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gargantext
clustering-louvain
Commits
70e38ea9
Commit
70e38ea9
authored
Mar 27, 2020
by
Przemyslaw Kaminski
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[FLouvain] second louvain step and runFLouvain cycle
parent
1acd124c
Changes
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-126
clustering-louvain.cabal
clustering-louvain.cabal
+2
-1
Example.hs
src/Data/Graph/Clustering/Example.hs
+23
-7
FLouvain.hs
src/Data/Graph/Clustering/FLouvain.hs
+46
-113
Louvain.hs
src/Data/Graph/Clustering/Louvain.hs
+3
-3
Types.hs
src/Data/Graph/Clustering/Louvain/Types.hs
+89
-0
Utils.hs
src/Data/Graph/Clustering/Louvain/Utils.hs
+15
-1
FGL.hs
src/Data/Graph/FGL.hs
+1
-1
No files found.
clustering-louvain.cabal
View file @
70e38ea9
...
...
@@ -4,7 +4,7 @@ cabal-version: 1.12
--
-- see: https://github.com/sol/hpack
--
-- hash:
e1e53adbd24148d990b70f078530a01370effd8531413470ea9947aa095bf24
7
-- hash:
70b34ec62fea08353f69f29cc103940feb22097a32b1f061446843b348e5f72
7
name: clustering-louvain
version: 0.1.0.0
...
...
@@ -30,6 +30,7 @@ library
Data.Graph.Clustering.Example
Data.Graph.Clustering.HLouvain
Data.Graph.Clustering.ILouvain
Data.Graph.Clustering.Louvain.Types
Paths_clustering_louvain
hs-source-dirs:
src
...
...
src/Data/Graph/Clustering/Example.hs
View file @
70e38ea9
...
...
@@ -4,28 +4,42 @@ import Protolude
import
Control.Monad
(
foldM_
)
import
Data.List
(
nub
,
sort
)
import
Data.Graph.Clustering.Louvain.Utils
import
Data.Graph.FGL
import
Data.Graph.Inductive
import
Data.Graph.Clustering.FLouvain
import
qualified
Data.Text
as
T
import
qualified
Text.ParserCombinators.Parsec
as
P
import
Text.Parsec.Language
(
haskellStyle
)
import
qualified
Text.Parsec.Token
as
PT
import
Data.Graph.Clustering.Louvain.Utils
import
Data.Graph.Clustering.Louvain.Types
import
Data.Graph.Clustering.FLouvain
-- | Run FLouvain.iterate on an example graph
-- Example call:
-- putStrLn $ prettify $ iterateOnce cuiller
-- Prelude.map (fst3 . unCommunity . snd) $ labNodes $ iterateOnce karate
iterateOnce
::
Gr
()
Double
->
CGr
iterateOnce
::
Gr
a
Double
->
CGr
a
iterateOnce
gr
=
iteration
fgr
cgr
where
fgr
=
toFGraph
gr
cgr
=
initialCGr
fgr
runIterations
::
Int
->
Gr
()
Double
->
IO
()
runIterations
n
gr
=
do
let
fgr
=
toFGraph
gr
runFLouvain
::
(
Show
a
,
Eq
a
)
=>
Int
->
Int
->
FGraph
a
()
->
IO
()
runFLouvain
0
_
fgr
=
return
()
runFLouvain
cycles
n
fgr
=
do
cgr
<-
runFIterations
n
fgr
let
fgrNext
=
louvainSecondStep
fgr
cgr
putStrLn
(
"-----------------"
::
Text
)
putStrLn
(
"New FGraph:"
::
Text
)
putStrLn
$
prettify
fgrNext
runFLouvain
(
cycles
-
1
)
n
fgrNext
runIterations
::
Show
a
=>
Int
->
Gr
a
Double
->
IO
(
CGr
a
)
runIterations
n
gr
=
runFIterations
n
$
toFGraph
gr
runFIterations
::
Show
a
=>
Int
->
FGraph
a
()
->
IO
(
CGr
a
)
runFIterations
n
fgr
=
do
let
fgrWeight
=
graphWeight
fgr
let
initCgr
=
initialCGr
fgr
...
...
