How to use the pydmd.cdmd.CDMD function in PyDMD

To help you get started, we’ve selected a few PyDMD examples, based on popular ways it is used in public projects.

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github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_plot_modes_3(self):
        dmd = CDMD()
        snapshots = [snap.reshape(20, 20) for snap in sample_data.T]
        dmd.fit(X=snapshots)
        dmd.plot_modes_2D()
        plt.close()
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_shape(self):
        dmd = CDMD(svd_rank=-1)
        dmd.fit(X=[d for d in sample_data.T])
        assert dmd.modes.shape[1] == sample_data.shape[1] - 1
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_cdmd_matrix_sample(self):
        dmd = CDMD(compression_matrix='sample')
        dmd.fit(X=sample_data)
        error_norm = np.linalg.norm(dmd.reconstructed_data - sample_data, 1)
        assert error_norm < 1e-10
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_dmd_time_3(self):
        dmd = CDMD()
        dmd.fit(X=sample_data)
        dmd.dmd_time['t0'] = 8
        dmd.dmd_time['tend'] = 11
        expected_data = sample_data[:, 8:12]
        np.testing.assert_allclose(dmd.reconstructed_data, expected_data)
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_cdmd_matrix_uniform(self):
        dmd = CDMD(compression_matrix='uniform')
        dmd.fit(X=sample_data)
        error_norm = np.linalg.norm(dmd.reconstructed_data - sample_data, 1)
        assert error_norm < 1e-10
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_cdmd_matrix_sparse(self):
        dmd = CDMD(compression_matrix='sparse')
        dmd.fit(X=sample_data)
        error_norm = np.linalg.norm(dmd.reconstructed_data - sample_data, 1)
        assert error_norm < 1e-10
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_plot_modes_1(self):
        dmd = CDMD()
        dmd.fit(X=sample_data)
        with self.assertRaises(ValueError):
            dmd.plot_modes_2D()
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_plot_modes_4(self):
        dmd = CDMD()
        snapshots = [snap.reshape(20, 20) for snap in sample_data.T]
        dmd.fit(X=snapshots)
        dmd.plot_modes_2D(index_mode=1)
        plt.close()
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_reconstructed_data(self):
        dmd = CDMD()
        dmd.fit(X=sample_data)
        dmd_data = dmd.reconstructed_data
        np.testing.assert_allclose(dmd_data, sample_data)
github mathLab / PyDMD / tests / test_cdmd.py View on Github external
def test_dmd_time_2(self):
        dmd = CDMD()
        dmd.fit(X=sample_data)
        dmd.dmd_time['t0'] = 10
        dmd.dmd_time['tend'] = 14
        expected_data = sample_data[:, -5:]
        np.testing.assert_allclose(dmd.reconstructed_data, expected_data)