def test_LCurve_init(self):
"""Test initializaiton"""
t = np.arange(6)
lc = az.LCurve(t, t * 0.5, t * 0.01)
assert (lc.nt == len(t))
assert (lc.dt == 1.)
assert (lc.iseven)
lc = az.LCurve(t[[0, 2, 3, 4, 5]], t[1:], t[1:] * 0.01)
assert (not lc.iseven)
def test_rebin_lc__w_gaps(self):
# t: 0 1 2 3 4 5 6 7
# x: 0 1 2 3 4 5 6 7
# xe:1 2 3 4 5 6 7 8
# : * - * - - - - *
t = np.arange(8, dtype=np.double)
x = np.arange(8, dtype=np.double)
xe = np.arange(1, 9) * 1.
ind = np.array([0, 2, 7])
lc = az.LCurve(t[ind], x[ind], xe[ind], 1.0)
lc1 = lc.rebin(2, min_exp=0.5, error='poiss')
np.testing.assert_array_almost_equal(lc1.time,
np.array([0.5, 2.5, 6.5]))
np.testing.assert_array_almost_equal(lc1.rate, np.array([0., 2., 7]))
np.testing.assert_array_almost_equal(
lc1.rerr, (np.array([((2.**0.5) + (7**0.5)) / 2, (2.**0.5),
(7**0.5)])))
# when original lc is even #
lc = lc.make_even()
lc1 = lc.rebin(2, min_exp=0.0, error='poiss')
np.testing.assert_array_almost_equal(lc1.time,
np.array([0.5, 2.5, 4.5, 6.5]))
np.testing.assert_array_almost_equal(lc1.rate,
np.array([0., 2., np.nan, 7]))
def test_rebin_lc(self):
t = np.arange(8, dtype=np.double)
x = np.arange(8, dtype=np.double)
xe = np.arange(1, 9) * 1.
lc = az.LCurve(t, x, xe)
lc1 = lc.rebin(2, error='poiss')
np.testing.assert_array_almost_equal(lc1.time, np.arange(0.5, 8, 2))
np.testing.assert_array_almost_equal(lc1.rate, np.arange(0.5, 8, 2))
np.testing.assert_array_almost_equal(
lc1.rerr,
np.sqrt(np.arange(0.5, 8, 2) * 2) / 2.)
def read_pn_lc(obs, dt, enL, lcdir, data_dir, interp=False, suff='', **kwargs):
"""Read PN light curves
obs: a list of observation folders
dt: time bin
enL: a string of space-separated bin boundaries
lcdir: directory name indicating the bin type. e.g 8l for 8 bins in log space
data_dir: folder containing the obsids
interp: if true, interpolate small gaps
suff: extra suffix to lc name if needed. e.g. __s; default:''
kwargs for read_pn_lcurve
"""
do_raw = False
#if do_raw: suff = ''
enL = np.array(enL.split(), np.double)
en, ene = (enL[1:] + enL[:-1]) / 2, (enL[1:] - enL[:-1]) / 2
Lc = [[
az.LCurve.read_pn_lcurve(
'{}/{}/pn/lc/{}/lc_{:03g}__{}{}.fits'.format(
data_dir, o, lcdir, dt, ie + 1, suff), **kwargs) for o in obs
] for ie in range(len(en))]
if do_raw:
rLc = [[
az.LCurve.read_pn_lcurve(
'{}/{}/pn/lc/{}/lc_{:03g}__{}{}.fits'.format(
data_dir, o, lcdir, dt, ie + 1, '__s'), **kwargs)
for o in obs
] for ie in range(len(en))]
LC = []
for ie in range(len(Lc)):
LC.append([])
for io in range(len(Lc[0])):
lc, rlc = Lc[ie][io], rLc[ie][io]
tt = np.intersect1d(lc.time, rlc.time)
ii = np.in1d(lc.time, tt)
rii = np.in1d(rlc.time, tt)
lc_new = az.LCurve(tt, rlc.rate[rii], rlc.rerr[rii], rlc.dt,
lc.fexp[ii])
LC[-1].append(lc_new)
Lc = LC
Lc = [[ll.make_even() for ll in l] for l in Lc]
if interp:
for l in Lc:
for ll in l:
ll.interp_small_gaps(np.int(1e3 / dt), noise='norm', seed=345)
return Lc, en, ene
def test_interp_small_gaps_2(self):
# t: 0 1 2 3 4 5 6 7
# x: 0 1 2 3 4 5 6 7
# xe:1 2 3 4 5 6 7 8
# : * - * - - - - *
t = np.arange(8, dtype=np.double)
x = np.arange(8, dtype=np.double)
xe = np.arange(1, 9) * 1.
