T_ADY_make_sys - Buzz documentation

FBNSSS_DARM(return_name=False, return_scale=False)[source]¶

code

docstring

"""

"""

def FBNSSS_DARM(return_name=False, return_scale = False):

    if return_name:
        name = "FOM BNS (Hand Fit)"
        return name

    #BNS_zpk = file_io.load(fjoin('ExampleModels_DARMFOM/BNS_FOM_from_DARM.yml'))
    BNS_zpk = file_io.load(fjoin('ExampleModels_DARMFOM/BNS_FOM_IR.yml'))
    F_z = np.array(BNS_zpk["z"], dtype=np.complex128)
    F_p = np.array(BNS_zpk["p"], dtype=np.complex128)
    F_k = BNS_zpk["k"]

    F = SISO.zpk(F_z, F_p, F_k).asSS.mimo("FBNS.out", "FBNS.in")
    F, scale = ssutil.normalize_gain(F, norm=1, return_scale=True)
    if return_scale:
        return scale
    else:
        return F

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.FBNSSS_DARM

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

FBNSSS_Fit(gain=1, return_name=False, return_scale=False)[source]¶

code

docstring

"""

"""

def FBNSSS_Fit(gain=1, return_name=False, return_scale = False):

    if return_name:
        name = "FOM BNS"
        return name

    if gain != 1:
        NotImplementedError("This function does not support gain scaling")

    BNS_zpk = file_io.load(fjoin('ExampleModels_newFOM/BNS_FOM.yml'))
    print(BNS_zpk['z'])
    F_z = np.array(BNS_zpk["z"], dtype=np.complex128)
    #BNS_zpk["p"].append(BNS_zpk["p"][-1])
    F_p = np.array(BNS_zpk["p"], dtype=np.complex128)
    F_k = BNS_zpk["k"]

    #print(len(F_z))
    #print(len(F_p))
    F_mod = SISO.zpk(F_z, F_p, F_k).asSS
    F_iod = {"FBNS.in": 0, "FBNS.out": 0}
    F = ssutil.wieldSS(F_mod.A, F_mod.B, F_mod.C, F_mod.D, iod=F_iod)
    F, scale = ssutil.normalize_gain(F, norm=1, return_scale=True)
    if return_scale:
        return scale
    else:
        return F

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.FBNSSS_Fit

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

FBNSSS_Hand(return_name=False, return_scale=False)[source]¶

code

docstring

"""

"""

def FBNSSS_Hand(return_name=False, return_scale = False):

    if return_name:
        name = "FOM BNS (Hand Fit)"
        return name

    BNS_zpk = file_io.load(fjoin('ExampleModels_newFOM/BNS_FOM_handfit.yml'))
    F_z = np.array(BNS_zpk["z"], dtype=np.complex128)
    F_p = np.array(BNS_zpk["p"], dtype=np.complex128)
    F_k = BNS_zpk["k"]

    F = SISO.zpk(F_z, F_p, F_k).asSS.mimo("FBNS.out", "FBNS.in")
    F, scale = ssutil.normalize_gain(F, norm=1, return_scale=True)
    if return_scale:
        return scale
    else:
        return F

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.FBNSSS_Hand

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

FBNSsimpSS(return_name=False, lo_ord=4, return_scale=False)[source]¶

This is a pytest needing documentation

code

def FBNSsimpSS(return_name=False, lo_ord=4, return_scale=False):
    if return_name:
        name = "FOM BNS Simple"
        return name

    BNS_zpk = file_io.load(fjoin('FOMs/FBNSsimp_FOM.yml'))
    print(BNS_zpk['z'])
    F_z = np.array(BNS_zpk["z"], dtype=np.complex128)
    F_p = np.array(BNS_zpk["p"], dtype=np.complex128)
    F_k = BNS_zpk["k"]

    F = SISO.zpk(F_z, F_p, F_k).asSS.mimo("FBNS.out", "FBNS.in")
    F, scale = ssutil.normalize_gain(F, norm=1, return_scale=True)
    if return_scale:
        return scale
    else:
        return F

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.FBNSsimpSS

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

FFlatSS(gain=1, return_name=False)[source]¶

This is a pytest needing documentation

code

def FFlatSS(gain=1, return_name=False):
    if return_name:
        name = "FOM Flat"
        return name

    return SISO.zpk([], [], gain).asSS.mimo("F2.out", "F2.in")

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.FFlatSS

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

addSS(namespace='T', dt=0.0001, sub=False, outSufx=None)[source]¶

Create a state space model for an adder. It has two inputs and one output.

Parameters:

namespace (string) – The namespace to use for the model i.e. the letter that comes at the beginning of the input and output names. Defaults to ‘T’.
dt (float, optional) – The time step. Defaults to 1e-4.
sub (bool, optional) – If true, the model will be a subtractor. Defaults to False.

Returns:

Returns the local name space for the function including the state space model as mod, input output dictionary as iod, and namespace.

Return type:

wield.bunch

code

docstring

"""Create a state space model for an adder. It has two inputs and one output.

Args:
    namespace (string): The namespace to use for the model i.e. the letter that comes at the beginning of the input and output names. Defaults to 'T'.
    dt (float, optional): The time step. Defaults to 1e-4.
    sub (bool, optional): If true, the model will be a subtractor. Defaults to False.

