///////////////////////////////////////////////////////////////////////
// File:        blamer.cpp
// Description: Module allowing precise error causes to be allocated.
// Author:      Rike Antonova
// Refactored:  Ray Smith
// Created:     Mon Feb 04 14:37:01 PST 2013
//
// (C) Copyright 2013, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////

#include "blamer.h"
#include "blobs.h"
#include "matrix.h"
#include "normalis.h"
#include "pageres.h"

// Names for each value of IncorrectResultReason enum. Keep in sync.
const char kBlameCorrect[] = "corr";
const char kBlameClassifier[] = "cl";
const char kBlameChopper[] = "chop";
const char kBlameClassLMTradeoff[] = "cl/LM";
const char kBlamePageLayout[] = "pglt";
const char kBlameSegsearchHeur[] = "ss_heur";
const char kBlameSegsearchPP[] = "ss_pp";
const char kBlameClassOldLMTradeoff[] = "cl/old_LM";
const char kBlameAdaption[] = "adapt";
const char kBlameNoTruthSplit[] = "no_tr_spl";
const char kBlameNoTruth[] = "no_tr";
const char kBlameUnknown[] = "unkn";

const char * const kIncorrectResultReasonNames[] = {
    kBlameCorrect,
    kBlameClassifier,
    kBlameChopper,
    kBlameClassLMTradeoff,
    kBlamePageLayout,
    kBlameSegsearchHeur,
    kBlameSegsearchPP,
    kBlameClassOldLMTradeoff,
    kBlameAdaption,
    kBlameNoTruthSplit,
    kBlameNoTruth,
    kBlameUnknown
};

const char *BlamerBundle::IncorrectReasonName(IncorrectResultReason irr) {
  return kIncorrectResultReasonNames[irr];
}

const char *BlamerBundle::IncorrectReason() const {
  return kIncorrectResultReasonNames[incorrect_result_reason_];
}

// Functions to setup the blamer.
// Whole word string, whole word bounding box.
void BlamerBundle::SetWordTruth(const UNICHARSET& unicharset,
                                const char* truth_str, const TBOX& word_box) {
  truth_word_.InsertBox(0, word_box);
  truth_has_char_boxes_ = false;
  // Encode the string as UNICHAR_IDs.
  GenericVector<UNICHAR_ID> encoding;
  GenericVector<char> lengths;
  unicharset.encode_string(truth_str, false, &encoding, &lengths, NULL);
  int total_length = 0;
  for (int i = 0; i < encoding.size(); total_length += lengths[i++]) {
    STRING uch(truth_str + total_length);
    uch.truncate_at(lengths[i] - total_length);
    UNICHAR_ID id = encoding[i];
    if (id != INVALID_UNICHAR_ID) uch = unicharset.get_normed_unichar(id);
    truth_text_.push_back(uch);
  }
}

// Single "character" string, "character" bounding box.
// May be called multiple times to indicate the characters in a word.
void BlamerBundle::SetSymbolTruth(const UNICHARSET& unicharset,
                                  const char* char_str, const TBOX& char_box) {
  STRING symbol_str(char_str);
  UNICHAR_ID id = unicharset.unichar_to_id(char_str);
  if (id != INVALID_UNICHAR_ID) {
    STRING normed_uch(unicharset.get_normed_unichar(id));
    if (normed_uch.length() > 0) symbol_str = normed_uch;
  }
  int length = truth_word_.length();
  truth_text_.push_back(symbol_str);
  truth_word_.InsertBox(length, char_box);
  if (length == 0)
    truth_has_char_boxes_ = true;
  else if (truth_word_.BlobBox(length - 1) == char_box)
    truth_has_char_boxes_ = false;
}

// Marks that there is something wrong with the truth text, like it contains
// reject characters.
void BlamerBundle::SetRejectedTruth() {
  incorrect_result_reason_ = IRR_NO_TRUTH;
  truth_has_char_boxes_ = false;
}

