def test_timeserie_getitem():
a = TimeSerie([1, 2, 3])
assert a[0] == 1
assert a[-1] == 3
b = TimeSerie([1, 2, 3, 4, 5, 6, 7])
assert b[1] == 2
return True
def test_timeserie_toevents():
a = TimeSerie([1, 2, 3], t0=1, fs=2, name="a")
e1, e2, e3 = a.to_events()
assert compare_events(e1, Event(1, t=1, name="a"))
assert compare_events(e2, Event(2, 1.5, name="a"))
assert compare_events(e3, Event(3, 2.0, name="a"))
return True
def test_statechangearray_totimeseries():
a = StateChangeArray([1, 3, 5, 7], t=[1, 2, 4, 7], name="a")
ts_a = a.to_timeseries(fs=2)
assert compare_timeseries(
ts_a,
TimeSerie([1, 1, 3, 3, 3, 3, 5, 5, 5, 5, 5, 5, 7],
t0=1,
fs=2,
name="a"))
b = StateChangeArray([1, 3, 5, 7], t=[1, 2, 2.25, 4])
with pytest.raises(ValueError):
ts_b = b.to_timeseries(fs=2)
with pytest.raises(NameError):
b.to_timeseries(fs=2, method="nonExistingMethod")
c = StateChangeArray([1, 3, 5, 7], t=[1, 2, 4, 8], name="c")
ts_c = c.to_timeseries(fs=2, method="interpolate")
assert compare_timeseries(
ts_c,
TimeSerie(
[1, 2, 3, 3.5, 4, 4.5, 5, 5.25, 5.5, 5.75, 6, 6.25, 6.5, 6.75, 7],
t0=1,
fs=2,
name="c",
),
)
return True
def test_timeserie_where():
a = TimeSerie([1, 2, 3, 4, 5, 6], t0=1, fs=1, name="a")
d = a.where(a.t >= 3)
d_test = np.array([3, 4, 5, 6])
assert len(d) == len(d_test)
assert all(d == d_test)
return True
def test_timeserie_rsub():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
sub_1 = 1 - a
assert compare_timeseries(sub_1, TimeSerie([0, -1, -2],
name="",
fs=1,
t0=1))
return True
def test_timeserie_invert():
a = TimeSerie([True, False], name="a", fs=1, t0=1)
b = TimeSerie([1, 2, 3, 4], name="b", fs=1, t0=1)
invert_1 = ~a
assert compare_timeseries(
invert_1, BooleanTimeSerie([False, True], name="(~a)", fs=1, t0=1))
with pytest.raises(ValueError):
invert_2 = ~b
return True
def test_timeserie_sub():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
b = TimeSerie([3, 1, 3], name="b", fs=1, t0=1)
sub_1 = a - b
assert compare_timeseries(
sub_1, TimeSerie([-2, 1, 0], name="(a - b)", fs=1, t0=1))
sub_2 = a - 1
assert compare_timeseries(sub_2, TimeSerie([0, 1, 2], name="", fs=1, t0=1))
c = TimeSerie([7, 8, 9, 0], name="c", fs=1, t0=0)
with pytest.raises(ValueError):
sub_3 = a - c
return True
def test_timeserie_add():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
b = TimeSerie([3, 1, 3], name="b", fs=1, t0=1)
add_1 = a + b
assert compare_timeseries(add_1,
TimeSerie([4, 3, 6], name="(a + b)", fs=1, t0=1))
add_2 = a + 1
assert compare_timeseries(add_2, TimeSerie([2, 3, 4], name="", fs=1, t0=1))
c = TimeSerie([7, 8, 9, 0], name="c", fs=1, t0=0)
with pytest.raises(ValueError):
add_3 = a + c
return True
def test_timeserie_tobool():
a = TimeSerie([0, 0, 0, 1, 2, 3], t0=1, fs=2, name="a")
b = a.to_bool(inplace=False)
assert compare_timeseries(
b,
BooleanTimeSerie([False, False, False, True, True, True],
t0=1,
fs=2,
name="a"),
)
a.to_bool(inplace=True)
assert compare_timeseries(a, b)
return True
def test_timeserie_neq():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
eq_1 = a != a
assert compare_timeseries(
eq_1,
BooleanTimeSerie([False, False, False], t0=1, name="(a != a)", fs=1))
eq_2 = a != 1
assert compare_timeseries(
eq_2, BooleanTimeSerie([False, True, True], t0=1, fs=1, name=""))
b = TimeSerie([1, 2, 3], fs=2, name="b", t0=1)
with pytest.raises(ValueError):
eq_4 = a != b
return True
def test_timeserie_or():
a = TimeSerie([True, True, False, False], name="a", fs=1, t0=1)
b = BooleanTimeSerie([True, False, True, False], name="b", fs=1, t0=1)
c = TimeSerie([1, 2, 3, 4], name="c", fs=1, t0=1)
d = BooleanTimeSerie([True, True, True, True], name="d", fs=2, t0=3)
and_1 = a | b
assert compare_timeseries(
and_1,
BooleanTimeSerie([True, True, True, False], name="(a | b)", fs=1,
t0=1))
with pytest.raises(ValueError):
