Added counting sort (#280)

Author: czgdp1807

pydatastructs/linear_data_structures/__init__.py

@@ -26,6 +26,7 @@
     brick_sort,
     brick_sort_parallel,
     heapsort,
-    matrix_multiply_parallel
+    matrix_multiply_parallel,
+    counting_sort
 )
 __all__.extend(algorithms.__all__)

pydatastructs/linear_data_structures/algorithms.py

@@ -1,5 +1,5 @@
 from pydatastructs.linear_data_structures.arrays import (
-    OneDimensionalArray, DynamicArray)
+    OneDimensionalArray, DynamicArray, Array)
 from pydatastructs.utils.misc_util import _check_type, _comp
 from concurrent.futures import ThreadPoolExecutor
 from math import log, floor
@@ -9,7 +9,8 @@
     'brick_sort',
     'brick_sort_parallel',
     'heapsort',
-    'matrix_multiply_parallel'
+    'matrix_multiply_parallel',
+    'counting_sort'
 ]
 
 def _merge(array, sl, el, sr, er, end, comp):
@@ -294,6 +295,83 @@ def heapsort(array, **kwargs):
     if _check_type(array, DynamicArray):
         array._modify(force=True)
 
+def counting_sort(array: Array) -> Array:
+    """
+    Performs counting sort on the given array.
+
+    Parameters
+    ==========
+
+    array: Array
+        The array which is to be sorted.
+
+    Returns
+    =======
+
+    output: Array
+        The sorted array.
+
+    Examples
+    ========
+
+    >>> from pydatastructs import DynamicOneDimensionalArray as DODA, counting_sort
+    >>> arr = DODA(int, [5, 78, 1, 0])
+    >>> out = counting_sort(arr)
+    >>> str(out)
+    "['0', '1', '5', '78']"
+    >>> arr.delete(2)
+    >>> out = counting_sort(arr)
+    >>> str(out)
+    "['0', '5', '78']"
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Counting_sort
+
+    Note
+    ====
+
+    Since, counting sort is a non-comparison sorting algorithm,
+    custom comparators aren't allowed.
+    The ouput array doesn't contain any `None` value.
+    """
+    max_val, min_val = array[0], array[0]
+    none_count = 0
+    for i in range(len(array)):
+        if array[i] is not None:
+            if max_val is None or max_val < array[i]:
+                max_val = array[i]
+            if min_val is None or array[i] < min_val:
+                min_val = array[i]
+        else:
+            none_count += 1
+    if min_val is None or max_val is None:
+        return array
+
+    count = [0 for _ in range(max_val - min_val + 1)]
+    for i in range(len(array)):
+        if array[i] is not None:
+            count[array[i] - min_val] += 1
+
+    total = 0
+    for i in range(max_val - min_val + 1):
+        count[i], total = total, count[i] +  total
+
+    output = type(array)(array._dtype,
+                        [array[i] for i in range(len(array))
+                         if array[i] is not None])
+    if _check_type(output, DynamicArray):
+        output._modify(force=True)
+
+    for i in range(len(array)):
+        x = array[i]
+        if x is not None:
+            output[count[x-min_val]] = x
+            count[x-min_val] += 1
+
+    return output
+
 def _matrix_multiply_helper(m1, m2, row, col):
     s = 0
     for i in range(len(m1)):

pydatastructs/linear_data_structures/tests/test_algorithms.py

@@ -1,7 +1,7 @@
 from pydatastructs import (
     merge_sort_parallel, DynamicOneDimensionalArray,
     OneDimensionalArray, brick_sort, brick_sort_parallel,
-    heapsort, matrix_multiply_parallel)
+    heapsort, matrix_multiply_parallel, counting_sort)
 from pydatastructs.utils.raises_util import raises
 import random
 
@@ -53,6 +53,20 @@ def test_brick_sort_parallel():
 def test_heapsort():
     _test_common_sort(heapsort)
 
+def test_counting_sort():
+    random.seed(1000)
+
+    n = random.randint(10, 20)
+    arr = DynamicOneDimensionalArray(int, 0)
+    for _ in range(n):
+        arr.append(random.randint(1, 1000))
+    for _ in range(n//3):
+        arr.delete(random.randint(0, n//2))
+
+    expected_arr = [102, 134, 228, 247, 362, 373, 448,
+                    480, 548, 686, 688, 696, 779]
+    assert counting_sort(arr)._data == expected_arr
+
 def test_matrix_multiply_parallel():
     ODA = OneDimensionalArray