Returns:
    wield.bunch: Returns the local name space for the function including the state space model as `mod`, input output dictionary as `iod`, and namespace.
"""

def addSS(namespace='T', dt=1e-4, sub=False, outSufx = None):

    A = np.zeros([0,0]) # Construct the A state matrix
    B = np.zeros([2,0]) # Construct the B state matrix
    C = np.zeros([0,1]) # Construct the C state matrix
    if sub:
        D = np.array([[1, -1]]) # Construct the D state matrix for a subtractor
    else:
        D = np.array([[1, 1]]) # Construct the D state matrix
    if outSufx == None:
        iod = {namespace+'.in.1': 0, namespace+'.in.2': 1, namespace+'.out': 0} # Input output dictionary
    else:
        iod = {namespace+'.in.1': 0, namespace+'.in.2': 1, namespace+'.out.'+outSufx: 0} # Input output dictionary
    return ssutil.wieldSS(A, B, C, D, iod=iod)

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.addSS

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

bode(sys, axB=None, F_Hz=None, omega_limits=None, include_zp=True, label=None, **kwargs)[source]¶

sys should be a wield.control.SISO object

code

docstring

"""
sys should be a wield.control.SISO object
"""

def bode(
    sys,
    axB=None,
    F_Hz=None,
    omega_limits=None,
    include_zp = True,
    label=None,
    **kwargs
):

    if axB is None:
        axB = mplfigB(Nrows = 2)

    if include_zp:
        z, p = sys._zp
        z = z[z.imag > 0]
        p = p[p.imag > 0]
        F_include = np.sort(np.concatenate(
            [
                z.imag,
                p.imag,
                z.imag - abs(z.real) - 1e-6,
                z.imag + abs(z.real) + 1e-6,
                p.imag - abs(p.real) - 1e-6,
                p.imag + abs(p.real) + 1e-6,
            ]
        )) / (2 * np.pi)
        F_include = F_include[F_include > 0]

        if omega_limits is None:
            omega_limits = (
                (F_include[0] + 1e-6) / 3,
                F_include[-1] * 3
            )

    if F_Hz is None:
        F_Hz = np.geomspace(omega_limits[0], omega_limits[1], 1000)

    if include_zp:
        print("F_include", F_include)
        F_Hz = np.sort(np.concatenate([F_Hz, F_include]))

    fr = sys.fresponse(f=F_Hz)
    axB.ax0.loglog(*fr.fplot_mag, label=label, **kwargs)
    if hasattr(axB, 'ax1'):
        axB.ax1.semilogx(*fr.fplot_deg225, label=label, **kwargs)
    return axB

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.bode

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

delayDrive(namespace='D', Sp=None, delay=0.001, order=1, numins=1, dt=0.0001)[source]¶

This is a pytest needing documentation

code

def delayDrive(namespace='D', Sp=None, delay=1e-3, order=1, numins=1, dt=1e-4):
    D = delaySS(namespace=namespace, delay=delay, order=order, numins=numins, dt=dt)

    if Sp is None or Sp == 1:
        #assert(False)
        return D

    #rename the input for pending merge
    D.iod[namespace + '.in.2'] = D.iod[namespace + '.in']
    del D.iod[namespace + '.in']

    #check that it only has 1 input and one output (THIS IS A HACKY WAY TO TEST)
    assert(len(Sp.iod) == 2)

    print(Sp.iod)
    Sp.iod.clear()
    Sp.iod[namespace + '.in'] = 0
    Sp.iod[namespace + '.out.1'] = 0
    print(Sp.iod)

    Dx = ssutil.multiconnect([Sp, D], [[namespace+'.in.2', namespace+'.out.1']])
    print(Dx.iod)
    return Dx

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.delayDrive

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

delaySS(namespace='D', delay=0.001, order=1, numins=1, dt=0.0001)[source]¶

Create a state space model for the delay block. It has one input and one output.

Parameters:

namespace (str, optional) – The namespace for the delay block. Defaults to ‘D’.
delay (_type_, optional) – The delay in seconds. Defaults to 1e-3.
order (int, optional) – Order of the filter. Defaults to 1.
numins (int, optional) – Number of inputs. Defaults to 1.
dt (_type_, optional) – The discretization time step. Defaults to 1e-4.

Returns:

Returns the local name space for the function including the state space model as mod, input output dictionary as iod, and namespace.

Return type:

wield.bunch

code

docstring

"""Create a state space model for the delay block. It has one input and one output.

Args:
    namespace (str, optional): The namespace for the delay block. Defaults to 'D'.
    delay (_type_, optional): The delay in seconds. Defaults to 1e-3.
    order (int, optional): Order of the filter. Defaults to 1.
    numins (int, optional): Number of inputs. Defaults to 1.
    dt (_type_, optional): The discretization time step. Defaults to 1e-4.

Returns:
    wield.bunch: Returns the local name space for the function including the state space model as `mod`, input output dictionary as `iod`, and namespace.
"""

def delaySS(namespace='D', delay=1e-3, order=1, numins=1, dt=1e-4):

    if delay==0:
        print('Delay is zero, using nullSS')
        D_mod = nullSS().mod
    else:
        # take the poles of this normalized bessel filter (delay=1s)
        z, p, k = scipy.signal.besselap(order, norm="delay")

        # now rescale for desired delay
        roots = p / delay * 2
        if order % 2 == 0:
            k = 1
        else:
            k = -1

        #siso_rep = SISO.zpk(-roots.conjugate(), roots, k)
        D_res = control.zpk(-roots.conjugate(), roots, k)
        D_mod = control.tf2ss(D_res)

    B_blocked = D_mod.B
    D_blocked = D_mod.D
    for ii in range(numins-1):
        B_blocked = np.block([[B_blocked, D_mod.B]])
        D_blocked = np.block([[D_blocked, D_mod.D]])

    mod = control.ss(D_mod.A, B_blocked, D_mod.C, D_blocked) # Create the system
    mod_dis = control.c2d(mod, dt) # Discretize the system
    iod = dict({namespace+'.in': 0, namespace+'.out': 0}) # Input output dictionary
    for ii in range(numins-1):
        iod[namespace+'.in.'+str(ii+1)] = ii+1

    return Bunch(locals())

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.delaySS

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

multi_bode(axB, F_Hz=None, include_zp=True, **kwargs)[source]¶

Plot multiple bode plots at once.

The main advantage is that the scale of the axes can be better auto-determined to capture all known poles and zeros. The input arguments should all be dictionaries containing the bode kwargs.

the usage should be

the kwargs on the top call are passed into all sub calls

with multi_bode(axB=axB, **kw_cmn) as bode:: bode(sisoA, label=’A’, **kw) bode(sisoB, label=’B’, **kw) bode(sisoC, label=’C’, **kw)

axB.save(‘figname.pdf’)

nullSS(namespace='N', gain=1)[source]¶

Create a state space model for the null block. It has one input and one output.

