# How to use precomputed distance matrix and min_sample for DBSCAN clustering method?

I want to perform DBSCAN on my datapoints, but I don't have access to the data, I just have the pairwise distance of datapoints. Additionally, I have no idea about the number of clusters but I do want that each cluster contains at least 40 data points. Does DBSCAN work with these conditions? For instance, can I have something like this? Or is more information needed? I want to emphasize that I have computed the pairwise distance and this is not the result of Euclidean or some other method.

from sklearn.cluster import DBSCAN

db = DBSCAN(min_samples=40, metric="precomputed")

y_db = db.fit_predict(my_pairwise_distance_matrix)


I am not sure what is eps parameter of DBSCAN(). How should I set that?