similar to: contour plot

Dear all, I wonder about what could actually be possible with the function "contour": 1/ - the definition of contour lines is most often meaningless when the contours are drawn in areas where no real data points exist. It can however happen that irregular distributions lead to more or less irregular clouds of data points. Interpolations (eg: loess regression, GLM, etc...) are however

Hi All, I'm having difficulty making a contour plot a would like some help. A standard contourplot can be made by having an x,y, and some matrix (shape x*y) with contents: x = 1:10 y = 1:10 cont <- matrix(runif(100,min=1,max=2),nrow=10,ncol=10) filled.contour(x,y,cont) Looks very nice. Sometimes data comes in a different format however. Basically an x and an y, and a vector z with all

Apologies for the mass mailing today! I am attempting to produce a contour plot for phsical data on a map matrix. I have a small number of data points which each has an (x,y) co-ordinate together with a corresponding value which I would like to cvreate a contour plot for. I have tried the following code: contour(data$x,data$y,data$value) but am told: Error in contour.default(data$x, data$y,

Dear all, When a conventional kriging and then a contour plot is limited with a polygon (as possible with krige.conv and contour.kriging), the polygon border is displayed in black by default. > kc<-krige.conv(CZdata,loc=pred.grid,borders=czpoly,krige=krige.control(obj.m=ls)) > plot(CZcoord,xlab="x",ylab="y",type="n",asp=1) >

Hi, I would like to make a contour plot with the data below, x-axis= Day (increasing order, day number is out of 365 days of a year), y-axis= Depth (varies), and z=pH. I tried to use filled.contour function, but not sure the proper way to ordinate my z results into a matrix with different x and y length. After that, if I attempted to plot the data, the x and y values are not in ascending

Hi All, I am trying to reproduce this using R instead. [image: Full-size image (38 K)] I tried using the following code *SChla <- read.csv("SM_Chla_data.csv")* *Atlantis <- SChla[16:66,]* *head(Atlantis)* * * Seamount Station Depth Pico Nano Micro Total_Ch dbar Latitude Longitud 16 Atlantis 1217 Surface 0.0639 0.1560 0.0398 0.2597 2.082 -32.71450 57.29733

Dear R users, I have created a Loess surface in R, in which x is relative longitude by miles, y is relative latitude by miles, and z is population density at the neighborhood level. The purpose is to identify some population centers in the region. I'm wondering if there is a way to determine the coordinates (x,y) of each center, so I can know exactly where they are. Let me use the

Hi R users I'm looking for a way to do a contour plot of the attached 2D matrix. Using contour() gives me some ugly contour lines that I would like to smooth. Any ideas? oliverjack38 http://r.789695.n4.nabble.com/file/n4642291/param1-4.txt param1-4.txt -- View this message in context: http://r.789695.n4.nabble.com/Smooth-contour-of-a-matrix-tp4642291.html Sent from the R help mailing

Hello, I have some data that will be in the form: structure(list(station = structure(c(20L, 2L, 4L, 19L, 3L, 11L, 1L, 5L, 10L, 12L, 17L, 18L, 6L, 9L, 13L, 16L, 7L, 8L, 15L, 14L ), .Label = c("1", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "2", "3",

Is it possible to plot unevenly spaced data with image/contour function? Below is an example of the type uneven data that I'm trying to plot with image/contour functions. For example, I would like to have the x-distance on the x-axis and y-distance on the y-axis and then the temperature values determine the color used. Unfortunately this data was sampled such that it is not evenly

By any chance are there any alternatives to image(...) and filled.contour(...) I used Rseek to search for that very topic, but didn't turn over any leads... http://www.rseek.org/?cx=010923144343702598753%3Aboaz1reyxd4&newwindow=1&q=alternative+to+image+and+filled.contour&sa=Search&cof=FORID%3A11&siteurl=www.rseek.org%252F#1238 I'm sure there are some out there, but

Question: I have matrix (n x3) that represents discrete data. Each row of matrix is 3-D point (x,y,z). I would like to get contour map (z value) at two dimension (x,y). How can I use related contour function to do this job? I am not sure if I clarify this question. For example, we can get point (x,y) at 2 dimension according to first two columns of matrix. Then I want to connect same value

Hello. Is there an easy-to-use contour plot function analogous to scatterplot3d that can draw handle a dataset of arbitrary (x,y,z) triplets? That is, say x, y, and z are each measured quanties, and exhibit neither order nor regularity. I looked at the lattice package function "contourplot" but it seems complicated, and it's not clear from the documentation whether it can

I apologize for what may be a newbie question: I have two sets of data, one is X,Y,Z data that I'd like to make a contour plot of (Z defining the contours), and a second set of X,Y data (Y as a function of X) which I would like made into a line plot OVERLAYED on the contour plot (X and Y from both plots are in the same units and will have overlapping values). Any suggestions on how to do this

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

Dear All, I would like to plot a scalar (e.g. a temperature) on a non-rectangular domain (or even better: I would simply like to be able to draw a contour plot on an arbitrary 2D domain). I wonder if there is any tool to achieve that with R. I did some online search in particular on the list archives, found several queries similar to this one but was not able to find any conclusive answer. I

Hi all, I have a data frame with "clustered" rows as follows: Cu1 x1 y1 z1 ... Cu1 x2 y2 z2 ... Cu1 x3 y3 z3 ... # end of first cluster Cu1 Cu2 x4 y4 z4 ... Cu2 x5 y5 z5 Cu2 ... # end of second cluster Cu2 Cu3 ... ... "cluster"-size is 3 in the example above (rows making up a cluster are always consecutive). Is there any faster way to sample n clusters (with

Hi, I thought about this but programming it seems rather difficult so I was wondering if a function exists for this in R (as most of the times it turns out that it does): I have a map (shapefile) and for about 50 points on that map (GPS locations) I have heights. Is there a function which can make a perspective plot or contour plot or the like from this little data? Or maybe some function I can

Hello, I'm dealing with the following problem: I have a table with x and y coordinates and corresponding values of a mineral concentration, let's call it z. Can someone provide me a short step-by-step manual for the steps necessary to get a contour map? How to sort and interpolate my matrix to an equidistant grid which can afterwards be plotted by contour(x,y,z)? (e.g. fill the

Dear, I have XYZ data available in a MySQL database. I get it out, can plot the data with the plot() function, load it into a geoR datastructure. But what I actually would like to do is a simple contouring of the data based on a no Kriging interpolation such as TIN based. I know the first thing I shold do is interpolate a full matrix for the region I have my points for, then contour should