picomats 0.1.1

Use the material. Sustain the assumptions.
Reduce uncertainty by making every assumption explicit.

Overview

PicoMats is an assumption-driven material ontology that sustains assumptions throughout your pipeline. It provides unit-informed material definitions with accompanying assumptions.

This is the demo/alpha release of PicoMats. The library and its ontology will be expanded.

- Follows a computational ontology called `Abstract-Fundamental Ontology`.
- Uses `UnitValues` and `PicoUnits` for encoding typed numerical definitions.
- Tracks assumptions alongside material definitions to reduce model uncertainty.

What is the Abstract-Fundamental Ontology?

It is a computational abstraction for both reductionist and pragmatist applications.

The model is based on two categories:

Abstract:       Defined by what it does     (characteristics).
Fundamental:    Defined by what it is       (structure/state).

Why does it exist?

The ontology emerges from this simple series:

Let's model a ball rolling down a ramp.
        ↓   
What forces act on the ball?
        ↓
Gravity, electromagnetic repulsion, and friction.
        ↓
How do we model friction?
        ↓
A coefficient? Isn't that arbitrary?
        ↓
Why not just model it?
        ↓
What exactly is friction?
        ↓
Oh, random microscopic interactions...

It's possible to model but computationally impractical for most applications.
Hence, the abstract section exists for empirical measurements.

But abstract isn't always the right model...

I want to research superconductors.
        ↓
Oh, my temperature range is 0 K to 200 K.
        ↓
Where do I get material definitions for that range?
        ↓
I'll just interpolate the standard Niobium definition.
        ↓
Actually, how were these measurements obtained?

When asking a fundamental question, it's better to build from fundamental properties.
Hence the fundamental section.

Quick Start

A step-by-step introduction is available in example/.

from picomats import m
from picomats import Materials

# Pulls materials into the simulation
copper = Materials.abstract.pure.copper

density = copper.physical.density
volume = 0.1 * m ** 3

mass = volume * density
# > 893.0 (kg)

Installation

To install:

pip install PicoMats

Documentation

Full documentation is available in the docs/ folder, including API reference, changelog, and contributors.