/******************************************************************************

 ** Filename:    stopper.c

 ** Purpose:     Stopping criteria for word classifier.

 ** Author:      Dan Johnson

 **

 ** (c) Copyright Hewlett-Packard Company, 1988.

 ** 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 <cctype>

#include <cmath>

#include <cstdio>

#include <cstring>

#include "stopper.h"

#ifndef DISABLED_LEGACY_ENGINE

#  include "ambigs.h"

#endif

#include <tesseract/unichar.h>

#include "ccutil.h"

#include "dict.h"

#include "helpers.h"

#include "matchdefs.h"

#include "pageres.h"

#include "params.h"

#include "ratngs.h"

/*----------------------------------------------------------------------------

              Private Code

----------------------------------------------------------------------------*/

namespace tesseract {

bool Dict::AcceptableChoice(const WERD_CHOICE &best_choice,

                            XHeightConsistencyEnum xheight_consistency) {

  float CertaintyThreshold = stopper_nondict_certainty_base;

  int WordSize;

  if (stopper_no_acceptable_choices) {

    return false;

  }

  if (best_choice.empty()) {

    return false;

  }

  bool no_dang_ambigs = !best_choice.dangerous_ambig_found();

  bool is_valid_word = valid_word_permuter(best_choice.permuter(), false);

  bool is_case_ok = case_ok(best_choice);

  if (stopper_debug_level >= 1) {

    const char *xht = "UNKNOWN";

    switch (xheight_consistency) {

      case XH_GOOD:

        xht = "NORMAL";

        break;

      case XH_SUBNORMAL:

        xht = "SUBNORMAL";

        break;

      case XH_INCONSISTENT:

        xht = "INCONSISTENT";

        break;

      default:

        xht = "UNKNOWN";

    }

    tprintf("\nStopper:  %s (word=%c, case=%c, xht_ok=%s=[%g,%g])\n",

            best_choice.unichar_string().c_str(), (is_valid_word ? 'y' : 'n'),

            (is_case_ok ? 'y' : 'n'), xht, best_choice.min_x_height(), best_choice.max_x_height());

  }

  // Do not accept invalid words in PASS1.

  if (reject_offset_ <= 0.0f && !is_valid_word) {

    return false;

  }

  if (is_valid_word && is_case_ok) {

    WordSize = LengthOfShortestAlphaRun(best_choice);

    WordSize -= stopper_smallword_size;

    if (WordSize < 0) {

      WordSize = 0;

    }

    CertaintyThreshold += WordSize * stopper_certainty_per_char;

  }

  if (stopper_debug_level >= 1) {

    tprintf("Stopper:  Rating = %4.1f, Certainty = %4.1f, Threshold = %4.1f\n",

            best_choice.rating(), best_choice.certainty(), CertaintyThreshold);

  }

  if (no_dang_ambigs && best_choice.certainty() > CertaintyThreshold &&

      xheight_consistency < XH_INCONSISTENT && UniformCertainties(best_choice)) {

    return true;

  } else {

    if (stopper_debug_level >= 1) {

      tprintf(

          "AcceptableChoice() returned false"

          " (no_dang_ambig:%d cert:%.4g thresh:%g uniform:%d)\n",

          no_dang_ambigs, best_choice.certainty(), CertaintyThreshold,

          UniformCertainties(best_choice));

    }

    return false;

  }

}

bool Dict::AcceptableResult(WERD_RES *word) const {

  if (word->best_choice == nullptr) {

    return false;

  }

  float CertaintyThreshold = stopper_nondict_certainty_base - reject_offset_;

  int WordSize;

  if (stopper_debug_level >= 1) {

    tprintf("\nRejecter: %s (word=%c, case=%c, unambig=%c, multiple=%c)\n",

            word->best_choice->debug_string().c_str(), (valid_word(*word->best_choice) ? 'y' : 'n'),

            (case_ok(*word->best_choice) ? 'y' : 'n'),

            word->best_choice->dangerous_ambig_found() ? 'n' : 'y',

            word->best_choices.singleton() ? 'n' : 'y');

  }

  if (word->best_choice->empty() || !word->best_choices.singleton()) {

    return false;

  }

  if (valid_word(*word->best_choice) && case_ok(*word->best_choice)) {

    WordSize = LengthOfShortestAlphaRun(*word->best_choice);

