similar to: function used to smooth the scatter plot and generate a density map

Hi, I''m using heatmap.2 to cluster my data, using the centroid method for clustering and the maximum method for calculating the distance matrix: library("gplots") library("RColorBrewer") test <- matrix(c(0.96, 0.07, 0.97, 0.98, 0.50, 0.28, 0.29, 0.77, 0.08, 0.96, 0.51, 0.51, 0.14, 0.19, 0.41, 0.51), ncol=4, byrow=TRUE)

heatmap.2 defaults to dist for calculating the distance matrix and hclust for clustering. Does anyone now how I can set dist to use the euclidean method and hclust to use the centroid method? I provided a compilable sample code bellow. I tried: distfun = dist(method = "euclidean"), but that doesn't work. Any ideas? library("gplots") library("RColorBrewer") test

I have used heatmap to visualize my microarray data. I have a matrix of M-values. I do the following. #The distance between the columns. sampdist <- dist(t(matrix[,]), method="euclidean") sclus <- hclust(sampdist, method="average") #The distance between the rows. genedist <- dist(matrix[,], method="euclidean") gclus <- hclust(genedist,

When plotting a heatmap with heatmap.2 the shortest euclidean distance cluster is plotted in the top left corner of the heatmap <http://r.789695.n4.nabble.com/file/n4651430/heatmap.2.jpeg> when plotting the same data with pheatmap the very same cluster is in the bottom right corner <http://r.789695.n4.nabble.com/file/n4651430/pheatmap.jpeg> I am just wondering what I would need

I have a data which contain some NA value in their elements. What I want to do is to **perform clustering without removing rows** where the NA is present. I understand that `gower` distance measure in `daisy` allow such situation. But why my code below doesn't work? __BEGIN__ # plot heat map with dendogram together. library("gplots") library("cluster")

Hi, How do I anchor z=0 to the white color in a levelplot so that the color changes from cyan to magenta precisely as z changes from negative to positive? Also is it easy to change color scheme, say to blue/red as it's more dramatic? Is there a better function for showing heatmap with a color bar? Thanks in advance for any help, I've played with image, heatmap and levelplot a little and

Hello, every one, Using the qt() function in R, I got a different Student t-value with the Student t table. e.g. the return value of function qt(0.95,9) is 1.833, while in table it is 2.262. I do not know why the difference exists. I guess it may be a bug in R. -- Íõ»¯Èå ²©Ê¿Ñо¿Éú ±±¾©Ê¦·¶´óѧ¾°¹ÛÉú̬Óë¿É³ÖÐøÐÔ¿ÆѧÑо¿ÖÐÐÄ ±±¾©Êк£µíÇøнֿÚÍâ´ó½Ö19ºÅ±±¾©Ê¦·¶´óѧÉúÃü¿ÆѧѧԺ 100875 Huaru

Any hint on the date of LLVM Social ShangHai? Zhang > 在 2018年5月29日，14:22，Leslie Zhai via llvm-dev <llvm-dev at lists.llvm.org> 写道： > > Hi Chris, > > Thanks for your response! > > Wu Wei made this happen! and he is organizing LLVM social in Shanghai, Hang Zhou and Shen Zhen. I hope one day there is LLVM developer meeting in China :) > > >> 在 2018年05月29日

Hi Chris, Thanks for your response! Wu Wei made this happen! and he is organizing LLVM social in Shanghai, Hang Zhou and Shen Zhen. I hope one day there is LLVM developer meeting in China :) 在 2018年05月29日 14:13, Chris Lattner 写道: > This is really great, thank you for getting this off the ground! > > -Chris > > >> On May 28, 2018, at 9:42 PM, Leslie Zhai <lesliezhai at

Hope live broadcast ! <br/><br/>Thanks,<br/>yaoxiao 在 2018-05-29 15:02:30，"Leslie Zhai via llvm-dev" <llvm-dev at lists.llvm.org> 写道： > > >在 2018年05月29日 14:58, mayuyu.io 写道: >> Any hint on the date of LLVM Social ShangHai? >Wu Wei scheduled July 1th http://hellollvm.org/ > > >> >> Zhang >> >>> 在

在 2018年05月29日 14:58, mayuyu.io 写道: > Any hint on the date of LLVM Social ShangHai? Wu Wei scheduled July 1th http://hellollvm.org/ > > Zhang > >> 在 2018年5月29日，14:22，Leslie Zhai via llvm-dev <llvm-dev at lists.llvm.org> 写道： >> >> Hi Chris, >> >> Thanks for your response! >> >> Wu Wei made this happen! and he is organizing LLVM social in

Dear list, In using the scatter.smooth() function (modreg) on a small data set (100 obs) the following error was produced: > scatter.smooth(Na, S) Warning message: k-d tree limited by memory. ncmax= 200 I haven't used scatter.smooth much but when I have, I haven't seen this message before. gc() returns > gc() used (Mb) gc trigger (Mb) Ncells 417693 11.2 667722

Hello When I run scatter.smooth(jitter(weight), jitter(height2), span = .25, evaluation = 50, pch = '.') I get the type of graph I thought I would get, but also a warning..... k-d tree limited by memory. ncmax= 528 I always get concerned when there are warnings I don't understand. What's a k-d tree? Is this something to be concerned about? Thanks Peter Peter L. Flom,

Hello, I have been using scatter.smooth and been trying to format my plots and been unable to adjust the line type or color of the smooth curve. When I specify col in scatter.smooth, I can adjust the color of the scatter plot points, but the line always stays black and solid. lty has no effect. When I specify par prior to calling scatter.smooth, col will change the color of the points,

Dear List, Having had my appetite sufficiently whetted by Prof. Ripley's email about the new graphics capabilities in Unixes, I wanted to try them out. I updated to svn r44608, configured with the following options: R is now configured for x86_64-unknown-linux-gnu Source directory: .. Installation directory: /usr/local C compiler: gcc -O3 -g -std=gnu99

How can perform logarithmic binning in the scatterplot? I could only take the log of the variables and plot them, but I am sure that is not the way. I have a very huge data, and would want to plot those high density scatterplots and code then with different colors for the bins/density. -- View this message in context:

I rewrote scatter.smooth to handle missing values, but I have a question about a move I had to make. Here's the code: Mscatter.smooth<-function (x, y, span = 2/3, degree = 1, family = c("symmetric", "gaussian"), xlab = deparse(substitute(x)), ylab = deparse(substitute(y)), ylim = range(y, prediction$y), evaluation = 50, ...) { if (inherits(x,

Hi, what i need is as the example i attached in the box plot. As you can see, the boxplot have margins and it kind of follow the coding I've added, but, it does not happen for the heat map. Could you help me with this.. Thanks in advance. the following is the coding i've used: # Draw the heatmap # heatmap.r # # Purpose: Create a heatmap # # Input: Data matrix as

Hi, I have created a heatmap using heatmap.2 having 7 clusters. I would like to extract the list of genes that are in these 7 clusters. Is there any function that can be used to extract genes for each cluster? Cheers, Sudhir -- __________________________________________________________ SAVE PAPER - Please do not print this e-mail unless absolutely necessary Being happy doesn't mean

Hello, I am entirely new to this list, and not very experienced with R yet (but very excited about it!!). I am struggling with a dataset of x and y coordinate points I am plotting as a density map as follows: trial <- read.csv(file="F12.csv", sep=",", skip=32, head=TRUE) trial.sub <- subset(trial, Seconds>=30) trial.sub <- subset(trial.sub, Seconds<=1830) d