Updates code after cvxpy 1.7.4 release

gcsopt/programs.py

@@ -216,12 +216,12 @@ def to_conic(self):
         conic_program = ConicProgram(cp_conic.x.size, id_to_range, self.binary_variable)
 
         # Define cost of conic program.
-        cd = cp_conic.c.toarray().flatten()
+        cd = cp_conic.q.toarray().flatten()
         conic_program.add_cost(cd[:-1], cd[-1])
 
         # Define constraints of conic program. Sparse matrices are converted to
         # dense arrays, since keeping them sparse seems to make things slower.
-        cols = cp_conic.c.shape[0]
+        cols = cp_conic.q.shape[0]
         Ab = cp_conic.A.toarray().reshape((-1, cols), order='F')
         K = [(type(c), c.size) for c in cp_conic.constraints]
         conic_program.add_constraints(Ab[:, :-1], Ab[:, -1], K)
@@ -234,4 +234,4 @@ def solve(self, **kwargs):
         """
         prob = cp.Problem(cp.Minimize(self.cost), self.constraints)
         prob.solve(**kwargs)
-        return prob.value
+        return prob.value

requirements.txt

@@ -1,3 +1,3 @@
 numpy
-cvxpy >=1.5, <=1.7.1
+cvxpy >=1.7.4
 pytest

setup.py

@@ -15,7 +15,7 @@
     packages=find_packages(),
     install_requires=[
         "numpy",
-        "cvxpy >=1.5, <=1.7.1",
+        "cvxpy >=1.7.4",
         "pytest",
     ],
 )