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Update tstart and tseg when using Lightcurve.truncate() #753

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Sep 6, 2023
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Update tstart and tseg when using Lightcurve.truncate() #753

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a6ab26d
Update tstart and tseg when truncating the lc
matteobachetti Sep 1, 2023
7f9ac55
Add changelog
matteobachetti Sep 1, 2023
c3790bc
Setup tests to verify correct update of meancounts and many other att…
matteobachetti Sep 6, 2023
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1 change: 1 addition & 0 deletions docs/changes/753.bugfix.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
Update tstart and tseg when using Lightcurve.truncate()
7 changes: 5 additions & 2 deletions stingray/lightcurve.py
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Expand Up @@ -1243,9 +1243,12 @@ def truncate(self, start=0, stop=None, method="index"):
raise ValueError("Unknown method type " + method + ".")

if method.lower() == "index":
return self._truncate_by_index(start, stop)
new_lc = self._truncate_by_index(start, stop)
else:
return self._truncate_by_time(start, stop)
new_lc = self._truncate_by_time(start, stop)
new_lc.tstart = new_lc.gti[0, 0]
new_lc.tseg = new_lc.gti[-1, 1] - new_lc.gti[0, 0]
return new_lc

def _truncate_by_index(self, start, stop):
"""Private method for truncation using index values."""
Expand Down
66 changes: 47 additions & 19 deletions stingray/tests/test_lightcurve.py
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Expand Up @@ -308,8 +308,8 @@ class TestLightcurve(object):
@classmethod
def setup_class(cls):
cls.times = np.array([1, 2, 3, 4])
cls.counts = np.array([2, 2, 2, 2])
cls.counts_err = np.array([0.2, 0.2, 0.2, 0.2])
cls.counts = np.array([2, 4, 6, 8])
cls.counts_err = np.array([0.2, 0.4, 0.6, 0.8])
cls.bg_counts = np.array([1, 0, 0, 1])
cls.bg_ratio = np.array([1, 1, 0.5, 1])
cls.frac_exp = np.array([1, 1, 1, 1])
Expand Down Expand Up @@ -632,7 +632,7 @@ def test_subtraction(self):

lc = lc2 - lc1

expected_counts = np.array([1, 2, 3, 4])
expected_counts = np.array([1, 0, -1, -2])
assert np.allclose(lc.counts, expected_counts)
assert lc1.mjdref == lc.mjdref

Expand All @@ -658,7 +658,9 @@ def test_indexing_with_unexpected_type(self):
def test_indexing(self):
lc = Lightcurve(self.times, self.counts)

assert lc[0] == lc[1] == lc[2] == lc[3] == 2
assert lc[0] == 2
assert lc[1] == 4
assert lc[3] == 8

def test_slicing(self):
lc = Lightcurve(
Expand All @@ -669,20 +671,20 @@ def test_slicing(self):
err=self.counts / 10,
err_dist="gauss",
)
assert np.allclose(lc[1:3].counts, np.array([2, 2]))
assert np.allclose(lc[:2].counts, np.array([2, 2]))
assert np.allclose(lc[1:3].counts, np.array([4, 6]))
assert np.allclose(lc[:2].counts, np.array([2, 4]))
assert np.allclose(lc[:2].gti, [[0.5, 2.5]])
assert np.allclose(lc[2:].counts, np.array([2, 2]))
assert np.allclose(lc[2:].counts, np.array([6, 8]))
assert np.allclose(lc[2:].gti, [[2.5, 4.5]])
assert np.allclose(lc[:].counts, np.array([2, 2, 2, 2]))
assert np.allclose(lc[:].counts, np.array([2, 4, 6, 8]))
assert np.allclose(lc[::2].gti, [[0.5, 1.5], [2.5, 3.5]])
assert np.allclose(lc[:].gti, lc.gti)
assert lc[:].mjdref == lc.mjdref
assert lc[::2].n == 2
assert np.allclose(lc[1:3].counts_err, np.array([2, 2]) / 10)
assert np.allclose(lc[:2].counts_err, np.array([2, 2]) / 10)
assert np.allclose(lc[2:].counts_err, np.array([2, 2]) / 10)
assert np.allclose(lc[:].counts_err, np.array([2, 2, 2, 2]) / 10)
assert np.allclose(lc[1:3].counts_err, np.array([0.4, 0.6]))
assert np.allclose(lc[:2].counts_err, np.array([0.2, 0.4]))
assert np.allclose(lc[2:].counts_err, np.array([0.6, 0.8]))
assert np.allclose(lc[:].counts_err, np.array([0.2, 0.4, 0.6, 0.8]))
assert lc[:].err_dist == lc.err_dist

