def test_quantity_output(self):
q = 500.25 * u.day
dt = TimeDelta(q)
assert dt.to(u.day) == q
assert dt.to_value(u.day) == q.value
assert dt.to_value('day') == q.value
assert dt.to(u.second).value == q.to_value(u.second)
assert dt.to_value(u.second) == q.to_value(u.second)
assert dt.to_value('s') == q.to_value(u.second)
# Following goes through "format", but should be the same.
assert dt.to_value('sec') == q.to_value(u.second)
def test_quantity_output(self):
q = 500.25*u.day
dt = TimeDelta(q)
assert dt.to(u.day) == q
assert dt.to_value(u.day) == q.value
assert dt.to(u.second).value == q.to_value(u.second)
assert dt.to_value(u.second) == q.to_value(u.second)
with pytest.raises(u.UnitsError):
dt.to(u.m)
with pytest.raises(u.UnitsError):
dt.to_value(u.m)
def test_quantity_output_errors(self):
dt = TimeDelta(250., format='sec')
with pytest.raises(u.UnitsError):
dt.to(u.m)
with pytest.raises(u.UnitsError):
dt.to_value(u.m)
with pytest.raises(u.UnitsError):
dt.to_value(unit=u.m)
with pytest.raises(ValueError,
match=("not one of the known formats.*"
"failed to parse as a unit")):
dt.to_value('parrot')
with pytest.raises(TypeError):
dt.to_value('sec', unit=u.s)
with pytest.raises(TypeError):
# TODO: would be nice to make this work!
dt.to_value(u.s, subfmt='str')
def test_to_value(self):
dt = TimeDelta(86400.0, format='sec')
assert dt.to_value('jd') == 1.
assert dt.to_value('jd', 'str') == '1.0'
assert dt.to_value('sec', subfmt='str') == '86400.0'
with pytest.raises(ValueError,
match=("not one of the known formats.*"
"failed to parse as a unit")):
dt.to_value('julian')
with pytest.raises(TypeError, match='missing required format or unit'):
dt.to_value()
def test_no_units_warning():
with pytest.warns(TimeDeltaMissingUnitWarning):
delta = TimeDelta(1)
assert delta.to_value(u.day) == 1
with pytest.warns(TimeDeltaMissingUnitWarning):
table = Table({"t": [1, 2, 3]})
delta = TimeDelta(table["t"])
assert np.all(delta.to_value(u.day) == [1, 2, 3])
with pytest.warns(TimeDeltaMissingUnitWarning):
delta = TimeDelta(np.array([1, 2, 3]))
assert np.all(delta.to_value(u.day) == [1, 2, 3])
with pytest.warns(TimeDeltaMissingUnitWarning):
t = Time('2012-01-01') + 1
assert t.isot[:10] == '2012-01-02'
with pytest.warns(TimeDeltaMissingUnitWarning):
comp = TimeDelta([1, 2, 3], format="jd") >= 2
assert np.all(comp == [False, True, True])
with pytest.warns(TimeDeltaMissingUnitWarning):
# 2 is also interpreted as days, not seconds
assert (TimeDelta(5 * u.s) > 2) is False
# with unit is ok
assert TimeDelta(1 * u.s).to_value(u.s) == 1
# with format is also ok
assert TimeDelta(1, format="sec").to_value(u.s) == 1
assert TimeDelta(1, format="jd").to_value(u.day) == 1
# table column with units
table = Table({"t": [1, 2, 3] * u.s})
assert np.all(TimeDelta(table["t"]).to_value(u.s) == [1, 2, 3])
def check_errors(init_time, dt, sat, trajectory, generate_plots=False):
"""Checks the errors for the given trajectory."""
# **** Check the results ****
step_offset = 0
test_stepsize = 1.0 * u.s
test_end = 0.01 * u.day
# print(f"Test duration: {(test_end - step_offset * dt).to(u.day)}")
# print(f"Step size: {test_stepsize}")
dt_list_hires = TimeDelta(
np.arange(
step_offset * dt.to_value(u.s),
test_end.to_value(u.s),
test_stepsize.to_value(u.s),
),
format="sec",
)
time_list_hires = init_time + dt_list_hires
# Generate the high-res test trajectory
e_test_list, r_test_list, v_test_list = sat.sgp4_array(
time_list_hires.jd1, time_list_hires.jd2)
r_test_list = CartesianRepresentation(r_test_list.transpose(), unit=u.km)
# Generate the error list
r_err_list = (
trajectory(time_list_hires).cartesian.without_differentials() -
r_test_list)
# Error stats
max_err = r_err_list.norm().max() # max expected error
max_nominal_err = r_err_list[-100:].norm().max(
) # max expected error nominal
if generate_plots:
print(f"max error at the beginning : {max_err.to(u.mm)}")
print(f"max error after settle down : {max_nominal_err.to(u.mm)}")
dt_list_hires_plot = dt_list_hires.to_value(u.day)
# Plot the error per axis
fr_ticker = np.arange(dt_list_hires_plot[0], dt_list_hires_plot[-1],
dt.to_value(u.day))
y_ticker = np.zeros(len(fr_ticker))
plt.figure()
plt.plot(
dt_list_hires_plot,
np.asarray(r_err_list.get_xyz(xyz_axis=1)),
fr_ticker,
y_ticker,
"x",
)
plt.legend(["x", "y", "z", "stepsize"])
plt.title(f"Interpolation Error\n({trajectory.interpolator_name})")
plt.xlabel("Time [days]")
plt.ylabel("Error [km]")
# plt.yscale("log") # Uncomment to get y axis in log scale
plt.show()
return max_err, max_nominal_err
