A tool that can help you augment your time series data customly.
We strongly recommend the usage of Anaconda for managing your python environments. Clone repo and install requirements.txt in a Python>=3.8.0 environment, including PyQt5==5.15.6. This set-up was tested under Windows 10 and Ubuntu 20.04.
$ conda create --name augment_tool python=3.8 # virtual env
$ conda activate augment_tool
$ git clone https://github.com/peijichen0324/data-augmentation-for-time-series-data # clone
$ cd data-augmentation-for-time-series-data/
$ pip install -r requirements.txt # install
Select channel
: Selects the channel you want to import (up to 6 channels).Select File
: Selects the data file.Select Folder
: Selects a data folder.Processing and Save
: Processes data augmentation and save in same folder.Progress Bar
: Displays the percentage of data augmentation processes that have completed.
Raw data Plot
: Displays the raw data.Augmentated data Plot
: Displays the augmentated data.
Jittering
: a way of simulating additive sensor noiseScaling
: changes the magnitude of the data in a window by multiplying by a random scalarPermulation
: randomly perturb the temporal location of within-window events.MagnitudeWarping
: changes the magnitude of each sample by convolving the data window with a smooth curve varying around one.TimeWarping
: another way to perturb the temporal location.RandomSampling
: random resampling the signal.RandomCutout
: random cut off some parts of the signal.