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fix: more stable default flattening (#45)
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LuisScoccola authored Mar 27, 2023
1 parent c720278 commit 30860d4
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Showing 3 changed files with 5 additions and 5 deletions.
4 changes: 2 additions & 2 deletions persistable/persistable.py
Original file line number Diff line number Diff line change
Expand Up @@ -263,7 +263,7 @@ def cluster(
n_clusters,
start,
end,
conservative_flattening_style=False,
conservative_flattening_style=True,
keep_low_persistence_clusters=False,
):
"""Cluster dataset passed at initialization.
Expand All @@ -285,7 +285,7 @@ def cluster(
two-parameter hierarchical clustering used to do persistence-based
clustering.
conservative_flattening_style: bool, optional, default is False
conservative_flattening_style: bool, optional, default is True
If false, flatten the hierarchical clustering using the approach
of 'Persistence-Based Clustering in Riemannian Manifolds' Chazal, Guibas,
Oudot, Skraba. If true, use the more conservative and more stable approach
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4 changes: 2 additions & 2 deletions persistable/persistable_interactive.py
Original file line number Diff line number Diff line change
Expand Up @@ -258,11 +258,11 @@ def run():

return port

def cluster(self, conservative_flattening_style=False, keep_low_persistence_clusters=False):
def cluster(self, conservative_flattening_style=True, keep_low_persistence_clusters=False):
"""Clusters the dataset with which the Persistable instance that was
passed through ``run_with`` was initialized.
conservative_flattening_style: bool, optional, default is False
conservative_flattening_style: bool, optional, default is True
If false, flatten the hierarchical clustering using the approach
of 'Persistence-Based Clustering in Riemannian Manifolds' Chazal, Guibas,
Oudot, Skraba. If true, use the more conservative and more stable approach
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2 changes: 1 addition & 1 deletion setup.py
Original file line number Diff line number Diff line change
Expand Up @@ -105,7 +105,7 @@ def readme():

setup(
name="persistable-clustering",
version="0.4.2",
version="0.4.3",
description="Density-based clustering for exploratory data analysis based on multi-parameter persistence",
long_description=readme(),
long_description_content_type="text/markdown",
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