Added parallel kruskal algorithm

pydatastructs/graphs/__init__.py

@@ -10,7 +10,8 @@
 from .algorithms import (
     breadth_first_search,
     breadth_first_search_parallel,
-    minimum_spanning_tree
+    minimum_spanning_tree,
+    minimum_spanning_tree_parallel
 )
 
 __all__.extend(algorithms.__all__)

pydatastructs/graphs/algorithms.py

@@ -7,11 +7,13 @@
 from pydatastructs.utils import GraphEdge
 from pydatastructs.miscellaneous_data_structures import DisjointSetForest
 from pydatastructs.graphs.graph import Graph
+from pydatastructs.linear_data_structures.algorithms import merge_sort_parallel
 
 __all__ = [
     'breadth_first_search',
     'breadth_first_search_parallel',
-    'minimum_spanning_tree'
+    'minimum_spanning_tree',
+    'minimum_spanning_tree_parallel'
 ]
 
 def breadth_first_search(
@@ -190,36 +192,109 @@ def _breadth_first_search_parallel_adjacency_list(
 
 _breadth_first_search_parallel_adjacency_matrix = _breadth_first_search_parallel_adjacency_list
 
+def _generate_mst_object(graph):
+    mst = Graph(*[getattr(graph, str(v)) for v in graph.vertices])
+    return mst
+
+def _sort_edges(graph, num_threads=None):
+    edges = list(graph.edge_weights.items())
+    if num_threads is None:
+        sort_key = lambda item: item[1].value
+        return sorted(edges, key=sort_key)
+
+    merge_sort_parallel(edges, num_threads,
+                        comp=lambda u,v: u[1].value <= v[1].value)
+    return edges
+
 def _minimum_spanning_tree_kruskal_adjacency_list(graph):
-    mst = Graph(*[getattr(graph, v) for v in graph.vertices])
-    sort_key = lambda item: item[1].value
+    mst = _generate_mst_object(graph)
     dsf = DisjointSetForest()
     for v in graph.vertices:
         dsf.make_set(v)
-    for _, edge in sorted(graph.edge_weights.items(), key=sort_key):
+    for _, edge in _sort_edges(graph):
         u, v = edge.source.name, edge.target.name
         if dsf.find_root(u) is not dsf.find_root(v):
             mst.add_edge(u, v, edge.value)
             dsf.union(u, v)
     return mst
 
-def _minimum_spanning_tree_kruskal_adjacency_matrix(graph):
-    mst = Graph(*[getattr(graph, str(v)) for v in graph.vertices])
-    sort_key = lambda item: item[1].value
+_minimum_spanning_tree_kruskal_adjacency_matrix = \
+    _minimum_spanning_tree_kruskal_adjacency_list
+
+def minimum_spanning_tree(graph, algorithm):
+    """
+    Computes a minimum spanning tree for the given
+    graph and algorithm.
+
+    Parameters
+    ==========
+
+    graph: Graph
+        The graph whose minimum spanning tree
+        has to be computed.
+    algorithm: str
+        The algorithm which should be used for
+        computing a minimum spanning tree.
+        Currently the following algorithms are
+        supported,
+        'kruskal' -> Kruskal's algorithm as given in
+                     [1].
+
+    Returns
+    =======
+
+    mst: Graph
+        A minimum spanning tree using the implementation
+        same as the graph provided in the input.
+
+    Examples
+    ========
+
+    >>> from pydatastructs import Graph, AdjacencyListGraphNode
+    >>> from pydatastructs import minimum_spanning_tree
+    >>> u = AdjacencyListGraphNode('u')
+    >>> v = AdjacencyListGraphNode('v')
+    >>> G = Graph(u, v)
+    >>> G.add_edge(u.name, v.name, 3)
+    >>> mst = minimum_spanning_tree(G, 'kruskal')
+    >>> u_n = mst.neighbors(u.name)
+    >>> mst.get_edge(u.name, u_n[0].name).value
+    3
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Kruskal%27s_algorithm
+    """
+    import pydatastructs.graphs.algorithms as algorithms
+    func = "_minimum_spanning_tree_" + algorithm + "_" + graph._impl
+    if not hasattr(algorithms, func):
+        raise NotImplementedError(
+        "Currently %s algoithm for %s implementation of graphs "
+        "isn't implemented for finding minimum spanning trees."
+        %(algorithm, graph._impl))
+    return getattr(algorithms, func)(graph)
+
+def _minimum_spanning_tree_parallel_kruskal_adjacency_list(graph, num_threads):
+    mst = _generate_mst_object(graph)
     dsf = DisjointSetForest()
     for v in graph.vertices:
         dsf.make_set(v)
-    for _, edge in sorted(graph.edge_weights.items(), key=sort_key):
+    edges = _sort_edges(graph, num_threads)
+    for _, edge in edges:
         u, v = edge.source.name, edge.target.name
         if dsf.find_root(u) is not dsf.find_root(v):
             mst.add_edge(u, v, edge.value)
             dsf.union(u, v)
     return mst
 
