Fix issues caught by pylint

Issue:
https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/clustering.gmi

* Fix a myriad of issues caught by pylint to ensure the code passes all tests.

4 files changed, 335 insertions, 219 deletions

diff --git a/gn3/computations/correlations2.py b/gn3/computations/correlations2.py
index 6c456db..93db3fa 100644
--- a/gn3/computations/correlations2.py
+++ b/gn3/computations/correlations2.py
@@ -1,15 +1,25 @@
+"""
+DESCRIPTION:
+    TODO: Add a description for the module
+
+FUNCTIONS:
+compute_correlation:
+    TODO: Describe what the function does..."""
+
 from math import sqrt
 from functools import reduce
 ## From GN1: mostly for clustering and heatmap generation
 
-def items_with_values(dbdata, userdata):
+def __items_with_values(dbdata, userdata):
     """Retains only corresponding items in the data items that are not `None` values.
-This should probably be renamed to something sensible"""
+    This should probably be renamed to something sensible"""
     def both_not_none(item1, item2):
+        """Check that both items are not the value `None`."""
         if (item1 is not None) and (item2 is not None):
             return (item1, item2)
         return None
     def split_lists(accumulator, item):
+        """Separate the 'x' and 'y' items."""
         return [accumulator[0] + [item[0]], accumulator[1] + [item[1]]]
     return reduce(
         split_lists,
@@ -17,19 +27,24 @@ This should probably be renamed to something sensible"""
         [[], []])
 
 def compute_correlation(dbdata, userdata):
-    x, y = items_with_values(dbdata, userdata)
-    if len(x) < 6:
-        return (0.0, len(x))
-    meanx = sum(x)/len(x)
-    meany = sum(y)/len(y)
+    """Compute some form of correlation.
+
+    This is extracted from
+    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/utility/webqtlUtil.py#L622-L647
+    """
+    x_items, y_items = __items_with_values(dbdata, userdata)
+    if len(x_items) < 6:
+        return (0.0, len(x_items))
+    meanx = sum(x_items)/len(x_items)
+    meany = sum(y_items)/len(y_items)
     def cal_corr_vals(acc, item):
         xitem, yitem = item
         return [
             acc[0] + ((xitem - meanx) * (yitem - meany)),
             acc[1] + ((xitem - meanx) * (xitem - meanx)),
             acc[2] + ((yitem - meany) * (yitem - meany))]
-    xyd, sxd, syd = reduce(cal_corr_vals, zip(x, y), [0.0, 0.0, 0.0])
+    xyd, sxd, syd = reduce(cal_corr_vals, zip(x_items, y_items), [0.0, 0.0, 0.0])
     try:
-        return ((xyd/(sqrt(sxd)*sqrt(syd))), len(x))
-    except ZeroDivisionError as zde:
-        return(0, len(x))
+        return ((xyd/(sqrt(sxd)*sqrt(syd))), len(x_items))
+    except ZeroDivisionError:
+        return(0, len(x_items))
diff --git a/gn3/computations/slink.py b/gn3/computations/slink.py
index 8d51f29..4aac6b3 100644
--- a/gn3/computations/slink.py
+++ b/gn3/computations/slink.py
@@ -7,13 +7,14 @@ slink:
     TODO: Describe what the function does...
 """
 import logging
-from functools import partial
 
 class LengthError(BaseException):
-    pass
+    """Raised whenever child lists/tuples are not the same length as the parent
+    list of tuple."""
 
 class MirrorError(BaseException):
-    pass
+    """Raised if the distance from child A to child B is not the same as the
+    distance from child B to child A."""
 
 def __is_list_or_tuple(item):
     return type(item) in [list, tuple]
@@ -50,19 +51,20 @@ def __raise_valueerror_if_child_list_distance_from_itself_is_not_zero(lists):
 def __raise_mirrorerror_of_distances_one_way_are_not_same_other_way(lists):
     """Check that the distance from A to B, is the same as the distance from B to A.
 If the two distances are different, throw an exception."""
-    for i in range(len(lists)):
-        for j in range(len(lists)):
-            if lists[i][j] != lists[j][i]:
-                raise MirrorError(
-                    ("Distance from one child({}) to the other ({}) "
-                     "should be the same in both directions.").format(
-                         lists[i][j], lists[j][i]))
+    inner_coords = range(len(lists))
+    coords = ((i, j) for i in inner_coords for j in inner_coords)
+    def __is_same_reversed(coord):
+        return lists[coord[0]][coord[1]] == lists[coord[1]][coord[0]]
+    if not all(map(__is_same_reversed, coords)):
+        raise MirrorError((
+            "Distance from one child to the other should be the same in both "
+            "directions."))
 
