def test_plot_eigs_narrowview_empty(self):
dmd = DMDBase()
# max/min throws an error if the array is empty (max used on empty
# array)
dmd.operator._eigenvalues = np.array([], dtype=np.complex)
with self.assertRaises(ValueError):
dmd.plot_eigs(show_axes=False, narrow_view=True, dpi=200)
def test_translate_tpow_negative(self):
dmd = DMDBase(opt=-1)
dmd._snapshots = sample_data
assert dmd._translate_eigs_exponent(10) == 10 - (sample_data.shape[1] -
1)
assert dmd._translate_eigs_exponent(0) == 1 - sample_data.shape[1]
def test_translate_tpow_vector(self):
dmd = DMDBase(opt=-1)
dmd._snapshots = sample_data
tpow = np.ndarray([0, 1, 2, 3, 5, 6, 7, 11])
for idx, x in enumerate(dmd._translate_eigs_exponent(tpow)):
assert x == dmd._translate_eigs_exponent(tpow[idx])
def test_enforce_ratio_x(self):
dmd = DMDBase()
supx, infx, supy, infy = dmd._enforce_ratio(10, 0, 0, 20, 10)
dx = supx - infx
dy = supy - infy
np.testing.assert_almost_equal(max(dx, dy) / min(dx, dy),
10,
decimal=6)
def test_plot_limits_narrow(self):
dmd = DMDBase()
dmd.operator._eigenvalues = np.array([complex(1, 2), complex(-1, -2)])
tp = dmd._plot_limits(True)
assert len(tp) == 4
supx, infx, supy, infy = tp
assert supx == 1.05
assert infx == -1.05
assert supy == 2.05
assert infy == -2.05
def __init__(self,
svd_rank: Union[int, float] = 0,
tlsq_rank: int = 0,
exact: bool = False,
opt: Union[bool, int] = False,
rescale_mode: Union[str, None, ndarray] = None,
forward_backward: bool = False,
sorted_eigs: Union[bool, str] = False) -> None:
PyDMDBase.__init__(self, svd_rank, tlsq_rank, exact, opt, rescale_mode,
forward_backward, sorted_eigs)
self._svd_modes: ndarray = None # svd modes
self._svd_vals: ndarray = None # singular values
def test_exact(self):
dmd = DMDBase(exact=True)
assert dmd.exact == True
def test_translate_tpow_positive(self):
dmd = DMDBase(opt=4)
assert dmd._translate_eigs_exponent(10) == 6
assert dmd._translate_eigs_exponent(0) == -4
def test_plot_limits(self):
dmd = DMDBase()
dmd.operator._eigenvalues = np.array([complex(-2, 2), complex(3, -3)])
limit = dmd._plot_limits(False)
assert limit == 5
def test_plot_snaps_2D(self):
dmd = DMDBase()
with self.assertRaises(ValueError):
dmd.plot_snapshots_2D()
def test_advanced_snapshot_parameter2(self):
dmd = DMDBase(opt=5)
assert dmd.opt == 5
def test_fit(self):
dmd = DMDBase(exact=False)
with self.assertRaises(NotImplementedError):
dmd.fit(sample_data)
def test_plot_eigs(self):
dmd = DMDBase()
with self.assertRaises(ValueError):
dmd.plot_eigs(show_axes=True, show_unit_circle=True)
def test_svd_rank_default(self):
dmd = DMDBase()
assert dmd.svd_rank == 0
def test_opt(self):
dmd = DMDBase(opt=True)
assert dmd.opt == True
def test_sorted_eigs_default(self):
dmd = DMDBase()
assert dmd.operator._sorted_eigs == False
def test_exact_default(self):
dmd = DMDBase()
assert dmd.exact == False
def test_tlsq_rank(self):
dmd = DMDBase(tlsq_rank=2)
assert dmd.tlsq_rank == 2
def test_tlsq_rank_default(self):
dmd = DMDBase()
assert dmd.tlsq_rank == 0
def test_svd_rank(self):
dmd = DMDBase(svd_rank=3)
assert dmd.svd_rank == 3
def test_sorted_eigs_param(self):
dmd = DMDBase(sorted_eigs='real')
assert dmd.operator._sorted_eigs == 'real'
def test_opt_default(self):
dmd = DMDBase()
assert dmd.opt == False