Parameters:

namespace (str, optional) – The namespace to use for the model i.e. the letter that comes at the beginning of the input and output names. Defaults to ‘N’.
gain (float, optional) – The gain of the null block. Defaults to 1.

Returns:

Returns Wield MIMO statespace

Return type:

MIMO Statespace

code

docstring

"""Create a state space model for the null block. It has one input and one output.

Args:
    namespace (str, optional): The namespace to use for the model i.e. the letter that comes at the beginning of the input and output names. Defaults to 'N'.
    gain (float, optional): The gain of the null block. Defaults to 1.

Returns:
    MIMO Statespace: Returns Wield MIMO statespace
"""

def nullSS(namespace='N', gain=1):


    A = np.zeros([0,0]) # Construct the A state matrix
    B = np.zeros([1,0]) # Construct the B state matrix
    C = np.zeros([0,1]) # Construct the C state matrix
    D = np.array([[gain]]) # Construct the D state matrix 
    iod = dict({namespace+'.in': 0, namespace+'.out': 0}) # Input output dictionary
    return ssutil.wieldSS(A, B, C, D, iod=iod)

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.nullSS

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

test_Make_ADY(folder)[source]¶

This is the main function that is called to create the model for the ASC DHARD Y.

code

docstring

"""
This is the main function that is called to create the model for the ASC DHARD Y.
"""

@pytest.mark.parametrize(
    'folder', [
        #'ExampleModels_rescale',
        'ExampleModels',
        'ExampleModels_working',
        'ExampleModels_working_F3',
        'ExampleModels_newFOM',
        'ExampleModels_newFOM_F3',
        'ExampleModels_DARMFOM'
    ]
)
@pytest.mark.gitlabCI
@pytest.mark.ADY
def test_Make_ADY(folder):

    S = ssutil.loadSys(fjoin(folder, 'ADY_E_from_fit.mat'))
    O = ssutil.loadSys(fjoin(folder, 'ADY_M_from_fit.mat'))
    P_fname = 'ADY_plant_from_fit.mat'
    P = ssutil.loadSys(fjoin(folder, P_fname))

    # w2_rescale = 2e5
    w2_rescale = 1e6
    S = (w2_rescale * S.siso('S.out', 'S.in')).mimo('S.out', 'S.in')
    O = (w2_rescale * O.siso('O.out', 'O.in')).mimo('O.out', 'O.in')

    if '_newFOM' in folder or '_newFOM_F3' in folder:
        FBNS_func = FBNSSS_Hand
        FBNS = FBNS_func()
        FBNS_scale = FBNS_func(return_scale=True)
    elif 'DARMFOM' in folder:
       FBNS_func = FBNSSS_DARM
       FBNS = FBNS_func()
       FBNS_scale = FBNS_func(return_scale=True)
    else:
        FBNS_func = FBNSsimpSS
        FBNS = FBNS_func()
        FBNS_scale = FBNS_func(return_scale=True)

        omega_limits=[1e-2, 1e4]
        axB = ssutil.bode(FBNS.siso('FBNS.out', 'FBNS.in'), omega_limits=omega_limits, label='Simple FBNS')
        axB = ssutil.bode(FBNSSS_Hand().siso('FBNS.out', 'FBNS.in'), omega_limits=omega_limits, axB=axB, label='Hand Fit FBNS')
        axB = ssutil.bode(FBNSSS_Fit().siso('FBNS.out', 'FBNS.in'), omega_limits=omega_limits, axB=axB, label='FBNS From Data')
        axB.save(tjoin('BNS_FOMS_Comp.pdf'))
        axB.save(tjoin('BNS_FOMS_Comp.png'))

    FFlat = FFlatSS()

    # Inject the coupling into the BNS FOM, normalize it to Hinf=1 and then collect its scale
    Coup = ssutil.loadSys(fjoin(folder, 'A2L_coupling_with_cal.mat')) # This is the Angle to length coupling it would be multiplied by the BNS FOM
    FBNS = ssutil.multiconnect([Coup, FBNS], [['FBNS.in', 'COUP.out']])
    FBNS = ssutil.truncate_io(FBNS, ['COUP.in'], ['FBNS.out','COUP.out']) #commented out to display DARM Spectrum
    #FBNS = ssutil.rename_io(FBNS, 'FBNS.in', 'FBNS.nocoup.in') # so that you can see the FBNS with no coupling
    FBNS = ssutil.rename_io(FBNS, 'COUP.out', 'FBNS.DARM.out') # to see DARM Spectrum
    FBNS = ssutil.rename_io(FBNS, 'COUP.in', 'FBNS.in')
    print(FBNS.iod)

    FBNS_Trash, Coup_scale = ssutil.normalize_gain(ssutil.truncate_io(FBNS, ['FBNS.in'], ['FBNS.out']), norm=1, return_scale=True, method='fq_resp')
    del FBNS_Trash
    FBNS = ssutil.scale_io(FBNS, 'FBNS.out', Coup_scale) # using this to scale preserves the DARM.out output

    FBNS_scale = FBNS_scale * Coup_scale
    np.savetxt(fjoin(folder, 'FBNS_scale.txt'), [FBNS_scale])
    print('FBNS scale', FBNS_scale)

    current_range = np.loadtxt(fjoin(folder, 'FBNS_Current_range.txt')) # Saved by the normalization in the make function
    io_scales = Bunch(
        FBNS = FBNS_scale,  # will need to apply this to the BNS FOM
        w2_rescale = w2_rescale,  # will need to divide by this on both FOMs
        # will need to be applied only to the Flat fom since the A2L_coupling_with_cal includes it as a factor
        ct2rad = 5.2e-11,  # Calibration from https://alog.ligo-wa.caltech.edu/aLOG/index.php?callRep=69551
        strain2m = 1/3995,  # Representing the 4km arm length. Strain is h = dL/L where L = 3995 m. The coupling is "I" is in rad to displacement so we need to convert it to strain for the BNS FOM which is in strain
        current_range = current_range,
    )
    io_scales.RMS_cal_F1 = 1/io_scales.FBNS * io_scales.strain2m / io_scales.w2_rescale
    io_scales.RMS_cal_F2 = io_scales.ct2rad / io_scales.w2_rescale
    file_io.save(fjoin(folder, 'io_scales.yml'), dict(io_scales))

