How uniformly the signal's growth structure fills angular space.
Maps the time series onto a logarithmic spiral in polar coordinates: each sample advances the angle by a data-dependent step (larger values rotate faster) while the radius grows exponentially. The resulting spiral path reflects multiplicative structure in the data.
How uniform are the angular step sizes along the spiral path? Computed as 1 minus the coefficient of variation of consecutive angular increments. 1.0 means all steps are the same size. Collatz Gap Lengths (0.984) scores highest: its angular increments are nearly constant in magnitude. Accelerometer sitting (0.968) and BTC Returns (0.961) are close behind — both have broad amplitude distributions that produce consistent angular steps. Collatz Parity scores 0.292 (strongly non-uniform — the binary values create only two angular step sizes). Constants score 0.0.
| Source | Domain | Value |
|---|---|---|
| Collatz Gap Lengths | number_theory | 0.9843 |
| Accel Sit | motion | 0.9678 |
| BTC Returns | financial | 0.9611 |
| ··· | ||
| Constant 0xFF | noise | 0.0000 |
| Constant 0x00 | noise | 0.0000 |
| Collatz Parity | number_theory | 0.2919 |
Logarithmic Spiral's angular_uniformity is a proxy for how well the signal's amplitude distribution fills the dynamic range. Signals with uniform or symmetric distributions achieve high uniformity; signals with degenerate or heavily skewed distributions concentrate in narrow angular sectors. It complements the distributional view by providing a geometric (rather than entropic) measure of amplitude spread. In the atlas, it separates continuous-valued signals with broad distributions (financial returns, accelerometer data) from binary or symbolic signals (Collatz parity, Morse code) along the scale view's angular axis.