refactor: reorganize backend modules into sub-packages for models, data, visualization, wafer, and controllers

src/pygui/backend/visualization/rbf_heatmap.py

@@ -0,0 +1,61 @@
+"""RBF (thin-plate spline) heatmap field.
+
+Uses CuPy for GPU acceleration when available, falls back to NumPy + SciPy.
+"""
+from __future__ import annotations
+
+import numpy as np
+from scipy.interpolate import RBFInterpolator
+
+try:
+    import cupy as _cupy  # type: ignore
+    BACKEND = "cupy"
+except Exception:
+    _cupy = None
+    BACKEND = "numpy"
+
+_KERNEL = "thin_plate_spline"
+_SMOOTHING = 0.0
+
+
+def interpolate_field(
+    xs: np.ndarray,
+    ys: np.ndarray,
+    vs: np.ndarray,
+    *,
+    width: int,
+    height: int,
+    extent: tuple[float, float, float, float],  # (xmin, xmax, ymin, ymax) in mm
+    round_clip: bool = False,
+) -> np.ndarray:
+    """Return a (height, width) float64 array of interpolated values.
+
+    Args:
+        xs, ys:      sensor positions in mm (1-D arrays, length N)
+        vs:          sensor values (length N)
+        width/height: output grid dimensions in pixels
+        extent:      (xmin, xmax, ymin, ymax) in the same mm space as xs/ys
+        round_clip:  if True, pixels outside the inscribed ellipse become NaN
+    """
+    coords = np.column_stack([xs, ys])
+    rbf = RBFInterpolator(coords, vs, kernel=_KERNEL, smoothing=_SMOOTHING)
+
+    xmin, xmax, ymin, ymax = extent
+    gx = np.linspace(xmin, xmax, width)
+    gy = np.linspace(ymin, ymax, height)
+    grid_x, grid_y = np.meshgrid(gx, gy)
+    flat = np.column_stack([grid_x.ravel(), grid_y.ravel()])
+
+    # RBFInterpolator always runs on CPU; CuPy only accelerates other ops if added later
+    field = rbf(flat).reshape(height, width)
+
+    if round_clip:
+        cx = (xmin + xmax) / 2
+        cy = (ymin + ymax) / 2
+        rx = (xmax - xmin) / 2
+        ry = (ymax - ymin) / 2
+        dist = ((grid_x - cx) / rx) ** 2 + ((grid_y - cy) / ry) ** 2
+        field = np.where(dist <= 1.0, field, np.nan)
+
+    return field.astype(np.float64)
+