How to use the pydmd.fbdmd.FbDMD function in pydmd

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github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_modes_shape(self):
        dmd = FbDMD(svd_rank=-1)
        dmd.fit(X=sample_data)
        assert dmd.modes.shape[1] == 2
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_plot_eigs_2(self):
        dmd = FbDMD(svd_rank=-1)
        dmd.fit(X=sample_data)
        dmd.plot_eigs(show_axes=False, show_unit_circle=False)
        plt.close()
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_dynamics(self):
        dmd = FbDMD(svd_rank=-1)
        dmd.fit(X=sample_data)
        assert dmd.dynamics.shape == (2, 100)
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_reconstructed_data(self):
        dmd = FbDMD(exact=True, svd_rank=-1)
        dmd.fit(X=sample_data)
        dmd_data = dmd.reconstructed_data
        dmd_data_correct = np.load('tests/test_datasets/fbdmd_data.npy')
        assert np.allclose(dmd_data, dmd_data_correct)
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_eigs_2(self):
        dmd = FbDMD(svd_rank=1)
        dmd.fit(X=sample_data)
        assert len(dmd.eigs) == 1
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_eigs_modulus_2(self):
        dmd = FbDMD(svd_rank=-1, exact=True)
        dmd.fit(X=sample_data)
        np.testing.assert_almost_equal(
            np.linalg.norm(dmd.eigs[1]), 1., decimal=6)
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_truncation_shape(self):
        dmd = FbDMD(svd_rank=1)
        dmd.fit(X=sample_data)
        assert dmd.modes.shape[1] == 1
github mathLab / PyDMD / tests / test_fbdmd.py View on Github external
def test_eigs_1(self):
        dmd = FbDMD(svd_rank=-1)
        dmd.fit(X=sample_data)
        assert len(dmd.eigs) == 2