# %%
PROJECT_PATH = '/home/md/Work/ligalytics/leagues_stable/'
import os, sys
sys.path.insert(0, PROJECT_PATH)
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "leagues.settings")
os.environ["DJANGO_ALLOW_ASYNC_UNSAFE"] = "true"

from leagues import settings
# settings.DATABASES['default']['NAME'] = PROJECT_PATH+'/db.sqlite3'
settings.DATABASES['default']['ENGINE'] = 'django.db.backends.postgresql_psycopg2'
settings.DATABASES['default']['HOST'] = '0.0.0.0'
settings.DATABASES['default']['PORT'] = '5432'
settings.DATABASES['default']['USER'] = 'postgres'
settings.DATABASES['default']['PASSWORD'] = 'secret123'
settings.DATABASES['default']['NAME'] = 'mypgsqldb'
settings.DATABASES['default']['ATOMIC_REQUESTS'] = False
settings.DATABASES['default']['AUTOCOMMIT'] = True
settings.DATABASES['default']['CONN_MAX_AGE'] = 0
settings.DATABASES['default']['CONN_HEALTH_CHECKS'] = False
settings.DATABASES['default']['OPTIONS'] = {}

os.environ["XPRESSDIR"] = "/opt/xpressmp"
os.environ["XPRESS"] = "/opt/xpressmp/bin"
os.environ["LD_LIBRARY_PATH"] = os.environ["XPRESSDIR"] + "/lib"
os.environ["DYLD_LIBRARY_PATH"] = os.environ["XPRESSDIR"] + "/lib"
os.environ["SHLIB_PATH"] = os.environ["XPRESSDIR"] + "/lib"
os.environ["LIBPATH"] = os.environ["XPRESSDIR"] + "/lib"
os.environ["PYTHONPATH"] = os.environ["XPRESSDIR"] + "/lib"
os.environ["CLASSPATH"] = os.environ["XPRESSDIR"] + "/lib/xprs.jar"
os.environ["CLASSPATH"] = os.environ["XPRESSDIR"] + "/lib/xprb.jar" + os.pathsep + os.environ["CLASSPATH"]
os.environ["CLASSPATH"] = os.environ["XPRESSDIR"] + "/lib/xprm.jar" + os.pathsep + os.environ["CLASSPATH"]
os.environ["PATH"] = os.environ["XPRESSDIR"] + "/bin" + os.pathsep + os.environ["PATH"]

POSTGRES_ENGINE=django.db.backends.postgresql_psycopg2
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
POSTGRES_USER=leagues_user
POSTGRES_PASSWORD=ligalytics
POSTGRES_DB=leagues_db

import django
django.setup()

from scheduler.models import *
import pulp
from pulp import lpSum, value, XPRESS, GUROBI, PULP_CBC_CMD
from django.db.models import Q
from django.template.loader import render_to_string

from qualifiers.models import *
from common.models import GlobalTeam, GlobalCountry
from scheduler.models import Season, Scenario, Team, DayObj, CountryClash, Country

from qualifiers.draws import groupTeams, optimize_inversions4
from scheduler.solver.tasks.optimize import optimize
from draws.solver.optimize_draws import ucl24_ha_matrix, ucl24_opponent_matrix


from django.template.loader import render_to_string
from django.core.files.storage import FileSystemStorage
from django.utils.translation import gettext_lazy as _

# from gurobipy import *
import pulp
from pulp import lpSum, value, XPRESS_PY, XPRESS, GUROBI, PULP_CBC_CMD
from math import sqrt,pow,sin,cos,atan2,pi, ceil
from collections import defaultdict
import timeit
import datetime
import operator
import random
import time
import copy
# from os import dup, dup2, close, path
import os
from importlib import import_module
import builtins as __builtin__
import logging
import networkx as nx
import json
import string 
import hashlib

from scheduler.models import *
from leagues.celery import celery, TASK_TIME_LIMIT
from leagues.settings import PULP_FOLDER
from scheduler.helpers import serialize_scenario, report_solverstatus
from scheduler.solver.functions import *
from scheduler.solver.tasks.optimize_localsearch import smartNeighbor
from scheduler.solver.tasks.optimize_submodels import ucl24_basicmodell, ueluecl24_basicmodell, ueluecl24_basicmodell_v2

# from research.learners import AttendanceLearner
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.ensemble import GradientBoostingRegressor
import random
import time
import json
import csv
import networkx as nx
import matplotlib.pyplot as plt
from datetime import timedelta

from django.contrib.sessions.models import Session

def getVal(v):
    if type(v) == int :
        return v
    else: 
        return v.value()


# scenario = Scenario.objects.get(id=9306)
scenario = Scenario.objects.get(id=9368)

s2 = scenario.id
user_name = 'md'
user_is_staff = True
runMode = 'Improve'
localsearch_time = 60
RUN_ENV = 'local'
solver = 'xpress'


# %%
thisScenario = Scenario.objects.get(id = s2)
thisSeason = thisScenario.season
thisLeague = thisSeason.league

mathModelName=thisLeague.name
if thisSeason.optimizationParameters!="":
    mathModelName=thisSeason.optimizationParameters

start_time = time.time()

writeProgress("Computation started !!", thisScenario.id, 3)

lengthScale = 1.0 if thisSeason.lengthUnit=="km" else 0.62 


def scaledDistanceString (dd):
    return str(int(lengthScale*dd+0.5))+ " "+ thisSeason.lengthUnit

otherScenGames=[]
if thisSeason.improvementObjective!="--":
    for otherScenario in Scenario.objects.filter(season=thisSeason):
        impObjWeight = 5
        if thisSeason.improvementObjective=="stick to old solutions":
            impObjWeight = -5
        if thisSeason.improvementObjective=="stick to old solutions heavily":
            impObjWeight = -50
        if otherScenario.solutionlist() != [['']]:
            for g in otherScenario.solutionlist():                
                otherScenGames.append((int(g[1]),int(g[2]),int(g[3]), impObjWeight ))

getGlobalCountry={ gc['uefa']: gc['id']  for gc in GlobalCountry.objects.values() }

teamObjects = Team.objects.filter(season=thisSeason,active=True).order_by('position').values()
teams=[]
realteams=[]
faketeams=[]
importantteams=[]
shortteams=[]
t_pos={}
t_pot={}
t_color={}
t_country={}
t_stadium = {}
t_shortname = {}
t_usePhases = {}
t_lon = {}
t_lat = {}
t_attractivity ={}
t_logo ={}
getTeamById={}
getTeamIdByName={}
getTeamIdByShortName={}
getTeamByName={}
getStadiumById={}
teamByShort={}
top4 = []
for t in teamObjects:
    # print (t['name'],  t['id'])
    teams.append(t['id'])
    shortteams.append(t['shortname'])
    teamByShort[t['shortname']]= t['name']
    getTeamIdByShortName[t['shortname']]=t['id']
    if t['name']!='-':
        realteams.append(t['id'])
    else:
        faketeams.append(t['id'])
    if t['very_important']:
        importantteams.append(t['id'])
    t_country[t['id']]= t['countryObj_id']
    t_pos[t['name']]= t['position']
    t_color[t['name']]="lightyellow"
    t_pot[t['id']]= t['pot']
    t_stadium[t['id']]=t['stadium']
    t_attractivity[t['id']]=t['attractivity']
    t_lon[t['id']]=t['longitude']
    t_lat[t['id']]=t['latitude']
    t_shortname[t['id']]=t['shortname']
    t_logo[t['id']]=""
    if t['logo']:
        t_logo[t['id']]="<img width='20px' height='20px' src='/media/"+t['logo']+"'>" 
    t_usePhases[t['id']]= thisScenario.usePhases
    getTeamById[t['id']]=t['name']
    getStadiumById[t['id']]=t['stadium']
    getTeamIdByName[t['name']]=t['id']
    getTeamByName[t['name']]=t
    if t['attractivity'] >= thisSeason.topTeamMinCoefficient :
        top4.append(t['id'])

inactive_teams=[]
for t in  Team.objects.filter(season=thisSeason,active=False).order_by('position').values():
    inactive_teams.append(t['id'])
    t_attractivity[t['id']]=t['attractivity']
    t_lon[t['id']]=t['longitude']
    t_lat[t['id']]=t['latitude']
    t_country[t['id']]= t['countryObj_id']
    getTeamById[t['id']]=t['name']

countryObjects = Country.objects.filter(season=thisSeason).order_by('name')
countries = [c.id for c in countryObjects]
cn_name = {c.id : c.name for c in countryObjects}
cn_shortname = {c.id : c.shortname for c in countryObjects}

NAS15=[c for c in countries if cn_shortname[c] in ["ESP","GER","ENG","ITA","FRA"]]

lowerBoundFound = False
distance ={}
attractivity ={}
distanceById={}
distanceInDaysById={}
# stadium_names = set([t['stadium'] for t in teamObjects if t['stadium']!=''])
# stadium_id={}
# stadium_name={}
# sid=0
# for stadium in stadium_names :
#     stadium_name[sid]=stadium
#     stadium_id[stadium]=sid
#     sid+=1
# stadiums = list(stadium_name.keys())

travelDict= thisSeason.travelDict()
for t1 in teamObjects:
    # if t1['stadium']!='':
    #     teamsOfStadium[stadium_id[t1['stadium']]].append(t1['id'])
    for t2 in teamObjects:
        # distance[t1['name'],t2['name']] = distanceInKm(t1,t2)
        # print (t1['name'],t2['name'],distance[t1['name'],t2['name']] ," -> ", travelDict[t1['id']][t2['id']]['distance'] )
        distance[t1['name'],t2['name']] = travelDict[t1['id']][t2['id']]['distance'] 
        distanceById[t1['id'],t2['id']] = distance[t1['name'],t2['name']]
        distanceInDaysById[t1['id'],t2['id']] = int(distance[t1['name'],t2['name']]/350 +0.99)
        attractivity[t1['id'],t2['id']] = int(100*t1['attractivity']*t2['attractivity'])


dayObjects = Day.objects.filter(season=thisSeason).values()
days = [ d['id'] for d in dayObjects if d['round']>0 ]
nDays = len(days)
getNiceDayRaw = { d['id'] : d['day']  for d in dayObjects}

higherSeasons = thisSeason.higherSeasons()
higherGames = thisSeason.higherGames()

this_season_team_names = list(getTeamByName.keys())

for d in thisSeason.higherDays():
    getNiceDayRaw[d.id] = d.day

higherTeamObjects = Team.objects.filter(season__in=higherSeasons,active=True).values()
higherDayObjects = Day.objects.filter(season__in=higherSeasons,maxGames__gte=1).values()
higherTeams = [ t['id'] for t in higherTeamObjects] 
higherTeamsOf={ t: [] for t in teams}
for t in higherTeamObjects:
    getTeamById[t['id']]=t['name']
    t_country[t['id']]=t['countryObj_id']
    if t['name'] in this_season_team_names:
        higherTeamsOf[getTeamIdByName[t['name']]].append(t['id'])

print ("Teams : " , teams)
print ("VIP Teams : " , importantteams)
print ("TOP Teams : " , top4)

allConferences = Conference.objects.filter(scenario=s2)
sharedStadiums = False
for ff in  thisSeason.federationmember.all():
    sharedStadiums= ff.federation.sharedStadiums

# print ("\nGroups : ")
t_conference = {t : 0 for t in teams }
conf_teams={}
for c in Conference.objects.filter(scenario=s2,regional=False).order_by('name'):
    # print ("A" , c)
    cteams = c.teams.filter(active=True)
    conf_teams[c.name]=[]
    for t in cteams:
        conf_teams[c.name].append(t.id)
        # print ("group for ", t)
        # if t_conference[t.id]!=0:
            # print (getTeamById[t.id] , " in several groups")
        if t_conference[t.id]==0 or len(cteams)< len(t_conference[t.id].teams.filter(active=True)):
            t_conference[t.id]=c
            # print  (" is " , c )
# for t in set([t for t in teams if t_conference[t]==0 ]):
    # print (" no group " ,  getTeamById[ t])
# return ''

displayConferences=Conference.objects.filter(scenario=s2, display_group=True)
displayGroups ={}
if thisSeason.groupBased:
    displayGroups ={ c.id : [t.id for t in c.teams.filter(active=True)] for c in displayConferences}
    for c in displayConferences:
        displayGroups[c.id]=[]        
        for t in c.teams.filter(active=True):
            displayGroups[c.id].append(t.id)
            t_conference[t.id]=c           
else:
    displayGroups['All'] = realteams

stadiums = Stadium.objects.filter(season=thisSeason)    
stadium_name={ s.id : s.name for s in stadiums }

teamsOfStadium ={ st.id:[] for st in stadiums }

teamsWithSameStadium = {t: [] for t in realteams}
getStadiumsByTeam = {t: [] for t in realteams}
getTeamsByStadium = {s.id: [] for s in stadiums}
getStadiumAvailability = { (s.id,d): 1 for s in stadiums for d in days}
for s in stadiums:
    for sp in s.stadiumpreferences.all():
        getStadiumsByTeam[sp.team.id].append(sp)
        getTeamsByStadium[s.id].append(sp)
    for sb in s.stadiumBlockings.filter(scenario=s2):
        getStadiumAvailability[s.id,sb.day.id]=0

for t in realteams:
    for s in getStadiumsByTeam[t]:
        teamsWithSameStadium[t]+=[t2.team.id for t2 in getTeamsByStadium[s.stadium.id] if t2.team.id!=t]
    teamsWithSameStadium[t] = list(set(teamsWithSameStadium[t]))

prioVal ={'A': 25 , 'B': 5 , 'C': 1, 'Hard' : 1000}

sw_prio = {}
sw_float1 = {}
sw_float2 = {}
sw_int1 = {}
sw_int2 = {}
sw_text = {}
for sw in SpecialWish.objects.filter(scenario=s2):
    sw_prio[sw.name]=prioVal[sw.prio] if sw.active else 0
    sw_float1[sw.name]=sw.float1
    sw_float2[sw.name]=sw.float2
    sw_int1[sw.name]=sw.int1
    sw_int2[sw.name]=sw.int2
    sw_text[sw.name]=sw.text
special_wishes=list(sw_prio.keys())
special_wishes_active = [ sw for sw in special_wishes if sw_prio[sw]>0 ]

print (special_wishes_active)

noBreakLimitTeams = []
if "allowManyBreaksInRow" in special_wishes_active :
    noBreakLimitTeams = sw_text["allowManyBreaksInRow"].split(",")
    print (noBreakLimitTeams)
    noBreakLimitTeams = [t for t in teams if getTeamById[t] in noBreakLimitTeams]
    print (noBreakLimitTeams)                

pairings_tmp = Pairing.objects.filter(scenario=s2, active=True).values()
pairings_tmp2 = Pairing.objects.filter(scenario__is_published=True, team1__id__in=teams, team2__id__in=higherTeams, active=True).exclude(scenario__season=thisSeason).values()
pairings_tmp3 = Pairing.objects.filter(scenario__is_published=True, team2__id__in=teams, team1__id__in=higherTeams, active=True).exclude(scenario__season=thisSeason).values()
pairings = []
for p in  [ p for p in pairings_tmp if p['team1_id'] in teams and p['team2_id'] in teams+higherTeams ] + [ p for p in pairings_tmp2 ] + [ p for p in pairings_tmp3]:
    if p not in pairings:
        pairings.append(p) 

pairTagweight = {}
for pair in pairings:
    pairTagweight[pair['id']] = Pairing.objects.get(id=pair['id']).tag_weight()
    if pair['dist'] in [3,7]:
        pair['nWishes'] = thisSeason.nRounds
    else:
        pair['nWishes'] = nDays
nElemPairings= sum(pair['nWishes'] for pair in pairings) 

breaks = Break.objects.filter(season=thisSeason).values()
tagBlockWeight = { t.id : t.blocking_weight for t in Tag.objects.filter(season=thisSeason) }
blockings_tmp = Blocking.objects.filter(scenario=s2,active=True).values()
blockings_tmp = [ bl for bl in blockings_tmp if  bl['team_id'] in teams ]

for bl in blockings_tmp:
    bl['weight'] =1 if bl['tag_id'] == None else tagBlockWeight[bl['tag_id']]

blockings = [ bl for bl in blockings_tmp if bl['weight'] >=0 ]
goodHomes = [ bl for bl in blockings_tmp if bl['weight'] <0 ]

# times = ['Early', 'Late']
timeObjects = TimeSlot.objects.filter(season=thisSeason).values()
times = [ str(t['id']) for t in timeObjects]
getTimeById = {str(t['id']):t['name'] for t in timeObjects}
getTimeStartById = {str(t['id']):t['start'] for t in timeObjects}
getIdByTime = {t['name']:str(t['id']) for t in timeObjects}

blocked_arena = {(t,d, tm) : False for t in teams for d in days for tm in ["----"] + times  }
hidden_arena = {(t,d, tm) : False for t in teams for d in days for tm in ["----"] + times  }
nBlockingHome=0
nBlockingAway=0

for bl in blockings:
    if bl['type'] in ["Hide","Game"]:
        hidden_arena[(bl['team_id'],bl['day_id'], bl['time'] )]=True

    if bl['type'] in ["Home","Hide","Game"]:
        if bl['tag_id']==None:
            blocked_arena[(bl['team_id'],bl['day_id'], bl['time'] )]=True                
            nBlockingHome+=1
    else:
        nBlockingAway+=1

nTeams=len(teams)
nPhases =thisSeason.numPhases
groupView = thisSeason.groupBased

gameCntr={(t1,t2) : 0 for t1 in teams for t2 in teams}
undirectedGameCntr={(t1,t2) : 0 for t1 in teams for t2 in teams}

if thisSeason.useFeatureOpponentMatrix:
    gameRequirements = GameRequirement.objects.filter(scenario=s2, team1__active=True, team2__active=True) 
    for gm in gameRequirements:
        if thisSeason.undirectedGames:
            undirectedGameCntr[(gm.team1.id,gm.team2.id)]+=gm.number
            undirectedGameCntr[(gm.team2.id,gm.team1.id)]+=gm.number
            # print ( "found undirected  game " , (gm.team1.id,gm.team2.id) , gm.number )
        else:
            gameCntr[(gm.team1.id,gm.team2.id)]+=gm.number
            # print ( "found directed  game " , (gm.team1.id,gm.team2.id) , gm.number )
else:
    for t1 in teams:
        for t2 in teams:
            if t1!=t2:
                gameCntr[(t1,t2)]+=nPhases/2

    for c in Conference.objects.filter(scenario=s2):
        cteams = c.teams.filter(active=True)
        for t1 in cteams:
            for t2 in cteams:
                if t1!=t2:
                    gameCntr[(t1.id,t2.id)]+=c.deltaGames/2

    for (t1,t2) in gameCntr.keys():
        if gameCntr[(t1,t2)]%1!=0 :
            undirectedGameCntr[(t1,t2)]=1
        gameCntr[(t1,t2)] = int(gameCntr[(t1,t2)])

games = [ gm for gm in gameCntr.keys() if gameCntr[gm]+undirectedGameCntr[gm]>0]

objectiveFunctionWeights = ObjectiveFunctionWeight.objects.filter(scenario=s2).values()

gew={}
gew['Trips'] = 5
gew['Derbies'] = 5
gew['Pairings'] = 5
for ow in objectiveFunctionWeights:
    gew[ow['name']]= ow['use'] * ow['prio']

objectivePrio = 'Breaks'
if  gew['Trips']>gew['Breaks'] :
    objectivePrio = 'Trips'

print("objectivePrio:", objectivePrio)

specialGameControl= mathModelName in ["Florida State League"]

if len(games)==0:
    games = [ (t1,t2) for t1 in teams for t2 in teams if t1!=t2 ]
    specialGameControl=True
    
realgames= [(t1,t2) for (t1,t2) in games if getTeamById[t1]!="-" and getTeamById[t2]!="-"]

# nur wenn die solutionlist alle spiele enthält, wird dieser modus aktiviert
evalRun = ( runMode == "Improve" and localsearch_time==0 
            and len(thisScenario.solutionlist())==sum([gameCntr[gm]+0.5*undirectedGameCntr[gm] for gm in realgames]) )

opponents = { t: set([]) for t in realteams}

for (t1,t2) in games:
    if t1 in realteams and t2 in realteams:
        opponents[t1].add(t2)
        opponents[t2].add(t1)

model7 = pulp.LpProblem(f"{PULP_FOLDER}/FindGameClusters_"+str(thisScenario.id), pulp.LpMinimize)

G = nx.Graph(realgames)
gmClusters = range(1,nTeams+2 - len(nx.maximal_matching(G)))

if nPhases>0 and not thisSeason.useFeatureOpponentMatrix and not specialGameControl:
    gmClusters = range(1,2)    

print ("gmClusters", gmClusters)

cntr=0
gameClusterTeams = {}
# gameClusterTeams = { c : [] for c in gmClusters }

t_incluster = {t : [] for t in realteams}
G = nx.Graph(realgames)
for c in nx.find_cliques(G):
    cntr+=1
    gameClusterTeams[cntr]=list(c)
    for t in gameClusterTeams[cntr]:
        t_incluster[t].append(cntr)
for t in realteams: 
    cntr+=1
    gameClusterTeams[cntr]=[t]
    t_incluster[t].append(cntr)

gmClusters = gameClusterTeams.keys()

groupUsed7 = { c : pulp.LpVariable('x7_'+str(c), lowBound = 0, upBound = 1,  cat = pulp.LpInteger) for c in gmClusters}

for t in realteams: 
    model7+= lpSum([ groupUsed7[c] for c in t_incluster[t]]) ==1 

model7+= lpSum([ groupUsed7[c] for c in groupUsed7.keys()]) 

if solver == "CBC":
    model7.solve(PULP_CBC_CMD(threads = 8,msg=1))
elif solver == "Gurobi":
    model7.solve(GUROBI(MIPGap=0.01,msg=1))
else:
    model7.solve(XPRESS(msg=1, targetGap=0.01, maxSeconds = 100, keepFiles=True)) 

gameClusters= [c for c in gmClusters if groupUsed7[c].value()>0.01]

for c in gameClusters:
    print ("CLUSTER " , c , gameClusterTeams[c])

biggestGroupSize = max([len(gameClusterTeams[c]) for c in gameClusters])

print ("biggestGroupSize", biggestGroupSize)

nPhases = min( [  gameCntr[(t1,t2)]+ gameCntr[(t2,t1)] + undirectedGameCntr[(t1,t2)] for (t1,t2) in realgames ])
tripStartHeuristicGroupsize = 1 if thisSeason.tripStartHeuristicGroupsize=="None" else int(thisSeason.tripStartHeuristicGroupsize)
defaultGameRepetions = 1 if not mathModelName in ["NHL", "NBA"] else 2
nPhases=max(1,int(nPhases/defaultGameRepetions))
phases = range(nPhases)

useBasicGames = nPhases>0

if not useBasicGames:
    print ('no basic games but biggest group size ', biggestGroupSize, ' in nPhases ' , nPhases )

nRounds = thisSeason.nRounds
rounds=range(1,nRounds+1)

# nRoundsPerPhase= 1
# if nPhases>0:
nRoundsPerPhase= int(nRounds/nPhases)

print ('nRounds ',nRounds)
print ('nPhases ',nPhases)
print ('nRoundsPerPhase ',nRoundsPerPhase)
print ('defaultGameRepetions ',defaultGameRepetions)
print ('tripStartHeuristicGroupsize ',tripStartHeuristicGroupsize)

script =thisSeason.optimizationScript
if script == '' :
    if useBasicGames:
        if not thisSeason.useFeatureOpponentMatrix:
            script += "HEURISTIC\n"
        script += "GAME;1-"+str(nRounds)+";0.1;200\n"
    # if nRounds <=10:
    #     script += "GAME;1;"+str(nRounds)+"\n"
    # else:
    if thisSeason.groupBased:
        for c in allConferences:
            if not c.regional and c.teams.count() <= 12:           
                # print ("### ", c,  c.teams.count())
                # print (c, lpSum([1 for c in c.teams.all()]))
                script += "GROUP;1-"+str(nRounds)+";0.05;30;"+c.name+"\n"
                for cr in range(nPhases):
                    minIntRound= min( (cr) * nRoundsPerPhase+1, nRounds)
                    maxIntRound= min( (cr+1)*nRoundsPerPhase, nRounds)
                    # script += "GROUP;"+ str(minIntRound) + ";"+str(maxIntRound)+";"+str(c.id)+"\n"

        # for cr in range(nPhases):
        #     minIntRound= min( (cr) * nRoundsPerPhase+1, nRounds)
        #     maxIntRound= min( (cr+1)*nRoundsPerPhase, nRounds)
        #     if len(newRounds)>1:
        #         script += "GAME;"+ str(minIntRound) + ";"+str(maxIntRound)+"\n"
    # else:
    #     for cr in range(nPhases):
    #         minIntRound= min( (cr) * nRoundsPerPhase+1, nRounds)
    #         maxIntRound= min( (cr+1)*nRoundsPerPhase, nRounds)
    #         newRounds= range(minIntRound,maxIntRound+1)
    #         # if nRounds1 > 9 :
    #         #     script += "HOMEAWAY;"+ str(minIntRound) + ";"+str(maxIntRound)+"\n"
    #         # if not useMinRounds:
    #         #     script += "BASICGAME;"+ str(cr*(nTeams-1)+1) + ";"+str((cr+1)*(nTeams-1))+"\n"
    #         if len(newRounds)>1 and False:
    #             script += "GAME;"+ str(minIntRound) + ";"+str(maxIntRound)+"\n"

script=script.replace('\r', '')
print ("script")
print (script)
optSteps = [ st.split(';') for st in script.split("\n")]
print (optSteps)

script =thisSeason.improvementScript
if script == '' :
    if thisSeason.groupBased:
        if nRounds >16:
            script += "ROUNDS\n"
        script += "GROUPS\n"
    else:
        # if solver != "CBC":
        #     script += "TEAMSROUNDS\n"
        # script += "PAIRS\n"
        script += "TEAMS\n"
        # script += "ROUNDS\n"
        # if solver != "CBC":
        #     script += "TEAMSROUNDS\n"

impScript=[]
script=script.replace('\r', '')
print (script)
if localsearch_time>0:
    for stall in script.split("\n") :
        st_tok = stall.split(";")
        print (st_tok)
        st=st_tok[0]
        impTime = int(st_tok[2]) if len(st_tok) > 2 else -1
        if (st=="GROUPS"):
            print ("ADDING GROUPS")
            onlyUseReoptGroups = False
            for c in allConferences:
                if c.reopt:
                    onlyUseReoptGroups = True
            if impTime==-1:
                impTime = 30
            for c in allConferences:
                tms = [t.id for t in c.teams.filter(active=True)]
                print ("C " , tms)
                if (len(tms) <= 8 or c.reopt) and (not onlyUseReoptGroups or c.reopt):
                    print ("C " , tms)
                    if impTime==-1:
                        impTime = 30
                    for tt in tms:
                        print ( c.id, " TEAM " , getTeamById[tt]) 
                    # impScript.append((st,1,nRounds, tms, max(30,1.2*nRounds)))
                    if nRounds <= 50 or len(tms)<=3:
                        # impScript.append((st,1,int(0.75*nRounds),tms, max(group_time,30), ""))
                        impScript.append((st,1,nRounds,tms, impTime, ""))
                    else:
                        impScript.append((st,1,int(0.5*nRounds),tms,impTime, ""))
                        impScript.append((st,int(0.25*nRounds),int(0.75*nRounds),tms,impTime, ""))
                        impScript.append((st,int(0.5*nRounds),nRounds, tms, impTime, ""))
                        # impScript.append((st,1,int(0.75*nRounds),tms, max(group_time,300), ""))
                        # impScript.append((st,int(0.25*nRounds),nRounds, tms, max(group_time,300), ""))
                # else:
                #     if len(tms) <= 8:
                #         impScript.append((st,1,int(0.5*nRounds),tms, 30))
                #         impScript.append((st,int(0.5*nRounds),nRounds, tms, 30))
                # else:
                    # impScript.append((st,1,int(0.25*nRounds),tms, 30))
                    # impScript.append((st,int(0.25*nRounds),int(0.5*nRounds),tms, 30))
                    # impScript.append((st,int(0.5*nRounds),int(0.75*nRounds),tms, 30))
                    # impScript.append((st,int(0.75*nRounds),nRounds, tms, 30))



        if (st=="TEAMS"):
            print ("ADDING TEAMS")
            for t in teams:
                nts=[t]
                if solver != "CBC" and gew['Trips']>=0 and nTeams<=76:
                    na = 2  if nTeams*nRounds >200  else 3
                    na= random.randint(1,na)
                    if len(st_tok)>1:
                        na=int(st_tok[1])-1
                    for i in range(na):
                    # for i in range(4):
                        nts.append(teams[random.randint(0,nTeams-1)])
                        # print ("adding ", i , nts)
                    nts=list(set(nts)) 
                if impTime==-1:
                    impTime = len(nts)*15
                impScript.append((st,1,nRounds,nts, impTime, ""))

        if impTime==-1:
            impTime = 30

        if (st=="ROUNDS"):
            na=5
            if len(st_tok)>1:
                na=int(st_tok[1])-1
            for r in rounds:
                if r%5==1 or nRounds<10:
                    nrs = random.randint(na,max(na,int(nRounds/6)))
                    #dont make time window too big 
                    nrs = na
                    impScript.append((st,r,min(nRounds,r+nrs ),teams, impTime, ""))

        if (st=="ENCOUNTERS"):
            na=10
            if len(st_tok)>1:
                na=int(st_tok[1])-1
            for r in rounds:
                if r%5==1 and  r+na <=nRounds :
                    impScript.append((st,r,r+na,teams, impTime , "STICKY_HOME") )

        if (st=="HOMEAWAY"):
            impScript.append((st,1,nRounds,teams, impTime , "STICKY_ENCOUNTER") )


        if (st=="SMART_TEAMS"):
            impTeams = int(st_tok[1]) if len(st_tok) > 1 else 3
            impScript.append((st,1,nRounds,impTeams, impTime,""))
        if (st=="SMART_ROUNDS"):                   
            impRounds = int(st_tok[1]) if len(st_tok) > 1 else 5   
            impScript.append((st,1,impRounds,nTeams, impTime,""))

        if impTime==-1:
            impTime = 20
                    
        if (st=="TEAMSROUNDS"):
            for t in teams:
                nts=[t]
                for i in range(8 +2*(t%2)):
                    nts.append(teams[random.randint(0,nTeams-1)])
                    nts=list(set(nts))
                st = random.randint( 1, nRounds-10 )
                impScript.append((st,st,min(st+12,nRounds),nts, impTime, ""))
                # st = random.randint( 1, nRounds-18 )
                # impScript.append((st,st,min(st+18,nRounds),nts, 120, ""))

        if (st=="PAIRS"):
            for p in pairings:
                impScript.append((st,1,nRounds, [p['team1_id'],p['team2_id']], impTime), "")


random.shuffle(impScript)
if runMode=='Improve':
    impScript= [("INIT",1,nRounds, [], 2000, "")] + impScript

getPhaseOfRound = { r : min( nPhases-1 , int((r-1)/nRoundsPerPhase)) for r in rounds }

if thisSeason.lastRoundOfPhaseOne>0:
    getPhaseOfRound = { r : 0 if r<=thisSeason.lastRoundOfPhaseOne else 1 for r in rounds }
    
getDaysOfPhase = { p : [] for p in phases }
getDays = { r : [] for r in rounds}
roundGamesMax = { r : 0 for r in rounds}
roundGamesMin = { r : 0 for r in rounds}
getDayById = { d['id'] : d for d in dayObjects}
getDayByDateTime = { }
getNiceShortDay = { d['id'] : d['day']  for d in dayObjects}
getNiceDay = { d['id'] : d['day']  for d in dayObjects}
getWeekDay = { d['id'] : '' for d in dayObjects}
getDateTimeDay = { d['id'] : '' for d in dayObjects}
getRoundByDay = { d['id'] : d['round'] for d in dayObjects if d['round']>=0 }
getDayMinGames = { d['id'] : d['minGames'] for d in dayObjects if d['round']>0 }
getDayMaxGames = { d['id'] : d['maxGames'] for d in dayObjects if d['round']>0 }
getRoundsByDay = { d['id'] : [] for d in dayObjects }
nDerbies = { d['id'] : [d['nDerbies']] for d in dayObjects}
roundDays =[]
roundDaysMin ={ }
roundDaysMax ={ }
wds= {0:'Mon', 1:'Tue', 2:'Wed', 3:'Thu', 4:'Fri', 5:'Sat', 6:'Sun'}
for d in dayObjects:
    if d['round']>0 :
        getRoundsByDay[d['id']].append(d['round'])
        getDays[d['round']].append(d['id'])
        roundDays.append((d['round'],d['id']))
        roundDaysMin[(d['round'],d['id'])]=d['minGames']
        roundDaysMax[(d['round'],d['id'])]=d['maxGames']
        roundGamesMax[d['round']]=min(nTeams/2, roundGamesMax[d['round']]+d['maxGames'] )
        roundGamesMin[d['round']]+=d['minGames']
        ph = getPhaseOfRound[d['round']]
        getDaysOfPhase[ph].append(d['id'])
    if d['round2']>0:
        getRoundsByDay[d['id']].append(d['round2'])
        getDays[d['round2']].append(d['id'])
        roundDays.append((d['round2'],d['id']))
        roundDaysMin[(d['round2'],d['id'])]=d['minGames2']
        roundDaysMax[(d['round2'],d['id'])]=d['maxGames2']
        roundGamesMax[d['round2']]=min(nTeams/2, roundGamesMax[d['round2']]+d['maxGames2'] )
        roundGamesMin[d['round2']]+=d['minGames2']

    dt = parse(d['day'])
    getDateTimeDay[d['id']] = dt
    getDayByDateTime[dt] = d['id']
    getNiceDay[d['id']] = str(dt.strftime('%a, %b %d, %Y'))
    getNiceShortDay[d['id']] = str(dt.strftime('%d.%m.%y'))
    getWeekDay[d['id']] = str(wds[dt.weekday()])

for d in higherDayObjects:
    getNiceDayRaw[d['id']] =  d['day']
    dt = parse(d['day'])
    getDateTimeDay[d['id']] = dt
    getNiceDay[d['id']] = str(dt.strftime('%a, %b %d, %Y'))
    getWeekDay[d['id']] = str(wds[dt.weekday()])

teamCountries = list(set( [t_country[t] for t in teams ]))
countries = [c for c in countries if c in teamCountries]

getWeekDaysPerRound = { r : [ getWeekDay[d] for d in getDays[r]] for r in rounds}

wd = {"Mondays":0 , "Tuesdays":1 , "Wednesdays":2 , "Thursdays":3 , "Fridays":4 , "Saturdays":5 , "Sundays":6}
t_site_bestTimeSlots = { (t,d): [] for t in realteams for d in days }
prio_weight = { "A" : 0 , "B" : 50 , "C" : 100}


stadiumTimeSlotPreferences = StadiumTimeSlotPreference.objects.filter(team__id__in=teams )    
theseStadiums= set([ stsp.stadiumTimeSlot.stadium for stsp in stadiumTimeSlotPreferences ])

teamsInStadium ={st.id: set([]) for st in theseStadiums }
getSharedStadiumName ={st.id: st.name for st in theseStadiums }
for stsp in stadiumTimeSlotPreferences:
    teamsInStadium[stsp.stadiumTimeSlot.stadium.id].add(stsp.team.id)
lonelyTeams = []
for st in teamsInStadium.keys():
    if len(teamsInStadium[st])==1:
        lonelyTeams+=teamsInStadium[st]

incompatible_timslots =  {}
getStadiumTimeSlot= {}
for st in theseStadiums:
    theseTimeSlots  = st.stadiumtimeslots.all().values()
    for ts1 in theseTimeSlots: 
        getStadiumTimeSlot[ts1['id']]=ts1
        incompatible_timslots[ts1['id']]=set([])
        if ts1["end"]<=ts1["start"]:
            ts1["end"]=datetime.time(ts1["start"].hour + 2, ts1["start"].minute)
    for ts1 in theseTimeSlots:
        for ts2 in theseTimeSlots:
            if ts1["weekday"]==ts2["weekday"] and ts1["start"]<=ts2["start"] and ts2["start"]<ts1["end"]:
                incompatible_timslots[ts1['id']].add(ts2['id'])
                incompatible_timslots[ts2['id']].add(ts1['id'])

