Python benchmark_time_series 예제들

예제 #1

파일: test_canonical_bicycle_id.py 프로젝트: StefenYin/CanonicalBicycleID

def test_benchmark_time_series():
    dataset = bdp.DataSet()
    trial = bdp.Run('700', dataset)

    timeSeries = cbi.benchmark_time_series(trial)

    testing.assert_allclose(trial.taskSignals['RollAngle'], timeSeries['p'])
    testing.assert_allclose(trial.taskSignals['RollRate'], timeSeries['pD'])
    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
                            timeSeries['pDD'])
    testing.assert_allclose(trial.taskSignals['SteerAngle'], timeSeries['d'])
    testing.assert_allclose(trial.taskSignals['SteerRate'], timeSeries['dD'])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
                            timeSeries['dDD'])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'], timeSeries['v'])
    testing.assert_allclose(trial.bicycleRiderParameters['g'], timeSeries['g'])
    testing.assert_allclose(trial.taskSignals['PullForce'], timeSeries['F'])

예제 #2

파일: test_canonical_bicycle_id.py 프로젝트: StefenYin/CanonicalBicycleID

def test_benchmark_time_series():
    dataset = bdp.DataSet()
    trial = bdp.Run('700', dataset)

    timeSeries = cbi.benchmark_time_series(trial)

    testing.assert_allclose(trial.taskSignals['RollAngle'], timeSeries['p'])
    testing.assert_allclose(trial.taskSignals['RollRate'], timeSeries['pD'])
    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
        timeSeries['pDD'])
    testing.assert_allclose(trial.taskSignals['SteerAngle'], timeSeries['d'])
    testing.assert_allclose(trial.taskSignals['SteerRate'], timeSeries['dD'])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
        timeSeries['dDD'])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'], timeSeries['v'])
    testing.assert_allclose(trial.bicycleRiderParameters['g'], timeSeries['g'])
    testing.assert_allclose(trial.taskSignals['PullForce'], timeSeries['F'])

예제 #3

파일: canonical_fit_quality.py 프로젝트: goatchurchprime/dissertation

    goodRuns = cPickle.load(f)

with open(read('pathToIdMat')) as f:
    idMat = cPickle.load(f)

dataset = bdp.DataSet()

roll = {k: [] for k in idMat.keys() + ['Whipple', 'Arm']}
steer = {k: [] for k in idMat.keys() + ['Whipple', 'Arm']}

allH = cbi.lateral_force_contribution(['Charlie', 'Jason', 'Luke'])

for runNum in goodRuns:
    trial = bdp.Run(runNum, dataset, filterFreq=15.)
    rider = trial.metadata['Rider']
    timeseries = cbi.benchmark_time_series(trial, subtractMean=True)
    for k, model in idMat.items():
        rollrsq, steerrsq, fig = cbi.input_prediction(timeseries, model)
        roll[k].append(rollrsq)
        steer[k].append(steerrsq)
        fig.savefig('plots/' + str(runNum) + '-' + k + '.png')
        plt.close(fig)
        del fig

    M, C1, K0, K2 = trial.bicycle.canonical(nominal=True)
    rollrsq, steerrsq, fig = cbi.input_prediction(timeseries,
                                                  (M, C1, K0, K2, allH[rider]))
    roll['Whipple'].append(rollrsq)
    steer['Whipple'].append(steerrsq)
    fig.savefig('plots/' + str(runNum) + '-whipple.png')
    plt.close(fig)

예제 #4

파일: canonical_fit_quality.py 프로젝트: Carreau/phd-dissertation

    goodRuns = cPickle.load(f)

with open(read('pathToIdMat')) as f:
    idMat = cPickle.load(f)

dataset = bdp.DataSet()

roll = {k : [] for k in idMat.keys() + ['Whipple', 'Arm']}
steer = {k : [] for k in idMat.keys() + ['Whipple', 'Arm']}

allH = cbi.lateral_force_contribution(['Charlie', 'Jason', 'Luke'])

for runNum in goodRuns:
    trial = bdp.Run(runNum, dataset, filterFreq=15.)
    rider = trial.metadata['Rider']
    timeseries = cbi.benchmark_time_series(trial, subtractMean=True)
    for k, model in idMat.items():
        rollrsq, steerrsq, fig = cbi.input_prediction(timeseries, model)
        roll[k].append(rollrsq)
        steer[k].append(steerrsq)
        fig.savefig('plots/' + str(runNum) + '-' + k + '.png')
        plt.close(fig)
        del fig

    M, C1, K0, K2 = trial.bicycle.canonical(nominal=True)
    rollrsq, steerrsq, fig = cbi.input_prediction(timeseries, (M, C1, K0, K2,
            allH[rider]))
    roll['Whipple'].append(rollrsq)
    steer['Whipple'].append(steerrsq)
    fig.savefig('plots/' + str(runNum) + '-whipple.png')
    plt.close(fig)