// Returns true if the provided word_choice is correct.
bool BlamerBundle::ChoiceIsCorrect(const WERD_CHOICE* word_choice) const {
  if (word_choice == NULL) return false;
  const UNICHARSET* uni_set = word_choice->unicharset();
  STRING normed_choice_str;
  for (int i = 0; i < word_choice->length(); ++i) {
    normed_choice_str +=
        uni_set->get_normed_unichar(word_choice->unichar_id(i));
  }
  STRING truth_str = TruthString();
  return truth_str == normed_choice_str;
}

void BlamerBundle::FillDebugString(const STRING &msg,
                                   const WERD_CHOICE *choice,
                                   STRING *debug) {
  (*debug) += "Truth ";
  for (int i = 0; i < this->truth_text_.length(); ++i) {
    (*debug) += this->truth_text_[i];
  }
  if (!this->truth_has_char_boxes_) (*debug) += " (no char boxes)";
  if (choice != NULL) {
    (*debug) += " Choice ";
    STRING choice_str;
    choice->string_and_lengths(&choice_str, NULL);
    (*debug) += choice_str;
  }
  if (msg.length() > 0) {
    (*debug) += "\n";
    (*debug) += msg;
  }
  (*debug) += "\n";
}

// Sets up the norm_truth_word from truth_word using the given DENORM.
void BlamerBundle::SetupNormTruthWord(const DENORM& denorm) {
  // TODO(rays) Is this the last use of denorm in WERD_RES and can it go?
  norm_box_tolerance_ = kBlamerBoxTolerance * denorm.x_scale();
  TPOINT topleft;
  TPOINT botright;
  TPOINT norm_topleft;
  TPOINT norm_botright;
  for (int b = 0; b < truth_word_.length(); ++b) {
    const TBOX &box = truth_word_.BlobBox(b);
    topleft.x = box.left();
    topleft.y = box.top();
    botright.x = box.right();
    botright.y = box.bottom();
    denorm.NormTransform(NULL, topleft, &norm_topleft);
    denorm.NormTransform(NULL, botright, &norm_botright);
    TBOX norm_box(norm_topleft.x, norm_botright.y,
                  norm_botright.x, norm_topleft.y);
    norm_truth_word_.InsertBox(b, norm_box);
  }
}

// Splits *this into two pieces in bundle1 and bundle2 (preallocated, empty
// bundles) where the right edge/ of the left-hand word is word1_right,
// and the left edge of the right-hand word is word2_left.
void BlamerBundle::SplitBundle(int word1_right, int word2_left, bool debug,
                               BlamerBundle* bundle1,
                               BlamerBundle* bundle2) const {
  STRING debug_str;
  // Find truth boxes that correspond to the split in the blobs.
  int b;
  int begin2_truth_index = -1;
  if (incorrect_result_reason_ != IRR_NO_TRUTH &&
      truth_has_char_boxes_) {
    debug_str = "Looking for truth split at";
    debug_str.add_str_int(" end1_x ", word1_right);
    debug_str.add_str_int(" begin2_x ", word2_left);
    debug_str += "\nnorm_truth_word boxes:\n";
    if (norm_truth_word_.length() > 1) {
      norm_truth_word_.BlobBox(0).print_to_str(&debug_str);
      for (b = 1; b < norm_truth_word_.length(); ++b) {
        norm_truth_word_.BlobBox(b).print_to_str(&debug_str);
        if ((abs(word1_right - norm_truth_word_.BlobBox(b - 1).right()) <
            norm_box_tolerance_) &&
            (abs(word2_left - norm_truth_word_.BlobBox(b).left()) <
            norm_box_tolerance_)) {
          begin2_truth_index = b;
          debug_str += "Split found";
          break;
        }
      }
      debug_str += '\n';
    }
  }
  // Populate truth information in word and word2 with the first and second
  // part of the original truth.
  if (begin2_truth_index > 0) {
    bundle1->truth_has_char_boxes_ = true;
    bundle1->norm_box_tolerance_ = norm_box_tolerance_;
    bundle2->truth_has_char_boxes_ = true;
    bundle2->norm_box_tolerance_ = norm_box_tolerance_;
    BlamerBundle *curr_bb = bundle1;
    for (b = 0; b < norm_truth_word_.length(); ++b) {
      if (b == begin2_truth_index) curr_bb = bundle2;
      curr_bb->norm_truth_word_.InsertBox(b, norm_truth_word_.BlobBox(b));
      curr_bb->truth_word_.InsertBox(b, truth_word_.BlobBox(b));
      curr_bb->truth_text_.push_back(truth_text_[b]);
    }
  } else if (incorrect_result_reason_ == IRR_NO_TRUTH) {
    bundle1->incorrect_result_reason_ = IRR_NO_TRUTH;
    bundle2->incorrect_result_reason_ = IRR_NO_TRUTH;
  } else {
    debug_str += "Truth split not found";
    debug_str += truth_has_char_boxes_ ?
        "\n" : " (no truth char boxes)\n";
    bundle1->SetBlame(IRR_NO_TRUTH_SPLIT, debug_str, NULL, debug);
    bundle2->SetBlame(IRR_NO_TRUTH_SPLIT, debug_str, NULL, debug);
  }
}

