import pdb
"""
The Bellman-Ford algorithm

Graph API:

    iter(graph) gives all nodes
    iter(graph[u]) gives neighbours of u
    graph[u][v] gives weight of edge (u, v)
"""

# Step 1: For each node prepare the destination and predecessor
def initialize(graph, source):
    d = {} # Stands for destination
    p = {} # Stands for predecessor
    for node in graph:
        d[node] = float('Inf') # We start admiting that the rest of nodes are very very far
        p[node] = None
    d[source] = 0 # For the source we know how to reach
    return d, p

def relax(node, neighbour, graph, d, p):
    # If the distance between the node and the neighbour is lower than the one I have now
    if d[neighbour] > d[node] + graph[node][neighbour]:
        # Record this lower distance
        d[neighbour]  = d[node] + graph[node][neighbour]
        p[neighbour] = node

def bellman_ford(graph, source):
    d, p = initialize(graph, source)
    for i in range(len(graph)-1): #Run this until is converges
        for u in graph:
            for v in graph[u]: #For each neighbour of u
                relax(u, v, graph, d, p) #Lets relax it

    # Step 3: check for negative-weight cycles
    for u in graph:
        for v in graph[u]:
            assert d[v] <= d[u] + graph[u][v]

    return d, p


def test():
    graph = {
        'a': {'b': -1, 'c':  4},
        'b': {'c':  3, 'd':  2, 'e':  2},
        'c': {},
        'd': {'b':  1, 'c':  5},
        'e': {'d': -3}
        }

    d, p = bellman_ford(graph, 'a')

    assert d == {
        'a':  0,
        'b': -1,
        'c':  2,
        'd': -2,
        'e':  1
        }

    assert p == {
        'a': None,
        'b': 'a',
        'c': 'b',
        'd': 'e',
        'e': 'b'
        }

if __name__ == '__main__': test()
