44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
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import numpy as np
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class CandidateEventsTS:
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def __init__(self, data, current_time, Mc, time_win, space_win=None):
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assert time_win > 0, f"Time windows is {time_win}, which should be a positive number"
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self.data = data
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self.current_time = current_time
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self.Mc = Mc
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self.time_win = time_win
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self.space_win = space_win
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def filter_by_time(self):
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indx = np.where((self.data[:, 4] > (self.current_time - self.time_win)) & (self.data[:, 4] <= self.current_time))[0]
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if len(indx) > 0:
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self.data = self.data[indx, :]
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else:
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self.data = []
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def filter_by_magnitude(self):
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if self.Mc:
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indx = np.where(self.data[:, 5] > self.Mc)[0]
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if len(indx) > 0:
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self.data = self.data[indx, :]
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else:
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self.data = []
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def filter_by_space(self):
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dist = np.sqrt(np.sum((self.data[:, 1:4] - self.data[-1, 1:4]) ** 2, axis=1))
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indx = np.where(dist < self.space_win)[0]
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if len(indx) > 0:
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self.data = self.data[indx, :]
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else:
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self.data = []
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def filter_data(self):
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self.filter_by_time()
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if len(self.data) > 0:
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self.filter_by_magnitude()
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if len(self.data) > 0 and self.space_win:
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self.filter_by_space()
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return self.data
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