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add statistical functions to numparam and nutmeg parsers

This commit is contained in:
h_vogt 2010-12-28 19:01:30 +00:00
parent 7632ca3ef3
commit 1ea76af678
9 changed files with 251 additions and 82 deletions
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9
ChangeLog
View File

@ -1,3 +1,12 @@
2010-12-28 Holger Vogt
* xpressn.c, cmath2.c, cmath2.h, randnumb.c, parse.c,
examples/Monte_Carlo/MonteCarlo.sp:
add poisson and exponential distribution to nutmeg parser,
add gauss, aunif, unif, limit to numparam parser
* spiceif.c: remove bug in experimental_code
* control.c: no i/o redirection in define command
(so > or < may be used safely)
2010-12-27 Robert Larice
* tests/bsim3soi/inv_dc.cir ,
* tests/bsim3soi/inv_tr.cir ,

26
examples/Monte_Carlo/MonteCarlo.sp
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@ -17,6 +17,20 @@ R2 0 OUT 141
set scratch=$curplot $ store its name to 'scratch'
setplot $scratch $ make 'scratch' the active plot
let bwh=unitvec(mc_runs) $ create a vector in plot 'scratch' to store bandwidth data
* define distributions for random numbers:
* unif: uniform distribution, deviation relativ to nominal value
* aunif: uniform distribution, deviation absolut
* gauss: Gaussian distribution, deviation relativ to nominal value
* agauss: Gaussian distribution, deviation absolut
* limit: if unif. distributed value >=0 then add +avar to nom, else -avar
define unif(nom, rvar) (nom + (nom*rvar) * sunif(0))
define aunif(nom, avar) (nom + avar * sunif(0))
define gauss(nom, rvar, sig) (nom + (nom*rvar)/sig * sgauss(0))
define agauss(nom, avar, sig) (nom + avar/sig * sgauss(0))
* define limit(nom, avar) (nom + ((sgauss(0) ge 0) ? avar : -avar))
define limit(nom, avar) (nom + ((sgauss(0) >= 0) ? avar : -avar))
*
*
dowhile run < mc_runs $ loop starts here
*
@ -24,23 +38,13 @@ R2 0 OUT 141
* alter c1 = aunif(1e-09, 100e-12)
* alter c1 = gauss(1e-09, 0.1, 3)
* alter c1 = agauss(1e-09, 100e-12, 3)
*
* define distributions for random numbers:
* unif: uniform distribution, deviation relativ to nominal value
* aunif: uniform distribution, deviation absolut
* gauss: Gaussian distribution, deviation relativ to nominal value
* agauss: Gaussian distribution, deviation absolut
define unif(nom, var) (nom + (nom*var) * sunif(0))
define aunif(nom, avar) (nom + avar * sunif(0))
define gauss(nom, var, sig) (nom + (nom*var)/sig * sgauss(0))
define agauss(nom, avar, sig) (nom + avar/sig * sgauss(0))
*
alter c1 = unif(1e-09, 0.1)
alter l1 = unif(10e-06, 0.1)
alter c2 = unif(1e-09, 0.1)
alter l2 = unif(10e-06, 0.1)
alter l3 = unif(40e-06, 0.1)
alter c3 = unif(250e-12, 0.1)
alter c3 = limit(250e-12, 25e-12)
*
ac oct 100 250K 10Meg
*

3
src/frontend/control.c
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@ -56,7 +56,8 @@ int stackp = 0;
* destroyed safely
*/
static char *noredirect[] = { "stop", NULL } ; /* Only one?? */
/* no redirection after the following commands (we may need more to add here!) */
static char *noredirect[] = { "stop", "define", NULL } ;
static struct control *

47
src/frontend/numparam/xpressn.c
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@ -17,7 +17,8 @@
#include "compatmode.h"
/* random numbers in /maths/misc/randnumb.c */
extern double gauss(void);
extern double gauss0(void);
extern double drand(void);
void debugwarn(tdico *d, char *s);
@ -46,11 +47,37 @@ ternary_fcn (int conditional, double if_value, double else_value)
static double
agauss (double nominal_val, double variation, double sigma)
agauss (double nominal_val, double abs_variation, double sigma)
{
double stdvar;
stdvar=variation/sigma;
return (nominal_val+stdvar*gauss());
stdvar=abs_variation/sigma;
return (nominal_val+stdvar*gauss0());
}
static double
gauss (double nominal_val, double rel_variation, double sigma)
{
double stdvar;
stdvar=nominal_val * rel_variation / sigma;
return (nominal_val + stdvar * gauss0());
}
static double
unif (double nominal_val, double rel_variation)
{
return (nominal_val + nominal_val * rel_variation * drand());
}
static double
aunif (double nominal_val, double abs_variation)
{
return (nominal_val + abs_variation * drand());
}
static double
limit (double nominal_val, double abs_variation)
{
return (nominal_val + (drand() > 0 ? abs_variation : -1. * abs_variation));
}
static void
@ -62,7 +89,8 @@ initkeys (void)
"and or not div mod if else end while macro funct defined"
" include for to downto is var");
scopy_up (&fmathS,
"sqr sqrt sin cos exp ln arctan abs pow pwr max min int log sinh cosh tanh ternary_fcn v agauss sgn");
"sqr sqrt sin cos exp ln arctan abs pow pwr max min int log sinh cosh"
" tanh ternary_fcn v agauss sgn gauss unif aunif limit");
}
static double
@ -1253,9 +1281,16 @@ formula (tdico * dico, char *s, bool *perror)
u = ternary_fcn ((int) v, w, u);
else if ((fu == 20))
u = agauss (v, w, u);
else if ((fu == 22))
u = gauss (v, w, u);
else if ((fu == 23))
u = unif (v, u);
else if ((fu == 24))
u = aunif (v, u);
else if ((fu == 25))
u = limit (v, u);
else
u = mathfunction (fu, v, u);
}
}
i = k;

