From 7a8506e6e55d369a11b1f52b3b14f04b61d3bd4a Mon Sep 17 00:00:00 2001 From: Roger Bivand Date: Tue, 10 Sep 2024 16:35:29 +0200 Subject: [PATCH] update docs --- docs/articles/CO69.html | 6 ++-- docs/articles/nb_sf.html | 28 ++++++++-------- docs/articles/subgraphs.html | 6 ++-- docs/pkgdown.yml | 2 +- docs/reference/bhicv.html | 2 +- docs/reference/compon.html | 4 +-- docs/reference/dnearneigh.html | 10 +++--- docs/reference/joincount.multi.html | 50 +++++++++++++++++++++++++++++ docs/reference/knearneigh.html | 4 +-- docs/reference/licd_multi.html | 42 ++++++++++++++++++++++++ docs/reference/localC.html | 4 +-- docs/reference/mstree.html | 2 +- docs/reference/nb2lines.html | 8 ++--- docs/reference/poly2nb.html | 4 +-- docs/reference/read.gwt2nb.html | 2 +- docs/reference/skater.html | 6 ++-- docs/search.json | 2 +- man/joincount.multi.Rd | 27 ++++++++++++++++ man/licd_multi.Rd | 30 +++++++++++++++++ 19 files changed, 194 insertions(+), 45 deletions(-) diff --git a/docs/articles/CO69.html b/docs/articles/CO69.html index f89106aa..ed42e027 100644 --- a/docs/articles/CO69.html +++ b/docs/articles/CO69.html @@ -548,7 +548,7 @@

Measures of spatial autocorrelation Prop_stdR <- lapply(vars, function(x) moran.test(eire_ge1[[x]], listw=lw_std, randomisation=TRUE)) }) 
##    user  system elapsed 
-##    0.12    0.00    0.12
+## 0.112 0.001 0.113 
 res <- sapply(c("MoranN", "MoranR", "GearyN", "GearyR", "Prop_unstdN", "Prop_unstdR", "Prop_stdN", "Prop_stdR"), function(x) sapply(get(x), "[[", "statistic"))
 rownames(res) <- vars
@@ -780,7 +780,7 @@ 
Simulating measures of s
 Prop_stdSad  <- lapply(lm_objs, function(x) lm.morantest.sad(x, listw=lw_std))
 })
##    user  system elapsed 
-##   0.066   0.000   0.066
+## 0.065 0.000 0.066 
 res <- sapply(c("MoranSad", "Prop_unstdSad", "Prop_stdSad"), function(x) sapply(get(x), "[[", "statistic"))
 rownames(res) <- vars
@@ -843,7 +843,7 @@

Simulating measures of s Prop_stdEx <- lapply(lm_objs, function(x) lm.morantest.exact(x, listw=lw_std)) }) 
##    user  system elapsed 
-##   0.082   0.000   0.082
+## 0.083 0.000 0.084 
 res <- sapply(c("MoranEx", "Prop_unstdEx", "Prop_stdEx"), function(x) sapply(get(x), "[[", "statistic"))
 rownames(res) <- vars
diff --git a/docs/articles/nb_sf.html b/docs/articles/nb_sf.html index 7eda3152..6a4a79f7 100644 --- a/docs/articles/nb_sf.html +++ b/docs/articles/nb_sf.html @@ -230,7 +230,7 @@

Contiguity neighbours for pol eps <- sqrt(.Machine$double.eps) system.time(for(i in 1:reps) NY8_sf_1_nb <- poly2nb(NY8_sf, queen=TRUE, snap=eps))/reps 
##    user  system elapsed 
-##  0.1853  0.0094  0.1960
+## 0.2036 0.0089 0.2136

Using spatial indices to check intersection of polygons is much faster than the legacy method in poly2nb. From spdep 1.1-7, use is made of GEOS through sf to find candidate @@ -406,12 +406,12 @@

