From d5f4fb16c965babd33c30be1155b90e44750acbd Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Thu, 12 Feb 2026 16:17:27 +0530
Subject: [PATCH 1/8] ENH: Add min_distance and distance_statistics functions
 for atom group analysis

---
 .gitignore                                    |   3 +
 package/MDAnalysis/analysis/distances.py      |  78 ++++++++++++
 .../analysis/test_distances.py                | 111 ++++++++++++++++++
 3 files changed, 192 insertions(+)

diff --git a/.gitignore b/.gitignore
index cf3cc8c87d0..e9ca72c0713 100644
--- a/.gitignore
+++ b/.gitignore
@@ -51,3 +51,6 @@ benchmarks/results
 .idea
 .vscode
 *.lock
+
+# virtual environments
+venv/
\ No newline at end of file
diff --git a/package/MDAnalysis/analysis/distances.py b/package/MDAnalysis/analysis/distances.py
index 44a09c4fcbd..32c741a7d87 100644
--- a/package/MDAnalysis/analysis/distances.py
+++ b/package/MDAnalysis/analysis/distances.py
@@ -44,6 +44,8 @@
     "contact_matrix",
     "dist",
     "between",
+    "min_distance",
+    "distance_statistics",
 ]
 
 import numpy as np
@@ -218,3 +220,79 @@ def between(group, A, B, distance):
     resA = ns_group.search(A, distance)
     resB = ns_group.search(B, distance)
     return resB.intersection(resA)
+
+
+def min_distance(A, B, box=None):
+    """Calculate the minimum distance between two atom groups.
+
+    This function computes the shortest distance between any atom in group A
+    and any atom in group B. Useful for protein-ligand analysis, membrane-protein
+    distances, or identifying close contacts between molecular regions.
+
+    Parameters
+    ----------
+    A : AtomGroup
+        First atom group
+    B : AtomGroup
+        Second atom group
+    box : array_like, optional
+        Simulation cell dimensions for periodic boundary conditions in the form
+        ``[lx, ly, lz, alpha, beta, gamma]``. If provided, minimum image
+        convention is applied.
+
+    Returns
+    -------
+    float
+        Minimum distance between any atom in A and any atom in B (in Angstroms)
+
+    .. versionadded:: 2.8.0
+    """
+    distances = distance_array(A.positions, B.positions, box=box)
+    return np.min(distances)
+
+
+def distance_statistics(A, B, box=None):
+    """Calculate statistical measures of distances between two atom groups.
+
+    Computes minimum, maximum, mean, and standard deviation of all pairwise
+    distances between atoms in groups A and B. Useful for characterizing
+    the overall separation and distribution of distances between molecular regions.
+
+    Parameters
+    ----------
+    A : AtomGroup
+        First atom group
+    B : AtomGroup
+        Second atom group
+    box : array_like, optional
+        Simulation cell dimensions for periodic boundary conditions in the form
+        ``[lx, ly, lz, alpha, beta, gamma]``. If provided, minimum image
+        convention is applied.
+
+    Returns
+    -------
+    dict
+        Dictionary containing:
+        
+        - 'min' : float
+            Minimum distance
+        - 'max' : float
+            Maximum distance
+        - 'mean' : float
+            Mean of all pairwise distances
+        - 'std' : float
+            Standard deviation of distances
+        - 'n_distances' : int
+            Total number of pairwise distances calculated
+
+    .. versionadded:: 2.8.0
+    """
+    distances = distance_array(A.positions, B.positions, box=box)
+    
+    return {
+        'min': float(np.min(distances)),
+        'max': float(np.max(distances)),
+        'mean': float(np.mean(distances)),
+        'std': float(np.std(distances)),
+        'n_distances': distances.size
+    }
diff --git a/testsuite/MDAnalysisTests/analysis/test_distances.py b/testsuite/MDAnalysisTests/analysis/test_distances.py
index 60c362d5cd6..c17ae46bffe 100644
--- a/testsuite/MDAnalysisTests/analysis/test_distances.py
+++ b/testsuite/MDAnalysisTests/analysis/test_distances.py
@@ -247,3 +247,114 @@ def test_between_return_type(self, dists, group, ag, ag2):
         returns an AtomGroup even when the returned group is empty."""
         actual = MDAnalysis.analysis.distances.between(group, ag, ag2, dists)
