Provided by: regina-normal_7.1-1_amd64 
NAME
tricensus - Form a census of triangulations
SYNOPSIS
tricensus [ -t, --tetrahedra=tetrahedra ] [ -2, --dim2 | -4, --dim4 ] [ -b, --boundary |
-i, --internal | -B, --bdryfaces=triangles ] [ -o, --orientable | -n, --nonorientable ] [
-f, --finite | -d, --ideal ] [ -m, --minimal | -M, --minprime | -N, --minprimep2 | -h,
--minhyp ] [ --allowinvalid ] [ -s, --sigs | -S, --canonical | -e, --encodings | -c,
--subcontainers ] [ -p, --genpairs | -P, --usepairs ] [ --threads=num_threads ] output-
file
tricensus --help
DESCRIPTION
Forms a census of all 2-, 3- or 4-manifold triangulations that satisfy some set of
conditions.
These conditions are specified using various command-line arguments. The only condition
that you must provide is the number of top-dimensional simplices (e.g., the number of
tetrahedra for 3-manifolds), but there are many other options available.
The default behaviour is to enumerate 3-manifold triangulations. If you wish to enumerate
2-manifold or 4-manifold triangulations instead, you must pass --dim2 or --dim4
respectively.
Each triangulation will be output precisely once up to combinatorial isomorphism. Invalid
triangulations (for 3-manifolds, this means triangulations with edges identified to
themselves in reverse, or vertices whose links have boundary but are not discs) will not
be output at all.
As the census progresses, the state of progress will be written (slowly) to standard
output. Once the census is complete, the full census will be saved to the given output
file.
You can use the options --genpairs and --usepairs to split a census into smaller pieces.
Caution:
A census with even a small number of top-dimensional simplices can take an
incredibly long time to run, and can chew up massive amounts of memory. It is
recommended that you try very small censuses to begin with (such as 3 or 4
simplices), and work upwards to establish the limits of your machine.
For very large census runs, it is highly recommended that you use the either the
--sigs or --encodings option, which will keep the output file small and
significantly reduce the memory footprint.
OPTIONS
-t, --tetrahedra=tetrahedra
Specifies the number of top-dimensional simplices used to build the triangulations.
For 2-manifolds, 3-manifolds and 4-manifolds, this specifies the number of
triangles, tetrahedra or pentachora respectively.
-2, --dim2
Build a census of 2-manifold triangulations, not 3-manifold triangulations.
This is incompatible with several options; for other options it simply translates
the relevant constraint into two dimensions. See each individual option for
details on how it interacts with --dim2.
This option cannot be used with --dim4.
-4, --dim4
Build a census of 4-manifold triangulations, not 3-manifold triangulations.
This is incompatible with several options; for other options it simply translates
the relevant constraint into four dimensions. See each individual option for
details on how it interacts with --dim4.
This option cannot be used with --dim2.
-b, --boundary
Only produce triangulations with at least one boundary triangle.
For 2-manifolds or 4-manifolds, this option ensures at least one boundary edge or
boundary tetrahedron respectively.
-i, --internal
Only produce triangulations with all triangles internal (i.e., with no boundary
triangles).
For 2-manifolds or 4-manifolds, this option ensures that all edges or tetrahedra
respectively are internal.
-B, --bdryfaces=triangles
Only produce triangulations with the precise number of boundary triangles
specified.
For 2-manifolds or 4-manifolds, this specifies the number of boundary edges or
boundary tetrahedra respectively.
-o, --orientable
Only produce orientable triangulations.
-n, --nonorientable
Only produce non-orientable triangulations.
-f, --finite
Only produce finite triangulations (triangulations with no ideal vertices).
This option cannot be used with --dim2.
-d, --ideal
Only produce triangulations with at least one ideal vertex. There might or might
not be internal vertices (whose links are spheres) as well.
This option cannot be used with --dim2.
-m, --minimal
Do not include triangulations that are obviously non-minimal.
This option uses a series of fast tests that try to eliminate non-minimal
triangulations, but that are not always conclusive. If Regina cannot quickly tell
whether a triangulation is non-minimal, it will place the triangulation in the
census regardless.
This option cannot be used with --dim4.
-M, --minprime
Do not include triangulations that are obviously non-minimal, non-prime and/or
disc-reducible.
