NetworkStatistics
: A process to collect summary statistics
- class epydemic.NetworkStatistics
A process that collects statistics about the final network. This process defines no events: it simply interrogates the underlying network and extracts a collection of descriptive statistics into the final experimental results. These are statistics commonly collected in different scenarios, which can thus be provided as standard.
A statistics process is intended to be composed with another process, for
which it collects a common set of summary network statistics. This allows
standart statistics to be collected from any epydemic
process.
The statistics gathered are:
The order of the network (number of nodes)
The number of edges
The mean degree of nodes
The degree histogram
The number of connected components
The number of nodes in the largest connected component
The number of nodes in the second-largest connected component
The process runs in the results-gathering phase, where is analyses the topology and features of the final network.
Results
-
NetworkStatistics.N:
Final
[str
] = 'epydemic.statistics.N' Result holding the order of the network.
-
NetworkStatistics.M:
Final
[str
] = 'epydemic.statistics.M' Result holding the total number of edges in the network.
-
NetworkStatistics.KMEAN:
Final
[str
] = 'epydemic.statistics.kmean' Result holding the mean degree of nodes in the network.
-
NetworkStatistics.KDIST:
Final
[str
] = 'epydemic.statistics.k_distribution' Result holding the degree histogram as an array.
-
NetworkStatistics.COMPONENTS:
Final
[str
] = 'epydemic.statistics.ncomponents' Result holding the number of connected components in the network.
-
NetworkStatistics.LCC:
Final
[str
] = 'epydemic.statistics.lcc' Result holding the size of the largest connected (“giant”) component
-
NetworkStatistics.SLCC:
Final
[str
] = 'epydemic.statistics.slcc' Result holding the size of the second-largest component
Building the process
- NetworkStatistics.results()
Extract the network summary statistics into a dict.
- Return type:
Dict
[str
,Any
]- Returns:
a dict of experimental results