2
src/frontend/parse.c
View File

@ -164,6 +164,8 @@ struct func ft_funcs[] = {
{ "norm", cx_norm } ,
{ "rnd", cx_rnd } ,
{ "sunif", cx_sunif } ,
{ "poisson",cx_poisson } ,
{ "exponential", cx_exponential } ,
{ "sgauss", cx_sgauss } ,
{ "pos", cx_pos } ,
{ "mean", cx_mean } ,

6
src/frontend/spiceif.c
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@ -1513,8 +1513,10 @@ do {\
_foo(lname,TRANan,1);
}
ft_curckt->ci_curTask->jobs->JOBname = NULL;
ckt->CKTcurJob = (&(ft_curckt->ci_curTask->taskOptions)) -> jobs;
// ckt->CKTcurJob = (&(ft_curckt->ci_curTask->taskOptions)) -> jobs;
ckt->CKTcurJob=ft_curckt->ci_curTask->jobs;
_foo(ft_curckt->ci_curTask->jobs->JOBname, char, -1);
ft_curckt->ci_curTask->jobs->JOBnextJob = NULL;

213
src/maths/cmaths/cmath2.c
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@ -32,7 +32,9 @@ extern void srandom (unsigned int seed);
*/
extern void checkseed(void); /* seed random or set by 'set rndseed=value'*/
extern double drand(void); /* from randnumb.c */
extern double gauss(void); /* from randnumb.c */
extern double gauss0(void); /* from randnumb.c */
extern int poisson(double); /* from randnumb.c */
extern double exprand(double); /* from randnumb.c */
static double *
d_tan(double *dd, int length)
@ -209,43 +211,52 @@ cx_uminus(void *data, short int type, int length, int *newlength, short int *new
}
}
/* random integers drawn from a uniform distribution
*data in: integer numbers, their absolut values are used,
maximum is RAND_MAX (32767)
*data out: random integers in interval [0, data[i][
standard library function rand() is used
*/
void *
cx_rnd(void *data, short int type, int length, int *newlength, short int *newtype)
{
*newlength = length;
checkseed();
if (type == VF_COMPLEX) {
ngcomplex_t *c;
ngcomplex_t *cc = (ngcomplex_t *) data;
int i;
ngcomplex_t *c;
ngcomplex_t *cc = (ngcomplex_t *) data;
int i;
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
int j, k;
j = (int)floor(realpart(&cc[i]));
k = (int)floor(imagpart(&cc[i]));
realpart(&c[i]) = j ? rand() % j : 0; //random() % j : 0;
imagpart(&c[i]) = k ? rand() % k : 0; //random() % k : 0;
}
return ((void *) c);
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
int j, k;
j = (int)floor(realpart(&cc[i]));
k = (int)floor(imagpart(&cc[i]));
realpart(&c[i]) = j ? rand() % j : 0;
imagpart(&c[i]) = k ? rand() % k : 0;
}
return ((void *) c);
} else {
double *d;
double *dd = (double *) data;
int i;
double *d;
double *dd = (double *) data;
int i;
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
int j;
j = (int)floor(dd[i]);
d[i] = j ? rand() % j : 0; //random() % j : 0;
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
int j;
j = (int)floor(dd[i]);
d[i] = j ? rand() % j : 0;
}
return ((void *) d);
}
return ((void *) d);
}
}
/* random numbers drawn from a uniform distribution
*data out: random numbers in interval [-1, 1[
*/
void *
cx_sunif(void *data, short int type, int length, int *newlength, short int *newtype)
{
@ -254,29 +265,108 @@ cx_sunif(void *data, short int type, int length, int *newlength, short int *newt
*newlength = length;
checkseed();
if (type == VF_COMPLEX) {
ngcomplex_t *c;
int i;
ngcomplex_t *c;
int i;
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
realpart(&c[i]) = drand();
imagpart(&c[i]) = drand();
}
return ((void *) c);
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
realpart(&c[i]) = drand();
imagpart(&c[i]) = drand();
}
return ((void *) c);
} else {
double *d;
int i;
double *d;
int i;
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
d[i] = drand();
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
d[i] = drand();
}
return ((void *) d);
}
return ((void *) d);
}
}
/* random numbers drawn from a poisson distribution
*data in: lambda
*data out: random integers according to poisson distribution,
with lambda given by each vector element
*/
void *
cx_poisson(void *data, short int type, int length, int *newlength, short int *newtype)
{
NG_IGNORE(data);
*newlength = length;
checkseed();