// "Joins" the blames from bundle1 and bundle2 into *this.
void BlamerBundle::JoinBlames(const BlamerBundle& bundle1,
                              const BlamerBundle& bundle2, bool debug) {
  STRING debug_str;
  IncorrectResultReason irr = incorrect_result_reason_;
  if (irr != IRR_NO_TRUTH_SPLIT) debug_str = "";
  if (bundle1.incorrect_result_reason_ != IRR_CORRECT &&
      bundle1.incorrect_result_reason_ != IRR_NO_TRUTH &&
      bundle1.incorrect_result_reason_ != IRR_NO_TRUTH_SPLIT) {
    debug_str += "Blame from part 1: ";
    debug_str += bundle1.debug_;
    irr = bundle1.incorrect_result_reason_;
  }
  if (bundle2.incorrect_result_reason_ != IRR_CORRECT &&
      bundle2.incorrect_result_reason_ != IRR_NO_TRUTH &&
      bundle2.incorrect_result_reason_ != IRR_NO_TRUTH_SPLIT) {
    debug_str += "Blame from part 2: ";
    debug_str += bundle2.debug_;
    if (irr == IRR_CORRECT) {
      irr = bundle2.incorrect_result_reason_;
    } else if (irr != bundle2.incorrect_result_reason_) {
      irr = IRR_UNKNOWN;
    }
  }
  incorrect_result_reason_ = irr;
  if (irr != IRR_CORRECT && irr != IRR_NO_TRUTH) {
    SetBlame(irr, debug_str, NULL, debug);
  }
}

// If a blob with the same bounding box as one of the truth character
// bounding boxes is not classified as the corresponding truth character
// blames character classifier for incorrect answer.
void BlamerBundle::BlameClassifier(const UNICHARSET& unicharset,
                                   const TBOX& blob_box,
                                   const BLOB_CHOICE_LIST& choices,
                                   bool debug) {
  if (!truth_has_char_boxes_ ||
      incorrect_result_reason_ != IRR_CORRECT)
    return;  // Nothing to do here.

  for (int b = 0; b < norm_truth_word_.length(); ++b) {
    const TBOX &truth_box = norm_truth_word_.BlobBox(b);
    // Note that we are more strict on the bounding box boundaries here
    // than in other places (chopper, segmentation search), since we do
    // not have the ability to check the previous and next bounding box.
    if (blob_box.x_almost_equal(truth_box, norm_box_tolerance_/2)) {
      bool found = false;
      bool incorrect_adapted = false;
      UNICHAR_ID incorrect_adapted_id = INVALID_UNICHAR_ID;
      const char *truth_str = truth_text_[b].string();
      // We promise not to modify the list or its contents, using a
      // const BLOB_CHOICE* below.
      BLOB_CHOICE_IT choices_it(const_cast<BLOB_CHOICE_LIST*>(&choices));
      for (choices_it.mark_cycle_pt(); !choices_it.cycled_list();
          choices_it.forward()) {
        const BLOB_CHOICE* choice = choices_it.data();
        if (strcmp(truth_str, unicharset.get_normed_unichar(
            choice->unichar_id())) == 0) {
          found = true;
          break;
        } else if (choice->IsAdapted()) {
          incorrect_adapted = true;
          incorrect_adapted_id = choice->unichar_id();
        }
      }  // end choices_it for loop
      if (!found) {
        STRING debug_str = "unichar ";
        debug_str += truth_str;
        debug_str += " not found in classification list";
        SetBlame(IRR_CLASSIFIER, debug_str, NULL, debug);
      } else if (incorrect_adapted) {
        STRING debug_str = "better rating for adapted ";
        debug_str += unicharset.id_to_unichar(incorrect_adapted_id);
        debug_str += " than for correct ";
        debug_str += truth_str;
        SetBlame(IRR_ADAPTION, debug_str, NULL, debug);
      }
      break;
    }
  }  // end iterating over blamer_bundle->norm_truth_word
}

