Initialization of numerical problem(s)

This step prepares the numerical optimization problem(s) for a CVXlab model, transforming symbolic definitions and data structures into a form ready for solution by a numerical solver.

Overview

• Fetches data from the input data Excel file(s) to the exogenous data tables of the SQLite database, verifying the consistency of the data provided.

• Loads and validates symbolic problem(s) expressions from the model settings, ensuring that all referenced variables and data tables are properly defined.

• Initializes CVXPY problem(s) variables and assigns data to exogenous ones.

• Constructs the CVXPY numerical problem(s) for each scenario, based on the symbolic expressions and defined variables.

API: refresh_database_and_initialize_problem()

Typical Usage

import cvxlab

# Previous steps:
# - Create model directory and setup files
# - Create Model instance
# - Fill sets data (coordinates)
# - Initialization of data structures
# - Fill input data Excel file(s)

# [CURRENT STEP] Initialization of numerical problem(s)
model.refresh_database_and_initialize_problem(
    table_key_list=[...],
    force_overwrite=False,
)

Parameters description

Parameter	Description	Default
table_key_list	List of data table keys to refresh from the input files. Leave empty when initializing a model for the first time; provide specific table keys when only selected data have changed.	[] (all tables)
force_overwrite	If True, overwrites existing SQLite data and numerical problem definitions without confirmation.	False

Workflow

When refresh_database_and_initialize_problem() is called on a Model instance:

• Loads exogenous data from the input data Excel file(s), assigning values to exogenous data tables in the SQLite database.

• Parses exogenous variables, and fills the empty entries in the related data tables with value provided by the blank_fill variable attribute. This facilitates the user in filling repetitive data entries in data tables.

• Loads and parses symbolic problem expressions from model settings, validating problem structure against a validation schema and raising explicit errors if any issues are found.

• Checks if all variables numeric data are present in the SQLite database: in case NULL entries are found, the method logs the table name and the corresponding row IDs, and raises an error.

• Initializes model variables structures, including all variables information such as the type (endogenous, exogenous, constants, hybrid), shape (rows and columns), cardinality (inter- and intra-problem dimensions) and the associated CVXPY variable object, according to the model settings.

• Fetches exogenous variable data from SQLite database and assigns it to the corresponding CVXPY variable objects.

• Constructs the numerical optimization problem(s) for each scenario, generating and assembling the expressions using the symbolic definitions and loaded data.

• If force_overwrite=True, any existing numerical value in exogenous data tables (or a selection of them, in case table_key_list is specified) and all variables and problems objects are overwritten without confirmation.