import numpy as np

class CandidateEventsTS:
    def __init__(self, data, current_time, Mc, time_win, space_win=None):
        assert time_win > 0, f"Time windows is {time_win}, which should be a positive number"

        self.data = data
        self.current_time = current_time
        self.Mc = Mc
        self.time_win = time_win
        self.space_win = space_win

    def filter_by_time(self):
        indx = np.where((self.data[:, 4] > (self.current_time - self.time_win)) & (self.data[:, 4] <= self.current_time))[0]
        if len(indx) > 0:
            self.data = self.data[indx, :]
        else:
            self.data = []

    def filter_by_magnitude(self):
        if self.Mc:
            indx = np.where(self.data[:, 5] > self.Mc)[0]
            if len(indx) > 0:
                self.data = self.data[indx, :]
            else:
                self.data = []

    def filter_by_space(self):
        dist = np.sqrt(np.sum((self.data[:, 1:4] - self.data[-1, 1:4]) ** 2, axis=1))
        indx = np.where(dist < self.space_win)[0]
        if len(indx) > 0:
            self.data = self.data[indx, :]
        else:
            self.data = []

    def filter_data(self):
        self.filter_by_time()
        if len(self.data) > 0:
            self.filter_by_magnitude()
            if len(self.data) > 0 and self.space_win:
                self.filter_by_space()

        return self.data