status: failed
duration: 17.543s
Captured stdout call
Length of H2 results:  30
Captured stderr call

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captured errors:
folder = 'ExampleModels'

    @pytest.mark.parametrize(
        'folder',
        [
            #'ExampleModels_rescale',
            'ExampleModels',
            'ExampleModels_working',
            'ExampleModels_working_F3',
            'ExampleModels_newFOM',
            'ExampleModels_newFOM_F3',
            'ExampleModels_DARMFOM',
        ]
    )
    def T_calc_H2(folder):
        sysB = get_systemB(folder = folder)
        io_scales = file_io.load(fjoin(folder, 'io_scales.yml')) # Saved by the normalization in the make function
    
        if '_F3' in folder:
            FOM_out = ["F3.out", "F2.out"]
        else:
            FOM_out = ["FBNS.out", "F2.out"]
        wn_in = ["S.in", "O.in"]
        control_in = ["U.in"]
        meas_out = ["T.out"]
    
        # currently NO-OP and could be removed
        sysB.sys = ssutil.scale_io(sysB.sys, FOM_out[0], FBNS_scale)
        sysB.sys = ssutil.scale_io(sysB.sys, FOM_out[1], FFlat_scale)
    
        # Scale the DARM output
        if 'DARM.out' in sysB.sys.outputs.keys():
            print('scaling DARM')
            DARM_scale_factor = strain2m * SNR_intg_factor
            sysB.sys = ssutil.scale_io(sysB.sys, 'DARM.out', DARM_scale_factor)
    
        params = {}
        if folder == 'ExampleModels':
            params["F1_gain"] = np.geomspace(1e-0, 1e6, 30) * 1/FBNS_scale
        elif folder == 'ExampleModels_newFOM_F3':
            params["F1_gain"] = np.geomspace(1e-0, 1e6, 30) * 1/FBNS_scale
        else:
            params["F1_gain"] = np.geomspace(1e2, 1e6, 15) * 1/FBNS_scale
            #params["F1_gain"] = np.geomspace(1e2, 5e7, 30) * 1/FBNS_scale
    
        results_H2_bare = compute.calcOpt(
            sysB.sys,
            control_in,
            wn_in,
            meas_out,
            FOM_out,
            params,
            solver="LQG",
            plant_orig=sysB.orig_plant,
        )
    
        print("Length of H2 results: ", len(results_H2_bare))
    
    
        plotting_omega = np.logspace(-3, 4, 1000) * 2 * np.pi
>       results_H2 = compute.calcFullResults(
            results_H2_bare,
            colormap="jet",
            plot_omega=plotting_omega,
            io_scales = io_scales,
        )

/builds/buzz/test/ASC_SOLVER/test_solver_ADY.py:125: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/builds/buzz/src/buzz/compute.py:486: in calcFullResults
    CL, CL_all_io = connectK(result)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

bunch = {'F1_gain': 1.0, 'F2_gain': 1.0, 'FOM_out': ['FBNS.out', 'F2.out'], 'K': MIMOStateSpace with 
 inputs ['C.in'], 
 outputs ['C.out'], 
 and 38 dimensional states, ...}

    def connectK(bunch):
        # this function gives G/(1-G) as the closed loop gain
        plant = bunch['plant']
        # plant_sc = bunch['plant_scaled']
        K = bunch['K']
        control_in = bunch['control_in']
        meas_out = bunch['meas_out']
        K_inname = iodutil.listinputs(K)[0]
        K_outname = iodutil.listoutputs(K)[0]
    
        conlist = [[K_inname, meas_out[0]], [control_in[0], K_outname]]
        # print("CONLIST: ", conlist)
        # print("IOD pl", plant.iod)
        # print("IOD K", K.iod)
        # CL_all_io = ssutil.multiconnect([K, plant], conlist)
        CL_all_io = ssutil.multiconnect([plant, K], conlist)
>       CL_all_io = CL_all_io.topological_sort()
E       AttributeError: 'MIMOStateSpace' object has no attribute 'topological_sort'

/builds/buzz/src/buzz/compute.py:347: AttributeError