[R] Help with spTransform() function and final plot colors
Poling, William
Po||ngW @end|ng |rom @etn@@com
Sun May 17 12:20:18 CEST 2020
Hello, I have found an additional problem.
I should be getting 3 columns back in the xy using data at some point.
$ ID : int 1 2 3 4 5 6 7 8 9 10 ...
# $ Clust : int 1 1 1 1 1 1 1 1 1 1 ... This is always - 1
# $ Clust.1 : int 1 1 1 1 1 1 1 1 1 1 ... This would be the cluster number, like 1-3, I am not getting this column back?
Yet the plot runs and indicates three different clusters?
WHP
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-----Original Message-----
From: Poling, William <PolingW using aetna.com>
Sent: Sunday, May 17, 2020 4:50 AM
To: r-help using r-project.org
Cc: Poling, William <PolingW using aetna.com>
Subject: Help with spTransform() function and final plot colors
#RStudio Version Version 1.2.1335
sessionInfo()
# R version 4.0.0 Patched (2020-05-03 r78349)
#Platform: x86_64-w64-mingw32/x64 (64-bit) #Running under: Windows 10 x64 (build 17763)
Hello. I am running my data through a routine I found that finds clusters of data points based on distance rule.
https://gis.stackexchange.com/questions/64392/finding-clusters-of-points-based-distance-rule-using-r
1. I get this error when I get to this point in the routine, see complete routine below?
xy <- spTransform(xy, CRS("+init=epsg:27700 +datum=WGS84")) non finite transformation detected:
I tried converting columns from numeric to Integer but did not help.
However, I continue to run the rest of the routine and the final sequence, the plot itself, seems to work Can this error be corrected somehow, despite the fact that it continues to work, just curious what it is I guess"
2. However in the plot at the end of the routine the color key appears with the colors but the clusters in the plot are black, see plot call at the end of the routine below?
Thank you for any advice.
WHP
ERROR:
non finite transformation detected:
coords.x1 coords.x2
[1,] -119.7339 39.53939 Inf Inf
[2,] -119.7665 39.39630 Inf Inf
[3,] -119.7794 39.28768 Inf Inf
[4,] -121.0234 39.20503 Inf Inf
[5,] -122.0047 47.19262 Inf Inf
[6,] -122.0135 47.18883 Inf Inf
[7,] -122.0379 47.52190 Inf Inf
[8,] -122.0578 47.60975 Inf Inf
[9,] -122.1330 47.13669 Inf Inf
[10,] -122.1509 47.55962 Inf Inf
[11,] -122.1706 47.15546 Inf Inf
[12,] -122.1846 47.23485 Inf Inf
[13,] -122.1846 48.15307 Inf Inf
[14,] -122.1851 47.44870 Inf Inf
[15,] -122.1954 47.68485 Inf Inf
[16,] -122.1990 47.51610 Inf Inf
[17,] -122.2014 47.44772 Inf Inf
[18,] -122.2025 47.69815 Inf Inf
[19,] -122.2037 47.67190 Inf Inf
[20,] -122.2090 47.40378 Inf Inf
[21,] -122.2108 47.25336 Inf Inf
[22,] -122.2291 47.63880 Inf Inf
[23,] -122.2419 47.76870 Inf Inf
[24,] -122.2722 48.04803 Inf Inf
[25,] -122.2732 47.87700 Inf Inf
[26,] -122.2804 47.77620 Inf Inf
[27,] -122.2839 47.82103 Inf Inf
[28,] -122.2890 47.86899 Inf Inf
[29,] -122.2993 47.67306 Inf Inf
[30,] -122.3180 47.38217 Inf Inf
[31,] -122.3270 47.40378 Inf Inf
[32,] -122.3474 47.43884 Inf Inf
[33,] -122.3484 47.53083 Inf Inf
[34,] -122.3581 47.27678 Inf Inf
[35,] -122.3618 47.76735 Inf Inf
[36,] -122.3700 47.56567 Inf Inf
[37,] -122.3908 47.54938 Inf Inf
[38,] -122.4128 47.64622 Inf Inf
[39,] -122.4293 47.17660 Inf Inf
[40,] -122.4621 47.44505 Inf Inf
