From 2cca97077e5406ebbfa63a904a0f9a9d2e6580c6 Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Fri, 7 Apr 2023 22:23:31 +0200
Subject: [PATCH 01/10] doctests resolved issues for transformations and
 u.add_Residue

---
 package/MDAnalysis/core/universe.py       | 8 +++++---
 package/MDAnalysis/lib/transformations.py | 8 ++++----
 2 files changed, 9 insertions(+), 7 deletions(-)

diff --git a/package/MDAnalysis/core/universe.py b/package/MDAnalysis/core/universe.py
index 572fdf628df..7f87800cb27 100644
--- a/package/MDAnalysis/core/universe.py
+++ b/package/MDAnalysis/core/universe.py
@@ -986,11 +986,13 @@ def add_Residue(self, segment=None, **attrs):
         -------
 
         Adding a new GLY residue, then placing atoms within it:
-
-        >>> newres = u.add_Residue(segment=u.segments[0], resid=42, resname='GLY')
+        >>> import MDAnalysis as mda
+        >>> from MDAnalysis.tests.datafiles import PSF, DCD
+        >>> u = mda.Universe(PSF, DCD)
+        >>> newres = u.add_Residue(segment=u.segments[0], resid=42, resname='GLY', resnum=0)
         >>> u.atoms[[1, 2, 3]].residues = newres
         >>> u.select_atoms('resname GLY and resid 42')
-        <AtomGroup with 3 atoms>
+        <AtomGroup with 10 atoms>
 
         """
         if len(self.segments) == 1:  # if only one segment, use this
diff --git a/package/MDAnalysis/lib/transformations.py b/package/MDAnalysis/lib/transformations.py
index f66d1c6ea2b..ef0040743be 100644
--- a/package/MDAnalysis/lib/transformations.py
+++ b/package/MDAnalysis/lib/transformations.py
@@ -108,7 +108,7 @@
 
 Examples
 --------
-
+>>> from MDAnalysis.lib.transformations import identity_matrix
 >>> alpha, beta, gamma = 0.123, -1.234, 2.345
 >>> origin, xaxis, yaxis, zaxis = (0, 0, 0), (1, 0, 0), (0, 1, 0), (0, 0, 1)
 >>> I = identity_matrix()
@@ -174,7 +174,7 @@
 
 def identity_matrix():
     """Return 4x4 identity/unit matrix.
-
+    >>> from MDAnalysis.lib.transformations import identity_matrix
     >>> I = identity_matrix()
     >>> np.allclose(I, np.dot(I, I))
     True
@@ -1180,7 +1180,7 @@ def quaternion_about_axis(angle, axis):
 
 def quaternion_matrix(quaternion):
     """Return homogeneous rotation matrix from quaternion.
-
+    >>> from MDAnalysis.lib.transformations import identity_matrix
     >>> M = quaternion_matrix([0.99810947, 0.06146124, 0, 0])
     >>> np.allclose(M, rotation_matrix(0.123, (1, 0, 0)))
     True
@@ -1212,7 +1212,7 @@ def quaternion_from_matrix(matrix, isprecise=False):
 
     If isprecise=True, the input matrix is assumed to be a precise rotation
     matrix and a faster algorithm is used.
-
+    >>> from MDAnalysis.lib.transformations import identity_matrix
     >>> q = quaternion_from_matrix(identity_matrix(), True)
     >>> np.allclose(q, [1., 0., 0., 0.])
     True

From 78ada17a3de80b7e6a31cb4e72bf303129507d0d Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Fri, 7 Apr 2023 22:28:57 +0200
Subject: [PATCH 02/10] Update transformations.py

---
 package/MDAnalysis/lib/transformations.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/package/MDAnalysis/lib/transformations.py b/package/MDAnalysis/lib/transformations.py
index ef0040743be..6e377dc1b9e 100644
--- a/package/MDAnalysis/lib/transformations.py
+++ b/package/MDAnalysis/lib/transformations.py
@@ -108,6 +108,7 @@
 
 Examples
 --------
+
 >>> from MDAnalysis.lib.transformations import identity_matrix
 >>> alpha, beta, gamma = 0.123, -1.234, 2.345
 >>> origin, xaxis, yaxis, zaxis = (0, 0, 0), (1, 0, 0), (0, 1, 0), (0, 0, 1)
@@ -174,6 +175,7 @@
 
 def identity_matrix():
     """Return 4x4 identity/unit matrix.
+
     >>> from MDAnalysis.lib.transformations import identity_matrix
     >>> I = identity_matrix()
     >>> np.allclose(I, np.dot(I, I))
@@ -1180,6 +1182,7 @@ def quaternion_about_axis(angle, axis):
 
 def quaternion_matrix(quaternion):
     """Return homogeneous rotation matrix from quaternion.
+
     >>> from MDAnalysis.lib.transformations import identity_matrix
     >>> M = quaternion_matrix([0.99810947, 0.06146124, 0, 0])
     >>> np.allclose(M, rotation_matrix(0.123, (1, 0, 0)))
@@ -1212,6 +1215,7 @@ def quaternion_from_matrix(matrix, isprecise=False):
 
     If isprecise=True, the input matrix is assumed to be a precise rotation
     matrix and a faster algorithm is used.
+
     >>> from MDAnalysis.lib.transformations import identity_matrix
     >>> q = quaternion_from_matrix(identity_matrix(), True)
     >>> np.allclose(q, [1., 0., 0., 0.])

From 3ea31aa3a8e91125bbbf26016a14e9208587944c Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Fri, 7 Apr 2023 22:30:18 +0200
Subject: [PATCH 03/10] Update universe.py

---
 package/MDAnalysis/core/universe.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/package/MDAnalysis/core/universe.py b/package/MDAnalysis/core/universe.py
index 7f87800cb27..bb8666e4432 100644
--- a/package/MDAnalysis/core/universe.py
+++ b/package/MDAnalysis/core/universe.py
@@ -986,6 +986,7 @@ def add_Residue(self, segment=None, **attrs):
         -------
 
         Adding a new GLY residue, then placing atoms within it:
+        
         >>> import MDAnalysis as mda
         >>> from MDAnalysis.tests.datafiles import PSF, DCD
         >>> u = mda.Universe(PSF, DCD)

From 9c32893c05f1d869d6c963b8e59c806197d6551f Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Sat, 8 Apr 2023 00:08:12 +0200
Subject: [PATCH 04/10] Update universe.py

---
 package/MDAnalysis/core/universe.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/package/MDAnalysis/core/universe.py b/package/MDAnalysis/core/universe.py
index bb8666e4432..7b8be89fe5b 100644
--- a/package/MDAnalysis/core/universe.py
+++ b/package/MDAnalysis/core/universe.py
@@ -992,8 +992,8 @@ def add_Residue(self, segment=None, **attrs):
         >>> u = mda.Universe(PSF, DCD)
         >>> newres = u.add_Residue(segment=u.segments[0], resid=42, resname='GLY', resnum=0)
         >>> u.atoms[[1, 2, 3]].residues = newres
-        >>> u.select_atoms('resname GLY and resid 42')
-        <AtomGroup with 10 atoms>
+        >>> u.select_atoms('resname GLY and resid 42 and resnum 0')
+        <AtomGroup with 3 atoms>
 
         """
         if len(self.segments) == 1:  # if only one segment, use this

From 5fc82dd4032aa4741646057b9296b864db360210 Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Sat, 8 Apr 2023 05:56:44 +0200
Subject: [PATCH 05/10] added missing import for greedy_splitext

---
 package/MDAnalysis/core/universe.py | 4 ++--
 package/MDAnalysis/lib/util.py      | 2 ++
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/package/MDAnalysis/core/universe.py b/package/MDAnalysis/core/universe.py
index 7b8be89fe5b..06db7195c8c 100644
--- a/package/MDAnalysis/core/universe.py
+++ b/package/MDAnalysis/core/universe.py
@@ -808,7 +808,7 @@ def add_TopologyAttr(self, topologyattr, values=None):
 
         >>> u.add_TopologyAttr('bfactors')
         >>> u.atoms.bfactors
-        array([ 0.,  0.,  0., ...,  0.,  0.,  0.])
+        array([0., 0., 0., ..., 0., 0., 0.])
 
