for regression - calculate the correlation coefficient between predictions and true values

pearson_metric_tensorflow.py

def pearson(x, y):
    '''Metric for correlation coefficient.
    Use as follows:
    model.compile(loss='mse', optimizer='adam', metrics=[pearson])
    '''    
    mx = K.mean(x)
    my = K.mean(y)
    xm, ym = x-mx, y-my
    r_num = K.sum(tf.multiply(xm,ym))
    r_den = K.sqrt(tf.multiply(K.sum(K.square(xm)), K.sum(K.square(ym))))
    r = tf.clip_by_value(r_num / (r_den + K.epsilon()), -1., 1.)
    return r