How do I pointwise multiply a numpy vector with a (1,) MVar with the matrix-friendly Python API?

If you are using Gurobi 10

In Gurobi 10, you can pointwise multiply a 1-D ndarray with a 1-D MVar of length one natively. This operation follows numpy's broadcasting rules. For example, the following expression:

$$\begin{align} \begin{bmatrix} y_1 \\ y_2 \\ y_3 \end{bmatrix} &= \begin{bmatrix} 1 \\ 1 \\ 1 \end{bmatrix} x \end{align}$$

can be constructed using the multiplication operator:

import gurobipy as gp
import numpy as np

m = gp.Model()
x = m.addMVar(1)
y = m.addMVar(3)

m.addConstr(y == np.ones(3) * x)

If you are using Gurobi 9.x

In Gurobi 9.x, it was not possible to pointwise multiply a 1-D ndarray with a 1-D MVar of length one. The above code results in TypeError: only size-1 arrays can be converted to Python scalars. Instead, this operation can be recast as a matrix-vector product:

import gurobipy as gp
import numpy as np

m = gp.Model()
x = m.addMVar(1)
y = m.addMVar(3)

m.addConstr(y == np.ones((3, 1)) @ x)

Note: Gurobi 9.0 introduced the first version of the Python matrix API. The developers are continually working to improve the usability of the matrix API.

Further information

• How do I multiply two MLinExpr objects together with the matrix-friendly Python API?
• How do I pointwise multiply two MVars with the matrix-friendly Python API?
• How do I multiply an array and a 2-D MVar object using the matrix-friendly Python API?
• How do I pointwise multiply an array and an MVar with the matrix-friendly Python API?