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: left-skewed; smooth / autocorrelated; long-range memory (persistent); red spectrum (low-frequency / 1-over-f power); volatility-clustering (bursty). The atlas additionally detects Nonstationarity:adf_pvalue.

What standard analysis sees
tail heaviness0.54
asymmetry0.15
occupancy0.76
short-range corr0.90
long-range memory0.91
spectral colour0.14
periodicity0.79
complexity0.60
time-irreversibility0.32
volatility clustering0.90
multifractality0.53
dimensionality0.20
nonstationarity0.82
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
Spectral Analysis:spectral_r2+2.0zbank-miss 1.3σ

Composition

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

Render Gallery

Atlas Position

Nearest neighborDistance
fBm (Persistent)1.97
fBm (Antipersistent)2.20
Brownian Walk2.29

Open in Atlas →

Which Geometries Light Up

Ammann-Beenker (Octagonal)Ammann-Beenker (Octagonal):convergent_resonancerank 3/3070.9370
Catch24Catch24:SP_Summaries_welch_rect_centroidrank 306/3070.0004
ChladniChladni:nodal_clusteringrank 4/3077.8920
MoiréMoiré:moire_phi_responserank 305/307-0.1181
Möbius-S³Möbius-S³:phi_return_cvrank 4/3075.4511
Sol (Thurston)Sol (Thurston):integrated_walk_smoothnessrank 2/3070.9127
Spectral AnalysisSpectral Analysis:spectral_r2rank 2/3070.9999
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