有3d gcode预览，基本能按要求切片，但是缩放后切片会失败

tmp/test_simplifier.py

@@ -1,35 +1,21 @@
+import time
 import numpy as np
 from stl import mesh
 
-def simplify_stl_grid(input_path, output_path, target_ratio=0.1):
-    m = mesh.Mesh.from_file(input_path)
-    vertices = m.vectors.reshape(-1, 3)
-    
-    min_v = vertices.min(axis=0)
-    max_v = vertices.max(axis=0)
-    bbox_size = max_v - min_v
-    max_dim = np.max(bbox_size)
-    
-    # Adjust resolution to rough target_ratio by guessing. 
-    # The number of vertices drops roughly by (resolution_factor)^2.
-    # So if we want 10% faces, resolution_factor can be heuristically set.
-    # Let's try 0.05
-    grid_size = max_dim * 0.05
-    
-    v_idx = np.round((vertices - min_v) / grid_size).astype(np.int32)
-    _, unique_idx, inv_idx = np.unique(v_idx, axis=0, return_index=True, return_inverse=True)
-    
-    new_vertices = vertices[unique_idx]
-    faces = inv_idx.reshape(-1, 3)
-    
-    valid = (faces[:,0] != faces[:,1]) & (faces[:,1] != faces[:,2]) & (faces[:,0] != faces[:,2])
-    valid_faces = faces[valid]
-    
-    new_m = mesh.Mesh(np.zeros(valid_faces.shape[0], dtype=mesh.Mesh.dtype))
-    for i, f in enumerate(valid_faces):
-        for j in range(3):
-            new_m.vectors[i][j] = new_vertices[f[j]]
-    
-    new_m.update_normals()
-    new_m.save(output_path)
+# create a dummy huge point cloud
+vertices = np.random.rand(1000000, 3) * 100
+min_v = vertices.min(axis=0)
+g_size = 2.0
 
+v_idx = np.round((vertices - min_v) / g_size).astype(np.int32)
+
+t0 = time.time()
+_, unique_idx, inv_idx = np.unique(v_idx, axis=0, return_index=True, return_inverse=True)
+print("axis=0 time:", time.time() - t0)
+
+v_idx = v_idx.astype(np.int64)
+t0 = time.time()
+max_idx = v_idx.max(axis=0) + 1
+v_1d = v_idx[:, 0] + v_idx[:, 1] * max_idx[0] + v_idx[:, 2] * max_idx[0] * max_idx[1]
+_, unique_idx, inv_idx = np.unique(v_1d, return_index=True, return_inverse=True)
+print("1D hash time:", time.time() - t0)