Friendpaste

--- Revision 613064313065
+++ Revision 313835323131
@@ -1,77 +1,1 @@
-def dijkstra(graph, start, end):
-    """
-    Dijkstra's algorithm Python implementation.
-    
-    Arguments:
-        graph: Dictionnary of dictionnary (keys are vertices).
-        start: Start vertex.
-        end: End vertex.
-    
-    Output:
-        List of vertices from the beggining to the end.
-        
-    Example:
-        
-    >>> graph = {
-    ...     'A': {'B': 10, 'D': 4, 'F': 10},
-    ...     'B': {'E': 5, 'J': 10, 'I': 17},
-    ...     'C': {'A': 4, 'D': 10, 'E': 16},
-    ...     'D': {'F': 12, 'G': 21},
-    ...     'E': {'G': 4},
-    ...     'F': {'H': 3},
-    ...     'G': {'J': 3},
-    ...     'H': {'G': 3, 'J': 5},
-    ...     'I': {},
-    ...     'J': {'I': 8},
-    ... }    
-    >>> dijkstra(graph, 'C', 'I')
-    ['C', 'A', 'B', 'I']
-    
-    """
-    
-    D = {} # Final distances dict
-    P = {} # Predecessor dict
-    
-    # Fill the dicts with default values
-    for node in graph.keys():
-        D[node] = -1 # Vertices are unreachable
-        P[node] = "" # Vertices have no predecessors
-        
-    D[start] = 0 # The start vertex needs no move
-    
-    unseen_nodes = graph.keys() # All nodes are unseen
-    
-    while len(unseen_nodes) > 0:
-        # Select the node with the lowest value in D (final distance)
-        shortest = None
-        node = ''
-        for temp_node in unseen_nodes:
-            if shortest == None:
-                shortest = D[temp_node]
-                node = temp_node
-            elif D[temp_node] < shortest:
-                shortest = D[temp_node]
-                node = temp_node
-                
-        # Remove the selected node from unseen_nodes
-        unseen_nodes.remove(node)
-        
-        # For each child (ie: connected vertex) of the current node
-        for child_node, child_value in graph[node].items():
-            if D[child_node] < D[node] + child_value:
-                D[child_node] = D[node] + child_value
-                # To go to child_node, you have to go through node
-                P[child_node] = node
-                
-    # Set a clean path
-    path = []
-    
-    # We begin from the end
-    node = end
-    # While we are not arrived at the beggining
-    while not (node == start):
-        path.insert(0, node) # Insert the predecessor of the current node
-        node = P[node] # The current node becomes its predecessor
-    
-    path.insert(0, start) # Finally, insert the start vertex
-    return path
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a	b
0		-	def dijkstra(graph, start, end):
0		-	"""
0		-	Dijkstra's algorithm Python implementation.
0		-
0		-	Arguments:
0		-	graph: Dictionnary of dictionnary (keys are vertices).
0		-	start: Start vertex.
0		-	end: End vertex.
0		-
0		-	Output:
0		-	List of vertices from the beggining to the end.
0		-
0		-	Example:
0		-
0		-	>>> graph = {
0		-	... 'A': {'B': 10, 'D': 4, 'F': 10},
0		-	... 'B': {'E': 5, 'J': 10, 'I': 17},
0		-	... 'C': {'A': 4, 'D': 10, 'E': 16},
0		-	... 'D': {'F': 12, 'G': 21},
0		-	... 'E': {'G': 4},
0		-	... 'F': {'H': 3},
0		-	... 'G': {'J': 3},
0		-	... 'H': {'G': 3, 'J': 5},
0		-	... 'I': {},
0		-	... 'J': {'I': 8},
0		-	... }
0		-	>>> dijkstra(graph, 'C', 'I')
0		-	['C', 'A', 'B', 'I']
0		-
0		-	"""
0		-
0		-	D = {} # Final distances dict
0		-	P = {} # Predecessor dict
0		-
0		-	# Fill the dicts with default values
0		-	for node in graph.keys():
0		-	D[node] = -1 # Vertices are unreachable
0		-	P[node] = "" # Vertices have no predecessors
0		-
0		-	D[start] = 0 # The start vertex needs no move
0		-
0		-	unseen_nodes = graph.keys() # All nodes are unseen
0		-
0		-	while len(unseen_nodes) > 0:
0		-	# Select the node with the lowest value in D (final distance)
0		-	shortest = None
0		-	node = ''
0		-	for temp_node in unseen_nodes:
0		-	if shortest == None:
0		-	shortest = D[temp_node]
0		-	node = temp_node
0		-	elif D[temp_node] < shortest:
0		-	shortest = D[temp_node]
0		-	node = temp_node
0		-
0		-	# Remove the selected node from unseen_nodes
0		-	unseen_nodes.remove(node)
0		-
0		-	# For each child (ie: connected vertex) of the current node
0		-	for child_node, child_value in graph[node].items():
0		-	if D[child_node] < D[node] + child_value:
0		-	D[child_node] = D[node] + child_value
0		-	# To go to child_node, you have to go through node
0		-	P[child_node] = node
0		-
0		-	# Set a clean path
0		-	path = []
0		-
0		-	# We begin from the end
0		-	node = end
0		-	# While we are not arrived at the beggining
0		-	while not (node == start):
0		-	path.insert(0, node) # Insert the predecessor of the current node
0		-	node = P[node] # The current node becomes its predecessor
0		-
0		-	path.insert(0, start) # Finally, insert the start vertex
0		-	return path
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