std::vector Schema::UpdateWeightedFeature()

in tensorflow_data_validation/anomalies/schema.cc [1218:1261]
43 lines of code
13 McCabe index (conditional complexity)

std::vector<Description> Schema::UpdateWeightedFeature(
    const FeatureStatsView& view, WeightedFeature* weighted_feature) {
  std::vector<Description> descriptions;
  int min_weight_length_diff = 0;
  int max_weight_length_diff = 0;
  for (const tensorflow::metadata::v0::CustomStatistic& custom_stat :
       view.custom_stats()) {
    const string& stat_name = custom_stat.name();
    // Stat names should be in-sync with the weighted_feature_stats_generator.
    if (stat_name == kMissingWeightedValue && custom_stat.num() != 0) {
      descriptions.push_back(
          {tensorflow::metadata::v0::AnomalyInfo::
               WEIGHTED_FEATURE_MISSING_VALUE,
           "Missing value feature",
           absl::StrCat("Found ", custom_stat.num(),
                        " examples missing value feature.")});
    } else if (stat_name == kMissingWeight && custom_stat.num() != 0) {
      descriptions.push_back(
          {tensorflow::metadata::v0::AnomalyInfo::
               WEIGHTED_FEATURE_MISSING_WEIGHT,
           "Missing weight feature",
           absl::StrCat("Found ", custom_stat.num(),
                        " examples missing weight feature.")});
    } else if (stat_name == kMinWeightLengthDiff && custom_stat.num() != 0) {
      min_weight_length_diff = custom_stat.num();
    } else if (stat_name == kMaxWeightLengthDiff && custom_stat.num() != 0) {
      max_weight_length_diff = custom_stat.num();
    }
  }
  if (min_weight_length_diff != 0 || max_weight_length_diff != 0) {
    descriptions.push_back(
        {tensorflow::metadata::v0::AnomalyInfo::
             WEIGHTED_FEATURE_LENGTH_MISMATCH,
         "Length mismatch between value and weight feature",
         absl::StrCat("Mismatch between weight and value feature with ",
                      kMinWeightLengthDiff, " = ", min_weight_length_diff,
                      " and ", kMaxWeightLengthDiff, " = ",
                      max_weight_length_diff, ".")});
  }
  if (!descriptions.empty()) {
    ::tensorflow::data_validation::DeprecateWeightedFeature(weighted_feature);
  }
  return descriptions;
}