ... OK
checking extension type ... Package
this is package 'BARD' version '1.05'
checking package name space information ... OK
checking package dependencies ... OK
checking if this is a source package ... OK
checking whether package 'BARD' can be installed ... OK
checking package directory ... OK
checking for portable file names ... OK
checking for sufficient/correct file permissions ... OK
checking DESCRIPTION meta-information ... OK
checking top-level files ... OK
checking index information ... OK
checking package subdirectories ... OK
checking R files for non-ASCII characters ... OK
checking R files for syntax errors ... OK
checking whether the package can be loaded ... OK
checking whether the package can be loaded with stated dependencies ... OK
checking whether the name space can be loaded with stated dependencies ... OK
checking for unstated dependencies in R code ... OK
checking S3 generic/method consistency ... OK
checking replacement functions ... OK
checking foreign function calls ... OK
checking R code for possible problems ... OK
checking Rd files ... OK
checking Rd metadata ... OK
checking Rd cross-references ... OK
checking for missing documentation entries ... OK
checking for code/documentation mismatches ... OK
checking Rd \usage sections ... OK
checking line endings in C/C++/Fortran sources/headers ... OK
checking line endings in Makefiles ... OK
checking for portable compilation flags in Makevars ... OK
checking for portable use of $BLAS_LIBS ... OK
checking examples ... ERROR
Running examples in 'BARD-Ex.R' failed.
The error most likely occurred in:

> ### * BARD.package
>
> flush(stderr()); flush(stdout())
>
> ### Name: BARD-package
> ### Title: A package for better automated redistricting.
> ### Aliases: BARD-package BARD
> ### Keywords: spatial IO spatial optimize models distribution
>
> ### ** Examples
>
>
> suffolk.map <- importBardShape(
+ file.path(system.file("shapefiles", package="BARD"),"suffolk_tracts")
+ )
Shapefile type: Polygon, (5), # of Shapes: 320
>
>
> numberdists <- 5
> kplan <- createKmeansPlan(suffolk.map,numberdists)
> rplan <- createRandomPlan(suffolk.map,numberdists)
> rplan2 <- createRandomPopPlan(suffolk.map,numberdists)
> plot(kplan)
>
> reportPlans(plans=list("kmeans"=kplan,"random 1"=rplan,"random pop"=rplan2), doplot=TRUE)
Plan Scores

Plan DistrictID RecodedID Contiguity Holes LW Compact Reock
1 kmeans 1 1 0.0000000 NA 0.08745115 0.3883830
2 kmeans 2 2 0.0000000 NA 0.13276734 0.6475287
3 kmeans 3 3 0.0000000 NA 0.07392494 0.5432474
4 kmeans 4 4 0.0000000 NA 0.37793995 0.6615332
5 kmeans 5 5 0.0000000 NA 0.15240584 0.5042317
6 kmeans Total Total 0.0000000 0 0.82448922 2.7449241
7 random 1 1 2 0.9655172 NA 0.52801530 0.8986329
8 random 1 2 3 0.9687500 NA 0.60587172 0.9635140
9 random 1 3 5 0.9642857 NA 0.60656867 0.9199742
10 random 1 4 1 0.9666667 NA 0.57862408 0.9124522
11 random 1 5 4 0.9565217 NA 0.73649144 0.9637701
12 random 1 Total Total 4.8217414 0 3.05557122 4.6583433
13 random pop 1 5 0.9705882 NA 0.73142962 0.9600882
14 random pop 2 4 0.9655172 NA 0.58192456 0.8923634
15 random pop 3 3 0.9642857 NA 0.55893342 0.9603486
16 random pop 4 2 0.9600000 NA 0.61155854 0.8698290
17 random pop 5 1 0.9696970 NA 0.51182008 0.9621503
18 random pop Total Total 4.8300882 0 2.99566623 4.6447795

Plan Differences

Comparing plan kmeans with plan random 1 :