ind = np.array([0, 2, 7])
lc = az.LCurve(t[ind], x[ind], xe[ind], 1.0)
lc = lc.make_even()
# no noise, all gaps #
lc.interp_small_gaps(maxgap=20, noise=None)
np.testing.assert_array_almost_equal(lc.rate, [0, 1, 2, 3, 4, 5, 6, 7])
np.testing.assert_array_almost_equal(lc.rerr, [1, 4, 3, 4, 4, 4, 4, 8])
def test_make_even(self):
t = np.arange(8) * 1.
x = np.arange(8) * 1.
xe = np.arange(1, 9) * 1.
ind = np.arange(0, 8, 2)
ind[-1] = len(t) - 1
lc = az.LCurve(t[ind], x[ind], xe[ind], 1.0)
assert (not lc.iseven)
lc1 = lc.make_even()
assert (lc1.iseven)
np.testing.assert_array_equal(t, lc1.time)
np.testing.assert_array_almost_equal(x[ind],
lc1.rate[~np.isnan(lc1.rate)])
# time cannot be cast to even, fail #
lc.time[1] += 0.5
with self.assertRaises(ValueError):
lc.make_even()
def test_interp_small_gaps_5(self):
# t: 0 1 2 3 4 5 6 7
# x: 0 1 2 3 4 5 6 7
# xe:1 2 3 4 5 6 7 8
# : * - * - - - - *
t = np.arange(8, dtype=np.double)
x = np.arange(8, dtype=np.double)
xe = np.arange(1, 9) * 1.
ind = np.array([0, 2, 7])
lc = az.LCurve(t[ind], x[ind], xe[ind], 1.0)
lc = lc.make_even()
# norm #
lc.interp_small_gaps(maxgap=1, noise='norm', seed=123)
np.random.seed(123)
pp = np.random.randn(8)[1] * 4 + 1
np.testing.assert_array_almost_equal(lc.rate,
[0, pp, 2] + [np.nan] * 4 + [7])
np.testing.assert_array_almost_equal(lc.rerr,
[1, 4, 3] + [np.nan] * 4 + [8])
def test_interp_small_gaps_4(self):
# t: 0 1 2 3 4 5 6 7
# x: 0 1 2 3 4 5 6 7
# xe:1 2 3 4 5 6 7 8
# : * - * - - - * -
# gap at the end of lc #
t = np.arange(8, dtype=np.double)
x = np.arange(8, dtype=np.double)
xe = np.arange(1, 9) * 1.
ind = np.array([0, 2, 6, 7])
lc = az.LCurve(t[ind], x[ind], xe[ind], 1.0)
lc.rate[-1] = np.nan
lc.rerr[-1] = np.nan
lc = lc.make_even()
lc.interp_small_gaps(maxgap=1, noise=None)
np.testing.assert_array_almost_equal(lc.rate,
[0, 1, 2] + [np.nan] * 3 + [6, 6])
np.testing.assert_array_almost_equal(lc.rerr, [1, 11 / 3, 3] +
[np.nan] * 3 + [7, 11 / 3])
def test_interp_small_gaps_1(self):
# t: 0 1 2 3 4 5 6 7
# x: 0 1 2 3 4 5 6 7
# xe:1 2 3 4 5 6 7 8
# : * - * - - - - *
t = np.arange(8, dtype=np.double)
x = np.arange(8, dtype=np.double)
xe = np.arange(1, 9) * 1.
ind = np.array([0, 2, 7])
lc = az.LCurve(t[ind], x[ind], xe[ind], 1.0)
# not even #
with self.assertRaises(ValueError):
lc.interp_small_gaps(maxgap=1, noise=None)
# no noise, 1 gap #
lc = lc.make_even()
lc.interp_small_gaps(maxgap=1, noise=None)
np.testing.assert_array_almost_equal(lc.rate,
[0, 1, 2] + [np.nan] * 4 + [7])
np.testing.assert_array_almost_equal(lc.rerr,
[1, 4, 3] + [np.nan] * 4 + [8])