infomap module¶

class infomap.Infomap(args=None)¶

Bases: infomap.InfomapWrapper

This class is a thin wrapper around Infomap C++ compiled with SWIG.

Examples

Create an instance and add nodes and links:

>>> import infomap
>>> im = infomap.Infomap()
>>> im.add_node(1)
>>> im.add_node(2)
>>> im.add_link(1, 2)
>>> im.run()
>>> im.codelength
1.0

Create an instance and read a network file:

>>> import infomap
>>> im = infomap.Infomap()
>>> im.read_file("ninetriangles.net")
>>> im.run("-N5")
>>> im.codelength
3.4841898804052187

For more examples, see the examples directory.

__init__(args=None)¶

Create a new Infomap instance.

Parameters: args (str, optional) – Space delimited parameter list (see Infomap documentation).

add_link(source_id, target_id, weight=1.0)¶

Add a link.

Notes

If the source or target nodes does not exist, they will be created.

See also

remove_link

Parameters

source_id (int) –
target_id (int) –
weight (float, optional) –

add_links(links)¶

Add several links.

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> links = (
...     (1, 2),
...     (1, 3)
... )
>>> im.add_links(links)
None

See also

add_link, remove_link

Parameters: links (iterable of tuples) – Iterable of tuples of int of the form (source_id, target_id, [weight])

add_multilayer_link(source_multilayer_node, target_multilayer_node, weight=1.0)¶

Add a multilayer link.

Adds a link between layers in a multilayer network.

Parameters

source_multilayer_node (tuple of int, or MultilayerNode) – If passed a tuple, it should be of the format (layer_id, node_id).
target_multilayer_node (tuple of int, or MultilayerNode) – If passed a tuple, it should be of the format (layer_id, node_id).
weight (float, optional) –

Examples

Usage with tuples:

>>> from infomap import Infomap
>>> im = Infomap()
>>> source_multilayer_node = (0, 1) # layer_id, node_id
>>> target_multilayer_node = (1, 2) # layer_id, node_id
>>> im.add_multilayer_link(source_multilayer_node, target_multilayer_node)
None

Usage with MultilayerNode

>>> from infomap import Infomap, MultilayerNode
>>> im = Infomap()
>>> source_multilayer_node = MultilayerNode(layer_id=0, node_id=1)
>>> target_multilayer_node = MultilayerNode(layer_id=1, node_id=2)
>>> im.add_multilayer_link(source_multilayer_node, target_multilayer_node)
None

add_multilayer_links(links)¶

Add several multilayer links.

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> links = (
...     ((0, 1), (1, 2)),
...     ((0, 3), (1, 2))
... )
>>> im.add_multilayer_links(links)
None

See also

add_multilayer_link

Parameters: links (iterable of tuples) – Iterable of tuples of the form (source_node, target_node, [weight])

add_node(node_id, name=None, teleportation_weight=None)¶

Add a node.

See also

set_name, add_nodes

Parameters

node_id (int) –
name (str, optional) –
teleportation_weight (float, optional) – Used for teleporting between layers in multilayer networks.

add_nodes(nodes)¶

Add several nodes.

See also

add_node

Examples

Add nodes

>>> from infomap import Infomap
>>> im = Infomap()
>>> im.add_nodes(range(4))
None

Add named nodes

>>> from infomap import Infomap
>>> im = Infomap()
>>> nodes = (
...     (1, "Node 1"),
...     (2, "Node 2"),
...     (3, "Node 3")
... )
>>> im.add_nodes(nodes)
None

Parameters: nodes (iterable of tuples or iterable of int) – Iterable of tuples on the form (node_id, [name], [teleportation_weight])

add_state_node(state_id, node_id)¶

Add a state node.

Notes

If a physical node with id node_id does not exist, it will be created. If you want to name the physical node, use set_name.

Parameters

state_id (int) –
node_id (int) – Id of the physical node the state node should be added to.

add_state_nodes(state_nodes)¶

Add several state nodes.

See also

add_state_node

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> states = (
...     (1, 1),
...     (2, 1),
...     (3, 2)
... )
>>> im.add_state_nodes(states)
None

Parameters: state_nodes (iterable of tuples) – Iterable of tuples of the form (state_id, node_id)

property bipartite_start_id¶

Get or set the bipartite start id.