K-nearest neighbours
 system.time(for (i in 1:reps) suppressWarnings(NY88_nb_sf <- knn2nb(knearneigh(NY8_ct_sf, k=1))))/reps
##    user  system elapsed 
-##  0.0271  0.0013  0.0286
+## 0.0232 0.0007 0.0240

Legacy code may be used omitting the kd-tree:

 system.time(for (i in 1:reps) suppressWarnings(NY89_nb_sf <- knn2nb(knearneigh(NY8_ct_sf, k=1, use_kd_tree=FALSE))))/reps
##    user  system elapsed 
-##  0.0263  0.0019  0.0284
+## 0.0233 0.0012 0.0246

Distance neighbours @@ -430,7 +430,7 @@

Distance neighbours
 system.time(for (i in 1:reps) suppressWarnings(NY810_nb <- dnearneigh(NY8_ct_sf, d1=0, d2=0.75*max_1nn)))/reps

##    user  system elapsed 
-##  0.0619  0.0013  0.0634
+## 0.0606 0.0012 0.0621

By default, the function uses dbscan::frNN() to build a kd-tree in 2D or 3D which is then used to find distance neighbours. For small n, the argument use_kd_tree=FALSE may speed up @@ -440,7 +440,7 @@

Distance neighbours
 system.time(for (i in 1:reps) suppressWarnings(NY811_nb <- dnearneigh(NY8_ct_sf, d1=0, d2=0.75*max_1nn, use_kd_tree=FALSE)))/reps
##    user  system elapsed 
-##  0.0469  0.0008  0.0479
+## 0.0445 0.0013 0.0459
@@ -470,7 +470,7 @@

K-nearest neighbourssf_use_s2(TRUE) system.time(for (i in 1:reps) pts_ll1_nb <- knn2nb(knearneigh(pts_ll, k=6)))/reps

##    user  system elapsed 
-##  0.0331  0.0001  0.0332
+## 0.0325 0.0000 0.0327

For this smaller data set, the legacy approach without spatial indexing is adequate, but slows down as the number of observations increases:

@@ -480,7 +480,7 @@

K-nearest neighbours
 system.time(for (i in 1:reps) pts_ll2_nb <- knn2nb(knearneigh(pts_ll, k=6)))/reps
##    user  system elapsed 
-##  0.0287  0.0001  0.0289
+## 0.0281 0.0001 0.0282

The WGS84 ellipsoid Great Circle distances differ a very little from the s2 spherical distances, yielding output that here diverges for two tract centroids:

@@ -535,7 +535,7 @@

Distance neighbours=0.75*max_1nn_ll)))/(reps/5) } 
##    user  system elapsed 
-##   0.068   0.000   0.068
+## 0.0665 0.0000 0.0665

Alternatively, spherical distances can be used with dwithin=FALSE and s2::s2_closest_edges(); although running in similar time, s2::s2_closest_edges() @@ -544,7 +544,7 @@

Distance neighbours
 system.time(for (i in 1:(reps/5)) suppressWarnings(pts_ll5_nb <- dnearneigh(pts_ll, d1=0, d2=0.75*max_1nn_ll, dwithin=FALSE)))/(reps/5)
##    user  system elapsed 
-##   0.054   0.000   0.054
+## 0.0535 0.0000 0.0540 
 if (packageVersion("s2") > "1.0.7") all.equal(pts_ll3_nb, pts_ll5_nb, check.attributes=FALSE)
## [1] TRUE
@@ -557,7 +557,7 @@

Distance neighbours=0.75*max_1nn_ll, dwithin=FALSE)))/(reps/5) } 
##    user  system elapsed 
-##   0.048   0.000   0.048
+## 0.044 0.000 0.044

Using s2::s2_dwithin_matrix() requires a second pass, one for the lower bound, another for the upper bound, and a set difference operation to find neighbours in the distance band:

@@ -567,7 +567,7 @@

Distance neighbours=0.75*max_1nn_ll)))/(reps/5) } 
##    user  system elapsed 
-##  0.0895  0.0005  0.0905
+## 0.0865 0.0000 0.0865 
 if (packageVersion("s2") > "1.0.7") all.equal(pts_ll3a_nb, pts_ll5a_nb, check.attributes=FALSE)
## [1] TRUE
@@ -576,7 +576,7 @@