-def minimum_spanning_tree(graph, algorithm):
+_minimum_spanning_tree_parallel_kruskal_adjacency_matrix = \
+    _minimum_spanning_tree_parallel_kruskal_adjacency_list
+
+def minimum_spanning_tree_parallel(graph, algorithm, num_threads):
     """
     Computes a minimum spanning tree for the given
-    graph and algorithm.
+    graph and algorithm using the given number of threads.
 
     Parameters
     ==========
@@ -234,6 +309,8 @@ def minimum_spanning_tree(graph, algorithm):
         supported,
         'kruskal' -> Kruskal's algorithm as given in
                      [1].
+    num_threads: int
+        The number of threads to be used.
 
     Returns
     =======
@@ -246,26 +323,26 @@ def minimum_spanning_tree(graph, algorithm):
     ========
 
     >>> from pydatastructs import Graph, AdjacencyListGraphNode
-    >>> from pydatastructs import minimum_spanning_tree
+    >>> from pydatastructs import minimum_spanning_tree_parallel
     >>> u = AdjacencyListGraphNode('u')
     >>> v = AdjacencyListGraphNode('v')
     >>> G = Graph(u, v)
     >>> G.add_edge(u.name, v.name, 3)
-    >>> mst = minimum_spanning_tree(G, 'kruskal')
+    >>> mst = minimum_spanning_tree_parallel(G, 'kruskal', 3)
     >>> u_n = mst.neighbors(u.name)
     >>> mst.get_edge(u.name, u_n[0].name).value
     3
 
     References
     ==========
 
-    .. [1] https://en.wikipedia.org/wiki/Kruskal%27s_algorithm
+    .. [1] https://en.wikipedia.org/wiki/Kruskal%27s_algorithm#Parallel_algorithm
     """
     import pydatastructs.graphs.algorithms as algorithms
-    func = "_minimum_spanning_tree_" + algorithm + "_" + graph._impl
+    func = "_minimum_spanning_tree_parallel_" + algorithm + "_" + graph._impl
     if not hasattr(algorithms, func):
         raise NotImplementedError(
         "Currently %s algoithm for %s implementation of graphs "
         "isn't implemented for finding minimum spanning trees."
         %(algorithm, graph._impl))
-    return getattr(algorithms, func)(graph)
+    return getattr(algorithms, func)(graph, num_threads)

pydatastructs/graphs/tests/test_algorithms.py

@@ -1,5 +1,6 @@
 from pydatastructs import (breadth_first_search, Graph,
-breadth_first_search_parallel, minimum_spanning_tree)
+breadth_first_search_parallel, minimum_spanning_tree,
+minimum_spanning_tree_parallel)
 
 
 def test_breadth_first_search():
@@ -148,3 +149,30 @@ def _test_minimum_spanning_tree(ds, algorithm):
 
