Gurobi matrix variable object. An
MVar is a NumPy ndarray of
Gurobi variables. Variables are always associated with a particular
model. You typically create these objects using
Many concepts, properties and methods of the MVar class lean on equivalents in NumPy's ndarray class. For explanations of concepts like shape, dimensions, or broadcasting, we refer you to the NumPy documentation.
expr1 = A @ x expr2 = A @ x + B @ y + z expr3 = x @ A @ x + y @ B @ yThe first two expressions are linear, while the third is quadratic.
In the examples above (and in general), and can be NumPy ndarray objects or any of the sparse matrix classes defined in SciPy.sparse. Dimensions of the operands must compatible, in the usual sense of Python's matrix multiplication operator. For example, in the expression , both and must have at least one dimension, and their inner-most dimensions must agree. For a complete description of shape compatibility rules, we refer you to Python's documentation
Variable objects have a number of attributes. The full list can be found in the Attributes section of this document. Some variable attributes can only be queried, while others can also be set. Recall that the Gurobi optimizer employs a lazy update approach, so changes to attributes don't take effect until the next call to Model.update, Model.optimize, or Model.write on the associated model.
We should point out a few things about variable attributes. Consider
lb attribute. Its value can be queried using
mvar.lb. The Gurobi library ignores letter case in attribute
names, so it can also be queried as
Attribute values are returned as a NumPy
ndarray that has the
same shape as
mvar, where each element contains the attribute
value for the corresponding element of the
An attribute can be set,
using a standard assignment statement (e.g.,
var.lb = l),
l being either an
ndarray with the appropriate
shape, or a scalar which is then applied to all of the associated
However, as mentioned earlier, attribute modification is done in a
lazy fashion, so you won't see the effect of the change immediately.
And some attributes can not be set (e.g., the
x attribute), so
attempts to assign new values to them will raise an exception.
You can also use MVar.getAttr/
MVar.setAttr to access
attributes. The attribute name can be passed to these routines as a
string, or you can use the constants defined in the
GRB.Attr class (e.g.,