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Python ContinuousTimeMSM.fit方法代码示例

本文整理汇总了Python中msmbuilder.msm.ContinuousTimeMSM.fit方法的典型用法代码示例。如果您正苦于以下问题：Python ContinuousTimeMSM.fit方法的具体用法？Python ContinuousTimeMSM.fit怎么用？Python ContinuousTimeMSM.fit使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类msmbuilder.msm.ContinuousTimeMSM的用法示例。


在下文中一共展示了ContinuousTimeMSM.fit方法的10个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_doublewell

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_doublewell():
    trjs = load_doublewell(random_state=0)['trajectories']
    for n_states in [10, 50]:
        clusterer = NDGrid(n_bins_per_feature=n_states)
        assignments = clusterer.fit_transform(trjs)

        for sliding_window in [True, False]:
            model = ContinuousTimeMSM(lag_time=100, sliding_window=sliding_window)
            model.fit(assignments)
            assert model.optimizer_state_.success
开发者ID:rmcgibbo，项目名称:msmbuilder，代码行数:12，代码来源:test_ratematrix.py

示例2: test_fit_1

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_fit_1():
    # call fit, compare to MSM
    sequence = [0, 0, 0, 1, 1, 1, 0, 0, 2, 2, 0, 1, 1, 1, 2, 2, 2, 2, 2]
    model = ContinuousTimeMSM(verbose=False)
    model.fit([sequence])

    msm = MarkovStateModel(verbose=False)
    msm.fit([sequence])

    # they shouldn't be equal in general, but for this input they seem to be
    np.testing.assert_array_almost_equal(model.transmat_, msm.transmat_)
开发者ID:synapticarbors，项目名称:msmbuilder-1，代码行数:13，代码来源:test_ratematrix.py

示例3: test_hessian

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_hessian():
    grid = NDGrid(n_bins_per_feature=10, min=-np.pi, max=np.pi)
    seqs = grid.fit_transform(load_doublewell(random_state=0)['trajectories'])
    seqs = [seqs[i] for i in range(10)]

    lag_time = 10
    model = ContinuousTimeMSM(verbose=True, lag_time=lag_time)
    model.fit(seqs)
    msm = MarkovStateModel(verbose=False, lag_time=lag_time)
    print(model.summarize())
    print('MSM timescales\n', msm.fit(seqs).timescales_)
    print('Uncertainty K\n', model.uncertainty_K())
    print('Uncertainty pi\n', model.uncertainty_pi())
开发者ID:synapticarbors，项目名称:msmbuilder-1，代码行数:15，代码来源:test_ratematrix.py

示例4: test_dump

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_dump():
    # gh-713
    sequence = [0, 0, 0, 1, 1, 1, 0, 0, 2, 2, 0, 1, 1, 1, 2, 2, 2, 2, 2]
    model = ContinuousTimeMSM(verbose=False)
    model.fit([sequence])

    d = tempfile.mkdtemp()
    try:
        utils.dump(model, '{}/cmodel'.format(d))
        m2 = utils.load('{}/cmodel'.format(d))
        np.testing.assert_array_almost_equal(model.transmat_, m2.transmat_)
    finally:
        shutil.rmtree(d)
开发者ID:Eigenstate，项目名称:msmbuilder，代码行数:15，代码来源:test_ratematrix.py

示例5: test_hessian_3

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_hessian_3():
    grid = NDGrid(n_bins_per_feature=4, min=-np.pi, max=np.pi)
    trajs = DoubleWell(random_state=0).get_cached().trajectories
    seqs = grid.fit_transform(trajs)
    seqs = [seqs[i] for i in range(10)]

    lag_time = 10
    model = ContinuousTimeMSM(verbose=False, lag_time=lag_time)
    model.fit(seqs)
    msm = MarkovStateModel(verbose=False, lag_time=lag_time)
    print(model.summarize())
    # print('MSM timescales\n', msm.fit(seqs).timescales_)
    print('Uncertainty K\n', model.uncertainty_K())
    print('Uncertainty eigs\n', model.uncertainty_eigenvalues())
开发者ID:Eigenstate，项目名称:msmbuilder，代码行数:16，代码来源:test_ratematrix.py

