pyts.datasets.load_pig_central_venous_pressure

pyts.datasets.load_pig_central_venous_pressure(return_X_y=False)[source]

Load and return the PigCVP dataset.

In the test set, a class is represented by four examples, the second and third 2000 data points of the before time series and the second and third 2000 data points of the after time series. Data created by Mathieu Guillame-Bert et al. Data edited by Shaghayegh Gharghabi and Eamonn Keogh.

Training samples 104
Test samples 208
Timestamps 2000
Classes 52
Parameters:
return_X_y : bool (default = False)

If True, return (data_train, data_test, target_train, target_test) instead of a Bunch object.
Returns:
data : Bunch

Dictionary-like object, with attributes:

data_train : array of floats

The time series in the training set.

data_test : array of floats

The time series in the test set.

target_train : array of integers

The classification labels in the training set.

target_test : array of integers

The classification labels in the test set.

DESCR : str

The full description of the dataset.

url : str

The url of the dataset.

(data_train, data_test, target_train, target_test) : tuple if return_X_y is True

References

[1]M. Guillame-Bert and A. Dubrawski, “Classification of Time Sequences using Graphs of Temporal Constraints”. Journal of Machine Learning Research, 2017.
[2]UCR archive entry for the PigCVP dataset

Examples

>>> from pyts.datasets import load_pig_central_venous_pressure
>>> bunch = load_pig_central_venous_pressure()
>>> bunch.data_train.shape
(104, 2000)
>>> X_train, X_test, y_train, y_test = load_pig_central_venous_pressure(
...    return_X_y=True)
>>> X_train.shape
(104, 2000)