annotate env/lib/python3.9/site-packages/networkx/algorithms/flow/tests/test_maxflow_large_graph.py @ 0:4f3585e2f14b draft default tip

"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"

"""Maximum flow algorithms test suite on large graphs.
"""

import os
import pytest

import networkx as nx
from networkx.algorithms.flow import build_flow_dict, build_residual_network
from networkx.algorithms.flow import boykov_kolmogorov
from networkx.algorithms.flow import dinitz
from networkx.algorithms.flow import edmonds_karp
from networkx.algorithms.flow import preflow_push
from networkx.algorithms.flow import shortest_augmenting_path
from networkx.testing import almost_equal

flow_funcs = [
    boykov_kolmogorov,
    dinitz,
    edmonds_karp,
    preflow_push,
    shortest_augmenting_path,
]


def gen_pyramid(N):
    # This graph admits a flow of value 1 for which every arc is at
    # capacity (except the arcs incident to the sink which have
    # infinite capacity).
    G = nx.DiGraph()

    for i in range(N - 1):
        cap = 1.0 / (i + 2)
        for j in range(i + 1):
            G.add_edge((i, j), (i + 1, j), capacity=cap)
            cap = 1.0 / (i + 1) - cap
            G.add_edge((i, j), (i + 1, j + 1), capacity=cap)
            cap = 1.0 / (i + 2) - cap

    for j in range(N):
        G.add_edge((N - 1, j), "t")

    return G


def read_graph(name):
    dirname = os.path.dirname(__file__)
    path = os.path.join(dirname, name + ".gpickle.bz2")
    return nx.read_gpickle(path)


def validate_flows(G, s, t, soln_value, R, flow_func):
    flow_value = R.graph["flow_value"]
    flow_dict = build_flow_dict(G, R)
    errmsg = f"Assertion failed in function: {flow_func.__name__}"
    assert soln_value == flow_value, errmsg
    assert set(G) == set(flow_dict), errmsg
    for u in G:
        assert set(G[u]) == set(flow_dict[u]), errmsg
    excess = {u: 0 for u in flow_dict}
    for u in flow_dict:
        for v, flow in flow_dict[u].items():
            assert flow <= G[u][v].get("capacity", float("inf")), errmsg
            assert flow >= 0, errmsg
            excess[u] -= flow
            excess[v] += flow
    for u, exc in excess.items():
        if u == s:
            assert exc == -soln_value, errmsg
        elif u == t:
            assert exc == soln_value, errmsg
        else:
            assert exc == 0, errmsg


class TestMaxflowLargeGraph:
    def test_complete_graph(self):
        N = 50
        G = nx.complete_graph(N)
        nx.set_edge_attributes(G, 5, "capacity")
        R = build_residual_network(G, "capacity")
        kwargs = dict(residual=R)

        for flow_func in flow_funcs:
            kwargs["flow_func"] = flow_func
            errmsg = f"Assertion failed in function: {flow_func.__name__}"
            flow_value = nx.maximum_flow_value(G, 1, 2, **kwargs)
            assert flow_value == 5 * (N - 1), errmsg

    def test_pyramid(self):
        N = 10
        # N = 100 # this gives a graph with 5051 nodes
        G = gen_pyramid(N)
        R = build_residual_network(G, "capacity")
        kwargs = dict(residual=R)

        for flow_func in flow_funcs:
            kwargs["flow_func"] = flow_func
            errmsg = f"Assertion failed in function: {flow_func.__name__}"
            flow_value = nx.maximum_flow_value(G, (0, 0), "t", **kwargs)
            assert almost_equal(flow_value, 1.0), errmsg

    def test_gl1(self):
        G = read_graph("gl1")
        s = 1
        t = len(G)
        R = build_residual_network(G, "capacity")
        kwargs = dict(residual=R)

        # do one flow_func to save time
        flow_func = flow_funcs[0]
        validate_flows(G, s, t, 156545, flow_func(G, s, t, **kwargs), flow_func)

    #        for flow_func in flow_funcs:
    #            validate_flows(G, s, t, 156545, flow_func(G, s, t, **kwargs),
    #                           flow_func)

    @pytest.mark.slow
    def test_gw1(self):
        G = read_graph("gw1")
        s = 1
        t = len(G)
        R = build_residual_network(G, "capacity")
        kwargs = dict(residual=R)

        for flow_func in flow_funcs:
            validate_flows(G, s, t, 1202018, flow_func(G, s, t, **kwargs), flow_func)

    def test_wlm3(self):
        G = read_graph("wlm3")
        s = 1
        t = len(G)
        R = build_residual_network(G, "capacity")
        kwargs = dict(residual=R)

        # do one flow_func to save time
        flow_func = flow_funcs[0]
        validate_flows(G, s, t, 11875108, flow_func(G, s, t, **kwargs), flow_func)

    #        for flow_func in flow_funcs:
    #            validate_flows(G, s, t, 11875108, flow_func(G, s, t, **kwargs),
    #                           flow_func)

    def test_preflow_push_global_relabel(self):
        G = read_graph("gw1")
        R = preflow_push(G, 1, len(G), global_relabel_freq=50)
        assert R.graph["flow_value"] == 1202018