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radalib-TOOLS_USAGE.txt
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radalib-TOOLS_USAGE.txt
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===================================================================
== Communities_Detection.exe ==
===================================================================
== Community detection by modularity optimization: ==
== - unweighted (UN) - uniform nullcase (UUN, WUN) ==
== - weighted (WN) - local average (WLA, WULA) ==
== - weighted signed (WS) - wh links unwh nullcase (WLUN) ==
== - link rank (WLR) - bipartite path motif (WBPM) ==
== - no nullcase (WNN) - bipartite path signed (WBPS) ==
== Algorithms, which can be combined: ==
== - exhaustive search (h) - louvain (l) ==
== - tabu search (t) - fast algorithm (f) ==
== - extremal (e) - reposition (r) ==
== - spectral (s) - bootstrapping (b) ==
== Initialization modes: ==
== - isolated (.) - best (!) - default (-) ==
== - together (+) - prev (:) ==
===================================================================
Usage: Communities_Detection.exe log_level modularity_type heuristics repetitions [ resistance [ penalty_coeff ] ] net_name lol_best_name
Logging Levels : N | S | P | V
also lowercase symbols
also case-insensitive full names (None, ...)
n = None p = Progress
s = Summary v = Verbose
Modularity Types : UN | UUN | WN | WS | WUN | WLA | WULA | WLUN | WNN | WLR | WBPM | WBPS
also lowercase symbols
also case-insensitive full names (Unweighted_Newman, ...)
UN = Unweighted_Newman
UUN = Unweighted_Uniform_Nullcase
WN = Weighted_Newman
WS = Weighted_Signed
WUN = Weighted_Uniform_Nullcase
WLA = Weighted_Local_Average
WULA = Weighted_Uniform_Local_Average
WLUN = Weighted_Links_Unweighted_Nullcase
WNN = Weighted_No_Nullcase
WLR = Weighted_Link_Rank
WBPM = Weighted_Bipartite_Path_Motif
WBPS = Weighted_Bipartite_Path_Signed
Heuristics String : [htseflrb!:.+-]+
also uppercase symbols
also single case-insensitive full names (Exhaustive, ...)
heuristics
h = Exhaustive l = Louvain
t = Tabu f = Fast
s = Spectral r = Reposition
e = Extremal b = Bootstrapping
initializations
! = Ini_Best . = Ini_Isolated
: = Ini_Prev + = Ini_Together
- = Ini_Default
Repetitions : positive integer
does not apply to [hlfr] algorithms
Resistance : resistance of nodes to join communities, as a common self-loop
positive or negative real number
0 | 0.0 | default => no resistance, do not add self-loops
Penalty Coefficient : relative importance of null-case term
non-negative real number
default => 1.0
Network name : name of the input network file in Pajek format (*.net)
Lol Best Filename : file for the best partition found in Lol format
if file exists, the partition becomes the initial partition
===================================================================
== Communities_Network.exe ==
===================================================================
== Find the Network of Communities of a given Network ==
===================================================================
Usage: Communities_Network.exe net_name clu_or_lol_name [ number_of_lines_to_skip ] comms_net_name weights_type [ decimal_digits ]
net_name : name of the input network file in Pajek format (*.net)
clu_or_lol_name : name of the file with the partition in Pajek or Lol format
number_of_lines_to_skip : non-negative integer
default => 0
ignored for partitions in Pajek format
comms_net_name : name of the output network of communities file in Pajek format
weights_type : I | F | D
also lowercase symbols
also case-insensitive full names
I = Integer = Int
F = Float
D = Double
decimal_digits : number of decimal digits for Float or Double output weights
ignored for Integer weights
default => 5
===================================================================
== Compare_Partitions.exe ==
===================================================================
== Compare partitions in Lol or Pajek format ==
== Many indices and metrics are calculated: ==
== - number of pairs, agreements and disagreements ==
== - Jaccard, Rand, adjusted Rand, Fowlkes Mallows ==
== - normalized mutual information, asymmetric Wallace ==
== - Mirkin, van Dongen, variation of information ==
===================================================================
Usage: Compare_Partitions.exe clu_or_lol(s)_1_name clu_or_lol(s)_2_name [ out_name [ out_format ] ] [ number_of_lines_to_skip ]
clu_or_lol(s)_1_name : name of the file with the first partition(s) in Pajek or Lol(s) format
only one partition per file if in Pajek format
clu_or_lol(s)_2_name : name of the file with the second partition(s) in Pajek or Lol(s) format
only one partition per file if in Pajek format
out_name : name of the output file
contingency table not shown in verbose format if output is not file and size > 30x10
out_format : V | T
also lowercase symbols
also case-insensitive full names (Verbose, ...)
