static void fill_random_vector(double *x, int n)
{
double mu = 1000*(random_uniform()-0.5);
double sigma = 500*random_uniform()+0.1;
for (int i = 0; i < n; i++)
x[i] = mu + sigma*random_normal();
}
int main()
{
int i;
double rands[1000];
for (i=0; i<1000; i++)
rands[i] = 1.0 + 0.5*random_normal();
return 0;
}
void fill_random_field(float *f, int w, int h, float sigma, float eta)
{
for (int i = 0; i < w * h * 2; i++)
f[i] = sigma*random_normal();
void gblur(float *y, float *x, int w, int h, int pd, float s);
gblur(f, f, w, h, 2, eta);
}
main()
{
int i;
for (i = 0; i < 200000; i++) {
/*myrandom(1);*/
printf("%.3f\n", random_normal(1, 2.65, 6.55));
}
}
/*the srcDim determines the fan-in to the hidden and output units. The weights ae initialised
to be inversely proportional to the sqrt(fanin)
*/
void initialiseWeights(double *weightMat,int length,int srcDim){
int i;
double randm;
srand((unsigned int)time(NULL));
for ( i = 0; i<(length);i++){
randm = random_normal();
weightMat[i] = randm*1/(sqrt(srcDim));
}
}
static GnmValue *
gnumeric_randnorm (GnmFuncEvalInfo *ei, GnmValue const * const *argv)
{
gnm_float mean = value_get_as_float (argv[0]);
gnm_float stdev = value_get_as_float (argv[1]);
if (stdev < 0)
return value_new_error_NUM (ei->pos);
return value_new_float (stdev * random_normal () + mean);
}
void initialiseBias(double *biasVec,int dim, int srcDim){
int i;
double randm;
for ( i = 0; i<dim;i++){
randm = random_normal();
biasVec[i] = randm*(1/sqrt(srcDim));
}
}
int main()
{
int i;
double rands[1000];
for (i=0; i<1000; i++){
rands[i] = 1.0 + 0.5*random_normal();
printf("%f\n",rands[i]);
}
return 0;
}
static gboolean
tool_random_engine_run_normal (data_analysis_output_t *dao,
tools_data_random_t *info,
normal_random_tool_t *param)
{
int i, n;
for (i = 0; i < info->n_vars; i++) {
for (n = 0; n < info->count; n++) {
gnm_float v;
v = param->stdev * random_normal () + param->mean;
dao_set_cell_float (dao, i, n, v);
}
}
return FALSE;
}
static GnmValue *
gnumeric_randsnorm (GnmFuncEvalInfo *ei, GnmValue const * const *argv)
{
gnm_float alpha = 0.;
gnm_float mean = 0.;
gnm_float stdev = 1.;
gnm_float result;
if (argv[0]) {
alpha = value_get_as_float (argv[0]);
if (argv[1]) {
mean = value_get_as_float (argv[1]);
if (argv[2])
stdev = value_get_as_float (argv[2]);
}
}
if (stdev < 0)
return value_new_error_NUM (ei->pos);
result = ((alpha == 0.) ? random_normal () : random_skew_normal (alpha));
return value_new_float (stdev * result + mean);
}
int main(int argc, char** argv){
int seed = getpid();
int c;
int option_index = 0;
int league_id;
int num_players;
struct argp_option options[] = {
{"seed",'s', "int", 0, 0},
{"league-id", 'l', "int", 0, 0},
{"players", 'n', "int", 0, 0},
{"hitter-mean",'h', "double", 0, 0},
{"hitter-sd", 'i', "double", 0, 0},
{"pitcher-mean", 'p', "double", 0, 0},
{"pitcher-sd", 'r', "double", 0, 0},
{0}
};
struct arguments args = {&seed, &league_id, &num_players, &HITTER_MEAN,
&HITTER_SD, &PITCHER_MEAN, &PITCHER_SD};
