tslearn.utils.from_tsfresh_dataset¶
- tslearn.utils.from_tsfresh_dataset(X)[source]¶
Transform a tsfresh-compatible dataset into a tslearn dataset.
- Parameters:
- X: pandas data-frame
tsfresh-formatted dataset (“flat” data frame, as described there)
- Returns:
- array, shape=(n_ts, sz, d)
tslearn-formatted dataset. Column order is kept the same as in the original data frame.
Notes
Conversion from/to tsfresh format requires pandas to be installed.
Examples
>>> import pandas as pd >>> tsfresh_df = pd.DataFrame(columns=["id", "time", "a", "b"]) >>> tsfresh_df["id"] = [0, 0, 0] >>> tsfresh_df["time"] = [0, 1, 2] >>> tsfresh_df["a"] = [-1, 4, 7] >>> tsfresh_df["b"] = [8, -3, 2] >>> tslearn_arr = from_tsfresh_dataset(tsfresh_df) >>> tslearn_arr.shape (1, 3, 2) >>> tsfresh_df = pd.DataFrame(columns=["id", "time", "a"]) >>> tsfresh_df["id"] = [0, 0, 0, 1, 1] >>> tsfresh_df["time"] = [0, 1, 2, 0, 1] >>> tsfresh_df["a"] = [-1, 4, 7, 9, 1] >>> tslearn_arr = from_tsfresh_dataset(tsfresh_df) >>> tslearn_arr.shape (2, 3, 1) >>> tsfresh_df = numpy.random.randn(10, 1, 16) >>> from_tsfresh_dataset( ... tsfresh_df ... ) Traceback (most recent call last): ... ValueError: X is not a valid input tsfresh array.