         .. versionchanged:: 0.17.0
            Can now also add TopologyAttrs with a string of the name of the
@@ -986,7 +986,7 @@ def add_Residue(self, segment=None, **attrs):
         -------
 
         Adding a new GLY residue, then placing atoms within it:
-        
+
         >>> import MDAnalysis as mda
         >>> from MDAnalysis.tests.datafiles import PSF, DCD
         >>> u = mda.Universe(PSF, DCD)
diff --git a/package/MDAnalysis/lib/util.py b/package/MDAnalysis/lib/util.py
index ab36932dbf1..88aaae9b74d 100644
--- a/package/MDAnalysis/lib/util.py
+++ b/package/MDAnalysis/lib/util.py
@@ -474,6 +474,8 @@ def greedy_splitext(p):
 
     Example
     -------
+
+    >>> from MDAnalysis.lib.util import greedy_splitext
     >>> greedy_splitext("/home/joe/protein.pdb.bz2")
     ('/home/joe/protein', '.pdb.bz2')
 

From 75f407a2fc12a7d1e5554cc958ee6b8b97f2581a Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Mon, 10 Apr 2023 14:53:06 +0200
Subject: [PATCH 06/10] Fixed all doctests in transformations.py file

---
 package/MDAnalysis/lib/transformations.py | 71 ++++++++++++++++++++++-
 1 file changed, 70 insertions(+), 1 deletion(-)

diff --git a/package/MDAnalysis/lib/transformations.py b/package/MDAnalysis/lib/transformations.py
index 6e377dc1b9e..0c44fc1096f 100644
--- a/package/MDAnalysis/lib/transformations.py
+++ b/package/MDAnalysis/lib/transformations.py
@@ -192,6 +192,7 @@ def identity_matrix():
 def translation_matrix(direction):
     """Return matrix to translate by direction vector.
 
+    >>> from MDAnalysis.lib.transformations import translation_matrix
     >>> v = np.random.random(3) - 0.5
     >>> np.allclose(v, translation_matrix(v)[:3, 3])
     True
@@ -205,6 +206,8 @@ def translation_matrix(direction):
 def translation_from_matrix(matrix):
     """Return translation vector from translation matrix.
 
+    >>> from MDAnalysis.lib.transformations import translation_matrix, \
+    ...     translation_from_matrix
     >>> v0 = np.random.random(3) - 0.5
     >>> v1 = translation_from_matrix(translation_matrix(v0))
     >>> np.allclose(v0, v1)
@@ -217,6 +220,7 @@ def translation_from_matrix(matrix):
 def reflection_matrix(point, normal):
     """Return matrix to mirror at plane defined by point and normal vector.
 
+    >>> from MDAnalysis.lib.transformations import reflection_matrix
     >>> v0 = np.random.random(4) - 0.5
     >>> v0[3] = 1.0
     >>> v1 = np.random.random(3) - 0.5
@@ -243,6 +247,8 @@ def reflection_matrix(point, normal):
 def reflection_from_matrix(matrix):
     """Return mirror plane point and normal vector from reflection matrix.
 
+    >>> from MDAnalysis.lib.transformations import reflection_matrix, \
+    ...     reflection_from_matrix, is_same_transform
     >>> v0 = np.random.random(3) - 0.5
     >>> v1 = np.random.random(3) - 0.5
     >>> M0 = reflection_matrix(v0, v1)
@@ -272,6 +278,9 @@ def reflection_from_matrix(matrix):
 def rotation_matrix(angle, direction, point=None):
     """Return matrix to rotate about axis defined by point and direction.
 
+    >>> from MDAnalysis.lib.transformations import rotation_matrix, \
+    ...     is_same_transform
+    >>> import random, math
     >>> R = rotation_matrix(math.pi/2.0, [0, 0, 1], [1, 0, 0])
     >>> np.allclose(np.dot(R, [0, 0, 0, 1]), [ 1., -1.,  0.,  1.])
     True
@@ -321,6 +330,9 @@ def rotation_matrix(angle, direction, point=None):
 def rotation_from_matrix(matrix):
     """Return rotation angle and axis from rotation matrix.
 
+    >>> from MDAnalysis.lib.transformations import rotation_matrix, is_same_transform \
+    ...     rotation_from_matrix
+    >>> import random, math
     >>> angle = (random.random() - 0.5) * (2*math.pi)
     >>> direc = np.random.random(3) - 0.5
     >>> point = np.random.random(3) - 0.5
@@ -363,6 +375,8 @@ def scale_matrix(factor, origin=None, direction=None):
 
     Use factor -1 for point symmetry.
 
+    >>> from MDAnalysis.lib.transformations import scale_matrix
+    >>> import random
     >>> v = (np.random.rand(4, 5) - 0.5) * 20.0
     >>> v[3] = 1.0
     >>> S = scale_matrix(-1.234)
@@ -399,6 +413,9 @@ def scale_matrix(factor, origin=None, direction=None):
 def scale_from_matrix(matrix):
     """Return scaling factor, origin and direction from scaling matrix.
 
+    >>> from MDAnalysis.lib.transformations import scale_matrix, scale_from_matrix, \
+    ...     is_same_transform
+    >>> import random
     >>> factor = random.random() * 10 - 5
     >>> origin = np.random.random(3) - 0.5
     >>> direct = np.random.random(3) - 0.5
@@ -446,6 +463,8 @@ def projection_matrix(point, normal, direction=None,
     If pseudo is True, perspective projections will preserve relative depth
     such that Perspective = dot(Orthogonal, PseudoPerspective).
 
+    >>> from MDAnalysis.lib.transformations import projection_matrix, \
+    ... is_same_transform
     >>> P = projection_matrix((0, 0, 0), (1, 0, 0))
     >>> np.allclose(P[1:, 1:], np.identity(4)[1:, 1:])
     True
@@ -505,6 +524,8 @@ def projection_from_matrix(matrix, pseudo=False):
     Return values are same as arguments for projection_matrix function:
     point, normal, direction, perspective, and pseudo.
 
+    >>> from MDAnalysis.lib.transformations import projection_matrix, \
+    ...     projection_from_matrix, is_same_transform
     >>> point = np.random.random(3) - 0.5
     >>> normal = np.random.random(3) - 0.5
     >>> direct = np.random.random(3) - 0.5
@@ -588,6 +609,7 @@ def clip_matrix(left, right, bottom, top, near, far, perspective=False):
     Homogeneous coordinates transformed by the perspective clip matrix
     need to be dehomogenized (devided by w coordinate).
 
+    >>> from MDAnalysis.lib.transformations import clip_matrix
     >>> frustrum = np.random.rand(6)
     >>> frustrum[1] += frustrum[0]
     >>> frustrum[3] += frustrum[2]
@@ -637,6 +659,8 @@ def shear_matrix(angle, direction, point, normal):
     given by the angle of P-P'-P", where P' is the orthogonal projection
     of P onto the shear plane.
 
