Why distances are calculated twice?

[NaserMonsefi]

Hi,

Thank for the great tutorial on document clustering. I am pretty new to text analytics and wanted to ask if there is a reason that distances are calculated twice for hierarchical document clustering?
First here on the `tfidf_matrix' using cosine distance:

from sklearn.metrics.pairwise import cosine_similarity
dist = 1 - cosine_similarity(tfidf_matrix)

and second time here over the dist through ward function that runs euclidean distance before doing the ward linkage:

linkage_matrix = ward(dist)

Is this something specially done for text clustering?

Thanks again