def test_join_with_different_dt(self):
_times = [5, 5.5, 6]
_counts = [2, 2, 2]
lc1 = Lightcurve(self.times, self.counts)
lc2 = Lightcurve(_times, _counts)
with warnings.catch_warnings(record=True) as w:
lc1.join(lc2)
assert "different bin widths" in str(w[0].message)
def test_join_with_different_dt(self):
_times = [5, 5.5, 6]
_counts = [2, 2, 2]
lc1 = Lightcurve(self.times, self.counts)
lc2 = Lightcurve(_times, _counts)
with warnings.catch_warnings(record=True) as w:
lc1.join(lc2)
assert "different bin widths" in str(w[0].message)
def test_join_with_different_mjdref(self):
shift = 86400. # day
lc1 = Lightcurve(self.times + shift,
self.counts,
gti=self.gti + shift,
mjdref=57000)
lc2 = Lightcurve(self.times, self.counts, gti=self.gti, mjdref=57001)
newlc = lc1.join(lc2)
# The join operation *averages* the overlapping arrays
assert np.allclose(newlc.counts, lc1.counts)
def test_join_disjoint_time_arrays(self):
_times = [5, 6, 7, 8]
_counts = [2, 2, 2, 2]
lc1 = Lightcurve(self.times, self.counts)
lc2 = Lightcurve(_times, _counts)
lc = lc1.join(lc2)
assert len(lc.counts) == len(lc.time) == 8
assert np.all(lc.counts == 2)
def test_join_different_err_dist_overlapping_times(self):
_times = [3, 4, 5, 6]
_counts = [4, 4, 4, 4]
lc1 = Lightcurve(self.times, self.counts, err_dist="poisson")
lc2 = Lightcurve(_times, _counts, err_dist="gauss")
with warnings.catch_warnings(record=True) as w:
lc3 = lc1.join(lc2)
assert "We are setting the errors to zero." in str(w[1].message)
assert np.all(lc3.counts_err == np.zeros_like(lc3.time))
def test_join_different_err_dist_disjoint_times(self):
_times = [5 , 6, 7, 8]
_counts =[2, 2, 2, 2]
lc1 = Lightcurve(self.times, self.counts, err_dist = "poisson")
lc2 = Lightcurve(_times, _counts, err_dist = "gauss")
lc3 = lc1.join(lc2)
assert np.all(lc3.counts_err[:len(self.times)] == lc1.counts_err)
assert np.all(lc3.counts_err[len(self.times):] == np.zeros_like(lc2.counts))
def test_join_different_err_dist_overlapping_times(self):
_times = [3, 4, 5, 6]
_counts = [4, 4, 4, 4]
lc1 = Lightcurve(self.times, self.counts, err_dist = "poisson")
lc2 = Lightcurve(_times, _counts, err_dist = "gauss")
with warnings.catch_warnings(record=True) as w:
lc3 = lc1.join(lc2)
assert "We are setting the errors to zero." in str(w[1].message)
assert np.all(lc3.counts_err == np.zeros_like(lc3.time))
def test_join_different_err_dist_disjoint_times(self):
_times = [5 , 6, 7, 8]
_counts =[2, 2, 2, 2]
lc1 = Lightcurve(self.times, self.counts, err_dist = "poisson")
lc2 = Lightcurve(_times, _counts, err_dist = "gauss")
lc3 = lc1.join(lc2)
assert np.all(lc3.counts_err[:len(self.times)] == lc1.counts_err)
assert np.all(lc3.counts_err[len(self.times):] == np.zeros_like(lc2.counts))
def test_join_disjoint_time_arrays(self):
_times = [5, 6, 7, 8]
_counts = [2, 2, 2, 2]
lc1 = Lightcurve(self.times, self.counts)
lc2 = Lightcurve(_times, _counts)
lc = lc1.join(lc2)
assert len(lc.counts) == len(lc.time) == 8
assert np.all(lc.counts == 2)
def test_join_overlapping_time_arrays(self):
_times = [3, 4, 5, 6]
_counts = [4, 4, 4, 4]
lc1 = Lightcurve(self.times, self.counts)
lc2 = Lightcurve(_times, _counts)
with warnings.catch_warnings(record=True) as w:
lc = lc1.join(lc2)
assert "overlapping time ranges" in str(w[0].message)
assert len(lc.counts) == len(lc.time) == 6
assert np.all(lc.counts == np.array([2, 2, 3, 3, 4, 4]))
def test_join_overlapping_time_arrays(self):
_times = [3, 4, 5, 6]
_counts = [4, 4, 4, 4]
lc1 = Lightcurve(self.times, self.counts)
lc2 = Lightcurve(_times, _counts)
with warnings.catch_warnings(record=True) as w:
lc = lc1.join(lc2)
assert "overlapping time ranges" in str(w[0].message)
assert len(lc.counts) == len(lc.time) == 6
assert np.all(lc.counts == np.array([2, 2, 3, 3, 4, 4]))
def test_join_different_err_dist_disjoint_times(self):
_times = [5, 6, 7, 8]
_counts = [2, 2, 2, 2]
lc1 = Lightcurve(self.times, self.counts, err_dist="poisson")
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=UserWarning)
lc2 = Lightcurve(_times, _counts, err_dist="gauss")
lc3 = lc1.join(lc2)
assert np.allclose(lc3.counts_err[:len(self.times)], lc1.counts_err)
assert np.allclose(lc3.counts_err[len(self.times):],
np.zeros_like(lc2.counts))
def test_join_with_different_mjdref(self):
shift = 86400. # day
lc1 = Lightcurve(self.times + shift,
self.counts,
gti=self.gti + shift,
mjdref=57000)
lc2 = Lightcurve(self.times, self.counts, gti=self.gti, mjdref=57001)
with warnings.catch_warnings(record=True) as w:
newlc = lc1.join(lc2)
# The join operation *averages* the overlapping arrays
assert np.allclose(newlc.counts, lc1.counts)
assert np.any([
"MJDref is different in the two light curves"
in str(wi.message) for wi in w
])
assert np.any([
"The two light curves have overlapping time ranges"
in str(wi.message) for wi in w
])
def test_join_with_different_mjdref(self):
lc1 = Lightcurve(self.times, self.counts, gti=self.gti, mjdref=57000)
lc2 = Lightcurve(self.times, self.counts, gti=self.gti, mjdref=57001)
with pytest.raises(ValueError):
lc1.join(lc2)
def test_join_with_different_mjdref(self):
lc1 = Lightcurve(self.times, self.counts, gti=self.gti, mjdref=57000)
lc2 = Lightcurve(self.times, self.counts, gti=self.gti, mjdref=57001)
with pytest.raises(ValueError):
lc1.join(lc2)