Dist ID New ID # of original blocks # Blocks Removed # Added % Shared
1 1 2 93 72 45 15.20
2 2 3 39 29 51 11.10
3 3 5 103 78 47 16.70
4 4 1 21 16 49 7.14
5 5 4 64 54 57 8.26
Holes NA NA 0 0 0 NA

Comparing plan kmeans with plan random pop :

Dist ID New ID # of original blocks # Blocks Removed # Added % Shared
1 1 5 93 72 42 15.60
2 2 4 39 28 51 12.20
3 3 3 103 76 41 18.80
4 4 2 21 16 60 6.17
5 5 1 64 53 51 9.57
Holes NA NA 0 0 0 NA
>
> ## Not run:
> ##D if (require("iplots",quietly=TRUE)) {
> ##D rplan<-editPlanInteractive(rplan,calcPopScore,predvar="POP")
> ##D }
> ##D
> ## End(Not run)
>
> myScore<-function(plan,...) {
+ return(calcContiguityScore(plan,...))
+ }
>
> #just for quick demonstration -- nelder method not effective
>
> improvedRplan<-refineNelderPlan(plan=rplan2, score.fun=myScore, displaycount=100, historysize=0, dynamicscoring=FALSE, tracelevel=1, maxit=100)
[1] "Score 0.96969696969697 0.96 0.964285714285714 0.96551724137931 0.970588235294118 iteration 100 2009-11-06 11:26:08"
[1] "Iterations: 100 ( 0.96969696969697 0.96 0.964285714285714 0.96551724137931 0.970588235294118 ) 2009-11-06 11:26:09"
[1] "Score 0.96969696969697 0.96 0.964285714285714 0.96551724137931 0.970588235294118 iteration 200 2009-11-06 11:26:09"
[1] "Iterations: 200 ( 0.96969696969697 0.96 0.964285714285714 0.96551724137931 0.970588235294118 )* 2009-11-06 11:26:09"
[1] "Score 0.96969696969697 0.96 0.964285714285714 0.96551724137931 0.970588235294118 iteration 300 2009-11-06 11:26:09"
[1] "Iterations: 300 ( 0.96969696969697 0.96 0.964285714285714 0.96551724137931 0.970588235294118 )* 2009-11-06 11:26:09"
>
> ## Not run:
> ##D # This works better, but will take a while
> ##D improvedRplan<-refineAnnealPlan(plan=rplan2, score.fun=myScore, historysize=0, dynamicscoring=FALSE, tracelevel=1)
> ## End(Not run)
>
> samples<-samplePlans(kplan, score.fun=myScore, ngenplans=10, gen.fun = "createRandomPlan", refine.fun="refineNelderPlan",refine.args=list(maxit=200,dynamicscoring=TRUE))
[1] "Generating plan # 1"
[1] "Generating plan # 2"
[1] "Generating plan # 3"
[1] "Generating plan # 4"
[1] "Generating plan # 5"
[1] "Generating plan # 6"
[1] "Generating plan # 7"
[1] "Generating plan # 8"
[1] "Generating plan # 9"
[1] "Generating plan # 10"
[1] "Starting refinement phase"
[1] "Refining plan..."

*** caught segfault ***
address 0x2b38425d2000, cause 'invalid permissions'

Traceback:
1: optim(plan, nelderScoreFun, method = "Nelder-Mead", control = control)
2: refineNelderPlan(maxit = 200, dynamicscoring = TRUE, plan = iplan, score.fun = score.fun)
3: do.call(refine.fun, myargs)
4: FUN(X[[1L]], ...)
5: lapply(X, FUN, ...)
6: lapplyBardCluster(combinedplans, myrefplan)
7: samplePlans(kplan, score.fun = myScore, ngenplans = 10, gen.fun = "createRandomPlan", refine.fun = "refineNelderPlan", refine.args = list(maxit = 200, dynamicscoring = TRUE))
aborting ...