    omega_limits=[1e-2, 1e4]

    omega_limits_noise = [1e-1, 1e3]
    axN = ssutil.bode(ssutil.asSISO(S), omega_limits=omega_limits_noise, label='Seismic')
    axN = ssutil.bode(ssutil.asSISO(O), axB=axN, omega_limits=omega_limits_noise, label='Meas. Noise')
    axN = ssutil.bode(ssutil.asSISO(P), axB=axN, omega_limits=omega_limits_noise, label='Plant')
    axN = ssutil.bode(ssutil.asSISO(S.siso('S.out', 'S.in') * P.siso('P.out', 'P.in')), axB=axN, omega_limits=omega_limits_noise, label='S*P')
    axN.save(tjoin('Noise_bode.png'))
    axN.save(tjoin('Noise_bode.pdf'))


    # control.bode(S.mod, dB=False, Hz=True, omega_limits=omega_limits, label='Seismic')
    # control.bode(O.mod, dB=False, Hz=True, omega_limits=omega_limits, label='Meas. Noise')
    # control.bode(P.mod, dB=False, Hz=True, omega_limits=omega_limits, label='Plant')
    # control.bode((S.siso('S.out', 'S.in') * P.siso('P.out', 'P.in')).mimo('out', 'in').mod, dB=False, Hz=True, omega_limits=omega_limits, label='S*P')
    # plt.legend()
    # plt.savefig(tjoin('Noise_bode.pdf'), bbox_inches='tight')
    # plt.savefig(tjoin('Noise_bode.png'), bbox_inches='tight', dpi=300)
    # plt.close()

    omega_limits_fom = np.array([1e-1, 1e5])*2*np.pi
    axFOM = ssutil.bode(FBNS.siso('FBNS.out', 'FBNS.in'), omega_limits=omega_limits_fom, label='FBNS')
    axFOM = ssutil.bode(FFlat.siso(iodutil.listoutputs(FFlat)[0], iodutil.listinputs(FFlat)[0]), axB=axFOM, omega_limits=omega_limits_fom, label='FFlat')
    axFOM.save(tjoin('FOM_bode.pdf'))
    axFOM.save(tjoin('FOM_bode.png'))
    # control.bode(FBNS.mod, dB=True, Hz=True, omega_limits=omega_limits, label='FBNS')
    # control.bode(FFlat.mod, dB=True, Hz=True, omega_limits=omega_limits, label='FFlat')
    # plt.legend()
    # plt.savefig(tjoin('FOM_bode.pdf'))
    # plt.savefig(tjoin('FOM_bode.png'))
    # plt.close()

    #make the SO
    #conlist =[['T_SO.in.1', 'O.out'], ['T_SO.in.2','S.out']]
    #T_SO = addSS(namespace='T_SO', sub=True)
    #SO = ssutil.multiconnect([S, O, T_SO], conlist)
    #SO = ssutil.truncate_io(SO, ['O.in', 'S.in'], ['T_SO.out', 'S.out'])
    #SO = ssutil.rename_io(SO, 'T_SO.out', 'O.out')

    #control.bode(SO.mod[SO.iod['S.out'], SO.iod['S.in']], dB=True, Hz=True, omega_limits=omega_limits, label='S to S')
    #control.bode(SO.mod[SO.iod['O.out'], SO.iod['O.in']], dB=True, Hz=True, omega_limits=omega_limits, label='O to O')
    #control.bode(SO.mod[SO.iod['O.out'], SO.iod['S.in']], dB=True, Hz=True, omega_limits=omega_limits, label='S to O', linestyle='--', linewidth=5)
    #control.bode(S.mod, dB=True, Hz=True, omega_limits=[1e-2, 1e3], label='Orig. S', linestyle='dotted', linewidth=4)
    #control.bode(O.mod, dB=True, Hz=True, omega_limits=[1e-2, 1e3], label='Orig. O', linestyle='dotted', linewidth=4)
    #plt.legend(fontsize=8)
    #plt.savefig(tjoin('SO_bode.pdf'))
    #plt.close()
    if '_F3' in folder:
        extras = 'F3_withP'
    else:
        extras = None

    SPOFF = ssutil.makeSPOFF(S, P, O, FBNS, FFlat, diagnostic=True, extras=extras, balance=True)
    #print('SPOFF', SPOFF.iod)
    #SPOFF = ssutil.balance_sys_gain(SPOFF)
    omega_limits=[1e-2, 1e3]

    axB = mplfigB(Nrows=2)
    F_Hz = np.geomspace(1e-2, 20, 1000)
    with multi_bode(axB=axB, F_Hz = F_Hz) as bode:
        bode(P['P.out', 'P.in'], label='P alone', linewidth=2, color='dodgerblue')
        bode(SPOFF['P.out', 'P.in'], label='P to P in SPOFF', color='orange')
        bode(SPOFF['P.out', 'S.in'], label='S to P', color='green')
        bode(SPOFF['S.out', 'S.in'], label='S to S', linestyle='dotted', linewidth=4, color='green')
        bode(SPOFF['P.out', 'SA.in'], linestyle='--', label='P Recombined', linewidth=4, color='dodgerblue')
        bode(SPOFF['S.out', 'SA.in'], label='P that moved to S', color='dodgerblue', linestyle='dotted', linewidth=6)
        bode(SPOFF['G.out', 'S.in'], label='Orig. S (from SPOFF)', color='red')
        bode(S['S.out', 'S.in'], label='Orig. S alone', linestyle='dotted', linewidth=4, color='red')
    axB.ax1.legend(fontsize=5)
    axB.save(tjoin('SPOFF_diagnostic_bode.pdf'))
    axB.save(tjoin('SPOFF_diagnostic_bode.png'))

    axB = mplfigB(Nrows=2)
    F_Hz = np.geomspace(1e-2, 20, 1000)
    with multi_bode(axB=axB, F_Hz = F_Hz) as bode:
        bode(sys=SPOFF['P.out', 'P.in'], label='P to P')
        bode(sys=SPOFF['P.out', 'S.in'], label='S to P')
        bode(sys=SPOFF['S.out', 'S.in'], label='S to S', linestyle=':', linewidth=2)
        bode(sys=S['S.out', 'S.in'], label='S to S (orig)', linestyle=':', linewidth=2)
        bode(sys=SPOFF['T.out', 'O.in'], label='O to Meas. Out')
        bode(sys=SPOFF['T.out', 'S.in'], label='S to Meas. Out')

    axB.ax1.legend(fontsize=5)
    axB.save(tjoin('SPOFF_bode.pdf'))
    axB.save(tjoin('SPOFF_bode.png'))

