AttributeError: 'gurobipy.Var' object has no attribute 'X' when model is optimized
AnsweredI am creating a Gurobi model to solve a minimization problem across a series of graphs, minimizing the distance from a node across a sample of graphs.
I have confirmed that the model is optimized, outputting model.Status of 2 and model.SolCount of 1. However, when trying to access the individual variable attributes using the var.X attribute, I get the title attribute error. Within prior debugging, I have seen that the .X attribute does not exist if the model has not yet been optimized, but mine has. Is there another way that I can get these values or fix this error? Thank you!
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Gurobi Staff
Hi Jack,
It will be hard to help without seeing some code. Are you able to share your code via a share drive, or github, or something like Google Colab?
- Riley
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Hi Riley,
The relevant code and files can all be found in the below Github repository:
https://github.com/Jack-Heavey-12/pool_testing/tree/main
The files 'pool.py' and 'lambda_pool.py' are both having the same errors.
Thank you for your help!
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Hi Jack,
I'd guess the issue is that you're creating the model within a function, and after the function is complete Python's garbage collector is removing the model, and consequently solution values.
A couple of solutions:
1) return the model object from the function, and assign it, so that it is not removed, or
2 you can assign the X values to an attribute on the variables, eg
def LinearProgram(graph, set_list, cascades, B=3, overlapping=True):
...
variables = m.getVars()
for v in variables:
v._X = v.X
return x, y, m.objVal, variables
...
def rounding(x_dict):
...
if limit <= x[S]._X:
...- Riley
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Thank you Riley, this did resolve the issue.
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