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Convert to mcml

Source: R/cluster-metrics.R
as_mcml.Rd

Converts an object to the mcml class, a representation of a multi-cluster network that does not depend on the tna package.

Usage

as_mcml(x, ...)

# S3 method for class 'cluster_summary'
as_mcml(x, ...)

# S3 method for class 'group_tna'
as_mcml(x, clusters = NULL, method = "sum", type = "tna", directed = TRUE, ...)

# S3 method for class 'mcml'
as_mcml(x, ...)

# Default S3 method
as_mcml(x, ...)

Arguments

x

A cluster_summary, group_tna or mcml object. Any other input is an error; summarize_clusters builds an mcml object from raw data.

...

Additional arguments passed to methods.

clusters

Integer or character vector of row-to-group assignments. Required when the group_tna has the same labels across all groups (row-level clustering from tna::group_model(cluster_data(...))).

method

Aggregation method for macro weights (default "sum").

type

Transition type (default "tna").

directed

Logical; whether the network is directed (default TRUE).

Value

An mcml object with components macro, clusters, cluster_members, and meta.

An mcml object.

An mcml object. When clusters is provided, macro$data contains the cluster assignments and macro$weights is NULL.

The input mcml object unchanged.

See also

summarize_clusters, as_tna

Examples

clusters <- list(C1 = c("Explore", "Reflect", "Discuss"),
                 C2 = c("Plan", "Create", "Share"),
                 C3 = c("Monitor", "Adapt", "Synthesize", "Evaluate"))
as_mcml(csum(regulation_net, clusters = clusters, type = "tna"))
#> $macro
#> $macro$weights
#>           C1        C2        C3
#> C1 0.6521739 0.2546584 0.0931677
#> C2 0.1500000 0.2777778 0.5722222
#> C3 0.4036364 0.1745455 0.4218182
#> 
#> $macro$inits
#>        C1        C2        C3 
#> 0.3391960 0.2374372 0.4233668 
#> 
#> $macro$labels
#> [1] "C1" "C2" "C3"
#> 
#> $macro$data
#> NULL
#> 
#> 
#> $clusters
#> $clusters$C1
#> $clusters$C1$weights
#>           Explore   Reflect Discuss
#> Explore 0.0000000 1.0000000       0
#> Reflect 1.0000000 0.0000000       0
#> Discuss 0.4615385 0.5384615       0
#> 
#> $clusters$C1$inits
#>   Explore   Reflect   Discuss 
#> 0.3333333 0.6666667 0.0000000 
#> 
#> $clusters$C1$labels
#> [1] "Explore" "Reflect" "Discuss"
#> 
#> $clusters$C1$data
#> NULL
#> 
#> 
#> $clusters$C2
#> $clusters$C2$weights
#>        Plan    Create     Share
#> Plan      0 0.3571429 0.6428571
#> Create    0 0.0000000 1.0000000
#> Share     1 0.0000000 0.0000000
#> 
#> $clusters$C2$inits
#>   Plan Create  Share 
#>   0.21   0.20   0.59 
#> 
#> $clusters$C2$labels
#> [1] "Plan"   "Create" "Share" 
#> 
#> $clusters$C2$data
#> NULL
#> 
#> 
#> $clusters$C3
#> $clusters$C3$weights
#>              Monitor     Adapt Synthesize Evaluate
#> Monitor    0.0000000 1.0000000          0        0
#> Adapt      0.0000000 0.0000000          1        0
#> Synthesize 1.0000000 0.0000000          0        0
#> Evaluate   0.4342105 0.5657895          0        0
#> 
#> $clusters$C3$inits
#>    Monitor      Adapt Synthesize   Evaluate 
#>  0.3448276  0.5086207  0.1465517  0.0000000 
#> 
#> $clusters$C3$labels
#> [1] "Monitor"    "Adapt"      "Synthesize" "Evaluate"  
#> 
#> $clusters$C3$data
#> NULL
#> 
#> 
#> 
#> $cluster_members
#> $cluster_members$C1
#> [1] "Explore" "Reflect" "Discuss"
#> 
#> $cluster_members$C2
#> [1] "Plan"   "Create" "Share" 
#> 
#> $cluster_members$C3
#> [1] "Monitor"    "Adapt"      "Synthesize" "Evaluate"  
#> 
#> 
#> $meta
#> $meta$type
#> [1] "tna"
#> 
#> $meta$method
#> [1] "sum"
#> 
#> $meta$directed
#> [1] TRUE
#> 
#> $meta$n_nodes
#> [1] 10
#> 
#> $meta$n_clusters
#> [1] 3
#> 
#> $meta$cluster_sizes
#> C1 C2 C3 
#>  3  3  4 
#> 
#> 
#> attr(,"class")
#> [1] "mcml"