@@ -41,6 +55,8 @@ runIterations n gr = do
putStrLn
(
"Non-empty communities: "
::
Text
)
mapM_
(
\
c
->
putStrLn
(
show
c
::
Text
))
coms
return
lastCgr
where
runIteration
fgr
fgrWeight
iterCgr
i
=
do
let
iterNextCgr
=
iteration
fgr
iterCgr
...
...
@@ -50,7 +66,7 @@ runIterations n gr = do
putStrLn
$
T
.
unpack
$
show
$
modularity
fgr
iterNextCgr
fgrWeight
return
iterNextCgr
runLouvainFirstStepIterate
::
Int
->
Gr
()
Double
->
(
Modularity
,
CGr
)
runLouvainFirstStepIterate
::
Int
->
Gr
a
Double
->
(
Modularity
,
CGr
a
)
runLouvainFirstStepIterate
n
gr
=
(
modularity
fgr
cgr
m
,
cgr
)
where
fgr
=
toFGraph
gr
...
...
src/Data/Graph/Clustering/FLouvain.hs
View file @
70e38ea9
...
...
@@ -40,29 +40,13 @@ import Data.Graph.Inductive
import
qualified
Data.List
as
DL
import
Data.Graph.FGL
-- "glue" : function to gather/merge communities
-- "klue" : function to split communities
data
ClusteringMethod
=
Glue
|
Klue
deriving
(
Eq
)
import
Data.Graph.Clustering.Louvain.Utils
(
fixPt
,
mkFGraph
)
import
Data.Graph.Clustering.Louvain.Types
------------------------------------------------------------------------
-- | Fixed point with at most n iterations
-- 'Int' argument is the maximal number of iterations to make
-- 'a -> a' is the iterator function
-- 'a -> Bool' is the condition checking function ('True' continues looping, 'False' breaks it)
-- 'a' is the initial value
fixPt
::
Int
->
(
a
->
a
)
->
(
a
->
Bool
)
->
a
->
a
fixPt
0
iterator
_
init
=
iterator
init
fixPt
n
iterator
cond
init
=
if
cond
next
then
fixPt
(
n
-
1
)
iterator
cond
init
else
next
where
next
=
iterator
init
-- | Main Louvain first step iteration function
louvainFirstStepIterate
::
Int
->
FGraph
a
b
->
CGr
louvainFirstStepIterate
::
Int
->
FGraph
a
b
->
CGr
a
louvainFirstStepIterate
n
gr
=
fixPt
n
iterator
cond
initCGr
where
initCGr
=
initialCGr
gr
...
...
@@ -72,95 +56,44 @@ louvainFirstStepIterate n gr = fixPt n iterator cond initCGr
-- | Second step from the Louvain paper -- given a clustering, create new graph
-- of clusters
louvainSecondStep
::
FGraph
a
b
->
CGr
->
FGraph
a
b
louvainSecondStep
gr
cgr
=
gr
louvainSecondStep
::
forall
a
b
c
.
Eq
c
=>
FGraph
a
b
->
CGr
c
->
FGraph
(
Community
c
)
()
louvainSecondStep
gr
cgr
=
mkFGraph
nodes
edges
where
nodes
::
[
LNode
(
Community
c
)]
--nodes = filter (\(_, com) -> length (comNodes com) > 0) $ labNodes cgr
nodes
=
labNodes
cgr
edges
::
[(
Node
,
Node
,
Double
)]
edges
=
concatMap
comEdges
$
labNodes
cgr
comEdges
::
LNode
(
Community
c
)
->
[(
Node
,
Node
,
Double
)]
comEdges
lnCom
=
mapMaybe
(
comToComEdge
lnCom
)
$
labNodes
cgr
comToComEdge
::
LNode
(
Community
c
)
->
LNode
(
Community
c
)
->
Maybe
(
Node
,
Node
,
Double
)
-- No self-edges
comToComEdge
lnCom1
lnCom2
|
lnCom1
==
lnCom2
=
Nothing
comToComEdge
(
_
,
com1
)
_
|
length
(
comNodes
com1
)
==
0
=
Nothing
comToComEdge
_
(
_
,
com2
)
|
length
(
comNodes
com2
)
==
0
=
Nothing
comToComEdge
(
com1N
,
com1
)
(
com2N
,
com2
)
=
Just
(
com1N
,
com2N
,
comToComWeight
gr
com1
com2
)
-- | Weight between communities. Base graph is needed to fetch weights between
-- individual nodes.