V = Verbose
T = Table
default => Verbose
number_of_lines_to_skip : number of lines to skip at the beginning of the Lol files
ignored for partitions in Pajek format
non-negative integer
default => 0
===================================================================
== Connected_Subgraphs.exe ==
===================================================================
== Split a network into its weak or strong connected components ==
===================================================================
Usage: Connected_Subgraphs.exe net_name_without_ext [ components_type ] [ skip_size ]
net_name_without_ext : name of the network file in Pajek format without the .net extension
components_type : W | S
also lowercase symbols
also case-insensitive full names (Weak, Strong)
W = Weak
S = Strong
default => Weak
skip_size : components smaller or equal to this size are skipped
non-negative integer
default => 0
===================================================================
== Convert_Clu_To_Lol.exe ==
===================================================================
== Convert a file with a partition in Pajek format (*.clu) ==
== into a file with a partition in Lol format ==
===================================================================
Usage: Convert_Clu_To_Lol.exe clu_file_name lol_file_name [ sorted ]
clu_file_name : name of the input partition file in Pajek format (*.clu)
lol_file_name : name of the output partition file in Lol format
sorted : any string as 3rd parameter produces a sorted List of Lists
communities sorted by decreasing size
elements of each community sorted by index
===================================================================
== Convert_Lol_To_Clu.exe ==
===================================================================
== Convert a file with a partition in Lol format into ==
== a file with a partition in Pajek format (*.clu) ==
===================================================================
Usage: Convert_Lol_To_Clu.exe lol_file_name clu_file_name [ number_of_lines_to_skip ]
lol_file_name : name of the input partition file in Lol format
clu_file_name : name of the output partition file in Pajek format (*.clu)
number_of_lines_to_skip : number of lines to skip at the beginning of the Lol file
non-negative integer
default => 0
===================================================================
== Data_Statistics.exe ==
===================================================================
== Find statistic indicators of a data set, in rows or columns: ==
== - minimum, maximum, percentiles ==
== - means: arithmetic, geometric, harmonic ==
== - variance, standard deviation, skewness, kurtosis ==
== - covariance, central moments ==
== - Pearson, Spearman and Kendall correlations, ==
== - linear regression ==
===================================================================
Usage: Data_Statistics.exe data_name [ statistics_name ] [ index1 [ index2 ] ] rows_or_columns [ decimal_digits ]
data_name : name of the data file
statistics_name : name of the file with the output proximities matrix
index1 index2 : indices of the row(s) or column(s) to obtain the statistics
if no indices indicated, all individual and pair statistics calculated
if first index indicated, the statistics of that row or column calculated
if both indices indicated, the pair statistics are calculated
0 < index1 < index2
rows_or_columns : R | C
also lowercase symbols
also case-insensitive full names (Rows, ...)
R = Rows
C = Cols = Columns
decimal_digits : number of decimal digits for float values
default => 14
===================================================================
== Data_To_Correlations.exe ==
===================================================================
== Find the correlations network of a data set ==
===================================================================
Usage: Data_To_Correlations.exe data_file rows_or_columns scaling_type correlations_file [ decimal_digits ]
rows_or_columns : R | C
also lowercase symbols
also case-insensitive full names (Rows, ...)
