import gurobipy as gp
from gurobipy import GRB, Model, quicksum

HYPEREDGES = {
    4: (['Butadien', 'Butadien'], []), 
    5: (['Butadien', 'Butadien'], ['Butadien', 'Butadien']), 
    7: (['Butadien', 'Butadien'], []), 
    9: (['p_{0,0}', 'p_{0,0}'], []), 
    10: (['p_{0,0}', 'p_{0,1}'], ['Butadien', 'Butadien']), 
    11: (['p_{0,0}', 'p_{0,1}'], []), 
    13: (['p_{0,0}', 'p_{0,2}'], []), 
    14: (['p_{0,0}', 'p_{0,2}'], []), 
    15: (['Butadien', 'p_{0,0}'], ['Butadien']), 
    16: (['p_{0,1}', 'p_{0,1}'], []), 
    18: (['p_{0,1}', 'p_{0,1}'], ['Butadien']), 
    20: (['p_{0,1}', 'p_{0,2}'], ['Butadien']), 
    21: (['Butadien', 'p_{0,1}'], ['Butadien']), 
    22: (['p_{0,1}', 'p_{0,2}'], []), 
    23: (['Butadien', 'p_{0,1}'], []), 
    24: (['p_{0,2}', 'p_{0,2}'], []), 
    25: (['Butadien', 'p_{0,2}'], ['Butadien']), 
    26: (['Butadien', 'p_{0,2}'], []), 
    28: (['p_{0,0}', 'p_{0,1}'], []), 
    30: (['Butadien', 'p_{0,0}'], []), 
    32: (['Butadien', 'p_{0,1}'], []), 
    33: (['Butadien', 'p_{0,1}'], []), 
    35: (['Butadien', 'p_{0,1}'], []), 
    37: (['Butadien', 'p_{0,1}'], []), 
    38: (['p_{0,3}'], []), 
    42: (['p_{0,4}'], []), 
    50: (['p_{0,3}', 'p_{0,3}'], []), 
    51: (['p_{0,3}', 'p_{0,4}'], []), 
    52: (['p_{0,3}', 'p_{0,5}'], []), 
    53: (['p_{0,3}', 'p_{0,6}'], []), 
    54: (['p_{0,3}', 'p_{0,8}'], []), 
    55: (['p_{0,3}', 'p_{0,9}'], []), 
    56: (['p_{0,3}', 'p_{0,10}'], []), 
    57: (['p_{0,2}', 'p_{0,3}'], []), 
    58: (['p_{0,0}', 'p_{0,3}'], []), 
    59: (['Butadien', 'p_{0,3}'], ['Butadien']), 
    60: (['p_{0,1}', 'p_{0,3}'], []), 
    61: (['p_{0,4}', 'p_{0,4}'], []), 
    62: (['p_{0,4}', 'p_{0,5}'], []), 
    64: (['p_{0,4}', 'p_{0,6}'], []), 
    65: (['p_{0,2}', 'p_{0,4}'], []), 
    66: (['p_{0,0}', 'p_{0,4}'], ['Butadien']), 
    67: (['Butadien', 'p_{0,4}'], []), 
    68: (['Butadien', 'p_{0,4}'], ['Butadien']), 
    69: (['p_{0,1}', 'p_{0,4}'], []), 
    70: (['p_{0,4}', 'p_{0,6}'], []), 
    71: (['p_{0,4}', 'p_{0,8}'], []), 
    72: (['p_{0,4}', 'p_{0,9}'], []), 
    73: (['p_{0,4}', 'p_{0,10}'], []), 
    74: (['p_{0,2}', 'p_{0,4}'], []), 
    75: (['p_{0,0}', 'p_{0,4}'], []), 
    76: (['p_{0,5}', 'p_{0,5}'], []), 
    77: (['p_{0,5}', 'p_{0,6}'], []), 
    78: (['p_{0,2}', 'p_{0,5}'], []), 
    79: (['p_{0,0}', 'p_{0,5}'], ['Butadien']), 
    80: (['Butadien', 'p_{0,5}'], []), 
    81: (['Butadien', 'p_{0,5}'], ['Butadien']), 
