Main functions#

`nngt.generate`(di_instructions, **kwargs)	Generate a `Graph` or one of its subclasses from a `dict` containing all the relevant informations.
`nngt.get_config`([key, detailed])	Get the NNGT configuration as a dictionary.
`nngt.load_from_file`(filename[, fmt, ...])	Load a Graph from a file.
`nngt.num_mpi_processes`()	Returns the number of MPI processes (1 if MPI is not used)
`nngt.on_master_process`()	Check whether the current code is executing on the master process (rank 0) if MPI is used.
`nngt.reset_config`()	Removed saved configuration and switch back to default
`nngt.save_config`()	Save configuration to make it persistent
`nngt.save_to_file`(graph, filename[, fmt, ...])	Save a graph to file.
`nngt.seed`([msd, seeds])	Seed the random generator used by NNGT (i.e.
`nngt.set_config`(config[, value, silent])	Set NNGT's configuration.
`nngt.use_backend`(backend[, reloading, silent])	Allows the user to switch to a specific graph library as backend.

Details#

nngt.generate(di_instructions, **kwargs)[source]#

Generate a Graph or one of its subclasses from a dict containing all the relevant informations.

Parameters:: di_instructions (dict) – Dictionary containing the instructions to generate the graph. It must have at least "graph_type" in its keys, with a value among "distance_rule", "erdos_renyi", "fixed_degree", "newman_watts", "price_scale_free", "random_scale_free". Depending on the type, di_instructions should also contain at least all non-optional arguments of the generator function.

See also

generation

nngt.get_config(key=None, detailed=False)[source]#: Get the NNGT configuration as a dictionary.

Note

This function has no MPI barrier on it.

nngt.load_from_file(filename, fmt='auto', separator=' ', secondary=';', attributes=None, attributes_types=None, notifier='@', ignore='#', name='LoadedGraph', directed=True, cleanup=False)[source]#

Load a Graph from a file.

Changed in version 2.0: Added optional attributes_types and cleanup arguments.

Warning

Support for GraphML and DOT formats are currently limited and require one of the non-default backends (DOT requires graph-tool).

Parameters:

filename (str) – The path to the file.
fmt (str, optional (default: “neighbour”)) – The format used to save the graph. Supported formats are: “neighbour” (neighbour list, default if format cannot be deduced automatically), “ssp” (scipy.sparse), “edge_list” (list of all the edges in the graph, one edge per line, represented by a source target-pair), “gml” (gml format, default if filename ends with ‘.gml’), “graphml” (graphml format, default if filename ends with ‘.graphml’ or ‘.xml’), “dot” (dot format, default if filename ends with ‘.dot’), “gt” (only when using graph_tool`<http://graph-tool.skewed.de/>_ as library, detected if `filename ends with ‘.gt’).
separator (str, optional (default “ “)) – separator used to separate inputs in the case of custom formats (namely “neighbour” and “edge_list”)
secondary (str, optional (default: “;”)) – Secondary separator used to separate attributes in the case of custom formats.
attributes (list, optional (default: [])) – List of names for the attributes present in the file. If a notifier is present in the file, names will be deduced from it; otherwise the attributes will be numbered. For “edge_list”, attributes may also be present as additional columns after the source and the target.
attributes_types (dict, optional (default: str)) – Backup information if the type of the attributes is not specified in the file. Values must be callables (types or functions) that will take the argument value as a string input and convert it to the proper type.
notifier (str, optional (default: “@”)) – Symbol specifying the following as meaningfull information. Relevant information are formatted @info_name=info_value, where info_name is in (“attributes”, “directed”, “name”, “size”) and associated info_value are of type (list, bool, str, int). Additional notifiers are @type=SpatialGraph/Network/SpatialNetwork, which must be followed by the relevant notifiers among @shape, @structure, and @graph.
ignore (str, optional (default: “#”)) – Ignore lines starting with the ignore string.
name (str, optional (default: from file information or ‘LoadedGraph’)) – The name of the graph.
directed (bool, optional (default: from file information or True)) – Whether the graph is directed or not.
cleanup (bool, optional (default: False)) – If true, removes nodes before the first one that appears in the edges and after the last one and renumber the nodes from 0.

Returns:

graph (Graph or subclass) – Loaded graph.

nngt.num_mpi_processes()[source]#: Returns the number of MPI processes (1 if MPI is not used)

nngt.on_master_process()[source]#

Check whether the current code is executing on the master process (rank 0) if MPI is used.

Returns:

True if rank is 0, if mpi4py is not present or if MPI is not used,
otherwise False.

nngt.reset_config()[source]#: Removed saved configuration and switch back to default

nngt.save_config()[source]#: Save configuration to make it persistent

nngt.save_to_file(graph, filename, fmt='auto', separator=' ', secondary=';', attributes=None, notifier='@')[source]#

Save a graph to file.

@todo: implement dot, xml/graphml, and gt formats

Parameters:

graph (Graph or subclass) – Graph to save.
filename (str) – The path to the file.
fmt (str, optional (default: “auto”)) – The format used to save the graph. Supported formats are: “neighbour” (neighbour list, default if format cannot be deduced automatically), “ssp” (scipy.sparse), “edge_list” (list of all the edges in the graph, one edge per line, represented by a source target-pair), “gml” (gml format, default if filename ends with ‘.gml’), “graphml” (graphml format, default if filename ends with ‘.graphml’ or ‘.xml’), “dot” (dot format, default if filename ends with ‘.dot’), “gt” (only when using graph_tool as library, detected if filename ends with ‘.gt’).
separator (str, optional (default “ “)) – separator used to separate inputs in the case of custom formats (namely “neighbour” and “edge_list”)
secondary (str, optional (default: “;”)) – Secondary separator used to separate attributes in the case of custom formats.
attributes (list, optional (default: None)) – List of names for the edge attributes present in the graph that will be saved to disk; by default (None), all attributes will be saved.
notifier (str, optional (default: “@”)) – Symbol specifying the following as meaningfull information. Relevant information are formatted @info_name=info_value, with info_name in (“attributes”, “attr_types”, “directed”, “name”, “size”). Additional notifiers are @type=SpatialGraph/Network/SpatialNetwork, which are followed by the relevant notifiers among @shape, @structure, and @graph to separate the sections.

Note

Positions are saved as bytes by numpy.nparray.tostring()

nngt.seed(msd=None, seeds=None)[source]#

Seed the random generator used by NNGT (i.e. the numpy RandomState: for details, see numpy.random.RandomState).

Parameters:

msd (int, optional) – Master seed for numpy RandomState. Must be convertible to 32-bit unsigned integers.
seeds (list of ints, optional) – Seeds for RandomState (when using MPI). Must be convertible to 32-bit unsigned integers, one entry per MPI process.

nngt.set_config(config, value=None, silent=False)[source]#

Set NNGT’s configuration.

Parameters:

config (dict or str) – Either a full configuration dictionary or one key to be set together with its associated value.
value (object, optional (default: None)) – Value associated to config if config is a key.

Examples

>>> nngt.set_config({'multithreading': True, 'omp': 4})
>>> nngt.set_config('multithreading', False)

Notes

See the config file nngt/nngt.conf.default or ~/.nngt/nngt.conf for details about your configuration.

This function has an MPI barrier on it, so it must always be called on all processes.