+    >>> from MDAnalysis.lib.transformations import shear_matrix
+    >>> import random, math
     >>> angle = (random.random() - 0.5) * 4*math.pi
     >>> direct = np.random.random(3) - 0.5
     >>> point = np.random.random(3) - 0.5
@@ -660,6 +684,9 @@ def shear_matrix(angle, direction, point, normal):
 def shear_from_matrix(matrix):
     """Return shear angle, direction and plane from shear matrix.
 
+    >>> from MDAnalysis.lib.transformations import shear_matrix, \
+    ...     shear_from_matrix, is_same_transform
+    >>> import random, math
     >>> angle = (random.random() - 0.5) * 4*math.pi
     >>> direct = np.random.random(3) - 0.5
     >>> point = np.random.random(3) - 0.5
@@ -717,6 +744,8 @@ def decompose_matrix(matrix):
 
     Raise ValueError if matrix is of wrong type or degenerative.
 
+    >>> from MDAnalysis.lib.transformations import translation_matrix, \
+    ...     decompose_matrix, scale_matrix, euler_matrix
     >>> T0 = translation_matrix((1, 2, 3))
     >>> scale, shear, angles, trans, persp = decompose_matrix(T0)
     >>> T1 = translation_matrix(trans)
@@ -801,6 +830,9 @@ def compose_matrix(scale=None, shear=None, angles=None, translate=None,
         translate : translation vector along x, y, z axes
         perspective : perspective partition of matrix
 
+    >>> from MDAnalysis.lib.transformations import compose_matrix, \
+    ...     decompose_matrix, is_same_transform
+    >>> import math
     >>> scale = np.random.random(3) - 0.5
     >>> shear = np.random.random(3) - 0.5
     >>> angles = (np.random.random(3) - 0.5) * (2*math.pi)
@@ -848,6 +880,7 @@ def orthogonalization_matrix(lengths, angles):
 
     The de-orthogonalization matrix is the inverse.
 
+    >>> from MDAnalysis.lib.transformations import orthogonalization_matrix
     >>> O = orthogonalization_matrix((10., 10., 10.), (90., 90., 90.))
     >>> np.allclose(O[:3, :3], np.identity(3, float) * 10)
     True
@@ -883,6 +916,10 @@ def superimposition_matrix(v0, v1, scaling=False, usesvd=True):
     The returned matrix performs rotation, translation and uniform scaling
     (if specified).
 
+    >>> from MDAnalysis.lib.transformations import superimposition_matrix, \
+    ... random_rotation_matrix, scale_matrix, translation_matrix, \
+    ... concatenate_matrices
+    >>> import random
     >>> v0 = np.random.rand(3, 10)
     >>> M = superimposition_matrix(v0, v0)
     >>> np.allclose(M, np.identity(4))
@@ -978,6 +1015,9 @@ def euler_matrix(ai, aj, ak, axes='sxyz'):
     ai, aj, ak : Euler's roll, pitch and yaw angles
     axes : One of 24 axis sequences as string or encoded tuple
 
+    >>> from MDAnalysis.lib.transformations import euler_matrix \
+    ... _AXES2TUPLE, _TUPLE2AXES
+    >>> import math
     >>> R = euler_matrix(1, 2, 3, 'syxz')
     >>> np.allclose(np.sum(R[0]), -1.34786452)
     True
@@ -1042,6 +1082,9 @@ def euler_from_matrix(matrix, axes='sxyz'):
 
     Note that many Euler angle triplets can describe one matrix.
 
+    >>> from MDAnalysis.lib.transformations import euler_matrix, \
+    ... euler_from_matrix, _AXES2TUPLE
+    >>> import math
     >>> R0 = euler_matrix(1, 2, 3, 'syxz')
     >>> al, be, ga = euler_from_matrix(R0, 'syxz')
     >>> R1 = euler_matrix(al, be, ga, 'syxz')
@@ -1096,6 +1139,7 @@ def euler_from_matrix(matrix, axes='sxyz'):
 def euler_from_quaternion(quaternion, axes='sxyz'):
     """Return Euler angles from quaternion for specified axis sequence.
 
+    >>> from MDAnalysis.lib.transformations import euler_from_quaternion
     >>> angles = euler_from_quaternion([0.99810947, 0.06146124, 0, 0])
     >>> np.allclose(angles, [0.123, 0, 0])
     True
@@ -1110,6 +1154,7 @@ def quaternion_from_euler(ai, aj, ak, axes='sxyz'):
     ai, aj, ak : Euler's roll, pitch and yaw angles
     axes : One of 24 axis sequences as string or encoded tuple
 
+    >>> from MDAnalysis.lib.transformations import quaternion_from_euler
     >>> q = quaternion_from_euler(1, 2, 3, 'ryxz')
     >>> np.allclose(q, [0.435953, 0.310622, -0.718287, 0.444435])
     True
@@ -1164,6 +1209,7 @@ def quaternion_from_euler(ai, aj, ak, axes='sxyz'):
 def quaternion_about_axis(angle, axis):
     """Return quaternion for rotation about axis.
 
+    >>> from MDAnalysis.lib.transformations import quaternion_about_axis
     >>> q = quaternion_about_axis(0.123, (1, 0, 0))
     >>> np.allclose(q, [0.99810947, 0.06146124, 0, 0])
     True
@@ -1216,7 +1262,9 @@ def quaternion_from_matrix(matrix, isprecise=False):
     If isprecise=True, the input matrix is assumed to be a precise rotation
     matrix and a faster algorithm is used.
 
-    >>> from MDAnalysis.lib.transformations import identity_matrix
+    >>> from MDAnalysis.lib.transformations import identity_matrix, \
+    ...     quaternion_from_matrix, rotation_matrix, random_rotation_matrix, \
+    ...     is_same_transform, quaternion_matrix
     >>> q = quaternion_from_matrix(identity_matrix(), True)
     >>> np.allclose(q, [1., 0., 0., 0.])
     True
@@ -1311,6 +1359,8 @@ def quaternion_multiply(quaternion1, quaternion0):
 def quaternion_conjugate(quaternion):
     """Return conjugate of quaternion.
 
+    >>> from MDAnalysis.lib.transformations import random_quaternion, \
+    ...     quaternion_conjugate
     >>> q0 = random_quaternion()
     >>> q1 = quaternion_conjugate(q0)
     >>> q1[0] == q0[0] and all(q1[1:] == -q0[1:])
@@ -1326,6 +1376,8 @@ def quaternion_conjugate(quaternion):
 def quaternion_inverse(quaternion):
     """Return inverse of quaternion.
 
+    >>> from MDAnalysis.lib.transformations import random_quaternion, \
+    ...     quaternion_inverse
     >>> q0 = random_quaternion()
     >>> q1 = quaternion_inverse(q0)
     >>> np.allclose(quaternion_multiply(q0, q1), [1, 0, 0, 0])
@@ -1338,6 +1390,7 @@ def quaternion_inverse(quaternion):
 def quaternion_real(quaternion):
     """Return real part of quaternion.
 
+    >>> from MDAnalysis.lib.transformations import quaternion_real
     >>> quaternion_real([3.0, 0.0, 1.0, 2.0])
     3.0
 
@@ -1348,6 +1401,7 @@ def quaternion_real(quaternion):
 def quaternion_imag(quaternion):
     """Return imaginary part of quaternion.
 
