mcxio(5) FILE FORMATS mcxio(5)
mcxio - the format specifications for input and output in the mcl family.
The primary objects in the MCL network analysis suite are graphs and clusterings. Graphs can be directed and may have loops. Both graphs and
clusterings are represented in a general unified format. This format specifies two domains (a source domain and a destination domain), along
with lists of arcs linking pairs of elements from the two domains. For graphs the two domains are simply both equal to the graph node
domain, whereas for clusterings one domain is the graph node domain and the other corresponds to the enumeration of clusters. Undirected
graphs are a special instance of a directed graph, where an edge from the undirected graph is represented by two arcs of identical weight,
one for each possible direction.
The general unified format alluded to above is in fact a simple rectangular sparse matrix representation. Sparse means that zero entries in
the matrix are not stored. A zero entry corresponds to an ordered node pair in the graph for which no arc exists from the first to the sec-
ond node. An undirected graph corresponds with a symmetric matrix.
The MCL suite uses a slight generalisation of the matrix concept, in that the row and column indices (that is, domains) can be arbitrary
lists of nonnegative integers. Usually, but not necessarily, a domain of size N will use the common representation of the list of integers
starting at 0 and ending at N-1. The source domain is always associated with the columns of a matrix, and the destination domain is always
associated with the rows of a matrix. The matrix format, introduced below, first specifies the two domains. It then represents the nonzero
matrix entries (corresponding with graph arc weights) in a column-wise fashion, as a list of lists. For each node from the source domain, it
presents the list of all its neighbours in the destination domain along with the corresponding weights. This document describes
native matrix format
The format that can be read in by any mcl application expecting a matrix argument. The native format closely resembles the layout of
matrices as residing in computer memory. There are two distinct encodings, respectively interchange and binary. Their relative merits are
described further below.
concatenated native matrix format
This always pertains to matrices in native format concatenated in a single file, refered to as a cat file. It is used for example to
encode hierarchical clusterings as generated by mclcm. A cat file either consists of matrices in interchange format or of matrices in
raw intermediate format
This is read by mcxassemble(1).
Used by applications such as mcl(1) and mcxdump(1) to convert between meaningful labels describing the input data and the numerical iden-
tifiers used internally.
The format used when streaming labels directly into mcl(1) or mcxload(1).
The syntax accepted by mcl(1), mcxalter(1) and many other programs to transform graphs and matrices.
The interchange format is a portable format that can be transmitted across computers and over networks and will work with any version of mcl
or its sibling programs. It is documented (here) and very stable. Applications can easily create matrices in this format. The drawback of
interchange format is that for very large graphs matrix encodings grow very big and are slow to read.
The binary format is not garantueed to be portable across machines or different versions of mcl or differently compiled versions of mcl. Its
distinct advantage is that for very large graphs the speed advantage over interchange format is dramatic.
Conversion between the two formats is easily achieved with mcxconvert. Both mcl(1) and mcxload(1) can save a matrix in either format after
constructing it from label input.
The concatenated format is generated e.g. by mclcm(1) and can be transformed by mcxdump(1) using the -imx-cat option. In cat format matrices
are simply concatenated, so it is easily generated from the command line if needed. For native binary format it is imperative that no addi-
tional bytes are inserted inbetween the matrix encodings. For native interchange format the only requirement is that the last matrix is fol-
lowed by nothing but white space.
A remark on the sloppy naming conventions used for mcl and its sibling utilities may be in order here. The prefix mcx is used for generic
matrix functionality, the prefix clm is used for generic cluster functionaliy. The utility mcx is a general purpose interpreter for manipu-
lating matrices (and grahps, sets, and clusterings). The set of all mcl siblings (cf. mclfamily(7)) is loosely refered to as the mcl family,
which makes use of the mcl libraries (rather than the mcx libraries). The full truth is even more horrible, as the mcl/mcx prefix conven-
tions used in the C source code follow still other rules.
In this document, 'MCL' means 'the mcl setting' or 'the mcl family'. An MCL program is one of the programs in the mcl family. The remainder
of this document contains the following sections.