R = Rows
C = Cols = Columns
scaling_type : NS | S01 | ZS
also lowercase symbols
also case-insensitive full names (No_Scale, ...)
NS = No_Scale
S01 = Scale_01
ZS = Z_Score
decimal_digits : number of decimal digits for float values
default => 14
===================================================================
== Data_To_Proximities.exe ==
===================================================================
== Calculate many types of proximities (distances or ==
== similarities) between rows or columns in a data set: ==
== - Euclidean, Manhattan, Chebyshev, Minkowski, Canberra ==
== - Bray Curtis, correlation, cosine ==
== - several scalings and transformations available ==
===================================================================
Usage: Data_To_Proximities.exe data_name proximities_name rows_or_columns scaling_type dissimilarity_type [ dissimilarity_param ] transform_type [ decimal_digits ]
data_name : name of the data file
proximities_name : name of the file with the output proximities matrix
if name has .net extension, the output is a network file in Pajek format
rows_or_columns : R | C
also lowercase symbols
also case-insensitive full names (Rows, ...)
R = Rows
C = Cols = Columns
scaling_type : NS | S01 | SZS
also lowercase symbols
also case-insensitive full names (No_Scaling, ...)
NS = No_Scaling
x
S01 = Scaling_01
(x - x_{min}) / (x_{max} - x_{min})
SZS = Scaling_Z_Score
(x - <x>) / sigma_x
dissimilarity_type : EUCL | MANH | CHEB | MINK | CANB | BRAY | CORD | CODI | CABS | CSQR | COSI
also lowercase symbols
also case-insensitive full names (Euclidean_Distance, ...)
EUCL = Euclidean_Distance
\sum_k (x_k - y_k)^2
MANH = Manhattan_Distance
\sum_k |x_k - y_k|
CHEB = Chebyshev_Distance
\max_k |x_k - y_k|
MINK = Minkowski_Distance
[\sum_k (x_k - y_k)^p]^(1/p)
CANB = Canberra_Distance:
\sum_k \frac{ |x_k - y_k| }{ |x_k| + |y_k| }
BRAY = Bray_Curtis_Dissimilarity:
\frac{2 \sum_k |x_k - y_k| }{ \sum_k (x_k + y_k) }
CORD = Correlation_Distance:
\sqrt{2 (1 - \rho)}
CODI = Correlation_Dissimilarity:
\frac{1}{2} (1 - \rho)
CABS = Correlation_Abs_Dissimilarity:
1 - |\rho|
CSQR = Correlation_Sqr_Dissimilarity:
\sqrt(1 - \rho^2)
COSI = Cosine_Dissimilarity
\frac{1}{2} (1 - \frac{x y}{|x| |y|})
dissimilarity_param : parameter for some dissimilarity types, otherwise ignored
for Minkowski Distance: parameter p of the p-norm
integer or float number
default => 14
for Correlation Distances: correlation type
P | S
also lowercase symbols
also case-insensitive full names (Pearson, ...)
P = Pearson
S = Spearman
default => Pearson
transform_type : NT | OMD | OM2D | IOD | EOMD
also lowercase symbols
also case-insensitive full names (No_Transform, ...)
