Skip to content

User Guide

Welcome to the OptiScope User Guide! This comprehensive guide will help you understand and effectively use OptiScope for your optimization analysis and visualization needs.

Overview

OptiScope is a modern Python library designed to simplify the analysis and visualization of optimization results. Whether you're working with single-objective or multi-objective optimization problems, OptiScope provides the tools you need to:

  • Load and manage optimization results from various file formats
  • Organize and filter solutions using result sets
  • Visualize high-dimensional optimization data
  • Perform advanced analysis on Pareto fronts and solution spaces
  • Store and retrieve results efficiently

What's in This Guide

This user guide is organized into the following sections:

Data Model

Learn about OptiScope's core data structures and how optimization results are represented. This section covers:

  • The OptimizationResult class and its components
  • Design variables, objectives, constraints, and observables
  • Problem metadata and variable types
  • How data is organized and accessed

File Formats

Discover the various file formats that OptiScope can read and write. This section includes:

  • Supported input formats (CSV, JSON, HDF5, etc.)
  • File format specifications and requirements
  • How to load optimization results from different sources
  • Creating custom file handlers for proprietary formats

Storage Backends

Understand how OptiScope manages data persistence and storage. Topics include:

  • Available storage backends (Memory, HDF5, SQLite)
  • Choosing the right storage backend for your needs
  • Saving and loading optimization results
  • Managing multiple results efficiently

Result Sets

Master the concept of result sets for organizing and analyzing subsets of solutions. Learn about:

  • What result sets are and why they're useful
  • Creating and managing result sets
  • Common use cases (Pareto fronts, feasible solutions, user selections)
  • Filtering and querying result sets

Visualization

Explore OptiScope's powerful visualization capabilities. This section covers:

  • Parallel coordinates plots for multi-dimensional data
  • Pareto front viewers for multi-objective optimization
  • Scatter matrix plots for correlation analysis
  • Interactive scatter plots with customizable axes
  • Optimization history visualization

Analysis Tools

Leverage advanced analysis tools to gain insights from your optimization results:

  • Pareto front identification and filtering
  • Smart Pareto filtering for cleaner fronts
  • TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)
  • Knee point detection for trade-off analysis
  • Feasibility analysis and constraint checking

Getting Help

If you're new to OptiScope, we recommend starting with the Getting Started section, which provides a quick introduction and installation guide.

For practical examples and code snippets, check out the Examples section.

For detailed API documentation, refer to the API Reference.

Next Steps

Ready to dive in? Start with the Data Model to understand how OptiScope represents optimization data, or jump directly to any section that interests you using the navigation menu.