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> im.add_node(1, "Left 1")
>>> im.add_node(2, "Left 2")
>>> im.bipartite_start_id = 3
>>> im.add_node(3, "Right 3")
>>> im.add_node(4, "Right 4")
>>> im.add_link(1, 3)
>>> im.add_link(1, 4)
>>> im.add_link(2, 4)
>>> im.run()
None

Parameters: start_id (int) – The node id where the second node type starts.
Returns: The node id where the second node type starts.
Return type: int

property codelength¶

Get the total (hierarchical) codelength.

See also

index_codelength, module_codelength

Returns: The codelength
Return type: float

property codelengths¶

Get the total (hierarchical) codelength for each trial.

See also

codelength

Returns: The codelengths for each trial
Return type: tuple of float

get_modules(depth_level=1, states=False)¶

Get the modules for a given depth in the hierarchical tree.

Parameters

depth_level (int, optional) – The level in the hierarchical tree. Set to 1 (default) to return the top modules (coarsest level), set to 2 for second coarsest level etc. Set to -1 to return the bottom level modules (finest level).
states (bool, optional) – For higher-order networks, if states is True, it will iterate over state nodes, otherwise it will iterate over physical nodes, merging state nodes with same node_id if they are in the same module. Note that the same physical node may end up on different paths in the tree. See notes on physical_tree.

Returns

Dict with node ids as keys and module ids as values.

Return type

dict of int

get_multilevel_modules(states=False)¶

Get all the modules.

Parameters: states (bool, optional) – For higher-order networks, if states is True, it will iterate over state nodes, otherwise it will iterate over physical nodes, merging state nodes with same node_id if they are in the same module. Note that the same physical node may end up on different paths in the tree. See notes on physical_tree.
Returns: Dict with node ids as keys and list of module ids as values.
Return type: dict of list of int

get_name(node_id, default=None)¶

Get the name of a node.

Notes

If the node name is an empty string, the default will be returned.

See also

set_name, names

Parameters

node_id (int) –
default (any) – The return value if the node name is missing.

Returns

The node name if it exists, else the default which is None

Return type

string or any

get_names()¶

Get all node names.

See also

names, get_name

Returns: A dict with node ids as keys and node names as values.
Return type: dict of string

get_nodes(depth_level=1, states=False)¶

A view of the tree

Parameters

depth_level (int, optional) – The module level returned by iterator.module_id. Set to 1 (default) to return the top modules (coarsest level), set to 2 for second coarsest level etc. Set to -1 to return the bottom level modules (finest level).
states (bool, optional) – For higher-order networks, if states is True, it will iterate over state nodes, otherwise it will iterate over physical nodes, merging state nodes with same node_id if they are in the same module. Note that the same physical node may end up on different paths in the tree. See notes on physical_tree.

Notes

For higher-order networks, each node is represented by a set of state nodes with the same node_id, where each state node represents a different memory constraining the random walker. This enables overlapping modules, where state nodes with the same node_id end up in different modules. However, the state nodes with the same node_id within each module are only visible as one (partial) physical node (if states = False).

Returns: An iterator over each node in the tree, depth first from the root
Return type: InfomapIterator or InfomapIteratorPhysical

get_tree(depth_level=1, states=False)¶

A view of the tree

Parameters

depth_level (int, optional) – The module level returned by iterator.module_id. Set to 1 (default) to return the top modules (coarsest level), set to 2 for second coarsest level etc. Set to -1 to return the bottom level modules (finest level).
states (bool, optional) – For higher-order networks, if states is True, it will iterate over state nodes, otherwise it will iterate over physical nodes, merging state nodes with same node_id if they are in the same module. Note that the same physical node may end up on different paths in the tree. See notes on physical_tree.

Notes

For higher-order networks, each node is represented by a set of state nodes with the same node_id, where each state node represents a different memory constraining the random walker. This enables overlapping modules, where state nodes with the same node_id end up in different modules. However, the state nodes with the same node_id within each module are only visible as one (partial) physical node (if states = False).

Returns: An iterator over each node in the tree, depth first from the root
Return type: InfomapIterator or InfomapIteratorPhysical

property index_codelength¶

Get the two-level index codelength.

See also

codelength, module_codelength

Returns: The two-level index codelength
Return type: float

property initial_partition¶

Get or set the initial partition.

This is a initial configuration of nodes into modules where Infomap will start the optimizer.

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> im.add_node(1)
>>> im.add_node(2)
>>> im.add_node(3)
>>> im.add_node(4)
>>> im.add_link(1, 2)
>>> im.add_link(1, 3)
>>> im.add_link(2, 3)
>>> im.add_link(2, 4)
>>> im.initial_partition = {
...     1: 0,
...     2: 0,
...     3: 1,
...     4: 1
... }
>>> im.run()
None

Notes

The initial partition is saved between runs. If you want to use an initial partition for one run only, use run(initial_partition=partition).

