cvxpy-base

import cvxpy as cp import numpy as np # Define variables x = cp.Variable() y = cp.Variable() # Define objective function objective = cp.Minimize((x - y)**2 + 1) # Define constraints constraints = [x + y >= 0, x - y >= 0, x <= 3] # Formulate the problem problem = cp.Problem(objective, constraints) # Solve the problem (requires a solver to be installed) try: problem.solve() if problem.status == cp.OPTIMAL or problem.status == cp.OPTIMAL_INACCURATE: print(f"Problem status: {problem.status}") print(f"Optimal value: {problem.value:.4f}") print(f"Optimal x: {x.value:.4f}") print(f"Optimal y: {y.value:.4f}") else: print(f"Problem did not solve to optimality. Status: {problem.status}") except cp.error.SolverError as e: print(f"Solver Error: {e}") print("\nHint: To solve problems with `cvxpy-base`, you must install a compatible solver separately. ") print("For example: `pip install ecos` or `pip install osqp`. ") print("Alternatively, install the full `cvxpy` package: `pip install cvxpy`.") except Exception as e: print(f"An unexpected error occurred: {e}")