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Decision Optimization utilities for IBM Watson Studio projects

Project description

DSE_DO_Utils

Decision Optimization utilities for IBM Watson Studio Local and ICPd projects.

Source (GitHub)
Documentation (GitHubPages)

This repository contains the package dse_do_utils. This can be installed using pip.

Main classes:

  1. ScenarioManager. Reads and writes table data from and to all combinations of csv-files, Excel spreadhseet and DO scenario.
  2. DataManager. A DataManager is mostly a container for data and functions for pre- and post-processing. Can be subclassed and stored in a script to be able to share code between multiple notebooks. Also contains some utilities for data manipulation, like the crossjoin.
  3. OptimizationEngine. Also mostly a container for functions around creating an optimization model and using the docplex APIs. Can be subclassed and stored in a script to be able to share code between multiple notebooks. Also contains some functions to create dvars and export .lp files.
  4. ScenarioPicker. Interactively pick an existing scenario from a drop-down menu in a notebook. Typically used in visualization notebooks.
  5. MapManager. For creating map visualizations using Folium.
  6. DOModelExporter. To export DO Models in CPDv2.5.

Installation (CPDv2.5)

(For Cloud Pak for Data v2.5)

CPDv2.5 is very different from the previous versions and it has a significant impact on how the dse-do-utils can be installed and used.

Options:

  1. Install using pip in a customized environment. This applies to both Jupyter and JupyterLab.
  2. Install as a package in JupyterLab.
  3. Install as modules in Jupyter
  4. Install/use as modules in the DO Model Builder

Install in customized environment

CPDv2.5 allows for easy customization of environments. Add the following to the customization configuration:

- pip:
    - dse-do-utils=0.3.0.0

This automatically downloads dse-do-utils from PyPI and installs the package.

For air-gapped systems that have no access to PyPI:

  1. Download the package from PyPI/Conda from an internet connected system as a wheel/zip file
  2. Upload the wheel/zip as a data asset
  3. Install package from wheel/zip

This downloads the package as a wheel/zip and puts it in the data assets

!pip download dse-do-utils -d /project_data/data_asset/

Then move the wheel/zip to the Data Assets. See the InstallationReadMe.md for more details on installation and usage in other cases.

Import

Then import the required classes from dse_do_utils:

from dse_do_utils import ScenarioManager, DataManager

This is the basics. For many ore details on other usage, see InstallationReadMe.md

Target environments

To be used within:

  1. CPDv2.1 (version 0.2.2.3 is preferred. But version 0.3.0.0 should be backwards compatible.)
  2. CPDv2.5 (version 0.3.0.0 and up)
  3. WSLv1.2.3 with Python 2.7 (version 0.2.2.3 only)
  4. WS Cloud (version 0.4.0.0 and up)

DO Model Builder and WML environments

When developing and using optimization models, there are 3 different environments the Python DO model might run in:

  1. A notebook environment.
  2. The DO Model Builder environment.
  3. The WML deployment environment.

In CPDv2.5:

  • Only the notebook environment can be regularly customized with the dse-do-utils.
  • The Model Builder environment cannot be customized. But, it has a feature to add 'files'. The dse-do-utils internal modules have been refactored to be able to be uploaded separately as individual modules.
  • The WML environment cannot be customized. But the same work-around for adding modules/files to the MB model can be used.

In CPDv3.0:

  • The WML environment can be customized using APIs.

In future releases of CPD:

  • The DO Model Builder will also allow for environment customization

Scope of classes/modules

The classes OptimizationEngine and DataManager are intended to be used within the optimization model code that will run in the Model Builder and WML deployment. All other classes, in particular the ScenarioManager are designed to be used outside of the Model Builder or WML, e.g. within #dd-ignore cells.

Therefore, the limitations in customizing environments can, for the moment, be avoided by not using the classes OptimizationEngine and DataManager.

Requirements

This package requires:

  1. dd-scenario. This package provides an interface to the DO scenarios. This package is only available within WSL and ICPd. It cannot be pip installed in other environments.
  2. docplex. This package interfaces with the CPLEX and CP Optimizer optimization engines.
  3. folium. Map visualization. Only for the MapManager.

Project details


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