// Checks whether chops were made at all the character bounding box
// boundaries in word->truth_word. If not - blames the chopper for an
// incorrect answer.
void BlamerBundle::SetChopperBlame(const WERD_RES* word, bool debug) {
  if (NoTruth() || !truth_has_char_boxes_ ||
      word->chopped_word->blobs.empty()) {
    return;
  }
  STRING debug_str;
  bool missing_chop = false;
  int num_blobs = word->chopped_word->blobs.size();
  int box_index = 0;
  int blob_index = 0;
  int16_t truth_x = -1;
  while (box_index < truth_word_.length() && blob_index < num_blobs) {
    truth_x = norm_truth_word_.BlobBox(box_index).right();
    TBLOB * curr_blob = word->chopped_word->blobs[blob_index];
    if (curr_blob->bounding_box().right() < truth_x - norm_box_tolerance_) {
      ++blob_index;
      continue;  // encountered an extra chop, keep looking
    } else if (curr_blob->bounding_box().right() >
               truth_x + norm_box_tolerance_) {
      missing_chop = true;
      break;
    } else {
      ++blob_index;
    }
  }
  if (missing_chop || box_index < norm_truth_word_.length()) {
    STRING debug_str;
    if (missing_chop) {
      debug_str.add_str_int("Detected missing chop (tolerance=",
                            norm_box_tolerance_);
      debug_str += ") at Bounding Box=";
      TBLOB * curr_blob = word->chopped_word->blobs[blob_index];
      curr_blob->bounding_box().print_to_str(&debug_str);
      debug_str.add_str_int("\nNo chop for truth at x=", truth_x);
    } else {
      debug_str.add_str_int("Missing chops for last ",
                            norm_truth_word_.length() - box_index);
      debug_str += " truth box(es)";
    }
    debug_str += "\nMaximally chopped word boxes:\n";
    for (blob_index = 0; blob_index < num_blobs; ++blob_index) {
      TBLOB * curr_blob = word->chopped_word->blobs[blob_index];
      curr_blob->bounding_box().print_to_str(&debug_str);
      debug_str += '\n';
    }
    debug_str += "Truth  bounding  boxes:\n";
    for (box_index = 0; box_index < norm_truth_word_.length(); ++box_index) {
      norm_truth_word_.BlobBox(box_index).print_to_str(&debug_str);
      debug_str += '\n';
    }
    SetBlame(IRR_CHOPPER, debug_str, word->best_choice, debug);
  }
}

// Blames the classifier or the language model if, after running only the
// chopper, best_choice is incorrect and no blame has been yet set.
// Blames the classifier if best_choice is classifier's top choice and is a
// dictionary word (i.e. language model could not have helped).
// Otherwise, blames the language model (formerly permuter word adjustment).
void BlamerBundle::BlameClassifierOrLangModel(
    const WERD_RES* word,
    const UNICHARSET& unicharset, bool valid_permuter, bool debug) {
  if (valid_permuter) {
    // Find out whether best choice is a top choice.
    best_choice_is_dict_and_top_choice_ = true;
    for (int i = 0; i < word->best_choice->length(); ++i) {
      BLOB_CHOICE_IT blob_choice_it(word->GetBlobChoices(i));
      ASSERT_HOST(!blob_choice_it.empty());
      BLOB_CHOICE *first_choice = NULL;
      for (blob_choice_it.mark_cycle_pt(); !blob_choice_it.cycled_list();
           blob_choice_it.forward()) {  // find first non-fragment choice
        if (!(unicharset.get_fragment(blob_choice_it.data()->unichar_id()))) {
          first_choice = blob_choice_it.data();
          break;
        }
      }
      ASSERT_HOST(first_choice != NULL);
      if (first_choice->unichar_id() != word->best_choice->unichar_id(i)) {
        best_choice_is_dict_and_top_choice_ = false;
        break;
      }
    }
  }
  STRING debug_str;
  if (best_choice_is_dict_and_top_choice_) {
    debug_str = "Best choice is: incorrect, top choice, dictionary word";
    debug_str += " with permuter ";
    debug_str += word->best_choice->permuter_name();
  } else {
    debug_str = "Classifier/Old LM tradeoff is to blame";
  }
  SetBlame(best_choice_is_dict_and_top_choice_ ? IRR_CLASSIFIER
                                              : IRR_CLASS_OLD_LM_TRADEOFF,
           debug_str, word->best_choice, debug);
}

// Sets up the correct_segmentation_* to mark the correct bounding boxes.
void BlamerBundle::SetupCorrectSegmentation(const TWERD* word, bool debug) {
  params_training_bundle_.StartHypothesisList();
  if (incorrect_result_reason_ != IRR_CORRECT || !truth_has_char_boxes_)
    return;  // Nothing to do here.

