def test_dmd_time_1(self):
dmd = DMD(svd_rank=2)
dmd.fit(X=sample_data)
expected_dict = {'dt': 1, 't0': 0, 'tend': 14}
np.testing.assert_equal(dmd.dmd_time, expected_dict)
def test_plot_eigs_2(self):
dmd = DMD()
dmd.fit(X=sample_data)
dmd.plot_eigs(show_axes=False, show_unit_circle=False)
plt.close()
def test_reconstructed_data(self):
dmd = DMD()
dmd.fit(X=sample_data)
dmd_data = dmd.reconstructed_data
np.testing.assert_allclose(dmd_data, sample_data)
def test_original_timesteps(self):
dmd = DMD()
dmd.fit(X=sample_data)
np.testing.assert_allclose(dmd.original_timesteps,
np.arange(sample_data.shape[1]))
def test_tdmd_plot(self):
dmd = DMD(tlsq_rank=3)
dmd.fit(X=sample_data)
dmd.plot_eigs(show_axes=False, show_unit_circle=False)
plt.close()
def test_dynamics_opt_1(self):
dmd = DMD(svd_rank=5, opt=True)
dmd.fit(X=sample_data)
assert dmd.dynamics.shape == (5, sample_data.shape[1])
def test_rank(self):
dmd = DMD(svd_rank=0.9)
dmd.fit(X=sample_data)
assert len(dmd.eigs) == 2
def test_plot_modes_4(self):
dmd = DMD()
snapshots = [snap.reshape(20, 20) for snap in sample_data.T]
dmd.fit(X=snapshots)
dmd.plot_modes_2D(index_mode=1)
plt.close()
def test_sorted_eigs_default(self):
dmd = DMD()
assert dmd.operator._sorted_eigs == False
def test_sorted_eigs_set_real(self):
dmd = DMD(sorted_eigs='real')
assert dmd.operator._sorted_eigs == 'real'
def test_truncation_shape(self):
dmd = DMD(svd_rank=3)
dmd.fit(X=sample_data)
assert dmd.modes.shape[1] == 3
def test_shape(self):
dmd = DMD(svd_rank=-1)
dmd.fit(X=sample_data)
assert dmd.modes.shape[1] == sample_data.shape[1] - 1
def test_rescale_mode_coefficients_count_check(self):
dmd_rescale = DMD(svd_rank=5,
opt=True,
rescale_mode=np.linspace(5, 10, 6))
with self.assertRaises(ValueError):
dmd_rescale.fit(X=sample_data)
def test_plot_modes_1(self):
dmd = DMD()
dmd.fit(X=sample_data)
with self.assertRaises(ValueError):
dmd.plot_modes_2D()
def test_Atilde_shape(self):
dmd = DMD(svd_rank=3)
dmd.fit(X=sample_data)
assert dmd.atilde.shape == (dmd.svd_rank, dmd.svd_rank)
def test_plot_modes_2(self):
dmd = DMD(svd_rank=-1)
dmd.fit(X=sample_data)
dmd.plot_modes_2D((1, 2, 5), x=np.arange(20), y=np.arange(20))
plt.close()
def test_eigs_2(self):
dmd = DMD(svd_rank=5)
dmd.fit(X=sample_data)
assert len(dmd.eigs) == 5
def test_plot_modes_5(self):
dmd = DMD()
snapshots = [snap.reshape(20, 20) for snap in sample_data.T]
dmd.fit(X=snapshots)
dmd.plot_modes_2D(index_mode=1, filename='tmp.png')
self.addCleanup(os.remove, 'tmp.1.png')
def test_plot_snapshots_3(self):
dmd = DMD()
snapshots = [snap.reshape(20, 20) for snap in sample_data.T]
dmd.fit(X=snapshots)
dmd.plot_snapshots_2D()
plt.close()