    WordSize -= stopper_smallword_size;

    if (WordSize < 0) {

      WordSize = 0;

    }

    CertaintyThreshold += WordSize * stopper_certainty_per_char;

  }

  if (stopper_debug_level >= 1) {

    tprintf("Rejecter: Certainty = %4.1f, Threshold = %4.1f   ", word->best_choice->certainty(),

            CertaintyThreshold);

  }

  if (word->best_choice->certainty() > CertaintyThreshold && !stopper_no_acceptable_choices) {

    if (stopper_debug_level >= 1) {

      tprintf("ACCEPTED\n");

    }

    return true;

  } else {

    if (stopper_debug_level >= 1) {

      tprintf("REJECTED\n");

    }

    return false;

  }

}

#if !defined(DISABLED_LEGACY_ENGINE)

bool Dict::NoDangerousAmbig(WERD_CHOICE *best_choice, DANGERR *fixpt, bool fix_replaceable,

                            MATRIX *ratings) {

  if (stopper_debug_level > 2) {

    tprintf("\nRunning NoDangerousAmbig() for %s\n", best_choice->debug_string().c_str());

  }

  // Construct BLOB_CHOICE_LIST_VECTOR with ambiguities

  // for each unichar id in BestChoice.

  BLOB_CHOICE_LIST_VECTOR ambig_blob_choices;

  bool ambigs_found = false;

  // For each position in best_choice:

  // -- choose AMBIG_SPEC_LIST that corresponds to unichar_id at best_choice[i]

  // -- initialize wrong_ngram with a single unichar_id at best_choice[i]

  // -- look for ambiguities corresponding to wrong_ngram in the list while

  //    adding the following unichar_ids from best_choice to wrong_ngram

  //

  // Repeat the above procedure twice: first time look through

  // ambigs to be replaced and replace all the ambiguities found;

  // second time look through dangerous ambiguities and construct

  // ambig_blob_choices with fake a blob choice for each ambiguity

  // and pass them to dawg_permute_and_select() to search for

  // ambiguous words in the dictionaries.

  //

  // Note that during the execution of the for loop (on the first pass)

  // if replacements are made the length of best_choice might change.

  for (int pass = 0; pass < (fix_replaceable ? 2 : 1); ++pass) {

    bool replace = (fix_replaceable && pass == 0);

    const UnicharAmbigsVector &table =

        replace ? getUnicharAmbigs().replace_ambigs() : getUnicharAmbigs().dang_ambigs();

    if (!replace) {

      // Initialize ambig_blob_choices with lists containing a single

      // unichar id for the corresponding position in best_choice.

      // best_choice consisting from only the original letters will

      // have a rating of 0.0.

      for (unsigned i = 0; i < best_choice->length(); ++i) {

        auto *lst = new BLOB_CHOICE_LIST();

        BLOB_CHOICE_IT lst_it(lst);

        // TODO(rays/antonova) Put real xheights and y shifts here.

        lst_it.add_to_end(

            new BLOB_CHOICE(best_choice->unichar_id(i), 0.0, 0.0, -1, 0, 1, 0, BCC_AMBIG));

        ambig_blob_choices.push_back(lst);

      }

    }

    UNICHAR_ID wrong_ngram[MAX_AMBIG_SIZE + 1];

    int wrong_ngram_index;

    int blob_index = 0;

    for (unsigned i = 0; i < best_choice->length(); blob_index += best_choice->state(i), ++i) {

      auto curr_unichar_id = best_choice->unichar_id(i);

      if (stopper_debug_level > 2) {

        tprintf("Looking for %s ngrams starting with %s:\n", replace ? "replaceable" : "ambiguous",

                getUnicharset().debug_str(curr_unichar_id).c_str());

      }

      int num_wrong_blobs = best_choice->state(i);

      wrong_ngram_index = 0;

      wrong_ngram[wrong_ngram_index] = curr_unichar_id;

      if (curr_unichar_id == INVALID_UNICHAR_ID || static_cast<size_t>(curr_unichar_id) >= table.size() ||

          table[curr_unichar_id] == nullptr) {

        continue; // there is no ambig spec for this unichar id

      }

      AmbigSpec_IT spec_it(table[curr_unichar_id]);

      for (spec_it.mark_cycle_pt(); !spec_it.cycled_list();) {

        const AmbigSpec *ambig_spec = spec_it.data();

        wrong_ngram[wrong_ngram_index + 1] = INVALID_UNICHAR_ID;

        int compare = UnicharIdArrayUtils::compare(wrong_ngram, ambig_spec->wrong_ngram);

        if (stopper_debug_level > 2) {

          tprintf("candidate ngram: ");

