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Replace FLOAT64 by double data type
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On most systems double is the IEEE 754 double-precision binary
floating-point format (64 bits). Tesseract does not support other systems.

Signed-off-by: Stefan Weil <[email protected]>
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@stweil
stweil committed Jul 2, 2018
1 parent 1a181a3 commit 919901e
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Showing 5 changed files with 78 additions and 79 deletions.
1 change: 0 additions & 1 deletion src/ccutil/host.h
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Original file line number Diff line number Diff line change
Expand Up @@ -32,7 +32,6 @@

// definitions of portable data types (numbers and characters)
using FLOAT32 = float;
using FLOAT64 = double;
using BOOL8 = unsigned char;

#if defined(_WIN32)
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142 changes: 71 additions & 71 deletions src/classify/cluster.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -175,20 +175,20 @@ struct STATISTICS {
};

struct BUCKETS {
DISTRIBUTION Distribution; // distribution being tested for
uint32_t SampleCount; // # of samples in histogram
FLOAT64 Confidence; // confidence level of test
FLOAT64 ChiSquared; // test threshold
uint16_t NumberOfBuckets; // number of cells in histogram
uint16_t Bucket[BUCKETTABLESIZE];// mapping to histogram buckets
uint32_t *Count; // frequency of occurrence histogram
FLOAT32 *ExpectedCount; // expected histogram
DISTRIBUTION Distribution; // distribution being tested for
uint32_t SampleCount; // # of samples in histogram
double Confidence; // confidence level of test
double ChiSquared; // test threshold
uint16_t NumberOfBuckets; // number of cells in histogram
uint16_t Bucket[BUCKETTABLESIZE]; // mapping to histogram buckets
uint32_t *Count; // frequency of occurrence histogram
FLOAT32 *ExpectedCount; // expected histogram
};

struct CHISTRUCT{
uint16_t DegreesOfFreedom;
FLOAT64 Alpha;
FLOAT64 ChiSquared;
double Alpha;
double ChiSquared;
};

// For use with KDWalk / MakePotentialClusters
Expand All @@ -199,8 +199,8 @@ struct ClusteringContext {
int32_t next; // next candidate to be used
};

typedef FLOAT64 (*DENSITYFUNC) (int32_t);
typedef FLOAT64 (*SOLVEFUNC) (CHISTRUCT *, double);
typedef double (*DENSITYFUNC) (int32_t);
typedef double (*SOLVEFUNC) (CHISTRUCT *, double);

#define Odd(N) ((N)%2)
#define Mirror(N,R) ((R) - (N) - 1)
Expand All @@ -215,12 +215,12 @@ typedef FLOAT64 (*SOLVEFUNC) (CHISTRUCT *, double);
deviations and x=BUCKETTABLESIZE is mapped to
+NORMALEXTENT standard deviations. */
#define SqrtOf2Pi 2.506628275
static const FLOAT64 kNormalStdDev = BUCKETTABLESIZE / (2.0 * NORMALEXTENT);
static const FLOAT64 kNormalVariance =
static const double kNormalStdDev = BUCKETTABLESIZE / (2.0 * NORMALEXTENT);
static const double kNormalVariance =
(BUCKETTABLESIZE * BUCKETTABLESIZE) / (4.0 * NORMALEXTENT * NORMALEXTENT);
static const FLOAT64 kNormalMagnitude =
static const double kNormalMagnitude =
(2.0 * NORMALEXTENT) / (SqrtOf2Pi * BUCKETTABLESIZE);
static const FLOAT64 kNormalMean = BUCKETTABLESIZE / 2;
static const double kNormalMean = BUCKETTABLESIZE / 2;

/** define lookup tables used to compute the number of histogram buckets
that should be used for a given number of samples. */
Expand Down Expand Up @@ -287,7 +287,7 @@ PROTOTYPE *MakeMixedProto(CLUSTERER *Clusterer,
CLUSTER *Cluster,
STATISTICS *Statistics,
BUCKETS *NormalBuckets,
FLOAT64 Confidence);
double Confidence);

void MakeDimRandom(uint16_t i, PROTOTYPE *Proto, PARAM_DESC *ParamDesc);

Expand All @@ -314,21 +314,21 @@ bool Independent(PARAM_DESC* ParamDesc,
BUCKETS *GetBuckets(CLUSTERER* clusterer,
DISTRIBUTION Distribution,
uint32_t SampleCount,
FLOAT64 Confidence);
double Confidence);

BUCKETS *MakeBuckets(DISTRIBUTION Distribution,
uint32_t SampleCount,
FLOAT64 Confidence);
double Confidence);

uint16_t OptimumNumberOfBuckets(uint32_t SampleCount);

