Edit: I've discovered one solution, which is to transform the 2d Temp matrix into a 1D array, re-running the code with just this matrix gave me the output I wanted i.e. plot coloured by height of z data. The code is below:
mycols<-colorRampPalette(c("dodgerblue", "firebrick"), space="rgb")
wireframe(Temp,
zlim=c(10,18),
ylab=list(label="Time", rot=-35), scales=list(arrows=FALSE),
zlab=list(label=expression(paste("Tw (", degree, "C)")), rot=94),
xlab=list(label="Distance downstream (m)", rot=35),
drape = T, shade=F, colorkey = T, aspect = c(1,1),
col.regions=mycols(200), col="black")
I'm using Windows 7, R version 2.15.0 and lattice_0.20-6.
I'm plotting observed data in lattice using wireframe, I have 3 matrices of observed values (Temp,Dist,Time) so I'm using the formula method (Temp~Dist*Time). How do I instruct wireframe to colour the wireframe based on the heights/ values of my z (Temp) data. At present my code produces a wireframe that colours the plot based on the values of my y (Time) data.
I attach below my code.
mycols<-colorRampPalette(c("dodgerblue", "firebrick"), space="rgb")
wireframe(Temp[1:13,97:193]~Dist[1:13,97:193]*Time[1:13,97:193],
zlim=c(10,18),
ylab=list(label="Time", rot=-35), scales=list(arrows=FALSE),
zlab=list(label=expression(paste("Tw (", degree, "C)")), rot=94),
xlab=list(label="Distance downstream (m)", rot=35),
drape = T, shade=F, colorkey = T, aspect = c(1,1),
col.regions=mycols(200), col="black")
Some sample data. Please excuse the naming of matrix columns:
structure(list(Tw1.1. = c(12.15, 11.18526437, 10.51390093, 10.134,
9.711, 9.597, 9.59, 9.557, 9.602, 9.673, 9.753, 10.017, 10.32
), Tw1.1..1 = c(11.97, 11.05071394, 10.39239194, 10.011, 9.63,
9.546, 9.59, 9.571, 9.648, 9.745, 9.837, 10.171, 10.49), Tw1.1..2 = c(11.79,
10.90182264, 10.26796411, 9.893, 9.563, 9.52, 9.6, 9.619, 9.713,
9.808, 9.956, 10.321, 10.6), Tw1.1..3 = c(11.64, 10.74647418,
10.14505213, 9.788, 9.526, 9.525, 9.62, 9.682, 9.787, 9.914,
10.105, 10.42, 10.7), Tw1.1..4 = c(11.52, 10.58632287, 10.01657543,
9.699, 9.514, 9.543, 9.67, 9.743, 9.885, 10.049, 10.249, 10.528,
10.79), Tw1.1..5 = c(11.39, 10.46294559, 9.879615153, 9.619,
9.529, 9.577, 9.74, 9.823, 10.017, 10.21, 10.361, 10.58, 10.84
), Tw1.1..6 = c(11.26, 10.3417786, 9.765186747, 9.576, 9.557,
9.645, 9.81, 9.933, 10.186, 10.344, 10.474, 10.664, 10.94), Tw1.1..7 = c(11.1,
10.22494533, 9.674806064, 9.546, 9.605, 9.717, 9.9, 10.072, 10.338,
10.453, 10.557, 10.76, 11.03), Tw1.1..8 = c(10.93, 10.1003152,
9.604424236, 9.549, 9.676, 9.8, 10, 10.244, 10.436, 10.561, 10.668,
10.848, 11.12), Tw1.1..9 = c(10.76, 9.970098496, 9.545171854,
9.577, 9.757, 9.891, 10.15, 10.399, 10.558, 10.667, 10.778, 10.941,
11.22), Tw1.1..10 = c(10.63, 9.858851801, 9.501869458, 9.611,
9.851, 10.014, 10.31, 10.503, 10.683, 10.789, 10.868, 11.059,
11.34), Tw1.1..11 = c(10.51, 9.770908839, 9.48413064, 9.676,
9.946, 10.164, 10.48, 10.632, 10.8, 10.89, 10.945, 11.152, 11.41
), Tw1.1..12 = c(10.4, 9.702806469, 9.508922546, 9.756, 10.074,
10.332, 10.59, 10.774, 10.905, 10.96, 11.031, 11.213, 11.48)), .Names = c("Tw1.1.",
"Tw1.1..1", "Tw1.1..2", "Tw1.1..3", "Tw1.1..4", "Tw1.1..5", "Tw1.1..6",
"Tw1.1..7", "Tw1.1..8", "Tw1.1..9", "Tw1.1..10", "Tw1.1..11",
"Tw1.1..12"), class = "data.frame", row.names = c("Open", "B8",
"B12", "B25", "B26", "B13", "UsAWS", "B19", "B5", "B3", "B27",
"B17", "DSAWS"))
Related
I need some help in overlaying a 2d density plot on top of a ggmap plot. I don't really know how to procede. Any help is welcome.
