diff --git a/lppls/lppls.py b/lppls/lppls.py index 54e7c63..186c471 100644 --- a/lppls/lppls.py +++ b/lppls/lppls.py @@ -27,7 +27,8 @@ def __init__(self, observations): @staticmethod @njit def lppls(t, tc, m, w, a, b, c1, c2): - return a + np.power(tc - t, m) * (b + ((c1 * np.cos(w * np.log(tc - t))) + (c2 * np.sin(w * np.log(tc - t))))) + dt = np.abs(tc - t) + 1e-8 + return a + np.power(dt, m) * (b + ((c1 * np.cos(w * np.log(dt))) + (c2 * np.sin(w * np.log(dt))))) def func_restricted(self, x, *args): """ @@ -49,7 +50,7 @@ def func_restricted(self, x, *args): # print('type', type(res)) # print('func_restricted', res) - delta = [self.lppls(t, tc, m, w, a, b, c1, c2) for t in observations[0, :]] + delta = self.lppls(observations[0, :], tc, m, w, a, b, c1, c2) delta = np.subtract(delta, observations[1, :]) delta = np.power(delta, 2) return np.sum(delta) @@ -64,8 +65,7 @@ def matrix_equation(observations, tc, m, w): P = observations[1] N = len(T) - # @TODO make taking tc - t or |tc - t| configurable - dT = np.abs(tc - T) + dT = np.abs(tc - T) + 1e-8 phase = np.log(dT) fi = np.power(dT, m) @@ -99,6 +99,8 @@ def matrix_equation(observations, tc, m, w): [np.sum(yihi)] ]) + matrix_1 += 1e-8 * np.eye(matrix_1.shape[0]) + return np.linalg.solve(matrix_1, matrix_2) def fit(self, max_searches, minimizer='Nelder-Mead', obs=None): diff --git a/setup.py b/setup.py index 039e4fd..9706ee0 100644 --- a/setup.py +++ b/setup.py @@ -4,7 +4,7 @@ long_description = fh.read() setuptools.setup(name='lppls', - version='0.6.12', + version='0.6.13', description='A Python module for fitting the LPPLS model to data.', packages=['lppls'], author='Josh Nielsen',