How to calculate entropy with Bertopic

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Desribe the bug

Hi everyone, first of all I would like to thank @MaartenGr and all the contributors for this amazing project.
For my project, I need to calculate the entropy of each topic. Could you help me how to calculate entropy in Bertopic. I have used probs to calculate, but the bug showed that the probs were 1 dimension array. But my code requires two dimension array. Thank you very much!

Reproduction

import numpy as np
import pandas as pd

doc_topic_matrix = np.array(probs)

normalized_doc_topic_matrix = doc_topic_matrix / doc_topic_matrix.sum(axis=1, keepdims=True)

topic_entropy = (-normalized_doc_topic_matrix * np.log2(normalized_doc_topic_matrix + 1e-9)).sum(axis=0)

entropy_df = pd.DataFrame({'Topic': range(len(topic_entropy)), 'Entropy': topic_entropy})

topic_freq['Entropy'] = sorted_entropy_df['Entropy'].values

BERTopic Version

0.16.4

No project file, test, or entry point is named. Start by reproducing the one-dimensional probs result with BERTopic 0.16.4 and clarify whether entropy should be calculated per document or topic; done means an agreed calculation and documented supported output.