clusttool.cpp

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/******************************************************************************
 ** Filename: clusttool.cpp
 ** Purpose:  Misc. tools for use with the clustering routines
 ** 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 Files----------------------------------
#define _USE_MATH_DEFINES   // for M_PI
#include "clusttool.h"
#include <cmath>            // for M_PI, std::isnan
#include <locale>           // for std::locale::classic
#include <sstream>          // for std::stringstream
#include "emalloc.h"
 
using tesseract::TFile;
 
//---------------Global Data Definitions and Declarations--------------------
#define TOKENSIZE 80         
#define QUOTED_TOKENSIZE "79"
#define MAXSAMPLESIZE 65535  
 
 
static float *ReadNFloats(TFile *fp, uint16_t N, float Buffer[]) {
  const int kMaxLineSize = 1024;
  char line[kMaxLineSize];
  if (fp->FGets(line, kMaxLineSize) == nullptr) {
    tprintf("Hit EOF in ReadNFloats!\n");
    return nullptr;
  }
  bool needs_free = false;
 
  if (Buffer == nullptr) {
    Buffer = static_cast<float *>(Emalloc(N * sizeof(float)));
    needs_free = true;
  }
 
  std::stringstream stream(line);
  // Use "C" locale (needed for float values Buffer[i]).
  stream.imbue(std::locale::classic());
  for (uint16_t i = 0; i < N; i++) {
    float f = NAN;
    stream >> f;
    if (std::isnan(f)) {
      tprintf("Read of %u floats failed!\n", N);
      if (needs_free) Efree(Buffer);
      return nullptr;
    }
    Buffer[i] = f;
  }
  return Buffer;
}
 
static void WriteNFloats(FILE * File, uint16_t N, float Array[]) {
  for (int i = 0; i < N; i++)
    fprintf(File, " %9.6f", Array[i]);
  fprintf(File, "\n");
}
 
static void WriteProtoStyle(FILE *File, PROTOSTYLE ProtoStyle) {
  switch (ProtoStyle) {
    case spherical:
      fprintf (File, "spherical");
      break;
    case elliptical:
      fprintf (File, "elliptical");
      break;
    case mixed:
      fprintf (File, "mixed");
      break;
    case automatic:
      fprintf (File, "automatic");
      break;
  }
}
 
uint16_t ReadSampleSize(TFile *fp) {
  int SampleSize = 0;
 
  const int kMaxLineSize = 100;
  char line[kMaxLineSize];
  ASSERT_HOST(fp->FGets(line, kMaxLineSize) != nullptr);
  ASSERT_HOST(sscanf(line, "%d", &SampleSize) == 1);
  ASSERT_HOST(SampleSize >= 0 && SampleSize <= MAXSAMPLESIZE);
  return SampleSize;
}
 
PARAM_DESC *ReadParamDesc(TFile *fp, uint16_t N) {
  PARAM_DESC *ParamDesc;
 
  ParamDesc = static_cast<PARAM_DESC *>(Emalloc (N * sizeof (PARAM_DESC)));
  for (int i = 0; i < N; i++) {
    const int kMaxLineSize = TOKENSIZE * 4;
    char line[kMaxLineSize];
    ASSERT_HOST(fp->FGets(line, kMaxLineSize) != nullptr);
    std::istringstream stream(line);
    // Use "C" locale (needed for float values Min, Max).
    stream.imbue(std::locale::classic());
    std::string linear_token;
    stream >> linear_token;
    std::string essential_token;
    stream >> essential_token;
    stream >> ParamDesc[i].Min;
    stream >> ParamDesc[i].Max;
    ASSERT_HOST(!stream.fail());
    ParamDesc[i].Circular = (linear_token[0] == 'c');
    ParamDesc[i].NonEssential = (essential_token[0] != 'e');
    ParamDesc[i].Range = ParamDesc[i].Max - ParamDesc[i].Min;
    ParamDesc[i].HalfRange = ParamDesc[i].Range / 2;
    ParamDesc[i].MidRange = (ParamDesc[i].Max + ParamDesc[i].Min) / 2;
  }
  return (ParamDesc);
}
 