[41,] -122.4904 47.27460 Inf Inf
[42,] -122.5515 46.93979 Inf Inf
[43,] -122.7348 42.37320 Inf Inf
[44,] -122.7827 47.31059 Inf Inf
[45,] -122.7987 47.23475 Inf Inf
[46,] -122.8385 42.35119 Inf Inf
[47,] -122.8537 42.34495 Inf Inf
[48,] -122.8904 42.39555 Inf Inf
[49,] -122.8927 42.33022 Inf Inf
[50,] -122.9451 47.37574 Inf Inf
[51,] -122.9594 42.30376 Inf Inf
[52,] -123.0641 47.16428 Inf Inf
[53,] -123.3413 42.44117 Inf Inf
Error in spTransform(xSP, CRSobj, ...) :
failure in points 1:2:3:4:5:6:7:8:9:10:11:12:13:14:15:16:17:18:19:20:21:22:23:24:25:26:27:28:29:30:31:32:33:34:35:36:37:38:39:40:41:42:43:44:45:46:47:48:49:50:51:52:53
In addition: Warning message:
In spTransform(xSP, CRSobj, ...) : 53 projected point(s) not finite
Here is the data:
dput(sample)
structure(list(ID = 1:53, Longitude = c(-119.733899, -119.766493, -119.779416, -121.0234, -122.004736, -122.013456, -122.0379, -122.0578, -122.132971, -122.150901, -122.170608, -122.18462, -122.184639, -122.185079, -122.195398, -122.198994, -122.201356, -122.202507, -122.20371, -122.209047, -122.210797, -122.229095, -122.2419, -122.27216, -122.273164, -122.280355, -122.28389, -122.289043, -122.299261, -122.318009, -122.326987, -122.347382, -122.34844, -122.358115, -122.361839, -122.37003, -122.390815, -122.41282, -122.429323, -122.462136, -122.490417, -122.551483, -122.734847, -122.782736, -122.798669, -122.838498, -122.853683, -122.8904, -122.89271, -122.94511, -122.959407, -123.064087, -123.341346), Latitude = c(39.53939, 39.396298, 39.287681, 39.205028, 47.192616, 47.188833, 47.5219, 47.609748, 47.13669, 47.559616, 47.155455, 47.234849, 48.15307, 47.448697, 47.684854, 47.516104, 47.447723, 47.698146, 47.6719, 47.403778, 47.253364, 47.638795, 47.768701, 48.048027, 47.876997, 47.776205, 47.821029, 47.868987, 47.673056, 47.382165, 47.403785, 47.438836, 47.530831, 47.276776, 47.76735, 47.565667, 47.549377, 47.646222, 47.176596, 47.445053, 47.274599, 46.939789, 42.373195, 47.310595, 47.234748, 42.351189, 42.344953, 42.395547, 42.33022, 47.375736, 42.303755, 47.164278, 42.441172)), class = "data.frame", row.names = c(NA, -53L))
Here is the routine:
require(sp)
require(rgdal)
#25*1609.34 = 40233.5
dis <- 40233.5 #Distance threshold 25miles converted to meters
x <- tmp1b[,c(6)]
head(x)
y <- tmp1b[,c(5)]
head(y)
str(y)
xy <- SpatialPointsDataFrame(matrix(c(x,y), ncol=2), data.frame(ID=seq(1:length(x))),
proj4string=CRS("+proj=longlat +ellps=WGS84 +datum=WGS84"))
str(xy)
xy <- spTransform(xy, CRS("+init=epsg:27700 +datum=WGS84"))#Error occurring here?
chc <- hclust(dist(data.frame(rownames=rownames(xy using data), x=coordinates(xy)[,1], #What is xy using data???? see str(xy)
y=coordinates(xy)[,2])), method="complete")
str(chc)
view(xy using data)#Look like 3 clusters
# Distance with a 25 Mile threshold
chc.dis <- cutree(chc, h=dis)
str(chc.dis)
view(chc.dis)
# Join results to meuse sp points
xy using data <- data.frame(xy using data, Clust=chc.dis)
str(xy using data)
view(xy using data)
# Plot results
plot(xy, col=factor(xy using data$Clust), pch=19)
box(col="black")
title(main="Clustering")
legend("topleft", legend=paste("Cluster", 1:3,sep=""),#Change from 4 in demo to 3 in my data
col=palette()[1:3], pch=rep(19,3), bg="white")
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