Perlin Noise

stochastic-process · 37 views
stochastic-processstochastic

What It Is

Spectral Perlin-like noise --- coherent smooth fluctuations with 1/f amplitude falloff, widely used for procedural terrain and texture generation

Interpretation

Standard analysis sees: smooth / autocorrelated; long-range memory (persistent); volatility-clustering (bursty). The atlas additionally detects Nonstationarity:adf_pvalue.

What standard analysis sees
tail heaviness0.52
asymmetry0.54
occupancy0.74
short-range corr0.89
long-range memory0.91
spectral colour0.15
periodicity0.81
complexity0.61
time-irreversibility0.60
volatility clustering0.89
multifractality0.45
dimensionality0.22
nonstationarity0.84
What the atlas adds
Nonstationarity:adf_pvalue+2.4z
unit-root nonstationarity (ADF cannot reject random-walk null)
Atlas-extreme metrics the standard bank can’t predict for this source
Moiré:moire_peak_alpha+2.5zbank-miss 1.5σ
Spectral Analysis:spectral_r2+2.0zbank-miss 1.5σ

Composition

dtypefloat64
range[-4.926, 3.454]
unique values16384 / 16384
mean ± std0 ± 1.81

Render Gallery

Atlas Position

Nearest neighborDistance
fBm (Persistent)1.98
fBm (Antipersistent)2.21
Brownian Walk2.30

Open in Atlas →

Which Geometries Light Up

Ammann-Beenker (Octagonal) › Ammann-Beenker (Octagonal):convergent_resonancerank 3/3060.9370
Catch24 › Catch24:SP_Summaries_welch_rect_centroidrank 305/3060.0004
Chladni › Chladni:nodal_clusteringrank 4/3067.8920
Moiré › Moiré:moire_phi_responserank 304/306-0.1181
Möbius-S³ › Möbius-S³:phi_return_cvrank 4/3065.4511
Sol (Thurston) › Sol (Thurston):integrated_walk_smoothnessrank 2/3060.9127
Spectral Analysis › Spectral Analysis:spectral_r2rank 2/3060.9999
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