comToComWeight
::
FGraph
a
b
->
Community
c
->
Community
c
->
Double
comToComWeight
gr
com1
com2
=
weight
where
weight
::
Double
weight
=
sum
$
map
(
\
n
->
unNodeComWeightSum
$
nodeComWeightSum
com2
$
context
gr
n
)
$
comNodes
com1
------------------------------------------------------------------------
-- Our basic graph. Nodes have custom labels. Edges have weight assigned to them.
newtype
Weight
=
Weight
{
unWeight
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
type
FEdge
b
=
(
Weight
,
b
)
fedgeWeight
::
FEdge
b
->
Double
fedgeWeight
=
unWeight
.
fst
sumEdgeWeights
::
Adj
(
FEdge
b
)
->
Double
sumEdgeWeights
es
=
sum
$
map
(
fedgeWeight
.
fst
)
es
type
FGraph
a
b
=
Gr
a
(
FEdge
b
)
-- | Used for k_i in formula (2)
-- (sum of the weights of the links incident to node i)
newtype
NodeWeightSum
=
NodeWeightSum
{
unNodeWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
nodeWeightSum
::
Context
a
(
FEdge
b
)
->
NodeWeightSum
nodeWeightSum
(
p
,
_
,
_
,
s
)
=
NodeWeightSum
$
sumEdgeWeights
$
p
<>
s
-- |Used for k_i,in in formula (2)
-- (Sum of weights of links from a given 'Node' to nodes in a given 'Community')
newtype
NodeComWeightSum
=
NodeComWeightSum
{
unNodeComWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
nodeComWeightSum
::
Community
->
Context
a
(
FEdge
b
)
->
NodeComWeightSum
nodeComWeightSum
com
(
p
,
_
,
_
,
s
)
=
NodeComWeightSum
$
sumEdgeWeights
$
filter
(
\
(
_
,
n
)
->
n
`
elem
`
comNodes
com
)
$
p
<>
s
newtype
NodeNonComWeightSum
=
NodeNonComWeightSum
{
unNodeNonComWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
nodeNonComWeightSum
::
Community
->
Context
a
(
FEdge
b
)
->
NodeNonComWeightSum
nodeNonComWeightSum
com
(
p
,
_
,
_
,
s
)
=
NodeNonComWeightSum
$
sumEdgeWeights
$
filter
(
\
(
_
,
n
)
->
n
`
notElem
`
comNodes
com
)
$
p
<>
s
-- Probably this structure is better to reduce the number of computations
-- (precompute sum of node weights, which is the k_i variable in formula (2)).
-- type FNode a = (NodeWeightSum, a)
-- fnodeWeightSum :: FNode a -> Double
-- fnodeWeightSum = unNodeWeightSum . fst
-- | This is the m variable in formula (2) of the Louvain paper
newtype
GraphWeightSum
=
GraphWeightSum
{
unGraphWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | This is the \Sum_in in formula (2) of the Louvain paper
-- (sum of the weights of the links inside C)
newtype
InWeightSum
=
InWeightSum
{
unInWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | This is the \Sum_tot in formula (2) of the Louvain paper
-- (sum of the weights of the links incident to nodes in C)
newtype
TotWeightSum
=
TotWeightSum
{
unTotWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | Computed Delta_Q value in (2)
newtype
DeltaQ
=
DeltaQ
{
unDeltaQ
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
newtype
Modularity
=
Modularity
{
unModularity
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | Type for the clusters we will be creating.
newtype
Community
=
Community
{
unCommunity
::
([
Node
],
InWeightSum
,
TotWeightSum
)
}
deriving
(
Show
,
Eq
,
Ord
)
comNodes
::
Community
->
[
Node
]
comNodes
(
Community
(
ns
,
_
,
_
))
=
ns
comInWeightSum
::
Community
->
InWeightSum
comInWeightSum
(
Community
(
_
,
inWeightSum
,
_
))
=
inWeightSum
comTotWeightSum
::
Community
->
TotWeightSum
comTotWeightSum
(
Community
(
_
,
_
,
totWeightSum
))
=
totWeightSum
type
CGrNode
=
Node
type
CGrEdge
=
(
InWeightSum
,
TotWeightSum
)
type
CGr
=
Gr
Community
()
graphWeight
::
FGraph
a
b
->
GraphWeightSum
graphWeight
gr
=
GraphWeightSum
$
0.5
*
ufold
(
\
(
_
,
n
,
_
,
_
)
->
weight'
$
context
gr
n
)
0
gr
where
weight'
(
p
,
_
,
_
,
s
)
acc
=
acc
+
(
sumEdgeWeights
$
p
<>
s
)
-- | Compute initial 'CGr' for a given 'FGraph a b'. This means, put each node
-- in a separate community.