struct argp argp = {options, arg_parser, 0, 0, global_child};
argp_parse(&argp, argc, argv, 0, 0, &args);
#ifdef _USEGSL_
gsl_rng_env_setup();
const gsl_rng_type *type = gsl_rng_default;
rng = gsl_rng_alloc(type);
gsl_rng_set(rng,seed);
#else
srand(seed);
#endif
Db_Object db = db_connect(CONFIG_FILE);
db->begin_transaction(db->conn);
fprintf(stderr,"Seed: %d\n",seed);
Array_List first_names = Array_List_create(sizeof(char*));
Array_List last_names = Array_List_create(sizeof(char*));
select_names(db,first_names,last_names);
int i;
struct player new_player;
struct hitter_skill hitter_skill;
struct pitcher_skill pitcher_skill;
struct fielder_skill fielder_skill;
for(i=0;i<num_players;i++){
int power= random_normal(HITTER_MEAN,HITTER_SD,MIN_SKILL,MAX_SKILL);
int contact = random_normal(HITTER_MEAN,HITTER_SD,MIN_SKILL,MAX_SKILL);
int fielding = random_normal(HITTER_MEAN,HITTER_SD,MIN_SKILL,MAX_SKILL);
int speed = random_normal(HITTER_MEAN,HITTER_SD,MIN_SKILL,MAX_SKILL);
int intelligence = random_normal(HITTER_MEAN,HITTER_SD,MIN_SKILL,MAX_SKILL);
int control = random_normal(PITCHER_MEAN,PITCHER_SD,MIN_SKILL,MAX_SKILL);
int movement = random_normal(PITCHER_MEAN,PITCHER_SD,MIN_SKILL,MAX_SKILL);
int velocity = random_normal(PITCHER_MEAN,PITCHER_SD,MIN_SKILL,MAX_SKILL);
int endurance = 0;
int bats = (rand()%100)+1;
int throws = (rand()%100)+1;
int position = rand()%18;
/*TODO: Make the choosing of names random.*/
int first_name = 8 * (power + contact + fielding + speed + bats) % first_names->length;
int last_name = 8 * (first_name + speed + intelligence + control + movement + velocity + bats + throws + control + movement + position) % last_names->length;
if(throws <= PERCENT_THROW_RIGHT){
new_player.throws = RIGHT;
}
else{
new_player.throws = LEFT;
}
if(bats<= PERCENT_HIT_SAME){
new_player.bats = new_player.throws;
}
else if(bats<PERCENT_HIT_SAME+PERCENT_HIT_DIFFERENT){
if(new_player.throws == RIGHT){
new_player.bats = LEFT;
}
else{
new_player.bats = RIGHT;
}
}
else{
new_player.bats = SWITCH;
}
if(position <= 9 && position > 1){
new_player. position = position;
pitcher_skill.end = random_normal(30.0,PITCHER_SD*SD_TWEAK,0,49);
}
else if(position>=15 || position == 1){
new_player.position =1;
pitcher_skill.end = random_normal(80.0,PITCHER_SD*SD_TWEAK,50,100);
}
else{
new_player.position = 0;
pitcher_skill.end = random_normal(30.0,PITCHER_SD*SD_TWEAK,0,49);
}
int vs_right_mod = 5;
int vs_left_mod = 5;
if(new_player.bats == RIGHT){
vs_right_mod = -5;
}
if(new_player.bats ==LEFT){
vs_left_mod = -5;
}
new_player.first_name = gget(first_names,first_name);
new_player.last_name = gget(last_names,last_name);
hitter_skill.cvr = calc_skill(contact+vs_right_mod,HITTER_SD);
hitter_skill.pvr = calc_skill(power+vs_right_mod,HITTER_SD);
hitter_skill.cvl = calc_skill(contact+vs_left_mod,HITTER_SD);
hitter_skill.pvl = calc_skill(power+vs_left_mod,HITTER_SD);
hitter_skill.spd = speed;
fielder_skill.range = calc_skill(fielding,HITTER_SD);
