Skip to content
This repository was archived by the owner on Jan 10, 2018. It is now read-only.

Command Line Interface

gampleman edited this page Dec 6, 2010 · 2 revisions
➔ experiment -h
experiment version 0.3.0
= Synopsis
This program will run an experimental batch or generate files      
for a new experiment

= Usage 
experiment command [options]
  
For help use: experiment -h

= Options
Usage: experiment [options]
    -v, --version
    -h, --help
    -V, --verbose
    -q, --quiet
    -e, --env [ENV]                  Sets the environment to run in.

Options for `generate`:
    -m, --description M              Description or hypothesis for the condition being generated.

Options for `run`:
    -c, --cv CV                      The number of cross validations to run.
    -o, --options OPTSTRING          Options to override or define configuration with.
                                     format as:  key1:val1,key2:val2
        --summary                    After a run of the experiment print out the summary to STDOUT.
    -D, --distributed                Run with a distributed computing mode.
                                     This will be the master server/work cue.
  Overrideable options (defined in config/config.yaml)
       ...

Options for `worker`:
    -a, --address MODE               Address to the master machine.

= Commands
== generate
Generates a new experiment condition
Usage of the -m flag for writing a hypothesis is recommended 

== new
generate a new project in the current directory

== list
Lists available experiments

== report
Generates 2 files in the report directory
method.mmd which sums up comments from experimental conditions
data.csv which sums all results in a table

== run
runs experiments passed as arguments
use the -o option to override configuration

== console
Creates an IRB console useful for debugging experiments
Loads up the environment for the condition passed

== worker
Starts a Worker implementation. It requires an --address option
of it's master server and will recieve tasks (experiments and
cross-validations) and compute them.
Clone this wiki locally