pyPPPETM.py 文件源码

def __init__(self, cnn=None, NetworkCode=None, StationCode=None, t=None):

        if t is None:
            ppp_soln = PPP_soln(cnn, NetworkCode, StationCode)
            t = ppp_soln.t

        # wrap around the solutions
        wt = np.sort(np.unique(t - np.fix(t)))

        # analyze the gaps in the data
        dt = np.diff(wt)

        # max dt (internal)
        dtmax = np.max(dt)

        # dt wrapped around
        dt_interyr = 1 - wt[-1] + wt[0]

        if dt_interyr > dtmax:
            dtmax = dt_interyr

        # save the value of the max wrapped delta time
        self.dt_max = dtmax

        # if dtmax < 3 months (90 days = 0.1232), then we can fit the annual
        # if dtmax < 1.5 months (45 days = 0.24657), then we can fit the semi-annual too

        if dtmax <= 0.1232:
            # all components (annual and semi-annual)
            self.A = np.array([sin(2 * pi * t), cos(2 * pi * t), sin(4 * pi * t), cos(4 * pi * t)]).transpose()
            self.frequencies = 2

        elif dtmax <= 0.2465:
            # only annual
            self.A = np.array([sin(2 * pi * t), cos(2 * pi * t)]).transpose()
            self.frequencies = 1

        else:
            # no periodic terms
            self.A = np.array([])
            self.frequencies = 0

        # variables to store the periodic amplitudes
        self.sin = np.array([])
        self.cos = np.array([])

        self.params = self.frequencies * 2