Big trees fall hard and kill the python

failure to create cairo surface: invalid value (typically too big) for the size of the input (surface, pattern, etc.)

I couldn't really include the largest graph as it would be too much. ( It is 22,000 x 1,000 pixels) or (about 80 M data) The continuing tree tests found the limit of graphing in python and perhaps dot itself.

[9, 7, 8, 25, 2, 8, 9, 3, 6]
[1, 3, 5, 3, 3, 1, 5, 1, 2]
['vase', 'coin', 'ring', 'gold', 'copper', 'lead', 'painting', 'silver', 'tv']
Dictionary Length 312 2 to the nth 512
Scope of solution 206

I used some csv code to input arrays as it is easier.

r = mlab.csv2rec('/home/user/tree.csv') N = len(r) for row in r: verts.append(row) for vert in verts: values.append(vert[0]) weights.append(vert[1]) item_names.append(vert[2])

Below is the csv file that was usable without overflow. I am sure I can do larger trees, but graphing them is a problem unless I do something else for large trees. It is interesting that the running time has everything to do with the scope of the solution and not the size of the problem. I would guess that this has something to do with sparse matrices as well.

value,weight,name 9,1,"vase" 7,3,"coin" 8,5,"ring" 25,3,"gold" 2,3,"copper" 8,1,"lead" 9,5,"painting" 3,1,"silver" 6,2,"tv"


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