示例6: test_fit_2

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_fit_2():
    grid = NDGrid(n_bins_per_feature=5, min=-np.pi, max=np.pi)
    seqs = grid.fit_transform(load_doublewell(random_state=0)['trajectories'])

    model = ContinuousTimeMSM(verbose=True, lag_time=10)
    model.fit(seqs)
    t1 = np.sort(model.timescales_)
    t2 = -1/np.sort(np.log(np.linalg.eigvals(model.transmat_))[1:])

    model = MarkovStateModel(verbose=False, lag_time=10)
    model.fit(seqs)
    t3 = np.sort(model.timescales_)

    np.testing.assert_array_almost_equal(t1, t2)
    # timescales should be similar to MSM (withing 50%)
    assert abs(t1[-1] - t3[-1]) / t1[-1] < 0.50
开发者ID:synapticarbors，项目名称:msmbuilder-1，代码行数:18，代码来源:test_ratematrix.py

示例7: test_guess

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_guess():
    ds = MullerPotential(random_state=0).get_cached().trajectories
    cluster = NDGrid(n_bins_per_feature=5,
                     min=[PARAMS['MIN_X'], PARAMS['MIN_Y']],
                     max=[PARAMS['MAX_X'], PARAMS['MAX_Y']])
    assignments = cluster.fit_transform(ds)

    model1 = ContinuousTimeMSM(guess='log')
    model1.fit(assignments)

    model2 = ContinuousTimeMSM(guess='pseudo')
    model2.fit(assignments)

    diff = model1.loglikelihoods_[-1] - model2.loglikelihoods_[-1]
    assert np.abs(diff) < 1e-3
    assert np.max(np.abs(model1.ratemat_ - model2.ratemat_)) < 1e-1
开发者ID:Eigenstate，项目名称:msmbuilder，代码行数:18，代码来源:test_ratematrix.py

示例8: test_score_2

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_score_2():
    ds = MullerPotential(random_state=0).get_cached().trajectories
    cluster = NDGrid(n_bins_per_feature=6,
                     min=[PARAMS['MIN_X'], PARAMS['MIN_Y']],
                     max=[PARAMS['MAX_X'], PARAMS['MAX_Y']])
    assignments = cluster.fit_transform(ds)
    test_indices = [5, 0, 4, 1, 2]
    train_indices = [3, 6, 7, 8, 9]

    model = ContinuousTimeMSM(lag_time=3, n_timescales=1)
    model.fit([assignments[i] for i in train_indices])
    test = model.score([assignments[i] for i in test_indices])
    train = model.score_
    print('train', train, 'test', test)
    assert 1 <= test < 2
    assert 1 <= train < 2
开发者ID:Eigenstate，项目名称:msmbuilder，代码行数:18，代码来源:test_ratematrix.py

示例9: test_score_2

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_score_2():
    from msmbuilder.example_datasets.muller import MULLER_PARAMETERS as PARAMS
    ds = MullerPotential(random_state=0).get()['trajectories']
    cluster = NDGrid(n_bins_per_feature=6,
          min=[PARAMS['MIN_X'], PARAMS['MIN_Y']],
          max=[PARAMS['MAX_X'], PARAMS['MAX_Y']])
    assignments = cluster.fit_transform(ds)
    test_indices = [5, 0, 4, 1, 2]
    train_indices = [3, 6, 7, 8, 9]

    model = ContinuousTimeMSM(lag_time=3, n_timescales=1)
    model.fit([assignments[i] for i in train_indices])
    test = model.score([assignments[i] for i in test_indices])
    train = model.score_
    print('train', train, 'test', test)
    assert 1 <= test < 2
    assert 1 <= train < 2
开发者ID:kyleabeauchamp，项目名称:msmbuilder，代码行数:19，代码来源:test_ratematrix.py

示例10: test_guess

# 需要导入模块: from msmbuilder.msm import ContinuousTimeMSM [as 别名]
# 或者: from msmbuilder.msm.ContinuousTimeMSM import fit [as 别名]
def test_guess():
    from msmbuilder.example_datasets.muller import MULLER_PARAMETERS as PARAMS

    cluster = NDGrid(n_bins_per_feature=5,
          min=[PARAMS['MIN_X'], PARAMS['MIN_Y']],
          max=[PARAMS['MAX_X'], PARAMS['MAX_Y']])

    ds = MullerPotential(random_state=0).get()['trajectories']
    assignments = cluster.fit_transform(ds)

    model1 = ContinuousTimeMSM(guess='log')
    model1.fit(assignments)

    model2 = ContinuousTimeMSM(guess='pseudo')
    model2.fit(assignments)

    assert np.abs(model1.loglikelihoods_[-1] - model2.loglikelihoods_[-1]) < 1e-3
    assert np.max(np.abs(model1.ratemat_ - model2.ratemat_)) < 1e-1
开发者ID:rmcgibbo，项目名称:msmbuilder，代码行数:20，代码来源:test_ratematrix.py


注：本文中的msmbuilder.msm.ContinuousTimeMSM.fit方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。