Distance neighbours
 system.time(for (i in 1:reps) suppressWarnings(pts_ll6_nb <- dnearneigh(pts_ll, d1=0, d2=0.75*max_1nn_ll, use_s2=FALSE)))/reps
##    user  system elapsed 
-##  0.0376  0.0000  0.0377
+## 0.0367 0.0000 0.0368

Minor differences may occur between the legacy ellipsoid and s2 spherical approaches:

@@ -606,7 +606,7 @@ 
Distance neighbours
 system.time(for (i in 1:reps) suppressWarnings(pts_ll6a_nb <- dnearneigh(pts_ll, d1=5, d2=0.75*max_1nn_ll, use_s2=FALSE)))/reps
##    user  system elapsed 
-##  0.0314  0.0001  0.0318
+## 0.0286 0.0001 0.0288 
 if (packageVersion("s2") > "1.0.7") all.equal(pts_ll5a_nb, pts_ll6a_nb, check.attributes=FALSE)
##  [1] "Component 20: Numeric: lengths (6, 5) differ"       
@@ -658,7 +658,7 @@ 
Contiguity neighbours for spherical polygon supportsf_use_s2(TRUE)
 system.time(for (i in 1:reps) NY8_sf_1_nb_ll <- poly2nb(NY8_sf_ll, queen=TRUE, snap=eps))/reps
##    user  system elapsed 
-##  0.1660  0.0016  0.1682
+## 0.1569 0.0024 0.1599 
 all.equal(NY8_sf_1_nb, NY8_sf_1_nb_ll, check.attributes=FALSE)
## [1] TRUE
diff --git a/docs/articles/subgraphs.html b/docs/articles/subgraphs.html index 91d90574..5c815182 100644 --- a/docs/articles/subgraphs.html +++ b/docs/articles/subgraphs.html @@ -179,7 +179,7 @@