  STRING debug_str;
  debug_str += "Blamer computing correct_segmentation_cols\n";
  int curr_box_col = 0;
  int next_box_col = 0;
  int num_blobs = word->NumBlobs();
  if (num_blobs == 0) return;  // No blobs to play with.
  int blob_index = 0;
  int16_t next_box_x = word->blobs[blob_index]->bounding_box().right();
  for (int truth_idx = 0; blob_index < num_blobs &&
       truth_idx < norm_truth_word_.length();
       ++blob_index) {
    ++next_box_col;
    int16_t curr_box_x = next_box_x;
    if (blob_index + 1 < num_blobs)
      next_box_x = word->blobs[blob_index + 1]->bounding_box().right();
    int16_t truth_x = norm_truth_word_.BlobBox(truth_idx).right();
    debug_str.add_str_int("Box x coord vs. truth: ", curr_box_x);
    debug_str.add_str_int(" ", truth_x);
    debug_str += "\n";
    if (curr_box_x > (truth_x + norm_box_tolerance_)) {
      break;  // failed to find a matching box
    } else if (curr_box_x >= truth_x - norm_box_tolerance_ &&  // matched
               (blob_index + 1 >= num_blobs ||  // next box can't be included
                next_box_x > truth_x + norm_box_tolerance_)) {
      correct_segmentation_cols_.push_back(curr_box_col);
      correct_segmentation_rows_.push_back(next_box_col-1);
      ++truth_idx;
      debug_str.add_str_int("col=", curr_box_col);
      debug_str.add_str_int(" row=", next_box_col-1);
      debug_str += "\n";
      curr_box_col = next_box_col;
    }
  }
  if (blob_index < num_blobs ||  // trailing blobs
      correct_segmentation_cols_.length() != norm_truth_word_.length()) {
    debug_str.add_str_int("Blamer failed to find correct segmentation"
                          " (tolerance=", norm_box_tolerance_);
    if (blob_index >= num_blobs) debug_str += " blob == NULL";
    debug_str += ")\n";
    debug_str.add_str_int(" path length ", correct_segmentation_cols_.length());
    debug_str.add_str_int(" vs. truth ", norm_truth_word_.length());
    debug_str += "\n";
    SetBlame(IRR_UNKNOWN, debug_str, NULL, debug);
    correct_segmentation_cols_.clear();
    correct_segmentation_rows_.clear();
  }
}

// Returns true if a guided segmentation search is needed.
bool BlamerBundle::GuidedSegsearchNeeded(const WERD_CHOICE *best_choice) const {
  return incorrect_result_reason_ == IRR_CORRECT &&
      !segsearch_is_looking_for_blame_ &&
      truth_has_char_boxes_ &&
      !ChoiceIsCorrect(best_choice);
}

// Setup ready to guide the segmentation search to the correct segmentation.
// The callback pp_cb is used to avoid a cyclic dependency.
// It calls into LMPainPoints::GenerateForBlamer by pre-binding the
// WERD_RES, and the LMPainPoints itself.
// pp_cb must be a permanent callback, and should be deleted by the caller.
void BlamerBundle::InitForSegSearch(const WERD_CHOICE *best_choice,
                                    MATRIX* ratings, UNICHAR_ID wildcard_id,
                                    bool debug, STRING *debug_str,
                                    TessResultCallback2<bool, int, int>* cb) {
  segsearch_is_looking_for_blame_ = true;
  if (debug) {
    tprintf("segsearch starting to look for blame\n");
  }
  // Fill pain points for any unclassifed blob corresponding to the
  // correct segmentation state.
  *debug_str += "Correct segmentation:\n";
  for (int idx = 0; idx < correct_segmentation_cols_.length(); ++idx) {
    debug_str->add_str_int("col=", correct_segmentation_cols_[idx]);
    debug_str->add_str_int(" row=", correct_segmentation_rows_[idx]);
    *debug_str += "\n";
    if (!ratings->Classified(correct_segmentation_cols_[idx],
                             correct_segmentation_rows_[idx],
                             wildcard_id) &&
        !cb->Run(correct_segmentation_cols_[idx],
                 correct_segmentation_rows_[idx])) {
      segsearch_is_looking_for_blame_ = false;
      *debug_str += "\nFailed to insert pain point\n";
      SetBlame(IRR_SEGSEARCH_HEUR, *debug_str, best_choice, debug);
      break;
    }
  }  // end for blamer_bundle->correct_segmentation_cols/rows
}
// Returns true if the guided segsearch is in progress.
bool BlamerBundle::GuidedSegsearchStillGoing() const {
  return segsearch_is_looking_for_blame_;
}