fielder_skill.arm = calc_skill(fielding,HITTER_SD);
fielder_skill.field = calc_skill(fielding,HITTER_SD);
new_player.intelligence = intelligence;
pitcher_skill.mov = calc_skill(movement,PITCHER_SD);
pitcher_skill.vel = calc_skill(velocity,PITCHER_SD);
pitcher_skill.ctrl = calc_skill(control,PITCHER_SD);
insert_player(db,&new_player,&hitter_skill,&pitcher_skill,&fielder_skill,league_id);
}
db->commit(db->conn);
db->close_connection(db->conn);
#ifdef _USEGSL_
gsl_rng_free(rng);
#endif
return 0;
}
static int calc_skill(int mean,double sd)
{
return random_normal(mean*1.0,sd*SD_TWEAK,MIN_SKILL,MAX_SKILL);
}
int main()
{
int i , j , k , rni ,error, current , previous , cs , current1 , previous1 , cs1 ;
float tmp,tmp1,rn,V[p],Vspike[p],In[p],rate[p],RT[q] ;
float rn1,V1[p],V1spike[p],In1[p],rate1[p],RT1[q] ;
FILE *frt ;
frt = fopen("Reactiontimeusher.txt","w");
FILE *frt1 ;
frt1 = fopen("StopReactiontimeusher.txt","w");
FILE *ferror ;
ferror = fopen("Probabilityusher.txt","w");
float sum_i,sum1_i,errper ;
double rands[1000];
double rands1[1000];
for(k=1;k<=s;k++) {
error = 0 ;
for (i=1; i<=q; i++){
rands[i] = 80.0 + 25.0*random_normal();
}
for (i=1;i<=k;i++){
rands1[i] = 0;
}
for (;i<=q;i++){
rands1[i] = 100.0 + 25.0*random_normal();
}
for(j=1;j<=q;j++){
for(i=1;i<=p;i++)
{
In[i] = 0 ;
In[i] = rands[j] ;
V[i] = 0 ;
Vspike[i] = 0 ;
}
for(i=1;i<=p;i++)
{
In1[i] = 0 ;
In1[i] = rands1[j] ;
V1[i] = 0 ;
V1spike[i] = 0 ;
}
sum_i = 0 ;
current = 0 ;
previous = 0 ;
cs=0 ;
sum1_i = 0 ;
current1 = 0 ;
previous1 = 0 ;
cs1=0 ;
V[1] = 0 ;
V1[1] = 0 ;
for(i=2;i<=p;i++)
{
sum_i = sum_i + (i*In[i])/p ;
V[i] = V[i-1] + sum_i*dt/(C) -0.8*V1[i-1];
sum1_i = sum1_i + (i*In1[i])/p ;
V1[i] = V1[i-1] + sum1_i*dt/(C) - 0.1*V[i-1];
if(V[i] > 10)
{
V[i] = 0 ;
Vspike[i] = 100 ;
}
if(V1[i] > 10)
{
V1[i] = 0 ;
V1spike[i] = 100 ;
}
}
cs = 0 ;
for(i=2;i<=p;i++)
{
if (Vspike[i] == 100 )
{
cs++ ;
if(cs>1) {
current = i ;
tmp = current - previous ;
rate[i] = 1.0 / tmp;
previous = i ;
}
}
else {rate[i] = rate[i-1];}
}
cs1 = 0 ;
for(i=2;i<=p;i++)
{
if (V1spike[i] == 100 )
{
cs1++ ;
if(cs1>1) {
current1 = i ;
tmp1 = current1 - previous1;
rate1[i] = 1.0 / tmp1;
previous1 = i ;
}
}
else {rate1[i] = rate1[i-1];}
}
/*
for(i=2;i<=p;i++){
if(rate[i] > 0.05){ fprintf(frt,"%d\t %f \t %d \n" , j , In[5] , i ) ; RT[j] = i; break; }
}
*/
for(i=2;i<=p;i++){
if(rate1[i] > 0.05){ fprintf(frt1,"%d\t %f \t %d \t %f \n" , j , In1[5] , i , rate1[i] ) ; RT1[j] = i; break; }
}
if( (rate[r]>rate1[r]) && (rate[r]>0.05) ) { error++ ;
fprintf(frt,"%f \t %f \t %d \n",rate[r],rate1[r],error) ; }
/*if( (rate1[r]>rate[r]) && (rate1[r]>0.05) ) {
fprintf(frt1,"%f \t %f \t %d \n",rate[r],rate1[r],error) ; }
*/
}
errper = (float)error / q ;
fprintf(ferror," %f \t %d \n " , errper , k ) ;
}
}
//return the length in bytes of a document, where length is
// sampled from a normal distribution with mean len_u and
// variance len_var
int doc_len() {
return (int)((double)len_u + random_normal() * len_var);
}