         assert isinstance(actual, MDAnalysis.core.groups.AtomGroup)
+
+class TestMinDistance(object):
+    @staticmethod
+    @pytest.fixture()
+    def u():
+        return MDAnalysis.Universe(GRO)
+
+    @staticmethod
+    @pytest.fixture()
+    def ag(u):
+        return u.atoms[:10]
+
+    @staticmethod
+    @pytest.fixture()
+    def ag2(u):
+        return u.atoms[12:33]
+
+    @staticmethod
+    @pytest.fixture()
+    def box():
+        return np.array([8, 8, 8, 90, 90, 90], dtype=np.float32)
+
+    @pytest.fixture()
+    def expected(self, ag, ag2):
+        distance_matrix = scipy.spatial.distance.cdist(ag.positions, ag2.positions)
+        return np.min(distance_matrix)
+
+    def test_min_distance_simple_case(self, ag, ag2, expected):
+        """Test MDAnalysis.analysis.distances.min_distance() for
+        a simple input case. Checks returned minimum distance
+        against expected value."""
+        actual = MDAnalysis.analysis.distances.min_distance(ag, ag2)
+        assert_allclose(actual, expected)
+
+    def test_min_distance_return_type(self, ag, ag2):
+        """Test that MDAnalysis.analysis.distances.min_distance()
+        returns a float."""
+        actual = MDAnalysis.analysis.distances.min_distance(ag, ag2)
+        assert isinstance(actual, float)
+
+    def test_min_distance_box(self, ag, ag2, box):
+        """Test that MDAnalysis.analysis.distances.min_distance()
+        correctly accounts for periodic boundary conditions."""
+        actual = MDAnalysis.analysis.distances.min_distance(ag, ag2, box=box)
+        assert isinstance(actual, float)
+        assert actual >= 0.0
+
+    def test_min_distance_identical_groups(self, ag):
+        """Test that min_distance() returns 0 when the two AtomGroups are identical."""
+        actual = MDAnalysis.analysis.distances.min_distance(ag, ag)
+        assert_allclose(actual, 0.0)
+
+    def test_min_distance_single_atom_groups(self, u):
+        """Test that min_distance() returns the correct distance when both AtomGroups contain a single atom."""
+        ag1 = u.atoms[0:1]
+        ag2 = u.atoms[1:2]
+        expected = np.linalg.norm(ag1.positions - ag2.positions)
+        actual = MDAnalysis.analysis.distances.min_distance(ag1, ag2)
+        assert_allclose(actual, expected)
+
+class TestDistanceStatistics(object):
+    @staticmethod
+    @pytest.fixture()
+    def u():
+        return MDAnalysis.Universe(GRO)
+
+    @staticmethod
+    @pytest.fixture()
+    def ag(u):
+        return u.atoms[:10]
+
+    @staticmethod
+    @pytest.fixture()
+    def ag2(u):
+        return u.atoms[12:33]
+
+    @staticmethod
+    @pytest.fixture()
+    def box():
+        return np.array([8, 8, 8, 90, 90, 90], dtype=np.float32)
+
+    @pytest.fixture()
+    def expected(self, ag, ag2):
+        distance_matrix = scipy.spatial.distance.cdist(ag.positions, ag2.positions)
+        return {
+            'min': np.min(distance_matrix),
+            'max': np.max(distance_matrix),
+            'mean': np.mean(distance_matrix),
+            'std': np.std(distance_matrix)
+        }
+
+    def test_distance_statistics_simple_case(self, ag, ag2, expected):
+        """Test MDAnalysis.analysis.distances.distance_statistics() for
+        a simple input case. Checks returned distance statistics
+        against expected values."""
+        actual = MDAnalysis.analysis.distances.distance_statistics(ag, ag2)
+        for key in expected:
+            assert_allclose(actual[key], expected[key])
+
+    def test_distance_statistics_return_type(self, ag, ag2):
+        """Test that MDAnalysis.analysis.distances.distance_statistics()
+        returns a dictionary."""
+        actual = MDAnalysis.analysis.distances.distance_statistics(ag, ag2)
+        assert isinstance(actual, dict)
+
+    def test_distance_statistics_box(self, ag, ag2, box):
+        """Test that MDAnalysis.analysis.distances.distance_statistics()
+        works correctly when a box is provided."""
+        actual = MDAnalysis.analysis.distances.distance_statistics(ag, ag2, box=box)
+        assert isinstance(actual, dict)
+        assert all(key in actual for key in ['min', 'max', 'mean', 'std'])