 def __raise_valueerror_on_negative_distances(lists):
     """Check that distances between 'somethings' are all positive, otherwise,
 raise an exception."""
     def zero_or_positive(val):
-        return val >= 0;
+        return val >= 0
     # flatten lists
     flattened = __flatten_list_of_lists(lists)
     if not all(map(zero_or_positive, flattened)):
@@ -76,7 +78,8 @@ def nearest(lists, i, j):
     Computes shortest distance between member(s) in `i` and member(s) in `j`.
 
     Description:
-    This is 'copied' over from genenetwork1, from https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/slink.py#L42-L64.
+    This is 'copied' over from genenetwork1, from
+    https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/slink.py#L42-L64.
 
     This description should be updated to better describe what 'member' means in
     the context where the function is used.
@@ -108,18 +111,20 @@ def nearest(lists, i, j):
     __raise_mirrorerror_of_distances_one_way_are_not_same_other_way(lists)
     __raise_valueerror_on_negative_distances(lists)
     #### END: Guard Functions ####
-    if type(i) == int and type(j) == int: # From member i to member j
+    if isinstance(i, int) and isinstance(j, int): # From member i to member j
         return lists[i][j]
-    elif type(i) == int and __is_list_or_tuple(j):
+
+    if isinstance(i, int) and __is_list_or_tuple(j):
         return min(map(lambda j_new: nearest(lists, i, j_new), j[:-1]))
-    elif type(j) == int and __is_list_or_tuple(i):
+    if isinstance(j, int) and __is_list_or_tuple(i):
         return min(map(lambda i_new: nearest(lists, i_new, j), i[:-1]))
-    elif __is_list_or_tuple(i) and __is_list_or_tuple(j):
+
+    if __is_list_or_tuple(i) and __is_list_or_tuple(j):
         coordinate_pairs = __flatten_list_of_lists(
             [[(itemi, itemj) for itemj in j[:-1]] for itemi in i[:-1]])
         return min(map(lambda x: nearest(lists, x[0], x[1]), coordinate_pairs))
-    else:
-        raise ValueError("member values (i or j) should be lists/tuples of integers or integers")
+
+    raise ValueError("member values (i or j) should be lists/tuples of integers or integers")
 
 def slink(lists):
     """
@@ -144,36 +149,39 @@ def slink(lists):
     """
     try:
         size = len(lists)
-        listindex = range(size)
         listindexcopy = list(range(size))
-        listscopy = [[item for item in child] for child in lists]
-        initSize = size
+        listscopy = [child[:] for child in lists]
+        init_size = size
         candidate = []
-        while initSize >2:
+        while init_size > 2:
             mindist = 1e10
-            for i in range(initSize):
-                for j in range(i+1,initSize):
+            for i in range(init_size):
+                for j in range(i+1, init_size):
                     if listscopy[i][j] < mindist:
-                        mindist =  listscopy[i][j]
-                        candidate=[[i,j]]
+                        mindist = listscopy[i][j]
+                        candidate = [[i, j]]
                     elif listscopy[i][j] == mindist:
-                        mindist =  listscopy[i][j]
-                        candidate.append([i,j])
+                        mindist = listscopy[i][j]
+                        candidate.append([i, j])
                     else:
                         pass
-            newmem = (listindexcopy[candidate[0][0]],listindexcopy[candidate[0][1]],mindist)
+            newmem = (
+                listindexcopy[candidate[0][0]], listindexcopy[candidate[0][1]],
+                mindist)
             listindexcopy.pop(candidate[0][1])
             listindexcopy[candidate[0][0]] = newmem
 
