Enhancement in sorting algorithms

pydatastructs/linear_data_structures/algorithms.py

@@ -1,6 +1,6 @@
 from pydatastructs.linear_data_structures.arrays import (
     OneDimensionalArray, DynamicArray)
-from pydatastructs.utils.misc_util import _check_type
+from pydatastructs.utils.misc_util import _check_type, _comp
 from concurrent.futures import ThreadPoolExecutor
 from math import log, floor
 
@@ -11,18 +11,16 @@
 def _merge(array, sl, el, sr, er, end, comp):
     l, r = [],  []
     for i in range(sl, el + 1):
-        if (i <= end and
-            array[i] is not None):
+        if i <= end:
             l.append(array[i])
             array[i] = None
     for i in range(sr, er + 1):
-        if (i <= end and
-            array[i] is not None):
+        if i <= end:
             r.append(array[i])
             array[i] = None
     i, j, k = 0, 0, sl
     while i < len(l) and j < len(r):
-        if comp(l[i], r[j]):
+        if _comp(l[i], r[j], comp):
             array[k] = l[i]
             i += 1
         else:

pydatastructs/linear_data_structures/arrays.py

@@ -217,11 +217,16 @@ def _modify(self, force=False):
         Contracts the array if Num(T)/Size(T) falls
         below load factor.
         """
-        if (self._num/self._size < self._load_factor) or force:
+        if force:
+            i = -1
+            while self._data[i] is None:
+                i -= 1
+            self._last_pos_filled = i%self._size
+        if (self._num/self._size < self._load_factor):
             arr_new = OneDimensionalArray(self._dtype, 2*self._num + 1)
             j = 0
             for i in range(self._last_pos_filled + 1):
-                if self[i] is not None:
+                if self._data[i] is not None:
                     arr_new[j] = self[i]
                     j += 1
             self._last_pos_filled = j - 1

pydatastructs/linear_data_structures/tests/test_algorithms.py

@@ -13,14 +13,22 @@ def test_merge_sort_parallel():
         arr.append(random.randint(1, 1000))
     for _ in range(n//3):
         arr.delete(random.randint(0, n//2))
-    expected_arr = [686, 779, 102, 134, 362,
-                    448, 480, 548, 228, 688,
-                    247, 373, 696, None, None,
-                    None, None, None, None,
-                    None, None, None, None,
+    expected_arr = [686, 779, 102, 134, 362, 448,
+                    480, 548, None, None, None,
+                    228, 688, 247, 373, 696, None,
+                    None, None, None, None, None,
+                    None, None, None, None, None,
                     None, None, None, None]
     merge_sort_parallel(arr, 5, start=2, end=10)
     assert arr._data == expected_arr
+    merge_sort_parallel(arr, 5)
+    expected_arr = [102, 134, 228, 247, 362, 373, 448,
+                    480, 548, 686, 688, 696, 779,
+                    None, None, None, None, None, None,
+                    None, None, None, None, None,
+                    None, None, None, None, None, None, None]
+    assert arr._data == expected_arr
+    assert (arr._last_pos_filled, arr._num, arr._size) == (12, 13, 31)
 
     n = random.randint(10, 20)
     arr = OneDimensionalArray(int, n)

pydatastructs/utils/misc_util.py

@@ -301,3 +301,17 @@ def __new__(cls, key, data=None):
         obj.data = data
         obj.parent, obj.size = [None]*2
         return obj
+
+def _comp(u, v, tcomp):
+    """
+    Overloaded comparator for comparing
+    two values where any one of them can be
+    `None`.
+    """
+    if u is None and v is not None:
+        return False
+    elif u is not None and v is None:
+        return True
+    elif u is None and v is None:
+        return False
+    return tcomp(u, v)