KappaTools

KaSim is a stochastic simulator for rule-based models written in Kappa. KaSa is
a static analyser for Kappa models.

Kappy is a python library to launch and analyse runs and outputs of
Kappa models.

User manual

See documentation page on kappalanguage.org.

Kappy API
documentation is online.

The latex sources of the "older" reference manual (and KaSa one) are
available in the man/ directory. To compile the manuel, in addition of
a decent LaTeX distribution you need
gnuplot and
graphviz to generate images (make sure
that dot is in the PATH of your OS). To generate the pdf of the
manual type

make doc

Installation

Core tools

Released versions come with
binaries for MacOS, Windows and Debian derivatives (as Ubuntu). Nightly
builds of the master branch
are built for these platforms by the continuous integration tools.

If you want or need your own build,

• Install opam (the OCaml
  package manager) and initialize it (by issuing opam init)

• In the source directory, install all the dependencies by opam install --deps-only .

• dune build

You can be more fine grained if you only need the command-line tools
(and therefore could install less dependencies) by doing opam install --deps-only kappa-binaries followed by make all

If nothing worked for you so far. Well, you're pretty much on your
own... Kappa tools depend upon the OCaml native compiler version
4.05.0 or above as well as dune, findlib, Lwt (>= 2.6.0), Re,
Fmt, Logs and Yojson libraries. Find any way to install them and
you'll be only a make all away from getting Kappa binaries...

Kappy

You should be able to pip install kappy.

• Under MacOS and linux (and if you're not using a python version so
  cutting edge that we haven't notice its release yet), wheels that
  contain the core binaries should be available.

• For other platforms/python versions, you need to get kappa agents by
  yourself thanks to the opam package manager by opam install kappa-binaries kappa-agents (or use an externaly hosted REST API)

• In order to develop in kappy and run all its tests, you need to
  follow the "get your own build section" above as well as install
  requests (and future).

Usage

KaSim

In order to run a simulation for 100 time units printing observables values
every 0.5 time unit, type

bin/KaSim kappa_file_1 ... kappa_file_n -l 100 -p 0.5 -o data_file

This will produce a data file of 200 point containing the
trajectory that was produced during the simulation.

Type:

bin/KaSim --help

for a complete list of options.

Kappy

Do:

import kappy
client = kappy.KappaRest("http\://url_of/the_server","project_name")

to get a kappa client that uses the REST API hosted by
http://url_of/the_server and deals with project project_name.

or do:

import kappy
client = kappy.KappaStd()

to get a kappa client that uses a kappa agent installed locally. Add a
string argument specifing the path/to/KaSimAgent to use a specific agent.

A minimal example of usage is:

model = "\
%agent: A(x[x.A]) \
%var: n_0 100 \
%var: k_on 1e-2 \
'rule' A(x[.]), A(x[.]) <-> A(x[1]), A(x[1]) @ k_on, 1 \
%plot: |A(x[.])| \
%init: n_0 A()"
client.add_model_string(model)
client.project_parse()
sim_params = kappy.SimulationParameter(pause_condition="[T] > 100",plot_period=1)
client.simulation_start(sim_params)
client.wait_for_simulation_stop()
results = client.simulation_plot()
client.simulation_delete()
# Rerun with some overwritten values for algebraic variables
client.project_parse(k_on=5e-2,n_0=500)
client.simulation_start(sim_params)
client.wait_for_simulation_stop()
results' = client.simulation_plot()
client.shutdown()

Tests

Launch the core/integration tests by make check.

Regenerate the reference files if you've changed something in the
outputs by make build-tests

Launch python tests by nosetests (after having followed the "Get
your own build" section).