Error when using Sparse matrix with Gurobi variables

回答済み

Sagnik Basumallik

2020年08月16日 21:10

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Hi,

I have a dense matrix H which I have transformed into a sparse matrix.

from scipy import sparse
sH = sparse.csr_matrix(H)

I have a D matrix which is an identity matrix with Gurobi variables in the diagonal <gurobi.Var z[i,j]>.

I try to multiple the following:

r = np.dot(np.transpose(sH),D)

This is the error I am getting: ( I do not get this error if my matrices are not sparse)

---------------------------------------------------------------------------
TypeError                                 
Traceback (most recent call last)
var.pxi in gurobipy.Var.__rmul__()
TypeError: float() argument must be a string or a number, not 'csc_matrix'
During handling of the above exception, another exception occurred:
TypeError                                 Traceback (most recent call last)
linexpr.pxi in gurobipy.LinExpr.__imul__()
TypeError: float() argument must be a string or a number, not 'csc_matrix'
During handling of the above exception, another exception occurred:
GurobiError                               Traceback (most recent call last)
<ipython-input-74-48094dbb4ef2> in <module>()
----> 1 r = np.dot(np.transpose(sH),D)
<__array_function__ internals> in dot(*args, **kwargs)
var.pxi in gurobipy.Var.__rmul__()
linexpr.pxi in gurobipy.LinExpr.__imul__()
linexpr.pxi in gurobipy.LinExpr.__mul__()
linexpr.pxi in gurobipy.LinExpr._mul()
GurobiError: Invalid argument to LinExpr multiplication

 

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• 正式なコメント

  

  Simranjit Kaur

  • Gurobi Staff

  2025年06月23日 03:08 編集済み

  This post is more than three years old. Some information may not be up to date. For current information, please check the Gurobi Documentation or Knowledge Base. If you need more help, please create a new post in the community forum. Or why not try our AI Gurobot?.
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  Jaromił Najman

  • Gurobi Staff

  2020年09月02日 07:35

  Hi Sagnik,

  Could you provide a minimal working example producing the error you posted?
  
  In case, you were able to solve the problem, could you provide the solution of how you achieved it?
  
  Best regards,
  Jaromił

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  Brannon King

  2023年11月07日 23:43

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  This question is old, but so as it has an answer: you can't use numpy functions on scipy sparse objects. The transpose should be sH.T and the dot product should be done via the @ operator: sH @ D . 

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