Internal representation of matrices in MCL
There are several aspects to the way in which MCL represents matrices. Internally, indices never act as an ofset in an array, and neither
do they participate in ofset computations. This means that they purely act as identifiers. The upshot is that matrices can be handled in
which the index domains are non-sequential (more below). Thus one can work with different graphs and matrices all using subsets of the same
set of indices/identifiers. This aids in combining data sets in different ways and easily comparing the respective results when experiment-
ing. Secondly, only nonzero values (and their corresponding indices) are stored. Thirdly, MCL stores a matrix as a listing of columns. Iter-
ating over a column is trivial; iterating over a row requires a costly transposition computation. The last two points should matter little
to the user of MCL programs.
In textbook expositions and in many matrix manipulation implementations, matrices are represented with sequentially indexed rows and col-
umns, with the indices usually starting at either zero or one. In the MCL setting, the requirement of sequentiality is dropped, and it fol-
lows naturally that no requirement is posed on the first index. The only requirement MCL poses on the indices is that they be nonnegative,
and can be represented by the integer type used by MCL. On many machines, the largest allowable integer will be 2147483647.
MCL associates two domains with a matrix M, the row domain and column domain. The matrix M can only have entries M[i,j] where i is in the
row domain and j is in the column domain. This is vital when specifying a matrix: it is illegal to specify an entry M[i,j] violating this
condition. However, it is not necessary to specify all entries M[i,j] for all possible combinations of i and j. One needs only specify those
entries for which the value is nonzero, and only nonzero values will be stored internally. In the MCL matrix format, the matrix domains must
be specified explicitly if they are not canonical (more below).
Strictly as an aside, the domains primarily exist to ensure data integrity. When combining matrices with addition or multiplication (e.g.
using the mcx utility), MCL will happily combine matrices for which the domains do not match, although it will usually issue a warning.
Conceptually, matrices auto-expand to the dimensions required for the operation. Alternatively, a matrix can be viewed as an infinite quad-
rant, with the domains delimiting the parts in which nonzero entries may exist. In the future, facilities could be added to MCL (c.q. mcx)
to allow for placing strict domain requirements on matrices when submitted to binary operations such as addition and multiplication.
From here on, all statements about matrices and graphs are really statements about matrices and graphs in the MCL setting. The specification
of a matrix quite closely matches the internal representation.
A matrix M has two domains: the column domain and the row domain. Both simply take the form of a set (represented as an ordered list) of
indices. A canonical domain is a domain of some size K where the indices are simply the first K nonnegative integers 0,1..,K-1. The domains
dictate which nonzero entries are allowed to occur in a matrix; only entries M[i,j] are allowed where i is in the row domain and j is in the
The matrix M is specified in three parts, for which the second is optional. The parts are:
This specifies the dimensions K and L of the matrix, where K is the size of the row domain, and L is the size of the column domain. It
looks as follows:
This dictates that a matrix will be specified for which the row domain has dimension 9 and the column domain has dimension 14.
The domain specification can have various forms: if nothing is specified, the matrix will have canonical domains and a canonical represen-
tation, similar to the representation encountered in textbooks. Alternatively, the row and column domains can each be specified sepa-
rately, and it is also possible to specify only one of them; the other will simply be a canonical domain again. Finally, it is possible to
declare the two domains identical and specify them simultaneously. It is perfectly legal in each case to explicitly specify a canonical
domain. It is required in each case that the number of indices listed in a domain corresponds with the dimension given in the header.
An example where both a row domain and a column domain are specified:
100 200 300 400 500 600 700 800 900 $
30 32 34 36 38 40 42 44 46 48 50 52 56 58 $
This example combines with the header given above, as the dimensions fit. Had the row domain specification been omitted, the row domain
would automatically be set to the integers 0,1,..8. Had the column specification been omitted, it would be set to 0,1,..13.
Suppose now that the header did specify the dimensions 10x10. Because the dimensions are identical, this raises the possibility that the
domains be identical. A valid way to specify the row domain and column domain in one go is this.
