rggplot2overlaycontourggmap
Overlay multiple data with 2D density using different colours onto ggmap
I feel like I've been endlessly searching for a solution to this and cannot find one anywhere. Basically, I need to overlay coloured contour maps as different layers (with different colours) onto a ggmap and cannot get this to work for my life. What I'm trying to do is take the example illustrated here: Overlay two ggplot2 stat_density2d plots with alpha channels only instead of mapping this onto a ggplot(), map it onto a ggmap(). I've read here: ggmap with geom_map superimposed that part of the difficulty in this is nullifying the implicit aesthetics sent from ggmap to ggplot, but I always encounter a whole series of errors regardless of what I do. Some of the errors I've encountered come from not recognizing 'group'. Use of geom_contour gives the following error when using the same format as below (z=X3):
Error in contourLines(x = sort(unique(data$x)), y = sort(unique(data$y)), :
no proper 'z' matrix specified
Part of the difficulty has also been with assigning different colours to the variables. Binding the columns (as done below and in the example linked above) and distinguishing variable a form variable B in column X3 by having an "a" or a "b" in the fourth column 'groups' does not seem to register that well with the scale_color_manual(). Ultimately, I'm trying to find a way of assigning a different color to each column of a data.frame - any thoughts on that would also be helpful.
I've included an example dataset and one of my approaches + errors - any help with this at all would be greatly appreciated (thank you in advance for your time/consideration)! Please let me know if there's anything else I can do to assist!
library(ggplot2)
library(ggmap)
#location defined by lon/lat coordinates
location <- c(-74.03990, 40.52726, -73.68864, 40.81141)
map <- get_map(location = location, scale="auto", zoom=11)
map2 <- ggmap(map)
map2 + stat_density2d(data=d, geom="density2d", aes(x=d[,1],y=d[,2], z=d[,3], color = group,alpha=..level..),size=2, contour=TRUE) +
scale_color_manual(values=c("a"="#FF0000", "b"="#00FF00"))
#Following error received: Error in if (any(h <= 0)) stop("bandwidths must be strictly positive") :
missing value where TRUE/FALSE needed
#Dataset (d):
d = read.table(header=TRUE, text="
X1 X2 X3 group
40.7462 -73.71148 2291 a
40.7566 -73.71418 291 a
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40.76221 -73.93153 7420 a
40.74512 -73.95693 9 a
NA NA 0 a
40.78075-73.8253 9 a
NA NA 138 a
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NA NA 11 a
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NA NA 18 a
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NA NA 433 a
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NA NA 0 a
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NA NA 0 a
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NA NA 6 a
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NA NA 987 a
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NA NA 0 a
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40.78485 -73.84128 7983 a
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NA NA 0 a
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NA NA 0 a
NA NA 0 a
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NA NA 0 a
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NA NA 0 a
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NA NA 0 a
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NA NA 0 a
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40.74512 -73.95693 26 b
NA NA 0 b
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NA NA 422 b
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40.72093 -73.84615 104323 b
40.74482 -73.90516 87453 b
40.72474 -73.90964 148989 b
40.71675 -73.8796 20918 b
NA NA 31 b
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NA NA 75 b
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40.70792 -73.82821 19029 b
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40.60775 -74.02394 0 b
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40.7309 -73.74566 22605 b
40.72102 -73.74224 12583 b
40.70977 -73.73865 7087 b
40.64696 -73.78481 293941 b
NA NA 1996 b
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40.67681 -73.77643 71514 b
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40.67581 -73.79662 2807 b
NA NA 0 b
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NA NA 0 b
40.60128 -73.76165 64099 b
40.59409 -73.7929 10962 b
40.59069 -73.80975 4070 b
40.57827 -73.84476 12337 b
NA NA 59 b
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40.7566 -73.71418 3325 b
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40.74512 -73.95693 853 b
NA NA 36030 b
40.78075 -73.8253 0 b
NA NA 0 b
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40.75145 -73.82103 168220 b
40.78485 -73.84128 88312 b
40.78639 -73.81086 158064 b
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40.72093 -73.84615 182240 b
40.74482 -73.90516 143954 b
40.72474 -73.90964 176588 b
40.71675 -73.8796 32620 b
NA NA 0 b
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NA NA 0 b
NA NA 0 b
