code: def test_prediction_is_too_low(self):
      saliency_map = np.random.random(
          size=(self.img.shape[0], self.img.shape[1])
      )
      mask = pic.generate_random_mask(
          image_height=self.img.shape[0],
          image_width=self.img.shape[1],
          fraction=0.1,
      )
      with self.assertRaisesRegex(
          pic.ComputePicMetricError, "min_pred_value"
      ):
          pic.compute_pic_metric(
              img=self.img,
              saliency_map=saliency_map,
              random_mask=mask,
              pred_func=lambda _: [0.9],
              saliency_thresholds=[0.1, 0.2],
              min_pred_value=0.95,
          )
  
file_path: saliency/saliency/metrics/pic_test.py
imports: import numpy
  import os
  import unittest
  from .None import pic
  from pathlib import Path
  from PIL import Image
label_desc: Use image node_id 11 for calling the PicTest obj's underlying member method code with example usage: obj.test_prediction_is_too_low() without return types