+    >>> from MDAnalysis.lib.transformations import quaternion_imag
     >>> quaternion_imag([3.0, 0.0, 1.0, 2.0])
     [0.0, 1.0, 2.0]
 
@@ -1358,6 +1412,9 @@ def quaternion_imag(quaternion):
 def quaternion_slerp(quat0, quat1, fraction, spin=0, shortestpath=True):
     r"""Return spherical linear interpolation between two quaternions.
 
+    >>> from MDAnalysis.lib.transformations import random_quaternion, \
+    ...     quaternion_slerp
+    >>> import math
     >>> q0 = random_quaternion()
     >>> q1 = random_quaternion()
     >>> q = quaternion_slerp(q0, q1, 0.0)
@@ -1403,6 +1460,8 @@ def random_quaternion(rand=None):
         Three independent random variables that are uniformly distributed
         between 0 and 1.
 
+    >>> from MDAnalysis.lib.transformations import random_quaternion, \
+    ...     vector_norm
     >>> q = random_quaternion()
     >>> np.allclose(1.0, vector_norm(q))
     True
@@ -1435,6 +1494,7 @@ def random_rotation_matrix(rand=None):
         Three independent random variables that are uniformly distributed
         between 0 and 1 for each returned quaternion.
 
+    >>> from MDAnalysis.lib.transformations import random_rotation_matrix
     >>> R = random_rotation_matrix()
     >>> np.allclose(np.dot(R.T, R), np.identity(4))
     True
@@ -1446,6 +1506,7 @@ def random_rotation_matrix(rand=None):
 class Arcball(object):
     """Virtual Trackball Control.
 
+    >>> from MDAnalysis.lib.transformations import Arcball
     >>> ball = Arcball()
     >>> ball = Arcball(initial=np.identity(4))
     >>> ball.place([320, 320], 320)
@@ -1628,6 +1689,7 @@ def arcball_nearest_axis(point, axes):
 def vector_norm(data, axis=None, out=None):
     """Return length, i.e. eucledian norm, of ndarray along axis.
 
+    >>> from MDAnalysis.lib.transformations import vector_norm
     >>> v = np.random.random(3)
     >>> n = vector_norm(v)
     >>> np.allclose(n, np.linalg.norm(v))
@@ -1667,6 +1729,7 @@ def vector_norm(data, axis=None, out=None):
 def unit_vector(data, axis=None, out=None):
     """Return ndarray normalized by length, i.e. eucledian norm, along axis.
 
+    >>> from MDAnalysis.lib.transformations import unit_vector
     >>> v0 = np.random.random(3)
     >>> v1 = unit_vector(v0)
     >>> np.allclose(v1, v0 / np.linalg.norm(v0))
@@ -1711,6 +1774,7 @@ def unit_vector(data, axis=None, out=None):
 def random_vector(size):
     """Return array of random doubles in the half-open interval [0.0, 1.0).
 
+    >>> from MDAnalysis.lib.transformations import random_vector
     >>> v = random_vector(10000)
     >>> np.all(v >= 0.0) and np.all(v < 1.0)
     True
@@ -1726,6 +1790,8 @@ def random_vector(size):
 def inverse_matrix(matrix):
     """Return inverse of square transformation matrix.
 
+    >>> from MDAnalysis.lib.transformations import random_rotation_matrix, \
+    ...     inverse_matrix
     >>> M0 = random_rotation_matrix()
     >>> M1 = inverse_matrix(M0.T)
     >>> np.allclose(M1, np.linalg.inv(M0.T))
@@ -1742,6 +1808,7 @@ def inverse_matrix(matrix):
 def concatenate_matrices(*matrices):
     """Return concatenation of series of transformation matrices.
 
+    >>> from MDAnalysis.lib.transformations import concatenate_matrices
     >>> M = np.random.rand(16).reshape((4, 4)) - 0.5
     >>> np.allclose(M, concatenate_matrices(M))
     True
@@ -1758,6 +1825,8 @@ def concatenate_matrices(*matrices):
 def is_same_transform(matrix0, matrix1):
     """Return True if two matrices perform same transformation.
 
+    >>> from MDAnalysis.lib.transformations import is_same_transform, \
+    ... random_rotation_matrix
     >>> is_same_transform(np.identity(4), np.identity(4))
     True
     >>> is_same_transform(np.identity(4), random_rotation_matrix())

From 139cacc47f50ddfc82331828abca35281b14636e Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Mon, 10 Apr 2023 18:06:56 +0200
Subject: [PATCH 07/10] import numpy as np && add more missing imports

---
 package/MDAnalysis/lib/transformations.py | 128 ++++++++++++++--------
 1 file changed, 84 insertions(+), 44 deletions(-)

diff --git a/package/MDAnalysis/lib/transformations.py b/package/MDAnalysis/lib/transformations.py
index 0c44fc1096f..6abb8fc6930 100644
--- a/package/MDAnalysis/lib/transformations.py
+++ b/package/MDAnalysis/lib/transformations.py
@@ -109,7 +109,8 @@
 Examples
 --------
 
->>> from MDAnalysis.lib.transformations import identity_matrix
+>>> from MDAnalysis.lib.transformations import *
+>>> import numpy
 >>> alpha, beta, gamma = 0.123, -1.234, 2.345
 >>> origin, xaxis, yaxis, zaxis = (0, 0, 0), (1, 0, 0), (0, 1, 0), (0, 0, 1)
 >>> I = identity_matrix()
@@ -177,6 +178,7 @@ def identity_matrix():
     """Return 4x4 identity/unit matrix.
 
     >>> from MDAnalysis.lib.transformations import identity_matrix
+    >>> import numpy as np
     >>> I = identity_matrix()
     >>> np.allclose(I, np.dot(I, I))
     True
@@ -193,6 +195,7 @@ def translation_matrix(direction):
     """Return matrix to translate by direction vector.
 
     >>> from MDAnalysis.lib.transformations import translation_matrix
+    >>> import numpy as np
     >>> v = np.random.random(3) - 0.5
     >>> np.allclose(v, translation_matrix(v)[:3, 3])
     True
@@ -206,8 +209,9 @@ def translation_matrix(direction):
 def translation_from_matrix(matrix):
     """Return translation vector from translation matrix.
 
-    >>> from MDAnalysis.lib.transformations import translation_matrix, \
-    ...     translation_from_matrix
+    >>> from MDAnalysis.lib.transformations import (translation_matrix,
+    ...     translation_from_matrix)
+    >>> import numpy as np
     >>> v0 = np.random.random(3) - 0.5
     >>> v1 = translation_from_matrix(translation_matrix(v0))
     >>> np.allclose(v0, v1)
@@ -221,6 +225,7 @@ def reflection_matrix(point, normal):
     """Return matrix to mirror at plane defined by point and normal vector.
 
     >>> from MDAnalysis.lib.transformations import reflection_matrix
+    >>> import numpy as np
     >>> v0 = np.random.random(4) - 0.5
     >>> v0[3] = 1.0
     >>> v1 = np.random.random(3) - 0.5
@@ -247,8 +252,9 @@ def reflection_matrix(point, normal):
 def reflection_from_matrix(matrix):
     """Return mirror plane point and normal vector from reflection matrix.
 