This is a subset of my data, including start and end coordinates for each individual ride of a fictional bike sharing company:
df <- structure(list(start_lat = c(41.94018, 41.890762, 41.845695,
41.857813, 41.9287386666667, 42.0044803333333, 41.879255, 41.886835,
41.874734, 41.95469, 41.95, 41.8809518333333, 41.96590013976,
41.909668, 41.931248, 41.96167, 41.912133, 41.87947235235, 41.936266,
41.922695, 41.9101756666667, 41.86, 41.91468, 41.892278, 42.03,
41.911386, 41.9716, 41.93, 41.940195, 41.9560855, 41.915784,
41.93314, 41.943739, 41.8671848333333, 41.87464, 41.882242, 41.926277,
41.96167, 41.76, 41.883668, 41.967096, 41.8, 41.9024035, 41.939743,
41.9093960065, 41.915983, 41.87772613, 41.8984238333333, 41.8836331666667,
41.925905, 41.967096, 41.92, 41.884576228, 41.838499, 41.9028846666667,
41.89993001, 41.8, 41.866095, 41.97, 41.9093960065, 41.88, 41.8922376666667,
41.81, 41.9438251666667, 41.883668, 41.9207793333333, 41.954383,
41.9434726666667, 41.8945555, 41.911386, 41.88917683258, 41.86722595682,
41.8531223333333, 41.92, 41.919936, 41.90096, 41.894722, 41.872187,
41.881892, 41.920082, 41.897448, 41.88917683258, 41.9, 41.925858,
41.89, 41.8908470406238, 41.85, 41.890173, 41.92556258, 41.885637,
41.9030376666667, 41.93314, 41.838198, 41.892278, 41.93, 41.894722,
41.90345, 41.6922943333333, 41.9080621666667, 42.025784), start_lng = c(-87.65304,
-87.631697, -87.6225141666667, -87.62455, -87.6538015, -87.6615086666667,
-87.639904, -87.62232, -87.6498425, -87.67393, -87.71, -87.6167566666667,
-87.6936384935, -87.648128, -87.644336, -87.65464, -87.634656,
-87.6256886059, -87.652662, -87.697153, -87.6823075, -87.62,
-87.64332, -87.612043, -87.71, -87.638677, -87.650154, -87.74,
-87.6529666666667, -87.668857, -87.634581, -87.64776, -87.66402,
-87.6260033333333, -87.65703, -87.641066, -87.630834, -87.65464,
-87.58, -87.64867, -87.667429, -87.58, -87.6277486666667, -87.658865,
-87.6776919292, -87.677335, -87.65478743, -87.6223878333333,
-87.629143, -87.64926, -87.667429, -87.7, -87.63188991, -87.6080766666667,
-87.6874035, -87.63443007, -87.59, -87.607267, -87.71, -87.6776919292,
-87.63, -87.6119485, -87.61, -87.671138, -87.64867, -87.6637163333333,
-87.648043, -87.6796343333333, -87.6534645, -87.638677, -87.6385057718,
-87.6153553902, -87.6318963333333, -87.74, -87.64883, -87.623777,
-87.634362, -87.661501, -87.648789, -87.677855, -87.628722, -87.6385057718,
-87.62, -87.638973, -87.66, -87.6186168193817, -87.72, -87.626185,
-87.65840426, -87.641823, -87.631299, -87.64776, -87.645143,
-87.612043, -87.71, -87.634362, -87.667747, -87.6426485, -87.6315093333333,
-87.684107), end_lat = c(41.918306, 41.886875, 41.8456825, 41.8530845574128,
41.890831, 41.99, 41.885637, 41.881319815, 41.88, 41.961068,
41.93, 41.880958, 41.966399801841, 41.89766, 41.9267559875, 41.9578665241517,
41.911386, 41.867888, 41.95078, 41.932588, 41.9245285, 41.8776751666667,
41.9105780349, 41.9239313113662, 42.0192226666667, 41.904613,
