Expand description
Decides the algorithm used to connect the nodes during Network
’s initialization. It can
also be used for identification purposes when the Model::Custom
variant is used.
Variants
ER
Fields
p: f64
The probability of connecting any given pair of nodes.
whole: bool
Should the network be in one piece
The Erdos–Renyi random network model.
BA
Fields
m0: usize
The initial number of clustered nodes.
m: usize
The number of nodes added in each step during network creation. Keep in mind that this should be strictly less or equal m0 and the Barabasi-Albert initialization function will panic if this is not the case.
The Barabasi–Albert preferential attachment model.
Custom(String)
Custom model, can be dynamically assigned to a network using Network::set_model
.
None
Placeholder for a network with no specified model. When a network is initialized with this model no immediate connections will be made.
Implementations
Trait Implementations
Auto Trait Implementations
impl RefUnwindSafe for Model
impl UnwindSafe for Model
Blanket Implementations
Mutably borrows from an owned value. Read more
The inverse inclusion map: attempts to construct self
from the equivalent element of its
superset. Read more
pub fn is_in_subset(&self) -> bool
pub fn is_in_subset(&self) -> bool
Checks if self
is actually part of its subset T
(and can be converted to it).
pub fn to_subset_unchecked(&self) -> SS
pub fn to_subset_unchecked(&self) -> SS
Use with care! Same as self.to_subset
but without any property checks. Always succeeds.
pub fn from_subset(element: &SS) -> SP
pub fn from_subset(element: &SS) -> SP
The inclusion map: converts self
to the equivalent element of its superset.