def test_index(self):
Expand Down Expand Up @@ -751,7 +753,8 @@ def test_join_disjoint_time_arrays(self):
lc = lc1.join(lc2)

assert len(lc.counts) == len(lc.time) == 8
assert np.allclose(lc.counts, 2)
assert np.allclose(lc.counts[4:], 2)
assert np.allclose(lc.counts[:4], self.counts)
assert lc.mjdref == lc1.mjdref

def test_join_overlapping_time_arrays(self):
Expand All @@ -765,7 +768,7 @@ def test_join_overlapping_time_arrays(self):
lc = lc1.join(lc2)

assert len(lc.counts) == len(lc.time) == 6
assert np.allclose(lc.counts, np.array([2, 2, 3, 3, 4, 4]))
assert np.allclose(lc.counts, np.array([2, 4, 5, 6, 4, 4]))

def test_join_different_err_dist_disjoint_times(self):
_times = [5, 6, 7, 8]
Expand Down Expand Up @@ -808,21 +811,30 @@ def test_truncate_by_index(self):

lc1 = lc.truncate(start=1)
assert np.allclose(lc1.time, np.array([2, 3, 4]))
assert np.allclose(lc1.counts, np.array([2, 2, 2]))
assert np.allclose(lc1.counts, np.array([4, 6, 8]))
assert np.allclose(lc1.countrate, np.array([4, 6, 8]))
assert np.allclose(lc1.bg_counts, np.array([0, 0, 1]))
assert np.allclose(lc1.bg_ratio, np.array([1, 0.5, 1]))
assert np.allclose(lc1.frac_exp, np.array([1, 1, 1]))
np.testing.assert_almost_equal(lc1.gti[0][0], 1.5)
assert lc1.mjdref == lc.mjdref
assert lc1.tstart == 1.5
assert lc1.tseg == 3
assert lc1.n == 3

lc2 = lc.truncate(stop=2)
assert np.allclose(lc2.time, np.array([1, 2]))
assert np.allclose(lc2.counts, np.array([2, 2]))
assert np.allclose(lc2.counts, np.array([2, 4]))
assert np.allclose(lc2.countrate, np.array([2, 4]))
assert np.allclose(lc2.bg_counts, np.array([1, 0]))
assert np.allclose(lc2.bg_ratio, np.array([1, 1]))
assert np.allclose(lc2.frac_exp, np.array([1, 1]))
np.testing.assert_almost_equal(lc2.gti[-1][-1], 2.5)
assert lc2.mjdref == lc.mjdref
assert lc2.n == 2

assert lc2.tstart == lc.tstart
assert lc2.tseg == 2

def test_truncate_by_time_stop_less_than_start(self):
lc = Lightcurve(self.times, self.counts)
Expand All @@ -836,19 +848,35 @@ def test_truncate_fails_with_incorrect_method(self):
lc1 = lc.truncate(start=1, method="wrong")

def test_truncate_by_time(self):
lc = Lightcurve(self.times, self.counts, gti=self.gti)
lc = Lightcurve(self.times, self.counts, err=self.counts_err, gti=self.gti)
# make sure they are initialized
lc.meancounts, lc.meanrate, lc.n

lc1 = lc.truncate(start=1, method="time")
assert np.allclose(lc1.time, np.array([1, 2, 3, 4]))
assert np.allclose(lc1.counts, np.array([2, 2, 2, 2]))
assert np.allclose(lc1.counts, np.array([2, 4, 6, 8]))
assert np.allclose(lc1.counts_err, np.array([0.2, 0.4, 0.6, 0.8]))
assert np.allclose(lc1.countrate, np.array([2, 4, 6, 8]))
np.testing.assert_almost_equal(lc1.gti[0][0], 0.5)
assert lc1.mjdref == lc.mjdref
assert lc1.tstart == 0.5
assert lc1.tseg == 4.0
assert lc1.meancounts == 5
assert lc1.meanrate == 5
assert lc1.n == 4

lc2 = lc.truncate(stop=3, method="time")
assert np.allclose(lc2.time, np.array([1, 2]))
assert np.allclose(lc2.counts, np.array([2, 2]))
assert np.allclose(lc2.counts, np.array([2, 4]))
assert np.allclose(lc2.counts_err, np.array([0.2, 0.4]))
assert np.allclose(lc2.countrate, np.array([2, 4]))
np.testing.assert_almost_equal(lc2.gti[-1][-1], 2.5)
assert lc2.mjdref == lc.mjdref
assert lc2.tstart == 0.5
assert lc2.tseg == 2
assert lc2.meancounts == 3
assert lc2.meanrate == 3
assert lc2.n == 2

def test_split_with_two_segments(self):
test_time = np.array([1, 2, 3, 6, 7, 8])
Expand Down