From 4df0aefee3e647c37dffa8ec24ee2ab825c69cf8 Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Thu, 12 Feb 2026 16:24:50 +0530
Subject: [PATCH 2/8] ENH: Add Suriya Sureshkumar to the list of authors

---
 package/AUTHORS | 1 +
 1 file changed, 1 insertion(+)

diff --git a/package/AUTHORS b/package/AUTHORS
index 973f1dd7943..38090a93346 100644
--- a/package/AUTHORS
+++ b/package/AUTHORS
@@ -270,6 +270,7 @@ Chronological list of authors
 2026
   - Mohammad Ayaan
   - Khushi Phougat
+  - Suriya Sureshkumar
   
 External code
 -------------

From a7fdba7b71a672b8df56605e39f5a0dbbb5b5ebd Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Thu, 12 Feb 2026 17:04:24 +0530
Subject: [PATCH 3/8] ENH: Clean up formatting in distance_statistics function

---
 package/MDAnalysis/analysis/distances.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/package/MDAnalysis/analysis/distances.py b/package/MDAnalysis/analysis/distances.py
index 32c741a7d87..9c78176ed6c 100644
--- a/package/MDAnalysis/analysis/distances.py
+++ b/package/MDAnalysis/analysis/distances.py
@@ -273,7 +273,7 @@ def distance_statistics(A, B, box=None):
     -------
     dict
         Dictionary containing:
-        
+
         - 'min' : float
             Minimum distance
         - 'max' : float
@@ -288,11 +288,11 @@ def distance_statistics(A, B, box=None):
     .. versionadded:: 2.8.0
     """
     distances = distance_array(A.positions, B.positions, box=box)
-    
+
     return {
-        'min': float(np.min(distances)),
-        'max': float(np.max(distances)),
-        'mean': float(np.mean(distances)),
-        'std': float(np.std(distances)),
-        'n_distances': distances.size
+        "min": float(np.min(distances)),
+        "max": float(np.max(distances)),
+        "mean": float(np.mean(distances)),
+        "std": float(np.std(distances)),
+        "n_distances": distances.size,
     }

From 467fb6e9c4d680d369b51e252be749d31ef96734 Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Fri, 13 Feb 2026 07:31:05 +0530
Subject: [PATCH 4/8] ENH: Fix GSDReader TypeError when indexing with NumPy
 scalar integers; add test for GSDReader numpy int indexing

---
 package/MDAnalysis/analysis/distances.py      |  76 ------------
 package/MDAnalysis/coordinates/GSD.py         |   3 +
 .../analysis/test_distances.py                | 111 ------------------
 .../MDAnalysisTests/coordinates/test_gsd.py   |  20 ++++
 4 files changed, 23 insertions(+), 187 deletions(-)

diff --git a/package/MDAnalysis/analysis/distances.py b/package/MDAnalysis/analysis/distances.py
index 9c78176ed6c..d3f5d95367b 100644
--- a/package/MDAnalysis/analysis/distances.py
+++ b/package/MDAnalysis/analysis/distances.py
@@ -220,79 +220,3 @@ def between(group, A, B, distance):
     resA = ns_group.search(A, distance)
     resB = ns_group.search(B, distance)
     return resB.intersection(resA)
-
-
-def min_distance(A, B, box=None):
-    """Calculate the minimum distance between two atom groups.
-
-    This function computes the shortest distance between any atom in group A
-    and any atom in group B. Useful for protein-ligand analysis, membrane-protein
-    distances, or identifying close contacts between molecular regions.
-
-    Parameters
-    ----------
-    A : AtomGroup
-        First atom group
-    B : AtomGroup
-        Second atom group
-    box : array_like, optional
-        Simulation cell dimensions for periodic boundary conditions in the form
-        ``[lx, ly, lz, alpha, beta, gamma]``. If provided, minimum image
-        convention is applied.
-
-    Returns
-    -------
-    float
-        Minimum distance between any atom in A and any atom in B (in Angstroms)
-
-    .. versionadded:: 2.8.0
-    """
-    distances = distance_array(A.positions, B.positions, box=box)
-    return np.min(distances)
-
-
-def distance_statistics(A, B, box=None):
-    """Calculate statistical measures of distances between two atom groups.
-
-    Computes minimum, maximum, mean, and standard deviation of all pairwise
-    distances between atoms in groups A and B. Useful for characterizing
-    the overall separation and distribution of distances between molecular regions.
-
-    Parameters
-    ----------
-    A : AtomGroup
-        First atom group
-    B : AtomGroup
-        Second atom group
-    box : array_like, optional
-        Simulation cell dimensions for periodic boundary conditions in the form
-        ``[lx, ly, lz, alpha, beta, gamma]``. If provided, minimum image
-        convention is applied.
-
-    Returns
-    -------
-    dict
-        Dictionary containing:
-
-        - 'min' : float
-            Minimum distance
-        - 'max' : float
-            Maximum distance
-        - 'mean' : float
-            Mean of all pairwise distances
-        - 'std' : float
-            Standard deviation of distances
-        - 'n_distances' : int
-            Total number of pairwise distances calculated
-
-    .. versionadded:: 2.8.0
-    """
-    distances = distance_array(A.positions, B.positions, box=box)
-
-    return {
-        "min": float(np.min(distances)),
-        "max": float(np.max(distances)),
-        "mean": float(np.mean(distances)),
-        "std": float(np.std(distances)),
-        "n_distances": distances.size,
-    }
diff --git a/package/MDAnalysis/coordinates/GSD.py b/package/MDAnalysis/coordinates/GSD.py
index 8212037e929..8874df048ae 100644
--- a/package/MDAnalysis/coordinates/GSD.py
+++ b/package/MDAnalysis/coordinates/GSD.py
@@ -128,7 +128,10 @@ def _reopen(self):
         self.open_trajectory()
 
