static int setup(void * owner)
{
int i,j;
char cbuf[200];
for (i=0;i<MAXTEAMS;i++){
for (j=0;j<MAXPLAYERINTEAMS;j++){
sprintf(cbuf,"planes/plane-%d-%d.png", i,j);
CRITICAL(right_anim[i][j] = animation_load(path_to_data(cbuf),64,1,100));
animation_make_loop(right_anim[i][j]);
right_anim[i][j]->trigger = frame_trigger;
}
}
for (j=0;j<MAXPLAYERINTEAMS;j++){
sprintf(cbuf,"planes/plane-%d-wreck.png", j);
CRITICAL(crashing[j] = animation_load(path_to_data(cbuf),64,1,180));
animation_make_loop(crashing[j]);
crashing[j]->trigger = crashing_trigger;
}
//NYANCAT
sprintf(cbuf,"planes/nyan-cat.png");
CRITICAL(right_anim[MAXTEAMS][0] = animation_load(path_to_data(cbuf),64,1,100));
sprintf(cbuf,"planes/nyan-cat.png");
CRITICAL(crashing[MAXPLAYERINTEAMS] = animation_load(path_to_data(cbuf),64,1,180));
animation_make_loop(right_anim[MAXTEAMS][0]);
animation_make_loop(crashing[MAXPLAYERINTEAMS]);
right_anim[MAXTEAMS][0]->trigger = frame_trigger;
crashing[MAXPLAYERINTEAMS]->trigger = crashing_trigger;
engine_strength = cfgnum("blueplane.engine_strength",5);
turn_amount = cfgnum("blueplane.turn_amount",0.02);
bomb_delay = cfgnum("blueplane.bomb_delay",1000);
bullet_delay = cfgnum("blueplane.bullet_delay",140);
hitpoints = cfgnum("blueplane.hitpoints",15);
mass = cfgnum("blueplane.mass",1);
air_isotropic = cfgnum("blueplane.air_isotropic",0.00005);
air_turnrate = cfgnum("blueplane.air_turnrate",0.00005);
air_normal = cfgnum("blueplane.air_normal",0.001);
nr_bombs = cfgnum("blueplane.nr_bombs",5);
crash_point = cfgnum("blueplane.crash_point",20);
return 0;
}
static int setup()
{
assert(anim = animation_load(path_to_data("mark.png"),
1,16,40));
animation_last_frame(anim)->trigger = frame_trigger;
return 0;
}
Identifier::Identifier(
const proto::ContactItemType type,
const proto::HDPath& path)
: ot_super()
{
CalculateDigest(path_to_data(type, path), DefaultType);
}
static int setup()
{
CRITICAL(grow = animation_load(path_to_data("whitesmoke.png"),
1,32,100));
animation_set_alpha(grow,128);
//animation_set_alpha(dissolve,128);
// animation_last_frame(grow)->next_frame = dissolve;
animation_last_frame(grow)->trigger = frame_trigger;
return 0;
}
static int general_setup(void)
{
int i;
maths_setup();
config_setup();
screen_w = cfgnum("screen.width", 800);
screen_h = cfgnum("screen.height", 600);
if (cfgnum("fullscreen", 0) == 1)
displayflags |= SDL_FULLSCREEN;
sprite_global.opt_alpha = cfgnum("alpha", 0);
i = SDL_Init(SDL_INITFLAGS);
assert(i == 0);
atexit(atexit_cleanup);
SDL_WM_SetCaption(VERSIONSTRING, 0);
sprite_global.display = SDL_SetVideoMode(screen_w, screen_h, 0, displayflags);
assert(sprite_global.display);
SDL_ShowCursor(SDL_DISABLE);
if (cfgnum("sound", 0) == 1)
{
sound_setup();
/* place the ear on the ground, in the center */
sound_move_ear(screen_w / 2, screen_h);
}
sprite_setup();
text_setup();
console_setup();
console_set_pos(9, 254);
console_load_bg(path_to_data("console-bg.png"));
sprite_types_setup();
char bg1[255];
char bg2[255];
sprintf(bg1,"data/bg%d.png",screen_w);
sprintf(bg2,"data/bgmask%d.png",screen_w);
sprite_background_load(bg1, bg2);
level_setup();
winds_setup();
return 0;
}
static int setup()
{
/*assert(anim = animation_load(path_to_data("gauge.png"),
16,1,4000000));*/
char cbuf[200];
int i;
for (i=0;i<MAXTEAMS;i++){
sprintf(cbuf,"planes/plane-%d-0.png", i);
