similar to: graphs with gradients of colors

Hello, I have a graphics-related question: I was wondering if anyone knows of a way to create a bar chart that is colored with a three-part gradient that changes at fixed y-values. Each bar needs to fade green-to-yellow at Y=.10 and from yellow-to-red at Y=.20. Is there an option in a package somewhere that offers an easy way to do this? Attached is a chart I macgyvered together in Excel using a

R2.7.1, WinXP Hi, I have a polygon inside a circle as follows: radius <- 3 x <- seq(-radius,radius,length=2000) y <- sqrt(radius^2-x^2) xx <- c(x,-x) yy <- c(y,-y) plot(xx,yy, xlim=c(-radius,radius),ylim=c(-radius,radius), type="l", ylab="", xlab="", axes=F) radius <- 2.7 x1 <- seq(-radius,radius,length=2000) y1 <- sqrt(radius^2-x1^2)

Hi, Is it possible to diagonally fill a rectangle with a color gradient? I noticed that the gradient.rect of plotrix could fill a rect either up and down or from side to side. I am looking for something similar but fills diagonally instead, e.g., from the upper left corner to the bottom right. Does anyone know how to do it in R? Thanks, -- Tom [[alternative HTML version deleted]]

Hi, I wonder whether there is a way to generate a polygon (a triangle in my case) with color gradient using grid.polygon() in package grid? I tried something like library(grid) grid.polygon(x=c(0, 0.5, 1), y=c(0.5, 1, 0.5), gp=gpar(col=NA, fill=colorRampPalette(c("green", "lightgray"), space="Lab")(200))) But am only

Why fails nls with "singular gradient" here? I post a minimal example on the bottom and would be very happy if someone could help me. Kind regards, ########### # define some constants smallc <- 0.0001 t <- seq(0,1,0.001) t0 <- 0.5 tau1 <- 0.02 # generate yy(t) yy <- 1/2 * ( 1- tanh((t - t0)/smallc) * exp(-t / tau1) ) + rnorm(length(t))*0.01 # show the curve

I'm trying to fit a Gompertz sigmoid as follows: x <- c(15, 16, 17, 18, 19) # arbitrary example data here; y <- c(0.1, 1.8, 2.2, 2.6, 2.9) # actual data is similar gm <- nls(y ~ a+b*exp(-exp(-c*(x-d))), start=c(a=?, b=?, c=?, d=?)) I have been unable to properly set the starting value '?'s. All of my guesses yield either a "singular gradient" error if they

Does anybody know of a function that implements the derivative (gradient) of the multivariate normal density with respect to the *parameters*? It?s easy enough to implement myself, but I?d like to avoid reinventing the wheel (with some bugs) if possible. Here?s a simple example of the result I?d like, using numerical differentiation: library(mvtnorm) library(numDeriv) f=function(pars, xx, yy)

I would like to estimate a 95% highest density area for a multivariate parameter space (In the context of anova). Unfortunately I have only experience with univariate kernel density estimation, which is remarkebly easier :) Using Gibbs, i have sampled from a posterior distirbution of an Anova model with k means (mu) and 1 common residual variance (s2). The means are independent of eachother, but

Hello Recently, I've been dealing with a seemingly simple problem. I have a table with two columns filled with values from a test I made (say, amount of precipitation and Months measured). Now, instead of plotting a typical linear graphic with precipitation on the y-axis and the months in the x-axys, I would like to "convert" the values of precipitation in a color gradient,

Hello, Can somebody help me on a colour question? I have a levelplot made with the following syntax: library(lattice) inp <- read.csv("hoenne1", header = TRUE) levelplot(z~x*y, data = inp, region = TRUE, pretty = TRUE, col.regions = terrain.colours) The file "hoenne1" contains the data. I'll give a short example: x,y,z 0,0,1 0,1,1 0,2,1 1,0,2 1,2,2 0,2,2 1,2,3 2,2,2

Dear R users When I use OPTIM with BFGS, I've got a significant result without an error message. However, when I use OPTIMX with BFGS( or spg), I've got the following an error message. ---------------------------------------------------------------------------------------------------- > optimx(par=theta0, fn=obj.fy, gr=gr.fy, method="BFGS", >

Hi Reuben, I am puzzled to note that the gradient check in "optimx" does not work for you. Can you send me a reproducible example so that I can figure this out? John - I think the best solution for now is to issue a "warning" rather than an error message, when the numerical gradient is not sufficiently close to the user-specified gradient. Best, Ravi.

Hello all, I’m trying to add some data points to a wireframe. X an Y axis are independent variables, Z axis is predicted probability. I’d like to add the original data points on which the predicted probabilities are based to the wireframe. I’ve followed some of the previous post on this but get stuck : ## first part yields the wireframe## setwd("C:/Temp") rnp <-

Hello, I would like to make a plot (preferably lines, but points will do too), where the line segment changes color depending on the value of the y-axis. For example, let's suppose the y-axis range is from -1 to 1. Points close to -1 would be colored blue, while points close to 1 will be colored red. Points in between will be varying degrees of blue/red depending on how close they

Hi, how can I create a rainbow gradient in R? For example, let's say I have a plot of y = x...and I want the plot to go from red -> orange -> yellow -> green -> blue -> etc. Right now, I know how to do something like go from red to blue, using the plotrix library: library(plotrix) redToBlue <-

Hi all, Is there a way to fill a rectangle or polygon with a color and/or transparency gradient? This would be extremely useful for me in terms of adding some additional information to some plots I'm making, especially if I could define the gradient on my own by putting functions into rgb something like rgb( r=f(x,y), g=f(x,y), b=f(x,y), alpha=f(x,y) ). Not so important whether the

Hi, I'm very interested in using the constrOptim() function currently in the R-devel sources. In particular, I'm trying to fit point process conditional intensity models via maximum likelihood. However, I noticed that the gradient of the objective function must be supplied for all but the Nelder-Mead method. I was wondering why this was because optim() itself does not require a gradient

Hi all,I would like to draw a simple circle where the color gradient follows the rule color = 1/(r^2) where r is the distance from the circle. I would also like to add a color bar with values going from -40 to -110 (and associate those with the color gradient that fills the circle). So far I experiemented with draw circle

Dear all Suppose I have teeth like data similar like x <- 1:200 y <- 0.03*x[1:100]+rnorm(100, mean=.001, sd=.03) z <- 3-rep(seq(1,100,10),each=10)*.03+rnorm(100,mean=.001, sd=.03) plot(x,c(y,z)) and I want to have a gradient estimations for some values from increasing part of data like y.agg <- aggregate(diff(c(y,z)), list(rep(seq(1,200,10),each=10)[1:199]), mean) y.agg[1:10,]

Dear R-help subscribers; I have a question regarding making gradients in R. I've searched on the web, but was only able to find functions that make a gradient between color X and Y, which is not what I want. I want to 'pick out' individual, smaller pieces of a gradient based on a range of numbers. Say that I have a range of numbers, leading from 0 to 1. Then I want 0 to refer to