abstract protected ModelType loadMotif(String filename);

  protected void initialize_defaults() {

    initialize_default_background();

    thresholds = new double[0];

    max_hash_size = 10000000;

    data_model = DataModel.PWM;

    thresholds_folder = null;

    effective_count = 100;

  protected abstract CanFindThreshold calculator();

  protected void initialize_defaults() {

    initialize_default_background();

    pvalue_boundary = BoundaryType.LOWER;

    max_hash_size = 10000000;

    data_model = DataModel.PWM;

    effective_count = 100;

    thresholds_folder = null;

  abstract protected ModelType loadMotif(File file);

  protected void initialize_defaults() {

    initialize_default_background();

    pvalue_boundary = BoundaryType.LOWER;

    max_hash_size = 10000000;

    pvalues = PrecalculateThresholdList.PVALUE_LIST;

    data_model = DataModel.PWM;

    effective_count = 100;

    double[] pvalues = PrecalculateThresholdList.PVALUE_LIST;

    // Higher discretization - better precision of score to Pvalue calculation and higher precalculation time

    // (given discretization is high enough, precalculation step though can take about a pair of minutes on large PWM collection)

    // But precalculation step should be done once

    // Wordwise background means that we calculate number of words instead of probabilities, this is a default mode

    // If one need to work with certain nucleotide background probabilities he should use:

    // BackgroundModel background = new Background(new double[]{pA, pC, pG, pT}); where {pA,... pT} are probabilities of respective nucleotides

    BackgroundModel background = new WordwiseBackground();

    // A actual pvalue will be less than requested. Not very important setting in this task

  protected abstract BackgroundType extractBackground(String str);

  protected abstract void initialize_default_background();

  protected void initialize_defaults() {

    initialize_default_background();

    maxHashSize = 10000000;

    maxPairHashSize = 10000;

    dataModel = DataModel.PWM;

    effectiveCount = 100.0;

    thresholds_folder = null;

  protected abstract void initialize_default_background();

  protected void initialize_defaults() {

    initialize_default_background();

    maxHashSize = 10000000;

    maxPairHashSize = 10000;

    dataModel = DataModel.PWM;

    effectiveCount = 100;

    pvalue = 0.0005;

    dataModelSecond = DataModel.PWM;

    effectiveCountFirst = 100.0;

    effectiveCountSecond = 100.0;

    pvalue = 0.0005;

    transposeFirst = false;

    transposeSecond = false;

    maxHashSize = 10000000;

    maxPairHashSize = 10000;

  }

  @Override

  public DiPWM discrete(Double rate) {

  }

  }

  @Override

  public PWM discrete(Double rate) {

  }

  public static void main(String[] args){

    PWM firstPWM = new PWMImporter().loadMotif("test_data/pwm/KLF4_f2.pwm");

    PWM secondPWM = new PWMImporter().loadMotif("test_data/pwm/SP1_f1.pwm");

    try {

//      CountingPWM secondPWMCounting = new CountingPWM(secondPWM.discrete(discretizer), new WordwiseBackground(), null);

      BackgroundModel background = new WordwiseBackground();