initialCGr
::
FGraph
a
b
->
CGr
initialCGr
::
FGraph
a
b
->
CGr
a
initialCGr
gr
=
gmap
singletonCom
gr
where
-- A singleton community is given:
-- the same node id for a community
-- same incoming/outgoing edges
-- custom Community label
singletonCom
(
p
,
v
,
_
,
s
)
=
(
p'
,
v
,
Community
([
v
],
iws
,
tws
),
s'
)
singletonCom
(
p
,
v
,
l
,
s
)
=
(
p'
,
v
,
Community
([
v
],
iws
,
tws
,
l
),
s'
)
where
p'
=
map
edgeComRemap
p
s'
=
map
edgeComRemap
s
...
...
@@ -177,7 +110,7 @@ initialCGr gr = gmap singletonCom gr
-- | Q function from Louvain paper (1).
-- We just fold over the communities (this is because of the delta(c_i, c_j)
-- param)
modularity
::
FGraph
a
b
->
CGr
->
GraphWeightSum
->
Modularity
modularity
::
FGraph
a
b
->
CGr
c
->
GraphWeightSum
->
Modularity
modularity
gr
cgr
m
=
Modularity
$
coeff
*
(
ufold
modularity'
0.0
cgr
)
where
coeff
=
0.5
/
(
unGraphWeightSum
m
)
...
...
@@ -194,9 +127,9 @@ modularity gr cgr m = Modularity $ coeff * ( ufold modularity' 0.0 cgr )
ki
::
Node
->
Double
ki
n
=
unNodeWeightSum
$
nodeWeightSum
$
context
gr
n
type
Delta
=
Community
->
NodeWeightSum
->
NodeComWeightSum
->
GraphWeightSum
->
DeltaQ
type
Delta
c
=
Community
c
->
NodeWeightSum
->
NodeComWeightSum
->
GraphWeightSum
->
DeltaQ
-- | Delta Q function from Louvain paper (2).
delta
::
Delta
delta
::
Delta
c
delta
com
ki
kiin
m
=
DeltaQ
$
acc
-
dec
where
inWeightSum
=
comInWeightSum
com
...
...
@@ -218,7 +151,7 @@ delta com ki kiin m = DeltaQ $ acc - dec
-- 'step . context gr . node''
-- We could avoid the higher complexity, eg. by precomputing the whole graph
-- into a HashMap Node [Edge].
iteration
::
FGraph
a
b
->
CGr
->
CGr
iteration
::
FGraph
a
b
->
CGr
c
->
CGr
c
iteration
gr
cs
=
xdfsFoldWith
suc'
(
\
(
_
,
v
,
_
,
_
)
->
step
gw
$
context
gr
$
v
)
cs
(
nodes
gr
)
gr
where
...
...
@@ -229,7 +162,7 @@ iteration gr cs = xdfsFoldWith suc' (\(_, v, _, _)
-- TODO Remember to filter out empty Communities
-- | Step for one node. We try re-assign it to a neighbouring community, where
-- the increase of modularity for graph will be the largest
step
::
GraphWeightSum
->
CFunFold
a
(
FEdge
b
)
CGr
step
::
forall
a
b
c
.
GraphWeightSum
->
CFunFold
a
(
FEdge
b
)
(
CGr
c
)
step
gw
ctx
@
(
_
,
v
,
_
,
_
)
cgr
=
newCgr
where
newCgr
=
case
mNc
of
...
...
