From 1f0521dfc7a8dd1e951b86d7ccdbee125a2ff5dc Mon Sep 17 00:00:00 2001
From: iosefa <ipercival@gmail.com>
Date: Wed, 14 Oct 2026 16:12:38 -1000
Subject: [PATCH] Prepare v0.5.0 release

---
 MANIFEST.in               |  2 ++
 pyforestscan/calculate.py | 10 +++++-----
 setup.py                  |  5 +++--
 3 files changed, 10 insertions(+), 7 deletions(-)
 create mode 100644 MANIFEST.in

diff --git a/MANIFEST.in b/MANIFEST.in
new file mode 100644
index 0000000..0994779
--- /dev/null
+++ b/MANIFEST.in
@@ -0,0 +1,2 @@
+include pytest.ini
+recursive-include tests *.py *.json *.R
diff --git a/pyforestscan/calculate.py b/pyforestscan/calculate.py
index 2baf652..2dddd5d 100644
--- a/pyforestscan/calculate.py
+++ b/pyforestscan/calculate.py
@@ -327,7 +327,7 @@ def calculate_voxel_stat(
     dimension: str,
     stat: str,
     z_index_range: Optional[Tuple[int, Optional[int]]] = None,
-):
+) -> Tuple[np.ndarray, List[float]]:
     """
     Compute a column-wise statistic for a given dimension over a 3-D voxel grid.
 
@@ -350,10 +350,10 @@ def calculate_voxel_stat(
             the first three voxels (indices 0, 1, 2).
 
     Returns:
-        tuple[np.ndarray, list]: (stat_array, extent)
-            - stat_array: 2-D array shaped (nx, ny) with the requested statistic per column.
-              Cells without points are NaN (except for 'count', which yields 0).
-            - extent: [x_min, x_max, y_min, y_max] covering the raster footprint.
+        tuple[np.ndarray, list]: The statistic array and raster extent. The array
+            has shape (nx, ny), with the requested statistic per column. Cells
+            without points are NaN, except for 'count', which yields 0. The
+            extent is [x_min, x_max, y_min, y_max], covering the raster footprint.
     """
     if dimension not in arr.dtype.names:
         raise KeyError(f"Dimension '{dimension}' not found in array fields")
diff --git a/setup.py b/setup.py
index 575a1ba..fdf0ef1 100644
--- a/setup.py
+++ b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="pyforestscan",
-    version="0.4.1",
+    version="0.5.0",
     author="Joseph Emile Honour Percival",
     author_email="ipercival@gmail.com",
     description="Analyzing forest structure using aerial LiDAR data",
@@ -20,7 +20,7 @@
         "License :: OSI Approved :: MIT License",
         "Operating System :: OS Independent",
     ],
-    packages=setuptools.find_packages(),
+    packages=setuptools.find_packages(exclude=("tests", "tests.*")),
     python_requires=">=3.11",
     install_requires=[
         'requests>=2.32.4',
@@ -33,6 +33,7 @@
         'numpy>=2.3.1',
         'matplotlib>=3.10.3',
         'scipy>=1.16.0',
+        'tqdm>=4.67.1',
     ],
     extras_require={
         'dev': [