fix(#1): fix precision loss in conversion

Also update .gitignore

.gitignore

@@ -1,3 +1,5 @@
 #survey content
 /surveys/*
 /output_las/*
+.DS_Store
+.venv

lasConverter.py

@@ -25,36 +25,12 @@ def CSV_2_LAS(surveys_folders, output_folder, output_name="merged_final1.las", c
     dir_to_id = {name: i+1 for i, name in enumerate(top_dirs)}
     pd.DataFrame(list(dir_to_id.items()), columns=["top_dir","id"]).to_csv(output_folder / "dir_mapping.csv", index=False)
 
-    # Create LAS header template
-    header = laspy.LasHeader(point_format=6, version="1.4")
-    header.scales = (1, 1, 1)
-    header.offsets = (0, 0, 0)
-
-    # Add extra dimensions
-    header.add_extra_dim(laspy.ExtraBytesParams(name="accepted", type=np.uint8))
-    header.add_extra_dim(laspy.ExtraBytesParams(name="TVU", type=np.float32))
-    header.add_extra_dim(laspy.ExtraBytesParams(name="THU", type=np.float32))
-
     temp_folder = output_folder / "tmp"
     temp_folder.mkdir(exist_ok=True)
 
     # Step 1: Write chunked LAS files
     print("Step 1: Writing LAS chunks...")
     file_counter = 1
-    points_in_file = 0
-    writer = None
-
-    def open_new_chunk_file():
-        nonlocal file_counter, points_in_file, writer
-        if writer:
-            writer.close()
-        las_path = temp_folder / f"{output_name}_chunk_{file_counter}.las"
-        writer = laspy.open(str(las_path), mode="w", header=header)
-        print(f"Writing chunk: {las_path}")
-        points_in_file = 0
-        file_counter += 1
-
-    open_new_chunk_file()
 
     for f in csv_files:
         top_dir_id = dir_to_id[f.relative_to(surveys_path).parts[0]]
@@ -79,29 +55,29 @@ def open_new_chunk_file():
             thu = df.iloc[:, 5].to_numpy(dtype=np.float32)
             ids = np.full(len(df), top_dir_id, dtype=np.uint16)
 
-            points = laspy.ScaleAwarePointRecord.zeros(len(df), header=header)
-            points.X = x
-            points.Y = y
-            points.Z = z
-            points.point_source_id = ids
-            points["accepted"] = accepted
-            points["TVU"] = tvu
-            points["THU"] = thu
-
-            # Split points into multiple LAS chunks if needed
-            start_idx = 0
-            while start_idx < len(points):
-                remaining_space = max_points_per_file - points_in_file
-                end_idx = start_idx + remaining_space
-                chunk = points[start_idx:end_idx]
-                writer.write_points(chunk)
-                points_in_file += len(chunk)
-                start_idx = end_idx
-                if points_in_file >= max_points_per_file:
-                    open_new_chunk_file()
-
-    if writer:
-        writer.close()
+             # Create LAS header template
+            header = laspy.LasHeader(point_format=6, version="1.4")
+
+            # Add extra dimensions
+            header.add_extra_dim(laspy.ExtraBytesParams(name="accepted", type=np.uint8))
+            header.add_extra_dim(laspy.ExtraBytesParams(name="TVU", type=np.float32))
+            header.add_extra_dim(laspy.ExtraBytesParams(name="THU", type=np.float32))
+
+            las = laspy.LasData(header)
+            las.x = x
+            las.y = y
+            las.z = z
+
+            # Add extra dimensions
+            las["accepted"] = accepted
+            las["TVU"] = tvu
+            las["THU"] = thu
+            las.point_source_id = ids
+
+            las_path = temp_folder / f"{output_name}_chunk_{file_counter}.las"
+            las.write(las_path)
+            print(f"✅ Wrote {las_path}")
+            file_counter += 1
 
     # Merging chunked LAS files into single LAS
     print("Step 2: Merging LAS chunks into final LAS...")