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feat(deep_causality_multivector): separated MLX code into dedicted files for better maintainabiliy.
Signed-off-by: Marvin Hansen <marvin.hansen@gmail.com>
1 parent 05d7a59 commit 583f779

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‎deep_causality_multivector/src/types/multivector/algebra/algebra_cpu.rs‎

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/*
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* SPDX-License-Identifier: MIT
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* Copyright (c) "2025" . The DeepCausality Authors and Contributors. All Rights Reserved.
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*/
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//! CPU-only implementations for Tier 3 algebra operations.
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//! This module is compiled when the MLX feature is disabled.
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use crate::{CausalMultiVector, CausalMultiVectorError};
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use deep_causality_num::{Field, RealField};
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use std::ops::{AddAssign, Neg, SubAssign};
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// Internal implementation methods
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impl<T> CausalMultiVector<T> {
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/// Computes the squared magnitude (squared norm) of the multivector.
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///
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/// $$ ||A||^2 = \langle A \tilde{A} \rangle_0 $$
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pub(in crate::types::multivector) fn squared_magnitude_impl(&self) -> T
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where
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T: Field + Copy + Clone + AddAssign + SubAssign + Neg<Output = T>,
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{
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let reverse = self.reversion_impl();
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let product = self.geometric_product_impl(&reverse);
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product.data[0] // Scalar part
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}
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/// Computes the inverse of the multivector $A^{-1}$ (CPU-only).
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pub(in crate::types::multivector) fn inverse_impl(&self) -> Result<Self, CausalMultiVectorError>
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where
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T: Field
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+ Copy
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+ Clone
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+ Neg<Output = T>
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+ core::ops::Div<Output = T>
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+ PartialEq
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+ AddAssign
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+ SubAssign,
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{
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let sq_mag = self.squared_magnitude_impl();
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if sq_mag == T::zero() {
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return Err(CausalMultiVectorError::zero_magnitude());
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}
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let reverse = self.reversion_impl();
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Ok(reverse / sq_mag)
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}
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/// Computes the dual of the multivector $A^*$ (CPU-only).
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pub(in crate::types::multivector) fn dual_impl(&self) -> Result<Self, CausalMultiVectorError>
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where
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T: Field
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+ Copy
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+ Clone
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+ Neg<Output = T>
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+ core::ops::Div<Output = T>
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+ PartialEq
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+ AddAssign
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+ SubAssign,
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{
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let pseudo = Self::pseudoscalar(self.metric);
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let pseudo_inv = pseudo.inverse_impl()?;
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Ok(self.geometric_product_impl(&pseudo_inv))
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}
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}
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// Public API methods - Tier 3 operations (CPU version)
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impl<T> CausalMultiVector<T>
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where
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T: RealField + Copy,
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{
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/// Normalizes the multivector to unit magnitude.
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pub fn normalize(&self) -> Self {
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let mag_sq = self.squared_magnitude_impl();
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if mag_sq <= T::epsilon() {
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return self.clone();
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}
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let scale_factor = T::one() / mag_sq.sqrt();
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self.scale(scale_factor)
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}
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}
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impl<T> CausalMultiVector<T>
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where
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T: Field + Copy + RealField,
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{
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/// Computes the Lie Commutator: $[A, B] = AB - BA$.
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/// Valid for all associative algebras.
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pub fn commutator(&self, rhs: &Self) -> Self {
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self.commutator_lie_impl(rhs)
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}
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/// Computes the Multiplicative Inverse.
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/// $A^{-1} = \tilde{A} / |A|^2$ (For Versors).
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/// Requires Division (Field).
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pub fn inverse(&self) -> Result<Self, CausalMultiVectorError> {
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let mag_sq = self.squared_magnitude_impl();
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if mag_sq.abs() <= T::epsilon() {
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return Err(CausalMultiVectorError::zero_magnitude());
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}
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let conjugate = self.reversion_impl();
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let scale = T::one() / mag_sq;
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Ok(conjugate.scale(scale))
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}
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/// The Geometric Product for Commutative Coefficients.
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/// This is the standard CPU implementation.
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pub fn geometric_product(&self, rhs: &Self) -> Self {
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self.geometric_product_impl(rhs)
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}
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}