    #print('SPOFF', SPOFF.iod)
    #print(SPOFF['T.out', 'S.in']._zp[1])

    #truncate_inputs = ['P.in', 'S.in', 'O.in', 'T.in.1', 'T.in.2', 'FBNS.in', 'F2.in', 'Zinf.in']
    #truncate_outputs = ['P.out', 'O.out', 'S.out', 'T.out', 'FBNS.out', 'F2.out']
    #SPOFF = ssutil.truncate_io(SPOFF, truncate_inputs, truncate_outputs)

    control.bode(SPOFF.mod[SPOFF.iod['F2.out'], SPOFF.iod['P.in']], dB=True, Hz=True, omega_limits=omega_limits, label='P to Flat FOM')
    control.bode(SPOFF.mod[SPOFF.iod['FBNS.out'], SPOFF.iod['P.in']], dB=True, Hz=True, omega_limits=omega_limits, label='P to BNS FOM')
    control.bode(SPOFF.mod[SPOFF.iod['P.out'], SPOFF.iod['S.in']], dB=True, Hz=True, omega_limits=omega_limits, label='S to P')
    control.bode(SPOFF.mod[SPOFF.iod['S.out'], SPOFF.iod['S.in']], dB=True, Hz=True, omega_limits=omega_limits, label='S to S', linestyle='dotted', linewidth=4)
    control.bode(SPOFF.mod[SPOFF.iod['T.out'], SPOFF.iod['O.in']], dB=True, Hz=True, omega_limits=omega_limits, label='O to Meas. Out')
    control.bode(SPOFF.mod[SPOFF.iod['T.out'], SPOFF.iod['S.in']], dB=True, Hz=True, omega_limits=omega_limits, label='S to Meas. Out')
    plt.legend(fontsize=5)
    plt.savefig(tjoin('SPOFF_all_bode.pdf'))
    plt.savefig(tjoin('SPOFF_all_bode.png'))
    plt.close()

    SPOFF_bal = ssutil.balance_sys_gain(SPOFF)

    axFOM_S = ssutil.bode(SPOFF.siso('FBNS.out', 'FBNS.in'), omega_limits=omega_limits_fom, label='FBNS', color='red')
    axFOM_S = ssutil.bode(SPOFF.siso(iodutil.listoutputs(FFlat)[0], iodutil.listinputs(FFlat)[0]), axB=axFOM_S, omega_limits=omega_limits_fom, label='FFlat', color='dodgerblue')
    axFOM_S = ssutil.bode(SPOFF_bal.siso('FBNS.out', 'FBNS.in'), omega_limits=omega_limits_fom, axB=axFOM_S, label='FBNS SPOFF bal', color='green')
    axFOM_S = ssutil.bode(SPOFF_bal.siso(iodutil.listoutputs(FFlat)[0], iodutil.listinputs(FFlat)[0]), axB=axFOM_S, omega_limits=omega_limits_fom, label='FFlat SPOFF bal', color='green')
    axFOM_S = ssutil.bode(FBNS.siso('FBNS.out', 'FBNS.in'), axB=axFOM_S, omega_limits=omega_limits_fom, label='FBNS orig.', linestyle='dotted', color='red', linewidth=4)
    axFOM_S = ssutil.bode(FFlat.siso(iodutil.listoutputs(FFlat)[0], iodutil.listinputs(FFlat)[0]), axB=axFOM_S, omega_limits=omega_limits_fom, label='FFlat orig.', color='dodgerblue', linestyle='dotted', linewidth=4)
    axFOM_S.save(tjoin('FOM_bode_from_SPOFF.pdf'))
    axFOM_S.save(tjoin('FOM_bode_from_SPOFF.png'))

    #SPOFF = ssutil.balance_sys_gain(SPOFF)

    P_load2 = ssutil.loadSys(fjoin(folder, P_fname))
    assert(np.allclose(P_load2.A, P.A))
    assert(np.allclose(P_load2.B, P.B))
    assert(np.allclose(P_load2.C, P.C))
    assert(np.allclose(P_load2.D, P.D))

    ssutil.savesys(SPOFF, tjoin('ADY_Sanex.mat'))
    ssutil.savesys(P, tjoin('ADY_plant.mat'))

    ssutil.savesys(SPOFF, fjoin(folder, 'ADY_Sanex.mat'))
    ssutil.savesys(P, fjoin(folder, 'ADY_plant.mat'))

    return

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.test_Make_ADY

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

test_Make_ADY[ExampleModels_newFOM_F3]

