0.6.6 release

.github/workflows/test.yaml

@@ -48,7 +48,7 @@ jobs:
         with:
           toolchain: stable
       - name: run benchmarks
-        run: cargo bench
+        run: CARGO_TARGET_X86_64_UNKNOWN_LINUX_GNU_RUNNER="timeout 600" cargo bench
 
   coverage:
     name: code coverage

CHANGELOG.md

@@ -1,5 +1,19 @@
 # changelog
 
+## 0.6.6 (2025-04-23)
+
+### added
+- organized traits into dedicated modules with feature flags
+- implemented conditional compilation for optional traits (optics, projection, manifold)
+- tensor test suite comparing mathematical representation and performance with geonum
+
+### changed
+- refactored codebase for improved maintainability and organization
+- moved primary types into separate modules (geonum.rs, multivector.rs, dimensions.rs)
+- reduced lib.rs size
+- fixed Clippy lints and warnings throughout codebase
+- new benchmark numbers in README
+
 ## 0.6.5 (2025-04-21)
 
 ### changed

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "geonum"
-version = "0.6.5"
+version = "0.6.6"
 edition = "2021"
 repository = "https://github.com/mxfactorial/geonum"
 description = "geometric number library supporting unlimited dimensions with O(1) complexity"
@@ -10,10 +10,18 @@ keywords = ["geonum", "geometry", "math", "algebra", "geometric-algebra"]
 categories = ["mathematics", "simulation", "algorithms", "data-structures"]
 authors = ["mxfactorial"]
 
+[features]
+default = []
+optics = []
+projection = []
+manifold = []
+all = ["optics", "projection", "manifold"]
+
 [dependencies]
 
 [dev-dependencies]
 criterion = "0.5"
+geonum = { path = ".", features = ["all"] }
 
 [[bench]]
 name = "geonum_benchmarks"

README.md

@@ -51,40 +51,40 @@ see [tests](https://github.com/mxfactorial/geonum/tree/develop/tests) to learn h
 
 | implementation | size | time |
 |----------------|------|------|
-| tensor (O(n³)) | 2 | 1.06 µs |
+| tensor (O(n³)) | 2 | 1.05 µs |
 | tensor (O(n³)) | 3 | 2.25 µs |
-| tensor (O(n³)) | 4 | 3.90 µs |
-| tensor (O(n³)) | 8 | 7.92 µs |
-| tensor (O(n³)) | 16 | 69.54 µs |
-| geonum (O(1)) | any | 9.83 ns |
+| tensor (O(n³)) | 4 | 4.20 µs |
+| tensor (O(n³)) | 8 | 7.83 µs |
+| tensor (O(n³)) | 16 | 66.65 µs |
+| geonum (O(1)) | any | 15.52 ns |
 
-geonum achieves constant O(1) time complexity regardless of problem size, 400× faster than tensor operations at size 4 and 7000× faster at size 16, eliminating cubic scaling of traditional tensor implementations
+geonum achieves constant O(1) time complexity regardless of problem size, 270× faster than tensor operations at size 4 and 4300× faster at size 16, eliminating cubic scaling of traditional tensor implementations
 
 #### extreme dimension comparison
 
 | implementation | dimensions | time | storage complexity |
 |----------------|------------|------|-------------------|
-| traditional ga | 10 | 543.40 ns (partial) | O(2^n) = 1024 components |
+| traditional ga | 10 | 545.69 ns (partial) | O(2^n) = 1024 components |
 | traditional ga | 30 | theoretical only | O(2^n) = 1 billion+ components |
 | traditional ga | 1000 | impossible | O(2^1000) ≈ 10^301 components |
 | traditional ga | 1,000,000 | impossible | O(2^1000000) components |
-| geonum (O(1)) | 10 | 134.12 ns | O(1) = 2 components |
-| geonum (O(1)) | 30 | 153.64 ns | O(1) = 2 components |
-| geonum (O(1)) | 1000 | 2.08 µs | O(1) = 2 components |
-| geonum (O(1)) | 1,000,000 | 2.94 ms | O(1) = 2 components |
+| geonum (O(1)) | 10 | 78.00 ns | O(1) = 2 components |
+| geonum (O(1)) | 30 | 79.64 ns | O(1) = 2 components |
+| geonum (O(1)) | 1000 | 77.44 ns | O(1) = 2 components |
+| geonum (O(1)) | 1,000,000 | 78.79 ns | O(1) = 2 components |
 
 geonum enables geometric algebra in million-dimensional spaces with constant time operations, achieving whats mathematically impossible with traditional implementations (requires more storage than atoms in the universe)
 
 #### multivector ops
 
 | operation | dimensions | time | traditional ga complexity |
 |-----------|------------|------|---------------------------|
-| grade extraction | 1,000,000 | 130.69 ns | O(2^n) |
-| grade involution | 1,000,000 | 157.18 ns | O(2^n) |
-| clifford conjugate | 1,000,000 | 112.90 ns | O(2^n) |
-| contractions | 1,000,000 | 266.31 ns | O(2^n) |
-| anti-commutator | 1,000,000 | 246.24 ns | O(2^n) |
-| all ops combined | 1,000 | 826.57 ns | impossible at high dimensions |
+| grade extraction | 1,000,000 | 136.46 ns | O(2^n) |
+| grade involution | 1,000,000 | 153.37 ns | O(2^n) |
+| clifford conjugate | 1,000,000 | 111.39 ns | O(2^n) |
+| contractions | 1,000,000 | 292.56 ns | O(2^n) |
+| anti-commutator | 1,000,000 | 264.46 ns | O(2^n) |
+| all ops combined | 1,000 | 883.74 ns | impossible at high dimensions |
 
 geonum performs all major multivector operations with exceptional efficiency in million-dimensional spaces, maintaining sub-microsecond performance for grade-specific operations that would require exponential time and memory in traditional geometric algebra implementations
 

benches/geonum_benchmarks.rs

@@ -260,10 +260,10 @@ fn bench_extreme_dimensions(c: &mut Criterion) {
             // we'll do a very limited calculation - just computing a small subset
             // of the full 1024×1024 operation
             let mut result = vec![0.0; 1024];
-            for i in 1..20 {
-                // Doing only 20 components for benchmarking sanity
-                for j in 1..20 {
-                    if v1[i] != 0.0 && v2[j] != 0.0 {
+            // Only 20 components for benchmarking sanity
+            for (i, &v1i) in v1.iter().enumerate().skip(1).take(19) {
+                for (j, &v2j) in v2.iter().enumerate().skip(1).take(19) {
+                    if v1i != 0.0 && v2j != 0.0 {
                         // XOR gives the resulting basis element index
                         let k = i ^ j;