-    >>> from MDAnalysis.lib.transformations import reflection_matrix, \
-    ...     reflection_from_matrix, is_same_transform
+    >>> from MDAnalysis.lib.transformations import (reflection_matrix,
+    ...     reflection_from_matrix, is_same_transform)
+    >>> import numpy as np
     >>> v0 = np.random.random(3) - 0.5
     >>> v1 = np.random.random(3) - 0.5
     >>> M0 = reflection_matrix(v0, v1)
@@ -278,9 +284,10 @@ def reflection_from_matrix(matrix):
 def rotation_matrix(angle, direction, point=None):
     """Return matrix to rotate about axis defined by point and direction.
 
-    >>> from MDAnalysis.lib.transformations import rotation_matrix, \
-    ...     is_same_transform
+    >>> from MDAnalysis.lib.transformations import (rotation_matrix,
+    ...     is_same_transform)
     >>> import random, math
+    >>> import numpy as np
     >>> R = rotation_matrix(math.pi/2.0, [0, 0, 1], [1, 0, 0])
     >>> np.allclose(np.dot(R, [0, 0, 0, 1]), [ 1., -1.,  0.,  1.])
     True
@@ -330,9 +337,10 @@ def rotation_matrix(angle, direction, point=None):
 def rotation_from_matrix(matrix):
     """Return rotation angle and axis from rotation matrix.
 
-    >>> from MDAnalysis.lib.transformations import rotation_matrix, is_same_transform \
-    ...     rotation_from_matrix
+    >>> from MDAnalysis.lib.transformations import (rotation_matrix,
+    ...     is_same_transform, rotation_from_matrix)
     >>> import random, math
+    >>> import numpy as np
     >>> angle = (random.random() - 0.5) * (2*math.pi)
     >>> direc = np.random.random(3) - 0.5
     >>> point = np.random.random(3) - 0.5
@@ -377,6 +385,7 @@ def scale_matrix(factor, origin=None, direction=None):
 
     >>> from MDAnalysis.lib.transformations import scale_matrix
     >>> import random
+    >>> import numpy as np
     >>> v = (np.random.rand(4, 5) - 0.5) * 20.0
     >>> v[3] = 1.0
     >>> S = scale_matrix(-1.234)
@@ -413,9 +422,10 @@ def scale_matrix(factor, origin=None, direction=None):
 def scale_from_matrix(matrix):
     """Return scaling factor, origin and direction from scaling matrix.
 
-    >>> from MDAnalysis.lib.transformations import scale_matrix, scale_from_matrix, \
-    ...     is_same_transform
+    >>> from MDAnalysis.lib.transformations import (scale_matrix,
+    ...      scale_from_matrix, is_same_transform)
     >>> import random
+    >>> import numpy as np
     >>> factor = random.random() * 10 - 5
     >>> origin = np.random.random(3) - 0.5
     >>> direct = np.random.random(3) - 0.5
@@ -463,8 +473,9 @@ def projection_matrix(point, normal, direction=None,
     If pseudo is True, perspective projections will preserve relative depth
     such that Perspective = dot(Orthogonal, PseudoPerspective).
 
-    >>> from MDAnalysis.lib.transformations import projection_matrix, \
-    ... is_same_transform
+    >>> from MDAnalysis.lib.transformations import (projection_matrix,
+    ...     is_same_transform)
+    >>> import numpy as np
     >>> P = projection_matrix((0, 0, 0), (1, 0, 0))
     >>> np.allclose(P[1:, 1:], np.identity(4)[1:, 1:])
     True
@@ -524,8 +535,9 @@ def projection_from_matrix(matrix, pseudo=False):
     Return values are same as arguments for projection_matrix function:
     point, normal, direction, perspective, and pseudo.
 
-    >>> from MDAnalysis.lib.transformations import projection_matrix, \
-    ...     projection_from_matrix, is_same_transform
+    >>> from MDAnalysis.lib.transformations import (projection_matrix,
+    ...     projection_from_matrix, is_same_transform)
+    >>> import numpy as np
     >>> point = np.random.random(3) - 0.5
     >>> normal = np.random.random(3) - 0.5
     >>> direct = np.random.random(3) - 0.5
@@ -610,6 +622,7 @@ def clip_matrix(left, right, bottom, top, near, far, perspective=False):
     need to be dehomogenized (devided by w coordinate).
 
     >>> from MDAnalysis.lib.transformations import clip_matrix
+    >>> import numpy as np
     >>> frustrum = np.random.rand(6)
     >>> frustrum[1] += frustrum[0]
     >>> frustrum[3] += frustrum[2]
@@ -661,6 +674,7 @@ def shear_matrix(angle, direction, point, normal):
 
     >>> from MDAnalysis.lib.transformations import shear_matrix
     >>> import random, math
+    >>> import numpy as np
     >>> angle = (random.random() - 0.5) * 4*math.pi
     >>> direct = np.random.random(3) - 0.5
     >>> point = np.random.random(3) - 0.5
@@ -684,9 +698,10 @@ def shear_matrix(angle, direction, point, normal):
 def shear_from_matrix(matrix):
     """Return shear angle, direction and plane from shear matrix.
 
-    >>> from MDAnalysis.lib.transformations import shear_matrix, \
-    ...     shear_from_matrix, is_same_transform
+    >>> from MDAnalysis.lib.transformations import (shear_matrix,
+    ...     shear_from_matrix, is_same_transform)
     >>> import random, math
+    >>> import numpy as np
     >>> angle = (random.random() - 0.5) * 4*math.pi
     >>> direct = np.random.random(3) - 0.5
     >>> point = np.random.random(3) - 0.5
@@ -744,8 +759,9 @@ def decompose_matrix(matrix):
 
     Raise ValueError if matrix is of wrong type or degenerative.
 
-    >>> from MDAnalysis.lib.transformations import translation_matrix, \
-    ...     decompose_matrix, scale_matrix, euler_matrix
+    >>> from MDAnalysis.lib.transformations import (translation_matrix,
+    ...     decompose_matrix, scale_matrix, euler_matrix)
+    >>> import numpy as np
     >>> T0 = translation_matrix((1, 2, 3))
     >>> scale, shear, angles, trans, persp = decompose_matrix(T0)
     >>> T1 = translation_matrix(trans)
@@ -830,9 +846,10 @@ def compose_matrix(scale=None, shear=None, angles=None, translate=None,
         translate : translation vector along x, y, z axes
         perspective : perspective partition of matrix
 
-    >>> from MDAnalysis.lib.transformations import compose_matrix, \
-    ...     decompose_matrix, is_same_transform
+    >>> from MDAnalysis.lib.transformations import (compose_matrix,
+    ...     decompose_matrix, is_same_transform)
     >>> import math
+    >>> import numpy as np
     >>> scale = np.random.random(3) - 0.5
     >>> shear = np.random.random(3) - 0.5
     >>> angles = (np.random.random(3) - 0.5) * (2*math.pi)
@@ -881,6 +898,7 @@ def orthogonalization_matrix(lengths, angles):
     The de-orthogonalization matrix is the inverse.
 
     >>> from MDAnalysis.lib.transformations import orthogonalization_matrix
+    >>> import numpy as np
     >>> O = orthogonalization_matrix((10., 10., 10.), (90., 90., 90.))
     >>> np.allclose(O[:3, :3], np.identity(3, float) * 10)
     True
@@ -916,10 +934,11 @@ def superimposition_matrix(v0, v1, scaling=False, usesvd=True):
     The returned matrix performs rotation, translation and uniform scaling
     (if specified).
 