@@ -246,9 +179,9 @@ step gw ctx@(_, v, _, _) cgr = newCgr
(
bestFitCom
,
DeltaQ
bestFitdq
)
=
maximumBy
(
\
(
_
,
deltaq1
)
(
_
,
deltaq2
)
->
compare
deltaq1
deltaq2
)
deltas
mNc
::
Maybe
(
LNode
Community
)
mNc
::
Maybe
(
LNode
(
Community
c
)
)
mNc
=
nodeCommunity
v
cgr
ncs
::
[
LNode
Community
]
ncs
::
[
LNode
(
Community
c
)
]
ncs
=
nodeNeighbours
v
cgr
-- We move node from community nc into ncs
...
...
@@ -258,17 +191,17 @@ step gw ctx@(_, v, _, _) cgr = newCgr
-- Just nc -> Just ( makeMove OutOf nc
-- , map (makeMove Into) ncs )
makeMove
::
Direction
->
LNode
Community
->
LNode
Community
makeMove
::
Direction
->
LNode
(
Community
c
)
->
LNode
(
Community
c
)
makeMove
direction
(
cn
,
c
)
=
(
cn
,
moveNodeWithContext
ctx
direction
c
)
-- k_i variable in formula (2)
ki
::
NodeWeightSum
ki
=
nodeWeightSum
ctx
deltas
::
[(
LNode
Community
,
DeltaQ
)]
deltas
::
[(
LNode
(
Community
c
)
,
DeltaQ
)]
deltas
=
map
(
\
c
->
(
c
,
delta'
c
))
ncs
delta'
::
LNode
Community
->
DeltaQ
delta'
::
LNode
(
Community
c
)
->
DeltaQ
delta'
com
=
delta
(
llab
com
)
ki
kiin
gw
where
-- k_i,in variable in formula (2)
...
...
@@ -291,14 +224,14 @@ data Direction = Into | OutOf
-- | Given 'Node' and 'Community' graph, find the 'LNode' of 'Community' which
-- contains the node
nodeCommunity
::
Node
->
CGr
->
Maybe
(
LNode
Community
)
nodeCommunity
::
Node
->
CGr
c
->
Maybe
(
LNode
(
Community
c
)
)
nodeCommunity
n
cgr
=
head
(
filter
f
$
labNodes
cgr
)
where
f
::
(
a
,
Community
)
->
Bool
f
::
(
a
,
Community
c
)
->
Bool
f
(
_
,
com
)
=
n
`
elem
`
comNodes
com
-- | Find 'LNode's of 'Community' graph neighbouring a given node
nodeNeighbours
::
Node
->
CGr
->
[
LNode
Community
]
nodeNeighbours
::
Node
->
CGr
c
->
[
LNode
(
Community
c
)
]
nodeNeighbours
n
cgr
=
case
nodeCommunity
n
cgr
of
Nothing
->
[]
...
...
@@ -312,16 +245,16 @@ nodeNeighbours n cgr =
-- Just (cn, _) -> lneighbors cgr cn
-- | Moves 'Node' in the 'Direction' of 'Community' and recomputes 'Community''s weights
moveNode
::
forall
a
b
.
FGraph
a
b
->
Node
->
Direction
->
Community
->
Community
moveNode
::
forall
a
b
c
.
FGraph
a
b
->
Node
->
Direction
->
Community
c
->
Community
c
moveNode
gr
n
direction
c
=
moveNodeWithContext
ctx
direction
c
where
ctx
::
Context
a
(
FEdge
b
)
ctx
=
context
gr
n
-- | Same as 'moveNode' above but with only node context, not whole graph
moveNodeWithContext
::
forall
a
b
.
Context
a
(
FEdge
b
)
->
Direction
->
Community
->
Community
moveNodeWithContext
ctx
@
(
_
,
n
,
_
,
_
)
direction
com
@
(
Community
(
ns
,
inwsum
,
totwsum
))
=
Community
(
newNs
,
InWeightSum
newInWsum
,
TotWeightSum
newTotWsum
)
moveNodeWithContext
::
forall
a
b
c
.
Context
a
(
FEdge
b
)
->
Direction
->
Community
c
->
Community
c
moveNodeWithContext
ctx
@
(
_
,
n
,
_
,
_
)
direction
com
@
(
Community
(
ns
,
inwsum
,
totwsum
,
l
))
=
Community
(
newNs
,
InWeightSum
newInWsum
,
TotWeightSum
newTotWsum
,
l
)
where
newNs
=
case
direction
of
Into
->
sort
(
n
:
ns
)
...