41.9947796884, 41.96, 41.9296915, 41.94, 41.94, 41.907066, 41.923931,
41.8707831666667, 41.87772613, 41.872187, 41.892278, 41.961004,
41.7689161666667, 41.8793563587, 41.95078, 41.79, 41.882242,
41.932225, 41.912133, 41.9093960065, 41.8810317, 41.9, 41.89,
41.912133, 41.926277, 41.93190196886, 41.874053, 41.8368228333333,
41.882754, 41.894666, 41.76, 41.882134, 41.96, 41.89637337, 41.87,
41.8787191666667, 41.8, 41.91, 41.917805, 41.88, 41.926277, 41.93,
41.8990156666667, 41.890762, 41.8854833079, 41.874754, 41.85,
41.94, 41.920771, 41.894345, 41.94334, 41.871737, 41.88338, 41.92154,
41.882134, 41.902997, 41.876243, 41.892278, 41.89, 41.886024,
41.86, 41.8918473721099, 41.9093960065, 41.8854833079, 41.89,
41.92883, 41.834734, 41.891466, 41.9296816666667, 41.902973,
41.918491153687, 41.75, 41.9218326666667, 41.9840446107), end_lng = c(-87.636282,
-87.62603, -87.6224476666667, -87.6319313049316, -87.6313945,
-87.66, -87.641823, -87.6295209193, -87.65, -87.695439, -87.71,
-87.616743, -87.6887042820454, -87.62351, -87.6344287848, -87.6495051383972,
-87.638677, -87.623041, -87.659172, -87.636427, -87.658447, -87.6240391666667,
-87.6494219288, -87.6358245313168, -87.6736431666667, -87.640552,
-87.6602845349, -87.69, -87.7080808333333, -87.67, -87.68, -87.667252,
-87.635825, -87.6257745, -87.65478743, -87.661501, -87.612043,
-87.649603, -87.634775, -87.6297910363, -87.659172, -87.6, -87.641066,
-87.658617, -87.634656, -87.6776919292, -87.62408432, -87.62,
-87.63, -87.634656, -87.630834, -87.7011951301, -87.627716, -87.6133453333333,
-87.6259215, -87.638437, -87.55, -87.625125, -87.69, -87.66098386,
-87.62, -87.6355345, -87.59, -87.66, -87.682437, -87.63, -87.630834,
-87.71, -87.6299358333333, -87.631697, -87.6523048564, -87.649807,
-87.64, -87.73, -87.663712, -87.622798, -87.67097, -87.65103,
-87.64117, -87.653818, -87.625125, -87.683825, -87.624426, -87.612043,
-87.65, -87.624117, -87.72, -87.6205801963806, -87.6776919292,
-87.6523048564, -87.63, -87.668507, -87.625813, -87.626761, -87.7081071666667,
-87.63128, -87.6974228024483, -87.64, -87.6439593333333, -87.6602738295
)), row.names = c(NA, -100L), class = "data.frame")
Next, i extracted min and max values for latitude and longitude and then used those values as limits for my map plot:
library(ggmap)
library(ggplot2)
map_lim <- data.frame(
min_lat = min(df[, c("start_lat", "end_lat")]),
max_lat = max(df[, c("start_lat", "end_lat")]),
min_lng = min(df[, c("start_lng", "end_lng")]),
max_lng = max(df[, c("start_lng", "end_lng")])
)
map_lim
## min_lat max_lat min_lng max_lng
## 1 41.69229 42.03 -87.74 -87.55
map <- get_stamenmap(
bbox = c(left = map_lim$min_lng, right = map_lim$max_lng, bottom = map_lim$min_lat, top = map_lim$max_lat)
)
ggmap(map)
This is the resulting map:
Now i want to add a 2d density plot based on the same set of coordinates on top of this map, but i don't know how to do it. This is my 2d density plot code.