    82: (['p_{0,1}', 'p_{0,5}'], []), 
    83: (['p_{0,1}', 'p_{0,5}'], []), 
    84: (['p_{0,5}', 'p_{0,6}'], []), 
    85: (['p_{0,5}', 'p_{0,8}'], []), 
    86: (['p_{0,5}', 'p_{0,9}'], []), 
    87: (['p_{0,5}', 'p_{0,10}'], []), 
    88: (['p_{0,0}', 'p_{0,5}'], []), 
    89: (['p_{0,6}', 'p_{0,6}'], []), 
    90: (['p_{0,6}', 'p_{0,8}'], []), 
    91: (['p_{0,6}', 'p_{0,9}'], []), 
    92: (['p_{0,6}', 'p_{0,10}'], []), 
    93: (['p_{0,2}', 'p_{0,6}'], []), 
    94: (['p_{0,0}', 'p_{0,6}'], []), 
    95: (['Butadien', 'p_{0,6}'], ['Butadien']), 
    96: (['Butadien', 'p_{0,6}'], []), 
    97: (['p_{0,1}', 'p_{0,6}'], ['Butadien']), 
    98: (['p_{0,1}', 'p_{0,6}'], []), 
    100: (['p_{0,0}', 'p_{0,6}'], []), 
    102: (['p_{0,0}', 'p_{0,7}'], []), 
    103: (['p_{0,8}', 'p_{0,8}'], []), 
    104: (['p_{0,8}', 'p_{0,9}'], []), 
    105: (['p_{0,8}', 'p_{0,10}'], []), 
    106: (['p_{0,2}', 'p_{0,8}'], []), 
    107: (['p_{0,0}', 'p_{0,8}'], []), 
    108: (['Butadien', 'p_{0,8}'], ['Butadien']), 
    109: (['p_{0,1}', 'p_{0,8}'], []), 
    110: (['p_{0,9}', 'p_{0,9}'], []), 
    111: (['p_{0,9}', 'p_{0,10}'], []), 
    112: (['p_{0,2}', 'p_{0,9}'], []), 
    113: (['p_{0,0}', 'p_{0,9}'], []), 
    114: (['Butadien', 'p_{0,9}'], ['Butadien']), 
    115: (['p_{0,1}', 'p_{0,9}'], []), 
    116: (['p_{0,10}', 'p_{0,10}'], []), 
    117: (['p_{0,2}', 'p_{0,10}'], []), 
    118: (['p_{0,0}', 'p_{0,10}'], []), 
    119: (['Butadien', 'p_{0,10}'], ['Butadien']), 
    120: (['p_{0,1}', 'p_{0,10}'], []), 
    121: (['p_{0,0}', 'p_{0,4}'], []), 
    123: (['p_{0,0}', 'p_{0,4}'], []), 
    125: (['Butadien', 'p_{0,7}'], []), 
    130: (['p_{0,14}'], []), 
    132: (['p_{0,15}'], []), 
    135: (['p_{0,0}', 'p_{0,11}'], []), 
    136: (['p_{0,12}', 'p_{0,12}'], []), 
    137: (['p_{0,12}', 'p_{0,13}'], []), 
    138: (['p_{0,12}', 'p_{0,14}'], []), 
    139: (['p_{0,12}', 'p_{0,15}'], []),
    140: (['p_{0,12}', 'p_{0,16}'], []), 
    141: (['p_{0,8}', 'p_{0,12}'], []), 
    142: (['p_{0,9}', 'p_{0,12}'], []), 
    143: (['Butadien', 'p_{0,12}'], ['Butadien']), 
    144: (['p_{0,10}', 'p_{0,12}'], []), 
    145: (['p_{0,0}', 'p_{0,12}'], []), 
    146: (['p_{0,1}', 'p_{0,12}'], []), 
    147: (['p_{0,2}', 'p_{0,12}'], []), 
    148: (['p_{0,3}', 'p_{0,12}'], []), 
    149: (['p_{0,4}', 'p_{0,12}'], []), 
    150: (['p_{0,5}', 'p_{0,12}'], []), 
    151: (['p_{0,6}', 'p_{0,12}'], []), 
    152: (['p_{0,13}', 'p_{0,13}'], []), 
