### 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?