if (type == VF_COMPLEX) {
ngcomplex_t *c;
ngcomplex_t *cc = (ngcomplex_t *) data;
int i;
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
realpart(&c[i]) = poisson (realpart(&cc[i]));
imagpart(&c[i]) = poisson (imagpart(&cc[i]));
}
return ((void *) c);
} else {
double *d;
double *dd = (double *) data;
int i;
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
d[i] = poisson(dd[i]);
}
return ((void *) d);
}
}
/* random numbers drawn from an exponential distribution
*data in: Mean values
*data out: exponentially distributed random numbers,
with mean given by each vector element
*/
void *
cx_exponential(void *data, short int type, int length, int *newlength, short int *newtype)
{
NG_IGNORE(data);
*newlength = length;
checkseed();
if (type == VF_COMPLEX) {
ngcomplex_t *c;
ngcomplex_t *cc = (ngcomplex_t *) data;
int i;
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
realpart(&c[i]) = exprand(realpart(&cc[i]));
imagpart(&c[i]) = exprand(imagpart(&cc[i]));
}
return ((void *) c);
} else {
double *d;
double *dd = (double *) data;
int i;
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
d[i] = exprand(dd[i]);
}
return ((void *) d);
}
}
/* random numbers drawn from a Gaussian distribution
mean 0, std dev 1
*/
void *
cx_sgauss(void *data, short int type, int length, int *newlength, short int *newtype)
{
@ -285,29 +375,32 @@ cx_sgauss(void *data, short int type, int length, int *newlength, short int *new
*newlength = length;
checkseed();
if (type == VF_COMPLEX) {
ngcomplex_t *c;
int i;
ngcomplex_t *c;
int i;
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
realpart(&c[i]) = gauss();
imagpart(&c[i]) = gauss();
}
return ((void *) c);
c = alloc_c(length);
*newtype = VF_COMPLEX;
for (i = 0; i < length; i++) {
realpart(&c[i]) = gauss0();
imagpart(&c[i]) = gauss0();
}
return ((void *) c);
} else {
double *d;
int i;
double *d;
int i;
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
d[i] = gauss();
d = alloc_d(length);
*newtype = VF_REAL;
for (i = 0; i < length; i++) {
d[i] = gauss0();
}
return ((void *) d);
}
return ((void *) d);
}
}
/* Compute the avg of a vector.
Created by A.M.Roldan 2005-05-21 */

2
src/maths/cmaths/cmath2.h
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@ -14,6 +14,8 @@ void * cx_uminus(void *data, short int type, int length, int *newlength, short i
void * cx_rnd(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_sunif(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_sgauss(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_poisson(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_exponential(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_mean(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_length(void *data, short int type, int length, int *newlength, short int *newtype);
void * cx_vector(void *data, short int type, int length, int *newlength, short int *newtype);

25
src/maths/misc/randnumb.c
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@ -69,7 +69,8 @@ double exprand(double);
void checkseed(void);
double drand(void);
double gauss(void);
double gauss0(void);
int poisson(double);
/* Check if a seed has been set by the command 'set rndseed=value'
@ -197,7 +198,7 @@ unsigned int CombLCGTausInt2(void)
/*** gauss ***/
double gauss(void)
double gauss0(void)
{
static bool gliset = TRUE;
static double glgset = 0.0;
@ -241,6 +242,26 @@ void rgauss(double* py1, double* py2)
}
/** Code by: Inexpensive
http://everything2.com/title/Generating+random+numbers+with+a+Poisson+distribution **/
int poisson(double lambda)
{
int k=0; //Counter
const int max_k = 1000; //k upper limit
double p = CombLCGTaus(); //uniform random number
double P = exp(-lambda); //probability
double sum=P; //cumulant
if (sum>=p) return 0; //done allready
for (k=1; k<max_k; ++k) { //Loop over all k:s
P*=lambda/(double)k; //Calc next prob
sum+=P; //Increase cumulant
if (sum>=p) break; //Leave loop
}
return k; //return random number
}
/* return an exponentially distributed random number */
double exprand(double mean)
{