Fix visualization reshape error with descriptive error messages and v…

…alidation (#3047)
AlexEMG · Jul 6, 2025 · Jul 1, 2025 · Jul 1, 2025 · Jul 1, 2025 · Jul 1, 2025
commit 2dbeea68b8a0cea05d7b42317850698b367a17a0
diff --git a/deeplabcut/utils/visualization.py b/deeplabcut/utils/visualization.py
@@ -34,6 +34,37 @@
 from deeplabcut.utils import auxiliaryfunctions, auxfun_videos
 
 
+def safe_reshape(array: np.ndarray, shape: tuple, context: str = "") -> np.ndarray:
+    """
+    Safely reshape an array with validation and descriptive error messages.
+
+    Args:
+        array: The numpy array to reshape
+        shape: The target shape for reshaping  
+        context: Optional context string to include in error messages
+
+    Returns:
+        The reshaped array
+
+    Raises:
+        ValueError: If the array cannot be reshaped to the target shape with
+                   a descriptive error message
+    """
+    expected_size = np.prod(shape)
+    actual_size = array.size
+
+    if actual_size != expected_size:
+        context_str = f" for {context}" if context else ""
+        raise ValueError(
+            f"Cannot reshape array of size {actual_size} into shape {shape}{context_str}. "
+            f"Expected {expected_size} elements but got {actual_size}. "
+            f"This may indicate missing data or inconsistent data structure. "
+            f"Please verify that all expected individuals, bodyparts, and coordinates are present in the data."
+        )
+
+    return array.reshape(shape)
+
+
 def get_cmap(n: int, name: str = "hsv") -> Colormap:
     """
     Args:
@@ -514,8 +545,16 @@ def plot_evaluation_results(
         df_predictions = row_multi[model_name]
 
         # Shape (num_individuals, num_bodyparts, xy)
-        ground_truth = df_gt.to_numpy().reshape((individuals, bodyparts, 2))
-        predictions = df_predictions.to_numpy().reshape((individuals, bodyparts, 3))
+        ground_truth = safe_reshape(
+            df_gt.to_numpy(), 
+            (individuals, bodyparts, 2),
+            f"ground truth data with {individuals} individuals and {bodyparts} bodyparts"
+        )
+        predictions = safe_reshape(
+            df_predictions.to_numpy(), 
+            (individuals, bodyparts, 3),
+            f"prediction data with {individuals} individuals and {bodyparts} bodyparts"
+        )
 
         bboxes = bounding_boxes.get(row_index)
 
@@ -527,15 +566,15 @@ def plot_evaluation_results(
             unique_bodyparts = len(
                 row_unique.index.get_level_values("bodyparts").unique()
             )
-            unique_ground_truth = (
-                row_unique[scorer]
-                .to_numpy()
-                .reshape((unique_individuals, unique_bodyparts, 2))
+            unique_ground_truth = safe_reshape(
+                row_unique[scorer].to_numpy(),
+                (unique_individuals, unique_bodyparts, 2),
+                f"unique ground truth data with {unique_individuals} individuals and {unique_bodyparts} bodyparts"
             )
-            unique_predictions = (
-                row_unique[model_name]
-                .to_numpy()
-                .reshape((unique_individuals, unique_bodyparts, 3))
+            unique_predictions = safe_reshape(
+                row_unique[model_name].to_numpy(),
+                (unique_individuals, unique_bodyparts, 3),
+                f"unique prediction data with {unique_individuals} individuals and {unique_bodyparts} bodyparts"
             )
 
         fig, ax = create_minimal_figure()