NT = No_Transform
D
OMD = One_Minus_Dissim
1 - D
OM2D = One_Minus_Two_Dissim
1 - 2 D
IOD = Inverse_Of_Dissim
\frac{1}{D}
EOMD = Exp_Of_Minus_Dissim
\exp(-D)
OIZ = One_If_Zero
\delta(D,0)
decimal_digits : number of decimal digits for float values
default => 14
===================================================================
== Extract_Subgraphs.exe ==
===================================================================
== Extract subgraphs from a graph ==
===================================================================
Usage: Extract_Subgraphs.exe net_name clu_or_lol_name out_name_prefix [ number_of_lines_to_skip ]
net_name : name of the network file in Pajek format
clu_or_lol_name : name of the file with the lists of nodes in Pajek or Lol format
out_name_prefix : prefix of the name of the output subgraph files
number_of_lines_to_skip : number of lines to skip at the beginning of the Lol file
ignored for partitions in Pajek format
non-negative integer
default => 0
===================================================================
== Hierarchical_Clustering.exe ==
===================================================================
== Agglomerative Hierarchical Clustering with MultiDendrograms ==
== and Binary Dendrograms, for distances and similarities ==
== Algorithms implemented: ==
== - (VL) Versatile linkage - (HL) Harmonic linkage ==
== - (SL) Single linkage - (WD) Ward ==
== - (CL) Complete linkage - (CD) Centroid ==
== - (AL) Arithmetic linkage - (BF) Beta flexible ==
== - (GL) Geometric linkage ==
== ==
== Equivalences between clustering algorithms for distances: ==
== Arithmetic Linkage Unweighted = UPGMA ==
== Versatile Linkage (param +1.0) = Complete Linkage ==
== Versatile Linkage (param +0.1) = Arithmetic Linkage ==
== Versatile Linkage (param 0.0) = Geometric Linkage ==
== Versatile Linkage (param -0.1) = Harmonic Linkage ==
== Versatile Linkage (param -1.0) = Single Linkage ==
== Beta Flexible (param 0.0) = Arithmetic Linkage ==
== For similarities, the signs of param must be exchanged ==
== ==
== MultiDendrograms generates always a unique dendrogram ==
== For Binary Dendrograms, in case of ties, many dendrograms ==
== may exist, and this tool can enumerate or count all of them, ==
== or choose the one with maximum cophenetic correlation ==
== See also ==
== https://webs-deim.urv.cat/~sergio.gomez/mdendro.php ==
== https://webs-deim.urv.cat/~sergio.gomez/multidendrograms.php ==
===================================================================
Usage: Hierarchical_Clustering.exe proximities_name output_prefix dendrogram_type proximity_type [ precision ] clustering_type [ weighting_type ] [ clustering_parameter ] [ dendrogram_mode [ max_num_dendrograms ] [ sample_probability ] ] [ internal_nodes_prefix ]
proximities_name : name of the proximities file, either in matrix or list form
in matrix form, the names may be in first column, first row, or none
in list form, missing values are filled with:
Double'Last for Distances
0.0 for Similarities
output_prefix : prefix of the output files
dendrogram_type : MD | BD
also lowercase symbols
also case-insensitive short and full names (Multidendrogram, ...)
MD | Multidendrogram
BD | Binary_Dendrogram
proximity_type : D | S
also lowercase symbols
also case-insensitive short and full names (Distance, ...)
D | DIST | Distance
S | SIM | Similarity
precision : Number of decimal significant digits of the data and for the calculations
if not specified, is that of the value with largest number of decimal digits
clustering_type : VL | SL | CL | AL | GL | HL | WD | CD | BF
also lowercase symbols
also case-insensitive short and full names (Versatile_Linkage, ...)
VL = Versatile_Linkage
SL = Single_Linkage
CL = Complete_Linkage
AL = Arithmetic_Linkage
GL = Geometric_Linkage
HL = Harmonic_Linkage
WD = Ward
CD = Centroid
BF = Beta_Flexible
weighting_type : W | UW
also lowercase symbols
also case-insensitive short and full names (Weighted, ...)