density2d <- ggplot(df, aes(x = start_lng, y = start_lat)) +
coord_equal(xlim = c(map_lim$min_lng, map_lim$max_lng), ylim = c(map_lim$min_lat, map_lim$max_lat)) +
xlab("Longitude") +
ylab("Latitude") +
stat_density2d(aes(fill = ..level..), alpha = 0.5, geom = "polygon") +
scale_fill_viridis_c()
density2d
You simply add the density layer to your map:
ggmap(map) +
stat_density2d(data = df, aes(x = start_lng, y = start_lat,
fill = ..level..), alpha = 0.5, geom = "polygon") +
scale_fill_viridis_c()
I have a dataframe like the following
mydata <- structure(list(Wife = c(15.972, 12.715, 8.333, 6.276, 2.179,
-1.408, -1.649, -4.647, -7.039, -5.299, -7.411, -9.776, -9.612
), Alternating = c(-2.622, -0.548, -1.331, 3.9, -1.802, 2.08,
1.481, 9.53, 7.709, -0.953, -4.823, -4.878, -5.245), Husband = c(-7.012,
-5.823, -3.99, -3.324, -5.828, -4.869, -3.941, 0.515, 9.551,
-0.868, 4.843, 24.544, -5.812), Jointly = c(-8.283, -7.569, -4.048,
-6.564, 4.418, 4.284, 4.157, -3.006, -7.306, 7.066, 7.086, -8.306,
19.397)), row.names = c("Laundry", "Main_meal", "Dinner", "Breakfeast",
"Tidying", "Dishes", "Shopping", "Official", "Driving", "Finances",
"Insurance", "Repairs", "Holidays"), class = "data.frame")
which lists the chi-square adjusted standardized residuals. Using the 'formattable' R package, I managed to get the below table (more nicely formatted than in the R console):
Issue
I cannot find a viable option to conditionally formatting some cells according to the size of the residual. What I am after is (for example) to have in GREEN the cells whose residual is larger than +1.96, and in RED those whose residual is smaller than -1.96.
I have indeed consulted the package's vignette, with no avail.
library(formattable)
library(dplyr)
mydata <- structure(list(Wife = c(
15.972, 12.715, 8.333, 6.276, 2.179,
-1.408, -1.649, -4.647, -7.039, -5.299, -7.411, -9.776, -9.612
), Alternating = c(
-2.622, -0.548, -1.331, 3.9, -1.802, 2.08,
1.481, 9.53, 7.709, -0.953, -4.823, -4.878, -5.245
), Husband = c(
-7.012,
-5.823, -3.99, -3.324, -5.828, -4.869, -3.941, 0.515, 9.551,
-0.868, 4.843, 24.544, -5.812
), Jointly = c(
-8.283, -7.569, -4.048,
-6.564, 4.418, 4.284, 4.157, -3.006, -7.306, 7.066, 7.086, -8.306,
19.397
)), row.names = c(
"Laundry", "Main_meal", "Dinner", "Breakfeast",
"Tidying", "Dishes", "Shopping", "Official", "Driving", "Finances",
"Insurance", "Repairs", "Holidays"
), class = "data.frame")
style_ci <- function(x) {
case_when(x > 1.96 ~ "green", x < -1.96 ~ "red", TRUE ~ "black")
}
formattable(mydata, list(
Wife = formatter("span", style = ~ style(color = style_ci(Wife))),
Alternating = formatter("span", style = ~ style(color = style_ci(Alternating))),
Husband = formatter("span", style = ~ style(color = style_ci(Husband))),
Jointly = formatter("span", style = ~ style(color = style_ci(Jointly)))
))
I have been trying to create a density plot in R that looks similar to the picture below.
