Analysis overview

The three operations answer different questions and have separate chapters.

Operation	Acts on	Meaning	Chapter
Granularity	Consecutive sequence blocks	Repeated block means	Granularity
Fourier	The mapped 2-D image	Centred FFT magnitude	Fourier maps
Difference	Curve visit indices	Mean distance to spatial neighbours	Locality

Granularity: average consecutive blocks

Use hp.plot(values, granularity=4) or obtain values with hp.data.granulate(). The periodic-region example explains the choice of block length.

Fourier: the mapped image’s 2-D spectrum

Use hp.plot(values, fourier=True) or hp.data.fourier(). The Thue–Morse example includes preprocessing, equations and contrast limits.

Difference: where spatial neighbours are far apart in sequence order

Use hp.plot(values, difference=True) or hp.curves.difference_map(). The locality chapter defines the field and shows comparable color scales.

Each plotting call produces one image. Fourier and difference are mutually exclusive.