    153: (['Butadien', 'p_{0,13}'], []), 
    154: (['Butadien', 'p_{0,13}'], ['Butadien']), 
    155: (['p_{0,0}', 'p_{0,13}'], ['Butadien']), 
    156: (['p_{0,1}', 'p_{0,13}'], []), 
    157: (['p_{0,1}', 'p_{0,13}'], []), 
    158: (['p_{0,2}', 'p_{0,13}'], []), 
    159: (['p_{0,4}', 'p_{0,13}'], []), 
    160: (['p_{0,5}', 'p_{0,13}'], []), 
    161: (['p_{0,6}', 'p_{0,13}'], []), 
    162: (['p_{0,13}', 'p_{0,14}'], []), 
    163: (['p_{0,13}', 'p_{0,15}'], []), 
    164: (['p_{0,13}', 'p_{0,16}'], []), 
    165: (['p_{0,8}', 'p_{0,13}'], []), 
    166: (['p_{0,9}', 'p_{0,13}'], []), 
    167: (['p_{0,10}', 'p_{0,13}'], []), 
    168: (['p_{0,0}', 'p_{0,13}'], []), 
    169: (['p_{0,2}', 'p_{0,13}'], []), 
    170: (['p_{0,3}', 'p_{0,13}'], []), 
    171: (['p_{0,14}', 'p_{0,14}'], []), 
    172: (['p_{0,14}', 'p_{0,15}'], []), 
    173: (['p_{0,14}', 'p_{0,16}'], []), 
    174: (['p_{0,8}', 'p_{0,14}'], []), 
    175: (['p_{0,9}', 'p_{0,14}'], []), 
    176: (['Butadien', 'p_{0,14}'], ['Butadien']), 
    177: (['p_{0,10}', 'p_{0,14}'], []), 
    178: (['p_{0,0}', 'p_{0,14}'], []), 
    179: (['p_{0,1}', 'p_{0,14}'], []), 
    180: (['p_{0,2}', 'p_{0,14}'], []), 
    181: (['p_{0,3}', 'p_{0,14}'], []), 
    182: (['p_{0,4}', 'p_{0,14}'], []), 
    183: (['p_{0,5}', 'p_{0,14}'], []), 
    184: (['p_{0,6}', 'p_{0,14}'], []), 
    185: (['p_{0,15}', 'p_{0,15}'], []), 
    186: (['p_{0,15}', 'p_{0,16}'], []), 
    187: (['p_{0,8}', 'p_{0,15}'], []), 
    188: (['p_{0,9}', 'p_{0,15}'], []), 
    189: (['Butadien', 'p_{0,15}'], ['Butadien']), 
    190: (['p_{0,10}', 'p_{0,15}'], []), 
    191: (['p_{0,0}', 'p_{0,15}'], []), 
    192: (['p_{0,1}', 'p_{0,15}'], []), 
    193: (['p_{0,2}', 'p_{0,15}'], []), 
    194: (['p_{0,3}', 'p_{0,15}'], []), 
    195: (['p_{0,4}', 'p_{0,15}'], []), 
    196: (['p_{0,5}', 'p_{0,15}'], []), 
    197: (['p_{0,6}', 'p_{0,15}'], []), 
    198: (['p_{0,16}', 'p_{0,16}'], []), 
    199: (['p_{0,8}', 'p_{0,16}'], []), 
    200: (['p_{0,9}', 'p_{0,16}'], []), 
    201: (['Butadien', 'p_{0,16}'], ['Butadien']), 
    202: (['p_{0,10}', 'p_{0,16}'], []), 
    203: (['p_{0,0}', 'p_{0,16}'], []), 
    204: (['p_{0,1}', 'p_{0,16}'], []), 
    205: (['p_{0,2}', 'p_{0,16}'], []), 
    206: (['p_{0,3}', 'p_{0,16}'], []), 
    207: (['p_{0,4}', 'p_{0,16}'], []), 
    208: (['p_{0,5}', 'p_{0,16}'], []), 
    209: (['p_{0,6}', 'p_{0,16}'], []), 
    211: (['Butadien', 'p_{0,11}'], []),
}

