6afdb4b148
Lucidia Core - AI reasoning engines for specialized domains: - Physicist (867 lines) - energy modeling, force calculations - Mathematician (760 lines) - symbolic computation, proofs - Geologist (654 lines) - terrain modeling, stratigraphy - Engineer (599 lines) - structural analysis, optimization - Painter (583 lines) - visual generation, graphics - Chemist (569 lines) - molecular analysis, reactions - Analyst (505 lines) - pattern recognition, insights - Plus: architect, researcher, mediator, speaker, poet, navigator Features: - FastAPI wrapper with REST endpoints for each agent - CLI with `lucidia list`, `lucidia run`, `lucidia api` - Codex YAML configurations for agent personalities - Quantum engine extensions 12,512 lines of Python across 91 files. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
"""Vector mathematics helpers for Lucidia core."""
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from __future__ import annotations
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from dataclasses import dataclass
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import math
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@dataclass(frozen=True)
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class Vector3:
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"""Simple three dimensional vector with basic operations.
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The class implements common arithmetic needed across Lucidia projects
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without pulling in heavy numerical dependencies. Only operations that are
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unambiguous for 3D vectors are provided. Instances are immutable so they
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can be safely shared.
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"""
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x: float
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y: float
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z: float
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def __add__(self, other: "Vector3") -> "Vector3":
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"""Return the element-wise sum of two vectors."""
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return Vector3(self.x + other.x, self.y + other.y, self.z + other.z)
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def __sub__(self, other: "Vector3") -> "Vector3":
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"""Return the element-wise difference of two vectors."""
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return Vector3(self.x - other.x, self.y - other.y, self.z - other.z)
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def __mul__(self, scalar: float) -> "Vector3":
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"""Return the vector scaled by ``scalar``."""
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return Vector3(self.x * scalar, self.y * scalar, self.z * scalar)
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__rmul__ = __mul__
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def dot(self, other: "Vector3") -> float:
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"""Return the dot product with ``other``."""
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return self.x * other.x + self.y * other.y + self.z * other.z
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def norm(self) -> float:
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"""Return the Euclidean norm of the vector."""
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return math.sqrt(self.dot(self))
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def as_tuple(self) -> tuple[float, float, float]:
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"""Return the vector components as a tuple."""
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return (self.x, self.y, self.z)
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__all__ = ["Vector3"]
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