fix(python): validate dimensions in list_to_2d_float_array

PythonClient/airsim/tests/__init__.py

@@ -0,0 +1 @@
+# unit tests

PythonClient/airsim/tests/test_utils_reshape.py

@@ -0,0 +1,52 @@
+"""Offline tests for list_to_2d_float_array guards."""
+import importlib.util
+import os
+import sys
+import types as pytypes
+import unittest
+
+import numpy as np
+
+_HERE = os.path.dirname(os.path.abspath(__file__))
+_UTILS = os.path.join(os.path.dirname(_HERE), "utils.py")
+
+
+def _load_utils():
+    pkg = pytypes.ModuleType("airsim")
+    pkg.__path__ = [os.path.dirname(_HERE)]
+    sys.modules["airsim"] = pkg
+    stub = pytypes.ModuleType("airsim.types")
+    sys.modules["airsim.types"] = stub
+    uspec = importlib.util.spec_from_file_location("airsim.utils", _UTILS)
+    umod = importlib.util.module_from_spec(uspec)
+    sys.modules["airsim.utils"] = umod
+    uspec.loader.exec_module(umod)
+    return umod
+
+
+_u = _load_utils()
+
+
+class TestListTo2d(unittest.TestCase):
+    def test_happy_path(self):
+        out = _u.list_to_2d_float_array([1, 2, 3, 4], 2, 2)
+        self.assertEqual(out.shape, (2, 2))
+        self.assertEqual(out.dtype, np.float32)
+        self.assertAlmostEqual(float(out[0, 0]), 1.0)
+
+    def test_empty_zero_by_zero(self):
+        out = _u.list_to_2d_float_array([], 0, 0)
+        self.assertEqual(out.shape, (0, 0))
+
+    def test_length_mismatch(self):
+        with self.assertRaises(ValueError) as ctx:
+            _u.list_to_2d_float_array([1, 2, 3], 2, 2)
+        self.assertIn("flat length", str(ctx.exception))
+
+    def test_negative_dim(self):
+        with self.assertRaises(ValueError):
+            _u.list_to_2d_float_array([], -1, 1)
+
+
+if __name__ == "__main__":
+    unittest.main()

PythonClient/airsim/utils.py

@@ -18,7 +18,29 @@ def string_to_float_array(bstr):
     return np.fromstring(bstr, np.float32)
 
 def list_to_2d_float_array(flst, width, height):
-    return np.reshape(np.asarray(flst, np.float32), (height, width))
+    """Reshape a flat float list into a height x width float32 array.
+
+    Raises ValueError with a clear message when dimensions are invalid so
+    empty or truncated depth buffers fail closed instead of cascading
+    opaque numpy reshape errors.
+    """
+    try:
+        w = int(width)
+        h = int(height)
+    except (TypeError, ValueError) as exc:
+        raise ValueError("width and height must be integers") from exc
+    if w < 0 or h < 0:
+        raise ValueError("width and height must be non-negative, got width=%r height=%r" % (w, h))
+    arr = np.asarray(flst, np.float32).reshape(-1)
+    expected = w * h
+    if arr.size != expected:
+        raise ValueError(
+            "flat length %d does not match width*height (%d*%d=%d)"
+            % (arr.size, w, h, expected)
+        )
+    if expected == 0:
+        return np.zeros((h, w), dtype=np.float32)
+    return np.reshape(arr, (h, w))
 
 def get_pfm_array(response):
     return list_to_2d_float_array(response.image_data_float, response.width, response.height)