     def _read_frame(self, frame):
+        # Convert numpy integer types to Python int for gsd compatibility
+        # GSD's HOOMDTrajectory only accepts Python int, not np.int64
         try:
+            frame = int(frame)
             myframe = self._file[frame]
         except IndexError:
             raise IOError from None
diff --git a/testsuite/MDAnalysisTests/analysis/test_distances.py b/testsuite/MDAnalysisTests/analysis/test_distances.py
index c17ae46bffe..60c362d5cd6 100644
--- a/testsuite/MDAnalysisTests/analysis/test_distances.py
+++ b/testsuite/MDAnalysisTests/analysis/test_distances.py
@@ -247,114 +247,3 @@ def test_between_return_type(self, dists, group, ag, ag2):
         returns an AtomGroup even when the returned group is empty."""
         actual = MDAnalysis.analysis.distances.between(group, ag, ag2, dists)
         assert isinstance(actual, MDAnalysis.core.groups.AtomGroup)
-
-class TestMinDistance(object):
-    @staticmethod
-    @pytest.fixture()
-    def u():
-        return MDAnalysis.Universe(GRO)
-
-    @staticmethod
-    @pytest.fixture()
-    def ag(u):
-        return u.atoms[:10]
-
-    @staticmethod
-    @pytest.fixture()
-    def ag2(u):
-        return u.atoms[12:33]
-
-    @staticmethod
-    @pytest.fixture()
-    def box():
-        return np.array([8, 8, 8, 90, 90, 90], dtype=np.float32)
-
-    @pytest.fixture()
-    def expected(self, ag, ag2):
-        distance_matrix = scipy.spatial.distance.cdist(ag.positions, ag2.positions)
-        return np.min(distance_matrix)
-
-    def test_min_distance_simple_case(self, ag, ag2, expected):
-        """Test MDAnalysis.analysis.distances.min_distance() for
-        a simple input case. Checks returned minimum distance
-        against expected value."""
-        actual = MDAnalysis.analysis.distances.min_distance(ag, ag2)
-        assert_allclose(actual, expected)
-
-    def test_min_distance_return_type(self, ag, ag2):
-        """Test that MDAnalysis.analysis.distances.min_distance()
-        returns a float."""
-        actual = MDAnalysis.analysis.distances.min_distance(ag, ag2)
-        assert isinstance(actual, float)
-
-    def test_min_distance_box(self, ag, ag2, box):
-        """Test that MDAnalysis.analysis.distances.min_distance()
-        correctly accounts for periodic boundary conditions."""
-        actual = MDAnalysis.analysis.distances.min_distance(ag, ag2, box=box)
-        assert isinstance(actual, float)
-        assert actual >= 0.0
-
-    def test_min_distance_identical_groups(self, ag):
-        """Test that min_distance() returns 0 when the two AtomGroups are identical."""
-        actual = MDAnalysis.analysis.distances.min_distance(ag, ag)
-        assert_allclose(actual, 0.0)
-
-    def test_min_distance_single_atom_groups(self, u):
-        """Test that min_distance() returns the correct distance when both AtomGroups contain a single atom."""
-        ag1 = u.atoms[0:1]
-        ag2 = u.atoms[1:2]
-        expected = np.linalg.norm(ag1.positions - ag2.positions)
-        actual = MDAnalysis.analysis.distances.min_distance(ag1, ag2)
-        assert_allclose(actual, expected)
-
-class TestDistanceStatistics(object):
-    @staticmethod
-    @pytest.fixture()
-    def u():
-        return MDAnalysis.Universe(GRO)
-
-    @staticmethod
-    @pytest.fixture()
-    def ag(u):
-        return u.atoms[:10]
-
-    @staticmethod
-    @pytest.fixture()
-    def ag2(u):
-        return u.atoms[12:33]
-
-    @staticmethod
-    @pytest.fixture()
-    def box():
-        return np.array([8, 8, 8, 90, 90, 90], dtype=np.float32)
-
-    @pytest.fixture()
-    def expected(self, ag, ag2):
-        distance_matrix = scipy.spatial.distance.cdist(ag.positions, ag2.positions)
-        return {
-            'min': np.min(distance_matrix),
-            'max': np.max(distance_matrix),
-            'mean': np.mean(distance_matrix),
-            'std': np.std(distance_matrix)
-        }
-
-    def test_distance_statistics_simple_case(self, ag, ag2, expected):
-        """Test MDAnalysis.analysis.distances.distance_statistics() for
-        a simple input case. Checks returned distance statistics
-        against expected values."""
-        actual = MDAnalysis.analysis.distances.distance_statistics(ag, ag2)
-        for key in expected:
-            assert_allclose(actual[key], expected[key])
-
-    def test_distance_statistics_return_type(self, ag, ag2):
-        """Test that MDAnalysis.analysis.distances.distance_statistics()
-        returns a dictionary."""
-        actual = MDAnalysis.analysis.distances.distance_statistics(ag, ag2)
-        assert isinstance(actual, dict)
-
-    def test_distance_statistics_box(self, ag, ag2, box):
-        """Test that MDAnalysis.analysis.distances.distance_statistics()
-        works correctly when a box is provided."""
-        actual = MDAnalysis.analysis.distances.distance_statistics(ag, ag2, box=box)
-        assert isinstance(actual, dict)
-        assert all(key in actual for key in ['min', 'max', 'mean', 'std'])
diff --git a/testsuite/MDAnalysisTests/coordinates/test_gsd.py b/testsuite/MDAnalysisTests/coordinates/test_gsd.py
index 102b8391df9..88ede6a9ac6 100644
--- a/testsuite/MDAnalysisTests/coordinates/test_gsd.py
+++ b/testsuite/MDAnalysisTests/coordinates/test_gsd.py
@@ -22,6 +22,7 @@
 #
 import os
 
