Downsampling (downsample
)¶
Downsampling reduces the number of frames in an observation sequence according to a specified downsample factor and one of two methods: averaging and decimation.
This is an especially helpful preprocessing method for speeding up classification times.
For further information, please see the preprocessing tutorial notebook.
Example¶
1 2 3 4 5 6 7 8  import numpy as np
from sequentia.preprocessing import downsample
# Create some sample data
X = [np.random.random((10 * i, 3)) for i in range(1, 4)]
# Downsample the data with downsample factor 5 and decimation
X = downsample(X, n=5, method='decimate')

API reference¶

sequentia.preprocessing.
downsample
(X, n, method='decimate')[source]¶ Downsamples an observation sequence (or multiple sequences) by either:
 Decimating the next \(n1\) observations
 Averaging the current observation with the next \(n1\) observations
Parameters:  X: numpy.ndarray or List[numpy.ndarray]
An individual observation sequence or a list of multiple observation sequences.
 n: int
Downsample factor.
 method: {‘decimate’, ‘average’}
The downsampling method.
Returns:  downsampled: numpy.ndarray or List[numpy.ndarray]
The downsampled input observation sequence(s).