sliding_window.py

from collections import Counter
import numpy as np


class SlidingWindow:
    def __init__(self, window_size, overlap_rate=0.5):
        self.window_size = window_size
        assert 0.0 < overlap_rate and overlap_rate <= 1.0
        self.overlap_rate = overlap_rate
        self.overlap = int(window_size * overlap_rate)
  
    def transform(self, x):
        seq_len = x.shape[0]
        assert seq_len > self.window_size
        data = [x[i:i+self.window_size] for i in range(0, seq_len-self.window_size, self.overlap)]

        data = np.stack(data, 0)
        return data
  
    def clean(self, labels):
        tmp = []
        for l in labels:
            window_size = len(l)
            c = Counter(l)
            common = c.most_common()
            values = list(c.values())
            
            if common[0][0] == 0 and values[0] == window_size // 2:
                label = common[1][0]
            else:
                label = common[0][0]

            tmp.append(label)

        return np.array(tmp)

    def __call__(self, x, y):
        data = self.transform(x)
        label = self.transform(y)
        label = self.clean(label)
        return data, label