TEND-EVEC(1)

💅 TEND-EVEC — the "gimme those eigenvectors" era 💅

okay bestie, welcome to tend-evec, which lives under the tend umbrella (that's tend(1) if you wanna go look). this little icon of a command calculates one or more eigenvectors in a DT volume 🧠✨ like, you hand it a diffusion tensor volume, and it pulls out eigenvectors for you. that's the whole vibe. no cap.

✨ SYNOPSIS ✨

tend evec -c <c0 ...> [-t <thresh>] [-i <nin>] [-o <nout>]

notice -c is not in brackets?? yeah. that's because it's basically the whole point. you must tell it which eigenvectors you want. it's not gonna guess. it has no thoughts about your intentions, only about your tensors 💀

🎀 OPTIONS 🎀

• -c <c0 ...> — which eigenvectors should be saved out. the lore: 0 = the largest, 1 = the middle, 2 = the smallest. want more than one?? be greedy, queen — 0 1, 1 2, 0 1 2, or "similar" combos. it takes 1..3 ints. periodt. 👑
• -t <thresh> — confidence threshold, and it's a float. default is 0.5. so if you don't say anything, it assumes 0.5 and moves on with its life. 🦋
• -i <nin> — the input diffusion tensor volume. default is -. that's the standard "read from stdin" situation, iykyk. 🍓
• -o <nout> — the output image, and heads up it's floating point (the type is string). default: -. so by default it goes to stdout. yes, you can pipe it. slay. 💖

🌸 SEE ALSO 🌸

• tend(1) — the parent, the main character
• tend-eval(1) — its sibling

and that's the whole page, bestie 💜 no filler, all killer.

lowkey the most important thing here is: -c is required. don't show up without it. the command will simply not know which eigenvectors you're obsessed with, and that's a tragedy we can avoid.

okay byeeee — this was the tend-evec manual page, born April 2021, hanging out in the User Commands section of the manual, and honestly?? iconic for it. go forth and compute eigenvectors 🧚🌈⭐