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40.64696 -73.78481 348916 b
NA NA 282 b
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40.67581 -73.79662 7434 b
NA NA 0 b
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NA NA 1480 b
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40.59409 -73.7929 14203 b
40.59069 -73.80975 10872 b
40.57827 -73.84476 18295 b
NA NA 0 b
40.55569 -73.92066 0 b
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40.7566 -73.71418 8573 c
40.74715 -73.93975 1843805 c
40.77288 -73.9263 133615 c
40.76257 -73.91345 137850 c
40.74463 -73.9202 81181 c
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40.74512 -73.95693 301 c
NA NA 0 c
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NA NA 1971 c
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40.75145 -73.82103 419811 c
40.78485 -73.84128 259427 c
40.78639 -73.81086 193106 c
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40.72093 -73.84615 438112 c
40.74482 -73.90516 394896 c
40.72474 -73.90964 629891 c
40.71675 -73.8796 92917 c
NA NA 124 c
40.70067 -73.88943 460613 c
NA NA 538 c
40.69402 -73.73622 15340 c
40.6981 -73.75899 20866 c
40.67166 -73.75257 136822 c
40.6576 -73.8448 49428 c
40.70792 -73.82821 80721 c
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40.7309 -73.74566 91395 c
40.72102 -73.74224 44871 c
40.70977 -73.73865 31075 c
40.64696 -73.78481 1221994 c
NA NA 7483 c
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40.70126 -73.8096 133303 c
40.67581 -73.79662 12025 c
NA NA 0 c
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NA NA 0 c
40.60128 -73.76165 268753 c
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NA NA 441 c
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40.74715 -73.93975 3241581 c
40.77288 -73.9263 261306 c
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NA NA 105752 c
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NA NA 0 c
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40.75145 -73.82103 744570 c
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NA NA 0 c
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NA NA 0 c
NA NA 0 c
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40.7309 -73.74566 96879 c
40.72102 -73.74224 58815 c
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NA NA 1223 c
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NA NA 0 c
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NA NA 6474 c
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NA NA 0 c
40.55569 -73.92066 12386 c
40.65856 -73.83793 5476703540 c
40.65856 -73.83793 5342856179 c
40.65856 -73.83793 6195156100 c
40.65856 -73.83793 5515386851 c
40.7462 -73.71148 192 d
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NA NA 28 d
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NA NA 25 d
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NA NA 4 d
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NA NA 6 d
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40.60775 -74.02394 1 d
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NA NA 25 d
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40.69816 -73.78689 252 d
40.67681 -73.77643 817 d
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NA NA 8 d
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NA NA 4 d
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NA NA 5 d
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40.76221 -73.93153 1028 d
40.74512 -73.95693 34 d
NA NA 33 d
40.78075 -73.8253 1 d
NA NA 8 d
40.76821 -73.8274 2704 d
40.75145 -73.82103 1832 d
40.78485 -73.84128 702 d
40.78639 -73.81086 917 d
40.76047 -73.79637 1160 d
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40.73963 -73.79449 643 d
40.72815 -73.78502 449 d
40.73014 -73.82703 582 d
40.75172 -73.85182 1277 d
40.76336 -73.87237 280 d
40.76539 -73.89324 297 d
40.77389 -73.87348 95 d
40.75169 -73.88364 1629 d
40.73884 -73.87853 1498 d
40.72642 -73.86153 1089 d
40.72093 -73.84615 2060 d
40.74482 -73.90516 1492 d
40.72474 -73.90964 1101 d
40.71675 -73.8796 543 d
NA NA 2 d
40.70067 -73.88943 1742 d
NA NA 2 d
NA NA 2 d
40.69402 -73.73622 140 d
40.6981 -73.75899 239 d
40.67166 -73.75257 433 d
40.6576 -73.8448 438 d
40.70792 -73.82821 419 d
40.68465 -73.84955 393 d
40.67645 -73.84444 391 d
40.70027 -73.83597 718 d
40.68867 -73.82292 682 d
40.67358 -73.81773 373 d
40.69406 -73.85863 443 d
40.66006 -73.73601 307 d
40.71561 -73.76847 359 d
40.7143 -73.82726 7 d
40.60775 -74.02394 3 d
40.73642 -73.72238 248 d
40.7309 -73.74566 237 d
40.72102 -73.74224 310 d
40.70977 -73.73865 222 d
40.64696 -73.78481 342 d
NA NA 13 d
40.71536 -73.79307 1220 d
40.69816 -73.78689 298 d
40.67681 -73.77643 939 d
40.70126 -73.8096 823 d
40.67581 -73.79662 98 d
NA NA 27 d
40.70128 -73.79597 3 d
NA NA 9 d
40.60128 -73.76165 490 d
40.59409 -73.7929 90 d
40.59069 -73.80975 132 d
40.57827 -73.84476 330 d
NA NA 2 d
40.55569 -73.92066 48 d")
Solution
The primary problem seems to be solved by using the correct columns for x and y aesthetics:
p = map2 +
stat_density2d(aes(x=X2 ,y=X1, z=X3, color=group, alpha=..level..),
data=d, size=2, contour=TRUE)
ggsave("map.png", plot=p, height=7, width=7)
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