def test_data_to_delays_average(self):
fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info)
w = fcal.data_to_delays(average=True)
for (i, k), (l, m) in w.keys():
nt.assert_almost_equal(w[(i, k), (l, m)][0],
self.delays[i] - self.delays[k] -
self.delays[l] + self.delays[m],
places=16)
def test_run_average(self):
fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info)
sols = fcal.run(average=True)
solved_delays = []
for pair in fcal.info.bl_pairs:
ant_indexes = fcal.info.blpair2antind(pair)
dlys = fcal.xhat[ant_indexes]
solved_delays.append(dlys[0] - dlys[1] - dlys[2] + dlys[3])
solved_delays = np.array(solved_delays).flatten()
nt.assert_equal(
np.testing.assert_almost_equal(fcal.M.flatten(),
solved_delays,
decimal=16), None)
def test_get_M(self):
fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info)
nt.assert_equal(fcal.get_M().shape,
(len(self.info.bl_pairs), len(self.times)))
_M = np.array([
1 * (self.delays[i] * np.ones(len(self.times)) -
self.delays[k] * np.ones(len(self.times)) -
self.delays[l] * np.ones(len(self.times)) +
self.delays[m] * np.ones(len(self.times)))
for (i, k), (l, m) in self.info.bl_pairs
])
nt.assert_equal(
np.testing.assert_almost_equal(_M, fcal.get_M(), decimal=16), None)
def test_get_N(self):
fcal = firstcal.FirstCal(self.data, self.wgts, self.freqs, self.info)
# the only requirement on N is it's shape.
nt.assert_equal(
fcal.get_N(len(fcal.info.bl_pairs)).shape,
(len(fcal.info.bl_pairs), len(fcal.info.bl_pairs)))