11 22 33 44 55 66 77 88 99 100 $
The matrix specification starts with the sequence
The 'begin' keyword in the '(mclmatrix' part is followed by a list of listings, where the primary list ranges over all column indices in M
(i.e. indices in the column domain), and where each secondary lists encodes all positive entries in the corresponding column. A secondary
list (or matrix column) starts with the index c of the column, and then contains a listing of all row entries in c (these are matrix
entries M[r,c] for varying r). The entry M[r,c] is specified either as 'r' or as 'r:f', where f is a float. In the first case, the entry
M[r,c] defaults to 1.0, in the second case, it is set to f. The secondary list is closed with the `$' character. A full fledged examples
thus looks as follows:
11 22 33 44 55 66 77 88 99 123 456 2147483647 $
0 1 2 $
0 44 88 99 456 2147483647 $
1 11 66 77 123 $
2 22 33 55 $
Note that the column domain is canonical; its specifiation could have been omitted. In this example, no values were specified. See below
A graph is simply a matrix where the row domain is the same as the column domain. Graphs should have positive entries only. Example:
11 22 33 44 55 66 77 88 99 123 456 2147483647 $
11 22:2 66:3.4 77:3 123:8 $
22 11:2 33:3.8 55:8.1 $
33 22:3.8 44:7 55:6.2 $
44 33:7 88:5.7 99:7.0 456:3 $
55 22:8.1 33:6.2 77:2.9 88:3.0 $
66 11:3.4 123:5.1 $
77 11:3 55:2.9 123:1.5 $
88 44:5.7 55:3.0 99:3.0 456:4.2 $
99 44:7.0 88:3.0 456:1.8 2147483647:3.9 $
123 11:8 66:5.1 77:1.5 $
456 44:3 88:4.2 99:1.8 2147483647:6.3 $
2147483647 99:3.9 456:6.3 $
Incidentally, clustering this graph with mcl, using default parameters, yields a cluster that is represented by the 12x3 matrix shown ear-
The following example shows the same graph, now represented on a canonical domain, and with all values implicitly set to 1.0:
0 1 5 6 9 $
1 0 2 4 $
2 1 3 4 $
3 2 7 8 10 $
4 1 2 6 7 $
5 0 9 $
6 0 4 9 $
7 3 4 8 10 $
8 3 7 10 11 $
9 0 5 6 $
10 3 7 8 11 $
11 8 10 $
There are few restrictions on the format that one might actually expect. Vectors and entries may occur in any order and need not be sorted.
Repeated entries and repeated vectors are allowed but are always discarded while an error message is emitted.
If you want functionally interesting behaviour in combining repeated vectors and repeated entries, have a look at the next section and at
Within the vector listing, the '#' is a token that introduces a comment until the end of line.
A file in raw format is simply a listing of vectors without any sectioning structure. No header specification, no domain specification, and
no matrix introduction syntax is used - these are supplied to the processing application by other means. The end-of-vector token '$' must
still be used, and the comment token '#' is still valid. mcxassemble(1) imports a file in raw format, creates a native matrix from the data
therein, and writes the matrix to (a different) file. It allows customizable behaviour in how to combine repeated entries and repeated vec-
tors. This is typically used in the following procedure. A) Do a one-pass-parse on some external cooccurrence file/format, generate raw data
during the parse and write it to file (without needing to build a huge data structure in memory). B) mcxassemble takes the raw data and
assembles it according to instruction into a native mcl matrix.
Tab format / label information
Several mcl programs accept options such as -tab, -tabc, -tabr, -use-tab, -strict-tab, and -extend-tab. The argument to these options is
invariably the name of a so-called tab file. Tab files are used to convert between labels (describing entities in the data) and indices as
used in the mcl matrix format. In a tab file each line starts with a unique number which presumably corresponds to an index used in a
matrix file. The rest of the line contains a descriptive string associated with the number. It is required that each string is unique,
although not all mcl programs enforce this at the time of writing. The string may contain spaces. Lines starting with # are considered
comment and are disregarded.
The ordered set of indices found in the tab file is called the tab domain.