-            initSize -= 1
-            for i in range(initSize):
-                for j in range(i+1,initSize):
-                    listscopy[i][j] = nearest(lists,listindexcopy[i],listindexcopy[j])
+            init_size -= 1
+            for i in range(init_size):
+                for j in range(i+1, init_size):
+                    listscopy[i][j] = nearest(
+                        lists, listindexcopy[i], listindexcopy[j])
                     listscopy[j][i] = listscopy[i][j]
-        listindexcopy.append(nearest(lists,listindexcopy[0],listindexcopy[1]))
+        listindexcopy.append(
+            nearest(lists, listindexcopy[0], listindexcopy[1]))
         return listindexcopy
-    except Exception as e:
-        # TODO: Look into making the logging log output to the system's
-        #    configured logger(s)
-        logging.warning("Exception: {}, {}".format(type(e), e))
+    except (LengthError, MirrorError, TypeError, IndexError) as exc:
+        # Look into making the logging log output to the system's
+        #   configured logger(s)
+        logging.warning("Exception: %s, %s", type(exc), exc)
         return []
diff --git a/tests/unit/computations/test_correlation.py b/tests/unit/computations/test_correlation.py
index 6153c8a..9450094 100644
--- a/tests/unit/computations/test_correlation.py
+++ b/tests/unit/computations/test_correlation.py
@@ -467,26 +467,28 @@ class TestCorrelation(TestCase):
         self.assertEqual(results, [expected_results])
 
     def test_compute_correlation(self):
-        for dbdata,userdata,expected in [
-                [[None,None,None,None,None,None,None,None,None,None],
-                 [None,None,None,None,None,None,None,None,None,None],
+        """Test that the new correlation function works the same as the original
+        from genenetwork1."""
+        for dbdata, userdata, expected in [
+                [[None, None, None, None, None, None, None, None, None, None],
+                 [None, None, None, None, None, None, None, None, None, None],
                  (0.0, 0)],
-                [[None,None,None,None,None,None,None,None,None,0],
-                 [None,None,None,None,None,None,None,None,None,None],
+                [[None, None, None, None, None, None, None, None, None, 0],
+                 [None, None, None, None, None, None, None, None, None, None],
                  (0.0, 0)],
-                [[None,None,None,None,None,None,None,None,None,0],
-                 [None,None,None,None,None,None,None,None,None,0],
+                [[None, None, None, None, None, None, None, None, None, 0],
+                 [None, None, None, None, None, None, None, None, None, 0],
                  (0.0, 1)],
-                [[0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,0],
+                [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
                  (0, 10)],
-                [[9.87,9.87,9.87,9.87,9.87,9.87,9.87,9.87,9.87,9.87],
-                 [9.87,9.87,9.87,9.87,9.87,9.87,9.87,9.87,9.87,9.87],
+                [[9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87],
+                 [9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87, 9.87],
                  (0.9999999999999998, 10)],
-                [[9.3,2.2,5.4,7.2,6.4,7.6,3.8,1.8,8.4,0.2],
-                 [0.6,3.97,5.82,8.21,1.65,4.55,6.72,9.5,7.33,2.34],
+                [[9.3, 2.2, 5.4, 7.2, 6.4, 7.6, 3.8, 1.8, 8.4, 0.2],
+                 [0.6, 3.97, 5.82, 8.21, 1.65, 4.55, 6.72, 9.5, 7.33, 2.34],
                  (-0.12720361919462056, 10)],
-                [[0,1,2,3,4,5,6,7,8,9],
-                 [None,None,None,None,2,None,None,3,None,None],
+                [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
+                 [None, None, None, None, 2, None, None, 3, None, None],
                  (0.0, 2)]]:
             with self.subTest(dbdata=dbdata, userdata=userdata):
-                self.assertEqual(compute_correlation(dbdata,userdata), expected)
+                self.assertEqual(compute_correlation(dbdata, userdata), expected)
diff --git a/tests/unit/computations/test_slink.py b/tests/unit/computations/test_slink.py
index 5627767..995393b 100644
--- a/tests/unit/computations/test_slink.py
+++ b/tests/unit/computations/test_slink.py
@@ -1,5 +1,4 @@
 """Module contains tests for slink"""
-import unittest
 from unittest import TestCase
 
 from gn3.computations.slink import slink
@@ -11,210 +10,302 @@ class TestSlink(TestCase):
     """Class for testing slink functions"""
 
     def test_nearest_expects_list_of_lists(self):
+        """Test that function only accepts a list of lists."""
         # This might be better handled with type-hints and mypy
         for item in [9, "some string", 5.432,
-                     [1,2,3], ["test", 7.4]]:
+                     [1, 2, 3], ["test", 7.4]]:
             with self.subTest(item=item):
                 with self.assertRaises(ValueError, msg="Expected list or tuple"):
                     nearest(item, 1, 1)
 
     def test_nearest_does_not_allow_empty_lists(self):
+        """Test that function does not accept an empty list, or any of the child
+        lists to be empty."""
         for lst in [[],
-                    [[],[]],
-                    [[],[],[]],
-                    [[0, 1, 2],[],[1, 2, 0]]]:
+                    [[], []],
+                    [[], [], []],
+                    [[0, 1, 2], [], [1, 2, 0]]]:
             with self.subTest(lst=lst):
                 with self.assertRaises(ValueError):
                     nearest(lst, 1, 1)
 