output

{'FBNS.in': 0, 'FBNS.out': 0, 'FBNS.DARM.out': 1}
FBNS scale 2.960593226947428e-11
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
The plant is stable and has no non-minphase zeros. This means that the plant is strictly proper and no adjustments need to be made to the plant
Adding F3 after the controller output
P' should be flat because of how it was constructed. Not adding P' to F3
F3 poles:  [-12566.37061436+0.00000000e+00j  -1256.63706144+1.84470726e-07j
  -1256.63706144-1.84470726e-07j   -181.60072098+2.77615779e-05j
   -181.60072098-2.77615779e-05j   -113.48687238+1.36190499e+02j
   -113.48687238-1.36190499e+02j   -113.49040983+1.36214122e+02j
   -113.49040983-1.36214122e+02j   -113.51048946+1.36186963e+02j
   -113.51048946-1.36186963e+02j   -113.51403078+1.36210579e+02j
   -113.51403078-1.36210579e+02j    -54.94582132+6.43809992e+00j
    -54.94582132-6.43809992e+00j    -55.53613297+5.09920472e+00j
    -55.53613297-5.09920472e+00j    -53.88160102+7.06211820e+00j
    -53.88160102-7.06211820e+00j    -54.95054365+3.20780445e+00j
    -54.95054365-3.20780445e+00j    -52.76652603+6.98932446e+00j
    -52.76652603-6.98932446e+00j    -51.92181189+6.33187146e+00j
    -51.92181189-6.33187146e+00j    -51.65851489+5.37273175e+00j
    -51.65851489-5.37273175e+00j    -51.659588  +4.50670881e+00j
    -51.659588  -4.50670881e+00j    -52.34223409+3.02722782e+00j
    -52.34223409-3.02722782e+00j    -36.19762324+7.51940781e-02j
    -36.19762324-7.51940781e-02j    -36.33045107+1.37453947e-01j
    -36.33045107-1.37453947e-01j    -36.43235831+5.62255577e-02j
    -36.43235831-5.62255577e-02j]
F3 zs:  [-12.74162146 +0.j         -28.96870337+15.01749344j
 -28.96870337-15.01749344j -62.09875771 +9.16044997j
 -62.09875771 -9.16044997j -54.01839166+16.05469555j
 -54.01839166-16.05469555j -30.58459061 +0.j
 -42.35683227+10.21345753j -42.35683227-10.21345753j
 -40.90782718 +0.j        ]
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>

test_Make_ADY[ExampleModels]

output

['0j', '0j', '0j', '0j', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)']
['0j', '0j', '0j', '0j', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)']
['(-2178.2052157029675+0j)', '(-287.1654677213149+0j)', '(-1695.4502902414451+0j)', '(-12.88579675913225+5.603093166973548j)', '(-12.88579675913225-5.603093166973548j)', '(-12.890063158702414+5.596646900702218j)', '(-12.890063158702414-5.596646900702218j)', '(-12.890063158702372+5.596646900702337j)', '(-12.890063158702372-5.596646900702337j)', '(-12.890063158702388+5.5966469007023j)', '(-12.890063158702388-5.5966469007023j)', '(-12.890063158702446+5.596646900702153j)', '(-12.890063158702446-5.596646900702153j)', '(-12.89006315870248+5.5966469007020585j)', '(-12.89006315870248-5.5966469007020585j)', '(-12.890063158702388+5.596646900702294j)', '(-12.890063158702388-5.596646900702294j)', '(-12.894331029649276+5.590187234277706j)', '(-12.894331029649276-5.590187234277706j)', '(-41254.24545663495+74429.27280788597j)', '(-41254.24545663495-74429.27280788597j)', '(-393.2693078650807+641.5816869585774j)', '(-393.2693078650807-641.5816869585774j)', '(-270.2702244864787+531.5395656330295j)', '(-270.2702244864787-531.5395656330295j)', '(-0.1697459318944503+0.05397308658344683j)', '(-0.1697459318944503-0.05397308658344683j)', '(-0.17074996279987628+0.056468761593217655j)', '(-0.17074996279987628-0.056468761593217655j)', '(-0.35336968654430834+1.2037757200586874j)', '(-0.35336968654430834-1.2037757200586874j)', '(-0.3531584357281473+1.2030238621502156j)', '(-0.3531584357281473-1.2030238621502156j)', '(-0.06095148837221796+1.7758885072601485j)', '(-0.06095148837221796-1.7758885072601485j)', '(-0.07262696482159792+2.327687224237036j)', '(-0.07262696482159792-2.327687224237036j)', '(-82.12808426287661+279.8184014267577j)', '(-82.12808426287661-279.8184014267577j)', '(-12.890063158702372+5.596646900702337j)', '(-12.890063158702372-5.596646900702337j)']
<IPython.core.display.Markdown object>
{'FBNS.in': 0, 'FBNS.out': 0, 'FBNS.DARM.out': 1}
FBNS scale 6.75666824737328e-11
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
The plant is stable and has no non-minphase zeros. This means that the plant is strictly proper and no adjustments need to be made to the plant
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>

test_Make_ADY[ExampleModels_newFOM]

output

{'FBNS.in': 0, 'FBNS.out': 0, 'FBNS.DARM.out': 1}
FBNS scale 2.960593226947428e-11
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
The plant is stable and has no non-minphase zeros. This means that the plant is strictly proper and no adjustments need to be made to the plant
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>

test_Make_ADY[ExampleModels_working_F3]