W = Weighted
UW = Unweighted
default => Unweighted
clustering_parameter : Clustering parameter, between -1.0 and +1.0, necessary for
VL = Versatile_Linkage
BF = Beta_Flexible
default => 0
ignored for the other clustering types
for VL
-1.0 corresponds to SL for DIST, and to CL for SIM
-0.1 corresponds to HL for DIST, and to AL for SIM
0.0 corresponds to GL
+0.1 corresponds to AL for DIST, and to HL for SIM
+1.0 corresponds to CL for DIST, and to SL for SIM
for BF
0.0 corresponds to AL
dendrogram_mode : Sorted | Unsorted | Sample | Best | Count
also case-insensitive full names
default => Sorted
mode discarded for MultiDendrograms
Sorted : outputs all dendrograms sorted by decreasing cophenetic correlation
Unsorted : outputs the first binary dendrograms found
Sample : outputs a sorted sample of binary dendrograms
Best : outputs the dendrogram(s) with largest cophenetic correlation
Count : outputs the number of binary dendrograms
structurally equivalent dendrograms may appear, even if built differently
this affects connected components of tied distances of size greater than 3
to obtain the structurally different dendrograms:
set 'dendrogram_mode' to 'Sorted' or 'Unsorted'
set 'internal_nodes_prefix' to 'None'
set 'max_num_dendrograms' such that all binary dendrograms are generated
run this tool
$ cat FILENAME-bd-newick.txt | grep -v Binary | sort | uniq
to count the structurally different dendrograms:
$ cat FILENAME-bd-newick.txt | grep -v Binary | sort | uniq | wc -l
max_num_dendrograms : Maximum number of binary dendrograms
default => 1000
stops recursion except for Count mode
sample_probability : Sample probability, between 0.0 and 1.0
default => 0.02
necessary for Sample mode, discarded for the rest
internal_nodes_prefix : Prefix for the names of the internal nodes
if 'None' (case insensitive) no names are assigned to internal nodes
default => Cluster_
===================================================================
== Links_Info.exe ==
===================================================================
== Obtain degrees and strengths of nodes attached to each link ==
===================================================================
Usage: Links_Info.exe net_name [ num_random_links ] links_info_name [ decimal_digits ]
net_name : name of the network file in Pajek format
num_random_links : number of random links in output info file
0 => all links
num_random_links >= num_links => all links
num_random_links > 1000000 => all links
default => 0
links_info_name : name of the file with the info of links
decimal_digits : number of decimal digits for float values
default => 5
===================================================================
== List_To_Net.exe ==
===================================================================
== Convert a file with the list of links of a graph into ==
== a network file in Pajek format (*.net) ==
===================================================================
Usage: List_To_Net.exe list_input_file net_output_file [ network_type ]
list_input_file : text file containing a list of links
net_output_file : name of the output network file in Pajek format (*.net)
network_type : A | D | U
also lowercase symbols
also case-insensitive full names (Auto, Directed, Undirected)
A = Auto
D = Directed
U = Undirected
default => Auto
in Auto, if the Graph is Symmetric, the output is Undirected
exception raised if inconsistent values exist
===================================================================
== Matrix_To_List.exe ==
===================================================================
== Convert a file with a graph in matrix form into ==
== a file with the list of links ==
===================================================================
Usage: Matrix_To_List.exe matrix_input_file list_output_file [ no_link_string ]
matrix_input_file : text file containing a matrix
list_output_file : name of the output list file
if the matrix is symmetric, the lower triangular links are discarded
no_link_string : string used to identify unexistent links within the matrix file
default => 0
===================================================================
== Matrix_To_Net.exe ==
===================================================================
== Convert a file with a graph in matrix form into ==
== a network file in Pajek format (*.net) ==
===================================================================
Usage: Matrix_To_Net.exe matrix_input_file net_output_file [ no_link_string ]
matrix_input_file : text file containing an adjacency or weights matrix
net_output_file : name of the output network file in Pajek format (*.net)
no_link_string : string used to identify unexistent links within the matrix file
default => 0
===================================================================
== Mesoscales_Detection.exe ==
===================================================================
== Mesoscales search by modularity optimization using ==
== resistance parameter (common self-loops) ==
== Algorithms, which can be combined: ==
== - exhaustive search (h) - louvain (l) ==
== - tabu search (t) - fast algorithm (f) ==
== - extremal (e) - reposition (r) ==
== - spectral (s) - bootstrapping (b) ==
===================================================================
Usage: Mesoscales_Detection.exe net_name weighted_modularity_type heuristics repetitions [ num_steps max_delta_loop_ratio ] [ min_self_loop max_self_loop ]
Network Name : Name of the input network file in Pajek format (*.net)
Weighted Modularity Types : WN | WS | WUN | WLA | WULA | WLUN | WNN | WLR | WBPM | WBPS
also lowercase symbols
also case-insensitive full names (Weighted_Newman, ...)