     _test_minimum_spanning_tree("List", "kruskal")
     _test_minimum_spanning_tree("Matrix", "kruskal")
+
+def test_minimum_spanning_tree_parallel():
+
+    def _test_minimum_spanning_tree_parallel(ds, algorithm):
+        import pydatastructs.utils.misc_util as utils
+        GraphNode = getattr(utils, "Adjacency" + ds + "GraphNode")
+        a, b, c, d, e = [GraphNode(x) for x in [0, 1, 2, 3, 4]]
+        graph = Graph(a, b, c, d, e)
+        graph.add_edge(a.name, c.name, 10)
+        graph.add_edge(c.name, a.name, 10)
+        graph.add_edge(a.name, d.name, 7)
+        graph.add_edge(d.name, a.name, 7)
+        graph.add_edge(c.name, d.name, 9)
+        graph.add_edge(d.name, c.name, 9)
+        graph.add_edge(d.name, b.name, 32)
+        graph.add_edge(b.name, d.name, 32)
+        graph.add_edge(d.name, e.name, 23)
+        graph.add_edge(e.name, d.name, 23)
+        mst = minimum_spanning_tree_parallel(graph, algorithm, 3)
+        expected_mst = [('0_3', 7), ('2_3', 9), ('3_4', 23), ('3_1', 32),
+                        ('3_0', 7), ('3_2', 9), ('4_3', 23), ('1_3', 32)]
+        assert len(expected_mst) == 2*len(mst.edge_weights.items())
+        for k, v in mst.edge_weights.items():
+            assert (k, v.value) in expected_mst
+
+    _test_minimum_spanning_tree_parallel("List", "kruskal")
+    _test_minimum_spanning_tree_parallel("Matrix", "kruskal")

pydatastructs/linear_data_structures/algorithms.py

@@ -8,7 +8,7 @@
     'merge_sort_parallel'
 ]
 
-def _merge(array, sl, el, sr, er, end):
+def _merge(array, sl, el, sr, er, end, comp):
     l, r = [],  []
     for i in range(sl, el + 1):
         if (i <= end and
@@ -22,7 +22,7 @@ def _merge(array, sl, el, sr, er, end):
             array[i] = None
     i, j, k = 0, 0, sl
     while i < len(l) and j < len(r):
-        if l[i] <= r[j]:
+        if comp(l[i], r[j]):
             array[k] = l[i]
             i += 1
         else:
@@ -61,6 +61,13 @@ def merge_sort_parallel(array, num_threads, **kwargs):
         is to be sorted.
         Optional, by default the index
         of the last position filled.
+    comp: lambda/function
+        The comparator which is to be used
+        for sorting. If the function returns
+        False then only swapping is performed.
+        Optional, by default, less than or
+        equal to is used for comparing two
+        values.
 
     Examples
     ========
@@ -70,14 +77,18 @@ def merge_sort_parallel(array, num_threads, **kwargs):
     >>> merge_sort_parallel(arr, 3)
     >>> [arr[0], arr[1], arr[2]]
     [1, 2, 3]
+    >>> merge_sort_parallel(arr, 3, comp=lambda u, v: u > v)
+    >>> [arr[0], arr[1], arr[2]]
+    [3, 2, 1]
 
     References
     ==========
 
     .. [1] https://en.wikipedia.org/wiki/Merge_sort
     """
     start = kwargs.get('start', 0)
-    end = kwargs.get('end', array._size - 1)
+    end = kwargs.get('end', len(array) - 1)
+    comp = kwargs.get("comp", lambda u, v: u <= v)
     for size in range(floor(log(end - start + 1, 2)) + 1):
         pow_2 = 2**size
         with ThreadPoolExecutor(max_workers=num_threads) as Executor:
@@ -88,7 +99,7 @@ def merge_sort_parallel(array, num_threads, **kwargs):
                     array,
                     i, i + pow_2 - 1,
                     i + pow_2, i + 2*pow_2 - 1,
-                    end).result()
+                    end, comp).result()
                 i = i + 2*pow_2
 
     if _check_type(array, DynamicArray):

pydatastructs/linear_data_structures/arrays.py

@@ -127,6 +127,9 @@ def fill(self, elem):
         for i in range(self._size):
             self._data[i] = elem
 
+    def __len__(self):
+        return self._size
+
 
 class DynamicArray(Array):
     """

pydatastructs/trees/binary_trees.py

@@ -28,7 +28,7 @@ class BinaryTree(object):
     key
         Required if tree is to be instantiated with
         root otherwise not needed.
-    comp: lambda
+    comp: lambda/function
         Optional, A lambda function which will be used
         for comparison of keys. Should return a
         bool value. By default it implements less