File content as of revision 4:00da8e8c7e2a:

#include "main.hpp"

LocalFileSystem *local_fs;  // マウントポイントを定義（ディレクトリパスになる）

// Pointer to Class instance (global)
SRNN            *srnn;
MCSVM           *mcsvm;
SensorModule    *sensor_module;
GraphicHandler  *graphic_handler;
// ネットワーク関係(global)
EthernetInterface    eth_if;
NTPClient            ntp_client;

// 系列データ
float* new_seqence_data;        // 現在の(一番新しい)系列データ
float* new_predict_data;        // 現在の予測結果
int*   new_predict_weather;     // 現在の予測天気
float* new_predict_probability; // 現在の予測天気の確率（厳密には,確率ではない...）
FILE*  seqence_data_fp;    // 系列データのファイルポインタ(SRNNと計器の記録に使う)
FILE*  predict_data_fp;    // 予測データ

volatile int ml_flag;
time_t now_time;
struct tm* local_time_p;

// 生存報告LED
DigitalOut live_led(LED1);

volatile int thread_count = 0;
int open_count = 0;

// 計器タスク
void read_task(void const *arg)
{
    // char str_buf[BUF_SIZE];


    // データ更新
    sensor_module->read_all_sensor();
    new_seqence_data[TEMPERATURE]  = sensor_module->get_temperture();
    new_seqence_data[AIR_PRESSURE] = sensor_module->get_pressure();
    new_seqence_data[HUMIDITY]     = sensor_module->get_humidity();
    printf("T:%f P:%f H:%f \r\n", new_seqence_data[TEMPERATURE], new_seqence_data[AIR_PRESSURE], new_seqence_data[HUMIDITY]);
    graphic_handler->set_now_data(new_seqence_data);

    seqence_data_fp = fopen( SEQUENCE_DATA_NAME, "a");
    check_file_open( seqence_data_fp, SEQUENCE_DATA_NAME);

    // 形式に沿った文字列を書き出す : y/m/d h:m,<temperature>,<air_pressure>,<humidity>
    fprintf( seqence_data_fp, "%d/%d/%d %d:%d:%d,%f,%f,%f\n",
             (local_time_p->tm_year + 1900), (local_time_p->tm_mon + 1), local_time_p->tm_mday, local_time_p->tm_hour, local_time_p->tm_min, local_time_p->tm_sec,
             new_seqence_data[TEMPERATURE], new_seqence_data[AIR_PRESSURE], new_seqence_data[HUMIDITY]);
    fclose( seqence_data_fp );

}

// 機械学習タスク
void ml_task(void const *arg)
{
    // ローカル変数
    int line = 0, diff_line;
    //float* srnn_sample = new float[LEN_DATA_SEQUENCE * DIM_SIGNAL];            // SRNNのサンプル
    float srnn_sample[LEN_DATA_SEQUENCE * DIM_SIGNAL];
    // 読み込みバッファ
    float buf_data[DIM_SIGNAL];
    char  str_buf[BUF_SIZE], str_dummy[50], str_dum1[10], str_dum2[10], str_dum3[10];

    printf("[%d] M.L.S.T.A.R.T \r\n", thread_count++);

    // 3. SRNNに学習データを読み込ませる.
    printf("Set SRNN sample... %02d:%02d \r\n", local_time_p->tm_hour, local_time_p->tm_min);
    seqence_data_fp = fopen( SEQUENCE_DATA_NAME, "r");
    check_file_open( seqence_data_fp, SEQUENCE_DATA_NAME);
    // まず、行数を数える
    line = 0;
    while( fgets( str_buf, BUF_SIZE, seqence_data_fp) != NULL ) {
        line++;
    }
    printf(" line : %d \r\n", line);
    // 差分行の計算
    diff_line = (line - LEN_DATA_SEQUENCE);
    rewind( seqence_data_fp );
    printf(" go to line : %d \r\n", diff_line);
    line = 0;
    // 差分行までfpを移動
    fflush( seqence_data_fp );
    while( fgets( str_buf, BUF_SIZE, seqence_data_fp) != NULL ) {
        line++;
        if ( line == diff_line ) break;
    }
    // 最新LEN_DATA_SEQUENCE個のデータを読み込む.
    line = 0;
    /*
    while( ( ret = fscanf( seqence_data_fp, " %[^\n,],%f,%f,%f", str_buf, &(buf_data[0]), &(buf_data[1]), &(buf_data[2])) ) != EOF ) {
        if (line == LEN_DATA_SEQUENCE) break;
        memcpy(&(srnn_sample[line * DIM_SIGNAL]), buf_data, sizeof(float) * DIM_SIGNAL);
        printf("sample %d : %s %f %f %f \r\n", diff_line + line, str_buf, MATRIX_AT(srnn_sample,DIM_SIGNAL,line,0), MATRIX_AT(srnn_sample,DIM_SIGNAL,line,1), MATRIX_AT(srnn_sample,DIM_SIGNAL,line,2));
        line++;
    }
    */

