Skip to main content

This app simulates an MPC compute call and creates a z-score file.

Project description

https://badge.fury.io/py/mpcs.svg https://travis-ci.org/FNNDSC/mpcs.svg?branch=master https://img.shields.io/badge/python-3.5%2B-blue.svg

Abstract

This app simulates a call to a remote Multi-Party Compute (MPC) in the context of a FreeSurfer workflow.

This particular application simply returns a z-score file to be consumed by a downstream plugin, typciall pl-z2labelmap.

NOTE: The <inputDir> is largely ignored by this plugin.

Synopsis

python mpcs.py                                                  \
    [--random] [--seed <seed>]                                  \
    [-p <f_posRange>] [--posRange <f_posRange>]                 \
    [-n <f_negRange>] [--negRange <f_negRange>]                 \
    [-z <zFile>] [--zFile <zFile>]                              \
    [-v <level>] [--verbosity <level>]                          \
    [--version]                                                 \
    [--man]                                                     \
    [--meta]                                                    \
    <inputDir>
    <outputDir>

Run

This plugin can be run in two modes: natively as a python package or as a containerized docker image.

Using PyPI

To run from PyPI, simply do a

pip install mpcs

and run with

mpcs.py --man /tmp /tmp

to get inline help. The app should also understand being called with only two positional arguments

mpcs.py /some/input/directory /destination/directory

Using docker run

To run using docker, be sure to assign an “input” directory to /incoming and an output directory to /outgoing. Make sure that the $(pwd)/out directory is world writable!

Now, prefix all calls with

docker run --rm -v $(pwd)/out:/outgoing                             \
        fnndsc/pl-mpcs mpcs.py                                      \

Thus, getting inline help is:

mkdir in out && chmod 777 out
docker run --rm -v $(pwd)/in:/incoming -v $(pwd)/out:/outgoing      \
        fnndsc/pl-mpcs mpcs.py                                      \
        --man                                                       \
        /incoming /outgoing

Arguments

[--random] [--seed <seed>]
If specified, generate a z-score file based on <posRange> and
<negRange>. In addition, if a further optional <seed> is passed,
then initialize the random generator with that seed, otherwise
system time is used.

[-p <f_posRange>] [--posRange <f_posRange>]
Positive range for random max deviation generation.

[-n <f_negRange>] [--negRange <f_negRange>]
Negative range for random max deviation generation.

[-z <zFile>] [--zFile <zFile>]
z-score file to save in output directory. Defaults to 'zfile.csv'.

[-v <level>] [--verbosity <level>]
Verbosity level for app. Not used currently.

[--version]
If specified, print version number.

[--man]
If specified, print (this) man page.

[--meta]
If specified, print plugin meta data.

Examples

Create a z-file with values between -3.0 and +3.0

mkdir in out && chmod 777 out
docker run --rm -v $(pwd)/in:/incoming -v $(pwd)/out:/outgoing      \
        fnndsc/pl-mpcs mpcs.py                                      \
        -random --seed 1                                            \
        --posRange 3.0 --negRange -3.0                              \
        in out

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mpcs, version 1.0.10
Filename, size File type Python version Upload date Hashes
Filename, size mpcs-1.0.10.tar.gz (6.0 kB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page