code: def test_some_correct(self):
      y_true = [-1, -1, -1, -1, 1, 1, 1]
      y_pred = [-1, 1, 1, -1, -1, 1, -1]
  
      result = metrics.false_positive_rate(y_true, y_pred)
      assert result == 0.5
      result = metrics.false_positive_rate(y_true, y_pred, pos_label=1)
      assert result == 0.5
      result = metrics.false_positive_rate(y_true, y_pred, pos_label=-1)
      assert result == pytest.approx(0.6666667)
  
imports: import numpy
  import pytest
  import sklearn.metrics
  import fairlearn.metrics
  from fairlearn.metrics._base_metrics import _get_labels_for_confusion_matrix
label_desc: Use image node_id 3 for calling the TestFPR obj's underlying member method code with example usage: obj.test_some_correct() without return types