apply transparent background to divide plot area based on x values using ggplot

apply transparent background to divide plot area based on x values using ggplot

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apply transparent background to divide plot area based on x values using ggplot
Tag : r , By : Noah
Date : November 29 2020, 04:01 AM

I hope this helps you . I think you want something like this. You'll have to designate groups and fill by that group in your geom_ribbon, and set your ymin and ymax as you like.
    mtcars$group <- ifelse(mtcars$wt <= 3.5, "<= 3.5", "> 3.5")
mtcars <- arrange(mtcars, wt)
mtcars$group2 <- rleid(mtcars$group)
mtcars_plot <- head(do.call(rbind, by(mtcars, mtcars$group2, rbind, NA)), -1)
mtcars_plot[,c("group2","group")] <- lapply(mtcars_plot[,c("group2","group")], na.locf)
mtcars_plot[] <- lapply(mtcars_plot, na.locf, fromLast = TRUE)

ggplot(mtcars_plot, aes(x = wt, y = mpg)) +
  geom_point() +
  geom_smooth(aes(), method=lm, se=F, fullrange=TRUE) +
  geom_ribbon(aes(ymin = mpg *.75, ymax = mpg * 1.25, fill = group), alpha = .25) +
  labs(fill = "Weight Class")
mtmodel <- lm(mpg ~ wt, data = mtcars)
mtcars$Low <- predict(mtmodel, newdata = mtcars, interval = "confidence")[,2]
mtcars$High <- predict(mtmodel, newdata = mtcars, interval = "confidence")[,3]
ggplot(mtcars_plot, aes(x = wt, y = mpg)) +
  geom_point() +
  geom_smooth(aes(), method=lm, se=F, fullrange=TRUE) +
  geom_ribbon(aes(ymin = Low, ymax = High, fill = group), alpha = .25) +
  labs(fill = "Weight Class") +
  scale_fill_manual(values = c("red", "orange"), name = "fill")

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R: change background color of plot for specific area only (based on x-values)

Tag : r , By : mtnmuncher
Date : March 29 2020, 07:55 AM
To fix the issue you can do This can be achieved by thinking about the plot somewhat differently to your description. Basically, you want to draw a coloured rectangle between the desired positions on the x-axis, filling the entire y-axis limit range. This can be achieved using rect(), and note how, in the example below, I grab the user (usr) coordinates of the current plot to give me the limits on the y-axis and that we draw beyond these limits to ensure the full range is covered in the plot.
plot(1:10, 1:10, type = "n", axes = FALSE) ## no axes
lim <- par("usr")
rect(2, lim[3]-1, 4, lim[4]+1, border = "red", col = "red")
axis(1) ## add axes back
box()   ## and the plot frame
X <- c(1,3)
Y <- c(2,4)
plot(1:10, 1:10, type = "n", axes = FALSE) ## no axes
lim <- par("usr")
rect(X[1], Y[1], X[2], Y[2], border = "red", col = "red")
axis(1) ## add axes back
box()   ## and the plot frame
botleft <- c(1,2)
topright <- c(3,4)
plot(1:10, 1:10, type = "n", axes = FALSE) ## no axes
lim <- par("usr")
rect(botleft[1], botleft[2], topright[1], topright[2], border = "red",
     col = "red")
axis(1) ## add axes back
box()   ## and the plot frame

Google polygonal map background color transparent, surrounding area semi-transparent overlay

Tag : development , By : phil
Date : March 29 2020, 07:55 AM
I wish did fix the issue. Using some CSS and a large 512 x 512px png I have managed to emulate what I wanted to achieve. I'm sure there would be more accurate methods but this has worked for me.
<!DOCTYPE html>
    <meta name="viewport" content="initial-scale=1.0, user-scalable=no" />
    <style type="text/css">
      html { height: 100% }
      body { height: 100%; margin: 0; padding: 0; }
      #map_canvas {
    background-color: #EAEAEA;
    border: 1px solid #CCCCCC;
    height: 400px;
    margin-bottom: 10px;
    margin-left: auto;
    margin-right: auto;
    width: 532px;
#map_canvas div div div div div img{ border:1000px solid black;margin:-1000px -1000px;}
/*#map_canvas div div div div div div div{ background: none repeat scroll 0px 0px rgba(0, 0, 0, 0.5);}*/
    <script type="text/javascript" src="http://maps.googleapis.com/maps/api/js?key=AIzaSyA7UaoyrY4KyoW1iEU0KFo0ZOxH5w30oZ8&sensor=true"></script>
    <script type="text/javascript">
var overlay;
USGSOverlay.prototype = new google.maps.OverlayView();

