I want to use plotly for interactive user-defined shapes.
I am aware this steps away from the graphics even though it remains in data-visualisation.
In my past work, I had used an xml file with the user defined shape, and had changed its color with the following code (attention, this is unfortunately not a self-contained example):
library(graphics)
library(grImport)
library(XML)
library(gridExtra)
library(jpeg)
library(png)
library(XML)
doc <- xmlParse("shape.eps.xml")
myDraw <- readPicture(saveXML(doc))
node <- xpathSApply(doc, paste("//path[#id='", myDraw, "']/context/rgb", sep = ""))[[1]]
rgbCol <- col2rgb(color)
xmlAttrs(node)["r"] = rgbCol[1]/255
For now I will go with the superposition of rectangles, but as along as my shape can defined split in rectangles. Is there then a way to import and color user-defined shapes with plotly?
Related
I feel like many similar questions have been asked but I haven't found a solution to my problem yet in the related questions.
I am trying to change the colors on my map using spplot and the col.region command.
I have tried setting up a palette with the RColorBrewer package. I have tried using various values for the n: 5,6,7 (I am using 5 quantiles for my cuts) and even 1 to see if it would result in any observable change, but to no avail. I have also changed the choice of color several times but it also didn't bring any change.
I have also tried setting up a color function the colorRampPalette function but also unsuccessfully.
The data I'm using can be downloaded here (sorry, I couldn't figure out how to upload it with the question) : http://www.data.drees.sante.gouv.fr/ReportFolders/reportFolders.aspx, by typing "APL" in search bar and taking the first excel file (2015); apologies can't manage to link it properly either)
My code is the following:
library(maptools)
library(raster)
library(RColorBrewer)
library(readxl)
library(classInt)
apl15 <- read_excel("DATA USED")
france_com<- getData(name = "GADM",
country="FRA",
level=5)
paca <- subset(fr_com,NAME_1=="Provence-Alpes-Côte d'Azur")
apl15 <- data.frame(apl15)
names(apl15) <- c("code_com","name_com","apl","apl_young","pop_com","dept","apl*pop")
id_paca <- match(paca$NAME_5,apl15$name_com)
key_paca<- apl15[id_paca,"apl"]
paca$apl <- key_paca
apl.qt <- classIntervals(paca$apl,
n=5,
style="quantile")
br <- apl.qt$brks
offs <- 0.0000001
br[1] <- br[1] - offs
br[length(br)] <- br[length(br)] + offs
paca$apl_q <- cut(paca$apl,br)
display.brewer.all(type="seq")
my.palette <- brewer.pal(6, "OrRd")
spplot(paca,"apl_q",
col.region=my.palette,
main="APL en PACA", cex.=.7)
I expect this map but with colors corresponding to the palette I have selected.
my data mapped onto a region:
.
Thanks in advance for any help!
I am creating an html document by creating various objects with ggplotly() and htmltools functions like h3() and html(). Then I submit them as a list to htmltools::save_html() to create an html file.
I would like to add ggplot charts directly as images, rather than attaching all the plotly bells and whistles. In the end, I will create a self-contained html file (no dependencies), and the plotly stuff would make that file excessively large.
Is there some function that converts a ggplot object into some html-type object? Or do I have to save the ggplot as a .png file, then read the .png file into some object that I add to the list in the save_html() function?
My R code looks something like this:
library("tidyverse")
library("plotly")
library("htmltools")
HTMLOut <- "c:/Users/MrMagoo/My.html")
df <- data.frame(x=1:25, y=c(1:25*1:25))
g7 <- ggplot(df,aes(x=x, y=y)) + geom_point()
p7 <- ggplotly(g7) # I would like to use something other than ggplotly here. Just capturing the ggplot as an image would be fine.
# create other objects to add to the html file
t7 <- h2(id="graph7", "Title for graph #7")
d7 <- p("description of graph 7")
save_html(list(t7, p7, d7), HTMLOut)
# of course, the real code has many more objects in that list – more graphs, text, tables, etc.
I would like to replace the plotly object (p7) with something that just presents g7 in a way that would not cause an error in the save_html function.
I had hoped to find a function that could directly Base64 encode a ggplot object, but it seems that I first need to output the 'ggplot' object as a .png file (or SVG, per Teng L, below), then base64-encode it. I was hoping there was a more direct way, but I may end up doing that, as in https://stackoverflow.com/a/33410766/3799203 , ending it with
g7img <- "<img src=\"data:image/png;base64,(base64encode string)\""
g7img <- htmltools::html(g7img)
If you want to save the plot as a dynamic plotly graph, you could use htmlwidgets::saveWidget. This will produce a stand-alone html file.
