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Tiago Peixoto
graph-tool
Commits
ed54390f
Commit
ed54390f
authored
Feb 02, 2014
by
Tiago Peixoto
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Change default value for parameter 'c' in multilevel_minimize()
parent
0e21f9a5
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src/graph_tool/community/blockmodel.py
src/graph_tool/community/blockmodel.py
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src/graph_tool/community/blockmodel.py
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ed54390f
...
...
@@ -1017,7 +1017,7 @@ class MinimizeState(object):
def
multilevel_minimize
(
state
,
B
,
nsweeps
=
10
,
adaptive_sweeps
=
True
,
epsilon
=
0
,
anneal
=
(
1.
,
1.
),
r
=
2.
,
nmerge_sweeps
=
10
,
greedy
=
True
,
c
=
1
.
,
dense
=
False
,
multigraph
=
False
,
sequential
=
True
,
c
=
0
.
,
dense
=
False
,
multigraph
=
False
,
sequential
=
True
,
checkpoint
=
None
,
minimize_state
=
None
,
verbose
=
False
):
r
"""Performs an agglomerative heuristic, which progressively merges blocks together (while allowing individual node moves) to achieve a good partition in ``B`` blocks.
...
...
@@ -1052,7 +1052,7 @@ def multilevel_minimize(state, B, nsweeps=10, adaptive_sweeps=True, epsilon=0,
If ``True``, the value of ``beta`` of the MCMC steps are kept at
infinity for all steps. Otherwise they change according to the ``anneal``
parameter.
c : ``float`` (optional, default: ``
1
.0``)
c : ``float`` (optional, default: ``
0
.0``)
This parameter specifies how often fully random moves are attempted,
instead of more likely moves based on the inferred block partition.
For ``c == 0``, no fully random moves are attempted, and for ``c == inf``
...
...
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