Parameters: module_ids (dict of int, or None) – Dict with node ids as keys and module ids as values.
Returns: Dict with node ids as keys and module ids as values.
Return type: dict of int

property leaf_modules¶

A view of the leaf modules, i.e. the bottom modules containing leaf nodes.

Returns: An iterator over each leaf module in the tree, depth first from the root
Return type: InfomapLeafModuleIterator

property max_depth¶

Get the max depth of the hierarchical tree.

Returns: The max depth
Return type: int

property meta_codelength¶

Get the meta codelength.

This is the meta entropy times the meta data rate.

See also

meta_entropy

Returns: The meta codelength
Return type: float

property meta_entropy¶

Get the meta entropy (unweighted by meta data rate).

See also

meta_codelength

Returns: The meta entropy
Return type: float

property module_codelength¶

Get the total codelength of the modules.

The module codelength is defined such that codelength = index_codelength + module_codelength

For a hierarchical solution, the module codelength is the sum of codelengths for each top module.

See also

codelength, index_codelength

Returns: The module codelength
Return type: float

property modules¶

A view of the (top-level) modules, mapping node_id to module_id.

Notes

In a higher-order network, a physical node (defined by node_id) may partially exist in multiple modules. However, the node_id can not exist multiple times as a key in the node-to-module map, so only one occurrence of a physical node will be retrieved. To get all states, use get_modules(states=True).

See also

get_modules

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> im.read_file("ninetriangles.net")
>>> im.run("-N5")
>>> for node_id, module_id in im.modules:
...     print(node_id, module_id)
...
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
0
0
0
0
0
0
0
0
0

See also

get_modules

Yields: tuple of int, int – An iterator of node_id, module_id pairs.

property names¶

Get all node names.

Short-hand for get_names.

See also

get_names, get_name

Returns: A dict with node ids as keys and node names as values.
Return type: dict of string

property network¶: Get the internal network.

property no_infomap¶

Set wether the optimizer should run or not.

Parameters: no_infomap (bool) –

property nodes¶

A view of the leaf nodes with the top level module ids

See also

get_nodes, InfomapLeafIterator

Returns: An iterator over each leaf node in the tree, depth first from the root
Return type: InfomapLeafIterator

property num_leaf_modules¶

Get the number of leaf modules in the tree

Returns: The number of leaf modules
Return type: int

property num_non_trivial_top_modules¶

Get the number of non-trivial top modules in the tree

A trivial module is a module with either one or all nodes within.

Returns: The number of non-trivial top modules
Return type: int

property num_top_modules¶

Get the number of top modules in the tree

Returns: The number of top modules
Return type: int

property one_level_codelength¶

Get the one-level codelength.

See also

codelength

Returns: The one-level codelength
Return type: float

property physical_nodes¶

A view of the physical leaf nodes with the top level module ids

Returns: An iterator over each physical leaf node in the tree, depth first from the root
Return type: InfomapLeafIteratorPhysical

property physical_tree¶

A view of the tree where that state nodes of the same node_id are merged to one physical node

See also

get_tree, InfomapIteratorPhysical

Returns: An iterator over each physical node in the tree, depth first from the root
Return type: InfomapIteratorPhysical

read_file(filename, accumulate=True)¶

Read network data from file.

Parameters

filename (str) –
accumulate (bool, optional) – If the network data should be accumulated to already added nodes and links (default True).

property relative_codelength_savings¶

Get the relative codelength savings.

This is defined as the reduction in codelength relative to the non-modular one-level solution:

S_L = 1 - L / L_1

where L is the codelength and L_1 the one_level_codelength.

See also

codelength, one_level_codelength

Returns: The relative codelength savings
Return type: float

remove_link(source_id, target_id)¶

Remove a link.

Notes

Removing links will not remove nodes if they become disconnected.

See also

add_link

Parameters

source_id (int) –
target_id (int) –

remove_links(links)¶

Remove several links.

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> links = (
...     (1, 2),
...     (1, 3)
... )
>>> im.remove_links(links)
None

See also

remove_link

Parameters: links (iterable of tuples) – Iterable of tuples of the form (source_id, target_id)

run(args=None, initial_partition=None)¶

Run Infomap.

Parameters

args (str, optional) – Space delimited parameter list (see Infomap documentation).
initial_partition (dict, optional) – Initial partition to start optimizer from (see initial_partition).

