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])