dendrogram

问题 I have the following code var m = [20, this.settings.get("margin_right"), 20, this.settings.get("margin_left")], w = width - m[1] - m[3], h = height - m[0] - m[2], i = 0; var tree = d3.layout.tree() .size([h, w]); var diagonal = d3.svg.diagonal() .projection(function(d) { return [d.y, d.x]; }); var vis = d3.select(this.el).append("svg:svg") .attr("width", w + m[1] + m[3]) .attr("height", h + m[0] + m[2]) .append("svg:g") .attr("transform", "translate(" + m[3] + "," + m[0] + ")"); data.x0 = h

问题 I am new to scipy but I managed to get the expected dendrogram. I am some more questions; In the dendrogram, distance between some points are 0 but its not visible due to image border. How can I remove the border and make the lower limit of y-axis to -1 , so that it is clearly visible. e.g. distance between these points are 0 (13,17), (2,10), (4,8,19) How can I prune/truncate on a particular distance. for e.g. prune at 0.4 How to write these clusters(after pruning) to a file My python code:

问题 I am trying to figure out how the output of scipy.cluster.hierarchy.dendrogram works... I thought I knew how it worked and I was able to use the output to reconstruct the dendrogram but it seems as if I am not understanding it anymore or there is a bug in Python 3 's version of this module. This answer, how do I get the subtrees of dendrogram made by scipy.cluster.hierarchy, implies that the dendrogram output dictionary gives dict_keys(['icoord', 'ivl', 'color_list', 'leaves', 'dcoord']) w/

问题 Is there an easy way to calculate lowest value of h in cut that produces groupings of a given minimum size? In this example, if I wanted clusters with at least ten members each, I should go with h = 3.80 : # using iris data simply for reproducible example data(iris) d <- data.frame(scale(iris[,1:4])) hc <- hclust(dist(d)) plot(hc) cut(as.dendrogram(hc), h=3.79) # produces 5 groups; group 4 has 7 members cut(as.dendrogram(hc), h=3.80) # produces 4 groups; no group has <10 members Since the

问题 How can I individually colour the labels of a dendrogram so that they match the colours of the clusters in MATLAB? Here is an example desired output generated using the code in my answer below (note the lables are just the 50 charater series 'A':'r' ): If there is a more straightforward way to do this, please do post an answer as I was unable to find the solution to this by googling. If not, the code is below for posterity. 回答1: I could not find a definitive answer to this but I managed to

问题 I have a numeric matrix in R with 24 rows and 10,000 columns. The row names of this matrix are basically file names from which I have read the data corresponding to each of the 24 rows. Apart from this I have a separate factor list with 24 entires, specifying the group to which the 24 files belong. There are 3 groups - Alcohols, Hydrocarbon and Ester. The names and the corresponding group to which they belong look like this: > MS.mz [1] "int-354.19" "int-361.35" "int-368.35" "int-396.38" "int

问题 I have done a Heat Map using the function heatmap.2 of gplots in R, but I don't have an idea of how to coloring the branches and tick labels per groups (Eg. if I cut the tree to have four gruops like in my second figure). I have checked that it is possible to color the dendrogram alone using dendextend package. Also there is a heatmap here: selecting number of leaf nodes of dendrogram in heatmap.2 in R with a colored dendrogram, but I can't implement it in my example. Somebody can help me

问题 I have a dendrogram given to me as images. Since it is not very large, I can construct it "by hand" into an R object. So my question is how do I manually create a dendrogram (or "hclust") object when all I have is the dendrogram image? I see that there is a function called "as.dendrogram" But I wasn't able to find an example on how to use it. (p.s: This post is following my question from here) Many thanks, Tal 回答1: I think you are better of creating an hclust object, and then converting it to

问题 I have a NxM matri with values that range from 0 to 20. I easily get an heatmap by using Matplotlib and pcolor. Now I'd like to apply a hierarchical clustering and a dendogram using scipy. I'd like to re-order each dimension (rows and columns) in order to show which element are similar (according to the clustering result). If the matrix would be square (NxN) the code would be something like: clustering = linkage(matrix, method="average") dendrogram(clustering, orientation='right') How can I

问题 I'm looking for a library capable of drawing dendrograms of data in Java (not calculating them, I can do it by myself).. do you have any clues? Already tried to search it over Google but haven't found anything that is not stand-alone (while I need to embed the generation inside my program). Thanks! 回答1: Check out the JUNG graph library. It won't perform the actual clustering for you but is a really good library for visualising your results. 回答2: Take a look at Archaeopteryx. It has fairly