...
src/Data/Graph/Clustering/Louvain.hs
View file @
70e38ea9
...
...
@@ -19,11 +19,11 @@ References:
module
Data.Graph.Clustering.Louvain
where
import
Data.Tuple.Extra
(
fst3
)
import
Data.List
(
maximumBy
,
nub
,
intersect
,
foldl'
,
zipWith
,
concat
)
import
Data.Graph.Inductive
import
Data.Graph.Clustering.Louvain.Utils
(
LouvainNode
(
..
),
toFGraph
)
import
Data.Graph.Clustering.FLouvain
(
louvainFirstStepIterate
,
Community
(
..
),
initialCGr
)
import
Data.Graph.Clustering.FLouvain
(
louvainFirstStepIterate
,
initialCGr
)
import
Data.Graph.Clustering.Louvain.Types
(
Community
(
..
),
comNodes
)
------------------------------------------------------------------------
-- | Definitions
------------------------------------------------------------------------
...
...
@@ -35,7 +35,7 @@ type Reverse = Bool
------------------------------------------------------------------------
flouvain
::
Int
->
Gr
()
Double
->
[[
Node
]]
flouvain
n
g
=
map
(
fst3
.
unCommunity
.
snd
)
$
labNodes
g'
flouvain
n
g
=
map
(
comNodes
.
snd
)
$
labNodes
g'
where
g'
=
louvainFirstStepIterate
n
(
toFGraph
g
)
------------------------------------------------------------------------
...
...
src/Data/Graph/Clustering/Louvain/Types.hs
0 → 100644
View file @
70e38ea9
module
Data.Graph.Clustering.Louvain.Types
where
import
Protolude
import
Data.Graph.Inductive
-- "glue" : function to gather/merge communities
-- "klue" : function to split communities
data
ClusteringMethod
=
Glue
|
Klue
deriving
(
Eq
)
newtype
Weight
=
Weight
{
unWeight
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
type
FEdge
b
=
(
Weight
,
b
)
fedgeWeight
::
FEdge
b
->
Double
fedgeWeight
=
unWeight
.
fst
sumEdgeWeights
::
Adj
(
FEdge
b
)
->
Double
sumEdgeWeights
es
=
sum
$
map
(
fedgeWeight
.
fst
)
es
-- Our basic graph. Nodes have custom labels. Edges have weight assigned to them.
type
FGraph
a
b
=
Gr
a
(
FEdge
b
)
-- | Used for k_i in formula (2)
-- (sum of the weights of the links incident to node i)
newtype
NodeWeightSum
=
NodeWeightSum
{
unNodeWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
nodeWeightSum
::
Context
a
(
FEdge
b
)
->
NodeWeightSum
nodeWeightSum
(
p
,
_
,
_
,
s
)
=
NodeWeightSum
$
sumEdgeWeights
$
p
<>
s
-- | Used for k_i,in in formula (2)
-- (Sum of weights of links from a given 'Node' to nodes in a given 'Community')
newtype
NodeComWeightSum
=
NodeComWeightSum
{
unNodeComWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
nodeComWeightSum
::
Community
c
->
Context
a
(
FEdge
b
)
->
NodeComWeightSum
nodeComWeightSum
com
(
p
,
_
,
_
,
s
)
=
NodeComWeightSum
$
sumEdgeWeights
$
filter
(
\
(
_
,
n
)
->
n
`
elem
`
comNodes
com
)
$
p
<>
s
newtype
NodeNonComWeightSum
=
NodeNonComWeightSum
{
unNodeNonComWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
nodeNonComWeightSum
::
Community
c
->
Context
a
(
FEdge
b
)
->
NodeNonComWeightSum
nodeNonComWeightSum
com
(
p
,
_
,
_
,
s
)
=
NodeNonComWeightSum
$
sumEdgeWeights
$
filter
(
\
(
_
,
n
)
->
n
`
notElem
`
comNodes
com
)
$
p
<>
s
-- Probably this structure is better to reduce the number of computations
-- (precompute sum of node weights, which is the k_i variable in formula (2)).