# for ts in incompatible_timslots.keys():
#     print ("")
#     print (ts)
#     for t2 in incompatible_timslots[ts]:
#         print (" - " , getStadiumTimeSlot[t2] )

# print ("incompatible_timslots", incompatible_timslots)

otherGames = [ ( stsb.homeTeam.name,  stsb.awayTeam.name, stsb.day, stsb.alternative_day, stsb.alternative_start, stsb.alternative_end, stsb.alternative_stadium, stsb.stadiumTimeSlot.id) for stsb in StadiumTimeSlotBlocking.objects.filter(stadiumTimeSlot_id__in=incompatible_timslots.keys()).exclude(homeTeam_id__in=teams).exclude(homeTeam=None) ]
# print (len (otherGames),"other games", otherGames)

blockedDayGames = { ts :[] for ts in incompatible_timslots.keys() }
for (h,a,d,d2,start2,end2,st2,ts1) in otherGames:
    if not d2:
        # print (d," : " , h," - " , a , " blocks games on "  )
        for ts2 in incompatible_timslots[ts1]:
            # print ( " ---  " ,  getStadiumTimeSlot[ts2] )
            blockedDayGames[ts2].append(d)
    else: 
        # print ( "CANT PLAY " , d2, start2,"-" ,e2, st2)
        d22 = getDayByDateTime[parse(d2)] 
        for ts in st2.stadiumtimeslots.all().values():
            if ts["start"]<end2 and start2<ts["end"] and ts["weekday"][:3]==getWeekDay[d22]:
                # print (  "    CONFLICT " , ts["weekday"][:3] , d2 ,parse(d2), getWeekDay[d22], ts["weekday"][:3]==getWeekDay[d22]," \n")
                blockedDayGames[ts['id']].append(d2)

stadiumTimeSlotPref = {}
for stsp in stadiumTimeSlotPreferences:
    t= stsp.team.id
    stadiumTimeSlotPref[(t,stsp.stadiumTimeSlot.id)]=stsp
    blockedDays = [ sb.day for sb in stsp.stadiumTimeSlot.stadiumtimeslotblockings.all().exclude(homeTeam_id__in=teams)]
    for d in days:             
        if getDateTimeDay[d].weekday() == wd[stsp.stadiumTimeSlot.weekday] and getNiceDayRaw[d] not in blockedDays + blockedDayGames[stsp.stadiumTimeSlot.id] :
            t_site_bestTimeSlots[(t,d)].append((stsp.prio, stsp.stadiumTimeSlot.id))        

# if the team is the only one in the stadium, it can focus on the best possible solution
for t in lonelyTeams:
    for d in days: 
        if len(t_site_bestTimeSlots[(t,d)])>1:
            # print (t_site_bestTimeSlots[(t,d)])
            t_site_bestTimeSlots[(t,d)]=sorted(t_site_bestTimeSlots[(t,d)])
            t_site_bestTimeSlots[(t,d)]=t_site_bestTimeSlots[(t,d)][:1]
            # print ("   -> " , t_site_bestTimeSlots[(t,d)])

# for (t,d) in t_site_bestTimeSlots.keys():
#     if len(t_site_bestTimeSlots[(t,d)])>0:
#         print(getTeamById[t], getNiceDay[d],  t_site_bestTimeSlots[(t,d)])

toTime=False
higherLeagueDayIds= []
upperAndLowerLeagueIds = []
higherLeagueGetRoundByDay= {d['id']:d['round'] for d in higherDayObjects}

for d in higherDayObjects:
    getRoundByDay[d['id']] =  0

for d in higherDayObjects:
    dt = parse(d['day'])
    getDateTimeDay[d['id']] = dt
    if dt not in getDayByDateTime.keys():
        getDayByDateTime[dt] = d['id']
        higherLeagueDayIds.append(d['id'])
        getNiceDay[d['id']] = str(dt.strftime('%a, %b %d, %Y'))
        # getRoundByDay[d['id']] =  d['round']
    else:
        upperAndLowerLeagueIds.append(getDayByDateTime[dt])
        thisLeagueDay=getDayByDateTime[dt]
        # print ("found day in both ", getNiceDay[thisLeagueDay] , " putting in round "  , getRoundByDay[thisLeagueDay]  )
        for d2 in higherDayObjects : 
            if higherLeagueGetRoundByDay[d2['id']] == higherLeagueGetRoundByDay[d['id']]:
                getRoundByDay[d2['id']] =  getRoundByDay[thisLeagueDay]
                # print ("assigning  day  ", d2['id']  , d2['day']  , " to  round "  , getRoundByDay[thisLeagueDay]  )

getHigherDaysByRound= { r: [d for d in higherLeagueDayIds if getRoundByDay[d]==r ]  for r in rounds }
getHigherDaysByRound[0]= [] 
# print (getHigherDaysByRound)

for p in pairings:
    p["days"]=days+higherLeagueDayIds
    if p["first_day_id"]:
        p["days"]=[d for d in p["days"] if getNiceDayRaw[p["first_day_id"]]<=getNiceDayRaw[d] ]
    if p["last_day_id"]:
        p["days"]=[d for d in p["days"] if getNiceDayRaw[d]<=getNiceDayRaw[p["last_day_id"]] ]
    print (p, p["days"])

earliestDay={r: getDays[r][0] for r in rounds }
latestDay={r: getDays[r][0] for r in rounds }
for r in rounds :
    for d in getDays[r]:
        dt=getDateTimeDay[d]
        if dt>getDateTimeDay[latestDay[r]]:
            latestDay[r]=d
        if dt<getDateTimeDay[earliestDay[r]]:
            earliestDay[r]=d

conferences = Conference.objects.filter(scenario=s2).values()
confTeams = {}
confName = {}
confRegional = {}
for c in Conference.objects.filter(scenario=s2):
    confTeams[c.id] = []
    confName[c.id] = c.name
    confRegional[c.id] = c.regional
    for t in c.teams.filter(active=True):
        confTeams[c.id].append(t.id)

basicTeams =[]
regionalteams = set([])
regionalConferences=Conference.objects.filter(scenario=s2, regional=True)

clusters=[0]
cluster_teams = {0:[]}
t_clusters = { t: [] for t in teams }
for c in regionalConferences:
    clusters.append(c.id)
    cluster_teams[c.id]=[]
    for t in c.teams.filter(active=True):
        cluster_teams[c.id].append(t.id)
        t_clusters[t.id].append(c.id)


for t in teams:
    if len(t_clusters[t])==0:
        cluster_teams[0].append(t)
        # nm=1
        # if len(clusters)>0:
        #     nm=max(c for c in clusters )+1
        # clusters.append(nm)
        # cluster_teams[nm]=[t]
        # t_cluster[t]=nm

# print ("clusters: ",clusters)
# print ("t_clusters: ",t_clusters)
# print ("cluster_teams: ",cluster_teams)


cluster_distances = {}

c_weight = { c: 1 for c in clusters }

for c1 in clusters:
    for c2 in clusters:
        dist=0
        for t1 in cluster_teams[c1]:
            for t2 in cluster_teams[c2]:
                dist+= distanceById[t1,t2]
        cluster_distances[c1,c2]= int(dist /(max(1,len(cluster_teams[c1]))*max(1,len(cluster_teams[c2]))))

    if cluster_distances[c1,c1]<100:
        c_weight[c1]= 1.3

    print ("CLUSTER ", c1)
    for t in cluster_teams[c1]:
        print ("--",getTeamById[t])    
    print ("---> Av Distance: ",  c1 ,cluster_distances[c1,c1])

c_lat = { c: sum([t_lat[t] for t in cluster_teams[c] ])/max(1,len(cluster_teams[c])) for c in clusters }
c_lon = { c: sum([t_lon[t] for t in cluster_teams[c] ])/max(1,len(cluster_teams[c])) for c in clusters }
tripToClusterSaving = { (t,c): 2.0*distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c])-cluster_distances[c,c] for t in teams for c in clusters }

for c in regionalConferences:
    print (c)
    # print (c.teamlist())
    cteams = c.teams.filter(active=True)
    for t in cteams:
        print (' - ' , t)
        regionalteams.add(t.id)

regionalGroupSizes = [ len( c.teams.filter(active=True))  for c in regionalConferences ]
if len(regionalGroupSizes)>0: 
    maxRegionalGroupSize = max([ len( c.teams.filter(active=True))  for c in regionalConferences ] )  
else:
    maxRegionalGroupSize =0
print ("maxRegionalGroupSize " , maxRegionalGroupSize)
print ("maxTourLength " , thisSeason.maxTourLength)

regionalParent={t : 0 for t in teams}
regionalKids={t : [] for t in teams}

regionalPatternUse=tripStartHeuristicGroupsize>1

print("regionalPatternUse", regionalPatternUse)

f_team={ t:t for t in teams }
if regionalPatternUse :
    teamPairs = [ (t1,t2) for (t1,t2) in games if t1<t2]
    print (len(teamPairs))
    # compatibility = {tp :0 for tp in teamPairs}
    compatibility = {(t1,t2) : len([d for d in days if not blocked_arena[(t1,d, "----" )] and not  blocked_arena[(t2,d, "----" )]]) for (t1,t2) in  teamPairs  }

    # compute regional clusters
    reg_clustersize = tripStartHeuristicGroupsize
    reg_num_clusters = int(nTeams/reg_clustersize+0.9)
    if reg_num_clusters%2==1:
        reg_num_clusters-=1
        reg_clustersize+=1

    reg_clusters = range(reg_num_clusters)
    # print (reg_clustersize)
    # print (reg_num_clusters)
    # print (reg_clusters)
    minLat = min([ t_lat[t] for t in teams])
    maxLat = max([ t_lat[t] for t in teams])
    minLon = min([ t_lon[t] for t in teams])
    maxLon = max([ t_lon[t] for t in teams])
    c_center_lat= { c: random.uniform(minLat, maxLat) for c in reg_clusters}
    c_center_lon= { c: random.uniform(minLon, maxLon) for c in reg_clusters}
    model_reg1 = pulp.LpProblem(f"{PULP_FOLDER}/Clustering_--_Regional_1_"+str(thisScenario.id), pulp.LpMinimize)
    reg_edges = [(t1,t2) for t1 in teams for t2 in teams if t1<t2 ]
    reg_x1 = {(t1,t2) : pulp.LpVariable('reg_x_'+str(t1)+'_'+str(t2), lowBound = 0, upBound = 1,  cat = pulp.LpInteger) for (t1,t2) in reg_edges}

    for t1 in teamObjects:        
        for t2 in teamObjects:        
            if (t1['id'],t2['id']) in reg_edges and t1['stadium']!='' and t1['stadium']==t2['stadium']  :
                reg_x1[(t1['id'],t2['id'])].upBound=0
                print ("forbidding in same group (stadium): " , t1['name'], t2['name'])
            if (t1['id'],t2['id']) in reg_edges and not (t_conference[t1['id']]==t_conference[t2['id']] or  '-' in [t1['name'],t2['name']]  ) :
                reg_x1[(t1['id'],t2['id'])].upBound=0
                print ("forbidding in same group (conference): " , t1['name'], t2['name'])
            # if t1['name'] =='Winnipeg Jets' and t2['name'] =='Edmonton Oilers':
            #     reg_x1[(t1['id'],t2['id'])].lowBound=1

    for t in teams :
        model_reg1+= lpSum([ reg_x1[(t1,t2)] for (t1,t2) in reg_edges if t in [t1,t2]]) <=1
    model_reg1+= lpSum([ reg_x1[(t1,t2)] for (t1,t2) in reg_edges]) ==reg_num_clusters
    print ("NEW OBJECTIVE ")
    comp =  lpSum([ compatibility[(t1,t2)] * reg_x1[(t1,t2)] for (t1,t2) in teamPairs] )
    # model_reg1+= comp 
    model_reg1+= lpSum([  distanceById[t1,t2] * reg_x1[(t1,t2)] for (t1,t2) in reg_edges if not "-" in [getTeamById[t1],getTeamById[t2]]])  

    if solver == "CBC":
        model_reg1.solve(PULP_CBC_CMD(msg=1))
    elif solver == "Gurobi":
        model_reg1.solve(GUROBI(MIPGap=0.0, TimeLimit=120, msg=1))
    else:
        model_reg1.solve(XPRESS(msg=1,maxSeconds=120, keepFiles=True))

    chosenEdges = [e for e in reg_edges if reg_x1[e].value()>0.9] 


    # for (t1,t2) in reg_edges:
    #     print ([getTeamById[t1],getTeamById[t2]] , distanceInKmByGPS(t_lon[t1],t_lat[t1],t_lon[t2],t_lat[t2])  , "\t " , not "-" in [getTeamById[t1],getTeamById[t2]])
    # for (t1,t2) in chosenEdges:
    #     print (" chosen " ,  getTeamById[t1],getTeamById[t2] , distanceInKmByGPS(t_lon[t1],t_lat[t1],t_lon[t2],t_lat[t2])  , "\t " , not "-" in [getTeamById[t1],getTeamById[t2]] )

    
    print (chosenEdges)
    print (comp.value())        
    

    model_reg = pulp.LpProblem(f"{PULP_FOLDER}/Clustering_--_Regional_"+str(thisScenario.id), pulp.LpMinimize)
    reg_x = {(t,c) : pulp.LpVariable('reg_x_'+str(t)+'_'+str(c), lowBound = 0, upBound = 1,  cat = pulp.LpContinuous) for t in teams for c in reg_clusters}
    for c in reg_clusters:
        model_reg+= lpSum([ reg_x[(t,c)] for t in teams ])<=reg_clustersize
        model_reg+= lpSum([ reg_x[(t,c)] for t in teams ])>=2
        (t1,t2) =  chosenEdges[c]
        compatibility = sum([1 for d in days if not blocked_arena[(t1,d, "----" )] and not  blocked_arena[(t2,d, "----" )]   ])
        print ("\nINIT CLUSTER ", getTeamById[t1], ", ", getTeamById[t2] , " ", compatibility )
        for t in [t1,t2]:
            sst= " --  "
            for d in days:
                if blocked_arena[(t,d, "----" )]:
                    sst+= "#"
                else:
                    sst+= " "                
            sst+= " " + getTeamById[t]
            print (sst)
        model_reg+= reg_x[(t1,c)] ==1
        model_reg+= reg_x[(t2,c)] ==1
        c_center_lat[c]= 0.5*(t_lat[t1] + t_lat[t2])
        c_center_lon[c]= 0.5*(t_lon[t1] + t_lon[t2])

                
    for t in teams :
        model_reg+= lpSum([ reg_x[(t,c)] for c in reg_clusters])==1
        
    for i in range(5):
        model_reg+= lpSum([ distanceInKmByGPS(t_lon[t],t_lat[t],c_center_lon[c],c_center_lat[c]) * reg_x[(t,c)] for t in teams for c in reg_clusters])

        if solver == "CBC":
            model_reg.solve(PULP_CBC_CMD())
        elif solver == "Gurobi":
            model_reg.solve(GUROBI(MIPGap=0.0, TimeLimit=120, msg=1))
        else:
            model_reg.solve(XPRESS(msg=1,maxSeconds=120, keepFiles=True))

        for c in reg_clusters:
            # print ("CLUSTER ", c)
            # for t in teams: 
            #     if reg_x[(t,c)].value()>0.01:
            #         print ( getTeamById[t], reg_x[(t,c)].value() , t_lat[t]  , t_lon[t] )
            c_center_lat[c]= 0.5*c_center_lat[c] + 0.5*sum ([ t_lat[t] *reg_x[(t,c)].value() for t in teams]) / sum ([reg_x[(t,c)].value() for t in teams])  
            c_center_lon[c]= 0.5*c_center_lon[c] + 0.5*sum ([ t_lon[t] *reg_x[(t,c)].value() for t in teams]) / sum ([reg_x[(t,c)].value() for t in teams])  
            # print ("new center ",c_center_lat[c], c_center_lon[c] )
            # print ()
    
    reg_cluster_teams = { c : [ t for t in teams if reg_x[(t,c)].value()>0.9 ] for c in reg_clusters }
    print (reg_clusters)

    useRegionalGroupsForTravel= thisSeason.nicename.find("LIGA NACIONAL")>=0
    if useRegionalGroupsForTravel:
        reg_cluster_teams={}
        i=0
        for c in cluster_teams.values():
            if len(c)>0:
                reg_cluster_teams[i]=c
                i+=1
        reg_clusters=reg_cluster_teams.keys()

    for c in reg_clusters:
        print ("CLUSTER ", c)
        for t in reg_cluster_teams[c]:
            print ( getTeamById[t],  t_lat[t]  , t_lon[t] )
        father = reg_cluster_teams[c][0] 
        basicTeams.append(father)
        for t in reg_cluster_teams[c][1:]:
            if t in realteams:
                regionalParent[t]=father
                regionalKids[father].append(t)
                f_team[t]=father
        
    print ("ergebnis")
    print (reg_cluster_teams)
    print (regionalParent)
    print (regionalKids)
    print ()

    # print ("ALL TEAMS REGIONAL ")
    # for c in regionalConferences:
        # father =0
        # for t in c.teams.filter(active=True):
            # if father ==0:
                # father =t.id
                # basicTeams.append(t.id)
            # else:
                # regionalParent[t.id]=father
                # regionalKids[father].append(t.id)
                # f_team[t.id]=father
else :
    basicTeams = teams

basicGames = [ (t1,t2) for (t1,t2) in games if t1 in basicTeams and t2 in basicTeams ]

# print("basicGames",basicGames)
# print (f_team)
# print ("basicTeams", basicTeams)
# print ('parents :')
# print (regionalParent)
# print (regionalKids)

# for t in basicTeams:
#     if len(regionalKids[t])>0:
#         print (getTeamById[t])
#         for t2 in regionalKids[t]:
#             print ("   " ,getTeamById[ t2] , t_conference [t]==t_conference[t2])
# miniGameSequenceLength = 1

nBasicTeams = len (basicTeams)
nBasicTeamsPerCluster = int(nBasicTeams/len(gameClusters)+0.9)
if nBasicTeamsPerCluster%2==1:
    nBasicTeamsPerCluster+=1

playSwissTable = "UCL24Patterns" in special_wishes_active 
playSwissTable=False

if playSwissTable:
    nBasicTeamsPerCluster=nTeams

nRounds1 = nBasicTeamsPerCluster-1
nBasicRounds= nPhases * (nBasicTeamsPerCluster-1)

if nBasicTeamsPerCluster==1 or nBasicRounds==1 or playSwissTable:
    nBasicRounds=nRounds
    nRounds1=nRounds

basicRounds = range (1,nBasicRounds+1)

print ("nPhases ", nPhases)
print ("nGameClusters ", len(gameClusters))
print ("nBasicTeamsPerCluster ", nBasicTeamsPerCluster)
print ("nBasicTeams ", nBasicTeams)
print ("nBasicRounds ", nBasicRounds)
print ("nRounds1 ", nRounds1)

stretch = nRounds/nBasicRounds
# print ("regionalPatternUse " , regionalPatternUse)
rounds1=range(1,nRounds1+1)
nGames=nTeams*nRounds1


getBasicRound={ r : int ((r-1)/stretch)+1  for r in rounds}
getRealRounds = { br : [ r for r in rounds if getBasicRound[r]==br ] for br in basicRounds}
# print ("stretch : " , stretch)

getBasicDays= {r : [] for r in basicRounds}
for r in rounds:
    getBasicDays[getBasicRound[r]]+=(getDays[r])

competitions = {}
for d in Day.objects.filter(season=thisSeason):
    for comp in d.internationalCompetitions.all():
        dtlb = getDateTimeDay[d.id] - datetime.timedelta(days=comp.nDaysNotPlayBefore)
        dtub = getDateTimeDay[d.id] + datetime.timedelta(days=comp.nDaysNotPlayAfter)
        for d2 in days:
            # dt =parse(getDayById[d2]['day'])
            dt =getDateTimeDay[d2]
            if dtlb<=dt and dt<=dtub:
                for t in comp.teams.filter(active=True):
                    # print ("adding ", (t.id,d2) , " for " , comp.name , dtlb , " <= ", dt , " <= ", dtub )
                    competitions[(t.id,d2)]=comp.name

getRoundDaysByDay = {d: [ rd for rd in roundDays if rd[1]==d ] for d in days}
getRoundDaysByRound = {r: [rd for rd in roundDays if rd[0]==r ] for r in rounds}

daysSorted =[]
for dt in sorted([ getDateTimeDay[d] for d in days]):
    daysSorted.append (  getDayByDateTime[dt] )

minRest = { (t,s1,s2) : thisSeason.minDaysBetweenGames for t in teams for s1 in ['A','H'] for s2 in ['A','H']}
for t in teamObjects:
    minRest[(t['id'],'H','H')] = max(minRest[(t['id'],'H','H')], t['minRest_HH'] )
    minRest[(t['id'],'H','A')] = max(minRest[(t['id'],'H','A')], t['minRest_HA'] )
    minRest[(t['id'],'A','H')] = max(minRest[(t['id'],'A','H')], t['minRest_AH'] )
    minRest[(t['id'],'A','A')] = max(minRest[(t['id'],'A','A')], t['minRest_AA'] )
    
maxMinRest = { t : max( [ minRest[(t,s1,s2)] for s1 in ['A','H'] for s2 in ['A','H'] ] )  for t in teams }

conflictDays = { (t,d) : [d] for d in days+higherLeagueDayIds for t in teams}
for t in teams:
    for d1 in days+higherLeagueDayIds:
        diffRounds =False
        for d2 in days+higherLeagueDayIds:
            # print (getRoundsByDay[d1],getRoundsByDay[d2],getRoundsByDay[d1]!=getRoundsByDay[d2])
            if getDateTimeDay[d2]>getDateTimeDay[d1] and  getDateTimeDay[d2]-getDateTimeDay[d1] <= datetime.timedelta(days=maxMinRest[t]):
                # print (getDateTimeDay[d1],getDateTimeDay[d2], getRoundByDay[d1], getRoundByDay[d2],getDateTimeDay[d2] > getDateTimeDay[d1] ,  getDateTimeDay[d2]-getDateTimeDay[d1] , datetime.timedelta(days=thisSeason.minDaysBetweenGames))
                conflictDays[(t,d1)].append(d2)
                if d1 in higherLeagueDayIds+upperAndLowerLeagueIds or d2 in higherLeagueDayIds+upperAndLowerLeagueIds or getRoundsByDay[d1]!=getRoundsByDay[d2]:
                    diffRounds=True

        if not diffRounds:
            conflictDays[(t,d1)]=[]     
            if len(higherTeamsOf[t])>0 and d1 in upperAndLowerLeagueIds:                
                conflictDays[(t,d1)]=[d1] 

# print (thisScenario.sol_solution)

varietyNetWorks=[]
networkName ={}
networkFavTeams ={}
for bn in BroadcastingNetwork.objects.filter(scenario=s2):
    networkName[bn.id] =bn.name
    networkFavTeams[bn.id] = [ t.id for t in bn.teams.all() ]
    if bn.variety:
        varietyNetWorks.append(bn.id)


fixedGames2 = []
for l in thisScenario.fixedgameslist():
    # print (l)
    if  int(l[0]) in getRoundsByDay.keys() and int(l[1]) in  realteams and int(l[2]) in realteams :            
        fixedGames2.append([int(l[1]),int(l[2]),int(l[0]) ])

fixedDays=[]
if thisScenario.sol_fixed_days!= "":
    fixedDays = [ int(g) for g in thisScenario.sol_fixed_days.split('_')] 


fixedRounds=[]
if thisScenario.sol_fixed!='':
    fixedRounds = [ int(g) for g in thisScenario.sol_fixed.split('_')]

fixedGames=[]
currentSolution=[]
currentAwayLocation = { (t,d) : False for t in teams for d in days} 
currentKickoffTimes = defaultdict(lambda:None)

excessGames = { rd: -roundDaysMax[rd] for rd in roundDays }
deficientGames = { rd: roundDaysMin[rd] for rd in roundDays }

fixedBroadCastingSlots = []

for l in thisScenario.solutionlist():
    # print ("adding " , l , len(l)>=4 , int(l[0]) in getRoundsByDay.keys() )
    if len(l)>=4 and int(l[0]) in getRoundsByDay.keys() and int(l[1]) in  realteams and int(l[2]) in realteams :
        # print (" ++++ ")
        h_id= int(l[1])
        a_id= int(l[2])
        r_id= int(l[3])
        d_id= int(l[0])
        # if len(l)>6 and l[6]!="None" and [h_id,a_id,d_id] in fixedGames2:
        if r_id not in getRoundsByDay[d_id] and len(getRoundsByDay[d_id])>0:
            print ("WRONG ROUND", d_id , " not in round " , r_id, " putting it in round " , getRoundsByDay[d_id][0])
            r_id = getRoundsByDay[d_id][0]
        if (r_id,d_id) in roundDays:
            excessGames[(r_id,d_id)]+=1
            deficientGames[(r_id,d_id)]-=1
        nf = [h_id, a_id, d_id]
        for tm in ["----"] + times :
            if  blocked_arena[(h_id,d_id,tm)] :
                print ("Allowing  ",tm , "usage of blocked arena of " ,  getTeamById[h_id] , " at " , getNiceDay[d_id] )
                blocked_arena[(h_id,d_id,tm)]=False

        if len(intersection(getRoundsByDay[d_id], fixedRounds))>0 :
            fixedGames.append(nf)
        if d_id in fixedDays :
            if not nf in fixedGames2:
                fixedGames2.append(nf)
        if len(l)>=4:
            currentSolution.append([ h_id, a_id, r_id,d_id])
            currentAwayLocation[(a_id,d_id)]=h_id
        if len(l) >= 5:
            if l[4].isnumeric() and l[4] in times:
                currentKickoffTimes[(h_id,a_id,d_id)] = l[4] 
            elif l[4] in getIdByTime.keys():
                currentKickoffTimes[(h_id,a_id,d_id)] = getIdByTime[l[4]]
            else:
                currentKickoffTimes[(h_id,a_id,d_id)] = None
        else: 
            if len(times)>0:
                currentKickoffTimes[(h_id,a_id,d_id)] = times[0]
        
        if len(l)>6 and l[6]!="None" and (evalRun or d_id in fixedDays or [h_id,a_id,d_id] in fixedGames2):
            for nw in l[6].split(";"):  
                if int(nw) in networkName.keys():
                    fixedBroadCastingSlots.append((h_id,a_id,d_id,int(nw)))

excessGames = { rd:  max(0,excessGames[rd])  for rd in roundDays }
deficientGames = { rd: max(0,deficientGames[rd])  for rd in roundDays }

print ("currentSolution:")
print (len(currentSolution))
print ("fixedDays :",len(fixedDays))
print ("fixedGames (nur runde ist wichtig):",len(fixedGames))
print ("fixedGames2 (datum ist wichtig):",len(fixedGames2))

# print ("fixedGames",fixedGames)
# for ff in fixedGames:
#     print (getNiceDay[ff[2]], "\t",getTeamById[ff[0]],"\t",getTeamById[ff[1]] )
# print ("fixedGames2",fixedGames2, thisScenario.sol_fixed_games)
# for ff in fixedGames2:
#     print (getNiceDay[ff[2]], "\t",getTeamById[ff[0]],"\t",getTeamById[ff[1]] )

tripElements={t:[] for t in teams}
trip_minDays={}
trip_maxDays={}
trip_prio={}
trip_weekdays={}
for te in TripElement.objects.filter(scenario=s2,active=True):        
    trip_minDays[te.id]=te.minDaysBetweenGames
    trip_maxDays[te.id]=te.maxDaysBetweenGames
    trip_prio[te.id]=te.prio
    trip_weekdays[te.id]=[ dd[:3] for dd in te.possible_start_weekdays() ]
    vt1= [ tt.id for tt in te.visited_teams_first.all()]
    vt2= [ tt.id for tt in te.visited_teams_second.all()]
    vt3= [ tt.id for tt in te.visited_teams_third.all()]
    vt4= [ tt.id for tt in te.visited_teams_fourth.all()]
    for tf in te.travelling_teams.all():
        tripElements[tf.id].append((te.id,vt1,vt2,vt3,vt4))

allowed_weekdays={'--' : [0,1,2,3,4,5,6], 'Mondays':[0], 'Tuesdays':[1], 'Wednesdays':[2], 'Thursdays':[3], 'Fridays':[4], 'Saturdays':[5],'Sundays':[6], 'Weekdays':[0,1,2,3,4], 'Weekends':[5,6], 'Mon.-Thu.':[0,1,2,3] , 'Fri.-Sun.':[4,5,6] } 

hawishes = HAWish.objects.filter(scenario=s2,active=True).order_by('prio').values()
hawTeams = {}
hawDays = {}
hawTimes = {}
hawRounds = {}
hawRoundsString = {}
hawTagweight = {}
for c in HAWish.objects.filter(scenario=s2):
    hawTagweight[c.id] = c.tag_weight()
    # print ()
    # print (c.reason   )
    hawDays[c.id] = []
    hawTeams[c.id] = [t.id for t in c.get_teams()]
    hawTimes[c.id]= [ str(dd.id) for dd in c.timeslots.all() ]

    if c.multidate:
        hawDays[c.id]= [ dd.id for dd in c.dates.all() ]
        # print ("multidate")
    else:
        if c.day and not c.day2:
            hawDays[c.id].append(c.day.id)
            # print('+ ',getDayById[e['day_id']])

        if not c.day and c.day2:
            hawDays[c.id].append(c.day2.id)
            # print('+ ',getDayById[e['day2_id']])

        if not c.day and not c.day2:
            for d in days:
                dt =  getDateTimeDay[d] 
                if dt.weekday() in allowed_weekdays[c.weekdays]:
                    # print (hawDays[e['id']])
                    hawDays[c.id].append(d)
                    # print('+ ',getDayById[d])

        if c.day and c.day2:
            day1= getDateTimeDay[c.day.id] 
            day2= getDateTimeDay[c.day2.id] 
            for d in days:
                dt = getDateTimeDay[d] 
                # print (day1, "<=" , dt , "<=", day2 , " " ,  day1<=dt and dt<=day2 )
                if day1<=dt and dt<=day2 and dt.weekday() in allowed_weekdays[c.weekdays]:
                    # print (day1, "<=" , dt , "<=", day2 , " " ,  day1<=dt and dt<=day2 )
                    hawDays[c.id].append(d)
                    # print('+ ',getDayById[d])

print ("processing encounters")
encwishes = EncWish.objects.filter(scenario=s2,active=True).order_by('prio').values()
encTeams1 = {}
encTeams2 = {}
encGroups = {}
encGames = {}
encTeams1String = {}
encTeams2String = {}
encDays =  { e['id'] : [] for e in encwishes}
encDaySets={}
encTimes = {}
encRounds =  { e['id'] : [] for e in encwishes}
encRoundsString =  { e['id'] : "" for e in encwishes}
encTagweight =  {}
for enc in encwishes:
    enc["seed"]= enc['reason'].find("Seed Game")>=0 or enc['reason'].find("SEED")>=0 
for c in EncWish.objects.filter(scenario=s2,active=True):
    encTagweight[c.id] = c.tag_weight()
    encTimes[c.id]= [ str(dd.id) for dd in c.timeslots.all() ]
    encTeams1[c.id] = []
    encTeams2[c.id] = []
    encGroups[c.id] = []
    encTeams1String[c.id] = ''
    encTeams2String[c.id] = ''
    if c.useEncounterGroups:
        for t in c.encounterGroups.all():
            encGroups[c.id].append(t)
    else:
        encTeams1[c.id] = [t.id for t in c.get_teams1()]
        encTeams2[c.id] = [t.id for t in c.get_teams2()]

    if c.useEncounterGroups:
        tmp_games = [(t1.id,t2.id) for eg in encGroups[c.id] for ec in eg.encounter_set.all() for t1 in ec.homeTeams.all() for t2 in ec.awayTeams.all() if t1!=t2 ]
        tmp_games += [(t2.id,t1.id) for eg in encGroups[c.id] for ec in eg.encounter_set.all() for t1 in ec.homeTeams.all()  for t2 in ec.awayTeams.all() if t1!=t2  and ec.symmetry]
        if c.minDistance>0:
            print ("before " , tmp_games)
            tmp_games=[(t1,t2) for (t1,t2) in tmp_games if distanceById[t1,t2]>=c.minDistance ]
            print ("after " , tmp_games)
        tmp_games=list(set(tmp_games))
        encGames[c.id] = [tmp_games]
    else:
        elemHomeTeams= [encTeams1[c.id]]
        if c.forEachTeam1:
            elemHomeTeams= [ [t] for t in encTeams1[c.id]]
        elemAwayTeams= [ encTeams2[c.id]]
        if c.forEachTeam2:
            elemAwayTeams= [ [t] for t in encTeams2[c.id]]
        encGames[c.id]= []
        # print ("NEW ENC ", c.reason )
        # print (" - ", elemHomeTeams,elemAwayTeams )
        for elh in elemHomeTeams:
            for ela in elemAwayTeams:
                # print (" ---  ENC ", elh,ela)
                tmp_games= [(t1,t2) for t1 in elh for t2 in ela if t1!=t2 ] 
                # tmp_games= [(t1,t2) for t1 in elh for t2 in ela if t1!=t2 and (t1,t2) in games] 
                if c.symmetry:
                    tmp_games += [(t1,t2) for t1 in ela for t2 in elh if t1!=t2 ] 
                    tmp_games=list(set(tmp_games))
                if c.minDistance>0:
                    print ("before " , tmp_games)
                    tmp_games=[(t1,t2) for (t1,t2) in tmp_games if distanceById[t1,t2]>=c.minDistance ]
                    print ("after " , tmp_games)
                if len(tmp_games)>0:
                    encGames[c.id].append(tmp_games)

    if c.multidate:
        encDays[c.id]= [ dd.id for dd in c.dates.all() ]
    else:
        if c.day:
            day1= getDateTimeDay[c.day.id] 

        if c.day and not c.day2:
            encDays[c.id].append(c.day.id)

        if not c.day and c.day2:
            encDays[c.id].append(c.day2.id)

        if not c.day and not c.day2:
            for d in days:
                dt= getDateTimeDay[d] 
                # dt = parse(getDayById[d]['day'])
                if dt.weekday() in allowed_weekdays[c.weekdays]:
                    encDays[c.id].append(d)

        if c.day and c.day2:
            # day1= parse(c.day.day)
            # day2= parse(c.day2.day)
            day1= getDateTimeDay[c.day.id] 
            day2= getDateTimeDay[c.day2.id] 
            for d in days:
                dt= getDateTimeDay[d] 
                # dt = parse(getDayById[d]['day'])
                if day1<=dt and dt<=day2 and dt.weekday() in allowed_weekdays[c.weekdays]:
                    encDays[c.id].append(d)

    encDaySets[c.id]=[]
    elemDays= [ encDays[c.id]]
    if c.forEachDay or c.forOneDay:
        elemDays= [ [d] for d in encDays[c.id]]

    lastDaySet=[]
    for d in elemDays :
        tmpDays=d
        if (c.forEachDay or c.forOneDay) and c.timeframe!=0:
            tmpDays = []
            # day1= parse(getDayById[d[0]]['day'])
            day1= getDateTimeDay[d[0]] 
            if  c.timeframe>0:
                day2= day1 + datetime.timedelta(days=c.timeframe-1)
                # print (e)
                # print (day1, day2)
                for d3 in days:
                    dt= getDateTimeDay[d3] 
                    # dt = parse(getDayById[d3]['day'])
                    if day1<=dt and dt<=day2 :
                        tmpDays.append(d3) 
            else:                    
                r1 = getDayById[d[0]]['round']
                for d3 in days:
                    # dt = parse(getDayById[d3]['day'])
                    dt= getDateTimeDay[d3] 
                    if day1<=dt and getRoundByDay[d3]< r1 + (-c.timeframe) :
                        tmpDays.append(d3)
                # print (" ROUNDWISH ", e, elemEncWishDays[cntr], e['timeframe'])
                # for d4 in elemEncWishDays[cntr]:
                #     print (" - " ,getDayById[d4]['day'])

        if len([ d for  d in  tmpDays if d not in lastDaySet ])>0:
            encDaySets[c.id].append(tmpDays)
            lastDaySet = tmpDays
            # print("-.--- NEW DAYS", tmpDays)

    for ds in encDaySets[c.id]:
        for d3 in ds:
            encRounds[c.id]+= getRoundsByDay[d3]
    encRounds[c.id]=sorted(list(set(encRounds[c.id])))
    for r in encRounds[c.id]:
        encRoundsString[c.id]+= str(r)+"_"
    if encRoundsString[c.id]!="":
        encRoundsString[c.id]=encRoundsString[c.id][:-1]
    # print (encRoundsString[c.id] , " # " ,c.affected_rounds ,  encRoundsString[c.id] != c.affected_rounds)