-    >>> from MDAnalysis.lib.transformations import superimposition_matrix, \
-    ... random_rotation_matrix, scale_matrix, translation_matrix, \
-    ... concatenate_matrices
+    >>> from MDAnalysis.lib.transformations import (superimposition_matrix,
+    ... random_rotation_matrix, scale_matrix, translation_matrix,
+    ... concatenate_matrices)
     >>> import random
+    >>> import numpy as np
     >>> v0 = np.random.rand(3, 10)
     >>> M = superimposition_matrix(v0, v0)
     >>> np.allclose(M, np.identity(4))
@@ -1015,9 +1034,10 @@ def euler_matrix(ai, aj, ak, axes='sxyz'):
     ai, aj, ak : Euler's roll, pitch and yaw angles
     axes : One of 24 axis sequences as string or encoded tuple
 
-    >>> from MDAnalysis.lib.transformations import euler_matrix \
-    ... _AXES2TUPLE, _TUPLE2AXES
+    >>> from MDAnalysis.lib.transformations import (euler_matrix
+    ... _AXES2TUPLE, _TUPLE2AXES)
     >>> import math
+    >>> import numpy as np
     >>> R = euler_matrix(1, 2, 3, 'syxz')
     >>> np.allclose(np.sum(R[0]), -1.34786452)
     True
@@ -1082,9 +1102,10 @@ def euler_from_matrix(matrix, axes='sxyz'):
 
     Note that many Euler angle triplets can describe one matrix.
 
-    >>> from MDAnalysis.lib.transformations import euler_matrix, \
-    ... euler_from_matrix, _AXES2TUPLE
+    >>> from MDAnalysis.lib.transformations import (euler_matrix,
+    ... euler_from_matrix, _AXES2TUPLE)
     >>> import math
+    >>> import numpy as np
     >>> R0 = euler_matrix(1, 2, 3, 'syxz')
     >>> al, be, ga = euler_from_matrix(R0, 'syxz')
     >>> R1 = euler_matrix(al, be, ga, 'syxz')
@@ -1140,6 +1161,7 @@ def euler_from_quaternion(quaternion, axes='sxyz'):
     """Return Euler angles from quaternion for specified axis sequence.
 
     >>> from MDAnalysis.lib.transformations import euler_from_quaternion
+    >>> import numpy as np
     >>> angles = euler_from_quaternion([0.99810947, 0.06146124, 0, 0])
     >>> np.allclose(angles, [0.123, 0, 0])
     True
@@ -1210,6 +1232,7 @@ def quaternion_about_axis(angle, axis):
     """Return quaternion for rotation about axis.
 
     >>> from MDAnalysis.lib.transformations import quaternion_about_axis
+    >>> import numpy as np
     >>> q = quaternion_about_axis(0.123, (1, 0, 0))
     >>> np.allclose(q, [0.99810947, 0.06146124, 0, 0])
     True
@@ -1229,7 +1252,9 @@ def quaternion_about_axis(angle, axis):
 def quaternion_matrix(quaternion):
     """Return homogeneous rotation matrix from quaternion.
 
-    >>> from MDAnalysis.lib.transformations import identity_matrix
+    >>> from MDAnalysis.lib.transformations import (identity_matrix,
+    ...     quaternion_matrix, rotation_matrix)
+    >>> import numpy as np
     >>> M = quaternion_matrix([0.99810947, 0.06146124, 0, 0])
     >>> np.allclose(M, rotation_matrix(0.123, (1, 0, 0)))
     True
@@ -1262,9 +1287,10 @@ def quaternion_from_matrix(matrix, isprecise=False):
     If isprecise=True, the input matrix is assumed to be a precise rotation
     matrix and a faster algorithm is used.
 
-    >>> from MDAnalysis.lib.transformations import identity_matrix, \
-    ...     quaternion_from_matrix, rotation_matrix, random_rotation_matrix, \
-    ...     is_same_transform, quaternion_matrix
+    >>> from MDAnalysis.lib.transformations import (identity_matrix,
+    ...     quaternion_from_matrix, rotation_matrix, random_rotation_matrix,
+    ...     is_same_transform, quaternion_matrix)
+    >>> import numpy as np
     >>> q = quaternion_from_matrix(identity_matrix(), True)
     >>> np.allclose(q, [1., 0., 0., 0.])
     True
@@ -1341,6 +1367,8 @@ def quaternion_from_matrix(matrix, isprecise=False):
 def quaternion_multiply(quaternion1, quaternion0):
     """Return multiplication of two quaternions.
 
+    >>> from MDAnalysis.lib.transformations import quaternion_multiply
+    >>> import numpy as np
     >>> q = quaternion_multiply([4, 1, -2, 3], [8, -5, 6, 7])
     >>> np.allclose(q, [28, -44, -14, 48])
     True
@@ -1359,8 +1387,9 @@ def quaternion_multiply(quaternion1, quaternion0):
 def quaternion_conjugate(quaternion):
     """Return conjugate of quaternion.
 
-    >>> from MDAnalysis.lib.transformations import random_quaternion, \
-    ...     quaternion_conjugate
+    >>> from MDAnalysis.lib.transformations import (random_quaternion,
+    ...     quaternion_conjugate)
+    >>> import numpy as np
     >>> q0 = random_quaternion()
     >>> q1 = quaternion_conjugate(q0)
     >>> q1[0] == q0[0] and all(q1[1:] == -q0[1:])
@@ -1376,8 +1405,9 @@ def quaternion_conjugate(quaternion):
 def quaternion_inverse(quaternion):
     """Return inverse of quaternion.
 
-    >>> from MDAnalysis.lib.transformations import random_quaternion, \
-    ...     quaternion_inverse
+    >>> from MDAnalysis.lib.transformations import (random_quaternion,
+    ...     quaternion_inverse)
+    >>> import numpy as np
     >>> q0 = random_quaternion()
     >>> q1 = quaternion_inverse(q0)
     >>> np.allclose(quaternion_multiply(q0, q1), [1, 0, 0, 0])
@@ -1412,9 +1442,10 @@ def quaternion_imag(quaternion):
 def quaternion_slerp(quat0, quat1, fraction, spin=0, shortestpath=True):
     r"""Return spherical linear interpolation between two quaternions.
 
-    >>> from MDAnalysis.lib.transformations import random_quaternion, \
-    ...     quaternion_slerp
+    >>> from MDAnalysis.lib.transformations import (random_quaternion,
+    ...     quaternion_slerp)
     >>> import math
+    >>> import numpy as np
     >>> q0 = random_quaternion()
     >>> q1 = random_quaternion()
     >>> q = quaternion_slerp(q0, q1, 0.0)
@@ -1460,8 +1491,9 @@ def random_quaternion(rand=None):
         Three independent random variables that are uniformly distributed
         between 0 and 1.
 
-    >>> from MDAnalysis.lib.transformations import random_quaternion, \
-    ...     vector_norm
+    >>> from MDAnalysis.lib.transformations import (random_quaternion,
+    ...     vector_norm)
+    >>> import numpy as np
     >>> q = random_quaternion()
     >>> np.allclose(1.0, vector_norm(q))
     True
@@ -1495,6 +1527,7 @@ def random_rotation_matrix(rand=None):
         between 0 and 1 for each returned quaternion.
 
     >>> from MDAnalysis.lib.transformations import random_rotation_matrix
+    >>> import numpy as np
     >>> R = random_rotation_matrix()
     >>> np.allclose(np.dot(R.T, R), np.identity(4))
     True
@@ -1507,6 +1540,7 @@ class Arcball(object):
     """Virtual Trackball Control.
 
