verde.train_test_split¶

verde.train_test_split(coordinates, data, weights=None, **kwargs)[source]¶

Split a dataset into a training and a testing set for cross-validation.

Similar to sklearn.model_selection.train_test_split but is tuned to work on multi-component spatial data with optional weights.

Extra keyword arguments will be passed to sklearn.model_selection.ShuffleSplit, except for n_splits which is always 1.

Parameters:

coordinates : tuple of arrays: Arrays with the coordinates of each data point. Should be in the following order: (easting, northing, vertical, …).
data : array or tuple of arrays: the data values of each data point. If the data has more than one component, data must be a tuple of arrays (one for each component).
weights : none or array or tuple of arrays: if not none, then the weights assigned to each data point. If more than one data component is provided, you must provide a weights array for each data component (if not none).

Returns:

train, test : tuples: Each is a tuple = (coordinates, data, weights) generated by separating the input values randomly.

Examples

>>> import numpy as np
>>> # Split 2-component data with weights
>>> data = (np.array([1, 3, 5, 7]), np.array([0, 2, 4, 6]))
>>> coordinates = (np.arange(4), np.arange(-4, 0))
>>> weights = (np.array([1, 1, 2, 1]), np.array([1, 2, 1, 1]))
>>> train, test = train_test_split(coordinates, data, weights,
...                                random_state=0)
>>> print("Coordinates:", train[0], test[0], sep='\n  ')
Coordinates:
  (array([3, 1, 0]), array([-1, -3, -4]))
  (array([2]), array([-2]))
>>> print("Data:", train[1], test[1], sep='\n  ')
Data:
  (array([7, 3, 1]), array([6, 2, 0]))
  (array([5]), array([4]))
>>> print("Weights:", train[2], test[2], sep='\n  ')
Weights:
  (array([1, 1, 1]), array([1, 2, 1]))
  (array([2]), array([1]))
>>> # Split single component data without weights
>>> train, test = train_test_split(coordinates, data[0], None,
...                                random_state=0)
>>> print("Coordinates:", train[0], test[0], sep='\n  ')
Coordinates:
  (array([3, 1, 0]), array([-1, -3, -4]))
  (array([2]), array([-2]))
>>> print("Data:", train[1], test[1], sep='\n  ')
Data:
  (array([7, 3, 1]),)
  (array([5]),)
>>> print("Weights:", train[2], test[2], sep='\n  ')
Weights:
  (None,)
  (None,)