FLOAT64 ComputeChiSquared(uint16_t DegreesOfFreedom, FLOAT64 Alpha);
double ComputeChiSquared(uint16_t DegreesOfFreedom, double Alpha);

FLOAT64 NormalDensity(int32_t x);
double NormalDensity(int32_t x);

FLOAT64 UniformDensity(int32_t x);
double UniformDensity(int32_t x);

FLOAT64 Integral(FLOAT64 f1, FLOAT64 f2, FLOAT64 Dx);
double Integral(double f1, double f2, double Dx);

void FillBuckets(BUCKETS *Buckets,
CLUSTER *Cluster,
Expand Down Expand Up @@ -369,14 +369,14 @@ void InitBuckets(BUCKETS *Buckets);
int AlphaMatch(void *arg1, // CHISTRUCT *ChiStruct,
void *arg2); // CHISTRUCT *SearchKey);

CHISTRUCT *NewChiStruct(uint16_t DegreesOfFreedom, FLOAT64 Alpha);
CHISTRUCT *NewChiStruct(uint16_t DegreesOfFreedom, double Alpha);

FLOAT64 Solve(SOLVEFUNC Function,
void *FunctionParams,
FLOAT64 InitialGuess,
FLOAT64 Accuracy);
double Solve(SOLVEFUNC Function,
void *FunctionParams,
double InitialGuess,
double Accuracy);

FLOAT64 ChiArea(CHISTRUCT *ChiParams, FLOAT64 x);
double ChiArea(CHISTRUCT *ChiParams, double x);

bool MultipleCharSamples(CLUSTERER* Clusterer,
CLUSTER* Cluster,
Expand Down Expand Up @@ -1223,7 +1223,7 @@ PROTOTYPE *MakeSphericalProto(CLUSTERER *Clusterer,

FillBuckets (Buckets, Cluster, i, &(Clusterer->ParamDesc[i]),
Cluster->Mean[i],
sqrt ((FLOAT64) (Statistics->AvgVariance)));
sqrt ((double) (Statistics->AvgVariance)));
if (!DistributionOK (Buckets))
break;
}
Expand Down Expand Up @@ -1260,7 +1260,7 @@ PROTOTYPE *MakeEllipticalProto(CLUSTERER *Clusterer,

FillBuckets (Buckets, Cluster, i, &(Clusterer->ParamDesc[i]),
Cluster->Mean[i],
sqrt ((FLOAT64) Statistics->
sqrt ((double) Statistics->
CoVariance[i * (Clusterer->SampleSize + 1)]));
if (!DistributionOK (Buckets))
break;
Expand Down Expand Up @@ -1292,7 +1292,7 @@ PROTOTYPE *MakeMixedProto(CLUSTERER *Clusterer,
CLUSTER *Cluster,
STATISTICS *Statistics,
BUCKETS *NormalBuckets,
FLOAT64 Confidence) {
double Confidence) {
PROTOTYPE *Proto;
int i;
BUCKETS *UniformBuckets = nullptr;
Expand All @@ -1308,7 +1308,7 @@ PROTOTYPE *MakeMixedProto(CLUSTERER *Clusterer,

FillBuckets (NormalBuckets, Cluster, i, &(Clusterer->ParamDesc[i]),
Proto->Mean[i],
sqrt ((FLOAT64) Proto->Variance.Elliptical[i]));
sqrt ((double) Proto->Variance.Elliptical[i]));
if (DistributionOK (NormalBuckets))
continue;

Expand Down Expand Up @@ -1688,7 +1688,7 @@ Independent(PARAM_DESC* ParamDesc,
BUCKETS *GetBuckets(CLUSTERER* clusterer,
DISTRIBUTION Distribution,
uint32_t SampleCount,
FLOAT64 Confidence) {
double Confidence) {
// Get an old bucket structure with the same number of buckets.
uint16_t NumberOfBuckets = OptimumNumberOfBuckets(SampleCount);
BUCKETS *Buckets =
Expand Down Expand Up @@ -1734,17 +1734,17 @@ BUCKETS *GetBuckets(CLUSTERER* clusterer,
*/
BUCKETS *MakeBuckets(DISTRIBUTION Distribution,
uint32_t SampleCount,
FLOAT64 Confidence) {
double Confidence) {
const DENSITYFUNC DensityFunction[] =
{ NormalDensity, UniformDensity, UniformDensity };
int i, j;
BUCKETS *Buckets;
FLOAT64 BucketProbability;
FLOAT64 NextBucketBoundary;
FLOAT64 Probability;
FLOAT64 ProbabilityDelta;
FLOAT64 LastProbDensity;
FLOAT64 ProbDensity;
double BucketProbability;
double NextBucketBoundary;
double Probability;
double ProbabilityDelta;
double LastProbDensity;
double ProbDensity;
uint16_t CurrentBucket;
bool Symmetrical;

