nomogeo 0.1.0

Exact observer-geometry kernel for visible precision and hidden-load calculus.

nomogeo

nomogeo is an exact observer-geometry kernel for visible precision, local visible calculus, hidden-load parametrisation, and quotient-side Gaussian contraction identities.

This PyPI package stages the nomogeo kernel only. The broader workspace also contains nomodescent, evidence, demonstrations, and research-facing materials, but those are intentionally excluded from this distribution.

Install

python -m pip install nomogeo

Dependencies

• numpy>=2.0
• scipy>=1.15

Quick Start

import numpy as np
from nomogeo import canonical_lift, hidden_load, inverse_visible_class, visible_precision

H = np.array([[3.0, 1.0], [1.0, 2.0]])
C = np.array([[1.0, 0.0]])

phi = visible_precision(H, C)
lift = canonical_lift(H, C)

T = np.diag([2.0, 1.0, 0.0])
Lambda = np.diag([0.3, 0.8])
X = inverse_visible_class(T, Lambda, lambda_representation="reduced")
load = hidden_load(T, X)

Included Surface

• Exact visible precision Phi_C(H) = (C H^{-1} C^T)^{-1}
• Canonical lift and hidden projector
• Local visible calculus (V, Q) and determinant-curvature split
• Hidden-load parametrisation beneath a fixed ceiling
• Hidden-load transport and contraction
• Quotient-side Gaussian distances and contraction utilities

Scope Boundaries

• The package is designed for exact finite-dimensional linear / Gaussian calculations.
• The fixed-ceiling inverse theorem requires the ceiling T as part of the input; it does not invert the global map (H, C) -> Phi_C(H).
• For long hidden composition, use hidden_contraction(...) and load_from_hidden_contraction(...) rather than treating raw load coordinates as associative.