def test_loadtarget(self):
data = "1 2\n3 4\n5 6"
fp = six.StringIO(data)
times_values = pytff.loadtarget(fp)
for lidx, line in enumerate(data.splitlines()):
for cidx, value in enumerate(line.split()):
fvalue = float(value)
pytff_value = times_values[cidx][0][lidx]
np.testing.assert_allclose(fvalue, pytff_value)
def test_split_data(self):
ogle_0_path = datasets.get("split_dat", "ogle_0.dat")
ogle_1_path = datasets.get("split_dat", "ogle_1.dat")
ogle_tff_path = datasets.get("split_dat", "tff.dat")
ogle_dff_path = datasets.get("split_dat", "dff.dat")
ogle_mch_path = datasets.get("split_dat", "match.dat")
ogle_tff = pytff.load_tff_dat(ogle_tff_path, self.tff.process_tff)
ogle_dff = pytff.load_tff_dat(ogle_dff_path, self.tff.process_dff)
ogle_mch = pytff.load_match_dat(ogle_mch_path, self.tff.process_matchs)
times_0, values_0 = pytff.loadtarget(ogle_0_path)
times_1, values_1 = pytff.loadtarget(ogle_1_path)
times, values = pytff.stack_targets(
(times_0, times_1), (values_0, values_1))
periods = np.array([0.6347522] * 2)
tff_data, dff_data, mch_data = self.tff.analyze(periods, times, values)
np.testing.assert_array_equal(tff_data, ogle_tff)
np.testing.assert_array_equal(dff_data, ogle_dff)
np.testing.assert_array_equal(mch_data, ogle_mch)
def test_single_data(self):
ogle_path = datasets.get("single_dat", "ogle.dat")
ogle_tff_path = datasets.get("single_dat", "tff.dat")
ogle_dff_path = datasets.get("single_dat", "dff.dat")
ogle_mch_path = datasets.get("single_dat", "match.dat")
ogle_tff = pytff.load_tff_dat(ogle_tff_path, self.tff.process_tff)
ogle_dff = pytff.load_tff_dat(ogle_dff_path, self.tff.process_dff)
ogle_mch = pytff.load_match_dat(ogle_mch_path, self.tff.process_matchs)
times, values = pytff.loadtarget(ogle_path)
periods = np.array([0.6347522])
tff_data, dff_data, mch_data = self.tff.analyze(periods, times, values)
np.testing.assert_array_equal(tff_data, ogle_tff)
np.testing.assert_array_equal(dff_data, ogle_dff)
np.testing.assert_array_equal(mch_data, ogle_mch)
def test_big_period(self):
bp_path = datasets.get("big_period", "star.dat")
bp_tff_path = datasets.get("big_period", "tff.dat")
bp_dff_path = datasets.get("big_period", "dff.dat")
bp_mch_path = datasets.get("big_period", "match.dat")
bp_tff = pytff.load_tff_dat(bp_tff_path, self.tff.process_tff)
bp_dff = pytff.load_tff_dat(bp_dff_path, self.tff.process_dff)
bp_mch = pytff.load_match_dat(bp_mch_path, self.tff.process_matchs)
times, values = pytff.loadtarget(bp_path)
periods = np.array([153.798519147])
tff_data, dff_data, mch_data = self.tff.analyze(periods, times, values)
for name in bp_tff.dtype.names:
np.testing.assert_array_equal(tff_data[name], bp_tff[name])
for name in bp_dff.dtype.names:
np.testing.assert_array_equal(dff_data[name], bp_dff[name])
for name in bp_mch.dtype.names:
np.testing.assert_array_equal(mch_data[name], bp_mch[name])
