A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from http://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/doxyhtml/njn__localmaxstatutil_8cpp_source.html below:

NCBI C++ ToolKit: src/algo/blast/gumbel_params/njn_localmaxstatutil.cpp Source File

49 #if defined(NCBI_COMPILER_ICC) && defined(__OPTIMIZE__) \ 50  && NCBI_COMPILER_VERSION >= 1000 && NCBI_COMPILER_VERSION < 1100 51 # define NEED_ICC_OPTIMIZATION_LIMITS 1 60 const Int4

*

const

*scoreMatrix_,

61 const double

*

const

*prob_,

67  if

(dimension2_ == 0) dimension2_ = dimension_;

74  for

(

i

= 0;

i

< dimension_;

i

++)

76  for

(j = 0; j < dimension2_; j++)

78

sum += prob_ [

i

][j];

83  const double

FUDGE = 20.0;

91  for

(

i

= 0;

i

< dimension_;

i

++)

93  for

(j = 0; j < dimension2_; j++)

95  if

(scoreMatrix_ [

i

][j] <

min

)

96  min

= scoreMatrix_ [

i

][j];

97  else if

(

max

< scoreMatrix_ [

i

][j])

98  max

= scoreMatrix_ [

i

][j];

104  size_t

dim =

static_cast <size_t>

(

max

-

min

+ 1);

105  double

*p =

new double

[dim];

106  for

(

i

= 0;

i

< dim;

i

++) p [

i

] = 0.0;

108  for

(

i

= 0;

i

< dimension_;

i

++)

110  for

(j = 0; j < dimension2_; j++)

112

p [scoreMatrix_ [

i

][j] -

min

] += prob_ [

i

][j];

118  for

(s =

min

; s <=

max

; s++)

120  if

(0.0 < p [s -

min

]) ++*dim_;

123

*p_ =

new double

[*dim_];

124

*score_ =

new Int4

[*dim_];

127  for

(s =

min

; s <=

max

; s++)

129  if

(0.0 < p [s -

min

]) {

130

(*score_) [*dim_] = s;

131

(*p_) [*dim_] = p [s -

min

];

141 const Int4

*

const

*scoreMatrix_,

147  double

**

prob

= MemUtil::newMatrix <double> (dimension_, dimension_);

149  for

(

i

= 0;

i

< dimension_;

i

++)

151  for

(j = 0; j < dimension_; j++)

153  prob

[

i

][j] = q_ [

i

] * q_ [j];

161  flatten

(dimension_, scoreMatrix_,

prob

, &dim, &score, &p);

163

MemUtil::deleteMatrix <double> (

prob

, dimension_, dimension_);

prob

= 0;

168  delete

[] score; score = 0;

193 #ifdef NEED_ICC_OPTIMIZATION_LIMITS 194 # pragma optimization_level 1 200

sum +=

n_prob

[

i

] * exp (x_ *

static_cast <double>

(

n_score

[

i

]));

222  const double

FACTOR = 0.5;

237  for

(

size_t i

= 0;

i

< dimension_;

i

++) {

238  mu

+=

static_cast <double>

(score_ [

i

]) * prob_ [

i

];

267  if

(lambda_ == 0.0) lambda_ =

lambda

(dimension_, score_, prob_);

278  return muPowerAssoc

(dimension_, score_, prob_, lambda_);

290  if

(lambda_ == 0.0) lambda_ =

lambda

(dimension_, score_, prob_);

308  if

(thetaMin_ == 0.0) thetaMin_ =

thetaMin

(dimension_, score_, prob_, lambda_);

313 #ifdef NEED_ICC_OPTIMIZATION_LIMITS 314 # pragma optimization_level 1 324  for

(

size_t i

= 0;

i

< dimension_;

i

++) {

325

sum += prob_ [

i

] * exp (theta_ *

static_cast <double>

(score_ [

i

]));

337  for

(

i

= 0;

i

< dimension_;

i

++) {

338  delta

= Integer::euclidAlgorithm <Int4> (

delta

, score_ [

i

]);

348  double

del =

static_cast <double>

(

delta

(dimension_, score_));

349  return

(1.0 - exp (-lambda_ * del)) / del;

356  return n_morgue

< oldValue_ ? oldValue_ +

n_score

[state_] : oldValue_;

371 double

*eOneMinusExpSumAlpha_,

376 double

*eOneMinusExpSumAlphaW_,

400  double

mu0 = 0.0 == mu0_ ?

mu

(dimension_, score_, prob_) : mu0_;

403  double

lambda0 = 0.0 == lambda0_ ?

lambda

(dimension_, score_, prob_) : lambda0_;

405  if

(lambda_ == 0.0) lambda_ = lambda0;

408  double

muAssoc0 = 0.0 == muAssoc0_ ?

muAssoc

(dimension_, score_, prob_, lambda0) : muAssoc0_;

411  double

thetaMin0 = 0.0 == thetaMin0_ ?

thetaMin

(dimension_, score_, prob_, lambda0) : thetaMin0_;

413  double

rMin0 = 0.0 == rMin0_ ?

rMin

(dimension_, score_, prob_, lambda0, thetaMin0) : rMin0_;

414  _ASSERT

(0.0 < rMin0 && rMin0 < 1.0);

418  const Int4

ITER =

static_cast <Int4>

(endW_) < ITER_MIN ? ITER_MIN :

static_cast <Int4>

(endW_);

422  Int4

entry = isStrict_ ? -1 : 0;

428  if

(time_ > 0.0) Sls::alp_data::get_current_time (time0);

432  if

(pAlphaW_) pAlphaW_ [0] = 0.0;

433  if

(eOneMinusExpSumAlphaW_) eOneMinusExpSumAlphaW_ [0] = 0.0;