-    def test_nearest_expects_exception_if_all_child_lists_are_not_of_equal_length_to_length_of_parent_list(self):
-        for lst in [[[0,1]],
-                    [[0,1,2],[3,4,5]],
-                    [[0,1,2,3],[4,5,6],[7,8,9,0]],
-                    [[0,1,2,3,4],[5,6,7,8,9],[1,2,3,4,5],[2,3],[3,4,5,6,7]]]:
+    def test_nearest_expects_children_are_same_length_as_parent(self):
+        """Test that children lists are same length as parent list."""
+        for lst in [[[0, 1]],
+                    [[0, 1, 2], [3, 4, 5]],
+                    [[0, 1, 2, 3], [4, 5, 6], [7, 8, 9, 0]],
+                    [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [1, 2, 3, 4, 5], [2, 3],
+                     [3, 4, 5, 6, 7]]]:
             with self.subTest(lst=lst):
                 with self.assertRaises(LengthError):
                     nearest(lst, 1, 1)
 
-    def test_nearest_expects_exception_if_distance_of_child_from_itself_is_not_zero(self):
+    def test_nearest_expects_member_is_zero_distance_from_itself(self):
+        """Test that distance of a member from itself is zero"""
         for lst in [[[1]],
-                    [[1,2],[3,4]],
-                    [1,0,0],[0,0,5],[0,3,4],
-                    [0,0,0,0],[0,0,3,3],[0,1,2,3],[0,3,2,0]]:
+                    [[1, 2], [3, 4]],
+                    [1, 0, 0], [0, 0, 5], [0, 3, 4],
+                    [0, 0, 0, 0], [0, 0, 3, 3], [0, 1, 2, 3], [0, 3, 2, 0]]:
             with self.subTest(lst=lst):
                 with self.assertRaises(ValueError):
                     nearest(lst, 1, 1)
 
-    def test_nearest_expects_exception_if_distance_from_child_a_to_child_b_is_not_distance_from_child_b_to_child_a(self):
-        for lst in [[[0,1],[2,0]],
-                    [[0,1,2],[1,0,3],[9,7,0]],
-                    [[0,1,2,3],[7,0,2,3],[2,3,0,1],[8,9,5,0]]]:
+    def test_nearest_expects_distance_atob_is_equal_to_distance_btoa(self):
+        """Test that the distance from member A to member B is the same as that
+        from member B to member A."""
+        for lst in [[[0, 1], [2, 0]],
+                    [[0, 1, 2], [1, 0, 3], [9, 7, 0]],
+                    [[0, 1, 2, 3], [7, 0, 2, 3], [2, 3, 0, 1], [8, 9, 5, 0]]]:
             with self.subTest(lst=lst):
                 with self.assertRaises(MirrorError):
                     nearest(lst, 1, 1)
 
     def test_nearest_expects_zero_or_positive_distances(self):
+        """Test that all distances are either zero, or greater than zero."""
         # Based on:
         # https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/slink.py#L87-L89
-        for lst in [[[0,-1,2,3],[-1,0,3,4],[2,3,0,5],[3,4,5,0]],
-                    [[0,1,-2,3],[1,0,3,4],[-2,3,0,5],[3,4,5,0]],
-                    [[0,1,2,3],[1,0,-3,4],[2,-3,0,5],[3,4,5,0]],
-                    [[0,1,2,-3],[1,0,3,4],[2,3,0,5],[-3,4,5,0]],
-                    [[0,1,2,3],[1,0,3,-4],[2,3,0,5],[3,-4,5,0]],
-                    [[0,1,2,3],[1,0,3,4],[2,3,0,-5],[3,4,-5,0]]]:
+        for lst in [[[0, -1, 2, 3], [-1, 0, 3, 4], [2, 3, 0, 5], [3, 4, 5, 0]],
+                    [[0, 1, -2, 3], [1, 0, 3, 4], [-2, 3, 0, 5], [3, 4, 5, 0]],
+                    [[0, 1, 2, 3], [1, 0, -3, 4], [2, -3, 0, 5], [3, 4, 5, 0]],
+                    [[0, 1, 2, -3], [1, 0, 3, 4], [2, 3, 0, 5], [-3, 4, 5, 0]],
+                    [[0, 1, 2, 3], [1, 0, 3, -4], [2, 3, 0, 5], [3, -4, 5, 0]],
+                    [[0, 1, 2, 3], [1, 0, 3, 4], [2, 3, 0, -5], [3, 4, -5, 0]]]:
             with self.subTest(lst=lst):
                 with self.assertRaises(ValueError, msg="Distances should be positive."):
                     nearest(lst, 1, 1)
 