# print(encDays)
# print (encGames)
# print (encDaySets) 
# print (encRounds) 
# print (encRoundsString) 
# return ("")

seed_games= []
for enc in encwishes :
    if not enc['useEncounterGroups'] and not enc['multidate'] and enc['seed'] and len(encTeams1[enc['id']])==1 and len(encTeams2[enc['id']])==1 and enc['day_id']:
        seed_games.append((encTeams1[enc['id']][0] ,encTeams2[enc['id']][0] ,enc['day_id']))
        # if blocked_arena[(encTeams1[enc['id']][0], enc['day_id'], "----" )]:
        #     print ("SEED GAME IN " , getTeamById[ encTeams1[enc['id']][0]] , " at day ", getNiceDay[enc['day_id']])            

# must_home = {t : sorted([ r  for (h,a,r) in seed_games if h==t]) for t in teams}
# must_away = {t : sorted([ r  for (h,a,r) in seed_games if h==a]) for t in teams}
# print (seed_games)
# print ("must_home",must_home)
# print ("must_away",must_away)
# exit(0)

if runMode=='Improve' and len(thisScenario.solutionlist())>0 :
    oldGameCntr={gm :0 for gm in games }
    for gm in currentSolution:
        if not (gm[0],gm[1]) in oldGameCntr.keys():
            print ("ALERT ",  (gm[0],gm[1]) ," not in ", oldGameCntr.keys() )
        else:
            oldGameCntr[(gm[0],gm[1])]+=1

    unsatisfied_seed_games= [ (h_id,a_id,d_id) for (h_id,a_id,d_id) in seed_games if currentAwayLocation[(a_id,d_id)]!=h_id ]
    missing_gms = [ (t1,t2) for (t1,t2) in realgames if oldGameCntr[(t1,t2)]<gameCntr[(t1,t2)] ]    
    missing_imp = [ ("MISSING",1,nRounds,[t1,t2], 30, "")  for (t1,t2) in missing_gms]    
    seed_imp = [ ("SEED",1,nRounds,[h_id,a_id], 30, "") for (h_id,a_id,d_id) in unsatisfied_seed_games ]
    impScript2 = missing_imp+impScript[1:] 
    if len(missing_imp)>8:
        random.shuffle(impScript2)
    impScript= impScript[:1] + seed_imp+ impScript2

    print ("missing_imp", missing_imp)
    print ("seed_imp", seed_imp)

    release_blocking_games = missing_gms
    if len( missing_gms)>0:
        release_blocking_games += realgames

    for (t1,t2) in release_blocking_games:
        for d in days: 
            if not hidden_arena[(t1,d, "----" )] :
                blocked_arena[(t1,d, "----" )]=False
                # print ("FREIGABE ", getTeamById[t1], getNiceDay[ d]) 
    


onlyEarlyDays= []
onlyLateDays= []

if mathModelName=="NBA" and nRounds >34:
    onlyLateDays=[d for d in days if not getWeekDay[d] in ["Sat", "Sun"] and not getNiceDay[d] in ["Fri, Nov 29, 2019", "Wed, Dec 25, 2019" ,"Tue, Dec 31, 2019", "Mon, Jan 20, 2020", "Mon, Jan 24, 2020"] + ["Fri, Dec 25, 2020" ,"Thu, Dec 31, 2020", "Mon, Jan 18, 2021" ] ]

# if thisSeason.useFeatureOpponentMatrix:     
#     for gm in gameRequirements:
#         # print (gm)
#         if gm.number> 0.5*nPhases:
#             extragames[(gm.team1.id,gm.team2.id)]= gm.number - 0.5*nPhases

alwaysConsiderAllGames = not mathModelName in ["Florida State League" , "UEFA NL"]

# print (conferences)
conferencewishes = ConferenceWish.objects.filter(scenario=s2).values()


# print ("encGroups" ,encGroups)



elemEncWishes ={e['id'] : [] for e in encwishes}
elemEncWishGames={}
elemEncWishDays={}
elemEncWishNum ={}

cntr=0
for e in encwishes:
    for eg in encGames[e['id']] :
        for ed in encDaySets[e['id']]:
            if (len(eg)>0 and len(ed)>0) or enc['minGames']>0:
                cntr+=1
                elemEncWishes[e['id']].append(cntr)
                elemEncWishGames[cntr] = eg
                elemEncWishDays[cntr] = ed
                elemEncWishNum[cntr] = 1
                if e['maxGames'] ==0:
                    elemEncWishNum[cntr]=len(elemEncWishDays[cntr])*len(elemEncWishGames[cntr]) 
                if e['minGames'] > 0:
                    elemEncWishNum[cntr]=e['minGames']


# print (elemEncWishGames)
# print (elemEncWishDays)


encRelRoundsMin  = { el :[] for enc in encwishes for el in elemEncWishes[enc['id']]}
encRelRoundsMax  = { el :[] for enc in encwishes for el in elemEncWishes[enc['id']]}

for enc in encwishes:
    # print (e)
    # print ("ENC !! "  , enc['reason'] )
    for el in elemEncWishes[enc['id']]:
        relDaysSet = set(elemEncWishDays[el])
        for r in basicRounds :
            if len(relDaysSet.intersection(set(getBasicDays[r])))>0:
                frac = len(relDaysSet.intersection(set(getBasicDays[r]))) / len (getBasicDays[r])
                # print (len(relDaysSet.intersection(set(getBasicDays[r]))) , len (getBasicDays[r]) , frac)
                if frac>0:
                    encRelRoundsMin[el].append(r)
                if frac==1:
                    encRelRoundsMax[el].append(r)

    enc['nWishes'] = sum ( elemEncWishNum[ee] for ee in elemEncWishes[enc['id']] )
    if enc['forOneDay']:
        enc['nWishes'] = enc['forOneDayNum'] * len([g for g in encGames[enc['id']] if len(encGames[enc['id']])>0]) 

nElemEncWishes= sum(w['nWishes'] for w in encwishes) 

# print (encRelRoundsMin)

elemHaWishes ={e['id'] : [] for e in hawishes}
elemHaWishTeams={}
elemHaWishDays ={}
elemHaWishFirstDay ={}
elemHaWishNum ={}

cntr =1
for e in hawishes:
    elemTeams= [ hawTeams[e['id']]]
    if e['forEachTeam']:
        elemTeams= [ [t] for t in hawTeams[e['id']]]

    elemDays= [ hawDays[e['id']]]
    if e['forEachDay'] or e['forOneDay'] :
        elemDays= [ [d] for d in hawDays[e['id']]]

    elemHaWishes[e['id']]=[]
    allElemDays=[]
    thisDaySet=[]
    lastDaySet = []
    # print("elemDays",elemDays)
    for d in elemDays :
        # print (e)
        if (e['forEachDay'] or e['forOneDay']) and e['timeframe']!=1:
            thisDaySet=[]
            # day1=  parse(getDayById[d[0]]['day'])
            day1= getDateTimeDay[d[0]]
            if  e['timeframe']>1:
                day2=day1 + datetime.timedelta(days=e['timeframe']-1)
                for d3 in days:
                    # dt = parse(getDayById[d3]['day'])
                    dt= getDateTimeDay[d3]
                    if day1<=dt and dt<=day2 :
                        thisDaySet.append(d3)
            else:
                r1 = getDayById[d[0]]['round']
                for d3 in days:
                    dt= getDateTimeDay[d3]
                    # dt = parse(getDayById[d3]['day'])
                    if day1<=dt and r1 <= getRoundByDay[d3] and getRoundByDay[d3]< r1 + (-e['timeframe']) :
                        thisDaySet.append(d3)
                # print (" ROUND HA WISH ", e['reason'], thisDaySet, e['timeframe'])
        else:
            thisDaySet=d

        # only create wish id new day set is superset
        if len([d for  d in thisDaySet if d not in lastDaySet])>0:
            for t in elemTeams:
                cntr+=1
                elemHaWishes[e['id']].append(cntr)
                elemHaWishTeams[cntr]=t
                elemHaWishDays[cntr]=thisDaySet.copy()
                elemHaWishFirstDay[cntr]=d[0]
                elemHaWishNum[cntr]=1
                if e['maxGames'] ==0:
                    elemHaWishNum[cntr]=len(elemHaWishDays[cntr])*len(elemHaWishTeams[cntr])
                if e['minGames'] > 0:
                    elemHaWishNum[cntr]=e['minGames']
            lastDaySet = thisDaySet.copy()
            allElemDays+= thisDaySet  

    hawRounds[e['id']]=[]
    for d3 in set(allElemDays):
        hawRounds[e['id']]+=getRoundsByDay[d3]
    hawRounds[e['id']]=sorted(list(set(hawRounds[e['id']])))
    hawRoundsString[e['id']]= ""
    for r in hawRounds[e['id']]:
        hawRoundsString[e['id']]+= str(r)+"_"
    if hawRoundsString[e['id']]!="":
        hawRoundsString[e['id']]=hawRoundsString[e['id']][:-1]
    e['nWishes'] = sum ( elemHaWishNum[ee] for ee in elemHaWishes[e['id']] )

    if e['forOneDay']:
        e['nWishes'] = e['forOneDayNum'] * len(elemTeams)
        
nElemHaWishes= sum(w['nWishes'] for w in hawishes) 
# # print ("nElemHaWishes",nElemHaWishes)
# print ("hawRounds",hawRounds)
# print ("hawRoundsString",hawRoundsString)



# encGroups = EncGroup.objects.filter(scenario=s2).values()
# derbyRestrictions = DerbyRestriction.objects.filter(scenario=s2).values()
# fairnessCons = FairnessCon.objects.filter(scenario=s2).values()
# englishWeeks = EnglishCon.objects.filter(scenario=s2).values()
# objectiveFunctionWeights = ObjectiveFunctionWeight.objects.filter(scenario=s2).values()

# gew={}
# for ow in objectiveFunctionWeights:
#     gew[ow['name']]= ow['use'] * ow['prio']

# print(attractivity)
# allow={}
# allow["ATL"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "OKC", "ORL", "PHI", "SAS", "TOR", "WAS"]
# allow["BKN"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DET", "IND", "MEM", "MIA", "MIL", "MIN", "NYK", "ORL", "PHI", "TOR", "WAS"]
# allow["BOS"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DET", "IND", "MEM", "MIA", "MIL", "MIN", "NYK", "ORL", "PHI", "TOR", "WAS"]
# allow["CHA"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "OKC", "ORL", "PHI", "SAS", "TOR", "WAS"]
# allow["CHI"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DEN", "DET", "HOU", "IND", "MEM", "MIL", "MIN", "NOP", "NYK", "OKC", "PHI", "SAS", "TOR", "WAS"]
# allow["CLE"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "OKC", "ORL", "PHI", "SAS", "TOR", "WAS"]
# allow["DAL"]=["ATL", "CHA", "CHI", "CLE", "DAL", "DEN", "HOU", "IND", "MEM", "MIL", "MIN", "NOP", "OKC", "ORL", "PHX", "SAS", "UTA"]
# allow["DEN"]=["DAL", "DEN", "GSW", "LAC", "LAL", "MEM", "MIL", "MIN", "OKC", "PHX", "POR", "SAC", "SAS", "UTA"]
# allow["DET"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "OKC", "ORL", "PHI", "TOR", "WAS"]
# allow["GSW"]=["DEN", "GSW", "LAC", "LAL", "PHX", "POR", "SAC", "UTA"]
# allow["HOU"]=["ATL", "CHA", "CHI", "DAL", "DEN", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "OKC", "ORL", "PHX", "SAS", "UTA"]
# allow["IND"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "OKC", "ORL", "PHI", "SAS", "TOR", "WAS"]
# allow["LAC"]=["GSW", "LAC", "LAL", "PHX", "POR", "SAC", "UTA"]
# allow["LAL"]=["GSW", "LAC", "LAL", "PHX", "POR", "SAC", "UTA"]
# allow["MEM"]=["ATL", "CHA", "CHI", "CLE", "DAL", "DEN", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "OKC", "ORL", "PHI", "SAS", "UTA", "WAS"]
# allow["MIA"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "HOU", "IND", "MEM", "MIA", "MIL", "NOP", "NYK", "OKC", "ORL", "PHI", "SAS", "WAS"]
# allow["MIL"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DEN", "DET", "HOU", "IND", "MEM", "MIL", "MIN", "NOP", "NYK", "OKC", "PHI", "SAS", "TOR", "WAS"]
# allow["MIN"]=["ATL", "CHA", "CHI", "CLE", "DAL", "DEN", "DET", "HOU", "IND", "MEM", "MIL", "MIN", "NOP", "OKC", "PHI", "PHX", "SAS", "UTA"]
# allow["NOP"]=["ATL", "CHA", "CHI", "CLE", "DAL", "DEN", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "OKC", "ORL", "PHI", "SAS", "WAS"]
# allow["NYK"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DET", "IND", "MEM", "MIA", "MIL", "MIN", "NYK", "ORL", "PHI", "TOR", "WAS"]
# allow["OKC"]=["ATL", "CHA", "CHI", "CLE", "DAL", "DEN", "DET", "HOU", "IND", "MEM", "MIL", "MIN", "NOP", "OKC", "ORL", "PHX", "SAS", "UTA"]
# allow["ORL"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DAL", "DET", "HOU", "IND", "MEM", "MIA", "MIL", "NOP", "NYK", "OKC", "ORL", "PHI", "SAS", "WAS"]
# allow["PHI"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DET", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "ORL", "PHI", "TOR", "WAS"]
# allow["PHX"]=["DAL", "DEN", "GSW", "HOU", "LAC", "LAL", "OKC", "PHX", "POR", "SAC", "SAS", "UTA"]
# allow["POR"]=["GSW", "LAC", "LAL", "PHX", "POR", "SAC", "UTA"]
# allow["SAC"]=["DEN", "GSW", "LAC", "LAL", "PHX", "POR", "SAC", "UTA"]
# allow["SAS"]=["ATL", "CHA", "CHI", "DAL", "DEN", "HOU", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "OKC", "ORL", "PHX", "SAS", "UTA"]
# allow["TOR"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DET", "IND", "MEM", "MIL", "MIN", "NYK", "PHI", "TOR", "WAS"]
# allow["UTA"]=["DAL", "DEN", "GSW", "LAC", "LAL", "MIN", "OKC", "PHX", "POR", "SAC", "SAS", "UTA"]
# allow["WAS"]=["ATL", "BKN", "BOS", "CHA", "CHI", "CLE", "DET", "IND", "MEM", "MIA", "MIL", "MIN", "NOP", "NYK", "ORL", "PHI", "TOR", "WAS"]

# print ("DISTANCES NBA")

# shortnames = allow.keys()
# for testDist in [1825,1850,1875]:
#     maxdist =0
#     mindist =1000000
#     cntr=0
#     for t in shortnames:
#         for t2 in shortnames:
#             thisdist = distance[teamByShort[t],teamByShort[t2]]
#             if t2 in allow[t]:
#                 maxdist = max(maxdist,thisdist)
#                 if thisdist > testDist:
#                     # print ("close : " ,teamByShort[t] , teamByShort[t2] , thisdist )
#                     cntr+=1
#             else:
#                 mindist = min(mindist,thisdist)
#                 if thisdist < testDist:
#                     # print ("far : " ,teamByShort[t] , teamByShort[t2] , thisdist )
#                     cntr+=1
#     print ("mismatch at " ,  testDist ," :  ", cntr)

# print ("maxdist ", maxdist)
# print ("mindist ", mindist)



# gameCntr = { (t1,t2) :0 for t1 in shortnames for t2 in shortnames }
# wantedGames =[('TOR','NOP'), ('LAC','LAL'), ('CHA','CHI'), ('ORL','CLE'), ('IND','DET'), ('PHI','BOS'), ('MIA','MEM'), ('BKN','MIN'), ('SAS','NYK'), ('DAL','WAS'), ('UTA','OKC'), ('POR','DEN'), ('PHX','SAC'), ('DET','ATL'), ('HOU','MIL'), ('GSW','LAC'), ('CHA','MIN'), ('BOS','TOR'), ('BKN','NYK'), ('MEM','CHI'), ('NOP','DAL'), ('OKC','WAS'), ('DEN','PHX'), ('SAC','POR'), ('LAL','UTA'), ('MIL','MIA'), ('DET','PHI'), ('NYK','BOS'), ('ATL','ORL'), ('CLE','IND'), ('HOU','NOP'), ('CHI','TOR'), ('SAS','WAS'), ('UTA','SAC'), ('PHX','LAC'), ('OKC','GSW'), ('MEM','BKN'), ('MIN','MIA'), ('DAL','POR'), ('LAL','CHA'), ('NYK','CHI'), ('DET','IND'), ('TOR','ORL'), ('ATL','PHI'), ('MIL','CLE'), ('NOP','GSW'), ('HOU','OKC'), ('SAS','POR'), ('SAC','DEN'), ('PHX','UTA'), ('LAC','CHA'), ('MIA','ATL'), ('DEN','DAL'), ('LAL','MEM'), ('CLE','CHI'), ('PHI','MIN'), ('ORL','NYK'), ('TOR','DET'), ('BKN','IND'), ('BOS','MIL'), ('WAS','HOU'), ('OKC','POR'), ('SAC','CHA'), ('UTA','LAC'), ('GSW','PHX'), ('ATL','MIA'), ('NOP','DEN'), ('LAC','SAS'), ('IND','CLE'), ('BKN','HOU'), ('ORL','MIL'), ('BOS','NYK'), ('CHI','DET'), ('DAL','LAL'), ('SAC','UTA'), ('GSW','SAS'), ('OKC','NOP'), ('DET','BKN'), ('ORL','DEN'), ('WAS','MIN'), ('MEM','PHX'), ('MIL','TOR'), ('GSW','CHA'), ('POR','PHI'), ('IND','CHI'), ('MIA','HOU'), ('NYK','SAC'), ('SAS','LAL'), ('CLE','DAL'), ('LAC','UTA'), ('WAS','DET'), ('BKN','NOP'), ('MEM','HOU'), ('MIN','MIL'), ('PHX','PHI'), ('GSW','POR'), ('CLE','BOS'), ('CHA','IND'), ('ATL','SAS'), ('CHI','LAL'), ('OKC','ORL'), ('DEN','MIA'), ('DET','NYK'), ('IND','WAS'), ('ATL','CHI'), ('HOU','GSW'), ('TOR','SAC'), ('MEM','MIN'), ('DAL','ORL'), ('UTA','PHI'), ('LAC','MIL'), ('CHA','BOS'), ('SAS','OKC'), ('PHX','MIA'), ('LAC','POR'), ('WAS','CLE'), ('IND','DET'), ('ORL','MEM'), ('ATL','SAC'), ('MIN','GSW'), ('NOP','TOR'), ('DAL','NYK'), ('UTA','MIL'), ('DEN','PHI'), ('POR','BKN'), ('LAL','MIA'), ('SAS','BOS'), ('CHA','NOP'), ('MEM','DAL'), ('OKC','GSW'), ('CHI','HOU'), ('MIN','DEN'), ('PHI','CHA'), ('ORL','IND'), ('OKC','MIL'), ('NYK','CLE'), ('PHX','BKN'), ('POR','ATL'), ('LAL','TOR'), ('DET','MIN'), ('BOS','DAL'), ('NOP','HOU'), ('SAS','MEM'), ('LAC','TOR'), ('GSW','UTA'), ('PHI','CLE'), ('IND','OKC'), ('MIA','DET'), ('CHI','NYK'), ('DEN','ATL'), ('UTA','BKN'), ('PHX','LAL'), ('SAC','POR'), ('CHA','MEM'), ('ORL','PHI'), ('HOU','LAC'), ('BOS','WAS'), ('MIN','SAS'), ('LAL','GSW'), ('POR','TOR'), ('CLE','MIA'), ('MIL','CHI'), ('NYK','DAL'), ('NOP','LAC'), ('PHX','ATL'), ('DEN','BKN'), ('CHA','DET'), ('ORL','SAS'), ('HOU','IND'), ('OKC','PHI'), ('MEM','UTA'), ('MIN','WAS'), ('GSW','BOS'), ('LAL','SAC'), ('CHI','BKN'), ('IND','MIL'), ('NYK','CHA'), ('MIN','HOU'), ('MIA','NOP'), ('SAS','POR'), ('DAL','TOR'), ('LAC','ATL'), ('CLE','PHI'), ('SAC','BOS'), ('MEM','DEN'), ('ORL','WAS'), ('NOP','GSW'), ('LAL','ATL'), ('NYK','CLE'), ('TOR','CHA'), ('BKN','IND'), ('CHI','MIL'), ('HOU','POR'), ('DAL','SAS'), ('PHX','BOS'), ('UTA','MIN'), ('LAC','OKC'), ('MEM','GSW'), ('NOP','POR'), ('SAC','PHX'), ('LAL','OKC'), ('PHI','NYK'), ('WAS','SAS'), ('BKN','CHA'), ('MIA','CLE'), ('DAL','GSW'), ('ATL','MIL'), ('TOR','ORL'), ('CHI','DET'), ('MIN','UTA'), ('DEN','HOU'), ('LAC','BOS'), ('MIL','POR'), ('PHX','NOP'), ('DET','ATL'), ('WAS','CHA'), ('BKN','SAC'), ('OKC','LAL'), ('CHI','MIA'), ('PHI','SAS'), ('DAL','CLE'), ('DEN','BOS'), ('UTA','GSW'), ('LAC','HOU'), ('MIN','PHX'), ('CHA','CHI'), ('IND','ORL'), ('PHI','MIA'), ('NYK','SAS'), ('ATL','TOR'), ('MEM','LAL'), ('CLE','POR'), ('MIL','DET'), ('UTA','NOP'), ('HOU','DAL'), ('NYK','BKN'), ('WAS','SAC'), ('DEN','PHX'), ('LAC','NOP'), ('CLE','BKN'), ('IND','MEM'), ('DET','ORL'), ('MIA','CHA'), ('ATL','MIN'), ('TOR','PHI'), ('BOS','SAC'), ('CHI','POR'), ('MIL','UTA'), ('SAS','LAL'), ('GSW','OKC'), ('DAL','LAC'), ('DEN','WAS'), ('BOS','BKN'), ('CHA','DET'), ('CLE','ORL'), ('PHI','SAC'), ('IND','UTA'), ('TOR','NYK'), ('MIL','ATL'), ('MEM','LAC'), ('HOU','MIA'), ('SAS','MIN'), ('PHX','WAS'), ('NOP','LAL'), ('POR','OKC'), ('GSW','CHI'), ('BKN','BOS'), ('DET','CHA'), ('ORL','TOR'), ('CLE','MIL'), ('NYK','PHI'), ('IND','ATL'), ('MIA','GSW'), ('OKC','NOP'), ('MEM','UTA'), ('SAS','LAC'), ('PHX','DAL'), ('POR','CHI'), ('LAL','WAS'), ('SAC','DEN'), ('PHI','IND'), ('HOU','ATL'), ('MIL','CHA'), ('BKN','MIA'), ('NYK','BOS'), ('MIN','MEM'), ('LAL','DAL'), ('NOP','OKC'), ('DET','SAS'), ('ORL','GSW'), ('TOR','UTA'), ('LAC','WAS'), ('CHA','PHX'), ('PHI','UTA'), ('ATL','GSW'), ('MEM','IND'), ('MIL','NYK'), ('SAC','CHI'), ('CLE','DET'), ('WAS','ORL'), ('NOP','DAL'), ('TOR','MIA'), ('SAS','HOU'), ('DEN','LAL'), ('LAC','POR'), ('CHA','GSW'), ('DET','MIL'), ('ORL','PHX'), ('ATL','BKN'), ('BOS','MIA'), ('OKC','IND'), ('CHI','MEM'), ('DAL','MIN'), ('UTA','LAL'), ('POR','SAC'), ('WAS','PHI'), ('NYK','DEN'), ('TOR','HOU'), ('NOP','PHX'), ('CHA','BKN'), ('DET','IND'), ('CLE','ORL'), ('BOS','DEN'), ('CHI','GSW'), ('OKC','MIN'), ('MIA','WAS'), ('MIL','LAC'), ('SAS','SAC'), ('POR','LAL'), ('DAL','NOP'), ('PHI','CLE'), ('NYK','IND'), ('HOU','PHX'), ('UTA','MEM'), ('BKN','DEN'), ('CHA','ATL'), ('MIA','CHI'), ('WAS','LAC'), ('PHI','TOR'), ('DAL','SAC'), ('POR','OKC'), ('LAL','MIN'), ('IND','LAC'), ('BOS','CLE'), ('NOP','DET'), ('MIL','ORL'), ('HOU','SAC'), ('CHI','TOR'), ('PHX','MIN'), ('UTA','OKC'), ('GSW','MEM'), ('PHI','DEN'), ('CHA','WAS'), ('MIA','ATL'), ('POR','NYK'), ('IND','BOS'), ('CLE','HOU'), ('TOR','LAC'), ('ORL','LAL'), ('BKN','CHA'), ('CHI','ATL'), ('MIN','UTA'), ('PHX','MEM'), ('MIL','NOP'), ('SAC','OKC'), ('GSW','NYK'), ('BOS','PHI'), ('SAS','CLE'), ('DET','DAL'), ('DEN','POR'), ('ORL','HOU'), ('PHI','NOP'), ('ATL','IND'), ('CHI','CHA'), ('MIN','LAC'), ('MIA','LAL'), ('MEM','MIL'), ('SAC','NYK'), ('UTA','GSW'), ('PHX','SAS'), ('TOR','BKN'), ('CHI','LAC'), ('MEM','WAS'), ('MIL','CLE'), ('DAL','MIA'), ('HOU','DET'), ('DEN','OKC'), ('NOP','ORL'), ('IND','CHA'), ('ATL','LAL'), ('BKN','PHI'), ('DEN','NYK'), ('GSW','SAC'), ('DET','WAS'), ('TOR','CLE'), ('OKC','CHI'), ('MIL','DAL'), ('MEM','MIA'), ('HOU','SAS'), ('PHX','POR'), ('IND','LAL'), ('CHA','SAC'), ('NYK','ATL'), ('NOP','BKN'), ('UTA','ORL'), ('LAC','PHX'), ('CLE','CHA'), ('WAS','CHI'), ('DET','TOR'), ('PHI','MIA'), ('OKC','MEM'), ('MIN','NOP'), ('DAL','BOS'), ('DEN','ORL'), ('POR','GSW'), ('ATL','UTA'), ('MIL','LAL'), ('SAS','BKN'), ('LAC','HOU'), ('CLE','MEM'), ('IND','SAC'), ('BOS','DET'), ('TOR','WAS'), ('PHI','DAL'), ('MIA','NYK'), ('OKC','PHX'), ('DEN','MIN'), ('POR','ORL'), ('GSW','NOP'), ('CHA','UTA'), ('BKN','ATL'), ('DET','CHI'), ('PHI','WAS'), ('NYK','MIL'), ('MEM','SAC'), ('SAS','LAC'), ('PHX','HOU'), ('POR','MIN'), ('TOR','DAL'), ('BOS','CHA'), ('MIL','IND'), ('OKC','LAC'), ('LAL','DEN'), ('CLE','ATL'), ('ORL','CHI'), ('DET','PHI'), ('IND','TOR'), ('NYK','WAS'), ('MIA','UTA'), ('MEM','SAS'), ('PHX','DEN'), ('SAC','HOU'), ('POR','NOP'), ('GSW','MIN'), ('TOR','BOS'), ('PHI','MIL'), ('GSW','HOU'), ('LAL','LAC'), ('DEN','NOP'), ('DET','WAS'), ('OKC','MEM'), ('BKN','NYK'), ('DAL','SAS'), ('SAC','MIN'), ('UTA','POR'), ('BOS','CLE'), ('CHA','OKC'), ('ORL','PHI'), ('ATL','MIL'), ('MIA','IND'), ('GSW','PHX'), ('DEN','MEM'), ('NOP','IND'), ('BOS','TOR'), ('CHI','ATL'), ('HOU','BKN'), ('MIN','CLE'), ('WAS','NYK'), ('MIA','PHI'), ('GSW','DAL'), ('SAS','DET'), ('MIL','ORL'), ('SAC','PHX'), ('POR','LAL'), ('LAC','UTA'), ('TOR','OKC'), ('MEM','CHA'), ('NOP','HOU'), ('DEN','SAC'), ('LAL','DAL'), ('ORL','ATL'), ('WAS','MIA'), ('MIN','BKN'), ('CHI','MIL'), ('UTA','DET'), ('POR','PHX'), ('CHA','BOS'), ('IND','PHI'), ('SAC','LAC'), ('TOR','CLE'), ('HOU','DEN'), ('SAS','GSW'), ('OKC','DAL'), ('WAS','ORL'), ('NYK','POR'), ('MIL','MIN'), ('LAL','PHX'), ('CLE','CHA'), ('IND','DEN'), ('MIA','TOR'), ('MIN','GSW'), ('CHI','UTA'), ('DAL','BKN'), ('SAS','OKC'), ('SAC','MEM'), ('LAC','DET'), ('BOS','ATL'), ('ORL','MIA'), ('WAS','POR'), ('HOU','PHI'), ('PHX','NYK'), ('LAL','NOP'), ('LAC','MEM'), ('BKN','TOR'), ('ORL','UTA'), ('ATL','IND'), ('CLE','OKC'), ('CHI','BOS'), ('WAS','DEN'), ('DAL','CHA'), ('GSW','DET'), ('MIL','SAS'), ('SAC','NOP'), ('LAC','NYK'), ('MIA','POR'), ('CLE','MIN'), ('PHX','MEM'), ('LAL','DET'), ('ORL','BKN'), ('WAS','BOS'), ('CHA','IND'), ('PHI','OKC'), ('ATL','DEN'), ('NOP','UTA'), ('DAL','CHI'), ('SAS','MIL'), ('SAC','GSW'), ('CLE','DET'), ('TOR','POR'), ('BKN','OKC'), ('MEM','MIN'), ('PHX','SAC'), ('LAL','NYK'), ('IND','MIA'), ('BOS','SAS'), ('CHA','TOR'), ('ORL','WAS'), ('DAL','DEN'), ('ATL','HOU'), ('NOP','CHI'), ('UTA','NYK'), ('GSW','MIL'), ('PHI','BOS'), ('DET','CLE'), ('MIN','POR'), ('OKC','HOU'), ('WAS','ATL'), ('BKN','MIA'), ('CHI','IND'), ('NYK','NOP'), ('MEM','SAS'), ('DAL','LAL'), ('UTA','CHA'), ('PHX','ORL'), ('SAC','MIL'), ('LAC','GSW'), ('HOU','MIN'), ('DET','CHI'), ('BOS','NOP'), ('OKC','LAL'), ('DAL','PHI'), ('DEN','CLE'), ('POR','MIL'), ('NYK','MIA'), ('WAS','UTA'), ('BKN','ATL'), ('MEM','GSW'), ('TOR','SAS'), ('PHX','CHA'), ('DEN','LAC'), ('DET','NOP'), ('IND','PHI'), ('BOS','CHI'), ('MIN','OKC'), ('POR','CHA'), ('SAC','ORL'), ('LAL','CLE'), ('ATL','PHX'), ('BKN','UTA'), ('MEM','HOU'), ('MIL','NYK'), ('LAC','CLE'), ('GSW','DAL'), ('PHI','BKN'), ('BOS','DET'), ('MIA','SAS'), ('MIN','IND'), ('OKC','TOR'), ('CHI','WAS'), ('DEN','CHA'), ('HOU','POR'), ('SAC','DAL'), ('LAL','ORL'), ('NYK','PHX'), ('MIL','BOS'), ('NOP','UTA'), ('GSW','DEN'), ('LAC','ORL'), ('PHI','CHI'), ('IND','MIN'), ('TOR','WAS'), ('MEM','CLE'), ('OKC','MIA'), ('SAS','ATL'), ('DAL','POR'), ('NOP','LAC'), ('BKN','MIL'), ('BOS','PHX'), ('ATL','DET'), ('NYK','PHI'), ('CHI','CLE'), ('MIN','TOR'), ('HOU','LAL'), ('GSW','ORL'), ('OKC','POR'), ('UTA','SAC'), ('SAS','MIA'), ('DEN','IND'), ('WAS','DET'), ('ATL','TOR'), ('BKN','PHI'), ('MIL','CHI'), ('MEM','NOP'), ('CLE','NYK'), ('HOU','OKC'), ('CHA','ORL'), ('MIA','SAC'), ('BOS','LAL'), ('MIN','DEN'), ('UTA','IND'), ('PHX','SAS'), ('POR','GSW'), ('DAL','LAC'), ('ORL','OKC'), ('DET','SAC'), ('ATL','LAC'), ('NYK','LAL'), ('BOS','MEM'), ('TOR','PHI'), ('MIA','WAS'), ('HOU','DEN'), ('CHI','MIN'), ('NOP','SAS'), ('PHX','IND'), ('GSW','UTA'), ('CLE','WAS'), ('BKN','LAL'), ('POR','DAL'), ('CHA','MIL'), ('ORL','BOS'), ('DET','MEM'), ('NYK','TOR'), ('OKC','ATL'), ('NOP','DEN'), ('MIN','HOU'), ('MIA','LAC'), ('CHI','SAC'), ('SAS','PHX'), ('GSW','IND'), ('UTA','DAL'), ('DET','BKN'), ('CLE','CHI'), ('MIN','OKC'), ('PHI','LAL'), ('DEN','HOU'), ('SAS','TOR'), ('NYK','BKN'), ('NOP','BOS'), ('ORL','LAC'), ('MEM','PHX'), ('ATL','WAS'), ('POR','IND'), ('DET','CLE'), ('MIA','ORL'), ('OKC','DAL'), ('MIN','SAC'), ('CHI','SAS'), ('UTA','HOU'), ('CHA','NYK'), ('TOR','ATL'), ('MIA','BOS'), ('PHI','GSW'), ('CLE','NOP'), ('MEM','DEN'), ('MIL','WAS'), ('DAL','PHX'), ('LAL','LAC'), ('IND','CHI'), ('BKN','DET'), ('NYK','MEM'), ('SAS','UTA'), ('POR','HOU'), ('SAC','OKC'), ('WAS','CHA'), ('CLE','TOR'), ('ATL','PHI'), ('BOS','GSW'), ('LAC','SAC'), ('DEN','UTA'), ('DET','TOR'), ('BKN','CHI'), ('HOU','DAL'), ('NOP','MEM'), ('MIL','DEN'), ('PHX','OKC'), ('LAL','POR'), ('LAC','MIN'), ('ORL','MIA'), ('IND','NYK'), ('WAS','BKN'), ('CLE','GSW'), ('DAL','ATL'), ('BOS','PHI'), ('SAS','CHA'), ('SAC','LAL'), ('POR','UTA'), ('DET','DEN'), ('HOU','NOP'), ('MIL','PHX'), ('TOR','CHI'), ('IND','DAL'), ('WAS','GSW'), ('CLE','NYK'), ('CHA','ORL'), ('ATL','BOS'), ('MIA','PHI'), ('BKN','PHX'), ('MEM','DET'), ('SAC','MIN'), ('LAC','SAS'), ('NOP','MIL'), ('HOU','CHA'), ('DEN','POR'), ('LAL','SAS'), ('DET','PHX'), ('BKN','GSW'), ('TOR','IND'), ('BOS','ORL'), ('MIN','ATL'), ('OKC','CLE'), ('DAL','MEM'), ('UTA','DEN'), ('LAC','MIA'), ('NYK','ORL'), ('CHI','NOP'), ('MIL','PHI'), ('POR','SAS'), ('LAL','HOU'), ('WAS','DAL'), ('PHI','MEM'), ('BOS','ATL'), ('OKC','DET'), ('IND','TOR'), ('PHX','HOU'), ('SAC','MIA'), ('UTA','POR'), ('ORL','MIL'), ('CHA','DAL'), ('DET','NYK'), ('TOR','BKN'), ('IND','NOP'), ('MIN','LAC'), ('GSW','LAL'), ('PHX','DEN'), ('SAC','SAS'), ('OKC','BOS'), ('PHI','CHI'), ('WAS','MEM'), ('ATL','NYK'), ('HOU','UTA'), ('CLE','LAC'), ('POR','MIA'), ('ORL','ATL'), ('IND','BKN'), ('DET','CHA'), ('TOR','MIN'), ('MIL','SAC'), ('DAL','UTA'), ('DEN','SAS'), ('GSW','MIA'), ('LAL','PHX'), ('WAS','CHI'), ('PHI','LAC'), ('NOP','POR'), ('OKC','SAS'), ('HOU','BOS'), ('CLE','ATL'), ('ORL','DET'), ('IND','MIL'), ('BKN','TOR'), ('NYK','WAS'), ('MIN','CHA'), ('MEM','POR'), ('DAL','SAC'), ('PHX','GSW'), ('UTA','MIA'), ('DEN','LAL'), ('BOS','LAC'), ('NOP','OKC'), ('DET','MIL'), ('ATL','MIA'), ('PHI','BKN'), ('CHI','CHA'), ('SAC','MEM'), ('GSW','HOU'), ('WAS','CLE'), ('ORL','DAL'), ('NYK','IND'), ('TOR','PHX'), ('MIN','BOS'), ('OKC','DEN'), ('UTA','SAS'), ('LAL','MEM'), ('POR','NOP'), ('LAC','SAC'), ('CHA','BKN'), ('ATL','DAL'), ('MIA','CLE'), ('CHI','PHX'), ('MIL','PHI'), ('UTA','HOU'), ('LAL','BOS'), ('TOR','IND'), ('DEN','MIN'), ('OKC','SAS'), ('CHI','WAS'), ('GSW','NOP'), ('POR','DET'), ('PHI','ATL'), ('CLE','MIA'), ('WAS','MIL'), ('BKN','ORL'), ('HOU','NYK'), ('DAL','MIN'), ('UTA','PHX'), ('LAC','MEM'), ('IND','CHA'), ('TOR','MIL'), ('CHI','OKC'), ('DEN','DET'), ('POR','BOS'), ('LAL','NOP'), ('GSW','SAC'), ('WAS','BKN'), ('CHA','NYK'), ('CLE','PHI'), ('SAS','DAL'), ('MIA','MIN'), ('ATL','ORL'), ('HOU','MEM'), ('PHX','LAC'), ('UTA','BOS'), ('PHI','NYK'), ('IND','POR'), ('OKC','SAC'), ('GSW','LAL'), ('ORL','MIN'), ('ATL','BKN'), ('TOR','CHA'), ('NOP','CLE'), ('MIA','DAL'), ('MIL','OKC'), ('MEM','SAC'), ('PHX','DET'), ('UTA','WAS'), ('LAC','DEN'), ('NYK','CHI'), ('MIA','BKN'), ('ATL','POR'), ('CLE','IND'), ('MEM','LAL'), ('BOS','HOU'), ('SAS','ORL'), ('PHX','GSW'), ('CHA','MIL'), ('MIN','DAL'), ('LAC','PHI'), ('SAC','DET'), ('DEN','TOR'), ('NOP','LAL'), ('GSW','WAS'), ('NYK','HOU'), ('ORL','POR'), ('CLE','UTA'), ('ATL','MEM'), ('MIA','MIL'), ('CHI','DAL'), ('SAS','IND'), ('CHA','SAS'), ('BOS','BKN'), ('OKC','LAC'), ('NOP','MIN'), ('DEN','GSW'), ('PHX','TOR'), ('LAL','PHI'), ('SAC','WAS'), ('CLE','BOS'), ('DET','OKC'), ('MIA','ORL'), ('BKN','MEM'), ('NYK','UTA'), ('MIN','CHI'), ('DAL','NOP'), ('MIL','IND'), ('POR','WAS'), ('CHA','DEN'), ('HOU','LAC'), ('SAC','PHI'), ('GSW','TOR'), ('WAS','ATL'), ('NYK','OKC'), ('BKN','SAS'), ('CHI','IND'), ('NOP','MIA'), ('MIN','ORL'), ('BOS','UTA'), ('DAL','MEM'), ('PHX','POR'), ('LAL','MIL'), ('CHA','HOU'), ('DET','UTA'), ('CLE','DEN'), ('MEM','ATL'), ('GSW','PHI'), ('POR','SAC'), ('BKN','CHI'), ('LAC','LAL'), ('MIN','NOP'), ('PHX','MIL'), ('BOS','OKC'), ('DAL','IND'), ('WAS','MIA'), ('HOU','ORL'), ('NYK','DET'), ('CLE','SAS'), ('SAC','TOR'), ('ATL','CHA'), ('DEN','MIL'), ('UTA','TOR'), ('IND','BOS'), ('WAS','NYK'), ('CHI','CLE'), ('SAS','DAL'), ('HOU','MIN'), ('MEM','ORL'), ('POR','PHX'), ('LAL','BKN'), ('GSW','LAC'), ('MIA','CHA'), ('PHI','DET'), ('ATL','NYK'), ('OKC','UTA'), ('DAL','DEN'), ('SAC','NOP'), ('ORL','CHI'), ('MIL','BOS'), ('POR','MEM'), ('GSW','BKN'), ('LAL','HOU'), ('CHA','CLE'), ('BOS','WAS'), ('OKC','MIN'), ('MIA','NYK'), ('SAS','DEN'), ('UTA','NOP'), ('LAC','BKN'), ('DAL','PHX'), ('ATL','CLE'), ('TOR','DET'), ('PHI','IND'), ('MIA','CHI'), ('MIL','GSW'), ('SAS','MIN'), ('UTA','MEM'), ('LAC','NOP'), ('POR','HOU'), ('ORL','CHA'), ('WAS','OKC'), ('CHI','BOS'), ('SAC','BKN'), ('LAL','DEN'), ('PHI','WAS'), ('NOP','ATL'), ('TOR','GSW'), ('MIL','MIA'), ('SAS','MEM'), ('UTA','LAL'), ('LAC','DAL'), ('DET','ORL'), ('NYK','CHA'), ('HOU','CLE'), ('MEM','OKC'), ('SAC','DAL'), ('POR','MIN'), ('PHI','TOR'), ('IND','GSW'), ('BOS','NYK'), ('ATL','OKC'), ('BKN','WAS'), ('CHI','MIA'), ('NOP','SAS'), ('DEN','LAC'), ('PHX','MIN'), ('LAL','UTA'), ('ORL','CLE'), ('CHA','PHI'), ('MIL','MEM'), ('HOU','SAC'), ('POR','DAL'), ('DET','GSW'), ('IND','MIA'), ('TOR','BOS'), ('ATL','WAS'), ('OKC','DEN'), ('SAS','CHI'), ('UTA','MIN'), ('LAC','PHX'), ('BKN','BOS'), ('PHI','ATL'), ('IND','CLE'), ('CHA','LAL'), ('ORL','SAC'), ('NYK','GSW'), ('HOU','CHI'), ('WAS','MIL'), ('MEM','NOP'), ('PHX','DAL'), ('TOR','DEN'), ('DET','LAL'), ('MIN','POR'), ('NOP','SAC'), ('SAS','UTA'), ('WAS','BOS'), ('NYK','LAC'), ('IND','PHX'), ('MIA','OKC'), ('BKN','ORL'), ('CHI','DEN'), ('MIL','DET'), ('DAL','HOU'), ('CHA','POR'), ('CLE','SAC'), ('TOR','LAL'), ('NOP','MEM'), ('MIN','PHI'), ('UTA','SAS'), ('ORL','IND'), ('BKN','LAC'), ('WAS','PHX'), ('DET','POR'), ('MIA','DEN'), ('NYK','TOR'), ('MEM','BOS'), ('MIL','HOU'), ('GSW','ATL'), ('CLE','LAL'), ('OKC','CHA'), ('CHI','PHI'), ('MIN','SAS'), ('DAL','UTA'), ('SAC','ATL'), ('ORL','BKN'), ('IND','HOU'), ('DET','LAC'), ('PHI','PHX'), ('BOS','POR'), ('NOP','NYK'), ('MIL','WAS'), ('DEN','SAS'), ('BKN','CLE'), ('CHA','LAC'), ('WAS','LAL'), ('CHI','NYK'), ('MIA','PHX'), ('MEM','TOR'), ('GSW','OKC'), ('UTA','ATL'), ('DAL','MIL'), ('DET','HOU'), ('BOS','MIN'), ('ORL','NOP'), ('PHI','POR'), ('GSW','SAS'), ('SAC','IND'), ('CHA','MIA'), ('CLE','PHX'), ('TOR','MEM'), ('BKN','POR'), ('MIN','LAL'), ('UTA','CHI'), ('DEN','OKC'), ('LAC','IND'), ('PHI','HOU'), ('ATL','NOP'), ('GSW','DEN'), ('SAC','SAS'), ('ORL','CHA'), ('WAS','NOP'), ('BKN','DET'), ('BOS','MIA'), ('MIN','DAL'), ('MEM','NYK'), ('OKC','PHX'), ('UTA','CLE'), ('MIL','TOR'), ('LAL','IND'), ('HOU','GSW'), ('SAC','LAC'), ('POR','UTA'), ('IND','BKN'), ('DET','MIA'), ('WAS','PHI'), ('ATL','CHA'), ('TOR','MIL'), ('NYK','MIN'), ('BOS','ORL'), ('MEM','DAL'), ('SAS','GSW'), ('DEN','CHI'), ('PHX','CLE'), ('LAC','OKC'), ('SAC','LAL'), ('CHA','ATL'), ('PHI','ORL'), ('BOS','MIL'), ('NYK','MIA'), ('IND','WAS'), ('PHX','CHI'), ('BKN','DAL'), ('DEN','UTA'), ('MIN','DET'), ('SAS','NOP'), ('HOU','TOR'), ('SAC','CLE'), ('POR','MEM'), ('LAL','OKC'), ('WAS','TOR'), ('ATL','DET'), ('MIA','IND'), ('PHI','MIL'), ('OKC','BKN'), ('NOP','CHA'), ('MIN','PHX'), ('DAL','HOU'), ('SAS','SAC'), ('DEN','MEM'), ('POR','CLE'), ('UTA','LAC'), ('LAL','CHI'), ('BOS','IND'), ('CHA','TOR'), ('NYK','ORL'), ('HOU','SAS'), ('LAC','CHI'), ('GSW','CLE'), ('MIA','DET'), ('MIL','BKN'), ('NOP','PHX'), ('MIN','SAC'), ('POR','DEN'), ('LAL','GSW'), ('ORL','BOS'), ('TOR','ATL'), ('OKC','NYK'), ('HOU','WAS'), ('SAS','PHI'), ('DAL','DET'), ('IND','ORL'), ('NOP','PHI'), ('CHA','WAS'), ('CLE','MIL'), ('CHI','BKN'), ('MIA','BOS'), ('MEM','OKC'), ('LAC','GSW'), ('DEN','SAC'), ('PHX','UTA'), ('SAS','HOU'), ('TOR','NYK'), ('MIL','ATL'), ('LAL','MIN'), ('CLE','BKN'), ('DET','BOS'), ('CHA','MIA'), ('IND','SAS'), ('CHI','ORL'), ('MEM','PHI'), ('HOU','PHX'), ('OKC','UTA'), ('NOP','WAS'), ('DEN','DAL'), ('LAC','MIN'), ('GSW','POR'), ('NYK','DET'), ('MIA','TOR'), ('UTA','DEN'), ('LAL','SAC'), ('PHI','CHA'), ('BOS','CHI'), ('ATL','CLE'), ('WAS','IND'), ('HOU','MEM'), ('BKN','MIL'), ('SAS','NOP'), ('MIN','NYK'), ('DAL','OKC'), ('ORL','TOR'), ('SAC','GSW'), ('POR','LAC'), ('PHX','LAL')]
# wantedEncounters = set(wantedGames)
# unwantedEncounters = [ (t1,t2) for t1 in shortnames for t2 in shortnames if not (t1,t2) in wantedEncounters ]
# # print ("unwanted ", unwantedEncounters)

