What is this?
StoSim is a light-weight framework for parameterised stochastic simulations. The researcher provides the simulation code (written in the programming language of his/her choice), but StoSim takes over a lot of tedious work from there on. StoSim can
create all necessary computation jobs (from lists of parameter settings)
execute these jobs on available CPUs (only your computer, the local network or PBS computation cluster)
handle stochastic repetition of settings and seeding of randomness (for repeatable experiments)
analyse the results with graphical plots and T-tests (it is easy to analyse results made with specific parameter settings)
back up code and results (to be able to go back to important milestones)
You can find tutorials and extensive documentation at http://stosim.nicolashoening.de and example simulations in the “example” folder.
Installation/Dependencies
the short answer:
pip install stosim
More details and help are in the documentation.
Dependencies
You need Python 3.3+, 2.7, or 2.6 if you install the argparse module locally.
- Distributing jobs needs Unix Screens, so if the screen command is not available on your system, you need to install it, e.g. on Debian::
sudo apt-get install screen
- To use the in-built plotting, you need gnuplot and epstopdf, e.g. on Debian::
sudo apt-get install gnuplot texlive-extra-utils
For T-Tests, you need Gnu R installed.
More details and help are in the documentation.
Running a simulation: A quick overview
Place an experiment configuration (stosim.conf) and your simulation code in a folder of your choice (see basic example in the examples folder). Call:
stosim
This assumes that you placed a configuration file describing your jobs (called stosim.conf) in the current folder. It also assumes you want to run the jobs, and in addition perform T-Tests and make plots (if stosim.conf says how). So the above command is synonymous to:
stosim --folder . --run --ttests --plots
The results will be put in the “data” directory, in your folder (but if you like the plotting/analysis capabilities of StoSim you might never have to look there).
One more example, where you know your stosim.conf is in a different folder and you only want to run:
stosim --folder <path-to-your-experiment-folder> --run
There are more features, e.g. –more to add more stochastic runs, –list to inspect data or –snapshot to make a snapshots of results at a given time that can be loaded back later. Do check out the tutorials where you can learn more.
1 maintainer
Metadata
1 maintainer
Release files for stosim 0.2.22
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| stosim-0.2.22.tar.gz | 22.1 kB | Without provenance | Details |
Release files / stosim-0.2.22.tar.gz
| Download URL | stosim-0.2.22.tar.gz |
|---|---|
| Size | 22.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
bb331edbf80545c881ea78db96277e6b3140c387df5aa56e0f3710fc538d827c
|
|
BLAKE2b-256 checksum How to use checksums |
ed8d41526d7275730803083665ca4b8783149875500bd7c5b1a217943a2af415
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for stosim 0.2.22
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