          UnicharIdArrayUtils::print(wrong_ngram, getUnicharset());

          tprintf("current ngram from spec: ");

          UnicharIdArrayUtils::print(ambig_spec->wrong_ngram, getUnicharset());

          tprintf("comparison result: %d\n", compare);

        }

        if (compare == 0) {

          // Record the place where we found an ambiguity.

          if (fixpt != nullptr) {

            UNICHAR_ID leftmost_id = ambig_spec->correct_fragments[0];

            fixpt->push_back(DANGERR_INFO(blob_index, blob_index + num_wrong_blobs, replace,

                                          getUnicharset().get_isngram(ambig_spec->correct_ngram_id),

                                          leftmost_id));

            if (stopper_debug_level > 1) {

              tprintf("fixpt+=(%d %d %d %d %s)\n", blob_index, blob_index + num_wrong_blobs, false,

                      getUnicharset().get_isngram(ambig_spec->correct_ngram_id),

                      getUnicharset().id_to_unichar(leftmost_id));

            }

          }

          if (replace) {

            if (stopper_debug_level > 2) {

              tprintf("replace ambiguity with %s : ",

                      getUnicharset().id_to_unichar(ambig_spec->correct_ngram_id));

              UnicharIdArrayUtils::print(ambig_spec->correct_fragments, getUnicharset());

            }

            ReplaceAmbig(i, ambig_spec->wrong_ngram_size, ambig_spec->correct_ngram_id, best_choice,

                         ratings);

          } else if (i > 0 || ambig_spec->type != CASE_AMBIG) {

            // We found dang ambig - update ambig_blob_choices.

            if (stopper_debug_level > 2) {

              tprintf("found ambiguity: ");

              UnicharIdArrayUtils::print(ambig_spec->correct_fragments, getUnicharset());

            }

            ambigs_found = true;

            for (int tmp_index = 0; tmp_index <= wrong_ngram_index; ++tmp_index) {

              // Add a blob choice for the corresponding fragment of the

              // ambiguity. These fake blob choices are initialized with

              // negative ratings (which are not possible for real blob

              // choices), so that dawg_permute_and_select() considers any

              // word not consisting of only the original letters a better

              // choice and stops searching for alternatives once such a

              // choice is found.

              BLOB_CHOICE_IT bc_it(ambig_blob_choices[i + tmp_index]);

              bc_it.add_to_end(new BLOB_CHOICE(ambig_spec->correct_fragments[tmp_index], -1.0, 0.0,

                                               -1, 0, 1, 0, BCC_AMBIG));

            }

          }

          spec_it.forward();

        } else if (compare == -1) {

          unsigned next_index;

          if (wrong_ngram_index + 1 < ambig_spec->wrong_ngram_size &&

              ((next_index = wrong_ngram_index + 1 + i) < best_choice->length())) {

            // Add the next unichar id to wrong_ngram and keep looking for

            // more ambigs starting with curr_unichar_id in AMBIG_SPEC_LIST.

            wrong_ngram[++wrong_ngram_index] = best_choice->unichar_id(next_index);

            num_wrong_blobs += best_choice->state(next_index);

          } else {

            break; // no more matching ambigs in this AMBIG_SPEC_LIST

          }

        } else {

          spec_it.forward();

        }

      } // end searching AmbigSpec_LIST

    }   // end searching best_choice

  }     // end searching replace and dangerous ambigs

  // If any ambiguities were found permute the constructed ambig_blob_choices

  // to see if an alternative dictionary word can be found.

  if (ambigs_found) {

    if (stopper_debug_level > 2) {

      tprintf("\nResulting ambig_blob_choices:\n");

      for (unsigned i = 0; i < ambig_blob_choices.size(); ++i) {

        print_ratings_list("", ambig_blob_choices.at(i), getUnicharset());

        tprintf("\n");