     >>> from MDAnalysis.lib.transformations import Arcball
+    >>> import numpy as np
     >>> ball = Arcball()
     >>> ball = Arcball(initial=np.identity(4))
     >>> ball.place([320, 320], 320)
@@ -1690,6 +1724,7 @@ def vector_norm(data, axis=None, out=None):
     """Return length, i.e. eucledian norm, of ndarray along axis.
 
     >>> from MDAnalysis.lib.transformations import vector_norm
+    >>> import numpy as np
     >>> v = np.random.random(3)
     >>> n = vector_norm(v)
     >>> np.allclose(n, np.linalg.norm(v))
@@ -1730,6 +1765,7 @@ def unit_vector(data, axis=None, out=None):
     """Return ndarray normalized by length, i.e. eucledian norm, along axis.
 
     >>> from MDAnalysis.lib.transformations import unit_vector
+    >>> import numpy as np
     >>> v0 = np.random.random(3)
     >>> v1 = unit_vector(v0)
     >>> np.allclose(v1, v0 / np.linalg.norm(v0))
@@ -1775,6 +1811,7 @@ def random_vector(size):
     """Return array of random doubles in the half-open interval [0.0, 1.0).
 
     >>> from MDAnalysis.lib.transformations import random_vector
+    >>> import numpy as np
     >>> v = random_vector(10000)
     >>> np.all(v >= 0.0) and np.all(v < 1.0)
     True
@@ -1790,8 +1827,9 @@ def random_vector(size):
 def inverse_matrix(matrix):
     """Return inverse of square transformation matrix.
 
-    >>> from MDAnalysis.lib.transformations import random_rotation_matrix, \
-    ...     inverse_matrix
+    >>> from MDAnalysis.lib.transformations import (random_rotation_matrix,
+    ...     inverse_matrix)
+    >>> import numpy as np
     >>> M0 = random_rotation_matrix()
     >>> M1 = inverse_matrix(M0.T)
     >>> np.allclose(M1, np.linalg.inv(M0.T))
@@ -1809,6 +1847,7 @@ def concatenate_matrices(*matrices):
     """Return concatenation of series of transformation matrices.
 
     >>> from MDAnalysis.lib.transformations import concatenate_matrices
+    >>> import numpy as np
     >>> M = np.random.rand(16).reshape((4, 4)) - 0.5
     >>> np.allclose(M, concatenate_matrices(M))
     True
@@ -1825,8 +1864,9 @@ def concatenate_matrices(*matrices):
 def is_same_transform(matrix0, matrix1):
     """Return True if two matrices perform same transformation.
 
-    >>> from MDAnalysis.lib.transformations import is_same_transform, \
-    ... random_rotation_matrix
+    >>> from MDAnalysis.lib.transformations import (is_same_transform,
+    ...     random_rotation_matrix)
+    >>> import numpy as np
     >>> is_same_transform(np.identity(4), np.identity(4))
     True
     >>> is_same_transform(np.identity(4), random_rotation_matrix())

From d9799765e7875f17de751f0065340129695046d2 Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Mon, 10 Apr 2023 19:46:35 +0200
Subject: [PATCH 08/10] Solved failing doctests in `core/universe.py` &
 `lib/util.py`

---
 package/MDAnalysis/core/universe.py |  4 ++--
 package/MDAnalysis/lib/util.py      | 10 ++++++++++
 2 files changed, 12 insertions(+), 2 deletions(-)

diff --git a/package/MDAnalysis/core/universe.py b/package/MDAnalysis/core/universe.py
index 06db7195c8c..e708402085a 100644
--- a/package/MDAnalysis/core/universe.py
+++ b/package/MDAnalysis/core/universe.py
@@ -1419,9 +1419,9 @@ def from_smiles(cls, smiles, sanitize=True, addHs=True,
         To use a different conformer generation algorithm, like ETKDGv3:
 
         >>> u = mda.Universe.from_smiles('CCO', rdkit_kwargs=dict(
-                                         params=AllChem.ETKDGv3()))
+            ... params=AllChem.ETKDGv3()))
         >>> u.trajectory
-        <RDKitReader with 1 frames of 9 atoms>
+        <RDKitReader with 10 frames of 9 atoms>
 
 
         .. versionadded:: 2.0.0
diff --git a/package/MDAnalysis/lib/util.py b/package/MDAnalysis/lib/util.py
index 88aaae9b74d..d3e08820a4f 100644
--- a/package/MDAnalysis/lib/util.py
+++ b/package/MDAnalysis/lib/util.py
@@ -1622,6 +1622,8 @@ def unique_rows(arr, return_index=False):
     --------
     Remove dupicate rows from an array:
 
+    >>> import numpy as np
+    >>> from MDAnalysis.lib.util import unique_rows
     >>> a = np.array([[0, 1], [1, 2], [1, 2], [0, 1], [2, 3]])
     >>> b = unique_rows(a)
     >>> b
@@ -1682,6 +1684,8 @@ def blocks_of(a, n, m):
 
     Examples
     --------
+    >>> import numpy as np
+    >>> from MDAnalysis.lib.util import blocks_of
     >>> arr = np.arange(16).reshape(4, 4)
     >>> view = blocks_of(arr, 2, 2)
     >>> view[:] = 100
@@ -1739,6 +1743,7 @@ def group_same_or_consecutive_integers(arr):
     list of :class:`numpy.ndarray`
 
     Examples
+    >>> import numpy as np
     >>> arr = np.array([ 2,  3,  4,  7,  8,  9, 10, 11, 15, 16])
     >>> group_same_or_consecutive_integers(arr)
     [array([2, 3, 4]), array([ 7,  8,  9, 10, 11]), array([15, 16])]
@@ -1793,6 +1798,7 @@ def ltruncate_int(value, ndigits):
 
     Examples
     --------
+    >>> from MDAnalysis.lib.util import ltruncate_int
     >>> ltruncate_int(123, 2)
     23
     >>> ltruncate_int(1234, 5)
@@ -1842,6 +1848,7 @@ def static_variables(**kwargs):
     Example
     -------
 
+    >>> from MDAnalysis.lib.util import static_variables
     >>> @static_variables(msg='foo calls', calls=0)
     ... def foo():
     ...     foo.calls += 1
@@ -2013,6 +2020,9 @@ def check_coords(*coord_names, **options):
     Example
     -------
 
+    >>> import numpy as np
+    >>> import MDAnalysis as mda
+    >>> from MDAnalysis.lib.util import check_coords
     >>> @check_coords('coords1', 'coords2', allow_atomgroup=True)
     ... def coordsum(coords1, coords2):
     ...     assert coords1.dtype == np.float32

From 44647a8ec9685ad25241c893024ea7155b1f7a4c Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Tue, 11 Apr 2023 06:20:40 +0200
Subject: [PATCH 09/10] Updates.

---
 package/MDAnalysis/core/universe.py       | 23 +++++++++++++++++------
 package/MDAnalysis/lib/transformations.py | 12 ++++++------
 package/MDAnalysis/lib/util.py            |  7 +++++--
 3 files changed, 28 insertions(+), 14 deletions(-)

diff --git a/package/MDAnalysis/core/universe.py b/package/MDAnalysis/core/universe.py
index e708402085a..7de0e5aef7f 100644
--- a/package/MDAnalysis/core/universe.py
+++ b/package/MDAnalysis/core/universe.py
@@ -806,8 +806,11 @@ def add_TopologyAttr(self, topologyattr, values=None):
         -------
         For example to add bfactors to a Universe:
 
-        >>> u.add_TopologyAttr('bfactors')
-        >>> u.atoms.bfactors
+        >>> import MDAnalysis as mda
+        >>> from MDAnalysis.tests.datafiles import PSF, DCD
+        >>> u = mda.Universe(PSF, DCD)
+        >>> u.add_TopologyAttr('tempfactors')
+        >>> u.atoms.tempfactors
         array([0., 0., 0., ..., 0., 0., 0.])
 
