pl-mpcs

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

Metadata

Release files for mpcs 1.0.10

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mpcs 1.0.10
File	Size	Uploaded	Provenance
mpcs-1.0.10.tar.gz	6.0 kB	May 23, 2019	Without provenance	Details

Release files / mpcs-1.0.10.tar.gz

Download URL	mpcs-1.0.10.tar.gz
Size	6.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`40adf39e80eac0c24e1513b3784d7236120a9eddd9567071c8b54461c293f3db`
BLAKE2b-256 checksum How to use checksums	`910afa6359108a16e946e35a212f957971057419dc51d98c0d52e4508e7a4ef8`
Upload date	May 23, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.3`

Security for mpcs 1.0.10

Report project as malware

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.

To learn more about protecting yourself from malicious actors, visit our package security documentation.