Lib module
Tools for the other modules.
Warning
These tools have been designed primarily for internal use throughout the
library and often work only in very specific situations (e.g.
find_idx_nearest()
works only on sorted arrays), so make
sure you read their doc carefully before using them.
Content
nngt.lib.InvalidArgument
|
Error raised when an argument is invalid. |
nngt.lib.delta_distrib ([graph, elist, num, …])
|
Delta distribution for edge attributes. |
nngt.lib.find_idx_nearest (array, values)
|
Find the indices of the nearest elements of values in a sorted array. |
nngt.lib.gaussian_distrib (graph[, elist, …])
|
Gaussian distribution for edge attributes. |
nngt.lib.is_integer (obj)
|
Return whether the object is an integer |
nngt.lib.is_iterable (obj)
|
Return whether the object is iterable |
nngt.lib.lin_correlated_distrib (graph[, …])
|
|
nngt.lib.log_correlated_distrib (graph[, …])
|
|
nngt.lib.lognormal_distrib (graph[, elist, …])
|
Lognormal distribution for edge attributes. |
nngt.lib.nonstring_container (obj)
|
Returns true for any iterable which is not a string or byte sequence. |
nngt.lib.uniform_distrib (graph[, elist, …])
|
Uniform distribution for edge attributes. |
Details
-
class nngt.lib.InvalidArgument[source]
Error raised when an argument is invalid.
-
nngt.lib.delta_distrib(graph=None, elist=None, num=None, value=1.0, **kwargs)[source]
Delta distribution for edge attributes.
- Parameters
graph (Graph
or subclass) – Graph for which an edge attribute will be generated.
elist (list of edges, optional (default: all edges)) – Generate values for only a subset of edges.
value (float, optional (default: 1.)) – Value of the delta distribution.
Returns (numpy.ndarray
) – Attribute value for each edge in graph.
-
nngt.lib.find_idx_nearest(array, values)[source]
Find the indices of the nearest elements of values in a sorted array.
Warning
Both array
and values
should be numpy.array objects and
array MUST be sorted in increasing order.
- Parameters
-
- Returns
idx (int or array representing the index of the closest value in array)
-
nngt.lib.gaussian_distrib(graph, elist=None, num=None, avg=None, std=None, **kwargs)[source]
Gaussian distribution for edge attributes.
- Parameters
graph (Graph
or subclass) – Graph for which an edge attribute will be generated.
elist (list of edges, optional (default: all edges)) – Generate values for only a subset of edges.
avg (float, optional (default: 0.)) – Average of the Gaussian distribution.
std (float, optional (default: 1.5)) – Standard deviation of the Gaussian distribution.
Returns (numpy.ndarray
) – Attribute value for each edge in graph.
-
nngt.lib.is_integer(obj)[source]
Return whether the object is an integer
-
nngt.lib.is_iterable(obj)[source]
Return whether the object is iterable
-
nngt.lib.lin_correlated_distrib(graph, elist=None, correl_attribute='betweenness', noise_scale=None, lower=None, upper=None, slope=None, offset=0.0, last_edges=False, **kwargs)[source]
-
nngt.lib.log_correlated_distrib(graph, elist=None, correl_attribute='betweenness', noise_scale=None, lower=0.0, upper=2.0, **kwargs)[source]
-
nngt.lib.lognormal_distrib(graph, elist=None, num=None, position=None, scale=None, **kwargs)[source]
Lognormal distribution for edge attributes.
- Parameters
graph (Graph
or subclass) – Graph for which an edge attribute will be generated.
elist (list of edges, optional (default: all edges)) – Generate values for only a subset of edges.
position (float, optional (default: 0.)) – Average of the normal distribution (i.e. log of the actual mean of the
lognormal distribution).
scale (float, optional (default: 1.5)) – Standard deviation of the normal distribution.
Returns (numpy.ndarray
) – Attribute value for each edge in graph.
-
nngt.lib.nonstring_container(obj)[source]
Returns true for any iterable which is not a string or byte sequence.
-
nngt.lib.uniform_distrib(graph, elist=None, num=None, lower=None, upper=None, **kwargs)[source]
Uniform distribution for edge attributes.
- Parameters
graph (Graph
or subclass) – Graph for which an edge attribute will be generated.
elist (list of edges, optional (default: all edges)) – Generate values for only a subset of edges.
lower (float, optional (default: 0.)) – Min value of the uniform distribution.
upper (float, optional (default: 1.5)) – Max value of the uniform distribution.
Returns (numpy.ndarray
) – Attribute value for each edge in graph.