439  if

(eSumAlpha_) *eSumAlpha_ = 0.0;

440  if

(eOneMinusExpSumAlpha_) *eOneMinusExpSumAlpha_ = 0.0;

442  for

(

size_t

w = 1; w < static_cast <size_t> (ITER); w++) {

446  if

(pAlphaW_) pAlphaW_ [w] = 0.0;

447  if

(eOneMinusExpSumAlphaW_) eOneMinusExpSumAlphaW_ [w] = 0.0;

450  if

(pAlphaW_) pAlphaW_ [w] += dynProgProb.

getProb

(

value

);

451  if

(eOneMinusExpSumAlphaW_) eOneMinusExpSumAlphaW_ [w] +=

453

(1.0 - exp (lambda_ *

static_cast <double>

(

value

)));

458  if

(eSumAlpha_) *eSumAlpha_ += dynProgProb.

getProb

(

value

) *

static_cast <double>

(

value

);

459  if

(eOneMinusExpSumAlpha_) *eOneMinusExpSumAlpha_ += dynProgProb.

getProb

(

value

) *

460

(1.0 - exp (lambda_ *

static_cast <double>

(

value

)));

471

Sls::alp_data::get_current_time (time1);

472  if

(time1 - time0 > time_)

474

*terminated_ =

true

;

482  if

(eSumAlpha_) *eSumAlpha_ += dynProgProb.

getProb

(

value

) *

static_cast <double>

(

value

);

483  if

(eOneMinusExpSumAlpha_) *eOneMinusExpSumAlpha_ += dynProgProb.

getProb

(

value

) *

484

(1.0 - exp (lambda_ *

static_cast <double>

(

value

)));

495  const double

FUDGE = 2.0;

505 double

*eOneMinusExpSumAlpha_,

516

eSumAlpha_, eOneMinusExpSumAlpha_, isStrict_, 0.0, 0, 0, 0,

517

lambda0_, mu0_, muAssoc0_, thetaMin0_, rMin0_, time_, terminated_);

525  for

(

size_t i

= 0;

i

< dimension_;

i

++) {

526  if

(prob_ [

i

] < 0.0 || 1.0 < prob_ [

i

])

return false

;

536  for

(

size_t i

= 1;

i

< dimension_;

i

++) {

537  if

(score_ [

i

] <= score_ [

i

- 1])

return false

;

550  if

(!

isProbDist

(dimension_, prob_))

return false

;

551  if

(0.0 <=

mu

(dimension_, score_, prob_))

return false

;

552  if

(score_ [dimension_ - 1] <= 0.0)

return false

;

virtual void setValueFct(ValueFct *valueFct_)

virtual double getProb(Int4 value_) const

virtual double getProbLost() const

virtual Int4 getValueUpper() const

int32_t Int4

4-byte (32-bit) signed integer

Namespace for mathematical applications.

const GenericPointer< typename T::ValueType > T2 value

bool relApprox(T x_, T y_, T eps_)

Real integerPower(Real x, Int n)

Int4 n_step(Int4 oldValue_, size_t state_)

double n_totalProbAssoc(double x_)

double n_meanPowerAssoc(double x_, Int4 power_=1L)

void n_setParameters(size_t dimension_, const Int4 *score_, const double *prob_, Int4 entry_=0)

Int4 n_bury(Int4 oldValue_, size_t state_)

void n_bracket(double *p_, double *q_)

double n_meanAssoc(double x_)

double muAssoc(size_t dimension_, const Int4 *score_, const double *prob_, double lambda_=0.0)

Int4 delta(size_t dimension_, const Int4 *score_)

double mu(size_t dimension_, const Int4 *score_, const double *prob_)

void descendingLadderEpochRepeat(size_t dimension_, const Int4 *score_, const double *prob_, double *eSumAlpha_=0, double *eOneMinusExpSumAlpha_=0, bool isStrict_=false, double lambda_=0.0, size_t endW_=0, double *pAlphaW_=0, double *eOneMinusExpSumAlphaW_=0, double lambda0_=0.0, double mu0_=0.0, double muAssoc0_=0.0, double thetaMin0_=0.0, double rMin0_=0.0, double time_=0.0, bool *terminated_=0)

double r(size_t dimension_, const Int4 *score_, const double *prob_, double theta_)

void flatten(size_t dimension_, const Int4 *const *scoreMatrix_, const double *const *prob_, size_t *dim_, Int4 **score_, double **p_, size_t dimension2_=0)

double lambda(size_t dimMatrix_, const Int4 *const *scoreMatrix_, const double *q_)

void descendingLadderEpoch(size_t dimension_, const Int4 *score_, const double *prob_, double *eSumAlpha_=0, double *eOneMinusExpSumAlpha_=0, bool isStrict_=false, double lambda0_=0.0, double mu0_=0.0, double muAssoc0_=0.0, double thetaMin0_=0.0, double rMin0_=0.0, double time_=0.0, bool *terminated_=0)

double rMin(size_t dimension_, const Int4 *score_, const double *prob_, double lambda_=0.0, double thetaMin_=0.0)

double thetaMinusDelta(double lambda_, size_t dimension_, const Int4 *score_)

bool isProbDist(size_t dimension_, const double *prob_)

double muPowerAssoc(size_t dimension_, const Int4 *score_, const double *prob_, double lambda_=0.0, Int4 power_=1)

bool isScoreIncreasing(size_t dimension_, const Int4 *score_)

double thetaMin(size_t dimension_, const Int4 *score_, const double *prob_, double lambda_=0.0)

bool isLogarithmic(size_t dimension_, const Int4 *score_, const double *prob_)

double bisection(double y_, double(*f_)(double, const T &), const T &param_, double p_, double q_, double tol_, double rtol_, Int4 *itmax_)

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4