VERTICES = ['Butadien', 'p_{0,0}', 'p_{0,1}', 'p_{0,2}', 'p_{0,3}', 'p_{0,4}', 'p_{0,5}', 'p_{0,6}', 'p_{0,7}', 'p_{0,8}', 'p_{0,9}', 'p_{0,10}', 'p_{0,11}', 'p_{0,12}', 'p_{0,13}', 'p_{0,14}', 'p_{0,15}', 'p_{0,16}', 'p_{0,17}', 'p_{0,18}']

VERTICESSMILES = ['C=CC=C', 'C=C', 'C=CC=CC=C', 'C1CCC(C=C)CC=1', 'C(CCC(C=C)CC=C)=C', 'C=CC=CC=CC=C', 'C1CCC(C=CC=C)CC=1', 'C=CC1C=CCCC1', 'C1CCCCC=1', 'C=CC1CC=CCC1C=C', 'C1CCC(C=C)C(C=C)C=1', 'C(C1CC(C=C)C=CC1)=C', 'C1C=CC=CC=1', 'C(CCC1C=CC=CC1)=C', 'C1C(C=CC=C)CCCC=1', 'C=CC(C=C)CCCC=C', 'C=CCCCCC=C', 'C=CC1C=CC(C=C)CC1', 'C1CC2CCCCC2CC=1', 'C1CC2C=CC=CC2CC=1']

FIXED_FLOWS = {
    #1: 1,
}

def build_model(name, hyperedges, vertices, nmrlikelihoods, excluded_support=None):
    model = Model(name)

    x = {e_id: model.addVar(vtype=GRB.INTEGER, lb = 0, name = f"x_{e_id}") for e_id in hyperedges}
    b = {e_id: model.addVar(vtype=GRB.BINARY, name = f"b_{e_id}") for e_id in hyperedges}
    n = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr")
    

    for v, nmr in zip(vertices, nmrlikelihoods):
        n[v] = nmr

    vertices = set(v for tails, heads in hyperedges.values() for v in tails + heads)

    for v in vertices:
        inflow = quicksum(x[e_id] for e_id, (_, heads) in hyperedges.items() if v in heads)
        outflow = quicksum(x[e_id] for e_id, (tails, _) in hyperedges.items() if v in tails)
        model.addConstr(inflow == outflow, name = f"flow_conservation_{v}")

    for e_id, value in FIXED_FLOWS.items():
        model.addConstr(x[e_id] == value, name = f"fixed_flow_{e_id}")

    for e_id in hyperedges:
        model.addGenConstrIndicator(b[e_id], 0, x[e_id] == 0, name = f"unused_implies_zero_{e_id}")
        model.addConstr(x[e_id] >= b[e_id], name = f"used_implies_positive_flow_{e_id}")

    reaction_path = {}


    if excluded_support:
        model.addConstr(quicksum(b[e_id] for e_id in excluded_support) <= len(excluded_support) - 1, name = "different_hyperedges",)
    
    #Multiplizier den node Wert mit infow + outflow
    model.ModelSense = GRB.MAXIMIZE


    #Multiply node value with infow or outflow
    model.setObjectiveN(
        quicksum(n[t_id[0]] * x[e_id] for e_id, (_, t_id) in hyperedges.items() if t_id != []),
        index = 0,
        priority = 2,
        name = "maximize_nmr_similarity",
    )    

    model.setObjectiveN(
        quicksum(-1 * x[e_id] for e_id in hyperedges),
        index=1,
        priority=1,
        name="minimize_used_hyperedges",
    )

    return model, x, b


def positive_entries(variable_dict, threshold = 0.5):
    return {e_id: var.X for e_id, var in variable_dict.items() if var.X > threshold}

def print_solution(title, flow_solution, binary_solution, hyperedges):
    print(f"\n{title}:")
    for e_id in sorted(flow_solution):
        flow = flow_solution[e_id]
        tails, heads = hyperedges[e_id]
        print(f"Hyperedge {e_id}: Flow = {flow}, Tails = {tails}, Heads = {heads}")
    print("\nBinary Variables:")
    for e_id in sorted(binary_solution):
        print(f"Binary Variable b_{e_id} = {binary_solution[e_id]}")

    print(f"\nTotal flow: {sum(flow_solution.values())}")
    print(f"Number of used hyperedges: {len(binary_solution)}")

def main():
    model, x, b = build_model("HypergraphFlow", HYPEREDGES, VERTICES, NMRLIKELYHOODS)
    model.optimize()
    if model.status != GRB.Status.OPTIMAL:
        print("No optimal solution found for the first model.")
        return
    optimal_solution = positive_entries(x)
    optimal_binary_solution = positive_entries(b)
    print_solution("Optimal Solution", optimal_solution, optimal_binary_solution, HYPEREDGES)

    """ excluded_support = list(optimal_binary_solution.keys())
    second_model, x2, b2 = build_model("SecondBestHypergraphFlow", HYPEREDGES, excluded_support=excluded_support,)

    second_model.optimize()
    if second_model.status == GRB.Status.OPTIMAL:
        second_solution = positive_entries(x2)
        second_binary_solution = positive_entries(b2)
        print_solution("Second Best Solution", second_solution, second_binary_solution, HYPEREDGES, VERTICES)
    else:
        print("No optimal solution found for the second best model.")
 """
if __name__ == "__main__":
    main()