      }

    }

    WERD_CHOICE *alt_word = dawg_permute_and_select(ambig_blob_choices, 0.0);

    ambigs_found = (alt_word->rating() < 0.0);

    if (ambigs_found) {

      if (stopper_debug_level >= 1) {

        tprintf("Stopper: Possible ambiguous word = %s\n", alt_word->debug_string().c_str());

      }

      if (fixpt != nullptr) {

        // Note: Currently character choices combined from fragments can only

        // be generated by NoDangrousAmbigs(). This code should be updated if

        // the capability to produce classifications combined from character

        // fragments is added to other functions.

        int orig_i = 0;

        for (unsigned i = 0; i < alt_word->length(); ++i) {

          const UNICHARSET &uchset = getUnicharset();

          bool replacement_is_ngram = uchset.get_isngram(alt_word->unichar_id(i));

          UNICHAR_ID leftmost_id = alt_word->unichar_id(i);

          if (replacement_is_ngram) {

            // we have to extract the leftmost unichar from the ngram.

            const char *str = uchset.id_to_unichar(leftmost_id);

            int step = uchset.step(str);

            if (step) {

              leftmost_id = uchset.unichar_to_id(str, step);

            }

          }

          int end_i = orig_i + alt_word->state(i);

          if (alt_word->state(i) > 1 || (orig_i + 1 == end_i && replacement_is_ngram)) {

            // Compute proper blob indices.

            int blob_start = 0;

            for (int j = 0; j < orig_i; ++j) {

              blob_start += best_choice->state(j);

            }

            int blob_end = blob_start;

            for (int j = orig_i; j < end_i; ++j) {

              blob_end += best_choice->state(j);

            }

            fixpt->push_back(

                DANGERR_INFO(blob_start, blob_end, true, replacement_is_ngram, leftmost_id));

            if (stopper_debug_level > 1) {

              tprintf("fixpt->dangerous+=(%d %d %d %d %s)\n", orig_i, end_i, true,

                      replacement_is_ngram, uchset.id_to_unichar(leftmost_id));

            }

          }

          orig_i += alt_word->state(i);

        }

      }

    }

    delete alt_word;

  }

  if (output_ambig_words_file_ != nullptr) {

    fprintf(output_ambig_words_file_, "\n");

  }

  for (auto data : ambig_blob_choices) {

    delete data;

  }

  return !ambigs_found;

}

void Dict::EndDangerousAmbigs() {}

#endif // !defined(DISABLED_LEGACY_ENGINE)

void Dict::SetupStopperPass1() {

  reject_offset_ = 0.0;

}

void Dict::SetupStopperPass2() {

  reject_offset_ = stopper_phase2_certainty_rejection_offset;

}

void Dict::ReplaceAmbig(int wrong_ngram_begin_index, int wrong_ngram_size,

                        UNICHAR_ID correct_ngram_id, WERD_CHOICE *werd_choice, MATRIX *ratings) {

  int num_blobs_to_replace = 0;

  int begin_blob_index = 0;

  int i;

  // Rating and certainty for the new BLOB_CHOICE are derived from the

  // replaced choices.

  float new_rating = 0.0f;

  float new_certainty = 0.0f;

  BLOB_CHOICE *old_choice = nullptr;

  for (i = 0; i < wrong_ngram_begin_index + wrong_ngram_size; ++i) {

    if (i >= wrong_ngram_begin_index) {

      int num_blobs = werd_choice->state(i);

      int col = begin_blob_index + num_blobs_to_replace;

      int row = col + num_blobs - 1;

      BLOB_CHOICE_LIST *choices = ratings->get(col, row);

      ASSERT_HOST(choices != nullptr);

      old_choice = FindMatchingChoice(werd_choice->unichar_id(i), choices);

      ASSERT_HOST(old_choice != nullptr);

      new_rating += old_choice->rating();

      new_certainty += old_choice->certainty();

      num_blobs_to_replace += num_blobs;

    } else {

      begin_blob_index += werd_choice->state(i);

    }

  }

  new_certainty /= wrong_ngram_size;

  // If there is no entry in the ratings matrix, add it.