    while( fgets( str_buf, BUF_SIZE, seqence_data_fp) != NULL ) {
        if (line == LEN_DATA_SEQUENCE) break;
        if (open_count > 20)
            printf("%d %s \r", line, str_buf);

        //sscanf( str_buf, " %[^\n,],%f,%f,%f", str_buf, &(buf_data[0]), &(buf_data[1]), &(buf_data[2])) )
        sscanf( str_buf, "%[^,],%[^,],%[^,],%[^,]", str_dummy
                , str_dum1
                , str_dum2
                , str_dum3);

        // エラーハンドル... 仕様か過失かわからないが, 19回目以降に開いたファイルはおかしい.
        buf_data[0] = float(atof(str_dum1));
        buf_data[1] = float(atof(str_dum2));
        buf_data[2] = float(atof(str_dum3));
        // 直前の結果+乱数
        if ( line >= 1 ) {
            if (fabsf(buf_data[TEMPERATURE] - srnn_sample[(line-1) * DIM_SIGNAL]) > 30)
                buf_data[TEMPERATURE] = (srnn_sample[(line-1) * DIM_SIGNAL + TEMPERATURE] + uniform_rand(1));
            if (fabsf(buf_data[AIR_PRESSURE] - srnn_sample[(line-1) * DIM_SIGNAL + AIR_PRESSURE]) > 30)
                buf_data[AIR_PRESSURE] = (srnn_sample[(line-1) * DIM_SIGNAL + 1] + uniform_rand(1));
            if (fabsf(buf_data[HUMIDITY] - srnn_sample[(line-1) * DIM_SIGNAL + 2]) > 30)
                buf_data[HUMIDITY] = (srnn_sample[(line-1) * DIM_SIGNAL + HUMIDITY] + uniform_rand(1));
        }

        memcpy(&(srnn_sample[line * DIM_SIGNAL]), buf_data, sizeof(float) * DIM_SIGNAL);
        /*
        srnn_sample[line * DIM_SIGNAL] = buf_data[0];
        srnn_sample[line * DIM_SIGNAL + 1] = buf_data[1];
        srnn_sample[line * DIM_SIGNAL + 2] = buf_data[2];
        */

        if (open_count > 20)
            printf(" %d str : %s , f0 : %f , f1 : %f , f2 : %f \r\n", line, str_dummy
                   , srnn_sample[line * DIM_SIGNAL]
                   , srnn_sample[line * DIM_SIGNAL + 1]
                   , srnn_sample[line * DIM_SIGNAL + 2]);
        // memcpy(&(srnn_sample[line * DIM_SIGNAL]), buf_data, sizeof(float) * DIM_SIGNAL);
        line++;
    }

    fclose( seqence_data_fp );
    srnn->set_sample(srnn_sample);

    // 4. SRNNの学習/予測結果から, MCSVMで天気識別
    printf("Learning... %02d:%02d \r\n", local_time_p->tm_hour, local_time_p->tm_min);
    srnn->learning();
    srnn->predict(new_seqence_data);
    memcpy(new_predict_data, srnn->predict_signal, sizeof(float) * DIM_SIGNAL * PREDICT_LENGTH);
    // MCSVMによる天候識別
    for (int i_predict = 0; i_predict < PREDICT_LENGTH; i_predict++) {
        // printf("predict_data[%d] : %f %f %f \r\n", i_predict, new_predict_data[i_predict * DIM_SIGNAL], new_predict_data[i_predict * DIM_SIGNAL + 1], new_predict_data[i_predict * DIM_SIGNAL + 2]);
        new_predict_weather[i_predict]     = mcsvm->predict_label(&(new_predict_data[i_predict * DIM_SIGNAL]));
        new_predict_probability[i_predict] = mcsvm->predict_probability(&(new_predict_data[i_predict * DIM_SIGNAL]));
        // printf("P_W : %d P_P : %f \r\n", new_predict_weather[i_predict], new_predict_probability[i_predict]);
    }
    printf("SVM predict finished \r\n");

