Visual C++ .NET - Funcion de c++ a R software

Hola, no tengo experiencia en programacion de C. Solo algunas cosas en el Software R de estadistica. Sobre todo la programacion de algunas funciones.

Tengo una funcion que por lo que me dijeron esta en C++ (yo no lo se) y necesito saber que hace en cada paso para poder pasarla a R.

Alguien me podra dat una mano

Pego la funcion. Despues tambien tengo el enlace a la pagina y calculadora on linde de dicha funcion.

gracias.

Female
/*
* Copyright 2017 ClinRisk Ltd.
*
* This file is part of QRISK3-2017 (https://qrisk.org).
*
* QRISK3-2017 is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* QRISK3-2017 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with QRISK3-2017. If not, see http://www.gnu.org/licenses/.
*
* Additional terms
*
* The following disclaimer must be held together with any risk score score generated by this code.
* If the score is displayed, then this disclaimer must be displayed or otherwise be made easily accessible, e.g. by a prominent link alongside it.
* The initial version of this file, to be found at http://svn.clinrisk.co.uk/opensource/qrisk2, faithfully implements QRISK3-2017.
* ClinRisk Ltd. have released this code under the GNU Lesser General Public License to enable others to implement the algorithm faithfully.
* However, the nature of the GNU Lesser General Public License is such that we cannot prevent, for example, someone accidentally
* altering the coefficients, getting the inputs wrong, or just poor programming.
* ClinRisk Ltd. stress, therefore, that it is the responsibility of the end user to check that the source that they receive produces the same
* results as the original code found at https://qrisk.org.
* Inaccurate implementations of risk scores can lead to wrong patients being given the wrong treatment.
*
* End of additional terms
*
*/


static double cvd_female_raw(
int age,int b_AF,int b_atypicalantipsy,int b_corticosteroids,int b_migraine,int b_ra,int b_renal,int b_semi,int b_sle,int b_treatedhyp,int b_type1,int b_type2,double bmi,int ethrisk,int fh_cvd,double rati,double sbp,double sbps5,int smoke_cat,int surv,double town
)
{
double survivor[16] = {
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0.988876402378082,
0,
0,
0,
0,
0
};

/* The conditional arrays */

double Iethrisk[10] = {
0,
0,
0.2804031433299542500000000,
0.5629899414207539800000000,
0.2959000085111651600000000,
0.0727853798779825450000000,
-0.1707213550885731700000000,
-0.3937104331487497100000000,
-0.3263249528353027200000000,
-0.1712705688324178400000000
};
double Ismoke[5] = {
0,
0.1338683378654626200000000,
0.5620085801243853700000000,
0.6674959337750254700000000,
0.8494817764483084700000000
};

/* Applying the fractional polynomial transforms */
/* (which includes scaling) */

double dage = age;
dage=dage/10;
double age_1 = pow(dage,-2);
double age_2 = dage;
double dbmi = bmi;
dbmi=dbmi/10;
double bmi_1 = pow(dbmi,-2);
double bmi_2 = pow(dbmi,-2)*log(dbmi);

/* Centring the continuous variables */

age_1 = age_1 - 0.053274843841791;
age_2 = age_2 - 4.332503318786621;
bmi_1 = bmi_1 - 0.154946178197861;
bmi_2 = bmi_2 - 0.144462317228317;
rati = rati - 3.476326465606690;
sbp = sbp - 123.130012512207030;
sbps5 = sbps5 - 9.002537727355957;
town = town - 0.392308831214905;

/* Start of Sum */
double a=0;

/* The conditional sums */

a += Iethrisk[ethrisk];
a += Ismoke[smoke_cat];

/* Sum from continuous values */

a += age_1 * -8.1388109247726188000000000;
a += age_2 * 0.7973337668969909800000000;
a += bmi_1 * 0.2923609227546005200000000;
a += bmi_2 * -4.1513300213837665000000000;
a += rati * 0.1533803582080255400000000;
a += sbp * 0.0131314884071034240000000;
a += sbps5 * 0.0078894541014586095000000;
a += town * 0.0772237905885901080000000;

/* Sum from boolean values */

a += b_AF * 1.5923354969269663000000000;
a += b_atypicalantipsy * 0.2523764207011555700000000;
a += b_corticosteroids * 0.5952072530460185100000000;
a += b_migraine * 0.3012672608703450000000000;
a += b_ra * 0.2136480343518194200000000;
a += b_renal * 0.6519456949384583300000000;
a += b_semi * 0.1255530805882017800000000;
a += b_sle * 0.7588093865426769300000000;
a += b_treatedhyp * 0.5093159368342300400000000;
a += b_type1 * 1.7267977510537347000000000;
a += b_type2 * 1.0688773244615468000000000;
a += fh_cvd * 0.4544531902089621300000000;

