Merge pull request #18 from den-sq/main

Revise Volume Writing

Addresses outstanding border artifact transposition issues, reduces memory usage somewhat.

Author: den-sq

.coverage

@@ -0,0 +1,3 @@
+[run]
+omit = *test*
+omit = *temp*

.coveragerc

@@ -1,9 +1,11 @@
 import os
 from pathlib import Path
-from tifffile import imread, TiffWriter
+from tifffile import imread, TiffWriter, memmap
 from .memory_usage import calculate_gigabytes_from_dimensions
 import shutil
 
+import numpy as np
+
 
 def load_and_save_tiff_from_slices(
     folder_name: str,
@@ -180,3 +182,36 @@ def parse_tiff_name(tiff_name: str) -> int:
 
 def num_digits_for_n_files(n: int) -> int:
     return len(str(n - 1))
+
+
+def write_memmap_with_create(file_path: os.PathLike, indicies: tuple[np.ndarray], data: np.ndarray,
+                             shape: tuple, dtype: type):
+    if file_path.exists():
+        try:
+            target_file = memmap(file_path)
+        except BaseException as be:
+            print(f"MM: {be} - {file_path} ")
+            import time
+            time.sleep(0.5)
+            target_file = memmap(file_path)
+    else:
+        if shape is None or dtype is None:
+            raise ValueError(f"Must have shape ({shape} given) and dtype ({dtype} given) when creating a memmap.")
+        target_file = memmap(file_path, shape=shape, dtype=dtype)
+        target_file[:] = 0
+
+    def ab(flags: np.ndarray[bool], index):
+        return tuple(dim[flags] for dim in index) if isinstance(index, tuple) else index[flags]
+
+    if indicies is not None and data is not None:
+        exist = target_file[indicies] != 0
+        if np.any(exist):
+            target_file[ab(exist, indicies)] = np.mean([target_file[indicies][exist], data[exist]],
+                                                       axis=0, dtype=target_file.dtype)
+            target_file[ab(np.invert(exist), indicies)] = data[np.invert(exist)]
+        else:
+            target_file[indicies] = data
+    elif indicies is not None or data is not None:
+        raise ValueError(f"Could not write data as indicies (None? {indicies is None})"
+                         f"or data (None? {data is None}) were missing.")
+    del target_file

python/coverage.svg

@@ -164,8 +164,7 @@ def slice_volume_from_grids(
         return slice_points.reshape(len(grids), height, width)
 
 
-def backproject_slices(bounding_box: BoundingBox, slice_rects: np.ndarray, slices: np.ndarray,
-                       volume: np.ndarray = None) -> tuple[np.ndarray]:
+def backproject_slices(bounding_box: BoundingBox, slice_rects: np.ndarray, slices: np.ndarray) -> tuple[np.ndarray]:
     """
     Write a slice to volume based on a grid of coordinates.  Returns coordinates.
 
@@ -185,7 +184,7 @@ def backproject_slices(bounding_box: BoundingBox, slice_rects: np.ndarray, slice
     """
     if slices.shape[0] == 0:
         # No slices, just return
-        return np.empty(0, dtype=np.uint16), np.empty(0, dtype=np.float32), np.empty(0, dtype=np.float32)
+        return np.empty((3, 0), dtype=np.uint16), np.empty(0, dtype=np.float32), np.empty(0, dtype=np.float32)
 
     # Normalize grid coordinates based on bounding box (since volume coordinates are truncated to bounding box)
     grid_call = partial(coordinate_grid, shape=slices[0].shape, floor=bounding_box.get_min())
@@ -224,10 +223,6 @@ def corner_weights(w, c):
     bordered_values = np.logical_and.reduce(np.less(net_lookup, bounding_box.get_max().reshape(3, 1)))
     set_values = np.logical_and((net_point_weights != 0), bordered_values)
 
-    if volume is not None:
-        volume[(net_lookup[0, set_values], net_lookup[1, set_values], net_lookup[2, set_values])] = \
-            (net_point_totals[set_values] / net_point_weights[set_values])[:, np.newaxis]
-
     return net_lookup[:, set_values], net_point_totals[set_values], net_point_weights[set_values]