This can significantly speed up the census and vastly reduce the final number of
triangulations produced.
As above, this option uses a series of fast tests that are not always conclusive.
If Regina cannot quickly tell whether a triangulation is non-minimal, non-prime or
disc-reducible, it will place the triangulation in the census regardless.
This option cannot be used with --dim2 or --dim4.
-N, --minprimep2
Do not include triangulations that are obviously non-minimal, non-prime,
P2-reducible and/or disc-reducible.
This can significantly speed up the census and vastly reduce the final number of
triangulations produced, even more so than --minprime.
As above, this option uses a series of fast tests that are not always conclusive.
If Regina cannot quickly tell whether a triangulation is non-minimal, non-prime,
P2-reducible or disc-reducible, it will place the triangulation in the census
regardless.
This option cannot be used with --dim2 or --dim4.
-h, --minhyp
Do not include triangulations that are obviously not minimal ideal triangulations
of cusped finite-volume hyperbolic 3-manifolds.
This can significantly speed up the census and vastly reduce the final number of
triangulations produced.
As above, this option uses a series of fast tests that are not always conclusive.
If Regina cannot quickly tell whether a triangulation is a minimal ideal
triangulation of a cusped finite-volume hyperbolic 3-manifold, it will place the
triangulation in the census regardless.
This option is designed for use with ideal triangulations only (so, for instance,
combining it with --finite or --boundary will produce an error message). This
option also cannot be used with --dim2 or --dim4.
--allowinvalid
Normally, tricensus will test each triangulation that is constructed for validity
before including it in the final output. If you pass --allowinvalid however, then
these validity tests will not be performed.
As a result, the output may include some invalid triangulations. However, it will
not include all invalid triangulations of the given size, since some invalid
constructions are pruned at earlier levels of the search tree by the census
algorithm (as opposed to being detected by the validity test when each full
triangulation has been constructed). For example, edges that are identified with
themselves in reverse are detected and pruned earlier in this way, and so will
never appear in the census output, even with the --allowinvalid option.
The one guarantee that you do get from this option is that the census will include
all invalid triangulations that could appear as a subcomplex of some valid
triangulation. For example, if a 3-dimensional triangulation is invalid only
because it has vertices whose links are spheres with multiple punctures, then it
will be included in the output.
This option cannot be used with finite/ideal options or minimality options.
-s, --sigs
Instead of writing a full Regina data file, just output a list of isomorphism
signatures.
The output file will be a plain text file. Each line will be a short string of
letters, digits and/or punctuation that uniquely encodes a triangulation up to
combinatorial isomorphism. You can import this text file from within Regina by
selecting File->Import->Isomorphism Signature List from the menu.
This option is highly recommended for large census enumerations. First, the output
file will be considerably smaller. More importantly, the memory footprint of
tricensus will also be much smaller: triangulations can be written to the output
file and forgotten immediately, instead of being kept in memory to construct a
final Regina data file.
-S, --canonical
A variant of --sigs that outputs a list of isomorphism signatures along with
matching isomorphisms.
The output file will be a plain text file. Each line will contain two short
strings, separated by a single space. The first string will be the same
isomorphism signature that is output by --sigs. The second string encodes an
isomorphism F with the property that, if we reconstruct a triangulation from the
isomorphism signature and apply the isomorphism F, then the resulting triangulation
will have a canonical facet pairing.
Here canonical has the same meaning as described below under the --usepairs option:
a facet pairing is in canonical form if it is a minimal representative of its
isomorphism class.
The isomorphisms themselves will be encoded using tight encodings, which (like
isomorphisms signatures) are short strings of letters, digits and/or punctuation.
Currently you will need to use either C++ or Python to decode these; for example,
in dimension 3 you would call Isomorphism<3>::tightDecoding().
If you do not need these isomorphisms, then you should use the simpler (and
slightly faster) option --sigs instead.
-e, --encodings
Instead of writing a full Regina data file, just output a list of tight encodings.
The output file will be a plain text file. Each line will be a short string of
letters, digits and/or punctuation that uniquely encodes a labelled triangulation
as a tight encoding.
Tight encodings differ from isomorphism signatures (as output by --sigs) in the
following ways:
• The main reason for using tight encodings is that they preserve the labelling of
simplices and their vertices (unlike isomorphism signatures, which only encode a
triangulation up to combinatorial isomorphism).