See also

initial_partition

set_meta_data(node_id, meta_category)¶

Set meta data to a node.

Parameters

node_id (int) –
meta_category (int) –

set_name(node_id, name)¶

Set the name of a node.

Parameters

node_id (int) –
name (str) –

set_names(names)¶

Set names to several nodes at once.

Example

>>> from infomap import Infomap
>>> im = Infomap()
>>> names = (
...     (1, "Node 1"),
...     (2, "Node 2")
... )
>>> im.set_names(names)
None

See also

set_name

Parameters: names (iterable of tuples) – Iterable of tuples on the form (node_id, name).

property tree¶

A view of the tree

See also

get_tree, InfomapIterator

Returns: An iterator over each node in the tree, depth first from the root
Return type: InfomapIterator

write_clu(filename, states=False, depth_level=1)¶

Write result to a clu file.

See also

write_tree, write_flow_tree

Parameters

filename (str) –
states (bool, optional) – If the state nodes should be included (default False).
depth_level (int, optional) – The depth in the hierarchical tree to write.

write_flow_tree(filename, states=False)¶

Write result to a ftree file.

See also

write_clu, write_tree

Parameters

filename (str) –
states (bool, optional) – If the state nodes should be included (default False).

write_tree(filename, states=False)¶

Write result to a tree file.

See also

write_clu, write_flow_tree

Parameters

filename (str) –
states (bool, optional) – If the state nodes should be included (default False).

class infomap.MultilayerNode(layer_id, node_id)¶

Bases: tuple

layer_id¶: Alias for field number 0

node_id¶: Alias for field number 1

class infomap.InfoNode(*args)¶

property child_degree¶

The number of children.

Returns: Number of children
Return type: int

property flow¶

Get the flow of the node.

Returns: The flow
Return type: float

get_meta_data(dimension=0)¶

Get meta data on a specific dimension.

Parameters: dimension (int) – The dimension (default 0)
Returns: The meta data
Return type: int

property is_leaf¶

True if the node has no children.

Returns: Is leaf node
Return type: bool

property is_leaf_module¶

True if the node has children but no grandchildren.

Returns: Is leaf module
Return type: bool

property is_root¶

True if the node has no parent.

Returns: Is root
Return type: bool

property layer_id¶

Get the layer id of a multilayer node.

Returns: The layer id
Return type: int

property meta_data¶

Meta data (on first dimension if more).

Returns: The meta data
Return type: int

property node_id¶

Get the physical node id.

Returns: The node id
Return type: int

property state_id¶

Get the state id of the node.

Returns: The state id
Return type: int

class infomap.InfomapIterator(*args)¶

property child_index¶

Get the child index.

Returns: The child index
Return type: int

property depth¶

Get the depth.

Returns: The depth
Return type: int

property module_id¶

Get the module id of the node.

Returns: The module id
Return type: int

property path¶

Get the path to the node in the tree.

Returns: The path
Return type: tuple of ints

class infomap.InfomapLeafModuleIterator(*args)¶

property child_index¶

Get the child index.

Returns: The child index
Return type: int

property depth¶

Get the depth.

Returns: The depth
Return type: int

property module_id¶

Get the module id of the node.

Returns: The module id
Return type: int

property path¶

Get the path to the node in the tree.

Returns: The path
Return type: tuple of ints

class infomap.InfomapLeafIterator(*args)¶

property child_index¶

Get the child index.

Returns: The child index
Return type: int

property depth¶

Get the depth.

Returns: The depth
Return type: int

property module_id¶

Get the module id of the node.

Returns: The module id
Return type: int

property path¶

Get the path to the node in the tree.

Returns: The path
Return type: tuple of ints

class infomap.InfomapIteratorPhysical(*args)¶

property child_index¶

Get the child index.

Returns: The child index
Return type: int

property depth¶

Get the depth.

Returns: The depth
Return type: int

property module_id¶

Get the module id of the node.

Returns: The module id
Return type: int

property path¶

Get the path to the node in the tree.

Returns: The path
Return type: tuple of ints

class infomap.InfomapLeafIteratorPhysical(*args)¶

property child_index¶

Get the child index.

Returns: The child index
Return type: int

property depth¶

Get the depth.

Returns: The depth
Return type: int

property module_id¶

Get the module id of the node.

Returns: The module id
Return type: int

property path¶

Get the path to the node in the tree.

Returns: The path
Return type: tuple of ints

infomap module¶

Infomap

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