+import numpy as np
 import pytest
 from numpy.testing import assert_almost_equal
 
@@ -73,3 +74,22 @@ def test_gsd_dimensions(self, GSD_U):
     def test_gsd_data_step(self, GSD_U):
         assert GSD_U.trajectory[0].data["step"] == 0
         assert GSD_U.trajectory[1].data["step"] == 500
+
+    def test_gsd_numpy_int_indexing(self, GSD_U):
+        """Test that GSDReader accepts numpy integer types (Issue #5224).
+        
+        The parallelization framework generates frame indices as np.int64,
+        but GSD's HOOMDTrajectory only accepts Python int. This test ensures
+        the reader properly converts numpy scalar integers.
+        """
+        # Test with np.int64 (most common from numpy arrays)
+        ts = GSD_U.trajectory[np.int64(0)]
+        assert ts.frame == 0
+        
+        # Test with negative indexing
+        ts = GSD_U.trajectory[np.int64(-1)]
+        assert ts.frame == 1
+        
+        # Test with other numpy integer types
+        ts = GSD_U.trajectory[np.int32(1)]
+        assert ts.frame == 1

From 8a103bc78e44a4295e05309c1bc75c10f3d96e67 Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Fri, 13 Feb 2026 07:39:55 +0530
Subject: [PATCH 5/8] ENH: Remove min_distance and distance_statistics from the
 public API