# for (t1, t2) in wantedGames:
#     gameCntr[(t1,t2)]+=1

# # for t1 in shortnames:
# #     for t2 in shortnames:
# #         print (gameCntr)

# playOnce = [ e for e in wantedEncounters if gameCntr[e] ==1]
# playTwice = [ e for e in wantedEncounters if gameCntr[e] ==2]

# t_cc = { t : [ c for c in confTeams.keys() if t in confTeams[c]] for t in teams }
# print (t_cc)

# interconferencegames = { (c1,c2) : 0 for c1 in confTeams.keys() for c2 in confTeams.keys() }

# for c in confTeams.keys():
#     print (confTeams[c])

# for (tn1, tn2) in playTwice:
#     print (teamByShort[tn1] , teamByShort[tn2])
#     t1 = getTeamIdByName[teamByShort[tn1]]
#     t2 = getTeamIdByName[teamByShort[tn2]]
#     for c1 in t_cc[t1]:
#         for c2 in t_cc[t2]:
#             interconferencegames[(c1,c2)]+=2


# for (c1,c2) in interconferencegames.keys():
#     print (confName[c1] , " - ",  confName[c2], " : ", interconferencegames[(c1,c2)])

#     # getTeamIdByName
# # print (playOnce)
# # print (playTwice)


# for t in teams: 
#     for c in clusters:
#         # tripToClusterSaving[(t,c)]= cluster_distances[c,c] -2*distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c])
#         print (cluster_distances[c,c], "-2*",distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c]) , cluster_distances[c,c] -2*distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c]) )
#         print ("  " , tripToClusterSaving[(t,c)]  , tripToClusterSaving[t,c] )

# for t in teams: 
#     for c in clusters:
#         print (getTeamById[t], " to ", c, " : " , cluster_distances[c,c] , "-2* " ,distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c]) ,  cluster_distances[c,c] -2.0*distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c]), cluster_distances[c,c] -2*distanceInKmByGPS(t_lon[t],t_lat[t], c_lon[c], c_lat[c]))
#         for t2 in cluster_teams[c]:
#             print ("--",getTeamById[t2])    
#         print ("---> " ,tripToClusterSaving[(t,c)])



# print (games)
# print (attractivity)
# for (t1,t2) in games:
#     print (t1,t2)
#     print (attractivity[t1,t2] )
gameAttractivity = { (t1,t2) : attractivity[t1,t2] for (t1,t2) in games if t1<t2 }

# print (gameAttractivity)


sorted_gameAttractivity = sorted(gameAttractivity.items(), key=operator.itemgetter(1))
# print ("ee " , sorted_gameAttractivity , " " , len (sorted_gameAttractivity))

nGames= len(games)

# print (range(int(0.8*0.5*nGames), int(0.5*nGames)) )

# for i in range(int(0.8*0.5*nGames), int(0.5*nGames)):
#     print ( i, i in sorted_gameAttractivity.keys()) 
# print (nGames , len(sorted_gameAttractivity))

# print (range(int(0.6*0.5*nGames), int(0.5*nGames)))

# print (len(sorted_gameAttractivity) , int(0.5*nGames), range(int(0.8*0.5*nGames), min( len(sorted_gameAttractivity) , int(0.5*nGames)) ))
# print (len(sorted_gameAttractivity) , int(0.5*nGames), range(int(0.6*0.5*nGames), min( len(sorted_gameAttractivity) , int(0.5*nGames))))
topGames = [ sorted_gameAttractivity[i] for i in range(int(0.8*0.5*nGames), min( len(sorted_gameAttractivity) , int(0.5*nGames)) ) ]
goodGames = [ sorted_gameAttractivity[i] for i in range(int(0.6*0.5*nGames), min( len(sorted_gameAttractivity) , int(0.5*nGames))) ]

broadcastingwishes = BroadcastingWish.objects.filter(scenario=s2)

# nGames


# print (hawishes)
# print (objectiveFunctionWeights)
# print ("\n\n",roundObjects)
# for d in roundObjects:
    # print (d)

# print (len(teams))
# for d in rounds:
    # print (d)

# print (neighborPattern)

# x={}
# # #create a binary variable to state that a table setting is used
# for t1 in teams:
#     for t2 in teams:
#         for d in rounds:
#             x[t1,t2,d] = pulp.LpVariable('x_'+t1+'_'+t2+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger)

# homePat=         {(t1,d)    : pulp.LpVariable('homePat_'+t1+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in teams for d in rounds}

# prioVal ={'A': 25 , 'B': 5 , 'C': 1, 'Hard' : 1000}

# t_conference = {t : 0 for t in teams }
# for c in Conference.objects.filter(scenario=s2,regional=False).order_by('name'):        
    # print ("A" , c)
    # cteams = c.teams.filter(active=True)
    # for t in cteams:
        # print ("group for ", t)
        # if t_conference[t.id]!=0:
            # print (getTeamById[t.id] , " in several groups")
        # if t_conference[t.id]==0 or len(cteams)< len(t_conference[t.id].teams.filter(active=True)):
            # t_conference[t.id]=c
            # print  (" is " , c )
# for t in set([t for t in teams if t_conference[t]==0 ]):
    # print (" no group " ,  getTeamById[ t])
# return ''


nonBlocked = { (t,r) : len(getBasicDays[r]) for r in basicRounds for t in teams}
travelDays = { (t,r) : len(getBasicDays[r]) for r in basicRounds for t in teams}
hideDays = { (t,r) : len(getBasicDays[r]) for r in basicRounds for t in teams}
nonBlockedRounds = { (t,r) : len(getDays[r]) for r in rounds for t in teams}
travelRounds = { (t,r) : len(getDays[r]) for r in rounds for t in teams}
hideRounds = { (t,r) : len(getDays[r]) for r in rounds for t in teams}

for bl in blockings:
    bl_val =1.0 if bl['time']=="----" else 0.5
    # if  bl['time']!="----":
    # print (bl, bl_val , getDayById[bl['day_id']] ,getDayById[bl['day_id']]['round'] ,getDayById[bl['day_id']]['round'] !=0 )
    if getDayById[bl['day_id']]['round'] !=0:
        if bl['type'] in ["Home","Hide","Game"]:
            nonBlocked[( bl['team_id'], getBasicRound[getDayById[bl['day_id']]['round']])]-=bl_val
            nonBlockedRounds[( bl['team_id'], getDayById[bl['day_id']]['round'])]-=bl_val
            # print ('FOUND HOME BLOCKING ', bl)
        if bl['type'] in ["Away","Hide","Game"]:
            travelDays[( bl['team_id'], getBasicRound[getDayById[bl['day_id']]['round']])]-=bl_val
            travelRounds[( bl['team_id'], getDayById[bl['day_id']]['round'])]-=bl_val
            # print ('FOUND AWAY BLOCKING ', bl)
        if bl['type'] in ["Hide","Game"]:
            hideDays[( bl['team_id'], getBasicRound[getDayById[bl['day_id']]['round']])]-=bl_val
            hideRounds[( bl['team_id'], getDayById[bl['day_id']]['round'])]-=bl_val
            # print ('FOUND AWAY BLOCKING ', bl)

noPlayRounds = { t:  [ r for r in rounds if nonBlockedRounds[(t,r)] + travelRounds[(t,r)]==0 ] for t in teams }
noHomeRounds = { t:  [ r for r in rounds if nonBlockedRounds[(t,r)] ==0 ] for t in teams }
# print("nonBlockedRounds" ,nonBlockedRounds)
# print("noHomeRounds" ,noHomeRounds)
# print("noPlayRounds" ,noPlayRounds)

playRounds = { t:  sorted([ r for r in rounds if  hideRounds[(t,r)]>0 ]) for t in teams }


# scale blocking of basic round to [0,1]
for t in teams: 
    for r in basicRounds:
        if len(getBasicDays[r])>0:
            nonBlocked[(t,r)]/=len(getBasicDays[r])
            travelDays[(t,r)]/=len(getBasicDays[r])
            if getTeamById[t]=="AX Armani Exchange Milan":
                print (r , getRealRounds[r] , nonBlocked[(t,r)] , nonBlocked[(t,r)] )

for t in teams:
    if mathModelName=="UEFA NL" and noPlayRounds[t] in [ [3,4] ]:
        t_usePhases[t]= False
        print ("No need for phases  " , getTeamById[t])
        for t2 in opponents[t]:
            t_usePhases[t2]= False
            print (" -- also no need for phases  " , getTeamById[t2])
    if getTeamById[t]=="AX Armani Exchange Milan":
        t_usePhases[t]= False
        print ("setting t_usePhases of ", getTeamById[t],t_usePhases[t] )

if "noPhaseForTeams" in special_wishes_active and sw_text["noPhaseForTeams"].strip()!="":
    noPhaseTeams = [st.strip() for st in sw_text["noPhaseForTeams"].split(",")]
    for t in teams:
        if getTeamById[t] in noPhaseTeams:
            t_usePhases[t]= False

runHeuristicModelFirst=False

if runMode=='New' and optSteps[0][0]=='HEURISTIC' and not thisSeason.groupBased and len(fixedGames)+len(fixedGames2)==0 :
    runHeuristicModelFirst=True

chosenGames = [ ]

useFullModel1= False

usePatterns= not mathModelName in ["NHL", "LNR"]
usePatterns= not mathModelName in ["NHL"]


balanceBreaks =  mathModelName=="LNR" 
haSymmetric = not mathModelName in ["NHL" , "LNR"]
haSymmetric = not mathModelName in ["NHL", "Ligue 1", "Costa Rica Premier League"]
haSymmetric = not mathModelName in ["NHL"]
# haSymmetric = not mathModelName in ["NHL" , "LNR"]
if thisSeason.symmetry:
    haSymmetric=True

use2BreakPatterns = False

# if thisSeason.initBreaks>=2 and objectivePrio != 'Trips' :
if thisSeason.initBreaks>=2  :
    use2BreakPatterns = True
# use2BreakPatterns = False

# if objectivePrio == 'Trips' and not regionalPatternUse:
#     use2BreakPatterns = False



# basicRounds= range(1,40) 
# half_symmetry_offset = 1 if mathModelName in [ "TOP 14"] else 0
half_symmetry_offset = 0 if thisSeason.symmetry or use2BreakPatterns or not thisSeason.startWithBreakAllowed or not thisSeason.endWithBreakAllowed  else 1

# if mathModelName in [ "Ligue 1"]:
#     half_symmetry_offset = 4 

# print (half_symmetry_offset ,  thisSeason.symmetry ,  use2BreakPatterns)


prev_mirror_round= { r :  0 if r<=nRounds1 else r-nRounds1+half_symmetry_offset for r in basicRounds }


# for r in basicRounds:
#     print (r, " --> " , prev_mirror_round[r] )
# print ("")


for r in basicRounds:
    if r>nRounds1 and int((r-1)/nRounds1) == int((prev_mirror_round[r]-1)/nRounds1):
        # prev_mirror_round[r]-=nRounds1
        prev_mirror_round[r] = int((r-1)/nRounds1-1)*nRounds1 +half_symmetry_offset+1-prev_mirror_round[r]%nRounds1

if mathModelName in [ "LNR"] and False:
    prev_mirror_round[14]=4 
    prev_mirror_round[15]=3 
    prev_mirror_round[16]=2 
    prev_mirror_round[17]=1 
    prev_mirror_round[18]=13 
    prev_mirror_round[19]=12 
    prev_mirror_round[20]=11 
    prev_mirror_round[21]=10 

    prev_mirror_round[22]=9 
    prev_mirror_round[23]=8 
    prev_mirror_round[24]=7 
    prev_mirror_round[25]=6 
    prev_mirror_round[26]=5 


# for r in basicRounds:
#     print (r, " --> " , prev_mirror_round[r] )


getPhaseOfBasicRound={ br : getPhaseOfRound[getRealRounds[br][0]] for br in basicRounds if len(getRealRounds[br])>0 }
for br in basicRounds:
    if br not in getPhaseOfBasicRound.keys():
        getPhaseOfBasicRound[br]= getPhaseOfBasicRound[br-1]

getBasicRoundsOfPhase={ ph : [ br for br in basicRounds if getPhaseOfBasicRound[br]==ph ] for ph in phases }

# print (getPhaseOfBasicRound)
# print (getBasicRoundsOfPhase)


if use2BreakPatterns or nTeams >200 or not usePatterns or thisSeason.minRoundsBetweenGameOfSameTeams>0 :
    useFullModel1=True
useFullModel1=True  


preplan_phases = phases
preplan_phases= [0]
if not haSymmetric:
    preplan_phases = phases

fixedGamesRounds=[]

starweight={t : 0.0 for t in teams}
for t1 in teams :
    for t2 in teams :
        starweight[t1]+=distance[getTeamById[t1],getTeamById[t2]]

# if thisSeason.minBreaks  or len(fixedGames)==0:

available_days={ (t,d) : min(1,getDayMaxGames[d]) for t in teams for d in days }

for bl in blockings:
    if bl['type'] in ["Home","Hide","Game"] and bl['time']=='----' and bl['tag_id'] == None :
        available_days[ bl['team_id'],bl['day_id']] =0

t_blocked_at={ (t,r) : sum([available_days[t,d] for d in getDays[r]])==0 for t in teams for r in rounds}

if runHeuristicModelFirst:

    debug= True
    debug= False
    comptime = 500
    gap = 0.05
    if debug:
        comptime = 30
        gap = 0.5

    possGames = optimize_model1(comptime,gap)
    print (possGames)
    print (len(possGames))
    chosenGames, unChosenGames = optimize_model4(possGames)

    print (len(chosenGames) , " chosen games" , chosenGames ) 
    print (len(unChosenGames) ,  "unchosen games : ", unChosenGames)  

    # exit(0)
    # print (len(chosenGames))

    fineDistributionModel4 = False
    fineDistributionModel4 = nBasicTeams<nTeams and thisSeason.useFeatureOpponentMatrix and mathModelName=="NBA"

    if fineDistributionModel4:            
        fixedGamesRounds= optimize_model4_fine(chosenGames)


    # print (r,  ' ' , parse(getNiceDay[earliestDay[r]]),  ' ',parse(getNiceDay[latestDay[r]]))



# print ('\n')
# for p in phases:
#     for  d in getDaysOfPhase[p] :
#         print (p,d, getRoundDaysByDay[d])

# return ''

# thisCountry =""
# for t in realteams:
#     thisCountry=t_country[t]  
# #     print (getTeamById[t], t_country[t] , t_conference[t])
# # print (thisCountry)
# print ("bt",len(bad_travels))

# if thisCountry=="United States":

#     print (thisCountry)
#     return ""



# for d in displayGroups.keys():
#     print (d, displayGroups[d])
# return ''

finalRoundDays=getRoundDaysByRound[nRounds].copy()
if mathModelName=="Champions Hockey League" and True:
    finalRoundDays+=getRoundDaysByRound[nRounds-1]


# print (finalRoundDays)
# return ''
# lastRoundSync = models.BooleanField(default=False, verbose_name="Synchronize games of last round")

model2 = pulp.LpProblem(f"{PULP_FOLDER}/League_Scheduling_Model_--_Schedule_Games_"+str(thisScenario.id), pulp.LpMinimize)

def makeIntVar(v):
    if type(v) != int :
        v.cat=pulp.LpInteger
        # print ("int var ", v)

def setStart(v,vl):
    if type(v) != int :
        vl=int(vl)
        v.setInitialValue(vl)
        # v.start = vl

def setLB(v,vl):
    if type(v) != int :
        vl=float(vl)
        v.lowBound = vl
        # print ("set lb ", v , " = ", vl)


def setUB(v,vl):
    if type(v) != int :
        vl=float(vl)
        v.upBound = vl
        # print ("set ub ", v , " = ", vl)

def getVal(v):
    if type(v) == int :
        return v
    else: 
        return v.value()

nextDay = { d : -1 for d in days+higherLeagueDayIds  }
nextnextDay = { d : -1 for d in days+higherLeagueDayIds  }
previousDay = { d : -1 for d in days+higherLeagueDayIds}

# cntr=0
lastDay=parse("01.01.1990")
lastlastDay=parse("01.01.1990")
for thisDay in sorted(getDayByDateTime.keys()):
    if thisDay-lastDay==datetime.timedelta(days=1):
        # cntr+=1
        d1 = getDayByDateTime[lastDay]
        d2 = getDayByDateTime[thisDay]
        nextDay[d1]=d2
        previousDay[d2]=d1
        # print ("next day of " ,  getNiceDay[d1] , ' ' , getNiceDay[d2])
    for dd2 in [lastDay,lastlastDay]:
        if thisDay-dd2==datetime.timedelta(days=2):
            nextnextDay[getDayByDateTime[dd2]]=getDayByDateTime[thisDay]
    lastlastDay=lastDay
    lastDay=thisDay

# print (cntr)
# cntr=0
# for d in days+higherLeagueDayIds :
#     for d2 in days+higherLeagueDayIds:
#         if  getDateTimeDay[d2]-getDateTimeDay[d]==datetime.timedelta(days=1):
#             cntr+=1
#             nextDay[d]=d2
#             previousDay[d2]=d
#             print ("next day of " ,  getNiceDay[d] , ' ' , getNiceDay[d2])
# print (cntr)


cntr= 0
cntr2= 0

# print ("games",games)
# print (roundDays)

seedTV = []
dontPlay = []
dontPlayGames = []

for bl in blockings:
    if bl['type'] in ["Hide","Game"]:
        dontPlay += [(bl['team_id'],bl['day_id']) ]

dontPlay += [(t,d)  for d in days for t in teams  if getDayMaxGames[d]==0 ] 

# for t1 in teams: 
#     for d in days:
#         if blocked_arena[(t1,d, "----" )] :
#             dontPlayGames += [(t1,t2,d) for t2 in teams]


# print()
# print(len(dontPlayGames) , " ", len (days)*len(teams)*(len(teams)-1))


if mathModelName=="NBA":
    for t1 in teams: 
        for d in days:
            if blocked_arena[(t1,d, "----" )] :
                dontPlayGames += [(t1,t2,d) for t2 in teams]
    # print (len(dontPlayGames), "BLOKING " )

    for enc in encwishes:
        # print ("ENC " ,enc , enc['reason'][:11],enc['reason'][:11]== 'TV Network:')    
        if enc['reason'][:11]== 'TV Network:':                
            print ("ENC " ,  encGames[enc['id']] ,encDays[enc['id']] )
            seedTV += [ (t1,t2,d,enc['reason'][12:]) for (t1,t2) in encGames[enc['id']] for d in encDays[enc['id']]]
        if enc['maxGames']== 0 and not enc['time'] in [getIdByTime["Early"], getIdByTime["Late"]]:
            dontPlayGames += [ (t1,t2,d) for (t1,t2) in encGames[enc['id']] for d in encDays[enc['id']]]

    #         print (len(dontPlayGames),encGames[enc['id']] , encDays[enc['id']] , enc['reason'] )
    

    usingRDs={t: [] for t in teams}
    for (t1,t2,d,channel) in  seedTV:
        # print (t1,t2,d , gameCntr[(t1,t2)], gameCntr[(t1,t2)]==1)
        usingRDs[t1]+=getRoundDaysByDay[d]
        usingRDs[t2]+=getRoundDaysByDay[d]
        for d2 in [ previousDay[d], nextDay[d]]:
            if channel=="ABC" and d2!=-1:
                dontPlay+=[(t1,d2), (t2,d2)]

    TVteams = [t for t in teams if len (usingRDs[t])>=10 ]

#     for t in teams:          
#         print (t, getTeamById[t], [ r for (r,d) in usingRDs[t]], t_conference[t])    

#     print (TVteams)
# print ("CHECKPOINT ", 5)

# print (seedTV)
# print (dontPlay)

x= {(t1,t2,rd) : 0 for t1 in teams for t2 in teams for rd in roundDays}
for (t1,t2) in games:
    for rd in roundDays:
        x[(t1,t2,rd)]=1

for (t1,t2,rd) in x.keys():
    if blocked_arena[(t1,rd[1],"----")] and runMode=='Improve' and not thisSeason.allowBlockingViosInImprove:
        # cntr +=1
        # print ("FORBIDDING")
        
        x[(t1,t2,rd)]=0

for (t1,t2,d,channel) in seedTV:
    if gameCntr[(t1,t2)]==1:
        for (r,d2) in roundDays:
            if d != d2 :
                # cntr +=1
                x[(t1,t2,(r,d2))]=0

    for t3 in teams:                
        if not t3 in [t1,t2]:
            for rd in getRoundDaysByDay[d]:
                x[(t1,t3,rd)]=0
                x[(t2,t3,rd)]=0
                x[(t3,t1,rd)]=0
                x[(t3,t2,rd)]=0
                # cntr +=4

for (t,d) in dontPlay:
    for t3 in teams:
        if not t3 in [t1,t2]:
            for rd in getRoundDaysByDay[d]:
                x[(t,t3,rd)]=0
                x[(t3,t,rd)]=0

for (t1,t2,d) in dontPlayGames:
    for rd in getRoundDaysByDay[d]:
        x[(t1,t2,rd)]=0

attendance = { (t1,t2,d) : 0 for (t1,t2) in games for d in days }
if thisSeason.useFeaturePrediction:
    # learner = AttendanceLearner(thisSeason.id)
    # attendance = learner.predict_games(attendance.keys())
    oldestTrainingGame= parse("2015-01-01")
    oldestTrainingGame=oldestTrainingGame.date()
    games_train = Game.objects.filter(season=thisSeason).exclude(historic_season=None)
    print ( " all games",len(games_train), )
    games_train = [g for g in games_train if g.date>oldestTrainingGame ]
    print ( " important games",len(games_train), )

    games_predict = attendance.keys()