and_2 = a | c
with pytest.raises(ValueError):
and_3 = b | d
return True
def test_report_totimeserie():
a = Report(2, 4, name="a")
ts_a = a.to_timeserie()
assert compare_timeseries(
ts_a, TimeSerie([0.0, 1.0, 1.0, 0.0], t0=1.0, fs=1, name="a"))
b = Report(3, 8, name="b")
ts_b = b.to_timeserie(fs=4, window=2)
cmp_b = TimeSerie([0.0, 0.0] + (20 * [1.0]) + [0.0, 0.0],
t0=2.5,
fs=4,
name="b")
ts_b._reprconfig["threshold"] = 100
cmp_b._reprconfig["threshold"] = 100
assert compare_timeseries(ts_b, cmp_b)
return True
def test_timeserie_greaterequalthen():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
b = TimeSerie([3, 1, 3], name="b", fs=1, t0=1)
lt_1 = a >= b
assert compare_timeseries(
lt_1, BooleanTimeSerie([False, True, True],
t0=1,
fs=1,
name="(a >= b)"))
lt_2 = a >= 2
assert compare_timeseries(
lt_2, BooleanTimeSerie([False, True, True], t0=1, fs=1, name=""))
c = TimeSerie([7, 8, 9, 0], name="c", fs=1, t0=0)
with pytest.raises(ValueError):
eq_3 = a >= c
return True
def test_timeserie_lessthen():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
b = TimeSerie([3, 1, 5], name="b", fs=1, t0=1)
lt_1 = b < a
assert compare_timeseries(
lt_1, BooleanTimeSerie([False, True, False],
t0=1,
fs=1,
name="(b < a)"))
lt_2 = a < 2
assert compare_timeseries(
lt_2, BooleanTimeSerie([True, False, False], t0=1, fs=1, name=""))
c = TimeSerie([7, 8, 9, 0], name="c", fs=1, t0=0)
with pytest.raises(ValueError):
eq_3 = a < c
return True
def test_timeserie_init():
a = TimeSerie([1, 2, 3], t0=0, fs=1, name="a")
assert all(a.data == [1, 2, 3])
assert a.t0 == 0
assert a.fs == 1
assert a.name == "a"
return True
def test_timeserie_roundt0():
a = TimeSerie(np.arange(10), name="a", fs=1, t0=1.1)
assert a.t0 == 1.1
a.round_t0()
assert a.t0 == 1.0
a = TimeSerie(np.arange(100), name="a", fs=10, t0=1.11)
assert a.t0 == 1.11
a.round_t0()
assert a.t0 == 1.1
def test_multiple_plots():
plt.ioff()
a = StateChangeArray([0, 1, 0, 1, 0], t=[0, 5, 10, 20, 30],
name="a").to_bool()
b = StateChangeArray([0, 1, 0, 1, 0], t=[0, 2, 5, 7, 15],
name="b").to_bool()
c = TimeSerie(np.linspace(0, 10, 100), t0=0, fs=10, name="c")
a.plot(b, c, align_x=True)
return True
def test_timeserie_empty():
a = TimeSerie.empty(1, 10, fs=10, name="a")
assert len(a) == 90
assert a.te == 9.9
b = TimeSerie.empty(2, 5, fs=4, name="b", inclusive=True)
assert len(b) == 13
assert b.te == 5.0
c = TimeSerie.empty(
dt.datetime(2018, 1, 1, 12),
dt.datetime(2018, 1, 1, 13),
fs=1,
name="c",
inclusive=True,
)
assert c.te - c.t0 == 3600.0
d = TimeSerie.empty(1.2, 4.8, fs=100, name="d")
assert d.t0 == 1.2
assert d.te == 4.79
return True
def test_timeserie_toreports():
a = TimeSerie(10 * np.sin(np.linspace(0, 2 * np.pi, 100)),
t0=1,
fs=10,
name="a")
b = a > 4
b.name = "a > 4"
reports = b.to_reports()
assert len(reports) == 1
assert compare_reports(reports[0], Report(1.7, 5.4, name="a > 4"))
return True
def test_timeserie_datetime_t0():
a = TimeSerie([1, 2, 3],
t0=pytz.utc.localize(dt.datetime(2000, 1, 1)),
fs=1,
name="a")
b = TimeSerie([1, 2, 3], t0=dt.datetime(2000, 1, 1), fs=1, name="b")
assert a.t0 == 946684800.0
assert a.te == 946684802.0
assert a.dt0 == dt.datetime(2000, 1, 1)
assert a.dte == dt.datetime(2000, 1, 1, 0, 0, 2)
assert all(a.dt == np.array(
["2000-01-01T00:00:00", "2000-01-01T00:00:01", "2000-01-01T00:00:02"],
dtype="datetime64",
))
assert b.t0 == 946684800.0
assert b.te == 946684802.0
assert b.dt0 == dt.datetime(2000, 1, 1)
assert b.dte == dt.datetime(2000, 1, 1, 0, 0, 2)
assert all(b.dt == np.array(
["2000-01-01T00:00:00", "2000-01-01T00:00:01", "2000-01-01T00:00:02"],
dtype="datetime64",
))
return True
def test_timeserie_properties():
a = TimeSerie([1, 2, 3], name="a", fs=2, t0=1)
assert a.hz == a.fs
a.hz = 1
assert a.fs == 1
b = TimeSerie([4, 5, 6], name="a", fs=1, t0=1)
