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Commit 2eb0166e authored by Dmitry.Shahtanov's avatar Dmitry.Shahtanov Committed by Alexander.Trofimov
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fix: Bug 21102 - Некорректный расчет нормальной функции распределения NORMDIST 

git-svn-id: svn://192.168.3.15/activex/AVS/Sources/TeamlabOffice/trunk/OfficeWeb@50498 954022d7-b5bf-4e40-9824-e11837661b57
parent ae3e99e6
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Showing with 232 additions and 49 deletions
Excel/model/FormulaObjects/parserFormula.js
View file @ 2eb0166e
......@@ -1195,7 +1195,7 @@ function cNumber( val ) {
}
extend( cNumber, cBaseType );
cNumber.prototype.getValue = function () {
return this.value.toFixed( cExcelSignificantDigits ) - 0;
return this.value//.toFixed( cExcelSignificantDigits ) - 0;
};
cNumber.prototype.tocString = function () {
return new cString( "" + this.value );
......@@ -1510,6 +1510,7 @@ cArea.prototype.foreach2 = function ( action ) {
if ( r ) {
r._foreach2( function ( _cell ) {
var val;
if ( _cell ) {
switch ( _cell.getType() ) {
case CellValueType.Number:
_cell.getValueWithoutFormat() == "" ? val = new cEmpty() : val = new cNumber( _cell.getValueWithoutFormat() )
......@@ -1530,6 +1531,9 @@ cArea.prototype.foreach2 = function ( action ) {
else
val = checkTypeCell( "" + _cell.getValueWithoutFormat() );
}
}
else
val = new cEmpty()
action(val);
} );
}
......@@ -1915,6 +1919,7 @@ cArea3D.prototype.foreach2 = function ( action ) {
if ( _r[i] )
_r[i]._foreach2( function ( _cell ) {
var val;
if(_cell){
switch ( _cell.getType() ) {
case CellValueType.Number:
_cell.getValueWithoutFormat() == "" ? val = new cEmpty() : val = new cNumber( _cell.getValueWithoutFormat() )
......@@ -1935,6 +1940,9 @@ cArea3D.prototype.foreach2 = function ( action ) {
else
val = checkTypeCell( "" + _cell.getValueWithoutFormat() );
}
}
else
val = new cEmpty()
action(val);
} );
}
......@@ -3084,7 +3092,7 @@ parserFormula.prototype = {
}
function parseNum( str ) {
if ( str.indexOf( "x" ) > -1 )//исключаем запись числа в 16-ричной форме из числа.
if ( str.indexOf( "x" ) > -1 || str == "" )//исключаем запись числа в 16-ричной форме из числа.
return false;
return !isNaN( str );
}
......@@ -3424,3 +3432,173 @@ function getLogGamma( fZ ) {
return Math.log( lcl_GetGammaHelper( fZ + 1 ) / fZ );
return lcl_GetLogGammaHelper( fZ + 2 ) - Math.log( fZ + 1 ) - Math.log( fZ );
}
function lcl_Erf0065( x ) {
var pn = [
1.12837916709551256,
1.35894887627277916E-1,
4.03259488531795274E-2,
1.20339380863079457E-3,
6.49254556481904354E-5
],
qn = [
1.00000000000000000,
4.53767041780002545E-1,
8.69936222615385890E-2,
8.49717371168693357E-3,
3.64915280629351082E-4
];
var fPSum = 0.0, fQSum = 0.0, fXPow = 1.0, fVal;
for ( var i = 0; i <= 4; ++i ) {
fPSum += pn[i] * fXPow;
fQSum += qn[i] * fXPow;
fXPow *= x * x;
}
return fVal = x * fPSum / fQSum;
}
/** Approximation algorithm for erfc for 0.65 < x < 6.0. */
function lcl_Erfc0600( x ) {
var fPSum = 0.0,
fQSum = 0.0,
fXPow = 1.0, pn, qn,
fVal;
if ( x < 2.2 ) {
var pn22 = [
9.99999992049799098E-1,
1.33154163936765307,
8.78115804155881782E-1,
3.31899559578213215E-1,
7.14193832506776067E-2,
7.06940843763253131E-3
],
qn22 = [
1.00000000000000000,
2.45992070144245533,
2.65383972869775752,
1.61876655543871376,
5.94651311286481502E-1,
1.26579413030177940E-1,
1.25304936549413393E-2
];
pn = pn22;
qn = qn22;
}
else /* if ( x < 6.0 ) this is true, but the compiler does not know */
{
var pn60 = [
9.99921140009714409E-1,
1.62356584489366647,
1.26739901455873222,
5.81528574177741135E-1,
1.57289620742838702E-1,
2.25716982919217555E-2
],
qn60 = [
1.00000000000000000,
2.75143870676376208,
3.37367334657284535,
2.38574194785344389,
1.05074004614827206,
2.78788439273628983E-1,
4.00072964526861362E-2
];
pn = pn60;
qn = qn60;
}
for ( var i = 0; i < 6; ++i ) {
fPSum += pn[i] * fXPow;
fQSum += qn[i] * fXPow;
fXPow *= x;
}
fQSum += qn[6] * fXPow;