    X= []
    y =[]
    homeAttendances = {t: [] for t in teams+inactive_teams}
    for game in games_train:
        if game.attendance>0:
            homeAttendances[game.homeTeam.id].append(game.attendance)
    for t in teams+inactive_teams:
        homeAttendances[t]=sorted(homeAttendances[t])
        # print (getTeamById[t], homeAttendances[t])
        if len(homeAttendances[t])==0:
            homeAttendances[t]=[7500]
    maxAttendance = {t: homeAttendances[t][-1] for t in teams+inactive_teams }
    # maxAttendance = {t: homeAttendances[t][int(0.9*(len(homeAttendances[t])))] for t in teams+inactive_teams }
    medianAttendance = {t: homeAttendances[t][int(0.5*(len(homeAttendances[t])))] for t in teams+inactive_teams }
    loyalty = {t: medianAttendance[t]/maxAttendance[t] for t in teams+inactive_teams }

    for t in teams+inactive_teams: 
        print (getTeamById[t], loyalty[t] , medianAttendance[t] , maxAttendance[t] , )

    def getFeatureVector(t1,t2,d):
        ds = distanceInKmByGPS(t_lon[t1],t_lat[t1], t_lon[t2], t_lat[t2])
        # print ( d.day ,  d.month ,  d.year , " -> " , (d.month+5)%12 , " -> " , int((d.month+4)%12/2) , d.month==12 and d.day >15 , d.weekday() , d.weekday() in [4,5,6])
        # print ( d.year," -> " , d.year-2015  )
        gm={
            # 'homeTeam_id': t1, 'awayTeam_id': t2, 
            # 'month':  d.month,
            'year':  d.year-2015 , 
            'month':  int((d.month+4)%12/2) , 
            'weekday': d.weekday() ,                
            'weekend': d.weekday() in [4,5,6],                
            'holiday':   d.month==12 and d.day >15 ,
            'summer':   d.month in [6,7,8,9],
            'winter':   d.month in [12,1,2],
            'home_attractivity': t_attractivity[t1],  'away_attractivity': t_attractivity[t2], 
            'attractivity_ratio': t_attractivity[t2]/max(1,t_attractivity[t1]), 
            'home_lat': t_lat[t1] , 'home_lon': t_lon[t1] , 
            'away_lat': t_lat[t2], 'away_lon': t_lon[t2], 
            'distance' : ds ,  
            'distance_frac' : ds/medianAttendance[t2] , 
            'loyalty_home' : loyalty[t1] ,
            'medianAttendance_home' : 0.001*medianAttendance[t1] ,
            'maxAttendance_home' :   0.001*maxAttendance[t1] , 
            # 'medianAttendance_away' : 0.001*medianAttendance[t2] , 
            # 'maxAttendance_away' :    0.001*maxAttendance[t2] , 
            }             
        for t in teams+inactive_teams:
            if t1 == t:
                gm["home_"+str(t1)]=True
            if t2 == t:
                gm["away_"+str(t2)]=False
        for c in countries:
            if t_country[t1] == c:
                gm["home_country_"+str(t1)]=True
            if t_country[t2] == c:
                gm["away_country_"+str(t2)]=False
        return list(gm.values()) 

    for game in games_train:
        X.append(getFeatureVector(game.homeTeam.id, game.awayTeam.id,game.date) )
        y.append(game.attendance)

    X_train, X_test, y_train, y_test = train_test_split(
        X, y, test_size=0.2, random_state=1)  

    rf_regressor = RandomForestRegressor(n_estimators = 200 ,  random_state = 42)
    # score on training  0.959517674767985
    # score on test  0.8494965525219991
    # rf_regressor = GradientBoostingRegressor(n_estimators = 200 ,  random_state = 42)
    # score on training  0.9022637786547619
    # score on test  0.8047414718789097
    rf_regressor.fit(X_train,y_train)
    score = rf_regressor.score(X_train,y_train)
    print ("score on training " , score)
    score = rf_regressor.score(X_test,y_test)
    print ("score on test " , score)

    X= []
    y =[]
    for (t1,t2,d) in attendance.keys():
        X.append(getFeatureVector(t1,t2,getDateTimeDay[d]) )

    attendance = dict(zip(games_predict,rf_regressor.predict(X)))

    for g in games_predict: 
        # print (g,  int (attendance[g]) , maxAttendance[g[0]],  int (attendance[g]) < maxAttendance[g[0]], min ( int (attendance[g]) , maxAttendance[g[0]]))
        attendance[g] = min ( int (attendance[g]) , maxAttendance[g[0]])

# print ( sum (x[ttrd] for ttrd in x.keys()) , len(games)*len(roundDays))

# x= {(t1,t2,rd) : 0 for t1 in teams for t2 in teams for rd in roundDays}
x_round= {(t1,t2,r) : 0 for t1 in teams for t2 in teams for r in rounds}
x_time= {(t1,t2,rd,tm) : 0 for t1 in teams for t2 in teams for rd in roundDays for tm in times}
if evalRun:
    x= {(t1,t2,rd) : 0 for t1 in teams for t2 in teams for rd in roundDays}
    for (t1,t2,r,d) in currentSolution:
        x[(t1,t2,(r,d))]=1
        if currentKickoffTimes[(t1,t2,d)] in times:
            x_time[(t1, t2, (r, d), currentKickoffTimes[(t1,t2,d)])]=1
        else:
            for tm in times:
                x_time[(t1,t2,(r,d),tm)] = pulp.LpVariable('x_'+str(t1)+'_'+str(t2)+'_'+str(r)+'_'+str(d)+'_'+tm , lowBound = 0, upBound = 1, cat = pulp.LpContinuous) 
            # print ("setting " , t1,t2,r,d,currentKickoffTimes[(t1,t2,d)])

for (t1,t2) in games:
    for rd in roundDays:
        # print ("make var " ,t1,t2,rd)
        if x[(t1,t2,rd)]==1 :
        # if not blocked_arena[(t1,rd[1],"----")] or runMode=='New':
            if not evalRun:
                x[(t1,t2,rd)] =  pulp.LpVariable('x_'+str(t1)+'_'+str(t2)+'_'+str(rd[0])+'_'+str(rd[1]), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) 
                cntr +=1
                if thisSeason.useFeatureKickOffTime:
                    for tm in times:
                        x_time[(t1,t2,rd,tm)] = pulp.LpVariable('x_'+str(t1)+'_'+str(t2)+'_'+str(rd[0])+'_'+str(rd[1])+'_'+tm , lowBound = 0, upBound = 1, cat = pulp.LpContinuous) 
            else: 
                cntr+=len(roundDays)

    for r in rounds:
        x_round[(t1,t2,r)]= pulp.LpVariable('x_round_'+str(t1)+'_'+str(t2)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpContinuous)
        model2+= x_round[(t1,t2,r)] == lpSum([x[(t1,t2,rd)] for rd in getRoundDaysByRound[r]])


t_prev_mirror_round ={(t,r) : 0 for t in teams for r in rounds}

for t1 in teams: 
    phaseLength= int(len(playRounds[t1])/nPhases+0.5)
    # print ("phaseLength", phaseLength)
    for i in range(len(playRounds[t1])):
        # print (i, phaseLength)
        if i >=phaseLength:
            # print ("setting " , playRounds[t1], playRounds[t1][i-phaseLength])
            # print ("setting " , playRounds[t1][i], "->",playRounds[t1][i-phaseLength])
            t_prev_mirror_round[(t1,playRounds[t1][i])]=playRounds[t1][i-phaseLength]
            # t_prev_mirror_round[(t,playRounds[t1][i])]=5


# for tr in t_prev_mirror_round.keys():
#     print(  "t_prev_mirror_round "  ,tr ,  t_prev_mirror_round[tr])

# print (prev_mirror_round)


if not evalRun:
    for (t1,t2) in games:
        for r in rounds:
            if r > nRounds1 and thisSeason.symmetry : 
                prev_round =prev_mirror_round[r]       
                if thisSeason.groupBased and len(noPlayRounds[t1])>0 and noPlayRounds[t1]==noPlayRounds[t2]:
                    prev_round=t_prev_mirror_round[t1,r]

                if prev_round>0:
                    model2+= x_round[(t1,t2,r)] == x_round[(t2,t1,prev_round)]
                # print ("x_round[(",t1,",",t2,",",r,")] == x_round[(",t2,t1,prev_mirror_round[r],")]")
                # print ( t1,t2,r , " -> ",prev_mirror_round[r])


# for (t1,t2) in games:
#     # every pair plays each other in each phase once
#     for p in phases:
#         if p<len(phases)-1 or True: # phase violation in last phase possible if it contained more rounds than necessary
#             if t_usePhases[t1] or t_usePhases[t2]:
#                 if thisSeason.groupBased and len(noPlayRounds[t1])>0 and noPlayRounds[t1]==noPlayRounds[t2]:
#                     relDays = []
#                     phaseLength= int(len(playRounds[t1])/nPhases+0.5)
#                     for rr in playRounds[t1][p*phaseLength:(p+1)*phaseLength]:
#                         relDays+=getDays[rr]
#                         print ("adding days of round ", rr , " to phase ", p)
#                     print ("reldays", relDays)                        
#                 else:
#                     relDays = getDaysOfPhase[p]
#                 model2 += lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)]  for d in relDays for rd in getRoundDaysByDay[d] ] ) <= 1


        
# for r in rounds:
    # if r > nRounds1 and  (thisSeason.symmetry or haSymmetric):                
        # print ( r , " -> ",prev_mirror_round[r])
# print (len(games)) 


    

for (t1,t2,(r,d)) in x.keys():
    if thisSeason.useFeatureKickOffTime:
        for tm in times :
            if blocked_arena[(t1,d,tm)] and runMode=='Improve':
                x_time[(t1,t2,(r,d), tm)]=0
                # print ("forbidding tm ", t1,t2,r,d, tm)
                cntr2+=1
                # print ("FORBIDDING")
                

print ("  .... got rid of " , len(x.keys())-cntr, " + " ,cntr2, "  vars") 




for (t1,t2,d,channel) in  seedTV:
    print (t1,t2,d , gameCntr[(t1,t2)], gameCntr[(t1,t2)]==1)
    model2+= lpSum([x[(t1,t2,rd)]  for rd in getRoundDaysByDay[d] ])==1

#    model2+= lpSum( x[rr] for rr in x.keys() )
#    model2.solve(XPRESS(msg=1,maxSeconds = 25, keepFiles=True))
#    return ""

if thisSeason.lastRoundSync:
    if thisSeason.useFeatureKickOffTime:
        lastRoundPlayed= {(g,rd,tm1) : pulp.LpVariable('x_'+str(g)+'_'+str(rd[1])+'_'+tm1 , lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for g in displayGroups.keys() for rd in finalRoundDays for tm1 in times}
    else:
        lastRoundPlayed= {(g,rd) : pulp.LpVariable('x_'+str(g)+'_'+str(rd[1]) , lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for g in displayGroups.keys() for rd in finalRoundDays }
homeInRound= {(t1,r) : pulp.LpVariable('homeInRound_'+str(t1)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in teams for r in rounds}
awayInRound= {(t1,r) : pulp.LpVariable('awayInRound_'+str(t1)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in teams for r in rounds}
gameInBasicRound= {(t1,t2,r) : pulp.LpVariable('gameInBasicRound_'+str(t1)+'_'+str(t2)+'_'+str(r), lowBound = 0, upBound = defaultGameRepetions, cat = pulp.LpContinuous) for (t1,t2) in games for r in basicRounds}
homeInBasicRound= {(t1,r) : pulp.LpVariable('homeInBasicRound_'+str(t1)+'_'+str(r), lowBound = 0,  cat = pulp.LpContinuous) for t1 in teams for r in basicRounds}
awayInBasicRound= {(t1,r) : pulp.LpVariable('awayInBasicRound_'+str(t1)+'_'+str(r), lowBound = 0,  cat = pulp.LpContinuous) for t1 in teams for r in basicRounds}
break3InRound= {(t1,r) : pulp.LpVariable('break3InRound_'+str(t1)+'_'+str(r), lowBound = 0, cat = pulp.LpContinuous) for t1 in teams for r in rounds}
# breakInRound= {(t1,r) : pulp.LpVariable('breakInRound_'+str(t1)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in teams for r in rounds}
# breaksTotal =  pulp.LpVariable('breaksTotal', lowBound = 0, cat = pulp.LpContinuous)

tripToSingleTripElement = {(t1,d,c) : pulp.LpVariable('tripToSingleTripElement_'+str(t1)+'_'+str(d)+'_'+str(c), lowBound = 0, upBound = 0, cat = pulp.LpContinuous) for t1 in teams for d in days for (c,v1,v2,v3,v4) in tripElements[t1] if getWeekDay[d] in trip_weekdays[c]}
tripToCluster = {(t1,r,c) : pulp.LpVariable('tripToCluster_'+str(t1)+'_'+str(r)+'_'+str(c), lowBound = 0, upBound = 0, cat = pulp.LpContinuous) for t1 in teams for r in rounds for c in clusters  if not c in t_clusters[t1] and r<nRounds}
tripToClusterDaily = {(t1,d,c) : pulp.LpVariable('tripToClusterDaily_'+str(t1)+'_'+str(d)+'_'+str(c), lowBound = 0, upBound = 0, cat = pulp.LpContinuous) for t1 in realteams for d in days for c in clusters if not c in t_clusters[t1]}
tooManyTop4InRow= {(t1,r) : pulp.LpVariable('tooManyTop4InRow_'+str(t1)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in teams for r in rounds}

tooManyHomesInStadium= {(stadium.id,d) : pulp.LpVariable('tooManyHomesInStadium_'+str(stadium.id)+'_'+str(d), lowBound = 0, cat = pulp.LpContinuous) for stadium in stadiums for d in days+higherLeagueDayIds}
pairingVio= {(pair['id'],d) : pulp.LpVariable('pairingVio_'+str(pair['id'])+'_'+str(d), lowBound = 0, cat = pulp.LpContinuous) for pair in pairings for d in days+higherLeagueDayIds}
derbyMissing= {d : pulp.LpVariable('derbyMissing_'+str(d), lowBound = 0, cat = pulp.LpContinuous) for d in days}

breakVio =  { (br['id'],t) : pulp.LpVariable('breakVio_'+ str(br['id'])+'_'+str(t) , lowBound = 0, cat = pulp.LpContinuous) for br in breaks for t in teams}
blockingVio =  { bl['id'] : pulp.LpVariable('blockingVio_'+ str(bl['id']) , lowBound = 0, cat = pulp.LpContinuous) for bl in blockings}
# blockingVioTotal =  pulp.LpVariable('blockingVioTotal', lowBound = 0, cat = pulp.LpContinuous)

hawVio =  { haw['id'] : pulp.LpVariable('hawVio'+ str(haw['id']) , lowBound = 0, cat = pulp.LpContinuous) for haw in hawishes}
HawVioTooLess =  { el : pulp.LpVariable('havviotooless_'+ str(el) , lowBound = 0, cat = pulp.LpContinuous) for haw in hawishes for el in elemHaWishes[haw['id']] }
HawVioTooMuch =  { el : pulp.LpVariable('havviotoomuch_'+ str(el) , lowBound = 0, cat = pulp.LpContinuous) for haw in hawishes for el in elemHaWishes[haw['id']] }
# HawVioTotal =  pulp.LpVariable('HawVioTotal', lowBound = 0, cat = pulp.LpContinuous)
encVio =  { enc['id'] : pulp.LpVariable('encVio'+ str(enc['id']) , lowBound = 0, cat = pulp.LpContinuous) for enc in encwishes}
encVioTooLess =  { el : pulp.LpVariable('encViotooless'+ str(enc['id'])+"_"+str(el) , lowBound = 0, cat = pulp.LpContinuous) for enc in encwishes for el in elemEncWishes[enc['id']]}
encVioTooMuch =  { el : pulp.LpVariable('encViotoomuch'+ str(enc['id'])+"_"+str(el) , lowBound = 0, cat = pulp.LpContinuous) for enc in encwishes for el in elemEncWishes[enc['id']]}
# encVioTotal =  pulp.LpVariable('encVioTotal', lowBound = 0, cat = pulp.LpContinuous)
confVio =  { conf['id'] : pulp.LpVariable('confVio'+ str(conf['id']) , lowBound = 0, cat = pulp.LpContinuous) for conf in conferencewishes}
# broadVio =  { d : pulp.LpVariable('broadVio'+ str(d) , lowBound = 0, cat = pulp.LpContinuous) for d in days}
broadVioTm =  { (b.id, r): pulp.LpVariable('broadVioTm_'+ str(b.id) +"_"+ str(r) , lowBound = 0, cat = pulp.LpContinuous) for b in broadcastingwishes for r in rounds}
competitionVio =  { (t,d) : pulp.LpVariable('competitionVio_'+ str(t) +'_'+ str(d) , lowBound = 0, cat = pulp.LpContinuous) for (t,d) in competitions.keys()}
gamesTooClose =  { (t,d) : pulp.LpVariable('gamesTooClose_'+ str(t) +'_'+ str(d) , lowBound = 0, cat = pulp.LpContinuous) for t in teams for d in days+higherLeagueDayIds if conflictDays[(t,d)]}
gamesTooClose2 =  { (t,r) : pulp.LpVariable('gamesTooClose2_'+ str(t) +'_'+ str(r) , lowBound = 0, cat = pulp.LpContinuous) for t in teams for r in rounds }
fixedGameVio =  { (t1,t2,d)  : pulp.LpVariable('fixedGameVio_'+ str(t1) +'_'+str(t2) +'_'+ str(d) , lowBound = 0, cat = pulp.LpContinuous) for (t1,t2,d) in fixedGames}
fixedGame2Vio =  { (t1,t2,d)  : pulp.LpVariable('fixedGame2Vio_'+ str(t1) +'_'+str(t2) +'_'+ str(d) , lowBound = 0, cat = pulp.LpContinuous) for (t1,t2,d) in fixedGames2}
missingGamesVio =  { (t1,t2)  : pulp.LpVariable('missingGamesVio_'+ str(t1) +'_'+str(t2) , lowBound = 0, cat = pulp.LpContinuous) for (t1,t2) in games}

home={}
away={}
home_time={}
away_time={}
away_in_cluster={}
away_in_cluster_day={}

getRoundDaysByBasicRound={br : [rd for r in getRealRounds[br] for rd in getRoundDaysByRound[r]] for br in basicRounds}
getMaxGameOnRoundDaysByBasicRound={br : sum ( roundDaysMax[rd]+excessGames[rd]  for r in getRealRounds[br] for rd in getRoundDaysByRound[r]) for br in basicRounds}

assignPattern2={}

if mathModelName in [ "Ligue 1" , "Costa Rica Premier League", "DFB3"]:                
    numPatterns= 2*nRounds1
    patternRange=[p for p in range(1,numPatterns+1)]
    patterns={}
    for  j in range (1,int(numPatterns/2)+1):
        patterns[2*j-1,1]= 1
        patterns[2*j,1]=0
    for  j in range(1,int(numPatterns/2)+1):
        for i in range (2,int(numPatterns/2)+1):
            patterns[2*j-1,i]= 1-patterns[2*j-1,i-1]
            if i>= 1 and  i==j :
                patterns[2*j-1,i]=1-patterns[2*j-1,i]
            patterns[2*j,i]= 1-patterns[2*j-1,i]

    forbiddenPatterns=[]
    if use2BreakPatterns :
        p_cntr=numPatterns
        for b1 in rounds1:
            for b2 in rounds1:
                if b1+2<=b2 and b1>1 and b2-b1<nTeams-3:
                    print ("breaks ", b1, b2  )
                    p_cntr+=2
                    for r in rounds1:
                        np=1
                        if r>1:
                            np = 1-patterns[p_cntr-1,r-1]
                        if r in [b1,b2]:
                            np=1-np
                        patterns[p_cntr-1,r]=np
                        patterns[p_cntr,r]=1-np
                    patternRange.append(p_cntr-1)
                    patternRange.append(p_cntr)

                    for p in [p_cntr-1 ,p_cntr]:
                        p_nhome_games = sum ([patterns[p,d] for d in rounds1  ])
                        print ( " - ", 100+p , " :" ,end="") 
                        for d in rounds1:
                            print (patterns[p,d] , end="" )
                        if p_nhome_games < nTeams/2-1 or p_nhome_games > nTeams/2 :
                            print (" ** BAD ** ", end="")
                            forbiddenPatterns.append(p)
                        print (" sum : " , sum ([patterns[p,d] for d in rounds1  ]))

    for j in range(1,numPatterns+1):
        print (j , " : " ,end="")
        for i in range (2,int(numPatterns/2)+1):
            print (patterns[j,i],end="")
        print("")

    forbiddenStarterPatterns = [ p for p in patternRange if not thisSeason.startWithBreakAllowed and patterns[p,1]==patterns[p,2]]
    forbiddenEndPatterns     = [ p for p in patternRange if not thisSeason.endWithBreakAllowed and patterns[p,nRounds1-1]==patterns[p,nRounds1]]
    forbiddenPatterns+=forbiddenStarterPatterns+forbiddenEndPatterns

    if mathModelName in ["DFB3"] and len(teams)>18:         
        forbiddenPatterns += [3,4,7,8,11,12,15,16,19,20,23,24,27,28]
    patternRange=[p for p in patternRange if p not in forbiddenPatterns]
    print (forbiddenPatterns)
    print (patternRange)
    print ("getPhaseOfRound",getPhaseOfRound)
    print ("getBasicRound",getBasicRound)

    assignPattern2={(p,t1,ph) : pulp.LpVariable('assignPattern2_'+str(t1)+'_'+str(p)+'_'+str(ph), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for p in patternRange for t1 in realteams for ph in phases}
    usePattern2={(p,ph) : pulp.LpVariable('usePat2_'+str(p) + '_' + str(ph), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for p in patternRange for ph in phases}
    for ph in phases:
        if runMode == 'New':
            for p in patternRange:
                model2+=  usePattern2[(p,ph)]== lpSum([ assignPattern2[p,t,ph] for t in realteams])
                if p%2==0:
                    model2+= usePattern2[(p,ph)]==usePattern2[p-1,ph]
                    # print ("complementaries " , p, p-1)
        for t in realteams:
            # every team one pattern
            model2 += lpSum( assignPattern2[(p,t,ph)] for p in patternRange)==1 , "one_pattern_for_2_%s_%s"%(t,ph)

            # for r in rounds:
            #     if r==1 or getBasicRound[r-1] != getBasicRound[r]:
            #         model2 += lpSum( homeInRound[(t,r2)]  for r2 in rounds if getBasicRound[r2]==getBasicRound[r])  == lpSum(assignPattern2[(p,t,getPhaseOfRound[r])] *  patterns[p,r-getPhaseOfRound[r]*nRounds1] for p in patternRange)

            for r in basicRounds:
                model2 += lpSum( homeInRound[(t,r2)] for r2 in getRealRounds[r])  == lpSum(assignPattern2[(p,t,getPhaseOfBasicRound[r])] *  patterns[p,r-getPhaseOfBasicRound[r]*nRounds1] for p in patternRange)

# for cs in currentSolution:
    # setLB(x[(cs[0],cs[1],(cs[2],cs[3]))],1)
# model2.solve(GUROBI(MIPGap=0.0, TimeLimit=20,msg=1))

for t in higherTeams :
    for d in days+higherLeagueDayIds:
        away[t,d] = 0
        home[t,d] = 0
        if thisSeason.useFeatureKickOffTime:
            for tm in times:
                away_time[t,d,tm] =  0 
                home_time[t,d,tm] =  0  

print ("READING UPPER GAMES", higherLeagueDayIds)

for (dy,t1,t2,rd,tm) in higherGames:
    dy2 = getDayByDateTime[getDateTimeDay[dy]]
    home[t1,dy2] = 1
    away[t2,dy2] = 1
    if  tm in getIdByTime.keys():
        home_time[t1,dy2,getIdByTime[tm]] =  1  
        away_time[t2,dy2,getIdByTime[tm]] =  1  
        
for t in realteams:
    for d in higherLeagueDayIds:
        away[t,d] = 0
        home[t,d] = 0
        if thisSeason.useFeatureKickOffTime:
            for tm in times:
                away_time[t,d,tm] =  0 
                home_time[t,d,tm] =  0 

    for d in days:
        away[t,d] = lpSum([x[(t2,t,rd)] for t2 in opponents[t] for rd in getRoundDaysByDay[d]]) or pulp.LpVariable('away'+str(t)+'_'+str(d), lowBound = 0, upBound = 0, cat = pulp.LpContinuous)
        home[t,d] = lpSum([x[(t,t2,rd)] for t2 in opponents[t] for rd in getRoundDaysByDay[d]]) or pulp.LpVariable('home'+str(t)+'_'+str(d), lowBound = 0, upBound = 0, cat = pulp.LpContinuous)
        if thisSeason.useFeatureKickOffTime:
            for t2 in opponents[t]:
                # print (t,t2,getTeamById[t], getTeamById[t2], (t,t2) in games )
                # if (t,t2) in games:
                for rd in getRoundDaysByDay[d]:
                    # TODO: HOTFIX
                    if (x[(t2,t,rd)] != 0):     
                        model2+= x[(t2,t,rd)] ==  lpSum([ x_time[(t2,t,rd,tm)] for tm in times])
            for tm in times:
                away_time[t,d,tm] = lpSum([x_time[(t2,t,rd,tm)] for t2 in opponents[t] for rd in getRoundDaysByDay[d] ])
                home_time[t,d,tm] = lpSum([x_time[(t,t2,rd,tm)] for t2 in opponents[t] for rd in getRoundDaysByDay[d] ])

        for c in clusters:
            away_in_cluster_day[t,d,c] = lpSum([x[(t2,t,rd)] for t2 in cluster_teams[c] for rd in getRoundDaysByDay[d] if t2 in opponents[t]])

for t in realteams:
    tms = [t] + higherTeamsOf[t]
    print (tms)
    for d in days+higherLeagueDayIds :
        model2 += home[(t,d)]+away[(t,d)] <= 1
        if len(higherTeamsOf[t])>0 and d in upperAndLowerLeagueIds:                
            model2 += lpSum([ home[(t1,d)]+away[(t1,d)] for t1 in tms ])  <= 1 + gamesTooClose[t,d]

        if conflictDays[(t,d)]:
            # print (t,getNiceDay[d],conflictDays[(t,d)])
            # for d2 in conflictDays[(t,d)]:
            #     if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'A','H')] ):
            #         print ("   - " ,getNiceDay[d2] ,getDateTimeDay[d2]-getDateTimeDay[d] , datetime.timedelta(days=minRest[(t,'A','A')])  ) 
            # model2 += lpSum([home[(t,d2)]+away[(t,d2)] for d2 in conflictDays[(t,d)]]) <= 1+ gamesTooClose[t,d]
            # if len(tms)>1:
            #     print (lpSum([ home[(t1,d)] for t1 in tms ]) +lpSum([ home[(t1,d2)] for d2 in conflictDays[(t,d)] for t1 in tms if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'H','H')] )] ))                
            model2 += lpSum([ home[(t1,d)] for t1 in tms ]) +lpSum([ home[(t1,d2)] for d2 in conflictDays[(t,d)] for t1 in tms if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'H','H')] )] ) <= 1+ gamesTooClose[t,d]
            model2 += lpSum([ home[(t1,d)] for t1 in tms ]) +lpSum([ away[(t1,d2)] for d2 in conflictDays[(t,d)] for t1 in tms if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'H','A')] )] ) <= 1+ gamesTooClose[t,d]
            model2 += lpSum([ away[(t1,d)] for t1 in tms ]) +lpSum([ home[(t1,d2)] for d2 in conflictDays[(t,d)] for t1 in tms if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'A','H')] )] ) <= 1+ gamesTooClose[t,d]
            model2 += lpSum([ away[(t1,d)] for t1 in tms ]) +lpSum([ away[(t1,d2)] for d2 in conflictDays[(t,d)] for t1 in tms if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'A','A')] )] ) <= 1+ gamesTooClose[t,d]
#             model2 += home[(t,d)]+lpSum([ away[(t,d2)] for d2 in conflictDays[(t,d)] if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'H','A')]) ] ) <= 1+ gamesTooClose[t,d]
#             model2 += away[(t,d)]+lpSum([ home[(t,d2)] for d2 in conflictDays[(t,d)] if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'A','H')]) ] ) <= 1+ gamesTooClose[t,d]
#             model2 += away[(t,d)]+lpSum([ away[(t,d2)] for d2 in conflictDays[(t,d)] if d2!=d and getDateTimeDay[d2]-getDateTimeDay[d] <= datetime.timedelta(days=minRest[(t,'A','A')]) ] ) <= 1+ gamesTooClose[t,d]


for t in realteams:
    for r in rounds:
        # awayInRound[t,r] = lpSum([x[(t2,t,dr)] for t2 in teams for dr in getRoundDaysByRound[r]])
        # homeInRound[t,r] = lpSum([x[(t,t2,dr)] for t2 in teams for dr in getRoundDaysByRound[r]])
        
        if thisSeason.gamesPerRound=="one day":
            # model2 += homeInRound[(t,r)]     == lpSum([home[(t,d)] for (r2,d) in getRoundDaysByRound[r]])
            model2 += homeInRound[(t,r)]     == lpSum([x[(t,t2,rd)] for t2 in opponents[t] for rd in getRoundDaysByRound[r]])
            model2 += awayInRound[(t,r)]     == lpSum([x[(t2,t,rd)] for t2 in opponents[t] for rd in getRoundDaysByRound[r]])
        else:
            model2 += homeInRound[(t,r)] == lpSum([x[(t,t2,getRoundDaysByRound[r][0])] for t2 in opponents[t] ])
            model2 += awayInRound[(t,r)] == lpSum([x[(t2,t,getRoundDaysByRound[r][0])] for t2 in opponents[t] ])

        model2 += homeInRound[(t,r)] + awayInRound[(t,r)] <= 1
        if r>=3:
            model2 += break3InRound[(t,r)] +2>= homeInRound[(t,r-2)]+homeInRound[(t,r-1)]+homeInRound[(t,r)] 
            model2 += break3InRound[(t,r)] +2>= awayInRound[(t,r-2)]+awayInRound[(t,r-1)]+awayInRound[(t,r)] 

        if r>1:
            if thisSeason.gamesPerRound=="one day":
                model2 += lpSum([x[(t,t4,d)]+x[(t4,t,d)] for t4 in top4 for d in (getRoundDaysByRound[r-1]+getRoundDaysByRound[r]) if t4 in opponents[t] ]) <= 1+tooManyTop4InRow[(t,r)]
            else:
                model2 += lpSum([x[(t,t4,d)]+x[(t4,t,d)] for t4 in top4 for d in [getRoundDaysByRound[r-1][0],getRoundDaysByRound[r][0]] if t4 in opponents[t] ]) <= 1+tooManyTop4InRow[(t,r)]

        for c in clusters:
            if thisSeason.gamesPerRound=="one day":
                away_in_cluster[t,r,c] = lpSum([x[(t2,t,rd)] for t2 in cluster_teams[c] for rd in getRoundDaysByRound[r] if t2 in opponents[t] ])
            else:
                away_in_cluster[t,r,c] = lpSum([x[(t2,t,getRoundDaysByRound[r][0])] for t2 in cluster_teams[c] if t2 in opponents[t] ])


print ("fixedGamesRounds:" ,fixedGamesRounds)
for (t1,t2,r) in fixedGamesRounds:
    model2+= lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByRound[r] ] )==1
    print ("fix ", t1,t2,r, lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByRound[r]] ))


# initTripsLate = False
initTripsLate = True
onlyFewTrips= False
cntr =0
if thisSeason.useFeatureTrips and not initTripsLate:
    if thisSeason.tripMode=="Clusters": 
        if useDailyTrips:            
            for d1 in days:
                otherTripDays = [ d2 for d2 in days if getDateTimeDay[d1]< getDateTimeDay[d2] and  getDateTimeDay[d2]<=getDateTimeDay[d1]+datetime.timedelta(days=thisSeason.maxDistanceWithinTrip+1) and (len(getRoundsByDay[d1])*len(getRoundsByDay[d2])>1 or  list(getRoundsByDay[d1])!=list(getRoundsByDay[d2]) )]

                for t in realteams:                 
                    for c in clusters:
                        if gew['Trips']>0  and not c in t_clusters[t] and len(otherTripDays)>0:
                            tripToClusterDaily[(t,d1,c)].upBound=1
        #                            tripToClusterDaily[(t,d1,c)] = pulp.LpVariable('tripToClusterDaily_'+str(t)+'_'+str(d1)+'_'+str(c), lowBound = 0, upBound = 1, cat = pulp.LpContinuous)
                            model2 +=  tripToClusterDaily[(t,d1,c)]  <= away_in_cluster_day[t,d1,c]
                            model2 +=  tripToClusterDaily[(t,d1,c)]  <= lpSum([away_in_cluster_day[t,d2,c] for d2 in otherTripDays ])
        #                            print ('considering trip of ' , getTeamById[t], ' in days ' , getNiceDay[d1] , getNiceDay[otherTripDays[0]] , otherTripDays,' to cluster ' , c , cluster_teams[c])
                            cntr +=2
        else :
            for r in rounds:
                otherTripRounds = [r2 for r2 in rounds if r2>r and getDateTimeDay[latestDay[r]]<= getDateTimeDay[earliestDay[r2]] and getDateTimeDay[earliestDay[r2]]-getDateTimeDay[latestDay[r]]<=datetime.timedelta(days=thisSeason.maxDistanceWithinTrip+1)]
                # print ("trip rounds ", r, otherTripRounds)
                for t in realteams: 
                    # forbid same opponents on successive days
                    for t2 in realteams: 
                        if t!=t2 and r>1 and forbidRepetitions:                        
                            model2 +=  lpSum([ (x[(t,t2,rd )]+x[(t2,t,rd)]) for rd in getRoundDaysByRound[r-1]+getRoundDaysByRound[r] ]) <= 1
                    
                    for c in clusters:
                        if len(otherTripRounds)>0 and gew['Trips']>0  and not c in t_clusters[t] :
                                tripToCluster[(t,r,c)].upBound=1
                                model2 +=  tripToCluster[(t,r,c)]  <= away_in_cluster[t,r,c]
                                model2 +=  tripToCluster[(t,r,c)]  <= lpSum([away_in_cluster[t,r2,c] for r2 in otherTripRounds  ])
                                # print ('considering trip of ' , getTeamById[t], ' in rounds ' , r , otherTripRounds,' to cluster ' , c )
                                cntr +=2