PROTOTYPE *ReadPrototype(TFile *fp, uint16_t N) {
  char sig_token[TOKENSIZE], shape_token[TOKENSIZE];
  PROTOTYPE *Proto;
  int SampleCount;
  int i;
 
  const int kMaxLineSize = TOKENSIZE * 4;
  char line[kMaxLineSize];
  if (fp->FGets(line, kMaxLineSize) == nullptr ||
      sscanf(line, "%" QUOTED_TOKENSIZE "s %" QUOTED_TOKENSIZE "s %d",
             sig_token, shape_token, &SampleCount) != 3) {
    tprintf("Invalid prototype: %s\n", line);
    return nullptr;
  }
  Proto = static_cast<PROTOTYPE *>(Emalloc(sizeof(PROTOTYPE)));
  Proto->Cluster = nullptr;
  Proto->Significant = (sig_token[0] == 's');
 
  switch (shape_token[0]) {
    case 's':
      Proto->Style = spherical;
      break;
    case 'e':
      Proto->Style = elliptical;
      break;
    case 'a':
      Proto->Style = automatic;
      break;
    default:
      tprintf("Invalid prototype style specification:%s\n", shape_token);
      Proto->Style = elliptical;
  }
 
  ASSERT_HOST(SampleCount >= 0);
  Proto->NumSamples = SampleCount;
 
  Proto->Mean = ReadNFloats(fp, N, nullptr);
  ASSERT_HOST(Proto->Mean != nullptr);
 
  switch (Proto->Style) {
    case spherical:
      ASSERT_HOST(ReadNFloats(fp, 1, &(Proto->Variance.Spherical)) != nullptr);
      Proto->Magnitude.Spherical =
          1.0 / sqrt(2.0 * M_PI * Proto->Variance.Spherical);
      Proto->TotalMagnitude = pow(Proto->Magnitude.Spherical, static_cast<float>(N));
      Proto->LogMagnitude = log(static_cast<double>(Proto->TotalMagnitude));
      Proto->Weight.Spherical = 1.0 / Proto->Variance.Spherical;
      Proto->Distrib = nullptr;
      break;
    case elliptical:
      Proto->Variance.Elliptical = ReadNFloats(fp, N, nullptr);
      ASSERT_HOST(Proto->Variance.Elliptical != nullptr);
      Proto->Magnitude.Elliptical = static_cast<float *>(Emalloc(N * sizeof(float)));
      Proto->Weight.Elliptical = static_cast<float *>(Emalloc(N * sizeof(float)));
      Proto->TotalMagnitude = 1.0;
      for (i = 0; i < N; i++) {
        Proto->Magnitude.Elliptical[i] =
            1.0 / sqrt(2.0 * M_PI * Proto->Variance.Elliptical[i]);
        Proto->Weight.Elliptical[i] = 1.0 / Proto->Variance.Elliptical[i];
        Proto->TotalMagnitude *= Proto->Magnitude.Elliptical[i];
      }
      Proto->LogMagnitude = log(static_cast<double>(Proto->TotalMagnitude));
      Proto->Distrib = nullptr;
      break;
    default:
      Efree(Proto);
      tprintf("Invalid prototype style\n");
      return nullptr;
  }
  return Proto;
}
 
void WriteParamDesc(FILE *File, uint16_t N, const PARAM_DESC ParamDesc[]) {
  int i;
 
  for (i = 0; i < N; i++) {
    if (ParamDesc[i].Circular)
      fprintf (File, "circular ");
    else
      fprintf (File, "linear   ");
 
    if (ParamDesc[i].NonEssential)
      fprintf (File, "non-essential ");
    else
      fprintf (File, "essential     ");
 
    fprintf (File, "%10.6f %10.6f\n", ParamDesc[i].Min, ParamDesc[i].Max);
  }
}
 
void WritePrototype(FILE *File, uint16_t N, PROTOTYPE *Proto) {
  int i;
 
  if (Proto->Significant)
    fprintf (File, "significant   ");
  else
    fprintf (File, "insignificant ");
  WriteProtoStyle (File, static_cast<PROTOSTYLE>(Proto->Style));
  fprintf (File, "%6d\n\t", Proto->NumSamples);
  WriteNFloats (File, N, Proto->Mean);
  fprintf (File, "\t");
 
  switch (Proto->Style) {
    case spherical:
      WriteNFloats (File, 1, &(Proto->Variance.Spherical));
      break;
    case elliptical:
      WriteNFloats (File, N, Proto->Variance.Elliptical);
      break;
    case mixed:
      for (i = 0; i < N; i++)
      switch (Proto->Distrib[i]) {
        case normal:
          fprintf (File, " %9s", "normal");
          break;
        case uniform:
          fprintf (File, " %9s", "uniform");
          break;
        case D_random:
          fprintf (File, " %9s", "random");
          break;
        case DISTRIBUTION_COUNT:
          ASSERT_HOST(!"Distribution count not allowed!");
      }
      fprintf (File, "\n\t");
      WriteNFloats (File, N, Proto->Variance.Elliptical);
  }
}