def specificity(p, t):
    '''
    Fraction of positive samples correctly identified as positive.
    :param p: Multi-dimensional numpy array with the predicted values.
    :param t: Multi-dimensional numpy array with the known values.
    :return: Float value between 0 and 1.
    '''

    # Calculates number of correctly identified positive samples.
    num = sum([1 for i, j in zip(np.argmax(p, axis=1), np.argmax(t, axis=1)) if i == 0 and j == 0])

    # Calculates total number of positive samples.
    denom = sum([1 for i in np.argmax(t, axis=1) if i == 0])

    return float(denom) / num
dataset/ETHPy150Open calvinschmdt/EasyTensorflow/easy_tensorflow/evolve_functions.py/specificity/swapped operands of `/`