graph-visualization

I have 42 variables and I have calculated the correlation matrix for them in Matlab. Now I would like to visualize it with a schemaball. Does anyone have any suggestions / experiences how this could be done in Matlab? The following pictures will explain my point better: In the pictures each parabola between variables would mean the strength of correlation between them. The thicker the line is, the more correlation. I prefer the style of picture 1 more than the style in picture 2 where I have used different colors to highlight the strength of correlation. Kinda finished I guess.. code can be

I have a matrix A in Matlab of dimension mx2 that contains in each row the labels of two nodes showing a direct link in a network, e.g.: if the network has 4 nodes the matrix A could be A=[1 2; 1 3; 2 1; 2 4; 3 2; 4 1; 4 2] , where the first row means that there is a link from 1 to 2 , the second row means that there is a link from 1 to 3 , etc. Could you suggest me a quick way to draw the network from A? If you want the links to be directional, and have the Bioinformatics toolbox, you can create a biograph object. This also allows for labelling the nodes with identification strings if you so

I have some data similar to the data.frame d as follows. d <- structure(list(ID = c("KP1009", "GP3040", "KP1757", "GP2243", "KP682", "KP1789", "KP1933", "KP1662", "KP1718", "GP3339", "GP4007", "GP3398", "GP6720", "KP808", "KP1154", "KP748", "GP4263", "GP1132", "GP5881", "GP6291", "KP1004", "KP1998", "GP4123", "GP5930", "KP1070", "KP905", "KP579", "KP1100", "KP587", "GP913", "GP4864", "KP1513", "GP5979", "KP730", "KP1412", "KP615", "KP1315", "KP993", "GP1521", "KP1034", "KP651", "GP2876", "GP4715", "GP5056", "GP555", "GP408", "GP4217", "GP641"), Type = c("B", "A", "B", "A", "B", "B", "B", "B",

The official way to visualize a TensorFlow graph is with TensorBoard, but sometimes I just want a quick look at the graph when I'm working in Jupyter. Is there a quick solution, ideally based on TensorFlow tools, or standard SciPy packages (like matplotlib), but if necessary based on 3rd party libraries? TensorFlow 2.0 now supports TensorBoard in Jupyter via magic commands (e.g %tensorboard --logdir logs/train ). Here's a link to tutorials and examples. [EDITS 1, 2] As @MiniQuark mentioned in a comment, we need to load the extension first( %load_ext tensorboard.notebook ). Below are usage

I'm trying to visualize a really huge network (3M nodes and 13M edges) stored in a database. For real-time interactivity, I plan to show only a portion of the graph based on user queries and expand it on demand. For instance, when a user clicks a node, I expand its neighborhood. (This is called "Search, Show Context, Expand on Demand" on this paper ). I have looked into several visualization tools, including Gephi , D3 , etc. They take a text file as input, but I don't have any idea how they can connect a database and update the graph based on users' interaction. The linked paper implemented a