  MATRIX_COORD coord(begin_blob_index, begin_blob_index + num_blobs_to_replace - 1);

  if (!coord.Valid(*ratings)) {

    ratings->IncreaseBandSize(coord.row - coord.col + 1);

  }

  if (ratings->get(coord.col, coord.row) == nullptr) {

    ratings->put(coord.col, coord.row, new BLOB_CHOICE_LIST);

  }

  BLOB_CHOICE_LIST *new_choices = ratings->get(coord.col, coord.row);

  BLOB_CHOICE *choice = FindMatchingChoice(correct_ngram_id, new_choices);

  if (choice != nullptr) {

    // Already there. Upgrade if new rating better.

    if (new_rating < choice->rating()) {

      choice->set_rating(new_rating);

    }

    if (new_certainty < choice->certainty()) {

      choice->set_certainty(new_certainty);

    }

    // DO NOT SORT!! It will mess up the iterator in LanguageModel::UpdateState.

  } else {

    // Need a new choice with the correct_ngram_id.

    choice = new BLOB_CHOICE(*old_choice);

    choice->set_unichar_id(correct_ngram_id);

    choice->set_rating(new_rating);

    choice->set_certainty(new_certainty);

    choice->set_classifier(BCC_AMBIG);

    choice->set_matrix_cell(coord.col, coord.row);

    BLOB_CHOICE_IT it(new_choices);

    it.add_to_end(choice);

  }

  // Remove current unichar from werd_choice. On the last iteration

  // set the correct replacement unichar instead of removing a unichar.

  for (int replaced_count = 0; replaced_count < wrong_ngram_size; ++replaced_count) {

    if (replaced_count + 1 == wrong_ngram_size) {

      werd_choice->set_blob_choice(wrong_ngram_begin_index, num_blobs_to_replace, choice);

    } else {

      werd_choice->remove_unichar_id(wrong_ngram_begin_index + 1);

    }

  }

  if (stopper_debug_level >= 1) {

    werd_choice->print("ReplaceAmbig() ");

    tprintf("Modified blob_choices: ");

    print_ratings_list("\n", new_choices, getUnicharset());

  }

}

int Dict::LengthOfShortestAlphaRun(const WERD_CHOICE &WordChoice) const {

  int shortest = INT32_MAX;

  int curr_len = 0;

  for (unsigned w = 0; w < WordChoice.length(); ++w) {

    if (WordChoice.unicharset()->get_isalpha(WordChoice.unichar_id(w))) {

      curr_len++;

    } else if (curr_len > 0) {

      if (curr_len < shortest) {

        shortest = curr_len;

      }

      curr_len = 0;

    }

  }

  if (curr_len > 0 && curr_len < shortest) {

    shortest = curr_len;

  } else if (shortest == INT32_MAX) {

    shortest = 0;

  }

  return shortest;

}

int Dict::UniformCertainties(const WERD_CHOICE &word) {

  float Certainty;

  float WorstCertainty = FLT_MAX;

  float CertaintyThreshold;

  double TotalCertainty;

  double TotalCertaintySquared;

  double Variance;

  float Mean, StdDev;

  int word_length = word.length();

  if (word_length < 3) {

    return true;

  }

  TotalCertainty = TotalCertaintySquared = 0.0;

  for (int i = 0; i < word_length; ++i) {

    Certainty = word.certainty(i);

    TotalCertainty += Certainty;

    TotalCertaintySquared += static_cast<double>(Certainty) * Certainty;

    if (Certainty < WorstCertainty) {

      WorstCertainty = Certainty;

    }

  }

  // Subtract off worst certainty from statistics.

  word_length--;

  TotalCertainty -= WorstCertainty;

  TotalCertaintySquared -= static_cast<double>(WorstCertainty) * WorstCertainty;

  Mean = TotalCertainty / word_length;

  Variance = ((word_length * TotalCertaintySquared - TotalCertainty * TotalCertainty) /

              (word_length * (word_length - 1)));

  if (Variance < 0.0) {

    Variance = 0.0;

  }

  StdDev = sqrt(Variance);

  CertaintyThreshold = Mean - stopper_allowable_character_badness * StdDev;

  if (CertaintyThreshold > stopper_nondict_certainty_base) {

    CertaintyThreshold = stopper_nondict_certainty_base;

  }

  if (word.certainty() < CertaintyThreshold) {

    if (stopper_debug_level >= 1) {

      tprintf(

          "Stopper: Non-uniform certainty = %4.1f"

          " (m=%4.1f, s=%4.1f, t=%4.1f)\n",

          word.certainty(), Mean, StdDev, CertaintyThreshold);

    }

    return false;

  } else {

    return true;

  }

}

} // namespace tesseract