Package: kappy
<img
src=”https://rawgithub.com/Kappa-Dev/KaSim/master/man/img/KaSim-Logo.svg”
alt=”KaSim logo” title=”Stochastic Kappa Simulator” align=”right” height=”90”/>
# KappaTools[![Build Status](https://api.travis-ci.com/Kappa-Dev/KappaTools.svg?branch=master)](https://travis-ci.com/Kappa-Dev/KappaTools)
[![Join the chat athttps://gitter.im/Kappa-Dev/KaSim](https://badges.gitter.im/Kappa-Dev/KaSim.svg)](https://gitter.im/Kappa-Dev/KaSim?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)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](https://kappalanguage.org/documentation).Kappy [API
documentation is online](https://kasim.readthedocs.io/en/latest/kappy.html).The latex sources of the “older” reference manual (and KaSa one) are
available in theman/directory. To compile the manuel, in addition of
a decent LaTeX distribution you need
[gnuplot](http://www.gnuplot.info/) and
[graphviz](http://www.graphviz.org/) to generate images (make sure
thatdotis in the PATH of your OS). To generate the pdf of the
manual typemake doc## Installation### Core tools[Released versions](https://github.com/Kappa-Dev/KaSim/releases) come with
binaries for MacOS, Windows and Debian derivatives (as Ubuntu). [Nightly
builds](https://tools.kappalanguage.org/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](https://opam.ocaml.org/doc/Install.html) (the OCaml
package manager) and initialize it (by issuingopam init)In the source directory, install all the dependencies byopam install –deps-only .dune buildYou can be more fine grained if you only need the command-line tools
(and therefore could install less dependencies) by doingopam install
–deps-only kappa-binariesfollowed bymake allIf 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 amake allaway from getting Kappa binaries…### KappyYou should be able topip 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 theopampackage manager byopam 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### KaSimIn order to run a simulation for 100 time units printing observables values
every 0.5 time unit, typebin/KaSim kappa_file_1 … kappa_file_n -l 100 -p 0.5 -o data_fileThis will produce a data file of 200 point containing the
trajectory that was produced during the simulation.Type:bin/KaSim –helpfor a complete list of options.### KappyDo:`python import kappy client =kappy.KappaRest("http\://url_of/the_server","project_name")`to get a kappa client that uses the REST API hosted byhttp://url_of/the_serverand deals with projectproject_name.or do:`python import kappy client = kappy.KappaStd() `to get a kappa client that uses a kappa agent installed locally. Add a
string argument specifing thepath/to/KaSimAgentto use a specific agent.A minimal example of usage is:`python model = "\ %agent: A(x[x.A]) \ %var: n_0 100 \ %var: k_on1e-2\ 'rule'A(x[.]),A(x[.])<->A(x[1]),A(x[1]) @ k_on, 1 \ %plot:|A(x[.])|\ %init: n_0A()"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 variablesclient.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() `## TestsLaunch the core/integration tests bymake check.Regenerate the reference files if you’ve changed something in the
outputs bymake build-testsLaunch python tests bynosetests(after having followed the “Get
your own build” section).