• In general, tight encodings use slightly more characters and are slightly faster
to compute than isomorphism signatures.
• Tight encodings are more difficult to work with. They use a wider variety of
punctuation symbols (which makes them inappropriate for filenames, and awkward to
use as hard-coded strings in source code). Moreover, at present you need to use
either C++ or Python to reconstruct triangulations from them; for example, in
dimension 3 you would call Triangulation<3>::tightDecoding().
If you are not sure whether to use isomorphism signatures or tight encodings, it is
recommended that you choose isomorphism signatures (--sigs).
Like --sigs, this option performs much better in large census enumerations than saving a
full Regina data file: the output file will be considerably smaller, and the memory
footprint of tricensus will also be much smaller. See the --sigs option for further
details.
You can also use --encodings with --genpairs, in which case the facet pairings will be
written using tight encodings instead of human-readable text representations. Tight
encodings of facet pairings cannot be used as input with --usepairs, and again you will
need to use C++ or Python to reconstruct facet pairings from them.
-c, --subcontainers
For each facet pairing, a new container will be created, and resultant
triangulations will be placed into these containers. These containers will be
created even if the facet pairing results in no triangulations.
See --genpairs below for further information on facet pairings.
This option cannot be used with --sigs, --canonical or --encodings.
-p, --genpairs
Only generate facet pairings, not triangulations. A facet pairing stores which
facets of top-dimension simplices are glued to which others, but it does not store
the precise rotations and/or reflections that are used for each gluing. For
3-manifolds a facet pairing represents a pairing of tetrahedron faces, for
2-manifolds it represents a pairing of triangle edges, and for 4-manifolds it
represents a pairing of pentachoron facets.
The outermost layer of the census code involves pairing off the facets of
individual top-dimensional simplices without determining the corresponding gluing
permutations. For each such facet pairing that is produced, Regina will try many
different sets of gluing permutations and generated the corresponding
triangulations.
Facet pairing generation consumes a very small fraction of the total census
runtime, and effectively divides the census into multiple pieces. This option
allows you to quickly generate a complete list of possible facet pairings, so that
you can feed subsets of this list to different machines to work on simultaneously.
The list of all facet pairings will be written to the given output file in a plain
text format (though you may omit the output file from the command line, in which
case the facet pairings will be written to standard output). By default, the
output format will be a space-separated numerical format, suitable for use with
--usepairs (see below). However, if you pass --encodings then the output format
will use tight encodings (which are shorter, contain no spaces, and are much harder
for humans to read). See --encodings for further details on tight encodings.
If you are coordinating your sub-censuses manually, you can use the option
--usepairs to generate triangulations from a subset of these facet pairings. In
this case, the facet pairings will need to be presented using the default space-
separated numerical format (not tight encodings).
Options for orientability, finiteness or minimality cannot be used with --genpairs;
instead you should use them later with --usepairs.
This option does not come with progress reporting, though typically it runs fast
enough that this does not matter. You can always track the state of progress by
counting lines in the output file.
-P, --usepairs
Use only the given subset of facet pairings to build the triangulations.
Each facet pairing that is processed must be in canonical form, i.e., must be a
minimal representative of its isomorphism class. All facet pairings generated
using --genpairs are guaranteed to satisfy this condition.
Facet pairings should be supplied on standard input, one per line. They should be
presented using the space-separated numerical format produced by the option
--genpairs.
This option effectively lets you run a subset of a larger census. See --genpairs
for further details on how to split a census into subsets that can run
simultaneously on different machines.
Options for the number of top-dimensional simplices (i.e., --tetrahedra) or
boundary facets (i.e., --boundary or --bdryfaces) cannot be used with --usepairs.
Instead you should pass these options earlier along with --genpairs when you split
the original census into pieces.
--threads=num_threads
Run the census in parallel using the given number of threads. This parallelisation
is typically very effective (particularly for larger censuses), in that the speed-
up factor is usually close to the theoretical maximum num_threads.
The way the parallelisation currently works is as follows. For each individual
facet pairing, the corresponding search tree is broken into a many smaller subtrees
(i.e., subsearches), each of which can be processed independently by different
threads.