No-neighbour observations w50m <- st_read(target) } 
## Reading layer `GB_2024_Wales_50m' from data source 
-##   `/tmp/RtmpPpr0yz/temp_libpathafa452560f839/spdep/etc/shapes/GB_2024_Wales_50m.gpkg.zip' 
+##   `/tmp/RtmpcuVtwS/temp_libpathba7861ea38876/spdep/etc/shapes/GB_2024_Wales_50m.gpkg.zip' 
 ##   using driver `GPKG'
 ## Simple feature collection with 32 features and 19 fields
 ## Geometry type: MULTIPOLYGON
@@ -371,7 +371,7 @@ 
Subgraphssc50m <- st_read(target)
 }
## Reading layer `GB_2024_southcoast_50m' from data source 
-##   `/tmp/RtmpPpr0yz/temp_libpathafa452560f839/spdep/etc/shapes/GB_2024_southcoast_50m.gpkg.zip' 
+##   `/tmp/RtmpcuVtwS/temp_libpathba7861ea38876/spdep/etc/shapes/GB_2024_southcoast_50m.gpkg.zip' 
 ##   using driver `GPKG'
 ## Simple feature collection with 119 features and 19 fields
 ## Geometry type: MULTIPOLYGON
@@ -654,7 +654,7 @@ 
Unintentional disconnected graphs    tokyo <- st_read(target)
 }
## Reading layer `tokyo' from data source 
-##   `/tmp/RtmpPpr0yz/temp_libpathafa452560f839/spdep/etc/shapes/tokyo.gpkg.zip' 
+##   `/tmp/RtmpcuVtwS/temp_libpathba7861ea38876/spdep/etc/shapes/tokyo.gpkg.zip' 
 ##   using driver `GPKG'
 ## Simple feature collection with 262 features and 3 fields
 ## Geometry type: MULTIPOLYGON
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index a91fa60a..8f9c3992 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -7,7 +7,7 @@ articles:
   nb: nb.html
   sids: sids.html
   subgraphs: subgraphs.html
-last_built: 2024-09-10T08:34Z
+last_built: 2024-09-10T14:30Z
 urls:
   reference: https://r-spatial.github.io/spdep/reference
   article: https://r-spatial.github.io/spdep/articles
diff --git a/docs/reference/bhicv.html b/docs/reference/bhicv.html
index e0475f4f..e5a01bb0 100644
--- a/docs/reference/bhicv.html
+++ b/docs/reference/bhicv.html
@@ -90,7 +90,7 @@ 
Examples    bh <- st_read(target)
 }
 #> Reading layer `bhicv' from data source 
-#>   `/tmp/RtmpPpr0yz/temp_libpathafa452560f839/spdep/etc/shapes/bhicv.gpkg.zip' 
+#>   `/tmp/RtmpcuVtwS/temp_libpathba7861ea38876/spdep/etc/shapes/bhicv.gpkg.zip' 
 #>   using driver `GPKG'
 #> Simple feature collection with 98 features and 8 fields
 #> Geometry type: POLYGON
diff --git a/docs/reference/compon.html b/docs/reference/compon.html
index 28873812..1b378eb2 100644
--- a/docs/reference/compon.html
+++ b/docs/reference/compon.html
@@ -189,12 +189,12 @@ 
Examplessystem.time(udir <- n.comp.nb(make.sym.nb(k6)))
 }
 #>    user  system elapsed 
-#>   2.104   0.000   2.111 
+#>   2.076   0.000   2.087 
 if (run) {
 system.time(dir <- n.comp.nb(k6))
 }
 #>    user  system elapsed 
-#>   0.701   0.003   0.707 
+#>   0.680   0.002   0.685 
 if (run) {
 udir$nc
 }
diff --git a/docs/reference/dnearneigh.html b/docs/reference/dnearneigh.html
index c226d66f..df95f316 100644
--- a/docs/reference/dnearneigh.html
+++ b/docs/reference/dnearneigh.html
@@ -222,14 +222,14 @@ 
Examples#> Warning: neighbour object has 11 sub-graphs
 system.time(o <- nbdists(gck1b, xy1))
 #>    user  system elapsed 
-#>   0.007   0.000   0.007 
+#>   0.006   0.000   0.006 
 (all.linked <- max(unlist(o)))
 #> [1] 522.4464
 # use s2 brute-force dwithin_matrix approach for s2 <= 1.0.7
 system.time(gc.nb.dwithin <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, dwithin=TRUE))
 #> Warning: neighbour object has 3 sub-graphs
 #>    user  system elapsed 
-#>   0.012   0.000   0.011 
+#>   0.011   0.001   0.012 
 summary(gc.nb, xy1, scale=0.5)
 #> Neighbour list object:
 #> Number of regions: 48 
@@ -251,13 +251,13 @@ 
Examples}
 #> Warning: neighbour object has 3 sub-graphs
 #>    user  system elapsed 