WN = Weighted_Newman
WS = Weighted_Signed
WUN = Weighted_Uniform_Nullcase
WLA = Weighted_Local_Average
WULA = Weighted_Uniform_Local_Average
WLUN = Weighted_Links_Unweighted_Nullcase
WNN = Weighted_No_Nullcase
WLR = Weighted_Link_Rank
WBPM = Weighted_Bipartite_Path_Motif
WBPS = Weighted_Bipartite_Path_Signed
Heuristics String : [htseflrb!:.+-]+
also uppercase symbols
also single case-insensitive full names (Exhaustive, ...)
heuristics
h = Exhaustive l = Louvain
t = Tabu f = Fast
s = Spectral r = Reposition
e = Extremal b = Bootstrapping
initializations
! = Ini_Best . = Ini_Isolated
: = Ini_Prev + = Ini_Together
- = Ini_Default
Repetitions : integer
absolute value indicates the number of repetitions
positive values indicate scan self-loops from min to max
negative values indicate scan self-loops from max to min
0 = no scan, just calculate min and max for WN and WS
ignored by [hlfr] algorithms
Number of Steps : default => 100
Max Delta Loop Ratio : default => 1.0000
ratio between last and first increments of the self-loop
use 1 for a linear scale of the self-loop
Min Self-loop : default => -1.0000
for WN and WS the default is calculated from the network
Max Self-loop : default => 1.0000
for WN and WS the default is calculated from the network
===================================================================
== Mesoscales_Fine_Tuning.exe ==
===================================================================
== Mesoscales fine-tuning after Mesoscales detection ==
===================================================================
Usage: Mesoscales_Fine_Tuning.exe net_name_without_ext weighted_modularity_type
net_name_without_ext : name of the network file in Pajek format without the .net extension
it is supposed that files with this name and the following endings exist:
*-table.txt: table with four columns: r, r-r_min, Q, num_comms
*-lols.txt: the partitions found for the mesoscale in Lol format
*-lols-extra.txt : optional file with extra partitions
weighted_modularity_types : WN | WS | WUN | WLA | WULA | WLUN | WNN | WLR | WBPM | WBPS
also lowercase symbols
also case-insensitive full names (Weighted_Newman, ...)
WN = Weighted_Newman
WS = Weighted_Signed
WUN = Weighted_Uniform_Nullcase
WLA = Weighted_Local_Average
WULA = Weighted_Uniform_Local_Average
WLUN = Weighted_Links_Unweighted_Nullcase
WNN = Weighted_No_Nullcase
WLR = Weighted_Link_Rank
WBPM = Weighted_Bipartite_Path_Motif
WBPS = Weighted_Bipartite_Path_Signed
===================================================================
== Modularity_Calculation.exe ==
===================================================================
== Calculate the total modularity, decomposed in node ==
== and community contributions ==
===================================================================
Usage: Modularity_Calculation.exe net_name clu_or_lol_name [ resistance [ penalty_coeff ] ] modularity_type [ modularity_details ] [ number_of_lines_to_skip ]
net_name : name of the input network file in Pajek format (*.net)
clu_or_lol_name : name of the file with the partition in Pajek or Lol format
resistance : resistance of nodes to join communities in the form of a common self-loop
positive or negative real number
0 | 0.0 | default => no resistance, i.e. do not add self-loops
penalty_coeff : relative importance of null-case term
non-negative real number
default => 1.0
modularity_type : UN | UUN | WN | WS | WUN | WLA | WULA | WLUN | WNN | WLR | WBPM | WBPS
also lowercase symbols
also case-insensitive full names (Unweighted_Newman, ...)