In my code below, I have created a stat_density_2D plot that successfully plots my data, however, it fails to recognize my fill variable (in this case exitspeed) and only plots one color.
Upon further research, I believe the reason for this is because stat_density_2d bins the fill into levels. The problem I am having is that my fill variable has multiple values for the points within a particular level ultimately resulting in a density plot that only displays one color. Does anyone know how to bin my data so that my density plot can recognize the fill variable (exitspeed)? Please see below for the dataset and R code. Thanks in advance!
Data:
structure(list(platelocheight = c(2.594, 3.803, 3.254, 3.599,
3.617, 3.297, 2.093, 3.611, 2.842, 3.316, 2.872, 3.228, 3.633,
4.28, 3.309, 2.8, 2.632, 3.754, 2.207, 3.604, 3.443, 2.188, 3.452,
2.553, 3.382, 3.067, 2.986, 2.785, 2.567, 3.804), platelocside = c(0.059,
-1.596, -0.65, -0.782, -0.301, -0.104, 0.057, -0.807, 0.003,
1.661, 0.088, -0.32, -1.115, -0.146, -0.364, -0.952, 0.254, 0.109,
-0.671, -0.803, -0.212, -0.069, -0.09, -0.472, 0.434, 0.337,
0.723, 0.508, -0.197, -0.635), exitspeed = c(69.891, 73.352,
83.942, 85.67, 79.454, 85.277, 81.078, 73.573, 77.272, 59.263,
97.343, 91.436, 76.264, 83.479, 47.576, 84.13, 60.475, 61.093,
84.54, 69.959, 88.729, 88.019, 82.18, 83.684, 86.296, 90.605,
79.945, 59.899, 62.522, 77.75)), .Names = c("platelocheight",
"platelocside", "exitspeed"), row.names = c(NA, 30L), class = "data.frame")
R-Code:
library(RODBC)
library(ggplot2)
con=odbcConnect('username',uid='userid', pwd = 'password')
df=sqlQuery(con,"select platelocheight, platelocside, exitspeed from tm_sample where pitchcall='InPlay'
and exitspeed is not null")
topKzone <- 3.5
botKzone <- 1.6
inKzone <- -0.95
outKzone <- 0.95
kZone <- data.frame(
x=c(inKzone, inKzone, outKzone, outKzone, inKzone),
y=c(botKzone, topKzone, topKzone, botKzone, botKzone)
)
df$h <- round(df$platelocheight)
df$s <- round(df$platelocside)
df$es<- round(df$exitspeed)
ggplot(kZone, aes(x,y)) +
stat_density_2d(data=df, aes(x=s, y=h, fill=es),geom="polygon") +
scale_fill_distiller(palette = "Spectral") +
geom_path(lwd=1.5, col="black") +
coord_fixed()
I'm trying to plot a relatively small data set, and I can't get it to show me the plot. It keeps giving the error Error: cannot allocate vector of size 9.7 Gb. This doesn't make much sense to me as the data set is rather small.
> nrow(locs)
[1] 130
> head(locs)
STATION AVGTRANGE LAT LONG
1: USC00286979 22.13333 40.6971 -75.2042
2: USC00360022 21.33333 40.5361 -79.8152
3: USC00360132 24.37037 40.5227 -78.3694
4: USC00360140 19.80000 40.4949 -78.4667
5: USC00360147 22.36667 41.3585 -77.9262
6: USC00360457 20.68000 40.8209 -76.4983
How I'm plotting it.
gg <- ggplot(data = locs, aes(x = LONG, y = LAT)) +
geom_raster(aes(fill=AVGTRANGE), interpolate=TRUE)
gg # can't allocate here
Here is the dput my data.