        #                        else :
        #                            model2 +=  tripToCluster[(t,r,c)] == 0
    else:
        tripDayPairs = {}
        for d1 in days:
            for d2 in days: 
                daysBetween = (getDateTimeDay[d2]-getDateTimeDay[d1]).days -1
                if daysBetween>=0 and getDayMaxGames[d1]>0 and getDayMaxGames[d2]>0 and daysBetween<=thisSeason.maxDistanceWithinTrip and getRoundByDay[d1]!=getRoundByDay[d2]:
                    # print (d1,d2,daysBetween, getNiceDay[d1],  getNiceDay[d2], )
                    if d1 not in tripDayPairs.keys():
                        tripDayPairs[d1]=[]
                    tripDayPairs[d1].append((d2, daysBetween))


        for t in teams:
            # print (getTeamById[t])
            # print (getTeamById[t],tripElements)
            for (c,v1,v2,v3,v4) in tripElements[t]:
                # if getTeamById[t]=="Regatas":
                #     print ("POSS TRIP ",getTeamById[t], (c, [ getTeamById[t3] for t3 in v1 ] , v2, [ getTeamById[t3] for t3 in v2 ] , [ getTeamById[t3] for t3 in v3 ] , [ getTeamById[t3] for t3 in v4 ]), trip_minDays[c], trip_maxDays[c])
                for d1 in tripDayPairs.keys():  
                    if getWeekDay[d1] in trip_weekdays[c] and ( not onlyFewTrips or t%6==d%6 ) :
                        otherTripDays = [d2 for (d2,daysBetween) in tripDayPairs[d1] if daysBetween>=trip_minDays[c] and daysBetween<=trip_maxDays[c]]
                        inBetweenDays = [d2 for (d2,daysBetween) in tripDayPairs[d1] if daysBetween<=trip_minDays[c] ]
                        otherTripDays3 = list(set([d2 for d11 in tripDayPairs.keys() for (d2,daysBetween) in tripDayPairs[d11] if d11 in otherTripDays and daysBetween>=trip_minDays[c] and daysBetween<=trip_maxDays[c]]))
                        otherTripDays4 = list(set([d2 for d11 in tripDayPairs.keys() for (d2,daysBetween) in tripDayPairs[d11] if d11 in otherTripDays3 and daysBetween>=trip_minDays[c] and daysBetween<=trip_maxDays[c]]))
                        # print ("possible? ", getTeamById[t] , getNiceDay[d1], otherTripDays,otherTripDays3,otherTripDays4)
                        if len(otherTripDays)>0 and (thisSeason.tripLength <3 or len (v3)==0 or len(otherTripDays3)>0)  and (thisSeason.tripLength <4 or len (v4)==0 or len(otherTripDays4)>0) :
                            # print ("building trip for " , getTeamById[t], " starting" , getNiceDay[d1] ,  [ getNiceDay[d] for d in otherTripDays ],  [ getNiceDay[d] for d in otherTripDays3 ] , [ getNiceDay[d] for d in otherTripDays4 ] )
                            tripToSingleTripElement[(t,d1,c)].upBound=1
                            model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v1                         for rd in getRoundDaysByDay[d1]])
                            model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v2 for d2 in otherTripDays for rd in getRoundDaysByDay[d2]])
                            for d3 in inBetweenDays:
                                model2 += tripToSingleTripElement[(t,d1,c)] <= 1- home[t,d3]
                                model2 += tripToSingleTripElement[(t,d1,c)] <= 1-lpSum([ x[(t2,t,rd)] for t2 in realteams if t2 not in v2 for rd in getRoundDaysByDay[d3]])
                            # if getTeamById[t]=="Regatas":
                            #     print (" ", getNiceDay[d1], [ getNiceDay[d2] for d2 in inBetweenDays ] ,[ getNiceDay[d2] for d2 in otherTripDays ] ," <= ",  [ (t2,t,rd) for t2 in v2 for d2 in otherTripDays for rd in getRoundDaysByDay[d2]])
                            if thisSeason.tripLength >=3 and len(v3)>0:
                                model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v3 for d2 in set(otherTripDays3) for rd in getRoundDaysByDay[d2]])
                            if thisSeason.tripLength >=4 and len(v4)>0: 
                                model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v4 for d2 in set(otherTripDays4) for rd in getRoundDaysByDay[d2]])
                            if (len(v3)>0 and len(otherTripDays3)==0) or (len(v4)>0 and len(otherTripDays4)==0) :
                                tripToSingleTripElement[(t,d1,c)].upBound=0
                            else:
                                cntr +=2

print ("built ", cntr , " trip constraints early")

if sharedStadiums:
    useStadiumTimeSlot = { (t,d,s) : pulp.LpVariable('useStadiumTimeSlot_'+str(t)+"_"+str(d)+"_"+str(s) , lowBound = 0, upBound = 1, cat = pulp.LpContinuous ) for (t,d) in t_site_bestTimeSlots.keys() for (p,s) in t_site_bestTimeSlots[(t,d)]}
    nonIceGame = { (t,d) : pulp.LpVariable('nonIceGame_'+str(t)+"_"+str(d) , lowBound = 0, upBound = 1, cat = pulp.LpContinuous ) for (t,d) in home.keys()}
    for (t,d) in t_site_bestTimeSlots.keys():                       
        if len(t_site_bestTimeSlots[t,d])==0 :
            model2 += home[(t,d)] == 0 + nonIceGame[(t,d)]
        else:
            model2 += home[(t,d)] == lpSum([useStadiumTimeSlot[(t,d,s)] for (p,s) in t_site_bestTimeSlots[t,d]])+ nonIceGame[(t,d)]
        if "AllowGamesWithoutIce" not in special_wishes_active:
            model2 += nonIceGame[(t,d)] == 0 

    getStadiumTimeSlotsPerDay={  (st.id,d) : [] for st in theseStadiums for d in days   }
    # for s in sorted(getStadiumTimeSlot.keys()):
    #     print (s,getStadiumTimeSlot[s])
    for (t,d,s) in useStadiumTimeSlot.keys():
        getStadiumTimeSlotsPerDay[getStadiumTimeSlot[s]['stadium_id'],d].append((t,s))
        # print (t,d,s)
        # print (getStadiumTimeSlot[s])

    for st in theseStadiums:
        for d in days :
            if len(getStadiumTimeSlotsPerDay[st.id,d])>1:
                # print ("CONFLICTS?",st, getNiceDay[d],  getStadiumTimeSlotsPerDay[st.id,d])                            
                conflicts_all = [ sorted(list(incompatible_timslots[s])) for t,s in getStadiumTimeSlotsPerDay[st.id,d]]
                conflicts =[] 
                for c in conflicts_all:
                    if c not in conflicts:
                        conflicts.append(c)
                print ("conflicts ", conflicts)
                for c in conflicts:                         
                    conflicting_slots = [useStadiumTimeSlot[(t,d,s)] for t,s in getStadiumTimeSlotsPerDay[st.id,d] if s in c ]
                    # print ("not at same time " ,conflicting_slots)
                    if len(conflicting_slots)>1:
                        model2 += lpSum(conflicting_slots) <=1
                        print ( "##############   constraint built ")
    
# cntr =0
# for t in teams:
#     for r in rounds:
#         for c in real_clusters:
#             if r>1 and runMode=='Improve':
#                 if gew['Trips']>0 and t_cluster[t]!=c \
#                         and parse(getNiceDay[earliestDay[r]])-parse(getNiceDay[latestDay[r-1]])<=datetime.timedelta(days=thisSeason.maxDistanceWithinTrip+1):
#                     model2 +=  tripToCluster[(t,r-1,c)]  <= away_in_cluster[t,r-1,c]
#                     model2 +=  tripToCluster[(t,r-1,c)]  <= away_in_cluster[t,r,c]
#                     tripToCluster[(t,r-1,c)].upBound=1
#                     # print ('considering trip of ' , getTeamById[t], ' in round ' , r , ' to cluster ' , c )
#                     cntr +=2
#                 else:
#                     model2 +=  tripToCluster[(t,r-1,c)] == 0

#             if r==nRounds  :
#                 model2 +=  tripToCluster[(t,r,c)] == 0
# print ("built ", cntr , " trip constraints")

if thisSeason.useFeatureKickOffTime:
    for t in realteams:
        for d in onlyEarlyDays:
            model2+= home_time[t,d,getIdByTime["Late"]]==0
            model2+= away_time[t,d,getIdByTime["Late"]]==0
        for d in onlyLateDays:
            model2+= home_time[t,d,getIdByTime["Early"]]==0
            model2+= away_time[t,d,getIdByTime["Early"]]==0


breakVioBalance = { t : pulp.LpVariable('breakVioBalance_'+str(t) , lowBound = 0, cat = pulp.LpContinuous) for t in realteams }
numBreaks = { t :  lpSum([  breakVio[(bl['id'],t)]  for bl in breaks ]) for t in realteams }
numBreaks1 = { t :  lpSum([  breakVio[(bl['id'],t)]  for bl in breaks if bl['round2']<=nRounds1 ]) for t in realteams }


succBreaks = [ bl for bl in breaks if  bl['round1']+1==bl['round2']  ]

if thisSeason.forbidDoubleBreaks:
    for bl1 in succBreaks:
        for bl2 in succBreaks:
            if bl1['round2']+1==bl2['round1']:
                for t in realteams:
                    model2+=  homeInRound[t,bl1['round1']] + homeInRound[t,bl1['round2']]  +  awayInRound[t,bl2['round1']] + awayInRound[t,bl2['round2']]   <=  3 +  0.2* breakVio[(bl1['id'],t)] 
                    model2+=  awayInRound[t,bl1['round1']] + awayInRound[t,bl1['round2']]  +  homeInRound[t,bl2['round1']] + homeInRound[t,bl2['round2']]   <=  3 +  0.2* breakVio[(bl1['id'],t)] 

for t in realteams:
    for bl in breaks:
        # print (getTeamById[t], realteams, getRoundDaysByRound[bl['round1']]+getRoundDaysByRound[bl['round2']] )
        # model2+=  breakVio[(bl['id'],t)] + 1 >=  lpSum([x[(t,t2,rd)] for t2 in realteams for rd in getRoundDaysByRound[bl['round1']]+getRoundDaysByRound[bl['round2']] ])
        # model2+=  breakVio[(bl['id'],t)] + 1 >=  lpSum([x[(t2,t,rd)] for t2 in realteams for rd in getRoundDaysByRound[bl['round1']]+getRoundDaysByRound[bl['round2']] ])
        model2+=  breakVio[(bl['id'],t)] + 1 >= homeInRound[t,bl['round1']] + homeInRound[t,bl['round2']]
        model2+=  breakVio[(bl['id'],t)] + 1 >= awayInRound[t,bl['round1']] + awayInRound[t,bl['round2']]
        if bl['round2'] + 1 <= nRounds:
            model2+=  0.2+breakVio[(bl['id'],t)] + 2 >= homeInRound[t,bl['round1']] + homeInRound[t,bl['round2']] + homeInRound[t,bl['round2']+1] 
            model2+=  0.2+breakVio[(bl['id'],t)] + 2 >= awayInRound[t,bl['round1']] + awayInRound[t,bl['round2']] + awayInRound[t,bl['round2']+1]         

    if balanceBreaks:
        model2+=  numBreaks[t] <= lpSum([ numBreaks[t2] for t2 in realteams])/len(realteams)  + breakVioBalance[t]
        for t2 in teams: 
            if half_symmetry_offset==0:
                model2+=  numBreaks[t2] <= 4
                model2+=  numBreaks[t2] >= 3
                model2+=  numBreaks1[t2] <= 2
            else:
                model2+=  numBreaks[t2] <= 5
                model2+=  numBreaks[t2] >= 1
        print ("balancing Breaks ")

        for bl in breaks:
            model2+=  breakVio[(bl['id'],t)] <= 2 - homeInRound[t,bl['round1']] - awayInRound[t,bl['round2']] 
            model2+=  breakVio[(bl['id'],t)] <= 2 - awayInRound[t,bl['round1']] - homeInRound[t,bl['round2']]

        

    if not evalRun:
        if not thisSeason.minBreaks and len(breaks)>0 and not balanceBreaks:
            for p in phases:
                # print ("Don't allow breaks for  ",t, " in phase ", p)
                model2+= lpSum([breakVio[(bl['id'],t)] for bl in breaks if getPhaseOfRound[bl['round1']]==p and getPhaseOfRound[bl['round2']]==p]) <= thisSeason.initBreaks

        if mathModelName in [ "Ligue 1"]:
            model2+= lpSum([breakVio[(bl['id'],t)] for bl in breaks ]) <= 4

        if not thisSeason.startWithBreakAllowed:
            model2+= homeInRound[t,1] + homeInRound[t,2]  <= 1
            model2+= awayInRound[t,1] + awayInRound[t,2]  <= 1
        if not thisSeason.endWithBreakAllowed:
            print ("NO BREAK FOR " , t , " in rounds " ,nRounds-1, nRounds)
            model2+= homeInRound[t,nRounds-1] + homeInRound[t,nRounds]  <= 1
            model2+= awayInRound[t,nRounds-1] + awayInRound[t,nRounds]  <= 1

# print ('\n')
# for p in phases:
#     for  d in getDaysOfPhase[p] :
#         print (p,d, getRoundDaysByDay[d])

# return ''

if len (fixedGamesRounds)==0:
    for br in basicRounds:
        imp_rds= getRoundDaysByBasicRound[br] if thisSeason.gamesPerRound=="one day" else [getRoundDaysByBasicRound[br][0]]
        # print (br, imp_rds)        
        for t1 in realteams:            
            model2 += homeInBasicRound[(t1,br)] == lpSum([x[(t1,t2,rd)] for t2 in opponents[t1] for rd in imp_rds])
            model2 += awayInBasicRound[(t1,br)] == lpSum([x[(t2,t1,rd)] for t2 in opponents[t1] for rd in imp_rds])
            for t2 in opponents[t1]:
                if (t1,t2) in games:
                    model2 += gameInBasicRound[(t1,t2,br)] == lpSum([ x[(t1,t2,rd)] for rd in imp_rds ])

                    # print ("§§§",t1,t2,br,gameInBasicRound[(t1,t2,br)].upBound )

# for ttr in x.keys():
#     makeIntVar(x[ttr])
# model2.solve(GUROBI(MIPGap=0.3, TimeLimit=180,msg=1))



getDays[0] =[]

# return 2
# for d in days+higherLeagueDayIds:
#     for stadium in stadiums:
#         factor = 0.001 if len(teamsOfStadium[stadium])==2 else 1.0
#         # print (stadium, teamsOfStadium[stadium] , len(teamsOfStadium[stadium]))
#         model2 += lpSum([home[t,d] for t in teamsOfStadium[stadium]]) <= 1 + factor*tooManyHomesInStadium[(stadium,d)]



if thisSeason.useFeaturePairings:

    # identify Fr.-Mo. weekends
    weekends = []
    sorted_days = sorted(days+higherLeagueDayIds, key=lambda x:getDateTimeDay[x])
    oneDay= datetime.timedelta(days=1)
    lastDay=-1
    lastWeekday ="Thu"        
    currentWeekend=[]
    for d in sorted_days:
        newWeekend = lastWeekday in ["Tue","Wed","Thu"] or getDateTimeDay[d]-getDateTimeDay[lastDay]>3*oneDay
        if newWeekend:
            if len(currentWeekend)>0:
                weekends.append(currentWeekend)
            currentWeekend=[]
        if getWeekDay[d] in ["Fri", "Sat", "Sun", "Mon"]:
            currentWeekend.append(d)
        lastDay=d
        lastWeekday=getWeekDay[d]
    if len(currentWeekend)>0:
        weekends.append(currentWeekend)

    for pair in pairings:
        pDaysSets = []
        pTeams = [pair['team1_id'], pair['team2_id']]
        factor = 1.0
        if pair['dist'] in [10,11] :
            # restrict to the weekend which overlap with the interval
            pDaysSets = [ w for w in weekends]
            pDaysSets = [ w for w in pDaysSets if not pair["first_day_id"] or not getNiceDayRaw[w[-1]] < getNiceDayRaw[pair["first_day_id"]]]
            pDaysSets = [ w for w in pDaysSets if not pair["last_day_id"] or not getNiceDayRaw[pair["last_day_id"]]<= getNiceDayRaw[w[0]]]
        else:                    
            for d in pair["days"]:
                pDays = [d]
                if pair['dist'] in [1,5,8,9] and nextDay[d]!=-1 and (nextDay[d] in days+higherLeagueDayIds) :
                    pDays.append(nextDay[d])
                if pair['dist'] in [8,9] and nextnextDay[d]!=-1 and (nextnextDay[d] in days+higherLeagueDayIds) :
                    pDays.append(nextnextDay[d])
                if pair['dist'] in [3,7]:
                    pDays=getDays[getRoundByDay[d]] + getHigherDaysByRound[getRoundByDay[d]]
                    # print ( getNiceDay[d],  getRoundByDay[d],  getDays[getRoundByDay[d]] , " +" ,getHigherDaysByRound[getRoundByDay[d]])
                if len(pDays)>0 and pDays not in pDaysSets and not ((pair['dist']==5 and len(pDays)!=2) or (pair['dist']==9 and len(pDays)!=3)):
                    pDaysSets.append(pDays.copy())
            #     print ("+++ ")
            # else: 
            #     print ("--- ")

            # if pair['prio'] =='A':
            #     factor = 0.1                        
        for pDays in pDaysSets:
            d= pDays[0]
            # print ("Treating day set starting with day " , getNiceDay[d], " ", pDays)
            if pair['dist'] in [2,6] and thisSeason.useFeatureKickOffTime:
                for tm in times:
                    if pair['type']== "Home":
                        if pair['dist']==2:
                            model2 += lpSum([home_time[t,d,tm] for t in pTeams]) <= 1 + factor*pairingVio[(pair['id'],d)]
                        else:
                            model2 += home_time[pair['team1_id'],d,tm] -  home_time[pair['team2_id'],d,tm]  <= factor*pairingVio[(pair['id'],d)]
                            model2 += home_time[pair['team2_id'],d,tm] -  home_time[pair['team1_id'],d,tm]  <= factor*pairingVio[(pair['id'],d)]
                    if pair['type']== "Away":
                        if pair['dist']==2:
                            model2 += lpSum([away_time[t,d,tm] for t in pTeams]) <= 1 + factor*pairingVio[(pair['id'],d)]
                        else:
                            model2 += away_time[pair['team1_id'],d,tm] -  away_time[pair['team2_id'],d,tm]  <= factor*pairingVio[(pair['id'],d)]
                            model2 += away_time[pair['team2_id'],d,tm] -  away_time[pair['team1_id'],d,tm]  <= factor*pairingVio[(pair['id'],d)]
                    if pair['type']== "Home and Away":
                        if pair['dist']==2:
                            model2 += lpSum([home_time[t,d,tm] + away_time[t,d,tm] for t in pTeams]) <= 1 + pairingVio[(pair['id'],d)]
                        else:
                            model2 += home_time[pair['team1_id'],d,tm] + away_time[pair['team1_id'],d,tm] -  home_time[pair['team2_id'],d,tm]  -  away_time[pair['team2_id'],d,tm]  <= factor*pairingVio[(pair['id'],d)]
                            model2 += home_time[pair['team2_id'],d,tm] + away_time[pair['team2_id'],d,tm] -  home_time[pair['team1_id'],d,tm]  -  away_time[pair['team1_id'],d,tm]  <= factor*pairingVio[(pair['id'],d)]

            else:
                if pair['type']== "Home":
                    if pair['dist'] in [0,1,8,3,10]:
                        model2 += lpSum([home[t,dd] for t in pTeams for dd in pDays ]) <= 1 + factor*pairingVio[(pair['id'],d)]
                    else:
                        model2 += lpSum([home[pair['team1_id'],dd] - home[pair['team2_id'],dd] for dd in pDays]) <=  factor*pairingVio[(pair['id'],d)]
                        model2 += lpSum([home[pair['team2_id'],dd] - home[pair['team1_id'],dd] for dd in pDays]) <=  factor*pairingVio[(pair['id'],d)]
                if pair['type']== "Away":
                    if pair['dist'] in [0,1,8,3,10]:
                        model2 += lpSum([away[t,dd] for t in pTeams for dd in pDays ]) <= 1 + factor*pairingVio[(pair['id'],d)]
                    else:
                        model2 += lpSum([away[pair['team1_id'],dd] - away[pair['team2_id'],dd] for dd in pDays]) <=  factor*pairingVio[(pair['id'],d)]
                        model2 += lpSum([away[pair['team2_id'],dd] - away[pair['team1_id'],dd] for dd in pDays]) <=  factor*pairingVio[(pair['id'],d)]
                if pair['type']== "Home and Away":
                    if pair['dist'] in [0,1,8,3,10]:
                        model2 += lpSum([home[t,dd] + away[t,dd] for t in pTeams for dd in pDays]) <= 1 + pairingVio[(pair['id'],d)]
                    else:
                        model2 += lpSum([home[pair['team1_id'],dd] + away[pair['team1_id'],dd] - home[pair['team2_id'],dd] - away[pair['team2_id'],dd] for dd in pDays]) <=  factor*pairingVio[(pair['id'],d)]
                        model2 += lpSum([home[pair['team2_id'],dd] + away[pair['team2_id'],dd] - home[pair['team1_id'],dd] - away[pair['team1_id'],dd] for dd in pDays]) <=  factor*pairingVio[(pair['id'],d)]


# print ("fixedGames:" ,fixedGames)
for (t1,t2,d) in fixedGames:
    model2+= lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByRound[getRoundByDay[d]] ] )==1 - fixedGameVio[(t1,t2,d)]
    # if not thisSeason.useFeatureKickOffTime or not currentKickoffTimes[(t1,t2,d)] :
    #     model2+= lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByRound[getRoundByDay[d]] ] )==1 - fixedGameVio[(t1,t2,d)]
    # else:
    #     model2+= lpSum ( [x_time[(t1,t2,rd,currentKickoffTimes[(t1,t2,d)])] for rd in getRoundDaysByRound[getRoundByDay[d]] ] )==1 - fixedGameVio[(t1,t2,d)]                
    if not thisScenario.allowFixedVio:
        model2+= fixedGameVio[(t1,t2,d)]==0
        print ("HARD FIXING TO ROUND", getRoundByDay[d], t1,t2,d )
    else: 
        print ("SOFT FIXING TO ROUND", getRoundByDay[d], t1,t2,d )

for (t1,t2,d) in fixedGames2:        
    if len([rd for rd in getRoundDaysByDay[d] if (t1,t2,rd) in x.keys()]) >0 :
        if not thisSeason.useFeatureKickOffTime or not currentKickoffTimes[(t1,t2,d)] :
            model2+= lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByDay[d]] )== 1 - fixedGame2Vio[(t1,t2,d)]
        else:
            model2+= lpSum ( [x_time[(t1,t2,rd,currentKickoffTimes[(t1,t2,d)])]  for rd in getRoundDaysByDay[d]] )== 1 - fixedGame2Vio[(t1,t2,d)]
        if not thisScenario.allowFixedVio:
            model2+= fixedGame2Vio[(t1,t2,d)]==0
            print ("HARD FIXING " , t1,t2,d , (t1,t2,d) in fixedGameVio.keys(), getRoundDaysByDay[d]  , getRoundByDay[d] )
        else:
            print ("SOFT FIXING " , t1,t2,d , (t1,t2,d) in fixedGameVio.keys(), getRoundDaysByDay[d]  )

# return ''
# use_currentSolution= False
# for (t1,t2,d) in fixedRoundGames:
#     # if thisScenario.allowFixedVio:
#     #     model2 += lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByRound[getRoundByDay[d]]] )==1 - fixedRoundGameVio[(t1,t2,d)]
#     # else:
#     model2 += lpSum ( [x[(t1,t2,rd)] for rd in getRoundDaysByRound[getRoundByDay[d]]] )==1

# # TESTING


use_currentSolution= False

currentGameCntr = { (t1,t2) :0 for t1 in teams for t2 in teams }

if runMode=='Improve' and len(currentSolution) > len(fixedGames) + len(fixedGames2 ) :
    use_currentSolution= True

# if use_currentSolution and len(currentSolution) !=len(fixedGames):    

teamGameCntr = { (t,r) :0 for t in teams for r in rounds }

if use_currentSolution:    
    for cs in currentSolution: 
        if len(cs)>=4:
            t1=cs[0]
            t2=cs[1]
            r=cs[2]
            d=cs[3]
            if (t1,t2,(r,d)) in x.keys():
                currentGameCntr[(t1,t2)] +=1
                setLB(x[(t1,t2,(r,d))],1)
                teamGameCntr[t1,r]+=1
                teamGameCntr[t2,r]+=1
                # if t1==16770:
                # print ("fixing " , t1 , t2, r ,d)

# for (t,r) in teamGameCntr.keys():
#     if teamGameCntr[(t,r)]!=1:
#         print (getTeamById[t], " plays " ,teamGameCntr[(t,r)] , " games in round ", r )
    
            
# sing for  16770 16766 0 2

# for ttr in x.keys():
#     makeIntVar(x[ttr])


# if len(currentSolution) ==len(fixedGames):
#     print ("alles fixieren")

# print ("TESTING")
# for ttr in x.keys():
#     makeIntVar(x[ttr])
# model2.solve(GUROBI(MIPGap=0.0, TimeLimit=40,msg=1))
# print ("TESTING DONE")



# print ("days " , days)
for d in days: 
    model2 += lpSum([x[(t1,t2,rd)] for (t1,t2) in games  for rd in getRoundDaysByDay[d] if distance[getTeamById[t1],getTeamById[t2]]<=thisSeason.maxDistanceDerby ]) >= nDerbies[d] - derbyMissing[d]
    minG = sum([ roundDaysMin[rd] - deficientGames[rd]  for rd in getRoundDaysByDay[d]])        
    maxG = sum([ roundDaysMax[rd] + excessGames[rd] for rd in getRoundDaysByDay[d]])        
    # print (getNiceDay[d] , maxG)
    # if minG<3 :
    if minG>0 :
        model2 += lpSum([ home[(t,d)] for t in realteams]) >= minG
    model2 += lpSum([ home[(t,d)] for t in realteams]) <= maxG

    if len(getRoundDaysByDay[d])>1:
        for rd in getRoundDaysByDay[d]:
            if roundDaysMin[rd]>0:
                model2 += lpSum([x[(t1,t2,rd)] for (t1,t2) in games ] ) >= roundDaysMin[rd] - deficientGames[rd] 
                # model2 += lpSum([x[(t1,t2,rd)] for (t1,t2) in games ] ) >= roundDaysMin[rd] 
                print ("At least ",roundDaysMin[rd] , " on " , rd)
            model2 += lpSum([x[(t1,t2,rd)] for (t1,t2) in games ] ) <= roundDaysMax[rd] + excessGames[rd] 

print ("rounds " , rounds, nRounds)
for r in rounds:
    # one game a round for everyone
    for t1 in realteams:
        if thisSeason.gamesPerRound=="one day":
            cnstr = lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)] for t2 in opponents[t1] for rd in getRoundDaysByRound[r]] )
            if len(cnstr) > 0:
                model2 += cnstr <= 1
        else:
            print ( getRoundDaysByRound[r], opponents[t1])
            if len(getRoundDaysByRound[r])>0:
                for rd in getRoundDaysByRound[r]:
                    if rd==getRoundDaysByRound[r][0]:
                        model2 += lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)] for t2 in opponents[t1]] ) <= 1
                    else:
                        for t2 in opponents[t1]:
                            model2 += x[(t1,t2,rd)] == x[(t1,t2,getRoundDaysByRound[r][0])]
                            # print ("linking ", getRoundDaysByRound[r][0] , " to ", rd , " game " , t1, t2)
    if len(getRoundDaysByRound[r])>1 and False:
        for rd in getRoundDaysByRound[r]:
            for t1 in realteams:
                model2 += lpSum([home[t1,rd[1]] + away[t1,rd[1]]] ) <= 1

# exit(0)
print ("realteams " , realteams)

print ("taking care of right numbers of games ... " ) 
cntr= 0

if not specialGameControl:
    for (t1,t2) in realgames: 
        if undirectedGameCntr[(t1,t2)]==0:
            model2 += lpSum([x[(t1,t2,rd)] for rd in roundDays] ) == gameCntr[(t1,t2)] - missingGamesVio[(t1,t2)]
        else:
            # model2 += lpSum([x[(t1,t2,rd)] for rd in roundDays] ) == gameCntr[(t1,t2)]+undirectedGameCntr[(t1,t2)] - missingGamesVio[(t1,t2)]
            model2 += missingGamesVio[(t1,t2)]  >= gameCntr[(t1,t2)] - lpSum([x[(t1,t2,rd)] for rd in roundDays] ) 
            model2 += missingGamesVio[(t1,t2)]  >= gameCntr[(t1,t2)]+gameCntr[(t2,t1)]+undirectedGameCntr[(t1,t2)] - lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)] for rd in roundDays] ) 
            model2 += lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)] for rd in roundDays] ) <= gameCntr[(t1,t2)]+gameCntr[(t2,t1)]+undirectedGameCntr[(t1,t2)] 
            
        missingGamesVio[(t1,t2)].upBound= max(0,gameCntr[(t1,t2)]+undirectedGameCntr[(t1,t2)] - currentGameCntr[(t1,t2)])

        # print (t1,t2,gameCntr[(t1,t2)], currentGameCntr[(t1,t2)] , lpSum([x[(t1,t2,rd)] for rd in roundDays] ) )

if thisSeason.useFeatureOpponentMatrix and False:
    gameCntr = { (t1,t2) : 0 for t1 in teams for t2 in teams }               
    for gm in gameRequirements:
        gameCntr[(gm.team1.id,gm.team2.id)] = gm.number
        if gm.number>0:
            # print ("++++  " ,gm)
            if gm.number <= 0.5*nPhases or currentGameCntr[(gm.team1.id,gm.team2.id)]==gm.number: 
                model2 += lpSum([x[(gm.team1.id,gm.team2.id,rd)] for rd in roundDays] ) == gm.number
                # print ("EQU " , gm) 
            else:
                model2 += lpSum([x[(gm.team1.id,gm.team2.id,rd)] for rd in roundDays] ) == gm.number - missingGamesVio[(gm.team1.id,gm.team2.id)]
                # print ("MAX " , gm) 
                model2 += missingGamesVio[(gm.team1.id,gm.team2.id)] <= gm.number -0.5*nPhases
                print ("games still missing for " , gm.team1.id, gm.team2.id, currentGameCntr[(gm.team1.id,gm.team2.id)] , gm.number)

print ("... done" ) 

# print (missingGamesVio.keys())


if not evalRun:
    for (t1,t2) in realgames:
        # every pair plays each other in each phase once
        for p in phases:
            if p<len(phases)-1 or True: # phase violation in last phase possible if it contained more rounds than necessary
                if t_usePhases[t1] or t_usePhases[t2]:
                    if thisSeason.groupBased and len(noPlayRounds[t1])>0 and noPlayRounds[t1]==noPlayRounds[t2]:
                        relDays = []
                        phaseLength= int(len(playRounds[t1])/nPhases+0.5)
                        for rr in playRounds[t1][p*phaseLength:(p+1)*phaseLength]:
                            relDays+=getDays[rr]
                            print ("adding days of round ", rr , " to phase ", p)
                    else:
                        relDays = getDaysOfPhase[p]
                    model2 += lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)]  for d in relDays for rd in getRoundDaysByDay[d] ] ) <= 1
                    # print (len(relDays),"reldays")                        
                    # print (getTeamById[t1],getTeamById[t2], lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)]  for d in relDays for rd in getRoundDaysByDay[d] ] ))

if not evalRun :
    for t in realteams:
        if t_usePhases[t] and thisSeason.distributeHomeGamesEvenlyOverPhases:
            for p in phases:
                rds = [r for r in rounds if getPhaseOfRound[r]==p ]
                nblocked =[ r for r in noHomeRounds[t] if r in rds]
                print (p, len(rds), len(nblocked), rds,nblocked, getTeamById[t])
            for p in phases:
                phaseLength= int(len(playRounds[t])/nPhases+0.5)
                model2 += lpSum([ home[(t,d)] for d in getDaysOfPhase[p] ] ) <= int(phaseLength/2+1)

    if thisSeason.minRoundsBetweenGameOfSameTeams>0:
        for r in rounds:
            if r +thisSeason.minRoundsBetweenGameOfSameTeams <=nRounds:
                rds = [ ]            
                for r2 in range(r,r+thisSeason.minRoundsBetweenGameOfSameTeams+1):
                    rds+=getRoundDaysByRound[r2]
                rds2 = [ ]            
                for r2 in range(r,r+int (0.5*thisSeason.minRoundsBetweenGameOfSameTeams)):
                    rds2+=getRoundDaysByRound[r2]
                # print ("ONLY ONE IN " , rds)
                # print ("ONLY ONE IN " , rds2)
                for t1 in realteams:
                    for t2 in realteams:
                        if t1<t2 and (gameCntr[(t1,t2)]*gameCntr[(t2,t1)]>0 or x_round[(t1,t2,r)]!=0) :
                                # model2 +=  lpSum([ (x[(t1,t2, rd)]+x[(t2,t1,rd)]) for rd in rds ]) <= 1 + gamesTooClose2[t1,r]
                                model2 +=  lpSum([ (x[(t1,t2, rd)]+x[(t2,t1,rd)]) for rd in rds ]) <= 1 


if thisSeason.lastRoundSync:
    for g in displayGroups.keys():
        affectedRounds = set([r for (r,d) in finalRoundDays])
        print ("affectedRounds", affectedRounds)
        if thisSeason.useFeatureKickOffTime:
            print ("sync time ", g, " " , displayGroups[g], " " , finalRoundDays, " ", times)
            for r in affectedRounds:
                model2 += lpSum([lastRoundPlayed[(g,rd,tm)] for rd in finalRoundDays for tm in times if rd[0]==r ]) == 1
            # model2 += lpSum([lastRoundPlayed[(g,rd,tm)] for rd in finalRoundDays for tm in times]) == len(affectedRounds)
            for t in displayGroups[g]:
                for rd in finalRoundDays:
                    for tm in times:
                        model2+= home_time[t,rd[1],tm]+ away_time[t,rd[1],tm] <= lastRoundPlayed[(g,rd,tm)]
        else: 
            # print ("sync time", g, " " , displayGroups[g], " " , finalRoundDays)
            for r in affectedRounds:
                model2 += lpSum([lastRoundPlayed[(g,rd)] for rd in finalRoundDays if rd[0]==r ]) == 1
            # model2 += lpSum([lastRoundPlayed[(g,rd)] for rd in finalRoundDays  ]) == len(affectedRounds)
            print (lpSum([lastRoundPlayed[(g,rd)] for rd in finalRoundDays ]) , " ==" , len(affectedRounds))
            for t in displayGroups[g]:
                for rd in finalRoundDays:
                    model2+= home[(t,rd[1])] + away[(t,rd[1])] <= lastRoundPlayed[(g,rd)]
                    # print ("home[(",t,rd[1],")] + away[(",t,rd[1],")] <= lastRoundPlayed[(",g,rd,")])")

    
if not evalRun:
    # max length home stands /trips
    for r in range (1,nRounds-thisSeason.maxTourLength+1):
        # print (" at least one home and away in rounds ")
        # for r3  in range(r,r+thisSeason.maxTourLength+1):
        #     print (r3 )
        for t in teams:
            if t not in noBreakLimitTeams:
                # model2 += lpSum([homeInRound[t,r2] for r2 in range(r,r+thisSeason.maxTourLength+1)]) >=1
                model2 += lpSum([awayInRound[t,r2] for r2 in range(r,r+thisSeason.maxTourLength+1)]) <=thisSeason.maxTourLength
                model2 += lpSum([homeInRound[t,r2] for r2 in range(r,r+thisSeason.maxTourLength+1)]) <=thisSeason.maxTourLength

print ("check 1")

    # blockings
for bl in blockings:
    if getDayById[bl['day_id']]['round'] !=0:
        if thisSeason.useFeatureKickOffTime and bl['time']!='----':
            if bl['type'] in ["Home", "Hide","Game"]:
                model2+=  blockingVio[bl['id']]== home_time[bl['team_id'], bl['day_id'],bl['time']]
                # print ('FOUND HOME BLOCKING ', bl)
            else:
                model2+=  blockingVio[bl['id']]== away_time[bl['team_id'], bl['day_id'],bl['time']]
                # print ('FOUND AWAY BLOCKING ', bl)
        else:
            if bl['type'] in ["Home", "Hide","Game"]:
                model2+=  blockingVio[bl['id']]== home[bl['team_id'], bl['day_id']]
                # print ('FOUND HOME BLOCKING ', bl)
            else:
                model2+=  blockingVio[bl['id']]== away[bl['team_id'], bl['day_id']]
                # print ('FOUND AWAY BLOCKING ', bl)


print ("check 2")

hawOneVio={}
hawForOneNotViolated={}

def getStringFromSet(ss):
    s2 =""
    for s in ss: 
        s2+=str(s)+"_"
    return s2[:-1]

