diff --git a/lppls/lppls.py b/lppls/lppls.py index e62b00e..4287115 100644 --- a/lppls/lppls.py +++ b/lppls/lppls.py @@ -146,9 +146,9 @@ def fit(self, max_searches, minimizer="Nelder-Mead", obs=None): # Increment search count on SVD convergence error, but raise all other exceptions. try: tc, m, w, a, b, c, c1, c2 = self.estimate_params(obs, seed, minimizer) - O = self.get_oscillations(w, tc, t1, t2) - D = self.get_damping(m, w, b, c) - return tc, m, w, a, b, c, c1, c2, O, D + # O = self.get_oscillations(w, tc, t1, t2) + # D = self.get_damping(m, w, b, c) + return tc, m, w, a, b, c, c1, c2, #O, D except Exception as e: # print(e) search_count += 1 @@ -270,8 +270,8 @@ def compute_indicators(self, res, filter_conditions_config=None): w = fits["w"] b = fits["b"] c = fits["c"] - O = fits["O"] - D = fits["D"] + # O = fits["O"] + # D = fits["D"] # t_delta = t2 - t1 # pct_delta_min = t_delta * 0.5 @@ -485,7 +485,7 @@ def compute_nested_fits( i_idx += 1 for j in range(0, window_delta, inner_increment): obs_shrinking_slice = obs[:, j:window_size] - tc, m, w, a, b, c, c1, c2, O, D = self.fit( + tc, m, w, a, b, c, c1, c2 = self.fit( max_searches, obs=obs_shrinking_slice ) res[i_idx - 1].append([]) diff --git a/setup.py b/setup.py index 79114fe..e077d5c 100644 --- a/setup.py +++ b/setup.py @@ -4,7 +4,7 @@ long_description = fh.read() setuptools.setup(name='lppls', - version='0.6.16', + version='0.6.17', description='A Python module for fitting the LPPLS model to data.', packages=['lppls'], author='Josh Nielsen',