Tab files are almost always employed in conjunction with an mcl matrix file. mcxdump(1) and clmformat(1) require by default that the tab
domain coincides with the matrix domain (either row or column or both) to which they will be applied. This can be relaxed for either by sup-
plying the --lazy-tab option.
mcl provides explicit modes for dealing with tab structures by means of the -extend-tab, -restrict-tab and -strict-tab options. Refer to the
Label input is a line based input where two nodes and an optional value are specified on each line. The nodes should be specified by labels.
If the labels contain spaces they should be separated by tabs (and the value if present should be separated from the second label by a tab
as well). The parse code will assume tab-separated labels if it sees a tab character in the input, otherwise it will split the input on any
kind of whitespace. Any line where the first non-whitespace character is the octothorp (#) is ignored. The following is an example of label
# the cat and the hat example
cat hat 0.2
hat bat 0.16
bat cat 1.0
bat bit 0.125
bit fit 0.25
fit hit 0.5
hit bit 0.16
mcl(1) can read in label input and cluster it when it is given the --abc option. It can optionally save the input graph in native format and
save the label information in a tab file with the -save-graph and -save-tab options.
Refer to the MCL getting started and MCL manual examples sections for more information on how MCL deals with label input.
mcxload(1) is a general purpose program for reading in label data and other stream formats. It encodes them in native mcl format and tab
files. It allows intermediate transformations on the values.
mcl(1), mcxload(1), mcxsubs(1), mcxassemble(1) and mcxalter(1) all accept the same transformation language in their respective tf-type
options and mcxsub's val specification.
A statement in this language is simply a comma-separated list of functions accepting a single numerical value. The syntax of a function
invocation in general is func(arg). The functions exp, log, neglog can also be given an empty parameter list, indicating that e is taken as
the exponent base. In this case, the invocation looks like func(). Functions with names that start with # operate on graphs in their
entirety. For example, #knn(50) indicates the k-Nearest Neighbour transformation for k=50. All other names encode functions that operate
directly on edges. Functions with names that start with #arc operate on directed graphs and yield directed graphs. Most of the other #
functions either expect an undirected graph (such as #knn()) or yield an undirected graph (such as #add() and #max(). The following are
lt Filter out values greater than or equal to arg.
lq Filter out values greater than arg.
gq Filter out values less than arg.
gt Filter out values less than or equal to arg.
ceil Set everything higher than arg to arg.
floor Set everything lower than arg to arg.
mul Multiply by arg.
add Add arg to it.
power Raise to power arg.
exp Raise arg (e if omitted) to value.
log Take log in base arg (e if omitted).
neglog Take minus log in base arg (e if omitted).
#knn k-Nearest Neighbour reduction with k=arg.
#ceilnb Cap neighbours at arg at most.
#mcl Cluster with inflation=arg, use induced graph.
#add Convert two arcs to one edge using addition.
#min Convert two arcs to one edge using minimum.
#max Convert two arcs to one edge using maximum.
#mul Convert two arcs to one edge using multiplication.
#rev Encode graph in reverse direction.
#tp Same as above in matrix speak (transpose).
#tug Perturb edge weights with factor arg.
#shrug Randomly perturb edge weights with factor arg.
#step Use the k-step relation, where k=arg.
#thread Set thread pool size to arg.
#arcmax Only keep largest arc between two nodes.
#arcsub Replace G by G - G^T.
#arcmcl As #mcl, use symmetrised graph for clustering.
mcl(1) accepts --abc-neg-log and --abc-neg-log10 to specify log transformations. Similarly, mcxload(1) accepts --stream-log, --stream-neg-
log, and --stream-neg-log10. The reason is that probabilities are sometimes encoded below the precision dictated by the IEEE (32 bit) float
specification. This poses a problem as the mcl applications encode values by default as floats, and the transformation specifications are
always applied to the mcl encoding. The options just mentioned are applied after a value has been read from an input stream and before it is
converted to the native encoding.
mcxassemble(1), and mclfamily(7) for an overview of all the documentation and the utilities in the mcl family.
Stijn van Dongen.
mcxio 12-068 8 Mar 2012 mcxio(5)