    // 5. 予測結果の書き込み
    printf("Write out predict... %02d:%02d \r\n", local_time_p->tm_hour, local_time_p->tm_min);
    predict_data_fp = fopen( PREDICT_DATA_NAME, "w");
    check_file_open( predict_data_fp, PREDICT_DATA_NAME);
    for (int i_predict = 0; i_predict < PREDICT_LENGTH; i_predict++) {
        // 予測時刻へ変換
        now_time += PREDICT_INTERVAL_TIME;
        local_time_p = localtime(&now_time);
        // 気象を文字列に変換
        switch(new_predict_weather[i_predict]) {
            case SHINY:
                strcpy(str_buf, "shiny");
                break;
            case CLOUDY:
                strcpy(str_buf, "cloudy");
                break;
            case RAINY:
                strcpy(str_buf, "rainy");
                break;
            case SNOWY:
                strcpy(str_buf, "snowy");
                break;
            default:
                fprintf( stderr, "Error in write predict result (in weather switch). \r\n");
                break;
        }
        // 書き出しフォーマット : y/m/d h:m,<weather>,<temperature>,<air_pressure>,<humidity>
        fprintf( predict_data_fp, "%d/%d/%d %d:%d:%d,%s,%f,%f,%f\n",
                 (local_time_p->tm_year + 1900), (local_time_p->tm_mon + 1), local_time_p->tm_mday, local_time_p->tm_hour, local_time_p->tm_min, local_time_p->tm_sec,
                 str_buf,
                 new_predict_data[i_predict * DIM_SIGNAL + TEMPERATURE],
                 new_predict_data[i_predict * DIM_SIGNAL + AIR_PRESSURE],
                 new_predict_data[i_predict * DIM_SIGNAL + HUMIDITY]);
    }
    fclose( predict_data_fp );

    // GraphicHandlerの現在予測データのセット
    graphic_handler->set_predict_data(new_predict_data, new_predict_weather, new_predict_probability);

    // delete [] srnn_sample;
    // delete local_time_p; <- してはいけない（戒め）

}

// 描画スレッド : 優先度低め
void draw_task(void const *arg)
{
    while (true) {

        if (ml_flag) {
            Thread::signal_wait(0x2, osWaitForever);
        }

        // printf("draw thread start. \r\n");
        if (time(NULL) % 60 == 0) {
            // 一分毎に表示時間を更新
            graphic_handler->update_time();
        }
        graphic_handler->update_image();
        // 画面更新
        graphic_handler->update_draw();
        // printf("draw thread finish. \r\n");
        Thread::wait(1 * 1000);

    }
}


// ネットワークスレッド : リソースの限界. 廃止.
/*
void network_task(void const *arg)
{
    while (true) {
        while (ml_flag) {
            Thread::signal_wait(0x3);
        }
        // 1. ポート80のListen
        http_server->poll();
        // for (int dum = 0; dum < 10000; dum++) ;
        net_led = !net_led;
        // Thread::wait(500);
    }
}
*/

// 生存報告LEDチカ
void liveled_task(void const *arg)
{
    while (true) {
        if (ml_flag) {
            Thread::signal_wait(0x1, osWaitForever);
        }
        live_led = !live_led;
        Thread::wait(1000);
    }
}

//
int main(void)
{
    set_new_handler(no_memory);
    local_fs = new LocalFileSystem("local");
    
    setup();

    // graphic_handler->draw_log("setup finish");
    ml_flag = 1;

    Thread draw_thread(draw_task, NULL, osPriorityNormal, 2000);
    Thread liveled_thread(liveled_task, NULL, osPriorityLow, 200);
    
    osThreadSetPriority(Thread::gettid() ,osPriorityHigh);
    while (true) {
        ml_flag = 1;
        now_time = time(NULL);
        local_time_p = localtime(&now_time);
        read_task(NULL);
        ml_task(NULL);
        ml_flag = 0;
        liveled_thread.signal_set(0x1);
        draw_thread.signal_set(0x2);
        Thread::wait(2 * 1000);
    }
    
    error("unreachable here");

}