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#include "parameters.h"
#include "../measurement/measurement.h"
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
extern int debug_learning;
double calculate_params(struct parameter_bundle *params)
{
unsigned int i;
params->score = 0;
for (i = 0; i < past_results.size(); i++)
compute_bundle(params, past_results[i]);
return params->score;
}
/*
* gradual linear convergence of non-independent variables works better if once in a while
* you make a wrong move....
*/
static int random_disturb(int retry_left)
{
if (retry_left < 10)
return 0;
if ( (rand() % 500) == 7)
return 1;
return 0;
}
static int try_zero(double value)
{
if (value > 0.01)
if ( (rand() % 100) == 1)
return 1;
if ( (rand() % 5) == 1)
return 1;
return 0;
}
static unsigned int previous_measurements;
/* leaks like a sieve */
void learn_parameters(int iterations)
{
struct parameter_bundle *best_so_far;
double best_score = 10000000000000000.0;
int retry = iterations;
int prevparam = -1;
int locked = 0;
static unsigned int bpi = 0;
unsigned int i;
// if (past_results.size() == previous_measurements)
// return;
previous_measurements = past_results.size();
double delta = 0.50;
best_so_far = &all_parameters;
if (!bpi)
bpi = get_param_index("base power");
calculate_params(best_so_far);
best_score = best_so_far->score;
delta = 0.001 / pow(0.8, iterations / 2.0);
if (iterations < 25)
delta = 0.001 / pow(0.5, iterations / 2.0);
if (delta > 0.2)
delta = 0.2;
if (1.0 * best_score / past_results.size() < 4 && delta > 0.05)
delta = 0.05;
if (debug_learning)
printf("Delta starts at %5.3f\n", delta);
if (best_so_far->parameters[bpi] > min_power)
best_so_far->parameters[bpi] = min_power;
/* We want to give up a little of base power, to give other parameters room to change;
base power is the end post for everything after all
*/
best_so_far->parameters[bpi] = best_so_far->parameters[bpi] * 0.99;
while (retry--) {
int changed = 0;
int bestparam;
double newvalue = 0;
double orgscore;
bestparam = -1;
calculate_params(best_so_far);
orgscore = best_score = best_so_far->score;
for (i = 1; i < best_so_far->parameters.size(); i++) {
double value, orgvalue;
orgvalue = value = best_so_far->parameters[i];
if (value <= 0.001) {
value = 0.1;
} else
value = value * (1 + delta);
if (i == bpi && value > min_power)
value = min_power;
if (i == bpi && orgvalue > min_power)
orgvalue = min_power;
if (value > 5000)
value = 5000;
// printf("Trying %s %4.2f -> %4.2f\n", param.c_str(), best_so_far->parameters[param], value);
best_so_far->parameters[i] = value;
calculate_params(best_so_far);
if (best_so_far->score < best_score || random_disturb(retry)) {
best_score = best_so_far->score;
newvalue = value;
bestparam = i;
changed++;
}
value = orgvalue * 1 / (1 + delta);
if (value < 0.0001)
value = 0.0;
if (try_zero(value))
value = 0.0;
if (value > 5000)
value = 5000;
// printf("Trying %s %4.2f -> %4.2f\n", param.c_str(), orgvalue, value);
if (orgvalue != value) {
best_so_far->parameters[i] = value;
calculate_params(best_so_far);
if (best_so_far->score + 0.00001 < best_score || (random_disturb(retry) && value > 0.0)) {
best_score = best_so_far->score;
newvalue = value;
bestparam = i;
changed++;
}
}
best_so_far->parameters[i] = orgvalue;
}
if (!changed) {
double mult;
if (!locked) {
mult = 0.8;
if (iterations < 25)
mult = 0.5;
delta = delta * mult;
}
locked = 0;
prevparam = -1;
} else {
if (debug_learning) {
printf("Retry is %i \n", retry);
printf("delta is %5.4f\n", delta);
printf("Best parameter is %i \n", bestparam);
printf("Changing score from %4.3f to %4.3f\n", orgscore, best_score);
printf("Changing value from %4.3f to %4.3f\n", best_so_far->parameters[bestparam], newvalue);
}
best_so_far->parameters[bestparam] = newvalue;
if (prevparam == bestparam)
delta = delta * 1.1;
prevparam = bestparam;
locked = 1;
}
if (delta < 0.001 && !locked)
break;
}
/* now we weed out all parameters that don't have value */
best_score = best_so_far->score;
for (i = 0; i < best_so_far->parameters.size(); i++) {
double orgvalue;
orgvalue = best_so_far->parameters[i];
best_so_far->parameters[i] = 0.0;
calculate_params(best_so_far);
if (best_so_far->score > best_score) {
best_so_far->parameters[i] = orgvalue;
} else {
best_score = best_so_far->score;
}
}
calculate_params(best_so_far);
if (debug_learning)
printf("Final score %4.2f (%i points)\n", best_so_far->score / past_results.size(), past_results.size());
// dump_parameter_bundle(best_so_far);
// dump_past_results();
}
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