CRITICAL(anim[i] = animation_load(path_to_data(cbuf),64,1,100));
}
return 0;
}
void about_mode(char *filename)
{
FILE *message = fopen(path_to_data(filename), "r");
char cbuf[2001];
size_t n;
if (message)
{
n = fread(cbuf, 1, 2000, message);
cbuf[n] = 0;
fclose(message);
}
else
{
sprintf(cbuf, "Error: could not open '%s'.", filename);
}
message_mode(cbuf);
}
int main(int argc, char *argv[]) {
// Initialize options to default values
double* step_size = new double;
TrainingOptions training_options = initDefaultTrainingOptions(step_size);
BenchmarkOptions benchmark_options = initDefaultBenchmarkOptions();
std::string path_to_data("data");
// Parse arguments to adjust options
parse_command_line_args(argc, argv, &training_options, &benchmark_options, &path_to_data);
printf("in main error goal is %f\n",benchmark_options.error_goal);
printf("in main run number is %d\n",benchmark_options.num_runs);
printf("in main step size is %f \n",*training_options.step_size);
// Model variables
FeatureType* data_points = new FeatureType[DATA_SET_SIZE]; // Data points
LabelType* labels = new LabelType[NUM_SAMPLES]; // Labels
FeatureType* parameter_vector = new FeatureType[PARAMETER_SIZE]; // Model parameters
//build train file path
std::string str_train_points_filepath(path_to_data +
std::string("/train-images-idx3-ubyte"));
const char* train_points_filepath = str_train_points_filepath.c_str();
std::string str_train_labels_filepath(path_to_data +
std::string("/train-labels-idx1-ubyte"));
const char* train_labels_filepath = str_train_labels_filepath.c_str();
//build test file path
std::string str_test_points_filepath(path_to_data +
std::string("/t10k-images-idx3-ubyte"));
const char* test_points_filepath = str_test_points_filepath.c_str();
std::string str_test_labels_filepath(path_to_data +
std::string("/t10k-labels-idx1-ubyte"));
const char* test_labels_filepath = str_test_labels_filepath.c_str();
// Read train data from files and insert into variables
if( readImageData (TRAIN_SET_SIZE, train_points_filepath,
data_points) != TRAIN_SET_SIZE)
return EXIT_FAILURE;
if( readImageLables(NUM_TRAINING, train_labels_filepath,
labels) != NUM_TRAINING)
return EXIT_FAILURE;
//Read test data from files and insert behind
if(readImageData(TEST_SET_SIZE, test_points_filepath,
&data_points[TRAIN_SET_SIZE])!= TEST_SET_SIZE)
return EXIT_FAILURE;
if(readImageLables(NUM_TESTING, test_labels_filepath,
&labels[NUM_TRAINING])!= NUM_TESTING)
return EXIT_FAILURE;
cout<<"read mnist data success"<<endl;
// Initialize data set and options structs
DataSet data_set;
data_set.data_points = data_points;
data_set.labels = labels;
data_set.parameter_vector = parameter_vector;
data_set.num_data_points = NUM_SAMPLES;
data_set.num_features = NUM_FEATURES;
// Initial shuffle of the data set to mix spam with ham
// shuffleKeyValue(data_points, labels, NUM_SAMPLES, NUM_FEATURES);
// runConvergenceRate(data_set, training_options, benchmark_options);
// runTrainAndTest(data_set, training_options, benchmark_options);
runConvergenceTime(data_set, training_options, benchmark_options);
// Free memory and exit
delete step_size;
delete[] data_points;
delete[] labels;
delete[] parameter_vector;
return 0;
}
static int setup()
{
assert(anim = animation_load(path_to_data("missile.png"),
64,1,1000000));
return 0;
}
