def expr_as_np_array(cvx_expr: Expression) -> np.ndarray:
"""
Convert cvxpy expression into a numpy array.
:param cvx_expr: The cvxpy expression to be converted.
:return: The numpy array of the cvxpy expression.
"""
if cvx_expr.is_scalar():
return np.array(cvx_expr)
if len(cvx_expr.shape) == 1:
return np.array(list(cvx_expr))
# Then cvx_expr is a 2-D array.
rows = []
for i in range(cvx_expr.shape[0]):
row = [cvx_expr[i, j] for j in range(cvx_expr.shape[1])]
rows.append(row)
arr = np.array(rows)
return arr
def promote(expr: Expression, shape: Tuple[int, ...]):
""" Promote a scalar expression to a vector/matrix.
Parameters
----------
expr : Expression
The expression to promote.
shape : tuple
The shape to promote to.
Raises
------
ValueError
If ``expr`` is not a scalar.
"""
expr = Expression.cast_to_const(expr)
if expr.shape != shape:
if not expr.is_scalar():
raise ValueError('Only scalars may be promoted.')
return Promote(expr, shape)
else:
return expr