-- type FNode a = (NodeWeightSum, a)
-- fnodeWeightSum :: FNode a -> Double
-- fnodeWeightSum = unNodeWeightSum . fst
-- | This is the m variable in formula (2) of the Louvain paper
newtype
GraphWeightSum
=
GraphWeightSum
{
unGraphWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | This is the \Sum_in in formula (2) of the Louvain paper
-- (sum of the weights of the links inside C)
newtype
InWeightSum
=
InWeightSum
{
unInWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | This is the \Sum_tot in formula (2) of the Louvain paper
-- (sum of the weights of the links incident to nodes in C)
newtype
TotWeightSum
=
TotWeightSum
{
unTotWeightSum
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | Computed Delta_Q value in (2)
newtype
DeltaQ
=
DeltaQ
{
unDeltaQ
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | Computed modularity in (1)
newtype
Modularity
=
Modularity
{
unModularity
::
Double
}
deriving
(
Show
,
Eq
,
Ord
)
-- | Type for the clusters we will be creating.
newtype
Community
a
=
Community
{
unCommunity
::
([
Node
],
InWeightSum
,
TotWeightSum
,
a
)
}
deriving
(
Show
,
Eq
,
Ord
)
comNodes
::
Community
c
->
[
Node
]
comNodes
(
Community
(
ns
,
_
,
_
,
_
))
=
ns
comInWeightSum
::
Community
c
->
InWeightSum
comInWeightSum
(
Community
(
_
,
inWeightSum
,
_
,
_
))
=
inWeightSum
comTotWeightSum
::
Community
c
->
TotWeightSum
comTotWeightSum
(
Community
(
_
,
_
,
totWeightSum
,
_
))
=
totWeightSum
comLabel
::
Community
c
->
c
comLabel
(
Community
(
_
,
_
,
_
,
c
))
=
c
type
CGrNode
=
Node
type
CGrEdge
=
(
InWeightSum
,
TotWeightSum
)
type
CGr
a
=
Gr
(
Community
a
)
()
graphWeight
::
FGraph
a
b
->
GraphWeightSum
graphWeight
gr
=
GraphWeightSum
$
0.5
*
ufold
(
\
(
_
,
n
,
_
,
_
)
->
weight'
$
context
gr
n
)
0
gr
where
weight'
(
p
,
_
,
_
,
s
)
acc
=
acc
+
(
sumEdgeWeights
$
p
<>
s
)
src/Data/Graph/Clustering/Louvain/Utils.hs
View file @
70e38ea9
...
...
@@ -19,7 +19,7 @@ import Data.Graph.Inductive
import
Data.List
(
lookup
,
nub
)
import
qualified
Data.Map.Strict
as
Map
import
Data.Graph.Clustering.
FLouvain
(
FGraph
,
Weight
(
..
))
import
Data.Graph.Clustering.
Louvain.Types
data
LouvainNode
=
LouvainNode
{
l_node_id
::
Int
,
l_community_id
::
Int
...
...
@@ -63,3 +63,17 @@ toFGraph gr = gmap remap gr
edgeMap
(
w
,
n
)
=
((
Weight
w
,
()
),
n
)
p'
=
map
edgeMap
p
s'
=
map
edgeMap
s
-- | Fixed point with at most n iterations
-- 'Int' argument is the maximal number of iterations to make
-- 'a -> a' is the iterator function
-- 'a -> Bool' is the condition checking function ('True' continues looping, 'False' breaks it)
-- 'a' is the initial value
fixPt
::
Int
->
(
a
->
a
)
->
(
a
->
Bool
)
->
a
->
a
fixPt
0
iterator
_
init
=
iterator
init
fixPt
n
iterator
cond
init
=
if
cond
next
then
fixPt
(
n
-
1
)
iterator
cond
init
else
next
where
next
=
iterator
init
src/Data/Graph/FGL.hs
View file @
70e38ea9
...
...
@@ -22,7 +22,7 @@ replaceLNode gr (n, ln) = gmap replacer gr
-- | Find LNode of a node (i.e. a node with label)
lnode
::
(
Graph
gr
)
=>
gr
a
b
->
Node
->
Maybe
(
LNode
a
)
lnode
cgr
n
=
case
lab
c
gr
n
of
lnode
gr
n
=
case
lab
gr
n
of
Nothing
->
Nothing
Just
l
->
Just
(
n
,
l
)
...
...
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