> dput(locs)
structure(list(STATION = structure(1:130, .Label = c("USC00286979",
"USC00360022", "USC00360132", "USC00360140", "USC00360147", "USC00360457",
"USC00360560", "USC00360656", "USC00360754", "USC00360785", "USC00360861",
"USC00360868", "USC00361139", "USC00361212", "USC00361301", "USC00361350",
"USC00361354", "USC00361362", "USC00361377", "USC00361480", "USC00361485",
"USC00361705", "USC00361726", "USC00361751", "USC00361802", "USC00361810",
"USC00361838", "USC00361920", "USC00362071", "USC00362183", "USC00362323",
"USC00362470", "USC00362574", "USC00362721", "USC00362942", "USC00363018",
"USC00363028", "USC00363226", "USC00363311", "USC00363321", "USC00363343",
"USC00363417", "USC00363437", "USC00363451", "USC00363632", "USC00363665",
"USC00363698", "USC00364214", "USC00364325", "USC00364432", "USC00364763",
"USC00364778", "USC00364815", "USC00364839", "USC00364896", "USC00364934",
"USC00364976", "USC00364992", "USC00365050", "USC00365109", "USC00365344",
"USC00365573", "USC00365686", "USC00365738", "USC00365902", "USC00365918",
"USC00366111", "USC00366151", "USC00366194", "USC00366238", "USC00366508",
"USC00366649", "USC00366886", "USC00366921", "USC00366927", "USC00367029",
"USC00367073", "USC00367103", "USC00367167", "USC00367186", "USC00367229",
"USC00367409", "USC00367477", "USC00367732", "USC00367782", "USC00367863",
"USC00367931", "USC00367938", "USC00368073", "USC00368184", "USC00368308",
"USC00368361", "USC00368400", "USC00368449", "USC00368469", "USC00368596",
"USC00368668", "USC00368868", "USC00368873", "USC00368888", "USC00368905",
"USC00369298", "USC00369367", "USC00369408", "USC00369823", "USR0000PALL",
"USW00003761", "USW00004726", "USW00004751", "USW00004787", "USW00004843",
"USW00013739", "USW00014711", "USW00014712", "USW00014736", "USW00014737",
"USW00014751", "USW00014762", "USW00014770", "USW00014777", "USW00014778",
"USW00014860", "USW00054737", "USW00054782", "USW00054786", "USW00054789",
"USW00054792", "USW00093778", "USW00094732", "USW00094823"), class = "factor"),
AVGTRANGE = c(22.1333333333333, 21.3333333333333, 24.3703703703704,
19.8, 22.3666666666667, 20.68, 23.35, 21.4333333333333, 25.75,
23.4333333333333, 23.6428571428571, 26.4333333333333, 27.551724137931,
25.3448275862069, 25.0666666666667, 26.6842105263158, 23.4444444444444,
29.6, 23.3, 30.2631578947368, 27.0454545454545, 25.9333333333333,
24.2083333333333, 27.448275862069, 28.2333333333333, 21.4666666666667,
24.1111111111111, 25.7333333333333, 23.8571428571429, 21.6,
26.08, 26.2916666666667, 27.1034482758621, 28.3666666666667,
27.9259259259259, 23.6, 25.7, 26.3666666666667, 26.0344827586207,
20.2666666666667, 23.0909090909091, 27.2727272727273, 25.9666666666667,
24.8214285714286, 20.2413793103448, 24.0333333333333, 20.6333333333333,
26.0344827586207, 22.6, 29.0333333333333, NA, 25.625, 19.0333333333333,
18.7666666666667, 21.0689655172414, 22, 24.1333333333333,
25.0333333333333, 24.0666666666667, 24.3666666666667, 20.7333333333333,
32.5, 26.6666666666667, NA, 22.2666666666667, 25.1333333333333,
27.1481481481481, 22.7, 24.4827586206897, 21.6071428571429,
20.8461538461538, 29.9333333333333, 17.3928571428571, 26.2666666666667,
23.84, 23.1481481481481, 23.8275862068966, 26.9, 26.7931034482759,
25.3636363636364, NA, 23.5333333333333, 27.3571428571429,
17.2, 24.5, 22.0666666666667, NA, 23.8333333333333, 26.5172413793103,
