Distribute PySPI jobs across a PBS cluster

Last update: Feb 10, 2022

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Overview

Distribute PySPI jobs across a PBS cluster

This repository contains scripts for distributing PySPI jobs across a PBS-type cluster. Each job will contain one calculator object that is associated with one multivariate time series (MTS).

The scripts assume the directory structure that is already set up in this repo: there is a database directory (database) that contains all MTS files, along with a YAML configuration file (sample.yaml) that specifies the relative location of each file (and, optionally, their name, dim_order, and any relevant labels).

Usage

Follow the PySPI documentation to install and set-up PySPI on your cluster
Ensure that any relevant initialization procedures (for setting up conda or anything else) is contained in the PBS script.
Copy all MTS (as numpy files) to the database folder, and update the sample.yaml file accordingly.
activate your conda environment:

conda activate pyspi

Submit the jobs:

python distribute_jobs.py

The results will be stored in the database under the same name as the numpy files. For example, if you have the file database/sample1.npy in your YAML file, then there will be a new folder called database/sample1 with a calc.pkl file inside that contains the calculator.

In order to access the results, load the calculator with dill

import dill

with open('calc.pkl','rb') as f:
  calc = dill.load(f)

Then you can view the contents as per the standard PySPI documentation, e.g.,

calc.table
calc.table['cov_EmpiricalCovariance]

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Comments

Added functionality for command-line inputs
Suggesting the following changes based on preliminary cluster usage:

implementation of command-line inputs for distribute_jobs.py to allow user to customise data location, sample YAML file, walltime, overwriting, and pbs notifications

pyspi_distribute.py now automatically generates a PBS script for each job based on user inputs

flexibility for user-supplied config.yaml to define a subset of SPIs to examine

creation of a script (create_yaml_for_samples.R) that automatically generates sample YAML file if the user wishes

updated readme to reflect these changes
opened by anniegbryant 2
Add option for user to only save calc.table to pickle file

Hi Oliver! In working with a large number of datasets using pyspi-distribute, I noticed that saving the entire calc object to calc.pkl was quickly taking up a good amount of space -- whereas my only downstream use for the calc object is calc.table. I added an option for a user to specify if they only want to save calc.table, in which case they can add the flag --table_only. The default is False, such that without specifying, the entire calc object is saved. Not sure if this is helpful/useful, just wanted to send your way.

opened by anniegbryant 0

Distribute PySPI jobs across a PBS cluster

Related tags

Overview

Distribute PySPI jobs across a PBS cluster

Usage

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Comments

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Owner

Oliver Cliff

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