Expand Down Expand Up @@ -1772,7 +1772,7 @@ BUCKETS *MakeBuckets(DISTRIBUTION Distribution,

if (Symmetrical) {
// allocate buckets so that all have approx. equal probability
BucketProbability = 1.0 / (FLOAT64) (Buckets->NumberOfBuckets);
BucketProbability = 1.0 / (double) (Buckets->NumberOfBuckets);

// distribution is symmetric so fill in upper half then copy
CurrentBucket = Buckets->NumberOfBuckets / 2;
Expand Down Expand Up @@ -1865,8 +1865,8 @@ uint16_t OptimumNumberOfBuckets(uint32_t SampleCount) {
* @note Exceptions: none
* @note History: 6/5/89, DSJ, Created.
*/
FLOAT64
ComputeChiSquared (uint16_t DegreesOfFreedom, FLOAT64 Alpha)
double
ComputeChiSquared (uint16_t DegreesOfFreedom, double Alpha)
#define CHIACCURACY 0.01
#define MINALPHA (1e-200)
{
Expand All @@ -1891,8 +1891,8 @@ ComputeChiSquared (uint16_t DegreesOfFreedom, FLOAT64 Alpha)
if (OldChiSquared == nullptr) {
OldChiSquared = NewChiStruct (DegreesOfFreedom, Alpha);
OldChiSquared->ChiSquared = Solve (ChiArea, OldChiSquared,
(FLOAT64) DegreesOfFreedom,
(FLOAT64) CHIACCURACY);
(double) DegreesOfFreedom,
(double) CHIACCURACY);
ChiWith[DegreesOfFreedom] = push (ChiWith[DegreesOfFreedom],
OldChiSquared);
}
Expand Down Expand Up @@ -1920,8 +1920,8 @@ ComputeChiSquared (uint16_t DegreesOfFreedom, FLOAT64 Alpha)
* @note Exceptions: None
* @note History: 6/4/89, DSJ, Created.
*/
FLOAT64 NormalDensity(int32_t x) {
FLOAT64 Distance;
double NormalDensity(int32_t x) {
double Distance;

Distance = x - kNormalMean;
return kNormalMagnitude * exp(-0.5 * Distance * Distance / kNormalVariance);
Expand All @@ -1936,13 +1936,13 @@ FLOAT64 NormalDensity(int32_t x) {
* @note Exceptions: None
* @note History: 6/5/89, DSJ, Created.
*/
FLOAT64 UniformDensity(int32_t x) {
static FLOAT64 UniformDistributionDensity = (FLOAT64) 1.0 / BUCKETTABLESIZE;
double UniformDensity(int32_t x) {
static double UniformDistributionDensity = (double) 1.0 / BUCKETTABLESIZE;

if ((x >= 0.0) && (x <= BUCKETTABLESIZE))
return UniformDistributionDensity;
else
return (FLOAT64) 0.0;
return (double) 0.0;
} // UniformDensity

/**
Expand All @@ -1955,7 +1955,7 @@ FLOAT64 UniformDensity(int32_t x) {
* @note Exceptions: None
* @note History: 6/5/89, DSJ, Created.
*/
FLOAT64 Integral(FLOAT64 f1, FLOAT64 f2, FLOAT64 Dx) {
double Integral(double f1, double f2, double Dx) {
return (f1 + f2) * Dx / 2.0;
} // Integral

Expand Down Expand Up @@ -2072,7 +2072,7 @@ uint16_t NormalBucket(PARAM_DESC *ParamDesc,
return 0;
if (X > BUCKETTABLESIZE - 1)
return ((uint16_t) (BUCKETTABLESIZE - 1));
return (uint16_t) floor((FLOAT64) X);
return (uint16_t) floor((double) X);
} // NormalBucket

/**
Expand Down Expand Up @@ -2107,7 +2107,7 @@ uint16_t UniformBucket(PARAM_DESC *ParamDesc,
return 0;
if (X > BUCKETTABLESIZE - 1)
return (uint16_t) (BUCKETTABLESIZE - 1);
return (uint16_t) floor((FLOAT64) X);
return (uint16_t) floor((double) X);
} // UniformBucket

/**
Expand Down Expand Up @@ -2259,10 +2259,10 @@ int ListEntryMatch(void *arg1, //ListNode
*/
void AdjustBuckets(BUCKETS *Buckets, uint32_t NewSampleCount) {
int i;
FLOAT64 AdjustFactor;
double AdjustFactor;