-#>    0.01    0.00    0.01 
+#>   0.010   0.000   0.009 
 if (packageVersion("s2") > "1.0.7") {
 system.time(gc.nb.dwithin <- dnearneigh(xy1, 0, all.linked, use_s2=TRUE, dwithin=TRUE))
 }
 #> Warning: neighbour object has 3 sub-graphs
 #>    user  system elapsed 
-#>   0.012   0.000   0.012 
+#>   0.012   0.000   0.011 
 if (packageVersion("s2") > "1.0.7") {
 summary(gc.nb.dwithin, xy1, scale=0.5)
 }
@@ -300,7 +300,7 @@ 
Examplessystem.time(gc.nb.legacy <- dnearneigh(xy1, 0, all.linked, use_s2=FALSE))
 #> Warning: neighbour object has 3 sub-graphs
 #>    user  system elapsed 
-#>   0.007   0.000   0.006 
+#>   0.006   0.000   0.006 
 summary(gc.nb, xy1, scale=0.5)
 #> Neighbour list object:
 #> Number of regions: 48 
diff --git a/docs/reference/joincount.multi.html b/docs/reference/joincount.multi.html
index 53c169cc..3c028905 100644
--- a/docs/reference/joincount.multi.html
+++ b/docs/reference/joincount.multi.html
@@ -229,6 +229,56 @@ 
Examplescat("replicates Upton & Fingleton table 3.7 (p. 169)\n")
 #> replicates Upton & Fingleton table 3.7 (p. 169)
 # }
+GDAL37 <- as.numeric_version(unname(sf_extSoftVersion()["GDAL"])) >= "3.7.0"
+file <- "etc/shapes/GB_2024_southcoast_50m.gpkg.zip"
+zipfile <- system.file(file, package="spdep")
+if (GDAL37) {
+    sc50m <- st_read(zipfile)
+} else {
+    td <- tempdir()
+    bn <- sub(".zip", "", basename(file), fixed=TRUE)
+    target <- unzip(zipfile, files=bn, exdir=td)
+    sc50m <- st_read(target)
+}
+#> Reading layer `GB_2024_southcoast_50m' from data source 
+#>   `/tmp/RtmpcuVtwS/temp_libpathba7861ea38876/spdep/etc/shapes/GB_2024_southcoast_50m.gpkg.zip' 
+#>   using driver `GPKG'
+#> Simple feature collection with 119 features and 19 fields
+#> Geometry type: MULTIPOLYGON
+#> Dimension:     XY
+#> Bounding box:  xmin: 82643.12 ymin: 5342.9 xmax: 640301.6 ymax: 187226.2
+#> Projected CRS: OSGB36 / British National Grid
+plot(sc50m[,"Winner"], pal=c("#2297E6", "#61D04F", "#DF536B", "#F5C710"))
+
+nb_sc_50m <- poly2nb(sc50m, row.names=as.character(sc50m$Constituency))
+#> Warning: neighbour object has 2 sub-graphs;
+#> if this sub-graph count seems unexpected, try increasing the snap argument.
+sub2 <- attr(nb_sc_50m, "region.id")[attr(nb_sc_50m, "ncomp")$comp.id == 2L]
+iowe <- match(sub2[1], attr(nb_sc_50m, "region.id"))
+diowe <- c(st_distance(sc50m[iowe,], sc50m))
+meet_criterion <- sum(diowe <= units::set_units(5000, "m"))
+cands <- attr(nb_sc_50m, "region.id")[order(diowe)[1:meet_criterion]]
+nb_sc_50m_iowe <- addlinks1(nb_sc_50m, from = cands[1],
+ to = cands[3:meet_criterion])
+ioww <- match(sub2[2], attr(nb_sc_50m, "region.id"))
+dioww <- c(st_distance(sc50m[ioww,], sc50m))
+meet_criterion <- sum(dioww <= units::set_units(5000, "m"))
+cands <- attr(nb_sc_50m, "region.id")[order(dioww)[1:meet_criterion]]
+nb_sc_50m_iow <- addlinks1(nb_sc_50m_iowe, from = cands[2], to = cands[3:meet_criterion])
+nb_sc_1_2 <- nblag_cumul(nblag(nb_sc_50m_iow, 2))
+joincount.multi(factor(sc50m$Winner), nb2listw(nb_sc_1_2, style="B"))
+#>             Joincount Expected Variance z-value
+#> Con:Con      146.0000  84.4324 116.3530  5.7077
+#> Green:Green    0.0000   0.0000   0.0000     NaN
+#> LD:LD        100.0000  75.8866 103.9440  2.3651
+#> Lab:Lab       63.0000  98.1057 136.0379 -3.0099
+#> Green:Con      4.0000   4.4438   5.8532 -0.1834
+#> LD:Con       198.0000 164.4210 166.3583  2.6034
+#> LD:Green       4.0000   4.2159   5.4573 -0.0924
+#> Lab:Con      184.0000 186.6401 180.9233 -0.1963
+#> Lab:Green      3.0000   4.7856   6.4663 -0.7022
+#> Lab:LD        98.0000 177.0688 175.2035 -5.9736
+#> Jtot         491.0000 541.5753 153.6123 -4.0806