=================================================================== == 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 - ) / 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 == =================================================================== == Find the minimum or maximum spanning tree of a == == weighted network == =================================================================== Usage: Spanning_Tree.exe net_name mst_net_name optimization_type weights_type [ decimal_digits ] net_name : name of the input network file in Pajek format (*.net) mst_net_name : name of the output spanning tree file in Pajek format (*.net) optimization_type : MIN | MAX also lowercase symbols also case-insensitive full names MIN = Minimum MAX = Maximum 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 =================================================================== == Symmetrize_Network.exe == =================================================================== == Symmetrization of a directed graph == =================================================================== Usage: Symmetrize_Network.exe net_name sym_net_name weights_type [ decimal_digits ] net_name : name of the input network file in Pajek format (*.net) sym_net_name : name of the output symmetrized network file in Pajek format (*.net) 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