/* Sum from interaction terms */

a += age_1 * (smoke_cat==1) * -4.7057161785851891000000000;
a += age_1 * (smoke_cat==2) * -2.7430383403573337000000000;
a += age_1 * (smoke_cat==3) * -0.8660808882939218200000000;
a += age_1 * (smoke_cat==4) * 0.9024156236971064800000000;
a += age_1 * b_AF * 19.9380348895465610000000000;
a += age_1 * b_corticosteroids * -0.9840804523593628100000000;
a += age_1 * b_migraine * 1.7634979587872999000000000;
a += age_1 * b_renal * -3.5874047731694114000000000;
a += age_1 * b_sle * 19.6903037386382920000000000;
a += age_1* b_treatedhyp * 11.8728097339218120000000000;
a += age_1 * b_type1 * -1.2444332714320747000000000;
a += age_1 * b_type2 * 6.8652342000009599000000000;
a += age_1 * bmi_1 * 23.8026234121417420000000000;
a += age_1 * bmi_2 * -71.1849476920870070000000000;
a += age_1 * fh_cvd * 0.9946780794043512700000000;
a += age_1 * sbp * 0.0341318423386154850000000;
a += age_1 * town * -1.0301180802035639000000000;
a += age_2 * (smoke_cat==1) * -0.0755892446431930260000000;
a += age_2 * (smoke_cat==2) * -0.1195119287486707400000000;
a += age_2 * (smoke_cat==3) * -0.1036630639757192300000000;
a += age_2 * (smoke_cat==4) * -0.1399185359171838900000000;
a += age_2 * b_AF * -0.0761826510111625050000000;
a += age_2 * b_corticosteroids * -0.1200536494674247200000000;
a += age_2 * b_migraine * -0.0655869178986998590000000;
a += age_2 * b_renal * -0.2268887308644250700000000;
a += age_2 * b_sle * 0.0773479496790162730000000;
a += age_2* b_treatedhyp * 0.0009685782358817443600000;
a += age_2 * b_type1 * -0.2872406462448894900000000;
a += age_2 * b_type2 * -0.0971122525906954890000000;
a += age_2 * bmi_1 * 0.5236995893366442900000000;
a += age_2 * bmi_2 * 0.0457441901223237590000000;
a += age_2 * fh_cvd * -0.0768850516984230380000000;
a += age_2 * sbp * -0.0015082501423272358000000;
a += age_2 * town * -0.0315934146749623290000000;

/* Calculate the score itself */
double score = 100.0 * (1 - pow(survivor[surv], exp(a)) );
return score;
}
Male
/*
* Copyright 2017 ClinRisk Ltd.
*
* This file is part of QRISK3-2017 (https://qrisk.org).
*
* QRISK3-2017 is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* QRISK3-2017 is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with QRISK3-2017. If not, see http://www.gnu.org/licenses/.
*
* Additional terms
*
* The following disclaimer must be held together with any risk score score generated by this code.
* If the score is displayed, then this disclaimer must be displayed or otherwise be made easily accessible, e.g. by a prominent link alongside it.
* The initial version of this file, to be found at http://svn.clinrisk.co.uk/opensource/qrisk2, faithfully implements QRISK3-2017.
* ClinRisk Ltd. have released this code under the GNU Lesser General Public License to enable others to implement the algorithm faithfully.
* However, the nature of the GNU Lesser General Public License is such that we cannot prevent, for example, someone accidentally
* altering the coefficients, getting the inputs wrong, or just poor programming.
* ClinRisk Ltd. stress, therefore, that it is the responsibility of the end user to check that the source that they receive produces the same
* results as the original code found at https://qrisk.org.
* Inaccurate implementations of risk scores can lead to wrong patients being given the wrong treatment.
*
* End of additional terms
*
*/

static double cvd_male_raw(
int age,int b_AF,int b_atypicalantipsy,int b_corticosteroids,int b_impotence2,int b_migraine,int b_ra,int b_renal,int b_semi,int b_sle,int b_treatedhyp,int b_type1,int b_type2,double bmi,int ethrisk,int fh_cvd,double rati,double sbp,double sbps5,int smoke_cat,int surv,double town
)
{
double survivor[16] = {
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0.977268040180206,
0,
0,
0,
0,
0
};

/* The conditional arrays */

double Iethrisk[10] = {
0,
0,
0.2771924876030827900000000,
0.4744636071493126800000000,
0.5296172991968937100000000,
0.0351001591862990170000000,
-0.3580789966932791900000000,
-0.4005648523216514000000000,
-0.4152279288983017300000000,
-0.2632134813474996700000000
};
double Ismoke[5] = {
0,
0.1912822286338898300000000,
0.5524158819264555200000000,
0.6383505302750607200000000,
0.7898381988185801900000000
};

/* Applying the fractional polynomial transforms */
/* (which includes scaling) */

double dage = age;
dage=dage/10;
double age_1 = pow(dage,-1);
double age_2 = pow(dage,3);
double dbmi = bmi;
dbmi=dbmi/10;
double bmi_2 = pow(dbmi,-2)*log(dbmi);
double bmi_1 = pow(dbmi,-2);

