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• Dendrogram generated by scipy-cluster does not show

  - by Space_C0wb0y

  I am using scipy-cluster to generate a hierarchical clustering on some data. As a final step of the application, I call the dendrogram function to plot the clustering. I am running on Mac OS X Snow Leopard using the built-in Python 2.6.1 and this matplotlib package. The program runs fine, but at the end the Rocket Ship icon (as I understand, this is the launcher for GUI applications in python) shows up and vanishes immediately without doing anything. Nothing is shown. If I add a 'raw_input' after the call, it just bounces up and down in the dock forever. If I run a simple sample application for matplotlib from the terminal it runs fine. Does anyone have any experiences on this?

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• plotting results of hierarchical clustering ontop of a matrix of data in python

  - by user248237

  How can I plot a dendrogram right on top of a matrix of values, reordered appropriately to reflect the clustering, in Python? An example is in the bottom of the following figure: http://www.coriell.org/images/microarray.gif I use scipy.cluster.dendrogram to make my dendrogram and perform hierarchical clustering on a matrix of data. How can I then plot the data as a matrix where the rows have been reordered to reflect a clustering induced by the cutting the dendrogram at a particular threshold, and have the dendrogram plotted alongside the matrix? I know how to plot the dendrogram in scipy, but not how to plot the intensity matrix of data with the right scale bar next to it. Any help on this would be greatly appreciated.

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• How do you compare the "similarity" between two dendrograms (in R) ?

  - by Tal Galili

  I have two dendrograms which I wish to compare to each other in order to find out how "similar" they are. But I don't know of any method to do so (let alone a code to implement it, say, in R). Any leads ? Thanks, Tal

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• hierarchical clustering with gene expression matrix in python

  - by user248237

  how can I do a hierarchical clustering (in this case for gene expression data) in Python in a way that shows the matrix of gene expression values along with the dendrogram? What I mean is like the example here: http://www.mathworks.cn/access/helpdesk/help/toolbox/bioinfo/ug/a1060813239b1.html shown after bullet point 6 (Figure 1), where the dendrogram is plotted to the left of the gene expression matrix, where the rows have been reordered to reflect the clustering. How can I do this in Python using numpy/scipy or other tools? Also, is it computationally practical to do this with a matrix of about 11,000 genes, using euclidean distance as a metric? thanks.

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• Error " Index exceeds Matrix dimensions"

  - by Mola

  Hi experts, I am trying to read an excel 2003 file which consist of 62 columns and 2000 rows and then draw 2d dendrogram from 2000 pattern of 2 categories of a data as my plot in matlab. When i run the script, it gives me the above error. I don't know why. Anybody has any idea why i have the above error? My data is here: http://rapidshare.com/files/383549074/data.xls Please delete the 2001 column if you want to use the data for testing. and my code is here: % Script file: cluster_2d_data.m d=2000; n1=22; n2=40; N=62 Data=xlsread('data.xls','A1:BJ2000'); X=Data'; R=1:2000; C=1:2; clustergram(X,'Pdist','euclidean','Linkage','complete','Dimension',2,... 'ROWLABELS',R,'COLUMNLABELS',C,'Dendrogram',{'color',5})

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• Drawing tree diagram in ASP.Net MVC

  - by Ivan Crojach Karacic

  I am creating an web application for my tae kwon do club. People are able to register online for a tournament. After the registration deadline the web application generates a dendrogram. Something like this: I am wondering now how to draw it. Because of the fact that there are my weight and age categories i have to draw them dynamicly for each group. What is the easiest way to draw this inside a MVC view?

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• Reordering matrix elements to reflect column and row clustering in naiive python

  - by bgbg

  Hello, I'm looking for a way to perform clustering separately on matrix rows and than on its columns, reorder the data in the matrix to reflect the clustering and putting it all together. The clustering problem is easily solvable, so is the dendrogram creation (for example in this blog or in "Programming collective intelligence"). However, how to reorder the data remains unclear for me. Eventually, I'm looking for a way of creating graphs similar to the one below using naive Python (with any "standard" library such as numpy, matplotlib etc, but without using R or other external tools).

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• hierarchical clustering on correlations in Python scipy/numpy?

  - by user248237

  How can I run hierarchical clustering on a correlation matrix in scipy/numpy? I have a matrix of 100 rows by 9 columns, and I'd like to hierarchically clustering by correlations of each entry across the 9 conditions. I'd like to use 1-pearson correlation as the distances for clustering. Assuming I have a numpy array "X" that contains the 100 x 9 matrix, how can I do this? I tried using hcluster, based on this example: Y=pdist(X, 'seuclidean') Z=linkage(Y, 'single') dendrogram(Z, color_threshold=0) however, pdist is not what I want since that's euclidean distance. Any ideas? thanks.

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• problem with hierarchical clustering in Python

  - by user248237

  I am doing a hierarchical clustering a 2 dimensional matrix by correlation distance metric (i.e. 1 - Pearson correlation). My code is the following (the data is in a variable called "data"): from hcluster import * Y = pdist(data, 'correlation') cluster_type = 'average' Z = linkage(Y, cluster_type) dendrogram(Z) The error I get is: ValueError: Linkage 'Z' contains negative distances. What causes this error? The matrix "data" that I use is simply: [[ 156.651968 2345.168618] [ 158.089968 2032.840106] [ 207.996413 2786.779081] [ 151.885804 2286.70533 ] [ 154.33665 1967.74431 ] [ 150.060182 1931.991169] [ 133.800787 1978.539644] [ 112.743217 1478.903191] [ 125.388905 1422.3247 ]] I don't see how pdist could ever produce negative numbers when taking 1 - pearson correlation. Any ideas on this? thank you.

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