TEND-STEN(1)

💅 tend-sten — bestie edition 💅

okay so this is tend-sten, a User Command, and it's literally here to calculate structure tensors from a scalar field. yes queen, that's the whole job. 🎀

✨ NAME ✨

tend-sten — calculate structure tensors from a scalar field 🦋

✨ SYNOPSIS ✨

tend sten [-ds <diff. scale>] [-is <int. scale>] [-df <downsample factor>] [-i <nin>] [-o <nout>]

✨ DESCRIPTION ✨

So like, tend-sten calculates structure tensors from a scalar field. 🫶

And before you ask — no, it is not a diffusion tensor. it's giving different energy entirely. but the vibe is still immaculate: it is symmetric and positive-definite, so she's well-behaved, no cap. 👑

✨ OPTIONS ✨

• -ds <diff. scale> — the differentiation scale, measured in pixels. it's the radius of the kernel used for differentiation to compute gradient vectors. type is int, default is "1". 🌸
• -is <int. scale> — the integration scale, also in pixels. it's the radius of the kernel used for blurring outer products of gradients, so that we can compute structure tensors. type is int, default is "2". ✨
• -df <downsample factor> — the factor by which to downsample when creating the volume of structure tensors. type is int, default is "1". 💫
• -i <nin> — the input scalar volume. default is "-". 🍓
• -o <nout> — the output filename, type is string, default is "-". 🎀

✨ SEE ALSO ✨

tend(1) — go read her too bestie, iykyk 💜

and that's the whole page!! 🌈 this beauty is from the User Commands manual, dated April 2021, and she's still serving TEND-STEN(1) realness to this very day. mwah 💅😭🔥