output

['0j', '0j', '0j', '0j', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)']
['0j', '0j', '0j', '0j', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)']
['(-2178.2052157029675+0j)', '(-287.1654677213149+0j)', '(-1695.4502902414451+0j)', '(-12.88579675913225+5.603093166973548j)', '(-12.88579675913225-5.603093166973548j)', '(-12.890063158702414+5.596646900702218j)', '(-12.890063158702414-5.596646900702218j)', '(-12.890063158702372+5.596646900702337j)', '(-12.890063158702372-5.596646900702337j)', '(-12.890063158702388+5.5966469007023j)', '(-12.890063158702388-5.5966469007023j)', '(-12.890063158702446+5.596646900702153j)', '(-12.890063158702446-5.596646900702153j)', '(-12.89006315870248+5.5966469007020585j)', '(-12.89006315870248-5.5966469007020585j)', '(-12.890063158702388+5.596646900702294j)', '(-12.890063158702388-5.596646900702294j)', '(-12.894331029649276+5.590187234277706j)', '(-12.894331029649276-5.590187234277706j)', '(-41254.24545663495+74429.27280788597j)', '(-41254.24545663495-74429.27280788597j)', '(-393.2693078650807+641.5816869585774j)', '(-393.2693078650807-641.5816869585774j)', '(-270.2702244864787+531.5395656330295j)', '(-270.2702244864787-531.5395656330295j)', '(-0.1697459318944503+0.05397308658344683j)', '(-0.1697459318944503-0.05397308658344683j)', '(-0.17074996279987628+0.056468761593217655j)', '(-0.17074996279987628-0.056468761593217655j)', '(-0.35336968654430834+1.2037757200586874j)', '(-0.35336968654430834-1.2037757200586874j)', '(-0.3531584357281473+1.2030238621502156j)', '(-0.3531584357281473-1.2030238621502156j)', '(-0.06095148837221796+1.7758885072601485j)', '(-0.06095148837221796-1.7758885072601485j)', '(-0.07262696482159792+2.327687224237036j)', '(-0.07262696482159792-2.327687224237036j)', '(-82.12808426287661+279.8184014267577j)', '(-82.12808426287661-279.8184014267577j)', '(-12.890063158702372+5.596646900702337j)', '(-12.890063158702372-5.596646900702337j)']
<IPython.core.display.Markdown object>
{'FBNS.in': 0, 'FBNS.out': 0, 'FBNS.DARM.out': 1}
FBNS scale 6.75666824737328e-11
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
The plant is stable and has no non-minphase zeros. This means that the plant is strictly proper and no adjustments need to be made to the plant
Adding F3 after the controller output
P' should be flat because of how it was constructed. Not adding P' to F3
F3 poles:  [-1884.96062603+5.03382207e-03j -1884.96062603-5.03382207e-03j
 -1884.95055828+5.03381170e-03j -1884.95055828-5.03381170e-03j
  -251.4713905 +0.00000000e+00j  -251.32761439+1.44179064e-01j
  -251.32761439-1.44179064e-01j  -251.18302987+0.00000000e+00j
   -26.50982787+1.35534312e+02j   -26.50982787-1.35534312e+02j
   -26.50983071+1.35534309e+02j   -26.50983071-1.35534309e+02j
  -181.60120388+0.00000000e+00j  -181.60023809+0.00000000e+00j
   -75.49360653+1.14900461e+02j   -75.49360653-1.14900461e+02j
   -75.49360681+1.14900420e+02j   -75.49360681-1.14900420e+02j
  -133.27390798+2.69593748e+01j  -133.27390798-2.69593748e+01j
  -133.27391544+2.69595262e+01j  -133.27391544-2.69595262e+01j
  -112.98413676+7.67739813e+01j  -112.98413676-7.67739813e+01j
  -112.9841968 +7.67740581e+01j  -112.9841968 -7.67740581e+01j
  -113.49378922+1.36256844e+02j  -113.49378922-1.36256844e+02j
  -113.55678375+1.36207254e+02j  -113.55678375-1.36207254e+02j
  -113.44409521+1.36193909e+02j  -113.44409521-1.36193909e+02j
  -113.50713428+1.36144156e+02j  -113.50713428-1.36144156e+02j
   -36.38042509+0.00000000e+00j   -36.35021801+5.22021695e-02j
   -36.35021801-5.22021695e-02j   -36.29000833+5.20946300e-02j
   -36.29000833-5.20946300e-02j   -36.25998742+0.00000000e+00j]
F3 zs:  [ 4.40097619e+05+5.55982318e+06j  4.40097619e+05-5.55982318e+06j
 -8.80438686e+05+0.00000000e+00j -1.21634279e+02+2.88605968e+02j
 -1.21634279e+02-2.88605968e+02j -2.07484152e+02+2.07760403e+02j
 -2.07484152e+02-2.07760403e+02j -1.32793944e+02+1.33276157e+02j
 -1.32793944e+02-1.33276157e+02j -1.49205071e+02+1.07696061e+02j
 -1.49205071e+02-1.07696061e+02j -1.57549943e+01+2.52141418e+01j
 -1.57549943e+01-2.52141418e+01j -4.37167724e+01+1.81587255e+01j
 -4.37167724e+01-1.81587255e+01j -5.10799314e+01+6.05670239e+00j
 -5.10799314e+01-6.05670239e+00j -6.93637160e+01+0.00000000e+00j
 -1.12984167e+02+7.67740197e+01j -1.12984167e+02-7.67740197e+01j
 -2.65098293e+01+1.35534310e+02j -2.65098293e+01-1.35534310e+02j
 -2.51327407e+02+0.00000000e+00j -2.51327418e+02+0.00000000e+00j
 -1.33273912e+02+2.69594505e+01j -1.33273912e+02-2.69594505e+01j
 -7.54936067e+01+1.14900440e+02j -7.54936067e+01-1.14900440e+02j
 -2.65098293e+01+1.35534310e+02j -2.65098293e+01-1.35534310e+02j
 -1.88495559e+03+0.00000000e+00j -1.88495559e+03+0.00000000e+00j
 -1.12984167e+02+7.67740197e+01j -1.12984167e+02-7.67740197e+01j
 -7.54936067e+01+1.14900440e+02j -7.54936067e+01-1.14900440e+02j
 -2.51327407e+02+0.00000000e+00j -2.51327418e+02+0.00000000e+00j
  0.00000000e+00+0.00000000e+00j]
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>

test_Make_ADY[ExampleModels_working]