/* Centring the continuous variables */

age_1 = age_1 - 0.234766781330109;
age_2 = age_2 - 77.284080505371094;
bmi_1 = bmi_1 - 0.149176135659218;
bmi_2 = bmi_2 - 0.141913309693336;
rati = rati - 4.300998687744141;
sbp = sbp - 128.571578979492190;
sbps5 = sbps5 - 8.756621360778809;
town = town - 0.526304900646210;

/* Start of Sum */
double a=0;

/* The conditional sums */

a += Iethrisk[ethrisk];
a += Ismoke[smoke_cat];

/* Sum from continuous values */

a += age_1 * -17.8397816660055750000000000;
a += age_2 * 0.0022964880605765492000000;
a += bmi_1 * 2.4562776660536358000000000;
a += bmi_2 * -8.3011122314711354000000000;
a += rati * 0.1734019685632711100000000;
a += sbp * 0.0129101265425533050000000;
a += sbps5 * 0.0102519142912904560000000;
a += town * 0.0332682012772872950000000;

/* Sum from boolean values */

a += b_AF * 0.8820923692805465700000000;
a += b_atypicalantipsy * 0.1304687985517351300000000;
a += b_corticosteroids * 0.4548539975044554300000000;
a += b_impotence2 * 0.2225185908670538300000000;
a += b_migraine * 0.2558417807415991300000000;
a += b_ra * 0.2097065801395656700000000;
a += b_renal * 0.7185326128827438400000000;
a += b_semi * 0.1213303988204716400000000;
a += b_sle * 0.4401572174457522000000000;
a += b_treatedhyp * 0.5165987108269547400000000;
a += b_type1 * 1.2343425521675175000000000;
a += b_type2 * 0.8594207143093222100000000;
a += fh_cvd * 0.5405546900939015600000000;

/* Sum from interaction terms */

a += age_1 * (smoke_cat==1) * -0.2101113393351634600000000;
a += age_1 * (smoke_cat==2) * 0.7526867644750319100000000;
a += age_1 * (smoke_cat==3) * 0.9931588755640579100000000;
a += age_1 * (smoke_cat==4) * 2.1331163414389076000000000;
a += age_1 * b_AF * 3.4896675530623207000000000;
a += age_1 * b_corticosteroids * 1.1708133653489108000000000;
a += age_1 * b_impotence2 * -1.5064009857454310000000000;
a += age_1 * b_migraine * 2.3491159871402441000000000;
a += age_1 * b_renal * -0.5065671632722369400000000;
a += age_1* b_treatedhyp * 6.5114581098532671000000000;
a += age_1 * b_type1 * 5.3379864878006531000000000;
a += age_1 * b_type2 * 3.6461817406221311000000000;
a += age_1 * bmi_1 * 31.0049529560338860000000000;
a += age_1 * bmi_2 * -111.2915718439164300000000000;
a += age_1 * fh_cvd * 2.7808628508531887000000000;
a += age_1 * sbp * 0.0188585244698658530000000;
a += age_1 * town * -0.1007554870063731000000000;
a += age_2 * (smoke_cat==1) * -0.0004985487027532612100000;
a += age_2 * (smoke_cat==2) * -0.0007987563331738541400000;
a += age_2 * (smoke_cat==3) * -0.0008370618426625129600000;
a += age_2 * (smoke_cat==4) * -0.0007840031915563728900000;
a += age_2 * b_AF * -0.0003499560834063604900000;
a += age_2 * b_corticosteroids * -0.0002496045095297166000000;
a += age_2 * b_impotence2 * -0.0011058218441227373000000;
a += age_2 * b_migraine * 0.0001989644604147863100000;
a += age_2 * b_renal * -0.0018325930166498813000000;
a += age_2* b_treatedhyp * 0.0006383805310416501300000;
a += age_2 * b_type1 * 0.0006409780808752897000000;
a += age_2 * b_type2 * -0.0002469569558886831500000;
a += age_2 * bmi_1 * 0.0050380102356322029000000;
a += age_2 * bmi_2 * -0.0130744830025243190000000;
a += age_2 * fh_cvd * -0.0002479180990739603700000;
a += age_2 * sbp * -0.0000127187419158845700000;
a += age_2 * town * -0.0000932996423232728880000;

/* Calculate the score itself */
double score = 100.0 * (1 - pow(survivor[surv], exp(a)) );
return score;
}

he revisado tu codigo y ya ordenado puedo mostrartelo pero realmente lo que haces es inicializar variables y vectores que son los identidad para los casos de estudio que pudieras indicarle al momento de usar las funciones aqui descritas, mas de eso no pudiera indicarte que hace porque hay que correrlo sabiendo como usar dichas funciones y observando el comportamiento si es acorde a lo esperado.
por otro lado le comento que a simple vista pareciera que este codigo estima y pondera un grado de incidencia o variables que pudiera afectar o determinar un valor promediado al cual utiliza como estandar. asi que consluyo que se debe estar basando en un estandar de calculo por varianzas predefinidas.

• codigo.rar(72,4 KB)