Here is a minimal example:
library(tidyverse);
library(plotly);
library(htmlwidgets);
df <- data.frame(x = 1:25, y = c(1:25 * 1:25))
gg <- ggplot(df,aes(x = x, y = y)) + geom_point()
# Save ggplotly as widget in file test.html
saveWidget(ggplotly(gg), file = "test.html");
I ended up generating a temparory image file, then base64 encoding it, within a function I called encodeGraphic() (borrowing code from LukeA's post):
library(ggplot2)
library(RCurl)
library(htmltools)
encodeGraphic <- function(g) {
png(tf1 <- tempfile(fileext = ".png")) # Get an unused filename in the session's temporary directory, and open that file for .png structured output.
print(g) # Output a graphic to the file
dev.off() # Close the file.
txt <- RCurl::base64Encode(readBin(tf1, "raw", file.info(tf1)[1, "size"]), "txt") # Convert the graphic image to a base 64 encoded string.
myImage <- htmltools::HTML(sprintf('<img src="data:image/png;base64,%s">', txt)) # Save the image as a markdown-friendly html object.
return(myImage)
}
HTMLOut <- "~/TEST.html" # Say where to save the html file.
g <- ggplot(mtcars, aes(x=gear,y=mpg,group=factor(am),color=factor(am))) + geom_line() # Create some ggplot graph object
hg <- encodeGraphic(g) # run the function that base64 encodes the graph
forHTML <- list(h1("My header"), p("Lead-in text about the graph"), hg)
save_html(forHTML, HTMLOut) # output it to the html file.
I think what you want may be close to one of the following:
Seems you are creating an HTML report but hasn't checked out RMarkdown. It comes with Base64 encode. When you create an RMarkdown report, pandoc automatically converts any plots into an HTML element within the document, so the report is self-contained.
SVG plots. This is less likely to be what you might want, but SVG plots are markup-language based and may be easily portable. Specify .svg extension when you use ggsave() and you should be getting an SVG image. Note that SVG is an as-is implementation of the plot, so if can be huge in file size if you have thousands of shapes and lines.
This is an extension to the Maurits Evers post. In this answer I'm showing how to combine multiple plotly plots in the same html file in an organized fashion:
library("plotly")
library("htmltools")
# a small helper function to avoid repetition
my_func <- function(..., title){
## Description:
## A function to add title to put multiple gg plotly objects under a html heading
##
## Arguments:
## ...: a list of gg objects
## title: a character vector to specify the heading text
# get the ... in list format
lst <- list(...)
# create the heading
tmp_title <- htmltools::h1(title)
# convert each ggplot to ggplotly and put them under the same div html tag
tmp_plot <- lapply(lst, ggplotly) |>
htmltools::div()
# return the final object as list
return(list(tmp_title, tmp_plot))
}
# a toy data
df <- data.frame(x = 1:25, y = c(1:25 * 1:25))
# the ggplot object using the toy data
gg <- ggplot(df,aes(x = x, y = y)) + geom_point()
# put everything in order
final_list <- list(my_func(obj = list(gg, gg, gg), title = "The first heading"),
my_func(obj = list(gg, gg), title = "The second heading"))
# write to disk as a unified HTML file
htmltools::save_html(html = final_list,
file = "index.html"))
Disclaimer: I specifically did this to avoid using widgetframe R package and to be completely on par with the documentation of plotly-r. You can read the link if you are comfortable with adding extra dependency and extra abstraction layer. I prefer to use packages if and only if necessary. :)
I have a raster object with a large number of attributes, and I would like to plot the spatial data in R and colour code it by a certain attribute. I have not been able to work out how to use the information of a particular attribute to achieve this. So far I have successfully extracted the attribute of choice using factorValues(), but I cannot determine how to now incorporate this information into the plot() function. I tried using the ratify() and level() functions mentioned in the raster package documentation, but I don’t understand how the simplified online examples can be adapted for a raster with multiple attributes.
Any advice on how to achieve this would be greatly appreciated.
# read in shapefile
shp = readOGR(".", "grid")
#convert to raster
r = raster(extent(shp))
res(r) = c(1,0.5)
ra = rasterize(shp, r)
#crop raster to desired extent
rcrop = crop(ra, extent(-12, 2, 29, 51))
# extract attribute value of interest
f = factorValues(rcrop, 1:420, layer=1, att=17, append.names=FALSE)
# here there are 420 cells in the raster and I am interested in plotting values of attribute 17 of the raster (this is currently a numeric attribute, not a factor)
#extra code to set attribute as the level to use for plotting colours???
rcrop = ratify(rcrop)
rat = levels(rcrop)[[1]] #this just extras row IDs..not what I want
#…
### plot: I want to plot the grid using 7 colours (I would ideally like to specify the breaks myself)
require(RColorBrewer)
cols = brewer.pal(7,"YlGnBu")
#set breaks
brks = seq(min(minValue(rcrop)),max(maxValue(rcrop),7))
#plot
plot(rcrop, breaks=brks, col=cols, axis.arg=arg)
The following is pretty hacky (and may perform poorly for large rasters), but I'm not sure if there's a way to link col.regions to a specified attribute.