b.data = [1, 2, 3]
assert isinstance(b.data, np.ndarray)
assert all(b.data == [1, 2, 3])
assert compare_timeseries(a, b)
with pytest.raises(ValueError):
a.channel = (1, 2, 3)
return True
def test_timeserie_plot():
plt.ioff()
a = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=1)
f = a.plot()
b = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5],
name="b",
fs=1,
t0=dt.datetime(2019, 1, 1))
f = b.plot(as_dt=True)
return True
def test_timeserie_interpolate():
a = TimeSerie([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], t0=0, fs=1, name="a")
t_new = np.arange(0, 9 + 0.5, 0.5)
b = a.interpolate(t_new, inplace=False)
assert compare_timeseries(
b, TimeSerie(np.arange(1, 10.5, 0.5), t0=0, fs=2, name="a"))
a.interpolate(t_new, inplace=True)
assert compare_timeseries(a, b)
c = BooleanTimeSerie([False, False, True, True, True, False, False],
t0=1,
fs=1,
name="c")
t_new = np.arange(1, 7 + 0.5, 0.5)
d = c.interpolate(t_new, inplace=False)
assert compare_timeseries(
d,
BooleanTimeSerie(3 * [False] + 7 * [True] + 3 * [False],
t0=1,
fs=2,
name="c"),
)
c.interpolate(t_new, inplace=True)
assert compare_timeseries(c, d)
return True
def test_timeserie_nparray():
a = TimeSerie(np.array([1, 2, 3]), t0=0, fs=1, name="a")
assert isinstance(a.data, np.ndarray)
b = TimeSerie([1, 2, 3], t0=0, fs=1, name="b")
assert isinstance(b.data, np.ndarray)
return True
def test_timeserie_len():
a = TimeSerie([1, 2, 3])
assert len(a) == 3
b = TimeSerie([1, 2, 3, 4, 5, 6, 7])
assert len(b) == 7
return True
def test_timeserie_tostatechangearray():
a = TimeSerie([1, 1, 1, 2, 2, 3, 4, 4, 4], t0=1, fs=2, name="a")
sta_a = a.to_statechangearray()
assert compare_statechangearrays(
sta_a, StateChangeArray([1, 2, 3, 4], t=[1, 2.5, 3.5, 4], name="a"))
return True
def test_timeserie_radd():
a = TimeSerie([1, 2, 3], name="a", fs=1, t0=1)
add_1 = 1 + a
assert compare_timeseries(add_1, TimeSerie([2, 3, 4], name="", fs=1, t0=1))
return True
def test_timeserie_at():
a = TimeSerie([1, 2, 3, 4, 5, 6], t0=1, fs=1, name="a")
assert a.at(2) == 2
return True
def test_timserie_mod():
a = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=1)
b = a.modify("default", inplace=False)
assert compare_timeseries(b, a)
a.modify("default", inplace=True)
assert compare_timeseries(a, b)
a = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=1)
b = a.modify("zero_negatives", inplace=False)
assert compare_timeseries(
b, TimeSerie([0, 0, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=1))
a.modify("zero_negatives", inplace=True)
assert compare_timeseries(a, b)
a = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=1)
b = a.modify("correct_negatives", inplace=False)
assert compare_timeseries(
b, TimeSerie([0, 1, 2, 3, 4, 5, 6, 7], name="a", fs=1, t0=1))
a.modify("correct_negatives", inplace=True)
assert compare_timeseries(a, b)
return True
def test_timeserie_tochannel():
a = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=3)
b = TimeSerie.empty(0, 20, fs=1)
a.to_channel(b)
assert len(a) == 20
assert a.t0 == 0
assert a.te == 19
assert a.at(3) == -2
assert a.at(4) == -1
assert a.at(5) == 0
assert a.at(6) == 1
assert a.at(7) == 2
assert a.at(8) == 3
assert a.at(9) == 4
assert a.at(10) == 5
c = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=3)
d = TimeSerie.empty(0, 20, fs=2)
with pytest.raises(ValueError):
c.to_channel(d)
e = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=3)
f = TimeSerie.empty(4, 20, fs=1)
with pytest.raises(DataLossError):
e.to_channel(f)
g = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=3)
h = TimeSerie.empty(0, 8, fs=1)
with pytest.raises(DataLossError):
g.to_channel(h)
i = TimeSerie([-2, -1, 0, 1, 2, 3, 4, 5], name="a", fs=1, t0=3)
j = TimeSerie.empty(0.5, 20.5, fs=1)
with pytest.raises(ValueError):
i.to_channel(j)
return True