     def test_nearest_returns_shortest_distance_given_coordinates_to_both_group_members(self):
+        """Test that the shortest distance is returned."""
         # This test is named wrong - at least I think it is, from the expected results
         # This tests distance when both `i`, and `j` are integers
         # We still need to add tests for when (either one/both) (is/are) not (an) integer(s)
         # https://github.com/genenetwork/genenetwork1/blob/master/web/webqtl/heatmap/slink.py#L39-L40
-        for lst, i, j, expected in [[[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     0,0,0],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     0,1,9],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     0,2,3],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     0,3,6],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     0,4,11],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     1,0,9],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     1,1,0],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     1,2,7],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     1,3,5],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     1,4,10],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     2,0,3],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     2,1,7],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     2,2,0],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     2,3,9],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     2,4,2],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     3,0,6],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     3,1,5],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     3,2,9],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     3,3,0],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     3,4,8],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     4,0,11],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     4,1,10],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     4,2,2],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     4,3,8],
-                                    [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                                     4,4,0],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     0,0,0],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     0,1,9],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     0,2,5.5],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     0,3,6],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     0,4,11],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     1,0,9],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     1,1,0],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     1,2,7],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     1,3,5],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     1,4,10],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     2,0,5.5],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     2,1,7],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     2,2,0],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     2,3,9],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     2,4,2],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     3,0,6],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     3,1,5],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     3,2,9],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     3,3,0],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     3,4,3],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     4,0,11],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     4,1,10],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     4,2,2],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     4,3,3],
-                                    [[[0,9,5.5,6,11],[9,0,7,5,10],[5.5,7,0,9,2],[6,5,9,0,3],[11,10,2,3,0]],
-                                     4,4,0]]:
+        for lst, i, j, expected in [
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 0, 0, 0],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 0, 1, 9],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 0, 2, 3],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 0, 3, 6],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 0, 4, 11],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 1, 0, 9],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 1, 1, 0],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 1, 2, 7],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 1, 3, 5],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 1, 4, 10],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 2, 0, 3],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 2, 1, 7],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 2, 2, 0],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 2, 3, 9],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 2, 4, 2],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 3, 0, 6],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 3, 1, 5],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 3, 2, 9],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 3, 3, 0],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 3, 4, 8],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 4, 0, 11],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 4, 1, 10],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 4, 2, 2],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 4, 3, 8],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 4, 4, 0],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 0, 0, 0],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 0, 1, 9],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 0, 2, 5.5],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 0, 3, 6],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 0, 4, 11],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 1, 0, 9],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 1, 1, 0],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 1, 2, 7],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 1, 3, 5],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 1, 4, 10],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 2, 0, 5.5],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 2, 1, 7],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 2, 2, 0],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 2, 3, 9],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 2, 4, 2],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 3, 0, 6],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 3, 1, 5],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 3, 2, 9],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 3, 3, 0],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 3, 4, 3],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 4, 0, 11],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 4, 1, 10],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 4, 2, 2],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 4, 3, 3],
+                [[[0, 9, 5.5, 6, 11], [9, 0, 7, 5, 10], [5.5, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 3], [11, 10, 2, 3, 0]],
+                 4, 4, 0]]:
             with self.subTest(lst=lst):
                 self.assertEqual(nearest(lst, i, j), expected)
 