rasterVis::levelplot does a nice job of labelling colour ramps corresponding to factor rasters, and while it provides an att argument allowing you to specify which attribute you're interested in, this seems to only modify the labelling of the ramp. Raster cell values control how the colour ramp is mapped to the raster, so it seems to me that we need to modify the cell values themselves. Maybe #OscarPerpiñán will chime in here to prove me wrong :)
We can create a simple function to substitute the original cell values with whichever attribute we want:
switch_att <- function(r, att) {
r[] <- levels(r)[[1]][values(r), att]
r
}
Let's download and import a small example polygon dataset from Natural Earth:
library(rasterVis)
library(rgdal)
require(RColorBrewer)
download.file(file.path('http://www.naturalearthdata.com',
'http//www.naturalearthdata.com/download/110m/cultural',
'ne_110m_admin_0_countries.zip'),
f <- tempfile())
unzip(f, exdir=tempdir())
shp <- readOGR(tempdir(), 'ne_110m_admin_0_countries')
rasterize the vector data:
r <- rasterize(shp, raster(raster(extent(shp), res=c(1, 1))))
And create some plots with levelplot:
levelplot(switch_att(r, 'continent'), col.regions=brewer.pal(8, 'Set2')) +
layer(sp.polygons(shp, lwd=0.5))
levelplot(switch_att(r, 'economy'), par.settings=BuRdTheme) +
layer(sp.polygons(shp, lwd=0.5))
EDIT
With Oscar's update to rasterVis, the switch_att hack above is no longer necessary.
devtools::install_github('oscarperpinan/rastervis')
levelplot(r, att='continent', col.regions=brewer.pal(8, 'Set2')) +
layer(sp.polygons(shp, lwd=0.5))
will produce the same figure as the first one above.
I am working on a shape file and like to highlight some of the boundaries (borders) of the regions (as figure 1):
Figure 1: some but not all of the regions (borders) of the shape file are highlighted
(Source: https://dl.dropboxusercontent.com/u/48721006/highlighted.png)
The highlighting is achieved with ArcMap. I can't figure out how to do the same with R (particularly with the spplot()). Any suggestions on this?
To get the shape file
library(sp)
library(maptools)
con <- url("http://gadm.org/data/rda/ZAF_adm2.RData")
print(load(con))
close(con)
plot(gadm)
Many thanks!
G
What I would do: (1) plot the complete set; (2) take a subset; (3) plot the subset with a different line type. For subsetting shape files, check this question.
plot(gadm)
# check class and structure of the data
class(gadm)
head(gadm#data)
# take a subset based on ID_2
some_polygons = subset(gadm,ID_2>=38840 & ID_2<38850)
plot(some_polygons, add=T, border='cyan', lwd=2)
I am trying to use the animation package to generate an "evolving" plot of points on a map. The map is generated from shapefiles (from the readShapeSpatial/readShapeLines functions).
The problem is when it's plotted in a for loop, the result is additive, whereas the ideal result is to have it evolve.
Are there ways of using par() that I am missing?
My question is: is there a way to clear just the points ploted from the points function
and not clearing the entire figure thus not having to regraph the shapefiles?
in case someone wants to see code:
# plotting underlying map
newyork <- readShapeSpatial('nycpolygon.shp')
routes <- readShapeLines('nyc.shp')
par(bg="grey25")
plot(newyork, lwd=2, col ="lightgray")
plot(routes,add=TRUE,lwd=0.1,col="lightslategrey")
# plotting points and save to GIF
ani.options(interval=.05)
saveGIF({
par(bg="grey25")
# Begin loop
for (i in 13:44){
infile <-paste("Week",i,".csv",sep='')
mydata <-read.csv(file = infile, header = TRUE, sep=",")
plotvar <- Var$Para
nclr <- 4
plotclr <-brewer.pal(nclr,"RdPu")
class<- classIntervals(plotvar,nclr,style = "pretty")
colcode <- findColours(class,plotclr)
points(Var$Lon,Var$Lat,col=colcode)
}
})
If you can accept a residual shadow or halo of ink, you can over-plot with color ="white" or == to your background choices. We cannot access your shape file but you can try it out by adding this line:
points(Var$Lon, Var$Lat, col="grey25")
It may leave gaps in other previously plotted figures or boundaries, because it's definitely not object-oriented. The lattice and ggplot2 graphics models are more object oriented, so if you want to post a reproducible example, that might be an alternate path to "moving" forward. I seem to remember that the rgl package has animation options in its repetoire.