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workouts/Exercise Library/SYSTEM.md
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rzen fce8fa4c17 Author the machine exercise circuit with props and corrected hip machine motions
Fourteen Planet Fitness machine exercises join the rig library, each with
authored motion, info page, and schematic equipment via the new props layer
(scene shapes, cables, bars, pads) rendered in lockstep by render.py and the
in-app figure renderer. Abductor and Adductor are authored face-on with the
real seated machine motion — knees-bent legs swinging apart/together against
knee pads — replacing the earlier middle-split depiction. The watch target
now bundles the figure renderer and motion rigs too.

Claude-Session: https://claude.ai/code/session_01LEoff8bXGBS83tK1c55Mf7
2026-07-06 16:29:31 -04:00

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Exercise Visual System

Exercise visuals are produced by an articulated 2D rig: one shared stick body posed per exercise by joint angles. Nothing is drawn by hand — a body profile plus a motion script resolve through forward kinematics into every frame, so figures are always in proportion, and the whole library can be re-proportioned (male/female), flipped, rotated in-plane, or re-themed by changing data, never artwork.

The rig

  • body.json — proportion profiles. Each profile is a table of bone lengths: headR, neck, spine1/spine2 (two chained segments so the spine can curve), upperArm/foreArm, thigh/shin, plus leftOffset (the small offset that separates left-limb attachments visually). neutral is the default; add profiles to add figures.
  • <Exercise>/motion.json — the exercise script: key frames of absolute joint angles (degrees, y-up: 0=forward/right, 90=up, 180=back/left, -90=down), a root pelvis position, and timing.
{
  "name": "Bird Dog",
  "primary": 2,                    // 1-based frame used for visual.svg
  "working": ["arm_r", "leg_l"],   // parts drawn in the accent color
  "hide": [],                      // limbs fully occluded in this view
  "frames": [
    {
      "hold": 0.5,                 // seconds held at this key frame
      "tween": 0.8,                // seconds animating to the NEXT frame
      "root": [190, 106],          // pelvis, canvas coords
      "spine": [171, 171],         // pelvis→mid, mid→neck angles
      "neck": 187, "gaze": 205,    // head direction; nose tick direction
      "arm_r": [-90, -90],         // upper-arm, forearm angles
      "arm_l": [-90, -90],
      "leg_r": [-83, 0],           // thigh, shin angles
      "leg_l": [-83, 0],
      "pins": {"hand_r": [105, 152], "hand_l": [111, 154]}
    }
  ]
}
  • Pins (IK) — a planted hand/foot names a target point (hand_r/hand_l/foot_r/foot_l); the renderer solves the two-bone chain analytically so the extremity holds that point exactly, using the authored angles only to pick the elbow/knee bend direction. A pin active in two consecutive key frames stays planted throughout the tween (plank forearms, side-plank support arm); a pin present in only one frame releases naturally (bird-dog arm lifting off).
  • Tweening happens in angle space (shortest path), so limbs swing in natural arcs and bone lengths never distort. The last frame tweens back to the first (looping). Asymmetric timing carries technique: leg raises lower slowly (tween 1.4 s down, 0.6 s up).
  • Face-on figuresgaze is optional: a frame without it faces the viewer and draws no nose tick. Used by exercises whose motion is lateral (abductor/adductor), where a side view would hide the movement.

The props layer

Machines and free weights are data too: an optional top-level "props" array adds an equipment layer around the figure. scene shapes and cables draw behind the figure in a recessive gray; joint-attached items (bar, dumbbell, pad) draw over the limbs in a darker gray and follow the resolved hand/foot positions every frame — a pinned foot pressing a pad carries the platform with it through the tween for free. The figure stays the hero: props are schematic silhouettes (a seat, a backrest, one handle), never scale drawings of the machine.

"props": [
  {"type": "scene", "shapes": [
    {"kind": "line", "pts": [[134, 123], [96, 36]], "w": 9},
    {"kind": "rect", "x": 54, "y": 104, "w": 40, "h": 8, "r": 3},
    {"kind": "circle", "c": [142, 77], "r": 3.5, "fill": true, "color": "prop"}
  ]},
  {"type": "cable", "from": [190, 8], "to": ["hand_r", "hand_l"]},
  {"type": "bar", "at": ["hand_r", "hand_l"], "halfLen": 26, "plateR": 0},
  {"type": "dumbbell", "at": "hand_r"},
  {"type": "pad", "at": ["foot_r", "foot_l"], "angle": 88, "halfLen": 20, "w": 6}
]
  • scene — static shapes in canvas coordinates: line (polyline, stroke width w), circle (fill: false for an outline), rect (filled, corner radius r). A shape may set "color": "prop" to use the darker attached-item gray (e.g. a fixed handle the hands rest on).
  • cable — a thin line from a fixed anchor from to a moving joint to; the machine's pulley line.
  • bar / dumbbell / pad — a segment centered on the joint(s) in at (a single extremity, or the midpoint of ["hand_r", "hand_l"]). bar lies at a fixed world angle (default 0 = horizontal — in side view a two-handed bar is drawn horizontal by convention); dumbbell and pad default to perpendicular to the lower bone (forearm/shin), or take an explicit angle. plateR puts filled discs on both ends (dumbbells default to 4.5). A prop whose limb is hidden that frame simply isn't drawn.
  • The same math is the plan for the app: a small SwiftUI renderer consumes body.json + motion.json and tweens angles on the lower half of the exercise screen (the paged timer flow occupies only the top half).

The visual language

  • Right vs left limb — the one rule that never bends: the figure's right-side limbs are dark (#3a3f4b), its left-side limbs are light (#a9afba) and drawn behind the body. Working limbs keep the split: right = teal #0d9488, left = light teal #86cfc5. Opposite-limb moves (bird dog, dead bug) read as visibly opposite: one dark-teal limb, one light-teal limb. render.py reference renders embed a small R — / L — legend for the rig author; the in-app renderer deliberately omits it — the labels are only anatomically true for right-facing figures, and the contrast alone carries the meaning.
  • Facing / front-of-torso — the head carries a nose tick (gaze angle); the belly is on that side. Prone noses point at the floor, supine at the ceiling. The head is drawn last, filled opaque, so overhead arms pass behind the face.
  • Spine — rendered as a smooth curve through pelvis → mid → neck; teal when the trunk is the working part.
  • Canvas 320×180, ground line at y = 152. Limbs listed in hide are fully occluded in this view and not drawn.

Rendering

cd "Exercise Library"
python3 render.py                 # all exercises: frames/*.svg, preview.gif, visual.svg
python3 render.py "Bird Dog"      # one exercise
python3 render.py --sheet         # + contact-sheet.png of every key frame
python3 render.py --demo          # + demo-sheet.png: profile / flip / theme variants
python3 render.py --figure=female # render with another body profile
python3 render.py --flip          # mirror the figure (faces the other way)
python3 render.py --export        # copy body.json + <Name>.motion.json + <Name>.info.md app resources

render.py needs only Pillow (for GIFs/sheets; the SVGs have no dependency). The library lives at the repo root, outside every target's source folders — same-named files per entry (info.md, visual.svg) would collide in Xcode's flat resource copy, so the library itself never enters the app bundle. Only the --export copies ship: body.json plus uniquely-named <Name>.motion.json and <Name>.info.md files in Workouts/Resources/ExerciseMotions/, consumed by the in-app SwiftUI renderer (Workouts/ExerciseFigure/) and the exercise-library reference screen (ExerciseInfo.swift parses the info pages). Re-run python3 render.py --export after editing any motion or info page; the library stays the source of truth.