// The segmentation search has ended. Sets the blame appropriately.
void BlamerBundle::FinishSegSearch(const WERD_CHOICE *best_choice,
                                   bool debug, STRING *debug_str) {
  // If we are still looking for blame (i.e. best_choice is incorrect, but a
  // path representing the correct segmentation could be constructed), we can
  // blame segmentation search pain point prioritization if the rating of the
  // path corresponding to the correct segmentation is better than that of
  // best_choice (i.e. language model would have done the correct thing, but
  // because of poor pain point prioritization the correct segmentation was
  // never explored). Otherwise we blame the tradeoff between the language model
  // and the classifier, since even after exploring the path corresponding to
  // the correct segmentation incorrect best_choice would have been chosen.
  // One special case when we blame the classifier instead is when best choice
  // is incorrect, but it is a dictionary word and it classifier's top choice.
  if (segsearch_is_looking_for_blame_) {
    segsearch_is_looking_for_blame_ = false;
    if (best_choice_is_dict_and_top_choice_) {
      *debug_str = "Best choice is: incorrect, top choice, dictionary word";
      *debug_str += " with permuter ";
      *debug_str += best_choice->permuter_name();
      SetBlame(IRR_CLASSIFIER, *debug_str, best_choice, debug);
    } else if (best_correctly_segmented_rating_ <
        best_choice->rating()) {
      *debug_str += "Correct segmentation state was not explored";
      SetBlame(IRR_SEGSEARCH_PP, *debug_str, best_choice, debug);
    } else {
      if (best_correctly_segmented_rating_ >=
          WERD_CHOICE::kBadRating) {
        *debug_str += "Correct segmentation paths were pruned by LM\n";
      } else {
        debug_str->add_str_double("Best correct segmentation rating ",
                                  best_correctly_segmented_rating_);
        debug_str->add_str_double(" vs. best choice rating ",
                                  best_choice->rating());
      }
      SetBlame(IRR_CLASS_LM_TRADEOFF, *debug_str, best_choice, debug);
    }
  }
}

// If the bundle is null or still does not indicate the correct result,
// fix it and use some backup reason for the blame.
void BlamerBundle::LastChanceBlame(bool debug, WERD_RES* word) {
  if (word->blamer_bundle == NULL) {
    word->blamer_bundle = new BlamerBundle();
    word->blamer_bundle->SetBlame(IRR_PAGE_LAYOUT, "LastChanceBlame",
                                  word->best_choice, debug);
  } else if (word->blamer_bundle->incorrect_result_reason_ == IRR_NO_TRUTH) {
    word->blamer_bundle->SetBlame(IRR_NO_TRUTH, "Rejected truth",
                                  word->best_choice, debug);
  } else {
    bool correct = word->blamer_bundle->ChoiceIsCorrect(word->best_choice);
    IncorrectResultReason irr = word->blamer_bundle->incorrect_result_reason_;
    if (irr == IRR_CORRECT && !correct) {
      STRING debug_str = "Choice is incorrect after recognition";
      word->blamer_bundle->SetBlame(IRR_UNKNOWN, debug_str, word->best_choice,
                                    debug);
    } else if (irr != IRR_CORRECT && correct) {
      if (debug) {
        tprintf("Corrected %s\n", word->blamer_bundle->debug_.string());
      }
      word->blamer_bundle->incorrect_result_reason_ = IRR_CORRECT;
      word->blamer_bundle->debug_ = "";
    }
  }
}

// Sets the misadaption debug if this word is incorrect, as this word is
// being adapted to.
void BlamerBundle::SetMisAdaptionDebug(const WERD_CHOICE *best_choice,
                                       bool debug) {
  if (incorrect_result_reason_ != IRR_NO_TRUTH &&
      !ChoiceIsCorrect(best_choice)) {
    misadaption_debug_ ="misadapt to word (";
    misadaption_debug_ += best_choice->permuter_name();
    misadaption_debug_ += "): ";
    FillDebugString("", best_choice, &misadaption_debug_);
    if (debug) {
      tprintf("%s\n", misadaption_debug_.string());
    }
  }
}