27.6551724137931, 21.2307692307692, 26.5384615384615, 19.5,
20.8, 25.3, 18.6666666666667, 25.2758620689655, 23.8333333333333,
24.3461538461538, 27.6551724137931, 25.7666666666667, 24,
26.0344827586207, 24.6, 28.7333333333333, 27.7, 20.1034482758621,
18.6071428571429, 26.1785714285714, 22.5714285714286, 22.6071428571429,
17.1785714285714, 19.3571428571429, 21.6071428571429, 24.4285714285714,
23.6071428571429, 21.6785714285714, 19.9642857142857, 25.2142857142857,
22.7241379310345, 23.0357142857143, 17.8928571428571, 22.2962962962963,
21.2857142857143, 21.8571428571429, 21, 25.6428571428571,
25.6071428571429, 19.4444444444444, 22.6785714285714), LAT = c(40.6971,
40.5361, 40.5227, 40.4949, 41.3585, 40.8209, 40.8619, 39.9355,
41.0072, 40.3803, 40.3916, 41.8975, 40.8415, 41.6516, 41.5217,
39.848, 39.9353, 41.9301, 40.1468, 41.0489, 41.1922, 39.7994,
39.9969, 41.3575, 41.775, 41.7391, 41.9903, 40.2258, 40.46,
40.1275, 41.5216, 40.4681, 40.50194, 40.0136, 40.71306, 41.1184,
41.4004, 39.8815, 41.5631, 40.0962, 40.5513, 40.9666, 40.2305,
39.78333, 40.5511, 39.77056, 40.2817, 40.5972, 41.4992, 41.6767,
40.0499, 40.1167, 41.4234, 40.1692, 40.3333, 40.8223, 40.9474,
40.5864, 41.64583, 41.131, 40.8344, 40.3391, 39.7808, 41.6725,
40.6475, 40.5319, 40.412, 40.61417, 40.1482, 40.075, 39.8,
41.9245, 39.9587, 40.8729, 40.12, 41.7394, 39.7275, 41.8157,
40.6515, 41.589, 40.9248, 41.3299, 41.4196, 39.8958, 40.5101,
40.683, 40.7831, 40.335, 40.05889, 41.05583, 39.8582, 41.8162,
40.5711, 40.7933, 41.40389, 41.008, 40.8532, 41.8975, 41.4792,
41.63, 41.7511, 41.84667, 39.89861, 41.7004, 40.0417, 41.4864,
39.8593, 40.31611, 41.8, 41.17833, 41.62639, 39.87327, 40.1962,
40.36667, 40.29639, 40.64985, 40.21722, 40.35472, 40.82056,
41.3336, 41.2433, 42.0803, 40.12028, 40.23833, 40.33, 41.13889,
41.04667, 39.91806, 40.08194, 40.4846), LONG = c(-75.2042,
-79.8152, -78.3694, -78.4667, -77.9262, -76.4983, -75.6428,
-77.2577, -76.4482, -76.0274, -79.8594, -78.7144, -79.9163,
-76.8463, -77.4478, -79.5898, -77.6394, -79.297, -79.8986,
-77.9411, -79.4361, -79.3665, -79.5963, -79.2172, -78.0417,
-77.971, -77.1567, -77.1894, -76.8703, -79.4058, -76.4043,
-78.7289, -80.0833, -78.3653, -79.5144, -75.7277, -79.8305,
-77.3506, -78.6014, -75.7513, -80.2167, -78.5871, -75.4354,
-79.9166, -75.9913, -77.0325, -76.8703, -79.1186, -80.4681,
-78.8036, -76.2742, -76.4333, -76.4933, -79.1411, -76.4667,
-75.6962, -76.8786, -77.5692, -80.425, -77.4336, -76.1352,
-79.8604, -79.041, -75.0641, -80.3861, -80.2172, -79.7245,
-79.7191, -74.953, -76.0717, -76.05, -78.0072, -75.1728,
-78.2161, -75.5011, -75.4465, -79.913, -78.2873, -78.5551,
-75.3303, -79.2825, -77.7381, -78.7493, -76.3948, -79.5459,
-79.6684, -76.8617, -75.313, -77.5213, -80.06, -77.4774,
-80.4249, -75.2781, -77.8672, -78.0183, -75.1876, -76.7891,
-77.1419, -79.4432, -79.693, -76.443, -79.1494, -80.1655,
-77.3871, -78.5278, -79.1025, -75.7861, -78.8338, -78.6333,
-78.8988, -80.215, -75.2267, -76.7724, -75.9666, -78.3202,
-75.4477, -76.8513, -79.9216, -76.8641, -75.7269, -76.9217,
-80.1824, -76.2944, -75.5572, -75.1225, -75.3794, -78.4116,
-76.8741, -75.0111, -80.2144)), .Names = c("STATION", "AVGTRANGE",
"LAT", "LONG"), class = c("data.table", "data.frame"), row.names = c(NA,
-130L), .internal.selfref = <pointer: 0x2a40128>, sorted = "STATION")
I am not sure what your are trying to achieve with the geom_raster, as your data does not seem to fit the purpose.