AdjustFactor = (((FLOAT64) NewSampleCount) /
((FLOAT64) Buckets->SampleCount));
AdjustFactor = (((double) NewSampleCount) /
((double) Buckets->SampleCount));

for (i = 0; i < Buckets->NumberOfBuckets; i++) {
Buckets->ExpectedCount[i] *= AdjustFactor;
Expand Down Expand Up @@ -2323,7 +2323,7 @@ int AlphaMatch(void *arg1, //CHISTRUCT *ChiStruct
* @note Exceptions: none
* @note History: Fri Aug 4 11:04:59 1989, DSJ, Created.
*/
CHISTRUCT *NewChiStruct(uint16_t DegreesOfFreedom, FLOAT64 Alpha) {
CHISTRUCT *NewChiStruct(uint16_t DegreesOfFreedom, double Alpha) {
CHISTRUCT *NewChiStruct;

NewChiStruct = (CHISTRUCT *) Emalloc (sizeof (CHISTRUCT));
Expand All @@ -2348,19 +2348,19 @@ CHISTRUCT *NewChiStruct(uint16_t DegreesOfFreedom, FLOAT64 Alpha) {
* @note Exceptions: none
* @note History: Fri Aug 4 11:08:59 1989, DSJ, Created.
*/
FLOAT64
double
Solve (SOLVEFUNC Function,
void *FunctionParams, FLOAT64 InitialGuess, FLOAT64 Accuracy)
void *FunctionParams, double InitialGuess, double Accuracy)
#define INITIALDELTA 0.1
#define DELTARATIO 0.1
{
FLOAT64 x;
FLOAT64 f;
FLOAT64 Slope;
FLOAT64 Delta;
FLOAT64 NewDelta;
FLOAT64 xDelta;
FLOAT64 LastPosX, LastNegX;
double x;
double f;
double Slope;
double Delta;
double NewDelta;
double xDelta;
double LastPosX, LastNegX;

x = InitialGuess;
Delta = INITIALDELTA;
Expand Down Expand Up @@ -2415,11 +2415,11 @@ void *FunctionParams, FLOAT64 InitialGuess, FLOAT64 Accuracy)
* @note Exceptions: none
* @note History: Fri Aug 4 12:48:41 1989, DSJ, Created.
*/
FLOAT64 ChiArea(CHISTRUCT *ChiParams, FLOAT64 x) {
double ChiArea(CHISTRUCT *ChiParams, double x) {
int i, N;
FLOAT64 SeriesTotal;
FLOAT64 Denominator;
FLOAT64 PowerOfx;
double SeriesTotal;
double Denominator;
double PowerOfx;

N = ChiParams->DegreesOfFreedom / 2 - 1;
SeriesTotal = 1;
Expand Down
2 changes: 1 addition & 1 deletion src/classify/cluster.h
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Original file line number Diff line number Diff line change
Expand Up @@ -51,7 +51,7 @@ typedef struct { // parameters to control clustering
FLOAT32 MaxIllegal; // max percentage of samples in a cluster which have
// more than 1 feature in that cluster
FLOAT32 Independence; // desired independence between dimensions
FLOAT64 Confidence; // desired confidence in prototypes created
double Confidence; // desired confidence in prototypes created
int MagicSamples; // Ideal number of samples in a cluster.
} CLUSTERCONFIG;

Expand Down
6 changes: 3 additions & 3 deletions src/classify/kdtree.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -168,7 +168,7 @@ void KDTreeSearch::Search(int *result_count,
for (int j = 0; j < count; j++) {
// Pre-cast to float64 as key is a template type and we have no control
// over its actual type.
distances[j] = (FLOAT32)sqrt((FLOAT64)results_.elements()[j].key);
distances[j] = (FLOAT32)sqrt((double)results_.elements()[j].key);
results[j] = results_.elements()[j].value;
}
}
Expand Down Expand Up @@ -478,8 +478,8 @@ FLOAT32 ComputeDistance(int k, PARAM_DESC *dim, FLOAT32 p1[], FLOAT32 p2[]) {
bool KDTreeSearch::BoxIntersectsSearch(FLOAT32 *lower, FLOAT32 *upper) {
FLOAT32 *query = query_point_;
// Compute the sum in higher precision.
FLOAT64 total_distance = 0.0;
FLOAT64 radius_squared =
double total_distance = 0.0;
double radius_squared =
results_.max_insertable_key() * results_.max_insertable_key();
PARAM_DESC *dim = tree_->KeyDesc;

Expand Down
6 changes: 3 additions & 3 deletions src/dict/stopper.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -465,9 +465,9 @@ int Dict::UniformCertainties(const WERD_CHOICE& word) {
float Certainty;
float WorstCertainty = MAX_FLOAT32;
float CertaintyThreshold;
FLOAT64 TotalCertainty;
FLOAT64 TotalCertaintySquared;
FLOAT64 Variance;
double TotalCertainty;
double TotalCertaintySquared;
double Variance;
FLOAT32 Mean, StdDev;
int word_length = word.length();

Expand Down

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