similar to: interp-problem

The akima package has a problematic license (it doesn't allow commercial use), so it's been recommended that people use the interp package instead. When I use interp::interp instead of akima::interp, I get reasonable output from your example. So that's another reason to drop akima... Duncan Murdoch On 26/01/2023 9:35 a.m., PIKAL Petr wrote: > Dear all > > I have this

Dear all I have this table > dput(mat) mat <- structure(c(2, 16, 9, 2, 16, 1, 1, 4, 7, 7, 44.52, 42.8, 43.54, 40.26, 40.09), dim = c(5L, 3L)) And I want to calculate result for contour or image plots as I did few years ago. However interp does not compute the z values and gives me zeros in z matrix. library(akima) > interp(mat[,1], mat[,2], mat[, 3], nx=5, ny=5) $x [1] 2.0 5.5

Dear R users, I want to do a fitted.contour plot of selected columns of a dataframe M with M$AM and M$Irradiance as x and y axes respectively. The level of the contour shall be determined by M$PR. Some words on my data first. Dataframe M looks like: head(M$Irradiance) [1] 293 350 412 419 477 509 head(M$AM) [1] 2.407 2.161 1.964 1.805 1.673 1.563 head(M$PR) [1] 70.102 72.600 75.097 80.167

Dear all; First of all, this is probably a more conceptual question than a R-related one, but still want to give it a try. When working with the interpolation function "interp" from the package akima and the triangulation function "tri.mesh" from package tripack I've got NA's for the interpolation and "error" for the triangulation. The data is arranged in a

Hi, I'm currently hunting a bug in the akima library, especially in the code behind the interpp.old function (bi-variate linear interpolation). It is based on a triangulation algorithm, interpolation at a given point needs to know the triangle which contains this point, then the interpolation is a straightforward calculation based on the three vertexes. The problem is: Sometimes the triangle

Dear all. I am using the akima function to produce 3d contour plots using interp based on irregular data. using the eg in the akima manual library("akima") data(akima) plot(y ~ x, data = akima, main = "akima example data") with(akima, text(x, y, formatC(z,dig=2), adj = -0.1)) ## linear interpolation akima.li <- interp(akima$x, akima$y, akima$z) image (akima.li, add=TRUE)

Hi How can I do the same has interp in s+ with R ? I've looked to "approxfun" but didn't figured out how to do it. Thanks EJ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body",

Dear All I hope that someone can help. I am working with sp pakage and akima library("akima") library(sp) imagine lots of different dataframes, of row = 100 columns = 3 of x and y coordinates with z values I will call these data frames for the sake of this example akima akima<-as.list(1:100) producing 100 dataframes dataframes of the form akima[[i]] I then wish to interp this

Hi everyone I was using spline to interpolate single or two consecutive missing data points in time series. However, when it comes to longer gaps in the data the spline function generate new data for both my known and unknown data (see below). Aside from not understanding why this happens, I thought thought I might try function "aspline" in library (akima). However, I cannot install or

Hi I'm looking to a function in R equivalent to S-PLUS' "interp". Is there any implementation in R? If not, is there any similar interpolation function such that at the data points the interpolated values concides with the data? Thanks in advance P.J. Paulo Justiniano Ribeiro Jr Dept Maths & Stats - Fylde College Lancaster University Lancaster LA1 4YF - U.K.

Full_Name: Jonathan Lees Version: 2.0.1 OS: linux-gnu Submission from: (NULL) (152.2.75.65) there is a problem with calculating the convex hull in 2-D interpolation using the codes interp fromt eh akima package: x =c(0.6505304, -1.1821562, -0.2600792, 0.7913716) y = c(1.0424226, 0.1754048, -1.4523334, 0.2349112) z = c(0.000, 3.042, 0.370, 0.122) EX = seq(from=min(x), to=max(x),

Hello, I have a long list of x-, y- and z-data and try to generate a heatmap. Obviously there are several data with identical x- and y-values. I get the following error message: Error in interp.old(x, y, z, xo = xo, yo = yo, ncp = 0, extrap = extrap, : duplicate data points: need to set 'duplicate = ..' Unfortunately there seems no help screen on "duplicate". I'd prefer

Hi, There is an excellent article at http://www.biomedcentral.com/1471-2105/9/307 by Stroble, et al. describing variable importance in random forests. Does anyone have any suggestions (besides imputation or removal of cases) for how to deal with data that *have* missing data for predictor variables? Below is an excerpt of some code referenced in the article. I have commented out one line and

Dear list members, I'm running some tests looking at differences between means for various levels of a factor, using Tukey's HSD method. I would like to plot the data as boxplots or dotplots, with horizontal significance lines indicating which groups are statistically significantly different, according to Tukey HSD. Here's a nice image showing an example of such a graphical

Hello all, I'm very new to R and am having some trouble with the results of the interp function. I'm trying to produce a chart roughly akin to a weather map with natural looking filled contours over a large region of the south pacific. I've got a list of points and values to be mapped to those points and I use the interp function as follows: tab<-read.table("data.txt")

Dear List, I'm using interp() to prepare 3d data for plotting with the contour() function. If have x,y and z data. All are arrays. X and Y are sampled in an orderly fashion on a grid (a circular sub-area of a grid - see plot). I'm trying to use interp() to get x and y arrays and a z matrix that can be fed to contour(). This is the command:

I wanted a simple function for bilinear interpolation on a 2-D grid, and interp.surface() in the fields package didn't quite suit my needs. In particular, it requires uniform spacing between grid points. It also didn't have the "visual" reference frame I was looking for. Here is an alternative function, followed by an example. # A function for bilinear interpolation on a 2-d

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 all! I'm using R 2.12.1 in Ubuntu 10.04. Problem is that when using functions like interp (package akima) and akimaInterp (package fUtilities), I get different results every time for the same data set. I've checked the interpolated results, and two examples (in attachment) have different sum of NA values. Also when I subtract the x,y,z values from two interpolations of the same data

hello! i'm dealing with the following: i've collected a factor covariable at irregularly placed sampling points along a line with spatial informations, i.e.: dataset<-c(x-coordinates, y-coordinates, level-of-factor) the factor describes the density of vegetation between 0 (no ground cover) and 5 (almost complete cover). id like to produce a map similar to the ones the akima package