function initialize() {
    var myLatLng = new google.maps.LatLng(-37.815676, 145.449005);
    var myOptions = {
        zoom: 9,
        center: myLatLng,
        mapTypeId: google.maps.MapTypeId.ROADMAP
    var map = new google.maps.Map(document.getElementById("map_canvas"), myOptions);
    var swBound = new google.maps.LatLng(-38.269876, 144.842405); // Latitude, Longitude = 182.749 or 107.183 or 108.4443 or 107.77615
    var neBound = new google.maps.LatLng(-37.161476, 146.249005); //  -0.5542, +0.7033 = 256px
    //var swBound = new google.maps.LatLng(-37.783, 144.966); 
    //var neBound = new google.maps.LatLng(-37.225, 145.66930); 
    //var swBound = new google.maps.LatLng(62.281819, -150.287132);
    //var neBound = new google.maps.LatLng(62.400471, -150.005608);
    var bounds = new google.maps.LatLngBounds(swBound, neBound);
    // Photograph courtesy of the U.S. Geological Survey
    var srcImage = 'images/mg_map_full.png';
    overlay = new USGSOverlay(bounds, srcImage, map);

function USGSOverlay(bounds, image, map) {
    // Now initialize all properties.
    this.bounds_ = bounds;
    this.image_ = image;
    this.map_ = map;
    // We define a property to hold the image's div. We'll
    // actually create this div upon receipt of the onAdd()
    // method so we'll leave it null for now.
    this.div_ = null;
    // Explicitly call setMap on this overlay
USGSOverlay.prototype.onAdd = function () {
    // Note: an overlay's receipt of onAdd() indicates that
    // the map's panes are now available for attaching
    // the overlay to the map via the DOM.
    // Create the DIV and set some basic attributes.
    var div = document.createElement('div');
    div.style.borderStyle = "none";
    div.style.borderWidth = "0";
    div.style.borderColor = "red";
    div.style.position = "absolute";
    div.style.opacity = "0.3";
    // Create an IMG element and attach it to the DIV.
    var img = document.createElement("img");
    img.src = this.image_;
    img.style.width = "100%";
    img.style.height = "100%";
    img.style.position = 'absolute';
    // Set the overlay's div_ property to this DIV
    this.div_ = div;
    // We add an overlay to a map via one of the map's panes.
    // We'll add this overlay to the overlayImage pane.
    var panes = this.getPanes();
USGSOverlay.prototype.draw = function () {
    // Size and position the overlay. We use a southwest and northeast
    // position of the overlay to peg it to the correct position and size.
    // We need to retrieve the projection from this overlay to do this.
    var overlayProjection = this.getProjection();
    // Retrieve the southwest and northeast coordinates of this overlay
    // in latlngs and convert them to pixels coordinates.
    // We'll use these coordinates to resize the DIV.
    var sw = overlayProjection.fromLatLngToDivPixel(this.bounds_.getSouthWest());
    var ne = overlayProjection.fromLatLngToDivPixel(this.bounds_.getNorthEast());
    // Resize the image's DIV to fit the indicated dimensions.
    var div = this.div_;
    div.style.left = sw.x + 'px';
    div.style.top = ne.y + 'px';
    div.style.width = (ne.x - sw.x) + 'px';
    div.style.height = (sw.y - ne.y) + 'px';
USGSOverlay.prototype.onRemove = function () {
    this.div_ = null;
  <body onload="initialize()">
    <div id="map_canvas" style="position: relative; background-color: rgb(229, 227, 223); overflow: hidden;"></div>

Grouped bar plot in ggplot with y values based on combination of 2 categorical variables?

Tag : r , By : Thierry Brunet
Date : March 29 2020, 07:55 AM
may help you . I think you are looking for the interaction() (i.e. get all unique pairings) between df$Verb_Type and df$speaker to get the column groupings you are after. You can pass this directly to ggplot or make a new variable ahead of time:
ggplot(df, aes(x = Frame, y = proportion_type,
               group = interaction(Verb_Type, speaker), fill = Verb_Type, alpha = speaker)) +
    geom_bar(stat = "identity", position = "dodge") +
    scale_alpha_manual(values = c(.5, 1))
df$grouper <- interaction(df$Verb_Type, df$speaker)
ggplot(df, aes(x = Frame, y = proportion_type,
               group = grouper, fill = Verb_Type, alpha = speaker)) +
    geom_bar(stat = "identity", position = "dodge") +
    scale_alpha_manual(values = c(.5, 1))

How to save the plot with the labels and ticks area transparent but not the main plot area in matplotlib?

Tag : python , By : Mostapen
Date : March 29 2020, 07:55 AM
Does that help There is a bug in the newest version of matplotlib. I'm not sure if this applies to here, because you do not state which version you are using.
The workaround would be to use a transparent facecolor and leave the other arguments at their defaults.
fig.savefig("fname", facecolor=(1,1,1,0))

Increasing the plot area in ggplot to cope with geom_text at plot edges

Tag : r , By : xie renhui
Date : March 29 2020, 07:55 AM
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