---
 package/MDAnalysis/analysis/distances.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/package/MDAnalysis/analysis/distances.py b/package/MDAnalysis/analysis/distances.py
index d3f5d95367b..44a09c4fcbd 100644
--- a/package/MDAnalysis/analysis/distances.py
+++ b/package/MDAnalysis/analysis/distances.py
@@ -44,8 +44,6 @@
     "contact_matrix",
     "dist",
     "between",
-    "min_distance",
-    "distance_statistics",
 ]
 
 import numpy as np

From 7bb5e515557f1b8e9fd19bb8d2ccfae39ac891d7 Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Fri, 13 Feb 2026 10:29:43 +0530
Subject: [PATCH 6/8] ENH: Remove Windows-specific test for offset lock
 creation in XDR reader

---
 testsuite/MDAnalysisTests/coordinates/test_xdr.py | 7 -------
 1 file changed, 7 deletions(-)

diff --git a/testsuite/MDAnalysisTests/coordinates/test_xdr.py b/testsuite/MDAnalysisTests/coordinates/test_xdr.py
index 2a2f236924e..c245420a60d 100644
--- a/testsuite/MDAnalysisTests/coordinates/test_xdr.py
+++ b/testsuite/MDAnalysisTests/coordinates/test_xdr.py
@@ -1051,13 +1051,6 @@ def test_persistent_offsets_readonly(self, tmpdir, trajectory):
             False,
         )
 
-    @pytest.mark.skipif(
-        sys.platform.startswith("win"),
-        reason="The lock file only exists when it's locked in windows",
-    )
-    def test_offset_lock_created(self, traj):
-        assert os.path.exists(XDR.offsets_filename(traj, ending="lock"))
-
 
 class TestXTCReader_offsets(_GromacsReader_offsets):
     __test__ = True

From 80b3c0c2939ea363a2c7f6e52ec25b9b3fec4b65 Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Fri, 13 Feb 2026 15:05:12 +0530
Subject: [PATCH 7/8] Fix: Restored test_offset_lock_created()

---
 testsuite/MDAnalysisTests/coordinates/test_xdr.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/testsuite/MDAnalysisTests/coordinates/test_xdr.py b/testsuite/MDAnalysisTests/coordinates/test_xdr.py
index c245420a60d..7440fda1654 100644
--- a/testsuite/MDAnalysisTests/coordinates/test_xdr.py
+++ b/testsuite/MDAnalysisTests/coordinates/test_xdr.py
@@ -1051,6 +1051,12 @@ def test_persistent_offsets_readonly(self, tmpdir, trajectory):
             False,
         )
 
+    @pytest.mark.skipif(
+        sys.platform.startswith("win"),
+        reason="The lock file only exists when it's locked in windows",
+    )
+    def test_offset_lock_created(self, traj):
+        assert os.path.exists(XDR.offsets_filename(traj, ending="lock"))
 
 class TestXTCReader_offsets(_GromacsReader_offsets):
     __test__ = True

From 650785d63c0e9ca8360b4b7e2cbf7fd402982739 Mon Sep 17 00:00:00 2001
From: suriyasureshok <240171.ad@rmkec.ac.in>
Date: Fri, 13 Feb 2026 15:39:52 +0530
Subject: [PATCH 8/8] ENH: Remove virtual environment directory from .gitignore

---
 .gitignore                                        | 3 ---
 testsuite/MDAnalysisTests/coordinates/test_gsd.py | 7 +++++++
 2 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/.gitignore b/.gitignore
index e9ca72c0713..cf3cc8c87d0 100644
--- a/.gitignore
+++ b/.gitignore
@@ -51,6 +51,3 @@ benchmarks/results
 .idea
 .vscode
 *.lock
-
-# virtual environments
-venv/
\ No newline at end of file
diff --git a/testsuite/MDAnalysisTests/coordinates/test_gsd.py b/testsuite/MDAnalysisTests/coordinates/test_gsd.py
index 88ede6a9ac6..e5478550464 100644
--- a/testsuite/MDAnalysisTests/coordinates/test_gsd.py
+++ b/testsuite/MDAnalysisTests/coordinates/test_gsd.py
@@ -93,3 +93,10 @@ def test_gsd_numpy_int_indexing(self, GSD_U):
         # Test with other numpy integer types
         ts = GSD_U.trajectory[np.int32(1)]
         assert ts.frame == 1
+
+        # Directly test _read_frame with numpy integers to ensure coverage
+        ts = GSD_U.trajectory._read_frame(np.int64(0))
+        assert ts.frame == 0
+        
+        ts = GSD_U.trajectory._read_frame(np.int32(1))
+        assert ts.frame == 1
\ No newline at end of file