term-score for topic models, 間違いがあれば指摘してくれると助かります。

term_score.py

import numpy as np
from scipy.special import softmax as np_softmax

def term_score(beta:np.array, dtype=np.float32) -> np.array:
    """reference: http://db-event.jpn.org/deim2011/proceedings/pdf/f4-1.pdf
    """
    β = np.array(beta)
    (K,V) = beta.shape
    if not (K-0.3) < beta.sum() < (K+0.3):
        β = np_softmax(beta, axis=-1)
    logβ = np.log(β)
    Z = (1/K) * np.sum(logβ, axis=0) 
    score = β * (logβ - Z)
    return score.astype(dtype)