return fVal = Math.exp( -1.0 * x * x ) * fPSum / fQSum;
}
/** Approximation algorithm for erfc for 6.0 < x < 26.54 (but used for all
x > 6.0). */
function lcl_Erfc2654( x ) {
var pn = [
5.64189583547756078E-1,
8.80253746105525775,
3.84683103716117320E1,
4.77209965874436377E1,
8.08040729052301677
],
qn = [
1.00000000000000000,
1.61020914205869003E1,
7.54843505665954743E1,
1.12123870801026015E2,
3.73997570145040850E1
];
var fPSum = 0.0, fQSum = 0.0, fXPow = 1.0, fVal;
for ( var i = 0; i <= 4; ++i ) {
fPSum += pn[i] * fXPow;
fQSum += qn[i] * fXPow;
fXPow /= x * x;
}
return fVal = Math.exp( -1.0 * x * x ) * fPSum / (x * fQSum);
}
function rtl_math_erf( x ) {
if ( x == 0.0 )
return 0.0;
var bNegative = false;
if ( x < 0.0 ) {
x = Math.abs( x );
bNegative = true;
}
var fErf = 1.0;
if ( x < 1.0e-10 )
fErf = parceFloat( x * 1.1283791670955125738961589031215452 );
else if ( x < 0.65 )
fErf = lcl_Erf0065( x );
else
fErf = 1.0 - rtl_math_erfc( x );
if ( bNegative )
fErf *= -1.0;
return fErf;
}
function rtl_math_erfc( x )
{
if ( x == 0.0 )
return 1.0;
var bNegative = false;
if ( x < 0.0 )
{
x = Math.abs( x );
bNegative = true;
}
var fErfc = 0.0;
if ( x >= 0.65 )
{
if ( x < 6.0 )
fErfc = lcl_Erfc0600( x );
else
fErfc = lcl_Erfc2654( x );
}
else
fErfc = 1.0 - rtl_math_erf( x );
if ( bNegative )
fErfc = 2.0 - fErfc;
return fErfc;
}
function integralPhi( x )
{ // Using gauss(x)+0.5 has severe cancellation errors for x<-4
return 0.5 * rtl_math_erfc(-x * 0.7071067811865475); // * 1/sqrt(2)
}
\ No newline at end of file
Excel/model/FormulaObjects/statisticalFunctions.js
View file @ 2eb0166e
......@@ -209,7 +209,7 @@ cFormulaFunction.Statistical = {
r.setArgumentsMin( 2 );
r.setArgumentsMax( 3 );
r.Calculate = function ( arg ) {
var arg0 = arg[0], arg1 = arg[1], arg2 = arg[2] ? arg[2] : arg[0], _sum = 0, _count = 0, valueForSearching, regexpSearch;
var arg0 = arg[0], arg1 = arg[1], arg2 = arg[2] ? arg[2] : arg[0], _sum = 0, _count = 0, valueForSearching;
if ( !(arg0 instanceof cRef || arg0 instanceof cRef3D || arg0 instanceof cArea) ) {
return this.value = new cError( cErrorType.wrong_value_type );
}
......@@ -670,7 +670,7 @@ cFormulaFunction.Statistical = {
r.setArgumentsMin( 2 );
r.setArgumentsMax( 2 );
r.Calculate = function ( arg ) {
var arg0 = arg[0], arg1 = arg[1], _count = 0, valueForSearching, regexpSearch;
var arg0 = arg[0], arg1 = arg[1], _count = 0, valueForSearching;
if ( !(arg0 instanceof cRef || arg0 instanceof cRef3D || arg0 instanceof cArea || arg0 instanceof cArea3D) ) {
return this.value = new cError( cErrorType.wrong_value_type );
}
......@@ -729,7 +729,7 @@ cFormulaFunction.Statistical = {
}
arg1 = arg1.toString();
var operators = new RegExp( "^ *[<=> ]+ *" ), searchOperators = new RegExp( "^ *[*?]" ), search, oper, val,
var operators = new RegExp( "^ *[<=> ]+ *" ), search, oper, val,
match = arg1.match( operators );
if ( match ) {
......@@ -741,10 +741,14 @@ cFormulaFunction.Statistical = {
}
valueForSearching = parseNum( search ) ? new cNumber( search ) : new cString( search );
if ( arg0 instanceof cArea ) {
val = arg0.getValue();
arg0.foreach2(function(_val){
// _val
_count += matching( _val, valueForSearching, oper );
})
/*val = arg0.getValue();
for ( var i = 0; i < val.length; i++ ) {
_count += matching( val[i], valueForSearching, oper );
}
}*/
}
else if ( arg0 instanceof cArea3D ) {
val = arg0.getValue();
......@@ -2464,12 +2468,13 @@ cFormulaFunction.Statistical = {
var arg0 = arg[0], arg1 = arg[1], arg2 = arg[2], arg3 = arg[3];
function normdist( x, mue, sigma, kum ){
if ( sigma <= 0 || x < 0 || x > 1)
if ( sigma <= 0 )
return new cError( cErrorType.not_numeric );
else if ( kum == false )
return new cNumber( phi( (x - mue) / sigma ) / sigma );
if ( kum )
return new cNumber( integralPhi((x-mue)/sigma) );
else
return new cNumber( 0.5 + gauss( (x - mue) / sigma ) );
return new cNumber( phi( (x - mue) / sigma ) / sigma );
}
......
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