Warning
This documentation describes a demonstration version for review purposes. The model is still under active development: equations may evolve, data examples may be simplified or synthetic, and taxonomies may change in future versions.
Note
MATER 0.15.0 is a major restructuring release. The 0.15.x series is
the new main development line and is not assumed to be directly compatible
with 0.14.x. See Versioning and migration for details.
MATER 0.15.0 documentation#
MATER (Multi-regional Assessments of Technologies, Energy and Resources) is an open-source Python library for building dynamic stock-flow models of socioeconomic systems.
It provides a modelling framework for dynamic Mass Flow Analysis (dMFA), dynamic Input-Output Analysis (dIOA), and biophysical assessments of technologies, infrastructures, resources, materials and pollutants.
MATER is organized around:
multidimensional pandas variables;
documented systems of equations called presets;
validated variable specifications;
input and output adapters;
a ports-and-adapters software architecture.
Install MATER and run your first simulation from pandas input variables.
This section is the fastest path to a first working example.
Learn how to use MATER in practical modelling workflows: input files, simulation settings, outputs, repositories and presets.
Discover the scientific motivation behind MATER and the software architecture of the package.
This section introduces the modelling approach and the role of MATER in dynamic stock-flow assessments.
Understand the main modelling concepts: variables, equations, presets, stock-flow dynamics and software architecture.
Browse the public Python API generated from the source code, including entry points, presets, equations, variables, ports and adapters.
Want to help improve MATER? Read the contribution guidelines and development recommendations.