예제 #5

파일: test_canonical_bicycle_id.py 프로젝트: StefenYin/CanonicalBicycleID

def test_benchmark_lstsq_matrices():
    dataset = bdp.DataSet()
    trial = bdp.Run('700', dataset)

    A, B, F = cbi.whipple_state_space(trial.metadata['Rider'], 1.0)
    H = np.dot(np.linalg.inv(B[2:]), F[2:])

    timeSeries = cbi.benchmark_time_series(trial, subtractMean=False)
    M, C1, K0, K2 = trial.bicycle.canonical(nominal=True)
    fixedValues = cbi.benchmark_canon_to_dict(M, C1, K0, K2, H)

    rollParams = [
        'Mpp', 'Mpd', 'C1pp', 'C1pd', 'K0pp', 'K0pd', 'K2pp', 'K2pd', 'HpF'
    ]

    A, B = cbi.benchmark_lstsq_matrices(rollParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
                            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
                            A[:, 1])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['RollRate'],
        A[:, 2])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['SteerRate'],
        A[:, 3])
    testing.assert_allclose(9.81 * trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 * trial.taskSignals['SteerAngle'], A[:, 5])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['RollAngle'],
        A[:, 6])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['SteerAngle'],
        A[:, 7])
    testing.assert_allclose(-trial.taskSignals['PullForce'], A[:, 8])
    testing.assert_allclose(np.zeros_like(trial.taskSignals['PullForce']), B)

    rollParams = ['Mpp', 'Mpd', 'C1pp', 'C1pd', 'K0pp', 'K0pd', 'K2pp', 'K2pd']

    A, B = cbi.benchmark_lstsq_matrices(rollParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
                            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
                            A[:, 1])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['RollRate'],
        A[:, 2])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['SteerRate'],
        A[:, 3])
    testing.assert_allclose(9.81 * trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 * trial.taskSignals['SteerAngle'], A[:, 5])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['RollAngle'],
        A[:, 6])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['SteerAngle'],
        A[:, 7])
    testing.assert_allclose(H[0] * trial.taskSignals['PullForce'], B)

    steerParams = [
        'Mdp', 'Mdd', 'C1dp', 'C1dd', 'K0dp', 'K0dd', 'K2dp', 'K2dd', 'HdF'
    ]

    A, B = cbi.benchmark_lstsq_matrices(steerParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
                            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
                            A[:, 1])

    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['RollRate'],
        A[:, 2])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['SteerRate'],
        A[:, 3])

    testing.assert_allclose(9.81 * trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 * trial.taskSignals['SteerAngle'], A[:, 5])

    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['RollAngle'],
        A[:, 6])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['SteerAngle'],
        A[:, 7])

    testing.assert_allclose(-trial.taskSignals['PullForce'], A[:, 8])
    testing.assert_allclose(trial.taskSignals['SteerTorque'], B)

    steerParams = [
        'Mdp', 'Mdd', 'C1dp', 'C1dd', 'K0dp', 'K0dd', 'K2dp', 'K2dd'
    ]

    A, B = cbi.benchmark_lstsq_matrices(steerParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
                            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
                            A[:, 1])

    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['RollRate'],
        A[:, 2])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['SteerRate'],
        A[:, 3])

    testing.assert_allclose(9.81 * trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 * trial.taskSignals['SteerAngle'], A[:, 5])

    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['RollAngle'],
        A[:, 6])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['SteerAngle'],
        A[:, 7])

    testing.assert_allclose(
        trial.taskSignals['SteerTorque'] +
        H[1] * trial.taskSignals['PullForce'], B)

    steerParams = ['Mdp', 'C1dd', 'K0dp', 'K2dp', 'K2dd']

    A, B = cbi.benchmark_lstsq_matrices(steerParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
                            A[:, 0])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed'] * trial.taskSignals['SteerRate'],
        A[:, 1])
    testing.assert_allclose(9.81 * trial.taskSignals['RollAngle'], A[:, 2])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['RollAngle'],
        A[:, 3])
    testing.assert_allclose(
        trial.taskSignals['ForwardSpeed']**2 * trial.taskSignals['SteerAngle'],
        A[:, 4])

    testing.assert_allclose(
        H[1] * trial.taskSignals['PullForce'] +
        trial.taskSignals['SteerTorque'] -
        fixedValues['Mdd'] * trial.taskSignals['SteerRate'].time_derivative() -
        fixedValues['C1dp'] * trial.taskSignals['ForwardSpeed'] *
        trial.taskSignals['RollRate'] -
        fixedValues['K0dd'] * 9.81 * trial.taskSignals['SteerAngle'], B)

