Changelog#

All notable changes to CVXlab will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]#

Introduced a redesigned guided terminal interface, available through cvxlab.gui(), for configuring and managing the complete modeling workflow.
Refactoring Model.run_model() method, adding three different solution modes: ‘parallel’ (default), ‘sequential’ (for linked sub-problems: results from one problem can be passed automatically to the next following a user-defined chain) and ‘integrated’ (working as the previous version).
Added selective scenario execution, easier inspection of available scenarios, and a model summary.
Added continuous, integer, and boolean variable domains through the new domain setting. The former integer setting is still migrated automatically.
Added per-problem solver selection and solver settings for multi-problem models, together with optional IPOPT support for non-linear problems.

Unified multi-problem execution around parallel, sequential, and integrated solution modes.
Replaced the early cvxlab.run() interface with the redesigned cvxlab.gui() interface. Existing calls to cvxlab.run() must be updated.
Improved validation of model settings, run configuration, variable filters, input files, and workbook contents, providing earlier and clearer feedback.
Improved selective data-table updates and overwrite handling for generated and imported data files.
Increased the minimum supported CVXPY version to 1.9.1 to allow explicit solution for nonlinear problems.

Improved sparse-variable handling: now sparse matrices are defined only for a given minimum matrix size.
Improved normalization of boolean values imported from Excel.
Made database cleanup and restoration more reliable, particularly on Windows.
Added clearer warnings for input data files that contain no values.
Preserved compatibility with the former integrated_problems argument through automatic migration to the new solution-mode configuration.

Added a complete guide for the redesigned interface and expanded the user guide for parallel, sequential, and integrated solution modes.
Added tutorials covering sequential workflows, nonlinear models, and decomposition into coupled convex sub-problems.
Added package-architecture and solution-mode diagrams, refreshed installation instructions, and added software citation metadata.

Frontend CLI (cvxlab.frontend.run()): interactive menu-driven interface for model setup and execution. Modules: interface, session, actions, display.
User-defined constants and operators: template modules (user_defined_constants.py, user_defined_operators.py) for custom symbolic extensions; auto-imported when present in the model directory (issue #109).
CSV input data support: models can now use CSV files as input data sources (issue #103).
Model.update_sets_tables(): update set definitions in an existing SQLite database without full regeneration.
skip_tables argument in Model.run_model() / Core.solve_integrated_problems(): selectively exclude tables from convergence checks.

Python ≥ 3.11 required: bumped requires-python; removed from __future__ import annotations across the codebase.
Integrated-solving convergence refactored: reworked algorithm in Core.solve_integrated_problems().
Centralized Defaults.LiteralTypes: shared Literal type aliases consolidated, replacing scattered definitions.
Identity matrix constant: now accepts a single set as dimensional argument (issue #101).
description columns in data structures are no longer processed, allowing free text (issue #105).
Removed CRITICAL log level from Logger.
Pinned pandas==2.3.3; removed deprecated errors='ignore' arguments (pandas 3.0 compatibility).

util.normalize_dataframe(): improved NaN handling and blank-fill logic.
SQLManager.dataframe_to_table(): string-type conversion and batch flag reset.
Database.load_data_input_files_to_database(): input directory path reference and NaN replacement before SQLite export.
Database.generate_blank_data_input_files(): corrected excel_dir_path argument.
Model.run_model(): selected solver now correctly logged.
util.pivot_dataframe_to_data_structure(): handle missing primary key column in Excel setup files.
Various error-catching improvements for symbolic expression validation and settings inconsistencies (issues #102, #104, #106, #107, #108).