demo.py

import numpy as np
from pandas import DataFrame

import dataframesegmenter as dfs

if __name__ == '__main__':
    # Generate sample data
    n_values = 1000
    n_classes = 4
    columns = "A,B,C,D".split(",")
    data = np.cumsum(np.random.normal(0, .1, (n_values, len(columns))), 0)
    data = DataFrame(data,
                     index=np.linspace(0, 5, n_values), columns=columns)
    # Now data is correct, generate class for each sample
    classes = np.array(["Class %i" % i for i in range(n_classes)])[np.linspace(0, n_classes - 1, n_values).astype(int)]
    data["class"] = classes

    # Run the UI
    s = dfs.Segmenter(data)
    res = s.run()

    # Run the UI in plot mode
    s = dfs.Segmenter(data, plot_method=dfs.Segmenter.PlotMethod.PLOT, lw=.5)
    res = s.run()

    # The result is the same dataframe as input, but with classes updated
    print(res)