<｜begin▁of▁sentence｜>### Instruction:
{'description': 'Suppose a researcher has applied two different clustering algorithms to the same dataset, resulting in two different label assignments for each sample in the data. The researcher wants to compare the clustering outputs by aligning one set of labels with the other. Assuming there are six samples and the true labels for these samples are given by y_true, while the predicted labels from the new clustering are denoted by y_pred, how can the researcher remap the y_pred labels to best match the y_true labels for a straightforward comparison?', 'data': {'y_true': 'A NumPy array (or array-like) of true labels, representing the clustering defined by the first algorithm: array([0, 0, 1, 1, 2, 2]).', 'y_pred': 'A NumPy array (or array-like) of predicted labels from the second clustering algorithm that needs to be remapped: array([2, 2, 1, 1, 0, 0]).'}, 'problem': 'The researcher seeks a way to remap the predicted labels (y_pred) such that they align as closely as possible with the true labels (y_true), and to obtain the mapping that describes the label changes.'}
### Response:
import numpy as np
from graspologic.utils import remap_labels

y_true = np.array([0,0,1,1,2,2])
y_pred = np.array([2,2,1,1,0,0])
remapped_y_pred, label_map = remap_labels(y_true, y_pred, return_map=True)
print('Remapped y_pred:', remapped_y_pred)
print('Label map:', label_map)
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