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); }