Consider the outputs of dot plot:
gg <- ggplot(data = locs, aes(x = LONG, y = LAT, colour = AVGTRANGE)) +
geom_point()
#geom_raster(aes(fill=AVGTRANGE), interpolate=TRUE)
gg
data(faithfuld)
gg <- ggplot(faithfuld, aes(waiting, eruptions, colour = density)) +
geom_point()
#geom_raster(aes(fill = density), interpolate = TRUE)
gg
I have also tried geom_contour on your data and it does not work:
gg <- ggplot(data = locs, aes(x = LONG, y = LAT, z = AVGTRANGE)) +
geom_contour()
gg
UPDATE
I have checked the code of the geom_raster and the reason it tries to create the giant plot is that resolution of the plot is based on the minimal distance between points. As some of the points in your data are quite close to each other size of the matrix is so large.
If you round LAT and LONG to 2 digits code works.
locs$LAT <- round(locs$LAT, 0)
locs$LONG <- round(locs$LONG, 0)
I have this dataset:
sample <- structure(list(A = c(1415.6, 1345.3, 1321.7, 1234.5, 1567.8,
1476.6, 1610.1, 1422.6, 1209.1, 1249.3, 1377.5, 1525.7, 1683.7,
1500.1, 1565.3, 1737.4, 1321, 1477.8, 1642, 1608.1, 1427.8, 1608.2,
1404.4, 1688.3, 1795.4), B = c(98, 457, 756, 971, 1148, 4260,
16307, 42614, 69787, 76301, 80491, 82267, 83975, 85310, 86322,
94492, 98798, 102514, 126045.986, 160848.998, 183607.7625, 212747.9255,
249117.2874, 306092.91, 339609.8663), C = c(1.2397, 1.5526, -0.1829,
-0.3298, -0.1945, 2.8669, 1.3536, 0.781, 0.0324, -1.4283, -0.4413,
-0.8583, -0.039, -0.2464, -0.277, 2.0885, -0.6405, -0.1474, 1.8457,
0.3913, -0.4248, 0.2472, 0.2216, 0.4489, -0.5306)), .Names = c("A",
"B", "C"), class = "data.frame", row.names = c(NA, -25L))
and I want to change the plot region colour in vis.gam function (invert the grey colour - the higher the number in the plot contours the darker the colour of the plot region and vice versa):
library(mgcv)
m0 <-gam(C ~ A + B, data = sample)
vis.gam(m0, plot.type="contour", color="gray")
I would like to just invert the colour palette. If not possible, change it manually.
I've tried somethoing like this (I choosed names only by chance)
vis.gam(m0,plot.type="contour", col=c("#FFFFFF", "#F7F7F7", "666666"))
vis.gam(m0,plot.type="contour", col=("grey25", "grey26", "grey27"))
but that is not working.
Unfortunately the definition of vis.gam doesn't allow what you want. Fortunately, it is fairly easy to modify this function to do what you want:
# first get the definition of vis.gam
newDef <- deparse(vis.gam)
# change the line defining the direction of the grey gradient
newDef[grep("gray\\(seq\\(",newDef)] <- " pal <- gray(seq(0.9, 0.1, length = nCol))"
# then define a new function with this new definition
vis.gam2 <- eval(parse(text=newDef))
Now using vis.gam2 will do what you want:
vis.gam2(m0, plot.type="contour", color="gray")