예제 #6

파일: test_canonical_bicycle_id.py 프로젝트: StefenYin/CanonicalBicycleID

def test_benchmark_lstsq_matrices():
    dataset = bdp.DataSet()
    trial = bdp.Run('700', dataset)

    A, B, F = cbi.whipple_state_space(trial.metadata['Rider'], 1.0)
    H = np.dot(np.linalg.inv(B[2:]), F[2:])

    timeSeries = cbi.benchmark_time_series(trial, subtractMean=False)
    M, C1, K0, K2 = trial.bicycle.canonical(nominal=True)
    fixedValues = cbi.benchmark_canon_to_dict(M, C1, K0, K2, H)

    rollParams = ['Mpp', 'Mpd',
                  'C1pp', 'C1pd',
                  'K0pp', 'K0pd',
                  'K2pp', 'K2pd',
                  'HpF']

    A, B = cbi.benchmark_lstsq_matrices(rollParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
            A[:, 1])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['RollRate'], A[:, 2])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['SteerRate'], A[:, 3])
    testing.assert_allclose(9.81 *
            trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 *
            trial.taskSignals['SteerAngle'], A[:, 5])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['RollAngle'], A[:, 6])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['SteerAngle'], A[:, 7])
    testing.assert_allclose(-trial.taskSignals['PullForce'], A[:, 8])
    testing.assert_allclose(np.zeros_like(trial.taskSignals['PullForce']), B)

    rollParams = ['Mpp', 'Mpd',
                  'C1pp', 'C1pd',
                  'K0pp', 'K0pd',
                  'K2pp', 'K2pd']

    A, B = cbi.benchmark_lstsq_matrices(rollParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
            A[:, 1])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['RollRate'], A[:, 2])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['SteerRate'], A[:, 3])
    testing.assert_allclose(9.81 *
            trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 *
            trial.taskSignals['SteerAngle'], A[:, 5])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['RollAngle'], A[:, 6])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['SteerAngle'], A[:, 7])
    testing.assert_allclose(H[0] * trial.taskSignals['PullForce'], B)

    steerParams = ['Mdp', 'Mdd', 'C1dp', 'C1dd', 'K0dp', 'K0dd', 'K2dp',
            'K2dd', 'HdF']

    A, B = cbi.benchmark_lstsq_matrices(steerParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
            A[:, 1])

    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['RollRate'], A[:, 2])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['SteerRate'], A[:, 3])

    testing.assert_allclose(9.81 *
            trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 *
            trial.taskSignals['SteerAngle'], A[:, 5])

    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['RollAngle'], A[:, 6])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['SteerAngle'], A[:, 7])

    testing.assert_allclose(-trial.taskSignals['PullForce'], A[:, 8])
    testing.assert_allclose(trial.taskSignals['SteerTorque'], B)

    steerParams = ['Mdp', 'Mdd', 'C1dp', 'C1dd', 'K0dp', 'K0dd', 'K2dp',
            'K2dd']

    A, B = cbi.benchmark_lstsq_matrices(steerParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
            A[:, 0])
    testing.assert_allclose(trial.taskSignals['SteerRate'].time_derivative(),
            A[:, 1])

    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['RollRate'], A[:, 2])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['SteerRate'], A[:, 3])

    testing.assert_allclose(9.81 *
            trial.taskSignals['RollAngle'], A[:, 4])
    testing.assert_allclose(9.81 *
            trial.taskSignals['SteerAngle'], A[:, 5])

    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['RollAngle'], A[:, 6])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['SteerAngle'], A[:, 7])

    testing.assert_allclose(trial.taskSignals['SteerTorque'] +
            H[1] * trial.taskSignals['PullForce'], B)

    steerParams = ['Mdp', 'C1dd', 'K0dp', 'K2dp', 'K2dd']

    A, B = cbi.benchmark_lstsq_matrices(steerParams, timeSeries, fixedValues)

    testing.assert_allclose(trial.taskSignals['RollRate'].time_derivative(),
            A[:, 0])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed'] *
            trial.taskSignals['SteerRate'], A[:, 1])
    testing.assert_allclose(9.81 *
            trial.taskSignals['RollAngle'], A[:, 2])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['RollAngle'], A[:, 3])
    testing.assert_allclose(trial.taskSignals['ForwardSpeed']**2 *
            trial.taskSignals['SteerAngle'], A[:, 4])

    testing.assert_allclose(
            H[1] * trial.taskSignals['PullForce'] +
            trial.taskSignals['SteerTorque'] -
            fixedValues['Mdd'] * trial.taskSignals['SteerRate'].time_derivative() -
            fixedValues['C1dp'] * trial.taskSignals['ForwardSpeed'] * trial.taskSignals['RollRate'] -
            fixedValues['K0dd'] * 9.81 * trial.taskSignals['SteerAngle'], B)