UN = Unweighted_Newman
UUN = Unweighted_Uniform_Nullcase
WN = Weighted_Newman
WS = Weighted_Signed
WUN = Weighted_Uniform_Nullcase
WLA = Weighted_Local_Average
WULA = Weighted_Uniform_Local_Average
WLUN = Weighted_Links_Unweighted_Nullcase
WNN = Weighted_No_Nullcase
WLR = Weighted_Link_Rank
WBPM = Weighted_Bipartite_Path_Motif
WBPS = Weighted_Bipartite_Path_Signed
modularity_details : T | TC | TN | TCN
also lowercase symbols
also case-insensitive full names (Total, Total_Communities, ...)
T = Total
TC = Total_Communities
TN = Total_Nodes
TCN = Total_Communities_Nodes
default => Total_Communities_Nodes
number_of_lines_to_skip : number of lines to skip at the beginning of the Lol files
ignored for partitions in Pajek format
non-negative integer
default => 0
===================================================================
== Multiplex_Aggregate.exe ==
===================================================================
== Aggregate the Layers of a Multiplex ==
===================================================================
Usage: Multiplex_Aggregate.exe list_input_file output_file network_type aggregation_type weights_type [ decimal_digits ]
list_input_file : text file containing the list of links of a multiplex
output_file : prefix of output layer networks
network_type : D | U
also lowercase symbols
also case-insensitive full names (Directed, Undirected)
D = Directed
U = Undirected
for repeated Edges, only the last one is stored
aggregation_type : W | U
also lowercase symbols
also case-insensitive full names (Weighted, Unweighted)
W = Weighted
U = Unweighted
weights_type : I | F | D
also lowercase symbols
also case-insensitive full names (Integer, ...)
I = Integer = Int
F = Float
D = Double
decimal_digits : number of decimal digits for float and double weights
ignored for Integer weights
default => 5
===================================================================
== Multiplex_Extract_Layers.exe ==
===================================================================
== Extract the Layers of a Multiplex as Networks in Pajek format ==
===================================================================
Usage: Multiplex_Extract_Layers.exe list_input_file net_output_prefix network_type
list_input_file : text file containing the list of links of a multiplex
net_output_prefix : prefix of output layer networks
network_type : D | U
also lowercase symbols
also case-insensitive full names (Directed, Undirected)
D = Directed
U = Undirected
for repeated Edges, only the last one is stored
===================================================================
== Net_To_List.exe ==
===================================================================
== Convert a network file in Pajek format (*.net) into ==
== a file with the list of links ==
===================================================================
Usage: Net_To_List.exe net_input_file list_output_file
net_input_file : name of the input network file in Pajek format (*.net)
list_output_file : name of the output network file in list format
===================================================================
== Net_To_Matrix.exe ==
===================================================================
== Convert a network file in Pajek format (*.net) into ==
== a file with a graph in matrix form ==
===================================================================
Usage: Net_To_Matrix.exe net_input_file matrix_output_file [ no_link_string ]
net_input_file : name of the input network file in Pajek format (*.net)
matrix_output_file : output text file containing the weights matrix of the network
the first line contains the names of the nodes
no_link_string : string used to identify unexistent links within the matrix file
default => 0
===================================================================
== Network_Properties.exe ==
===================================================================
== Find many global, node and edge properties of a network: ==
== - connectedness (weak or strong) ==
== - degrees, strengths, clustering coefficients, entropies ==
== - assortativities, path lengths, efficiencies, diameters ==
== - betweenness (nodes and edges) ==
== - degree distribution ==
== Works with weighted and unweighted, directed and undirected, ==
== positive and signed networks ==
===================================================================
Usage: Network_Properties.exe net_name [ properties ] [ decimal_digits ]
Network Name : Name of the input network file in Pajek format (*.net)
Properties String : [GNEDLUFA]+
also uppercase symbols
also single case-insensitive full names (All, Global, ...)
