code: def perror_to_bounded_log10_perror(
      perror, min_prob=1.0 - _MAX_CONFIDENCE
  ):
      """Computes log10(p) for the given probability.
  
      The log10 probability is capped by -_MAX_CONFIDENCE.
  
      Args:
        perror: float. The probability to log10.
        min_prob: float. The minimum allowed probability.
  
      Returns:
        log10(p).
  
      Raises:
        ValueError: If probability is outside of [0.0, 1.0].
      """
      if not 0 <= perror <= 1:
          raise ValueError(
              "perror must be between zero and one: {}".format(perror)
          )
      return perror_to_log10_perror(max(perror, min_prob))
  
file_path: deepvariant/third_party/nucleus/util/genomics_math.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import numpy
  from third_party.nucleus.util.python import math
label_desc: Use image node_id 1 for calling a global function with example usage: perror_to_bounded_log10_perror(perror, min_prob) and returns: perror_to_log10_perror