    # hawishes
for haw in hawishes:
    print (haw['reason'])
    for el in elemHaWishes[haw['id']]:
        if thisSeason.useFeatureKickOffTime and len(hawTimes[haw['id']])>0:
            if haw['homeAway']=='Home':
                relGames = lpSum([home_time[t,d,tm] for d in elemHaWishDays[el] for t in elemHaWishTeams[el] for tm in hawTimes[haw['id']]])
                # print (haw['id'] ," haw : ", relGames, hawTimes[haw['id']])
            elif haw['homeAway']=='Away':
                relGames = lpSum([away_time[t,d,tm] for d in elemHaWishDays[el] for t in elemHaWishTeams[el] for tm in hawTimes[haw['id']]])
            else :
                # print(haw,el)
                relGames = lpSum([home_time[t,d,tm] + away_time[t,d,tm] for d in elemHaWishDays[el] for t in elemHaWishTeams[el] for tm in hawTimes[haw['id']]]) \
                            - lpSum([x_time[(t1,t2,rd,tm)] for d in elemHaWishDays[el] for rd in getRoundDaysByDay[d] for tm in hawTimes[haw['id']] for t1 in elemHaWishTeams[el] for t2 in elemHaWishTeams[el] if (t1,t2,rd,tm) in x_time.keys()]) 

        else:
            if haw['homeAway']=='Home':
                relGames = lpSum([home[t,d] for d in elemHaWishDays[el] for t in elemHaWishTeams[el]  ])
            elif haw['homeAway']=='Away':
                relGames = lpSum([away[t,d] for d in elemHaWishDays[el] for t in elemHaWishTeams[el] ])
            else :
                relGames = lpSum([home[t,d] + away[t,d] for d in elemHaWishDays[el] for t in elemHaWishTeams[el]]) - lpSum([x[t1,t2,rd] for d in elemHaWishDays[el] for rd in getRoundDaysByDay[d] for t1 in elemHaWishTeams[el] for t2 in elemHaWishTeams[el] if (t1,t2,rd) in x.keys() ]) 
        if haw['minGames'] >0 :
            model2+=  relGames  >= haw['minGames'] - HawVioTooLess[el]
            # print ("adding min ha constraint")
        if haw['maxGames'] >=0 :
            model2+=  relGames  <= haw['maxGames'] + HawVioTooMuch[el]
            # print ("adding max ha constraint")


    usedConstraintNames = [""]
    if haw['forOneDay']:
        # print (haw['forOneDay'], hawDays[haw['id']])
        # print ([el for el in elemHaWishes[haw['id']] ])
        # for el in elemHaWishes[haw['id']] :
        #     print("- " , elemHaWishDays[el]  , elemHaWishTeams[el] )
        # print ([ (el, elemHaWishFirstDay[el])  for el in elemHaWishes[haw['id']] ])
        relTeamString = { el : getStringFromSet(elemHaWishTeams[el]) for el in elemHaWishes[haw['id']] }
        relTeams = set([ relTeamString[el] for el in elemHaWishes[haw['id']]])
        # print (relTeams)
        for rt in relTeams:
            rtname = rt 
            if len(rt)>50 :
                scname=""
                while scname in usedConstraintNames:
                    ttt = bytes(rt+ ''.join(random.choice(string.ascii_lowercase) for i in range(10)), 'utf-8')
                    scname = hashlib.sha224(ttt).hexdigest()
                    rtname = scname[:10]
                    usedConstraintNames.append(rtname)
                    # print ("use rtname to encode wishes ", rtname)

            hawOneVio[(haw['id'], rt)]= pulp.LpVariable('hawOneVio_'+str(haw['id'])+"_"+rtname, cat=pulp.LpContinuous)
            for fd in hawDays[haw['id']]:
                relWishes = [el for el in elemHaWishes[haw['id']] if elemHaWishFirstDay[el]== fd]
                # relWishes = [el for el in elemHaWishes[haw['id']] ]
                # print (" -" , relWishes , [elemHaWishDays[el] for el in relWishes])
                hawForOneNotViolated[(haw['id'], rt, fd)]= 0
                if len(relWishes)>0:
                    hawForOneNotViolated[(haw['id'], rt, fd)]= pulp.LpVariable('hawForOneViolated_'+str(haw['id'])+"_"+rtname+"_"+str(fd), cat=pulp.LpBinary)
                    model2 +=  lpSum( HawVioTooMuch[el]+HawVioTooLess[el] for el in relWishes if relTeamString[el]==rt) <= 1000 *  (1-hawForOneNotViolated[(haw['id'],rt, fd)])
            model2 += lpSum( hawForOneNotViolated[(haw['id'], rt, fd)] for fd in hawDays[haw['id']] ) >= haw['forOneDayNum']-hawOneVio[(haw['id'],rt)]
        model2 += lpSum( hawOneVio[(haw['id'], rt)] for rt in relTeams ) == hawVio[haw['id']]
    else:
        # print (haw['forOneDay'], hawDays[haw['id']])
        model2 += hawVio[haw['id']]== lpSum( HawVioTooMuch[el]+HawVioTooLess[el] for el in elemHaWishes[haw['id']]) 


    if haw['prio']=="Hard" and "HardHAWishesNotBreakable" in special_wishes_active:
        model2+=  hawVio[haw['id']] ==0
        print ("WISH HARD" ,haw['reason'])


# HawVioTotal=lpSum([prioVal[haw['prio']] * (HawVioTooLess[el]+HawVioTooMuch[el]) for haw in hawishes for el in elemHaWishes[haw['id']]])
# print (hawDays)
# print (elemHaWishFirstDay) 

encOneVio={}
encForOneNotViolated={}
print ("check 3")
# encwishes
for enc in encwishes:
    # print (enc)
    for el in elemEncWishes[enc['id']]:        
        # print (enc)
        # model2+=  encVio[enc['id']] == 1 - x[enc['team1_id'], enc['team2_id'], enc['day_id']]

        if thisSeason.useFeatureKickOffTime and len(encTimes[enc['id']])>0:
            if enc['minGames'] >0 :
                model2+=  encVioTooLess[el] >= enc['minGames'] - lpSum([ x_time[(t1,t2,rd, tm )]  for d in elemEncWishDays[el] for rd in getRoundDaysByDay[d] for (t1,t2) in elemEncWishGames[el] for tm in encTimes[enc['id']] if (t1,t2) in games  ])
            if enc['maxGames'] >=0 :
                # if enc['maxGames']==0:
                print (enc['reason'], '  ', elemEncWishDays[el], '  ',enc['time'], '  ', encTeams1[enc['id']] , '  ',encTeams2[enc['id']]   )
                #     print (lpSum([x_time[(t1,t2,rd, enc['time'])]  for d in elemEncWishDays[el] for rd in getRoundDaysByDay[d] for (t1,t2) in elemEncWishGames[el] if (t1,t2) in games  ]))
                model2+=  encVioTooMuch[el] >= -enc['maxGames'] + lpSum([x_time[(t1,t2,rd, tm )]  for d in elemEncWishDays[el] for rd in getRoundDaysByDay[d] for (t1,t2) in elemEncWishGames[el] for tm in encTimes[enc['id']] if (t1,t2) in games  ])
        else:
            if enc['minGames'] >0 :
                model2+=  encVioTooLess[el] >= enc['minGames'] - lpSum([ x[t1,t2,rd]  for d in elemEncWishDays[el] for rd in getRoundDaysByDay[d] for (t1,t2) in elemEncWishGames[el] if (t1,t2) in games  ])
            if enc['maxGames'] >=0 :
                # if enc['maxGames']==0:
                #     print (enc['reason'], '  ', encDays[enc['id']], '  ', encTeams1[enc['id']] , '  ',encTeams2[enc['id']]   )
                model2+=  encVioTooMuch[el] >= -enc['maxGames'] + lpSum([ x[t1,t2,rd]  for d in elemEncWishDays[el] for rd in getRoundDaysByDay[d] for (t1,t2) in elemEncWishGames[el] if (t1,t2) in games  ])

    if enc['forOneDay']:
        for ed in encDaySets[enc['id']]:
            if len(ed)>0:
                relWishes = [ el for el in elemEncWishes[enc['id']] if elemEncWishDays[el] == ed ]
                print ("###",ed, relWishes)                
                encForOneNotViolated[(enc['id'], ed[0])]= pulp.LpVariable('encForOneNotViolated_'+str(enc['id'])+"_"+str(ed[0]), cat=pulp.LpBinary)
                model2 +=  lpSum( encVioTooMuch[el]+encVioTooLess[el] for el in relWishes) <= 1000 * (1-encForOneNotViolated[(enc['id'], ed[0])])
        model2 += lpSum( encForOneNotViolated[(enc['id'], ed[0])] for ed in encDaySets[enc['id']] if len(ed)>0 ) >= enc['forOneDayNum']-encVio[enc['id']]
    else:
        model2 += encVio[enc['id']]== lpSum( encVioTooMuch[el]+encVioTooLess[el] for el in elemEncWishes[enc['id']]) 


    if enc['prio']=="Hard" and "HardEncWishesNotBreakable" in special_wishes_active:
        model2+=  encVio[enc['id']] ==0
        print ("WISH HARD" ,enc['reason'])


print ("check 4")
    

for cf in conferencewishes:
    print (confTeams[cf['conference_id']])
    model2 += lpSum([x[t1,t2, rd] for t1 in confTeams[cf['conference_id']] for t2 in confTeams[cf['conference_id']] for rd in getRoundDaysByDay[cf['day_id']] if (t1,t2, rd) in x.keys() ]) <=  cf['maxGames'] + confVio[cf['id']]
    model2 += lpSum([x[t1,t2, rd] for t1 in confTeams[cf['conference_id']] for t2 in confTeams[cf['conference_id']] for rd in getRoundDaysByDay[cf['day_id']] if (t1,t2, rd) in x.keys() ]) >=  cf['minGames'] - confVio[cf['id']]
    print (cf , " : " , confTeams[cf['conference_id']])
    if thisSeason.groupBased:
        model2+= confVio[cf['id']]==0

b_slots={(b.id,r) : [] for b in broadcastingwishes for r in rounds}
if thisSeason.useFeatureKickOffTime:
    for b in broadcastingwishes:
        b_weekdays = [sl.weekday[:3] for sl in b.slots.all() ]
        for r in rounds:
            if len( [wd for wd in b_weekdays if wd in getWeekDaysPerRound[r]]) ==  len(b_weekdays):
                b_slots[(b.id,r)] = [ (d,str(sl.timeslot.id),sl.quality) for sl in b.slots.all() for d in getDays[r] if getWeekDay[d]==sl.weekday[:3]]
                if len(b_slots[(b.id,r)])>0:
                    model2 += lpSum([ x_time[g[0][0],g[0][1],(r,d),tm]+x_time[g[0][1],g[0][0],(r,d),tm] for g in topGames for (d,tm,q) in b_slots[(b.id,r)]]) >=  b.minGames - broadVioTm[(b.id,r)]
                    model2 += lpSum([ x_time[t1,t2,(r,d),tm] for (t1,t2) in games for (d,tm,q) in b_slots[(b.id,r)]]) >=  b.minGames - 0.5*broadVioTm[(b.id,r)]
                    if b.network.id in networkFavTeams.keys() :
                        model2 += lpSum([ x_time[t1,t2,(r,d),tm] for (t1,t2) in games for (d,tm,q) in b_slots[(b.id,r)] if t1 in networkFavTeams[b.network.id] or t2 in networkFavTeams[b.network.id]  ]) >=  b.minGames - 0.1*broadVioTm[(b.id,r)]
                        # if b.network.name== "Super Sport":
                            # print ("  -   " ,r , lpSum([ x_time[t1,t2,(r,d),tm] for (t1,t2) in games for (d,tm,q) in b_slots[(b.id,r)] if t1 in networkFavTeams[b.network.id] or t2 in networkFavTeams[b.network.id]  ]))

# return ""
weekdayHomePref={}
dayHomePref={}
for t in teams:
    tm = getTeamByName[getTeamById[t]]
    weekdayHomePref[(t,'Mon')]=tm['home_pref_mo']
    weekdayHomePref[(t,'Tue')]=tm['home_pref_tu']
    weekdayHomePref[(t,'Wed')]=tm['home_pref_we']
    weekdayHomePref[(t,'Thu')]=tm['home_pref_th']
    weekdayHomePref[(t,'Fri')]=tm['home_pref_fr']
    weekdayHomePref[(t,'Sat')]=tm['home_pref_sa']
    weekdayHomePref[(t,'Sun')]=tm['home_pref_su']
    for d in days :
        dayHomePref[(t,d)]=weekdayHomePref[(t,getWeekDay[d])]


maxTravelDistance =  max([ distanceById[t1,t2] for t1 in realteams for t2 in realteams ]) 
maxTravelDistance = max(1,maxTravelDistance)

singleTripWeight=50
breakImbalanceTotal= lpSum([ breakVioBalance[t] for t in realteams])
tripSavedTotal2= ( lpSum([ singleTripWeight *tripToSingleTripElement[(t,d,c)] for (t,d,c) in tripToSingleTripElement.keys() ]) 
                    +(  lpSum([ c_weight[c] *tripToClusterSaving[(t,c)] *tripToCluster[(t,r,c)] for (t,r,c) in tripToCluster.keys() ])
                    +lpSum([ c_weight[c] *tripToClusterSaving[(t,c)] *tripToClusterDaily[(t,d,c)] for (t,d,c) in tripToClusterDaily.keys()]))/maxTravelDistance )
# HawVioTotal=lpSum([prioVal[haw['prio']] * (HawVioTooLess[el]+HawVioTooMuch[el]) for haw in hawishes for el in elemHaWishes[haw['id']]])
HawVioTotal=lpSum([prioVal[haw['prio']] * hawTagweight[haw['id']]* hawVio[haw['id']] for haw in hawishes])
encVioTotal=lpSum([prioVal[enc['prio']] * encTagweight[enc['id']] * encVio[enc['id']] for enc in encwishes])
seedVioTotal=lpSum([100*prioVal[enc['prio']] * encVio[enc['id']] for enc in encwishes if enc['seed'] ])
confVioTotal=lpSum([prioVal[conf['prio']] * confVio[conf['id']] for conf in conferencewishes])
# broadVioTotal=lpSum([ 10 * broadVio[d] for d in days]) + lpSum([ 10 * broadVioTm[b.id] for b in broadcastingwishes])
broadVioTotal=lpSum([ 10 * broadVioTm[(b.id,r)] for b in broadcastingwishes for r in rounds])
breakVioTotal=lpSum([prioVal[bl['prio']]*breakVio[(bl['id'],t)] for bl in breaks for t in realteams]) + 2*lpSum([prioVal[bl['prio']]*breakVio[(bl['id'],t)] for bl in breaks for t in importantteams])
break3VioTotal=lpSum([2*break3InRound[t,r] for t in teams for r in rounds])
tooManyTop4InRowTotal=lpSum([ 10*tooManyTop4InRow[(t,r)] for t in teams for r in rounds])
pairingVioTotal=lpSum([ 5 *prioVal[pair['prio']] * pairTagweight[pair['id']] * pairingVio[(pair['id'],d)] for pair in pairings for d in days+higherLeagueDayIds])
# blockingVioTotal=lpSum([ 100 * blockingVio[bl['id']] for bl in blockings if bl['type']=="Home"])
# print (blockings)    
# for bl in blockings: 
    # if bl['type'] in ["Home"]:
        # print (blocked_arena[(bl["team_id"],bl["day_id"],"----")], getTeamById[bl["team_id"]], getNiceDay[bl["day_id"]]  , bl )

fulfBlocks =set([(bl["team_id"], getRoundByDay[bl["day_id"]]) for bl in blockings if bl['type'] in ["Home"] and blocked_arena[(bl["team_id"],bl["day_id"],"----")]]  )

blockingVioTotal2=lpSum([ -30 * homeInRound[tr]  for tr in fulfBlocks if thisSeason.allowBlockingViosInImprove and runMode=='Improve'] ) 
blockingVioTotal=lpSum([ 100 * bl['weight']*blockingVio[bl['id']] for bl in blockings if bl['type'] in ["Home", "Hide","Game"]]) +blockingVioTotal2
goodHomesTotal=lpSum([ 100 * gh['weight']* home[gh['team_id'],gh['day_id']]for gh in goodHomes ]) 
travelVioTotal=lpSum([ 100 * blockingVio[bl['id']] for bl in blockings if bl['type']=="Away"])
gamesTooCloseTotal=lpSum([ 120 * gamesTooClose[(t,d)] for t in teams for d in days+higherLeagueDayIds if conflictDays[(t,d)]]) + lpSum([ 120 * gamesTooClose2[(t,r)] for t in teams for r in rounds ])
derbiesMissingTotal=lpSum([ 30 * derbyMissing[d] for d in days])
tooManyHomesInStadiumTotal=lpSum([ 110 * tooManyHomesInStadium[(stadium.id, d)] for stadium in stadiums for d in days+higherLeagueDayIds])
unpreferredTotal=lpSum([ home[t, d] for t in teams for d in days if dayHomePref[(t,d)]==0 ])
# competitionVioTotal=lpSum([ 100 * competitionVio[(c,d,t)] for (c,d,t) in competitions])
competitionVioTotal=lpSum([ 100 * (home[t,d]+ away[t,d]) for (t,d) in competitions.keys()])
fixedGameVioTotal=lpSum([ 10000 * fixedGameVio[(t1,t2,d)] for (t1,t2,d) in fixedGames]) + lpSum([ 10000 * fixedGame2Vio[(t1,t2,d)] for (t1,t2,d) in fixedGames2]) 
missingGamesVioTotal=lpSum([ 2000000 * missingGamesVio[(t1,t2)] for (t1,t2) in realgames])
# TODO -  UNDO CHANGES: missingGamesVioTotal=lpSum([ 2000 * missingGamesVio[(t1,t2)] for (t1,t2) in games])
oldScenGamesTotal=lpSum([ wg * x[t1,t2,rd] for (t1,t2,r,wg) in otherScenGames for rd in getRoundDaysByRound[r]] )
totalAttendance=lpSum([ attendance[(t1,t2,d)] * x[t1,t2,(r,d)] for (t1,t2) in games for (r,d) in roundDays ] )

specialObjectives = 0
specialWishItems ={ sw:[] for sw in special_wishes_active}
specialWishVio ={}


optCameraMovement = "Standard"
if  thisLeague.name in ["Indian Super League"] and thisSeason.name != "2021":
    optCameraMovement = "TV-Kits" 
# if  thisLeague.name in ["Indian Premier League"] and thisSeason.useFeatureBroadcasting:
#     optCameraMovement = "Stadiums" 

# tvkitproblem = {}
move2 = {}
newtrip2 = {}
if optCameraMovement == "TV-Kits": 
    networkIds=networkName.keys()    
    TV_day_pairs = [ (d1, d2) for d1 in days for d2 in days if getDateTimeDay[d1]+datetime.timedelta(days=1)<getDateTimeDay[d2]  and  getDateTimeDay[d1]>=getDateTimeDay[d2] -datetime.timedelta(days=20) ] 
    movements = [ (t1,d1,t2,d2)  for t1 in realteams for t2 in realteams for (d1,d2) in TV_day_pairs  if getDateTimeDay[d2]-getDateTimeDay[d1] >= datetime.timedelta(days=distanceInDaysById[(t1,t2)]+1 )  ]

    if thisLeague.name in ["Indian Super League"] and thisSeason.name not in ["2021", "2022"]:
        minDays = { ('Ben', 'Ben'): 0, ('Ben', 'Che'): 1, ('Ben', 'FC '):  2, ('Ben', 'Nor'): 12, ('Ben', 'Jam'):  6, ('Ben', 'Ker'): 3, ('Ben', 'Moh'): 6, ('Ben', 'Eas'): 6, ('Ben', 'Mum'): 3, ('Ben', 'Hyd'): 2, ('Ben', 'Odi'): 5, ('Ben', 'Pun'): 7,
                    ('Che', 'Ben'): 1, ('Che', 'Che'): 0, ('Che', 'FC '):  3, ('Che', 'Nor'): 11, ('Che', 'Jam'):  5, ('Che', 'Ker'): 3, ('Che', 'Moh'): 5, ('Che', 'Eas'): 5, ('Che', 'Mum'): 4, ('Che', 'Hyd'): 2, ('Che', 'Odi'): 4, ('Che', 'Pun'): 7,
                    ('FC ', 'Ben'): 2, ('FC ', 'Che'): 3, ('FC ', 'FC '):  0, ('FC ', 'Nor'): 14, ('FC ', 'Jam'):  7, ('FC ', 'Ker'): 3, ('FC ', 'Moh'): 7, ('FC ', 'Eas'): 7, ('FC ', 'Mum'): 2, ('FC ', 'Hyd'): 2, ('FC ', 'Odi'): 5, ('FC ', 'Pun'): 6,
                    ('Nor', 'Ben'): 12,('Nor', 'Che'): 11,('Nor', 'FC '): 14, ('Nor', 'Nor'):  0, ('Nor', 'Jam'):  5, ('Nor', 'Ker'): 14,('Nor', 'Moh'): 5, ('Nor', 'Eas'): 5, ('Nor', 'Mum'): 12, ('Nor', 'Hyd'): 10, ('Nor', 'Odi'): 6, ('Nor', 'Pun'): 8,
                    ('Jam', 'Ben'): 6, ('Jam', 'Che'): 5, ('Jam', 'FC '):  7, ('Jam', 'Nor'):  5, ('Jam', 'Jam'):  0, ('Jam', 'Ker'): 10, ('Jam', 'Moh'): 1, ('Jam', 'Eas'):1, ('Jam', 'Mum'): 6, ('Jam', 'Hyd'): 5, ('Jam', 'Odi'): 2, ('Jam', 'Pun'): 5,
                    ('Ker', 'Ben'): 3, ('Ker', 'Che'): 3, ('Ker', 'FC '):  3, ('Ker', 'Nor'): 14, ('Ker', 'Jam'): 10, ('Ker', 'Ker'): 0, ('Ker', 'Moh'): 10,('Ker', 'Eas'): 10, ('Ker', 'Mum'): 6, ('Ker', 'Hyd'): 5, ('Ker', 'Odi'): 8, ('Ker', 'Pun'): 11,
                    ('Moh', 'Ben'): 6, ('Moh', 'Che'): 5, ('Moh', 'FC '):  7, ('Moh', 'Nor'):  5, ('Moh', 'Jam'):  1, ('Moh', 'Ker'): 10, ('Moh', 'Moh'): 0, ('Moh', 'Eas'): 0, ('Moh', 'Mum'): 6, ('Moh', 'Hyd'): 5, ('Moh', 'Odi'): 2, ('Moh', 'Pun'): 5,
                    ('Eas', 'Ben'): 6, ('Eas', 'Che'): 5, ('Eas', 'FC '):  7, ('Eas', 'Nor'):  5, ('Eas', 'Jam'):  1, ('Eas', 'Ker'): 10, ('Eas', 'Moh'): 0, ('Eas', 'Eas'): 0, ('Eas', 'Mum'): 6, ('Eas', 'Hyd'): 5, ('Eas', 'Odi'): 2, ('Eas', 'Pun'): 5,
                    ('Mum', 'Ben'): 3, ('Mum', 'Che'): 4, ('Mum', 'FC '):  2, ('Mum', 'Nor'): 12, ('Mum', 'Jam'):  6, ('Mum', 'Ker'): 6, ('Mum', 'Moh'): 6, ('Mum', 'Eas'): 6, ('Mum', 'Mum'): 0, ('Mum', 'Hyd'): 3, ('Mum', 'Odi'): 5, ('Mum', 'Pun'): 5,
                    ('Hyd', 'Ben'): 2, ('Hyd', 'Che'): 2, ('Hyd', 'FC '):  2, ('Hyd', 'Nor'): 10, ('Hyd', 'Jam'):  5, ('Hyd', 'Ker'): 5, ('Hyd', 'Moh'): 5, ('Hyd', 'Eas'): 5, ('Hyd', 'Mum'): 3, ('Hyd', 'Hyd'): 0, ('Hyd', 'Odi'): 4, ('Hyd', 'Pun'): 5, 
                    ('Odi', 'Ben'): 5, ('Odi', 'Che'): 4, ('Odi', 'FC '):  5, ('Odi', 'Nor'):  6, ('Odi', 'Jam'):  2, ('Odi', 'Ker'): 8, ('Odi', 'Moh'): 2, ('Odi', 'Eas'): 2, ('Odi', 'Mum'): 5, ('Odi', 'Hyd'): 4, ('Odi', 'Odi'): 0, ('Odi', 'Pun'): 6,
                    ('Pun', 'Ben'): 7, ('Pun', 'Che'): 7, ('Pun', 'FC '):  6, ('Pun', 'Nor'):  8, ('Pun', 'Jam'):  5, ('Pun', 'Ker'): 11, ('Pun', 'Moh'): 5, ('Pun', 'Eas'): 5, ('Pun', 'Mum'): 5, ('Pun', 'Hyd'): 5, ('Pun', 'Odi'): 6, ('Pun', 'Pun'): 0,
                    }

        minDays = { (t1,t2) : minDays[(getTeamById[t1][:3],getTeamById[t2][:3])] for t1 in teams for t2 in teams  }
        movements = [(t1,d1,t2,d2) for (t1,d1,t2,d2) in movements if (((getDateTimeDay[d2]-getDateTimeDay[d1]).total_seconds()/(3600*24))-1) >= minDays[t1,t2]]

    pred2 ={ (t,d) :[] for t in realteams for d in days }
    succ2 ={ (t,d) :[] for t in realteams for d in days }
    move2 = { (t1,d1,t2,d2) : pulp.LpVariable('move2_'+str(t1)+'_'+str(d1)+'_'+str(t2)+'_'+str(d2),  lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for (t1,d1,t2,d2) in movements }
    unserved_tv = { (t1,d1) : pulp.LpVariable('unserved_tv'+str(t1)+'_'+str(d1),  lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in realteams for d1 in days  }
    newtrip2 = { (t1,d1) : pulp.LpVariable('newtrip2_'+str(t1)+'_'+str(d1),  lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in realteams for d1 in days  }
    tooManyTrips2 = pulp.LpVariable('tooManyTrips2',  lowBound = 0, cat = pulp.LpContinuous)

    for (t1,d1,t2,d2) in movements:
        # print (getTeamById[t1] , getTeamById[t2] , distanceById[t1,t2] , distanceInDaysById[t1,t2]  , getNiceDay[d1] , getNiceDay[d2]  )
        pred2[(t2,d2)].append( (t1,d1,t2,d2))
        succ2[(t1,d1)].append( (t1,d1,t2,d2))

    # if thisLeague.name in ["Indian Super League"]:
    #     for (t,d) in newtrip2.keys():
    #         # model2+= home[(t,d)] == lpSum( movement[tdtd] for tdtd in  pred2[(t,d)] ) 
    #         model2+= home[(t,d)] >= lpSum( move2[tdtd] for tdtd in succ2[(t,d)] ) 
    #         model2+= home[(t,d)] == lpSum( move2[tdtd] for tdtd in pred2[(t,d)] ) + newtrip2 [(t,d)] + unserved_tv[(t,d)]
    #         model2+= lpSum( move2[tdtd] for tdtd in move2.keys() if tdtd[0] == t and tdtd[1] == d) <= 1 - unserved_tv[(t,d)]
    #     model2+= lpSum( unserved_tv[k] for k in unserved_tv.keys()) <= 1
    #     model2+= tooManyTrips2 <= 0
    # else:
    for (t,d) in newtrip2.keys():
        # model2+= home[(t,d)] == lpSum( movement[tdtd] for tdtd in  pred2[(t,d)] ) 
        model2+= home[(t,d)] >= lpSum( move2[tdtd] for tdtd in succ2[(t,d)] ) 
        model2+= home[(t,d)] == lpSum( move2[tdtd] for tdtd in pred2[(t,d)] ) + newtrip2 [(t,d)]
    tv_phases = [ [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],[16,17,18,19,20,21,22]]
    for tvp in tv_phases:
        model2+= home[(t,d)] == lpSum( newtrip2[(t,d)] for (t,d) in newtrip2.keys() if getRoundByDay[d] in tvp ) <= len(networkIds) +  tooManyTrips2 

            # model2+= home[(t,d)] <= lpSum(home[(t2,d2)] for t2 in realteams for d2 in otherDays if  getDateTimeDay[d2]<=getDateTimeDay[d]- datetime.timedelta(days=distanceInDaysById[(t,t2)]) ) +tvkitproblem[(t,d)] 
    specialObjectives +=  0.01*lpSum( distanceById[t1,t2]*move2[(t1,d1,t2,d2)] for (t1,d1,t2,d2) in movements)+  100000* tooManyTrips2

jamshedpurVio={}
if thisLeague.name in ["Indian Super League"]:
    jamshedpur = getTeamByName["Jamshedpur FC"]['id'] 
    print ("Jamshedpur FC" , jamshedpur)
    jamshedpurVio = { d1  : pulp.LpVariable('jamshedpurVio_'+str(d1),  lowBound = 0, upBound = 1, cat = pulp.LpContinuous)  for d1 in days  }
    for d in days:
        fourdays = [d2 for d2 in days if getDateTimeDay[d2]>=getDateTimeDay[d] and  getDateTimeDay[d2]<=getDateTimeDay[d]+datetime.timedelta(days=3)  ]
        otherday = [d2 for d2 in fourdays if getDateTimeDay[d2]==getDateTimeDay[d]+datetime.timedelta(days=3)  ]
        if len(otherday)>0:
            otherday=otherday[0]
            print (getNiceDay[d], fourdays , getNiceDay[otherday] )
            for t in realteams:
                if t!=jamshedpur:
                    # model2+= lpSum( x[jamshedpur,t, rd] for d2 in fourdays for rd in getRoundDaysByDay[d2] ) + lpSum( home[t,d2] + away[t,d2] for d2 in fourdays )   <= 2  + jamshedpurVio[d]
                    model2+= lpSum( x[jamshedpur,t, rd] for rd in getRoundDaysByDay[d] )        +  home[t,otherday] + away[t,otherday] <= 1  + jamshedpurVio[d]
                    model2+= lpSum( x[jamshedpur,t, rd] for rd in getRoundDaysByDay[otherday] )  +  home[t,d]       + away[t,d]        <= 1  + jamshedpurVio[d] 
                else:
                    model2+= home[t,d] + away[t,otherday]  <= 1  + jamshedpurVio[d]
                    model2+= away[t,d] + home[t,otherday]  <= 1  + jamshedpurVio[d]

    specialObjectives +=  1000*lpSum( jamshedpurVio[d] for d in days)

    


if "AlwaysEnoughRestDays" in special_wishes_active:
    model2+=lpSum([ gamesTooClose[(t,d)] for t in teams for d in days if conflictDays[(t,d)]]) ==0 

if "NoPairingVio" in special_wishes_active:
    # model2+=pairingVioTotal==0
    hardpairs = [ p for p in pairings  if p['prio']=="Hard" ]
    if len(hardpairs)>0:
        model2+=lpSum([ pairingVio[(pair['id'],d)] for pair in pairings for d in days+higherLeagueDayIds if pair['prio']=="Hard"])==0

if "NoBreaks" in special_wishes_active:
    model2+=breakVioTotal==0

if "SyncDaysInGroups" in special_wishes_active:
    for (t1,t2) in games:
        for d in days:
            model2+= home[(t1,d)]+away[(t1,d)]  ==  home[(t2,d)]+away[(t2,d)]  

if "austrianSymmetry" in special_wishes_active:
    for (t1,t2) in games:
        if (t2,t1) in games:
            for (r1,r2) in [(1,7),(2,8),(3,9),(4,10),(5,6)] :
                model2+= lpSum([x[t1,t2, rd] for rd in getRoundDaysByRound[r1]]) ==  lpSum([x[t2,t1, rd] for rd in getRoundDaysByRound[r2]])


# if "3RestDaysBetweenMD2andMD3" in special_wishes_active:
#     print ("3RestDaysBetweenMD2andMD3")
#     sw_type="3RestDaysBetweenMD2andMD3"
#     # for  (r2,d2) in  getRoundDaysByRound[2] :
#     #     for (r3,d3) in  getRoundDaysByRound[3]
#     #         print (getDateTimeDay[d2],getDateTimeDay[d3])
#     dpairs = [(d2, d3) for  (r2,d2) in  getRoundDaysByRound[2] for (r3,d3) in  getRoundDaysByRound[3] if getDateTimeDay[d3]-getDateTimeDay[d2]== datetime.timedelta(days=sw_int1[sw_type]+1) ]
#     for (d2,d3) in dpairs: 
#         for t in realteams: 
#             model2 += home[(t,d2)]+away[(t,d2)]==home[(t,d3)] +away[(t,d3)]
#         print (getDateTimeDay[d2],getDateTimeDay[d3])
#     

if thisSeason.useFeatureStadiums:
    stadium_teams = [ t for t in realteams if len(getStadiumsByTeam[t])>0 ]
    playInStadium = { (t,d,sp.stadium.id) : pulp.LpVariable('playInStadium_'+str(t)+'_'+str(d)+'_'+str(sp.stadium.id), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t in stadium_teams for d in days for sp in getStadiumsByTeam[t] }

    for d in days :
        for t in stadium_teams:
            print ([ playInStadium[t,d,sp.stadium.id] for sp in getStadiumsByTeam[t] ])
            model2+=lpSum([ playInStadium[t,d,sp.stadium.id] for sp in getStadiumsByTeam[t] ])== home[(t,d)]
        for s in stadiums:
            print ([ playInStadium[t,d,sp.stadium.id] for sp in getStadiumsByTeam[t] ])
            model2+=lpSum([ playInStadium[sp.team.id,d,s.id] for sp in s.stadiumpreferences.all() ]) <= getStadiumAvailability[(s.id,d)] +tooManyHomesInStadium[(s.id,d)]

    specialObjectives += -1 *lpSum([ prioVal[sp.prio]* playInStadium[t,d,sp.stadium.id] for t in stadium_teams for d in days for sp in getStadiumsByTeam[t] ])

print (special_wishes_active)

if "minHomeAttractivity" in special_wishes_active:
    # showAttractivity =  min([d.attractivity for d in days]) < max([d.attractivity for d in days]) 
    sw_type="minHomeAttractivity"
    for t in realteams: 
        specialWishItems[sw_type].append((t))
        specialWishVio[(sw_type,t)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t), lowBound=0, cat=pulp.LpContinuous)
        model2 += lpSum([ home[t,d]*getDayById[d]['attractivity'] for d in days ]) >= sw_int1[sw_type] - specialWishVio[(sw_type,t)]            
    specialObjectives += lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t)] for t in realteams ])

if "alwaysFixedRestDaysWhenPossible" in special_wishes_active:
    print ("alwaysFixedRestDaysWhenPossible")
    sw_type="alwaysFixedRestDaysWhenPossible"
    dpairs=[]
    for r in rounds:
        if r<nRounds:
            dpairs += [(d2, d3) for  (r2,d2) in  getRoundDaysByRound[r] for (r3,d3) in  getRoundDaysByRound[r+1] if getDateTimeDay[d3]-getDateTimeDay[d2]== datetime.timedelta(days=sw_int1[sw_type]+1) ]
    for (d2,d3) in dpairs: 
        print ("found days " , getNiceDay[d2],  getNiceDay[d3], )
        for t in realteams: 
            specialWishItems[sw_type].append((t,d2))
            specialWishVio[(sw_type,t,d2)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d2), lowBound=0, cat=pulp.LpContinuous)
            model2 += home[(t,d2)]+away[(t,d2)] <= home[(t,d3)] +away[(t,d3)] + specialWishVio[(sw_type,t,d2)]
            model2 += home[(t,d3)]+away[(t,d3)] <= home[(t,d2)] +away[(t,d2)] + specialWishVio[(sw_type,t,d2)]
        # print (getDateTimeDay[d2],getDateTimeDay[d3])
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])
    
if "numAfricanTripsToEurope" in special_wishes_active:
    print ("numAfricanTripsToEurope")
    sw_type="numAfricanTripsToEurope"
    european_teams = [t for t in realteams if t_lat[t] >= 0]
    african_teams = [t for t in realteams if t_lat[t] < 0]
    alwaysTripStarterRounds = [1,8,10,11,12,14,16,18]