‎deep_causality_multivector/src/types/multivector/algebra/algebra_mlx.rs‎

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/*
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* SPDX-License-Identifier: MIT
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* Copyright (c) "2025" . The DeepCausality Authors and Contributors. All Rights Reserved.
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*/
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//! MLX-accelerated implementations for Tier 3 algebra operations.
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//! This module is compiled only when the MLX feature is enabled.
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use crate::{CausalMultiVector, CausalMultiVectorError};
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use deep_causality_num::{Field, RealField};
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use std::ops::{AddAssign, Neg, SubAssign};
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impl<T> CausalMultiVector<T> {
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/// Computes the squared magnitude (squared norm) of the multivector.
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///
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/// $$ ||A||^2 = \langle A \tilde{A} \rangle_0 $$
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///
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/// MLX-optimized version.
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pub(in crate::types::multivector) fn squared_magnitude_impl(&self) -> T
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where
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T: Field
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+ Copy
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+ Clone
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+ AddAssign
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+ SubAssign
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+ Neg<Output = T>
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+ Default
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+ PartialOrd
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+ Send
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+ Sync
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+ 'static,
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{
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let reverse = self.reversion_impl();
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let product = self.geometric_product_impl(&reverse);
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product.data[0] // Scalar part
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}
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/// Computes the inverse of the multivector $A^{-1}$.
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///
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/// $$ A^{-1} = \frac{\tilde{A}}{A \tilde{A}} $$
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///
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/// Only valid if $A \tilde{A}$ is a non-zero scalar (Versor).
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pub(in crate::types::multivector) fn inverse_impl(&self) -> Result<Self, CausalMultiVectorError>
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where
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T: Field
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+ Copy
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+ Clone
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+ Neg<Output = T>
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+ core::ops::Div<Output = T>
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+ PartialEq
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+ AddAssign
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+ SubAssign
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+ Default
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+ PartialOrd
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+ Send
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+ Sync
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+ 'static,
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{
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let sq_mag = self.squared_magnitude_impl();
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if sq_mag == T::zero() {
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return Err(CausalMultiVectorError::zero_magnitude());
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}
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let reverse = self.reversion_impl();
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let scale = T::one() / sq_mag;
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// Manual scaling to avoid Module<T> trait bound issue
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let scaled_data = reverse.data.iter().map(|v| *v * scale).collect();
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Ok(Self {
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data: scaled_data,
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metric: reverse.metric,
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})
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}
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/// Computes the dual of the multivector $A^*$.
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///
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/// $$ A^* = A I^{-1} $$
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/// where $I$ is the pseudoscalar.
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pub(in crate::types::multivector) fn dual_impl(&self) -> Result<Self, CausalMultiVectorError>
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where
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T: Field
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+ Copy
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+ Clone
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+ Neg<Output = T>
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+ core::ops::Div<Output = T>
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+ PartialEq
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+ AddAssign
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+ SubAssign
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+ Default
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+ PartialOrd
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+ Send
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+ Sync
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+ 'static,
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{
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let pseudo = Self::pseudoscalar(self.metric);
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let pseudo_inv = pseudo.inverse_impl()?;
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Ok(self.geometric_product_impl(&pseudo_inv))
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}
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}
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// Public API methods implementation (Normalize, Commutator, etc for MLX)
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impl<T> CausalMultiVector<T>
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where
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T: RealField + Copy,
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{
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/// Normalizes the multivector to unit magnitude.
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pub fn normalize(&self) -> Self
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where
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T: Default + PartialOrd + Send + Sync + 'static,
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{
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let mag_sq = self.squared_magnitude_impl();
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if mag_sq <= T::epsilon() {
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return self.clone();
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}
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let scale_factor = T::one() / mag_sq.sqrt();
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self.scale(scale_factor)
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}
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}
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impl<T> CausalMultiVector<T>
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where
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T: Field + Copy + RealField,
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{
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/// Computes the Lie Commutator: $[A, B] = AB - BA$.
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/// Valid for all associative algebras.
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pub fn commutator(&self, rhs: &Self) -> Self
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where
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T: Default + PartialOrd + Send + Sync + 'static,
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{
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self.commutator_lie_impl(rhs)
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}
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/// Computes the Multiplicative Inverse (Public Wrapper).
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/// $A^{-1} = \tilde{A} / |A|^2$ (For Versors).
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/// Requires Division (Field).
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pub fn inverse(&self) -> Result<Self, CausalMultiVectorError>
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where
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T: Default + PartialOrd + Send + Sync + 'static,
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{
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self.inverse_impl()
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}
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/// The Geometric Product for Commutative Coefficients.
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///
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/// With `mlx` feature on macOS aarch64: Automatically accelerates N≥6 algebras via GPU.
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pub fn geometric_product(&self, rhs: &Self) -> Self
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where
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T: Default + PartialOrd + Send + Sync + 'static,
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{
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self.geometric_product_impl(rhs)
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}
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}

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