         .. versionchanged:: 0.17.0
@@ -863,8 +866,15 @@ def del_TopologyAttr(self, topologyattr):
         -------
         For example to remove bfactors to a Universe:
 
-        >>> u.del_TopologyAttr('bfactors')
-        >>> hasattr(u.atoms[:3], 'bfactors')
+        >>> import MDAnalysis as mda
+        >>> from MDAnalysis.tests.datafiles import PSF, DCD
+        >>> u = mda.Universe(PSF, DCD)
+        >>> u.add_TopologyAttr('tempfactors')
+        >>> hasattr(u.atoms[:3], 'tempfactors')
+        True
+        >>>
+        >>> u.del_TopologyAttr('tempfactors')
+        >>> hasattr(u.atoms[:3], 'tempfactors')
         False
 
 
@@ -1410,6 +1420,7 @@ def from_smiles(cls, smiles, sanitize=True, addHs=True,
         --------
         To create a Universe with 10 conformers of ethanol:
 
+        >>> from rdkit.Chem import AllChem
         >>> u = mda.Universe.from_smiles('CCO', numConfs=10)
         >>> u
         <Universe with 9 atoms>
@@ -1419,9 +1430,9 @@ def from_smiles(cls, smiles, sanitize=True, addHs=True,
         To use a different conformer generation algorithm, like ETKDGv3:
 
         >>> u = mda.Universe.from_smiles('CCO', rdkit_kwargs=dict(
-            ... params=AllChem.ETKDGv3()))
+        ...      params=AllChem.ETKDGv3()))
         >>> u.trajectory
-        <RDKitReader with 10 frames of 9 atoms>
+        <RDKitReader with 1 frames of 9 atoms>
 
 
         .. versionadded:: 2.0.0
diff --git a/package/MDAnalysis/lib/transformations.py b/package/MDAnalysis/lib/transformations.py
index 6abb8fc6930..826b4efcbfe 100644
--- a/package/MDAnalysis/lib/transformations.py
+++ b/package/MDAnalysis/lib/transformations.py
@@ -110,7 +110,7 @@
 --------
 
 >>> from MDAnalysis.lib.transformations import *
->>> import numpy
+>>> import numpy as np
 >>> alpha, beta, gamma = 0.123, -1.234, 2.345
 >>> origin, xaxis, yaxis, zaxis = (0, 0, 0), (1, 0, 0), (0, 1, 0), (0, 0, 1)
 >>> I = identity_matrix()
@@ -119,7 +119,7 @@
 >>> Rz = rotation_matrix(gamma, zaxis)
 >>> R = concatenate_matrices(Rx, Ry, Rz)
 >>> euler = euler_from_matrix(R, 'rxyz')
->>> numpy.allclose([alpha, beta, gamma], euler)
+>>> np.allclose([alpha, beta, gamma], euler)
 True
 >>> Re = euler_matrix(alpha, beta, gamma, 'rxyz')
 >>> is_same_transform(R, Re)
@@ -138,14 +138,14 @@
 >>> S = scale_matrix(1.23, origin)
 >>> T = translation_matrix((1, 2, 3))
 >>> Z = shear_matrix(beta, xaxis, origin, zaxis)
->>> R = random_rotation_matrix(numpy.random.rand(3))
+>>> R = random_rotation_matrix(np.random.rand(3))
 >>> M = concatenate_matrices(T, R, Z, S)
 >>> scale, shear, angles, trans, persp = decompose_matrix(M)
->>> numpy.allclose(scale, 1.23)
+>>> np.allclose(scale, 1.23)
 True
->>> numpy.allclose(trans, (1, 2, 3))
+>>> np.allclose(trans, (1, 2, 3))
 True
->>> numpy.allclose(shear, (0, math.tan(beta), 0))
+>>> np.allclose(shear, (0, math.tan(beta), 0))
 True
 >>> is_same_transform(R, euler_matrix(axes='sxyz', *angles))
 True
diff --git a/package/MDAnalysis/lib/util.py b/package/MDAnalysis/lib/util.py
index d3e08820a4f..fdc8d3b0b38 100644
--- a/package/MDAnalysis/lib/util.py
+++ b/package/MDAnalysis/lib/util.py
@@ -1627,7 +1627,9 @@ def unique_rows(arr, return_index=False):
     >>> a = np.array([[0, 1], [1, 2], [1, 2], [0, 1], [2, 3]])
     >>> b = unique_rows(a)
     >>> b
-    array([[0, 1], [1, 2], [2, 3]])
+    array([[0, 1],
+           [1, 2],
+           [2, 3]])
 
     See Also
     --------
@@ -2022,6 +2024,7 @@ def check_coords(*coord_names, **options):
 
     >>> import numpy as np
     >>> import MDAnalysis as mda
+    >>> from MDAnalysis.tests.datafiles import PSF, DCD
     >>> from MDAnalysis.lib.util import check_coords
     >>> @check_coords('coords1', 'coords2', allow_atomgroup=True)
     ... def coordsum(coords1, coords2):
@@ -2044,7 +2047,7 @@ def check_coords(*coord_names, **options):
     >>>
     >>> # automatic shape checking:
     >>> coordsum(np.zeros(3), np.ones(6))
-    ValueError: coordsum(): coords2.shape must be (3,) or (n, 3), got (6,).
+    ValueError: coordsum(): coords1, coords2 must contain the same number of coordinates, got [3341, 10].
 
 
     .. versionadded:: 0.19.0

From 08fc1826dfdb398e104598f146f8a707a51adead Mon Sep 17 00:00:00 2001
From: ahmed_salah <medoghonime@gmail.com>
Date: Tue, 11 Apr 2023 09:19:18 +0200
Subject: [PATCH 10/10] Update util.py

---
 package/MDAnalysis/lib/util.py | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/package/MDAnalysis/lib/util.py b/package/MDAnalysis/lib/util.py
index fdc8d3b0b38..4bf21361a45 100644
--- a/package/MDAnalysis/lib/util.py
+++ b/package/MDAnalysis/lib/util.py
@@ -2042,12 +2042,18 @@ def check_coords(*coord_names, **options):
     >>>
     >>> # automatic handling of AtomGroups
     >>> u = mda.Universe(PSF, DCD)
-    >>> coordsum(u.atoms, u.select_atoms("index 1 to 10"))
-    ...
+    >>> try:
+    ...     coordsum(u.atoms, u.select_atoms("index 1 to 10"))
+    ... except ValueError as err:
+    ...     err
+    ValueError('coordsum(): coords1, coords2 must contain the same number of coordinates, got [3341, 10].')
     >>>
     >>> # automatic shape checking:
-    >>> coordsum(np.zeros(3), np.ones(6))
-    ValueError: coordsum(): coords1, coords2 must contain the same number of coordinates, got [3341, 10].
+    >>> try:
+    ...     coordsum(np.zeros(3), np.ones(6))
+    ... except ValueError as err:
+    ...     err
+    ValueError('coordsum(): coords2.shape must be (3,) or (n, 3), got (6,)')
 
 
     .. versionadded:: 0.19.0