output

['0j', '0j', '0j', '0j', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)']
['0j', '0j', '0j', '0j', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)', '(-0+24.649822653310352j)', '(-0-24.649822653310352j)', '(-0+20.897110605542636j)', '(-0-20.897110605542636j)', '(-0+13.963002900860413j)', '(-0-13.963002900860413j)', '(-0+4.903154579458684j)', '(-0-4.903154579458684j)']
['(-2178.2052157029675+0j)', '(-287.1654677213149+0j)', '(-1695.4502902414451+0j)', '(-12.88579675913225+5.603093166973548j)', '(-12.88579675913225-5.603093166973548j)', '(-12.890063158702414+5.596646900702218j)', '(-12.890063158702414-5.596646900702218j)', '(-12.890063158702372+5.596646900702337j)', '(-12.890063158702372-5.596646900702337j)', '(-12.890063158702388+5.5966469007023j)', '(-12.890063158702388-5.5966469007023j)', '(-12.890063158702446+5.596646900702153j)', '(-12.890063158702446-5.596646900702153j)', '(-12.89006315870248+5.5966469007020585j)', '(-12.89006315870248-5.5966469007020585j)', '(-12.890063158702388+5.596646900702294j)', '(-12.890063158702388-5.596646900702294j)', '(-12.894331029649276+5.590187234277706j)', '(-12.894331029649276-5.590187234277706j)', '(-41254.24545663495+74429.27280788597j)', '(-41254.24545663495-74429.27280788597j)', '(-393.2693078650807+641.5816869585774j)', '(-393.2693078650807-641.5816869585774j)', '(-270.2702244864787+531.5395656330295j)', '(-270.2702244864787-531.5395656330295j)', '(-0.1697459318944503+0.05397308658344683j)', '(-0.1697459318944503-0.05397308658344683j)', '(-0.17074996279987628+0.056468761593217655j)', '(-0.17074996279987628-0.056468761593217655j)', '(-0.35336968654430834+1.2037757200586874j)', '(-0.35336968654430834-1.2037757200586874j)', '(-0.3531584357281473+1.2030238621502156j)', '(-0.3531584357281473-1.2030238621502156j)', '(-0.06095148837221796+1.7758885072601485j)', '(-0.06095148837221796-1.7758885072601485j)', '(-0.07262696482159792+2.327687224237036j)', '(-0.07262696482159792-2.327687224237036j)', '(-82.12808426287661+279.8184014267577j)', '(-82.12808426287661-279.8184014267577j)', '(-12.890063158702372+5.596646900702337j)', '(-12.890063158702372-5.596646900702337j)']
<IPython.core.display.Markdown object>
{'FBNS.in': 0, 'FBNS.out': 0, 'FBNS.DARM.out': 1}
FBNS scale 6.75666824737328e-11
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
The plant is stable and has no non-minphase zeros. This means that the plant is strictly proper and no adjustments need to be made to the plant
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>

test_Make_ADY[ExampleModels_DARMFOM]

output

{'FBNS.in': 0, 'FBNS.out': 0, 'FBNS.DARM.out': 1}
FBNS scale 8.646766852528927e-11
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
The plant is stable and has no non-minphase zeros. This means that the plant is strictly proper and no adjustments need to be made to the plant
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>
<IPython.core.display.Markdown object>

transposeSys(sys, FOM_ns)[source]¶

This is a pytest needing documentation

code

def transposeSys(sys, FOM_ns):
    # add Z_inf as an input
    sys_inf_in_badname = ssutil.duplicate_io(sys, 'T.in.1')
    sys_inf_in = ssutil.rename_io(sys_inf_in_badname, 'T.in.1.2', 'Zinf.in')
    #print(sys.iod)

    inputs= ['D.in', 'O.in', 'S.in', 'Zinf.in']
    outputs_no_inf = [fns + '.out' for fns in FOM_ns] + ['T.out']

    sys_red = ssutil.truncate_io(sys_inf_in, inputs, outputs_no_inf)

    # Transpose the system
    sys_transpose = ssutil.transpose(sys_red)

    # Reorder the inputs and outputs
    sys_transpose = ssutil.reorder_io(sys_transpose, 
        [fns + '.in' for fns in FOM_ns] + ['T.in'], [
        'Zinf.out',
        'S.out',
        'O.out',
        'D.out'
    ])

    return sys_transpose

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.transposeSys

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

ws_tf2ss(z, p, k, gain=1, mfactor=1, angular=True)[source]¶

Takes a python control zpk and returns a python control statespace. Uses more numerically stable wield computations to convert between.

code

docstring

"""
Takes a python control zpk and returns a python control statespace.
Uses more numerically stable wield computations to convert between.
"""

def ws_tf2ss(z, p, k, gain=1, mfactor=1, angular=True):

    ws_zpk = SISO.zpk(z, p, k * gain, angular=True, fiducial_rtol=1e-5, fiducial_atol=1e-10)
    ws_SS = ws_zpk.asSS * mfactor
    # print("ZPK: ", ws_SS.asZPK.z, ws_SS.asZPK.p)

    # return control.ss(ws_SS.A.T, ws_SS.C.T, ws_SS.B.T, ws_SS.D.T)
    return control.ss(ws_SS.A, ws_SS.B, ws_SS.C, ws_SS.D)

pytest information

This code is wrapped in a pytest function using conventions detailed in pytest_conventions. The full name of this test, as known by the documentation, is:

test.ASC_SOLVER.T_ADY_make_sys.ws_tf2ss

The full name is useful when building documentation, to link a reference to this page using :func:`name`, or directly include it with an autofunction directive. The collapse nodes below show every instance of the test run. There may only be one, but if the test was run multiple times through pytest parametrizations, the list can be longer.

`FBNSSS_DARM`([return_name, return_scale])
`FBNSSS_Fit`([gain, return_name, return_scale])
`FBNSSS_Hand`([return_name, return_scale])
`FBNSsimpSS`([return_name, lo_ord, return_scale])	This is a pytest needing documentation
`FFlatSS`([gain, return_name])	This is a pytest needing documentation
`addSS`([namespace, dt, sub, outSufx])	Create a state space model for an adder.
`bode`(sys[, axB, F_Hz, omega_limits, ...])	sys should be a wield.control.SISO object
`delayDrive`([namespace, Sp, delay, order, ...])	This is a pytest needing documentation
`delaySS`([namespace, delay, order, numins, dt])	Create a state space model for the delay block.
`multi_bode`(axB[, F_Hz, include_zp])	Plot multiple bode plots at once.
`nullSS`([namespace, gain])	Create a state space model for the null block.
`test_Make_ADY`(folder)	This is the main function that is called to create the model for the ASC DHARD Y.
`transposeSys`(sys, FOM_ns)	This is a pytest needing documentation
`ws_tf2ss`(z, p, k[, gain, mfactor, angular])	Takes a python control zpk and returns a python control statespace.

T_ADY_make_sys¶