G = Global
N = Nodes
E = Edges
D = Degrees
L = Distances
U = Unweighted
F = Fast
A = All
default => All
properties available in each class
G: type and size of graph, connectedness, average and total degree and strength,
minimum and maximum values, asymmetry, reciprocity, assortativity,
average clustering coefficient, average path length, diameter, efficiency,
average entropy
N: degrees, strengths, self-loop, minimum, maximum and average values,
clustering coefficient, average and maximum path lengths, efficiency,
entropy, node betweenness
E: edge betweenness
D: degree distribution
L: distances between nodes
U: unweighted properties, excluding weighted ones
F: only fast calculation properties:
exclude average and maximum path length, diameter, efficiency,
betweenness and distances
A: all properties available; disables Unweighted and Fast
processed from left to right, thus AU is not equivalent to UA
weights should be distances to have meaningful shortest path weighted properties
Decimal Digits : number of decimal digits for float values
default => 14
===================================================================
== Reformat_Partitions.exe ==
===================================================================
== Reformat partitions in Lol or Pajek format changing ==
== nodes' indices by nodes' names, and grouping in columns ==
===================================================================
Usage: Reformat_Partitions.exe net_name clu_or_lol_name lol_out_name [ header_lines header_mode ] [ group_by justify_width skip_size ]
net_name : name of the network file in Pajek format (*.net)
clu_or_lol_name : name of the partitions file in Pajek format (*.clu) or Lol format
in Lol format, the file may contain many partitions, e.g. those describing mesoscales
lol_out_name : name of the reformatted partition file
header_lines : number of lines of the header before a partition in Lol format
non-negative integer
default => 0
ignored for partitions in Pajek format (*.clu)
header_mode : CH | NH | SH
also lowercase symbols
also case-insensitive full names (Copy_Header, ...)
CH = Copy_Header
NH = No_Header
SH = Separator_Header
default => No_Header
group_by : number of columns for the nodes' names in the reformatted partition file
positive integer
default => 1
justify_width : width of the columns for the nodes' names
positive integer
default => 1
skip_size : modules smaller or equal to this size are skipped
non-negative integer
default => 0
===================================================================
== Size_Reduction.exe ==
===================================================================
== Reduction of the size of a network preserving modularity, ==
== by elimination of simple and triangular 'hairs' ==
== Only for Weighted_Newman (WN) modularity type ==
===================================================================
Usage: Size_Reduction.exe net_name_without_ext weights_type [ decimal_digits ]
net_name_without_ext : name of the network file in Pajek format without the .net extension
weights_type : I | F | D
also lowercase symbols
also case-insensitive full names
I = Integer = Int
F = Float
D = Double
decimal_digits : number of decimal digits for Float or Double output weights
ignored for Integer weights
default => 5
===================================================================
== Size_Reduction_Lol_Expand.exe ==
===================================================================
== Expansion of a partition of a size-reduced network into ==
== a partition of the original network ==
===================================================================
Usage: Size_Reduction_Lol_Expand.exe reduced_lol_name reducing_lol_name expanded_lol_name [ header_lines header_mode ]
reduced_lol_name : name of the input partition file in Lol format of a size-reduced network
the file may contain many partitions
reducing_lol_name : name of the input partition file in Lol format which has reduced a network
expanded_lol_name : name of the output partition file in Lol format
corresponds to the expansion of the partition of the size-reduced network
header_lines : number of lines of the header before a partition in Lol format
non-negative integer
default => 0
ignored for partitions in Pajek format (*.clu)
header_mode : CH | NH | SH
also lowercase symbols
also case-insensitive full names (Copy_Header, ...)
CH = Copy_Header
NH = No_Header
SH = Separator_Header
default => No_Header
===================================================================
== Sort_Nodes.exe ==
===================================================================
== Sort nodes randomly or according to degree ==
===================================================================
Usage: Sort_Nodes.exe net_name sorted_net_name [ sort_direction ]
sort_direction : A | D | R
also lowercase symbols
also case-insensitive full names (Ascending, ...)
A = Asc = Ascending
D = Desc = Descending
R = Rand = Random
default => Ascending
===================================================================
== Spanning_Tree.exe ==