This has two consequences:
• The --threads option cannot be used with --genpairs, since the facet pairings are
still enumerated in serial.
• The output that writes each facet pairing to the console will appear deceptively
fast. This is because each facet pairing will be written as soon as it is
constructed by the main thread, and its many subsearches will be placed in a
queue for other threads to process while the main thread moves on to the next
facet pairing. Once all of the pairings have been output, you may still face a
long wait while the threads together work their way through the queue of
subsearches that has accumulated.
EXAMPLES
The following command forms a census of all 3-tetrahedron closed non-orientable 3-manifold
triangulations, and puts the results in the file results.rga. To ensure that
triangulations are closed we use the options -i (no boundary triangles) and -f (no ideal
vertices).
example$ tricensus -t 3 -nif results.rga
Starting census generation...
0:1 0:0 1:0 1:1 | 0:2 0:3 2:0 2:1 | 1:2 1:3 2:3 2:2
0:1 0:0 1:0 2:0 | 0:2 1:2 1:1 2:1 | 0:3 1:3 2:3 2:2
0:1 0:0 1:0 2:0 | 0:2 2:1 2:2 2:3 | 0:3 1:1 1:2 1:3
1:0 1:1 2:0 2:1 | 0:0 0:1 2:2 2:3 | 0:2 0:3 1:2 1:3
Finished.
Total triangulations: 5
example$
The following command forms a census of 4-tetrahedron closed orientable 3-manifold
triangulations, where the census creation is optimised for prime minimal triangulations.
Although all prime minimal triangulations will be included, there may be some non-prime or
non-minimal triangulations in the census also.
example$ tricensus -t 4 -oifM results.rga
Starting census generation...
0:1 0:0 1:0 1:1 | 0:2 0:3 2:0 2:1 | 1:2 1:3 3:0 3:1 | 2:2 ...
0:1 0:0 1:0 1:1 | 0:2 0:3 2:0 3:0 | 1:2 2:2 2:1 3:1 | 1:3 ...
...
1:0 1:1 2:0 3:0 | 0:0 0:1 2:1 3:1 | 0:2 1:2 3:2 3:3 | 0:3 ...
Finished.
Total triangulations: 17
example$
The following command generates all face pairings for a 5-tetrahedron census of 3-manifold
triangulation in which all triangulations have precisely two boundary triangles. The face
pairings will be written to pairings.txt, whereupon they can be broken up and distributed
for processing at a later date.
example$ tricensus --genpairs -t 5 -B 2 pairings.txt
Total face pairings: 118
example$
The face pairings generated in the previous example can then be fleshed out into a full
census of all 3-manifold triangulations with five tetrahedra, precisely two boundary
triangles and no ideal vertices as follows. The number of tetrahedra and boundary
triangles were already specified in the previous command, and cannot be supplied here.
The face pairings will be read from pairings.txt, and the final census will be written to
results.rga.
example$ tricensus --usepairs -f results.rga < pairings.txt
Trying face pairings...
0:1 0:0 1:0 1:1 | 0:2 0:3 2:0 2:1 | 1:2 1:3 3:0 3:1 | 2:2 ...
0:1 0:0 1:0 1:1 | 0:2 0:3 2:0 2:1 | 1:2 1:3 3:0 3:1 | 2:2 ...
...
... (running through all 118 face pairings)
...
1:0 2:0 3:0 4:0 | 0:0 2:1 3:1 4:1 | 0:1 1:1 3:2 4:2 | 0:2 ...
Total triangulations: 5817
example$
MACOS USERS
If you downloaded a drag-and-drop app bundle, this utility is shipped inside it. If you
dragged Regina to the main Applications folder, you can run it as
/Applications/Regina.app/Contents/MacOS/tricensus.
WINDOWS USERS
The command-line utilities are installed beneath the Program Files directory; on some
machines this directory is called Program Files (x86). You can start this utility by
running c:\Program Files\Regina\Regina 7.1\bin\tricensus.exe.
SEE ALSO
censuslookup, sigcensus, regina-gui.
AUTHOR
This utility was written by Benjamin Burton <bab@maths.uq.edu.au>. Many people have been
involved in the development of Regina; see the users' handbook for a full list of credits.
11 September 2022 TRICENSUS(1)