[BUG]: Automargin for quiver plots is a little off with `arrowref: 'paper'`

Desired behavior

Quiver automargin should always result in an initial plot area which contains all arrow endpoints.

Current behavior

The current quiver implementation calculates the arrow endpoints assuming arrowref: 'data', uses those endpoints to compute the automargin extents, and then if arrowref is 'paper'`, applies an adjustment factor to the arrow endpoints.

If the x:y aspect ratio of the data is pretty close to 1:1, this works OK because the arrow endpoints don't change much. But if the aspect ratio of the data is very far from 1:1, this can result in an initial plot where the arrow endpoints extend outside of the plotted area.

Example

{
  "data": [
    {
      "type": "quiver",
      "uhoverformat": ".3f",
      "yhoverformat": ".3f",
      "xhoverfomrat": ".3f",
      "vhoverformat": ".3f",
      "x": [0],
      "y": [0],
      "u": [1],
      "v": [0.1],
      "arrowref": "paper"
    }
  ],
  "layout": {
    "width": 800,
    "height": 600,
    "showlegend": false
  }
}

Screenshot:

Notice how the tip of the arrow extends off the right side of the plot.

Fix

The relevant logic is around lines 200-206 in src/traces/quiver/calc.js.

It's a bit of a chicken-and-egg problem, because when arrowref is 'paper', the data position of the arrow endpoints depends on the axis scales, which depend on the position of the arrow endpoints. I think there is probably an algebraic solution but haven't quite been able to figure it out. Alternatively there's probably an iterative or approximate approach we could apply here that would still be an improvement over the current behavior.

Inizia in src/traces/quiver/calc.js intorno alle righe 200-206 e riproduci la figura quiver fornita con arrowref impostato su paper. Traccia il modo in cui vengono calcolati gli estremi delle frecce e le estensioni di automargin rispetto alle scale degli assi. Il lavoro è completato quando l'area iniziale del grafico contiene tutti gli estremi delle frecce, anche quando le proporzioni dei dati differiscono sostanzialmente da 1:1.