diff --git a/tests/test_visualization.py b/tests/test_visualization.py
@@ -0,0 +1,127 @@
+#
+# DeepLabCut Toolbox (deeplabcut.org)
+# © A. & M.W. Mathis Labs
+# https://github.com/DeepLabCut/DeepLabCut
+#
+# Please see AUTHORS for contributors.
+# https://github.com/DeepLabCut/DeepLabCut/blob/master/AUTHORS
+#
+# Licensed under GNU Lesser General Public License v3.0
+#
+
+import numpy as np
+import pytest
+from deeplabcut.utils.visualization import safe_reshape
+
+
+class TestSafeReshape:
+    """Test cases for the safe_reshape function."""
+
+    def test_valid_reshape(self):
+        """Test that valid reshapes work correctly."""
+        array = np.array([1, 2, 3, 4, 5, 6, 7, 8])
+        result = safe_reshape(array, (2, 2, 2))
+        expected = array.reshape((2, 2, 2))
+        np.testing.assert_array_equal(result, expected)
+
+    def test_valid_reshape_with_context(self):
+        """Test that valid reshapes work correctly with context."""
+        array = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
+        result = safe_reshape(array, (2, 2, 3), "test context")
+        expected = array.reshape((2, 2, 3))
+        np.testing.assert_array_equal(result, expected)
+
+    def test_invalid_reshape_too_small(self):
+        """Test that reshape with too few elements raises proper error."""
+        array = np.array([1, 2, 3, 4])  # 4 elements
+        with pytest.raises(ValueError) as exc_info:
+            safe_reshape(array, (2, 2, 2))  # Expects 8 elements
+
+        error_msg = str(exc_info.value)
+        assert "Cannot reshape array of size 4 into shape (2, 2, 2)" in error_msg
+        assert "Expected 8 elements but got 4" in error_msg
+        assert "missing data or inconsistent data structure" in error_msg
+
+    def test_invalid_reshape_too_large(self):
+        """Test that reshape with too many elements raises proper error."""
+        array = np.array(range(20))  # 20 elements
+        with pytest.raises(ValueError) as exc_info:
+            safe_reshape(array, (2, 2, 2))  # Expects 8 elements
+
+        error_msg = str(exc_info.value)
+        assert "Cannot reshape array of size 20 into shape (2, 2, 2)" in error_msg
+        assert "Expected 8 elements but got 20" in error_msg
+
+    def test_invalid_reshape_with_context(self):
+        """Test that reshape errors include context when provided."""
+        array = np.array([1, 2, 3, 4])
+        context = "ground truth data with 2 individuals and 2 bodyparts"
+
+        with pytest.raises(ValueError) as exc_info:
+            safe_reshape(array, (2, 2, 2), context)
+
+        error_msg = str(exc_info.value)
+        assert f"for {context}" in error_msg
+        assert "Cannot reshape array of size 4 into shape (2, 2, 2)" in error_msg
+
+    def test_empty_array(self):
+        """Test that empty arrays are handled correctly."""
+        array = np.array([])
+        with pytest.raises(ValueError) as exc_info:
+            safe_reshape(array, (1, 1), "empty array")
+
+        error_msg = str(exc_info.value)
+        assert "Cannot reshape array of size 0 into shape (1, 1)" in error_msg
+
+    def test_original_error_scenario(self):
+        """Test the specific error scenario from the issue."""
+        # This reproduces the exact error: "cannot reshape array of size 8 into shape (2,4,2)"
+        array = np.array([1, 2, 3, 4, 5, 6, 7, 8])  # 8 elements
+        with pytest.raises(ValueError) as exc_info:
+            safe_reshape(array, (2, 4, 2))  # Expects 16 elements
+
+        error_msg = str(exc_info.value)
+        assert "Cannot reshape array of size 8 into shape (2, 4, 2)" in error_msg
+        assert "Expected 16 elements but got 8" in error_msg
+
+    def test_single_dimension(self):
+        """Test reshaping to single dimension."""
+        array = np.array([[1, 2], [3, 4]])
+        result = safe_reshape(array, (4,))
+        expected = array.reshape((4,))
+        np.testing.assert_array_equal(result, expected)
+
+    def test_multidimensional_input(self):
+        """Test reshaping multidimensional input arrays."""
+        array = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])  # 2x2x2 = 8 elements
+        result = safe_reshape(array, (4, 2))
+        expected = array.reshape((4, 2))
+        np.testing.assert_array_equal(result, expected)
+
+    @pytest.mark.parametrize("shape", [
+        (2, 2, 2),
+        (1, 8, 1),
+        (4, 2),
+        (8,),
+    ])
+    def test_various_valid_shapes(self, shape):
+        """Test various valid reshape operations."""
+        array = np.arange(8)
+        result = safe_reshape(array, shape)
+        expected = array.reshape(shape)
+        np.testing.assert_array_equal(result, expected)
+
+    @pytest.mark.parametrize("array_size,shape", [
+        (6, (2, 2, 2)),  # 6 elements into 8-element shape
+        (10, (2, 2, 2)),  # 10 elements into 8-element shape 
+        (4, (3, 3)),  # 4 elements into 9-element shape
+        (0, (2, 2)),  # empty array into non-empty shape
+    ])
+    def test_various_invalid_shapes(self, array_size, shape):
+        """Test various invalid reshape operations."""
+        array = np.arange(array_size)
+        with pytest.raises(ValueError) as exc_info:
+            safe_reshape(array, shape)
+
+        error_msg = str(exc_info.value)
+        assert f"Cannot reshape array of size {array_size} into shape {shape}" in error_msg