-    def test_given_a_list_or_tuple_of_members_distances_and_a_coordinate_find_closest_member_to_member_at_coordinate(self):
-        for md, ml, mc, ed in [
-                [[[0,9,3],[9,0,7],[3,7,0]],(0,2,3),1,7],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],[0,1,2,3,4],3,0],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],[0,1,2,4],3,5],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],[0,2,4],3,6],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],[2,4],3,9]]:
+    def test_nearest_gives_shortest_distance_between_list_of_members_and_member(self):
+        """Test that the shortest distance is returned."""
+        for members_distances, members_list, member_coordinate, expected_distance in [
+                [[[0, 9, 3], [9, 0, 7], [3, 7, 0]], (0, 2, 3), 1, 7],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]], [0, 1, 2, 3, 4], 3, 0],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]], [0, 1, 2, 4], 3, 5],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]], [0, 2, 4], 3, 6],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]], [2, 4], 3, 9]]:
             with self.subTest(
-                    members_distances=md, members_list=ml, member_coordinate=mc,
-                    expected_distance=ed):
-                self.assertEqual(nearest(md, ml, mc), ed)
-                self.assertEqual(nearest(md, mc, ml), ed)
+                    members_distances=members_distances,
+                    members_list=members_list,
+                    member_coordinate=member_coordinate,
+                    expected_distance=expected_distance):
+                self.assertEqual(
+                    nearest(
+                        members_distances, members_list, member_coordinate),
+                    expected_distance)
+                self.assertEqual(
+                    nearest(
+                        members_distances, member_coordinate, members_list),
+                    expected_distance)
 
-    def test_given_2_lists_or_tuples_of_members_distances_nearest_returns_shortest_distance(self):
-        for md, ml, mc, ed in [
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                 [0,1,2,3,4],[0,1,2,3,4],0],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                 [0,1],[3,4],6],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                 [0,1],[2,3,4],3],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],[11,10,2,8,0]],
-                 [0,2],[3,4],6]]:
+    def test_nearest_returns_shortest_distance_given_two_lists_of_members(self):
+        """Test that the shortest distance is returned."""
+        for members_distances, members_list, member_list2, expected_distance in [
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 [0, 1, 2, 3, 4], [0, 1, 2, 3, 4], 0],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 [0, 1], [3, 4], 6],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 [0, 1], [2, 3, 4], 3],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8], [11, 10, 2, 8, 0]],
+                 [0, 2], [3, 4], 6]]:
             with self.subTest(
-                    members_distances=md, members_list=ml, member_coordinate=mc,
-                    expected_distance=ed):
-                self.assertEqual(nearest(md, ml, mc), ed)
-                self.assertEqual(nearest(md, mc, ml), ed)
+                    members_distances=members_distances,
+                    members_list=members_list,
+                    member_list2=member_list2,
+                    expected_distance=expected_distance):
+                self.assertEqual(
+                    nearest(
+                        members_distances, members_list, member_list2),
+                    expected_distance)
+                self.assertEqual(
+                    nearest(
+                        members_distances, member_list2, members_list),
+                    expected_distance)
 
     def test_slink_wrong_data_returns_empty_list(self):
+        """Test that empty list is returned for wrong data."""
         for data in [1, "test", [], 2.945, nearest, [0]]:
             with self.subTest(data=data):
                 self.assertEqual(slink(data), [])
 
     def test_slink_with_data(self):
+        """Test slink with example data, and expected results for each data
+        sample."""
         for data, expected in [
-                [[[0,9],[9,0]],[0,1,9]],
-                [[[0,9,3],[9,0,7],[3,7,0]],[(0,2,3),1,7]],
-                [[[0,9,3,6],[9,0,7,5],[3,7,0,9],[6,5,9,0]],[(0,2,3),(1,3,5),6]],
-                [[[0,9,3,6,11],[9,0,7,5,10],[3,7,0,9,2],[6,5,9,0,8],
-                  [11,10,2,8,0]],
-                 [(0,(2,4,2),3),(1,3,5),6]]]:
+                [[[0, 9], [9, 0]], [0, 1, 9]],
+                [[[0, 9, 3], [9, 0, 7], [3, 7, 0]], [(0, 2, 3), 1, 7]],
+                [[[0, 9, 3, 6], [9, 0, 7, 5], [3, 7, 0, 9], [6, 5, 9, 0]],
+                 [(0, 2, 3), (1, 3, 5), 6]],
+                [[[0, 9, 3, 6, 11], [9, 0, 7, 5, 10], [3, 7, 0, 9, 2],
+                  [6, 5, 9, 0, 8],
+                  [11, 10, 2, 8, 0]],
+                 [(0, (2, 4, 2), 3), (1, 3, 5), 6]]]:
             with self.subTest(data=data):
                 self.assertEqual(slink(data), expected)