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I am trying to perform test summarize using self organizing map (SOM) as the clustering model. Do we have any libraries for performing SOM in python.
There is one here, but in general SOM implementations are not part of the main machine learning libraries. There are two reasons
SOM's, although nice to look at, don't really perform well in real problems.
It is too easy to construct one by yourself.
I would suggest to make it yourself. It is very easy and a great way to introduce yourself to python. The main code of the SOM itself is about 3 lines (a loop and one update). The remaing of the code would be for loading the data and plotting them, but you won't avoid that part of the code by using an external library
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I currently have a MIP model formulated in Gurobi's python API, but recently I've been looking into tools such as PuLP and OR-Tools that allow me to build a model and feed it to multiple different optimizers. One feature of Gurobi used extensively in my model is the ability to have constraints that use functions such as and, or, min, max, and abs. However it seems as if PuLP and OR-Tools do not support these. Are there any alternatives that do support these? Or would I have to reformulate my model if I want to use something like this?
For or-tools, we only provide the minimal API for the linear solver.
If your problem is more structured (scheduling, routing, CP-like constraints), you can have a look at the CP-SAT interface:
https://developers.google.com/optimization/
https://github.com/google/or-tools/blob/master/ortools/sat/doc/index.md
Python examples are here:
https://github.com/google/or-tools/tree/master/examples/python
You might also want to have a look at Pyomo. It supports a variety of modeling tools and can call different solvers.
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Often on the Internet I saw such images and now I am interested in the implementation of this algorithm. The input is a template and a set of words, on the basis of which the image is drawn, the more often the word is used the more space it takes. As far as I know there is already a library for python that allows you to generate such images. Could you tell me which one?
Word cloud allows you to do this, and using its masks features should allow you to shape them: https://github.com/amueller/word_cloud would give you more information on how this can be done.
The above image is constructed using wordCloud!. Here you can find a tutorial on python.
I hope this helps...
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Using python I'm traying to monitor a small network, I did this using zabbix before and it work perfectly, zabbix is much bigger than what i want to do.
just ping every device in a text file.
I want to graphically visualize the results, opengl, matplotlib.. are very strong but are bigger than what I want to do.
Is there a python module that can do like this result:
example of graphical representation of results (map)
I just want to keep things very simple.
Try to use graph-tool if you're looking for a tool to analyze a network.
Graph-tool is an efficient Python module for manipulation and statistical analysis of graphs (a.k.a. networks). Conveniently draw your graphs, using a variety of algorithms and output formats (including to the screen).
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I have a huge set of coupled nonlinear integro-partial differential equations. After a long while trying to simplify the equations and solve them at least semi-analytically I have come to conclude there has been left no way for me but an efficient numerical method. Finite element seems most amenable as is based on Galerkin method which gives a weak form solution, so a great hope that it might finally solve the equations. But at the same time I am so new to this field to write the codes all from the scratch:
Is there any Python library already available that can efficiently do a Finite Element analysis?
Also I was interested if softwares like FEniCS/Dolphin might also solve integro-differential equations?
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I am looking for an API (preferably in python) that could be used to analyze complex networks. Basically I want to find things like:
Average shortest path,
Degree distribution
Giant Component
local clustering coefficient, global clustering coefficient etc..
Thanks
I would suggest Networkx and PyGraphViz. I've used them for a similar (but not as complex) graphing project in python and I love it.
The boost graph library has Python bindings.
I've used igraph on Linux. It started to grind on 64k nodes but that graph was becoming unwieldy any way.
Not sure about performance next to PyGraphViz but now you have a plenty of options.