    # print ("european_teams", european_teams)
    # print ("african_teams", african_teams)

    europeanTripStarter = { (t,r) : pulp.LpVariable('europeanTripStarter_'+str(t)+'_'+str(r),  lowBound = 0, upBound = 1, cat = pulp.LpContinuous)  for t in african_teams for r in rounds }
    for t in african_teams: 
        # print ("BUILD CONSTRAINT FOR " , getTeamById[t])
        for mm in ["min","max"]:
            specialWishItems[sw_type].append((t,mm))
            specialWishVio[(sw_type,t,mm)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+'_'+mm, lowBound=0, cat=pulp.LpContinuous)

        for r in rounds: 
            if r in alwaysTripStarterRounds:
                model2 +=  lpSum([ x[t1,t,rd] for t1 in european_teams for rd in getRoundDaysByRound[r]])  == europeanTripStarter[t,r]
                # print (r, lpSum([ x[t1,t,rd] for t1 in european_teams for rd in getRoundDaysByRound[r]]))
            else:
                model2 +=  lpSum([ x[t1,t,rd] for t1 in european_teams for rd in getRoundDaysByRound[r]]) \
                            - lpSum([ x[t1,t,rd] for t1 in european_teams for rd in getRoundDaysByRound[r-1]]) <= europeanTripStarter[t,r]
                model2 +=  europeanTripStarter[t,r] <= lpSum([ x[t1,t,rd] for t1 in european_teams for rd in getRoundDaysByRound[r]])  
                model2 +=  europeanTripStarter[t,r] <= 1-lpSum([ x[t1,t,rd] for t1 in european_teams for rd in getRoundDaysByRound[r-1]]) 
        model2 += lpSum([ europeanTripStarter[t,r] for r in rounds ])  <= sw_int1[sw_type] + specialWishVio[(sw_type,t,"max")]
        model2 += lpSum([ europeanTripStarter[t,r] for r in rounds ])  >= sw_int2[sw_type] - specialWishVio[(sw_type,t,"min")]
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,mm)] for (t,mm) in specialWishItems[sw_type] ])
    
            
if "RecoverBeforeDistantGame" in special_wishes_active:
    sw_type="RecoverBeforeDistantGame"
    distantTeams = { t: [ t2 for t2 in realteams if distanceById[t,t2]> sw_int1[sw_type] and t2!=t] for t in realteams } 
    for d in days:
        nextDays = [ d2 for d2 in days if getDateTimeDay[d]<getDateTimeDay[d2] and getDateTimeDay[d2]-getDateTimeDay[d]<= datetime.timedelta(days=sw_int2[sw_type]) ]
        # print (d, nextDays )
        if len(nextDays)>0:
            specialWishItems[sw_type]+=[(t,d) for t in realteams]
            for t in realteams:
                # print ("\n",getTeamById[t], ":", [ (getTeamById[t2] ,  distanceById[t,t2]) for t2 in distantTeams[t] ])
                specialWishVio[(sw_type,t,d)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
                model2+= home[(t,d)] + lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for d2 in nextDays for rd in getRoundDaysByDay[d2] ]) <= 1 + specialWishVio[(sw_type,t,d)]  
                # print ("GAMES :", lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for rd in getRoundDaysByDay[d] ]))
                # print ("HOMES :", lpSum([ home[(t,d2)] for d2 in nextDays]))
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])
                    
if "RecoverAfterDistantGame" in special_wishes_active:
    sw_type="RecoverAfterDistantGame"
    distantTeams = { t: [ t2 for t2 in realteams if distanceById[t,t2]> sw_int1[sw_type] and t2!=t] for t in realteams } 
    for d in days:
        nextDays = [ d2 for d2 in days if getDateTimeDay[d]<getDateTimeDay[d2] and getDateTimeDay[d2]-getDateTimeDay[d]<= datetime.timedelta(days=sw_int2[sw_type]) ]
        # print (d, nextDays )
        # if len(nextDays)>0 and (thisSeason.league.name != "ICE Hockey League" or getWeekDay[d]=="Fri" ):
        if len(nextDays)>0:
            specialWishItems[sw_type]+=[(t,d) for t in realteams]
            for t in realteams:
                # print ("\n",getTeamById[t], ":", [ (getTeamById[t2] ,  distanceById[t,t2]) for t2 in distantTeams[t] ])
                specialWishVio[(sw_type,t,d)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
                model2+= lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for rd in getRoundDaysByDay[d] ]) + lpSum([ home[(t,d2)] for d2 in nextDays]) <= 1 + specialWishVio[(sw_type,t,d)]  
                # print ("GAMES :", lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for rd in getRoundDaysByDay[d] ]))
                # print ("HOMES :", lpSum([ home[(t,d2)] for d2 in nextDays]))
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])
                    
if "RecoverAfterDistantGame2" in special_wishes_active:
    sw_type="RecoverAfterDistantGame2"
    distantTeams = { t: [ t2 for t2 in realteams if distanceById[t,t2]> sw_int1[sw_type] and t2!=t] for t in realteams } 
    for d in days:
        nextDays = [ d2 for d2 in days if getDateTimeDay[d]<getDateTimeDay[d2] and getDateTimeDay[d2]-getDateTimeDay[d]<= datetime.timedelta(days=sw_int2[sw_type]) ]
        # print (d, nextDays )
        # if len(nextDays)>0 and (thisSeason.league.name != "ICE Hockey League" or getWeekDay[d]=="Fri" ):
        if len(nextDays)>0:
            specialWishItems[sw_type]+=[(t,d) for t in realteams]
            for t in realteams:
                # print ("\n",getTeamById[t], ":", [ (getTeamById[t2] ,  distanceById[t,t2]) for t2 in distantTeams[t] ])
                specialWishVio[(sw_type,t,d)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
                model2+= lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for rd in getRoundDaysByDay[d] ]) + lpSum([ home[(t,d2)] for d2 in nextDays]) <= 1 + specialWishVio[(sw_type,t,d)]  
                # print ("GAMES :", lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for rd in getRoundDaysByDay[d] ]))
                # print ("HOMES :", lpSum([ home[(t,d2)] for d2 in nextDays]))
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])
                    
if "NoSingleDistantGame" in special_wishes_active:
    sw_type="NoSingleDistantGame"
    distantTeams = { t: [ t2 for t2 in realteams if distanceById[t,t2]> sw_int1[sw_type] and t2!=t] for t in realteams } 
    for d in days:
        otherDays = [ d2 for d2 in days if d!=d2 and getDateTimeDay[d2]-getDateTimeDay[d]<= datetime.timedelta(days=sw_int2[sw_type]-1) and getDateTimeDay[d]-getDateTimeDay[d2]<= datetime.timedelta(days=sw_int2[sw_type]-1) ]
        if len(otherDays)>0:
            specialWishItems[sw_type]+=[(t,d) for t in realteams]
            for t in realteams:
                specialWishVio[(sw_type,t,d)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
                model2+= lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for rd in getRoundDaysByDay[d] ]) - lpSum([ x[t1,t,rd] for t1 in distantTeams[t] for d2 in otherDays for rd in getRoundDaysByDay[d2] ])  <=  specialWishVio[(sw_type,t,d)]  
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])
    # # print (specialObjectives)

if "halfSeasonNumGames" in special_wishes_active:
    sw_type="halfSeasonNumGames"
    specialWishItems[sw_type]=days
    sw_nGames = sum([ gameCntr[gm]+0.5*undirectedGameCntr[gm] for gm in games])
    specialIn2ndHalf={}
    for d in days:
        # variable is 1 if day belongs to second half 
        sw_days_before = [ d2 for d2 in days if getDateTimeDay[d2]<getDateTimeDay[d]]
        sw_days_after = [ d2 for d2 in days if getDateTimeDay[d2]>getDateTimeDay[d]]
        specialIn2ndHalf[(d)]= pulp.LpVariable('specialIn2ndHalf_'+str(d), lowBound=0, upBound=1, cat=pulp.LpInteger)
        specialWishVio[(sw_type,d)]= pulp.LpVariable('specialWishVio_'+sw_type+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
        sw_gamesSoFar = lpSum([ home[(t,d2)] for t in teams for d2 in sw_days_before])
        sw_gamesAfter = lpSum([ home[(t,d2)] for t in teams for d2 in sw_days_after])
        if len(sw_gamesSoFar) <= 0.5* len(sw_gamesAfter):
            specialIn2ndHalf[d]=0
        elif len(sw_gamesAfter) <= 0.5* len(sw_gamesSoFar):
            specialIn2ndHalf[d]=1
        else:
            specialIn2ndHalf[(d)]= pulp.LpVariable('specialIn2ndHalf_'+str(d), lowBound=0, upBound=1, cat=pulp.LpInteger)
            model2+= specialIn2ndHalf[sw_days_before[-1]] <=  specialIn2ndHalf[d]

        model2+=  sw_gamesAfter >= 0.5*sw_nGames*(1-specialIn2ndHalf[d]) - specialWishVio[(sw_type,d)]
        model2+=  sw_gamesSoFar >= 0.5*sw_nGames*(specialIn2ndHalf[d])- specialWishVio[(sw_type,d)]
        for t in teams:
            sw_home_before = lpSum([ home[(t,d2)] for d2 in sw_days_before])
            sw_away_before = lpSum([ away[(t,d2)] for d2 in sw_days_before])
            sw_home_after  = lpSum([ home[(t,d2)] for d2 in sw_days_after])
            sw_away_after  = lpSum([ away[(t,d2)] for d2 in sw_days_after])
            model2+=  sw_home_after+sw_away_after >= sw_int1[sw_type]*(1-specialIn2ndHalf[d]) - 5*specialWishVio[(sw_type,d)]
            model2+=  sw_home_after >= sw_int2[sw_type]*(1-specialIn2ndHalf[d]) - 5*specialWishVio[(sw_type,d)]
            model2+=  sw_home_before+sw_away_before >= sw_int1[sw_type]*(specialIn2ndHalf[d]) - 5*specialWishVio[(sw_type,d)]
            model2+=  sw_home_before >= sw_int2[sw_type]*(specialIn2ndHalf[d]) - 5*specialWishVio[(sw_type,d)]

    specialObjectives += 10000*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,d)] for d in specialWishItems[sw_type] ])

if "RestDaysAfterLateGame" in special_wishes_active:
    sw_type="RestDaysAfterLateGame"
    for d in days:
        nextDays = [ d2 for d2 in days if getDateTimeDay[d]<getDateTimeDay[d2] and getDateTimeDay[d2]-getDateTimeDay[d]<= datetime.timedelta(days=sw_int1[sw_type]) ]
        # print (d, nextDays )
        if len(nextDays)>0:
            specialWishItems[sw_type]+=[(t,d) for t in realteams]
            for t in realteams:
                specialWishVio[(sw_type,t,d)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
                model2+= home_time[(t,d,getIdByTime["Late"])]+away_time[(t,d,getIdByTime["Late"])]  + lpSum([ home[(t,d2)]+away[(t,d2)] for d2 in nextDays]) <= 1 + specialWishVio[(sw_type,t,d)]  
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])
    # print (specialObjectives)
    

if "EveryPotOnceAtHome" in special_wishes_active:
    pots=sorted(list(set(t_pot[t] for t in realteams)))
    for t in realteams:
        for p in pots:
            model2+= lpSum([ x[t,t2,rd] for t2 in realteams for rd in roundDays if t_pot[t2] == p] ) <= 1  
            # print ( getTeamById[t] , "pot", p , ":", lpSum([ x[t,t2,rd] for t2 in realteams for rd in roundDays if t_pot[t2] == p] ) , " <= 1 " )
    
if "playWeekendsCompletelyHomeOrAway" in special_wishes_active:
    sw_type="playWeekendsCompletelyHomeOrAway"        
    weekendDays = [d for d in days if getWeekDay[d] in ["Fri"]]
    specialHomeAwayOnWeekend={}
    for d in weekendDays:
        nextDays = [ d2 for d2 in days if getDateTimeDay[d]<getDateTimeDay[d2] and getDateTimeDay[d2]-getDateTimeDay[d]<= datetime.timedelta(days=2) ]
        specialWishItems[sw_type]+=[(t,d) for t in realteams]
        for t in realteams:
            specialWishVio[(sw_type,t,d)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
            for ha in ["Home", "Away"] :
                specialHomeAwayOnWeekend[(t,d,ha)]= pulp.LpVariable('specialHomeAwayOnWeekend_'+ha+'_'+str(t)+"_"+str(d), lowBound=0, cat=pulp.LpContinuous)
            for d2 in [d]+nextDays:
                model2+= home[(t,d2)] <= specialHomeAwayOnWeekend[(t,d,"Home")]
                model2+= away[(t,d2)] <= specialHomeAwayOnWeekend[(t,d,"Away")]
            model2+= specialHomeAwayOnWeekend[(t,d,"Home")]+specialHomeAwayOnWeekend[(t,d,"Away")]<=1+specialWishVio[(sw_type,t,d)]
    specialObjectives += 10*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t,d)] for (t,d) in specialWishItems[sw_type] ])

if "alternateHAforSameEncounters" in special_wishes_active:
    sw_type="alternateHAforSameEncounters"
    for p in phases:                
        if p>0:
            relrd =[ rd for d in getDaysOfPhase[p-1]+getDaysOfPhase[p]  for rd in getRoundDaysByDay[d]]
            for (t1,t2) in games:                
                model2+=  lpSum( x[(t1,t2,rd)] for rd in relrd ) <= 1

standardObjectives=1+gew['Home-/Away']*HawVioTotal\
        +gew['Home-/Away']*3*unpreferredTotal \
        +gew['Pairings']*pairingVioTotal \
        +gew['Availabilities']*blockingVioTotal \
        +gew['Availabilities']*goodHomesTotal \
        +gew['Availabilities']*travelVioTotal \
        +gew['Availabilities']*gamesTooCloseTotal \
        -5*gew['Trips']*tripSavedTotal2 \
        +gew['Breaks']*breakVioTotal \
        +gew['Breaks']*2*break3VioTotal \
        +gew['Breaks']*1*breakImbalanceTotal \
        +5*gew['Encounters']*encVioTotal \
        +5*gew['Encounters']*seedVioTotal \
        +gew['Conferences']*confVioTotal  \
        +gew['Availabilities']*tooManyHomesInStadiumTotal \
        +gew['Broadcasting']*broadVioTotal \
        +gew['Derbies']*derbiesMissingTotal \
        +5*competitionVioTotal \
        +1.0*tooManyTop4InRowTotal\
        +fixedGameVioTotal\
        +missingGamesVioTotal\
        +oldScenGamesTotal\
        -0.01*totalAttendance 

if sharedStadiums:
    standardObjectives+= lpSum ( prio_weight[p] * useStadiumTimeSlot[(t,d,s)]  for (t,d) in t_site_bestTimeSlots.keys() for (p,s) in t_site_bestTimeSlots[(t,d)]) \
                        +100000* lpSum([ nonIceGame[(t,d)] for (t,d) in nonIceGame.keys()]) 


model2+= standardObjectives 

# model2+= fixedGameVioTotal +missingGamesVioTotal
# model2+= fixedGameVioTotal 
# print ("TESTING")
# for ttr in x.keys():
#     makeIntVar(x[ttr])
# model2.solve(GUROBI(MIPGap=0.0, TimeLimit=40,msg=1))
# print ("TESTING DONE")


global_coeff = {t['id'] : int(t['attractivity'])  for t in teamObjects }
domestic_coeff = {t['id'] : int(0.1+10*(t['attractivity']-int(t['attractivity']))) for t in teamObjects }

def quality_of_game(t1, t2):
    return global_coeff[t1]*global_coeff[t2]

def quality_of_game_dom(t1, t2 , country):
    if t_country[t1]==country:
        return domestic_coeff[t1]*global_coeff[t2]
    else:
        return global_coeff[t1]*domestic_coeff[t2]


print ("Broadcasting " , gew['Broadcasting'])

if thisSeason.useFeatureBackToBack:
    critical_day_pairs = [ (d1,d2) for r in [r1 for r1 in rounds if r1>1] for d1 in getDays[r-1] for d2 in getDays[r] if getDateTimeDay[d2]-getDateTimeDay[d1]==datetime.timedelta(days=1) ]
    nextCritical ={ d1 : False for d1 in days}
    for (d1,d2) in critical_day_pairs:
        nextCritical[d1]=d2

    badBackToBack= { (t,d1) : pulp.LpVariable('badBackToBack_'+str(t)+"_"+str(d1) , lowBound = 0, cat = pulp.LpContinuous) for t in teams for (d1,d2) in critical_day_pairs }
    back2backBlocks = []
    color_weight = { "Y" : 0.003 ,  "R" : 0.05 ,  "X" : 1.0 , }


show_TV_markets = False

# START SPECIAL CONSTRAINTS

# hat leider nicht geklappt :
# specialOpt = False
# optFileName = "optimize_" + thisSeason.league.name.replace(' ', '_')
# if path.exists("scheduler/"+optFileName+".py"):
#     specialOpt = import_module('scheduler.'+optFileName)

# if specialOpt:
#     specialOpt.enhanceModel2(model2) 
# with open("scheduler/"+optFileName+".py") as f: exec(f.read())

if mathModelName=="NHL":
    startDoubleGame= { (t1,t2,r) : pulp.LpVariable('startDoubleGame'+str(t1)+"_"+str(t2)+"_"+str(r) , lowBound = 0,  cat = pulp.LpContinuous) for (t1,t2)  in games for r in rounds if r<nRounds }

    bad_travels = [ (t1,t2,"X") for t1 in realteams for t2 in realteams if distanceById[t1,t2]>1300]
    # print (bad_travels)
    # for (t1,t2,c) in bad_travels:
    #     print (getTeamById[t1] , " - " , getTeamById[t2])

    # print(thisSeason.name[-3:])

    thisCountry =""
    for t in realteams:
        thisCountry=t_country[t]  
    #     print (getTeamById[t], t_country[t] , t_conference[t])
    # print (thisCountry)

    for (t1,t2,r) in startDoubleGame.keys():
        model2 += startDoubleGame[(t1,t2,r)] <= x_round[(t1,t2,r)]
        model2 += startDoubleGame[(t1,t2,r)] <= x_round[(t1,t2,r+1)]
    
    specialObjectives+= -100* lpSum( [ startDoubleGame[ttr] for ttr in startDoubleGame.keys()])   

    if thisCountry=="United States":
        for (t1,t2) in games:
            for r in rounds:
                if r>=3:
                    model2 += x_round[(t1,t2,r-2)]+x_round[(t1,t2,r-1)]+x_round[(t1,t2,r)]<=2
                    # print ("no 3 in row " , t1, t2, r-2 , r)

        bad_travels = [ (t1,t2,"X") for t1 in realteams for t2 in realteams if distanceById[t1,t2]>1300 and t_conference[t1]==t_conference[t2]]
        # print (len(bad_travels))
        # for (t1,t2,c) in bad_travels:
        #     print (getTeamById[t1] , " - " , getTeamById[t2])

        back2backBlocks += [ ([t1],[t2],1.0)  for (t1,t2,c) in bad_travels]    

        contractable=True
        while contractable:
            contractable=False
            for ((tms1_a,tms2_a,w_a),(tms1_b,tms2_b,w_b)) in [ (b1,b2) for b1 in back2backBlocks for b2 in back2backBlocks if b1!=b2 and b1[2]==b2[2] and t_conference[b1[0][0]]==t_conference[b2[0][0]] ]:
                if min([ distanceById[t1,t2] for t1 in tms1_a for t2 in tms2_b]) > 1300 and min([ distanceById[t1,t2] for t1 in tms1_b for t2 in tms2_a]) > 1300 :
                    # print ("unify ", b1,b2)
                    back2backBlocks.remove((tms1_a,tms2_a,w_a))
                    back2backBlocks.remove((tms1_b,tms2_b,w_b))
                    back2backBlocks.append((list(set(tms1_a+tms1_b)), list(set(tms2_a+tms2_b)), w_a))
                    contractable=True
                    break;

        # print (len(back2backBlocks)," back2backBlocks")
        # for (tms1,tms2,w) in back2backBlocks:
        #     print ("")
        #     print (tms1,tms2,w)
        #     for t1 in set(tms1):
        #         print ("from ", getTeamById[t1])
        #     for t2 in set(tms2):
        #         print ("to ", getTeamById[t2])
        # print (len(bad_travels), "bad_travels")
        # print (len(back2backBlocks),"back2backBlocks")

    else:    
        # startDoubleGame 
        for r in rounds:
            if r>=5:
                for (t1,t2) in games:
                    if gameCntr[(t2,t1)]>0 : 
                        model2 += lpSum(x_round[(t1,t2,r2)] + x_round[(t2,t1,r2)] for r2 in [r-4,r-3,r-2,r-1,r])<=3
                    else:
                        model2 += lpSum(x_round[(t1,t2,r2)] for r2 in [r-4,r-3,r-2,r-1,r])<=3
                # if r>2 and r <10:
                #     model2 += x_round[(t1,t2,r-1)] <= x_round[(t1,t2,r-2)] + x_round[(t1,t2,r)]

            if r>=9:
                for t1 in teams : 
                    model2 += lpSum(homeInRound[(t1,r2)] for r2 in rounds if r2>=r-8 and r2<=r)>=1
                    model2 += lpSum(awayInRound[(t1,r2)] for r2 in rounds if r2>=r-8 and r2<=r)>=1

        east_teams = [ t for t in realteams     if                      t_lon[t]>= -87]
        center_teams = [ t for t in realteams   if  -87 > t_lon[t] and t_lon[t]>=-100 ]
        west_teams = [ t for t in realteams if t_lon[t]< -113]
        back2backBlocks += [ (east_teams, center_teams+west_teams,1.0), (center_teams+west_teams,east_teams,1.0) ]


if mathModelName=="Champions Hockey League":
    show_TV_markets = True
    # toTime={(c,d) : ["n/a"] for c in countries for d in days}
    # for d in days:
    #     for (c,tms) in [ ("SWE", ["18:05/19:05","20:35"]), ("FIN",["19:00"]), 
    #                      ("CZE",["17:00 or 17:30", "19:30 or 20:00"]),  ("SVK",["17:00 or 17:30", "19:30 or 20:00"]),
    #                      ("HUN" , ["19:00"]),
    #                      ("AUT",["20:20"]), 
    #                      ("SUI",["19:45"]),
    #                      ("GER",["18:00"]), 
    #                      ("NOR",["18:00"]), 
    #                      ("DEN",["18:00"]), 
    #                      ("POL",["18:00"]), 
    #                      ("SLO",["19:15"]), 
    #                      ("FRA",["20:00"]), 
    #                      ("SCO",["20:00 or 20:30"]),
    #                      ]:
    #         toTime[(c,d)]=tms

    #     for (cntries,nds,tms) in   [ 
    #             (["SWE"],["2022-09-03","2022-09-04"],["14:35","15:05"]),
    #             (["CZE","SVK"],["2022-09-03","2022-09-04"],["16:00","18:30"]),
    #             (["CZE","SVK"],["2022-09-10"],["15:00 or 16:00","17:30 or 18:30"]),
    #             (["CZE","SVK"],["2022-09-11",],["15:00 or 16:00","18:30"]),
    #             (["HUN"],["2022-09-03","2022-09-04","2022-09-10","2022-09-11"],["18:00"]),
    #             (["AUT"],["2022-09-02"],["19:30"]),(["AUT"],["2022-09-09"],["18:00"]),
    #             (["SUI"],["2022-09-01"],["20:00"]),
    #             (["SUI"],["2022-09-03","2022-09-10"],["14:30/15:00"]),
    #             (["SUI"],["2022-09-04","2022-09-11"],["16:30"]),
    #             (["GER"],["2022-09-01","2022-09-02",],["20:15"]),
    #             (["GER"],["2022-09-03","2022-09-10",],["17:00"]),
    #             (["GER"],["2022-09-04",],["15:00 or 19:00"]),
    #             (["GER"],["2022-09-08",],["19:00","20:00"]),
    #             (["GER"],["2022-09-09",],["16:45"]),
    #             (["GER"],["2022-09-11",],["?"]),
    #             (["NOR"],["2022-09-08"],["no pref."]),
    #             (["NOR"],["2022-10-04","2022-10-05","2022-10-10","2022-10-11",],["18:30"]),
    #             (["DEN"],["2022-09-02","2022-09-09",],["19:30"]),
    #             (["DEN"],["2022-09-08"],["no pref."]),
    #             (["SLO"],["2022-09-08"],["20:00"]),
    #             (["SLO"],["2022-09-03"],["18:00"]),
    #             (["SLO"],["2022-09-04"],["17:30"]),
    #             (["SLO"],["2022-09-08","2022-09-09",],["18:00 or 20:00"]),
    #             (["SLO"],["2022-09-10","2022-09-11",],["18:00"]),
    #              ]  :
    #         if getNiceDayRaw[d] in nds: 
    #             for c in cntries:
    #                 toTime[(c,d)]=tms
    #         else:
    #             print (getNiceDayRaw[d], nds, getNiceDayRaw[d] in nds)

    # critical_day_pairs_CHL = [ (d1,d2)  for d1 in set(getDays[1]+getDays[3]) for d2 in set(getDays[2]+getDays[4]) if getDateTimeDay[d2]-getDateTimeDay[d1]==datetime.timedelta(days=2) ]

    # confusingDays = [ d for d in getDays[1]+getDays[2] if d in getDays[3]+getDays[4]] 
    # for (t1,t2) in games: 
        # print (getTeamById[t1], "  " ,getTeamById[t2], lpSum([ x[(t1,t2,rd)] for r2 in [1,2,3] for rd in getRoundDaysByRound[r2]]) )
        # model2+= lpSum([ x[(t1,t2,rd)] + x[(t2,t1,rd)]  for r2 in [1,2,3] for rd in getRoundDaysByRound[r2]]) <= 1 
        # model2+= lpSum([ x[(t1,t2,rd)] + x[(t2,t1,rd)]  for r2 in [4,5,6] for rd in getRoundDaysByRound[r2]]) <= 1 

        # for d in confusingDays:
        #     rnds = [1,2] if t_pot[t]!=5 else [3,4]
        #     for r2 in rnds:
        #         if (r2,d) in roundDays:
        #             setUB(x[(t1,t2,(r2,d))],0)
        #             # print ("forbidding " ,r2 ,d, " on day " , getNiceDay[d])
        

    # for t in teams : 
    #     # model2+= lpSum([ home[(t,d1)] + away[t,d1] for d1 in confusingDays ]) == 2 
    #     for (d1,d2) in critical_day_pairs_CHL:                 
    #         model2 += home[(t,d1)]==home[(t,d2)] 
    #         model2 += away[(t,d1)]==away[(t,d2)] 
    #         # model2 += homeInRound[(t1,1)] == homeInRound[(t1,2)] 


if mathModelName=="Florida State League":
    notEnoughHomes= { t : pulp.LpVariable('notEnoughHomes_'+str(t) , lowBound = 0, cat = pulp.LpContinuous) for t in teams }
    notEnoughAways= { t : pulp.LpVariable('notEnoughAways_'+str(t) , lowBound = 0, cat = pulp.LpContinuous) for t in teams }
    for t in teams:
        # model2+= lpSum( [ homeInRound[t,r] for r in rounds]) >= 20
        model2+= lpSum( [ home[t,d] for d in days]) >= 70 - notEnoughHomes[t]
        model2+= lpSum( [ away[t,d] for d in days]) >= 70 - notEnoughAways[t]
        model2+= lpSum( [ home[t,d] for d in days]) <= 70 + notEnoughHomes[t]
        model2+= lpSum( [ away[t,d] for d in days]) <= 70 + notEnoughAways[t]
        # print ("doing special stuff ", thisSeason.gamesPerRound=="one day")


    getConference={}
    for c in confTeams.keys():
        if len(confTeams[c])>2:
            for t in confTeams[c]:
                getConference[t]=c

    visited_unbalanced_MINLB= {(t1,t2) : pulp.LpVariable('visited_too_less_'+str(t1)+'_'+str(t2), lowBound = 0, cat = pulp.LpContinuous) for (t1,t2) in games }
    for (t1,t2) in games:
        # print (t1 , t2, getRoundDaysByRound[1][0], distance[getTeamById[t1],getTeamById[t2]] , getConference[t1]==getConference[t2] )
        model2+= lpSum([x[(t1,t2,getRoundDaysByRound[r][0])] for r in rounds]) >=1
        model2+= lpSum([x[(t1,t2,getRoundDaysByRound[r][0])] for r in rounds]) >=2- visited_unbalanced_MINLB[(t1,t2)]
        model2+= lpSum([x[(t1,t2,getRoundDaysByRound[r][0])] for r in rounds]) <=3+ visited_unbalanced_MINLB[(t1,t2)]
    # exit(0)

    # model2+= x[(13859,13860,(1, 26627))] >=1

    # for r in rounds:
    #     print (r, getRoundDaysByRound[r] ,  len(getRoundDaysByRound[r]))

    # visited_too_less_MINLB=   { (t1,t2) : not_visited * x[(t1,t2,getRoundDaysByRound[r][0])]  for (t1,t2) in games }
    travelCost_Driving_MINLB= { (t1,t2,r) : distance[getTeamById[t1],getTeamById[t2]] * x[(t1,t2,getRoundDaysByRound[r][0])]  for (t1,t2) in games for r in rounds }
    travelCost_Hotel_MINLB  = { (t1,t2,r) : len(getRoundDaysByRound[r]) * (getConference[t1]!=getConference[t2]) * x[(t1,t2,getRoundDaysByRound[r][0])]  for (t1,t2) in games for r in rounds }

    travelCost_Total_MINLB  = lpSum([0.001*travelCost_Driving_MINLB[(t1,t2,r)]+0.2*travelCost_Hotel_MINLB[(t1,t2,r)]  for (t1,t2) in games for r in rounds])

    total_visited_unbalanced_MINLB  = lpSum([visited_unbalanced_MINLB[(t1,t2)] for (t1,t2) in games])

    notEnoughGames_MINLB  = lpSum([notEnoughHomes[t] + notEnoughAways[t] for t in teams])

    # specialObjectives+=travelCost_Total_MINLB+10*visited_too_less_MINLB
    specialObjectives+=100*( 0.1*travelCost_Total_MINLB+0.2*total_visited_unbalanced_MINLB+2*notEnoughGames_MINLB)
    

if mathModelName in ["ALPS" ,"ICE Hockey League" , "ICEYSL"]:

    if mathModelName != "ALPS"  and False:
        firstTwoPhases= [ (r,d) for (r,d) in roundDays if r<=26 ]
        secondTwoPhases= [ (r,d) for (r,d) in roundDays if r>= 27 ]
        for (t1,t2) in games:
            # print (t1 , t2, getRoundDaysByRound[1][0], distance[getTeamById[t1],getTeamById[t2]] , getConference[t1]==getConference[t2] )
            for rrr in [firstTwoPhases, secondTwoPhases]:
                model2+= lpSum([x[(t1,t2,rd)] for rd in rrr]) <=1

    # trips_ICE_raw={
    #     'DEC': [['AVS', 'VIC'],[ 'ZNO', 'BWL'],[ 'IBC', 'G99', 'KAC'],['VSV', 'HKO']],
    #     'AVS': [['DEC', 'HCI', 'HCB', 'PUS', 'RBS']],
    #     'HCB': [['ZNO', 'VIC'],['IBC', 'AVS']],
    #     'G99': [['HCB', 'PUS', 'DEC', 'HCI']],
    #     'BWL': [['HCB', 'PUS', 'DEC']],
    #     'ZNO': [['HCB', 'PUS'   'DEC', 'HCI']],
    #     'VSV': [['HCB', 'PUS'],[ 'DEC', 'HCI'],[ 'VIC', 'AVS'],[ 'VIC', 'IBC', 'ZNO']],
    #     'KAC': [['PUS', 'HCB'],[ 'HCI', 'DEC']],
    #     'RBS': [],
    #     'VIC': [['HCB', 'PUS'],['DEC', 'HCI']],
    #     'HCI': [['VIC', 'AVS'],[ 'BWL', 'ZNO'],[ 'BWL', 'IBC'],[ 'VSV', 'KAC', 'HKO']],
    #     'IBC': [['HCB', 'PUS'],[ 'DEC', 'HCI'],[ 'HKO', 'VSV']],
    #     'HKO': [['HCB', 'PUS'],[ 'DEC', 'HCI']],
    #     'PUS': []}


    # trips_ICE_raw={
    #     'DEC': [['BWL', 'IBC' , 'AVS' , 'ZNO' , 'VIC' ],[ 'IBC', 'G99', 'KAC'],['VSV', 'HKO']],
    #     'AVS': [['DEC', 'HCI', 'HCB', 'PUS', 'RBS']],
    #     'HCB': [['BWL', 'IBC' , 'AVS' , 'ZNO' , 'VIC' ]],
    #     'G99': [['HCB', 'PUS', 'DEC', 'HCI']],
    #     'BWL': [['HCB', 'PUS', 'DEC']],
    #     'ZNO': [['HCB', 'PUS','DEC', 'HCI']],
    #     'VSV': [['HCB', 'PUS', 'DEC', 'HCI'],[ 'VIC', 'AVS', 'VIC', 'IBC', 'ZNO']],
    #     'KAC': [['PUS', 'HCB', 'HCI', 'DEC']],
    #     'RBS': [],
    #     'VIC': [['HCB', 'PUS','DEC', 'HCI']],
    #     'HCI': [['BWL', 'IBC' , 'AVS' , 'ZNO' , 'VIC' ],[ 'VSV', 'KAC', 'HKO']],
    #     'IBC': [['HCB', 'PUS', 'DEC', 'HCI'],[ 'HKO', 'VSV']],
    #     'HKO': [['HCB', 'PUS', 'DEC', 'HCI']],
    #     'PUS': [['BWL', 'IBC' , 'AVS' , 'ZNO' , 'VIC' ]]}


    trips_ICE_raw={
        'DEC': [['AVS', 'VIC'],['IBC', 'ZNO'],['G99', 'HKO']],
        'AVS': [['DEC', 'HCI'],['HCB', 'PUS']],
        'HCB': [['AVS', 'VIC'],['IBC', 'ZNO']],
        'G99': [],
        'BWL': [],
        'ZNO': [['DEC', 'HCI'],['HCB', 'PUS']],
        'VSV': [],
        'KAC': [],
        'RBS': [],
        'VIC': [['DEC', 'HCI'],['HCB', 'PUS']],
        'HCI': [['AVS', 'VIC'],['IBC', 'ZNO']],
        'IBC': [['DEC', 'HCI'],['HCB', 'PUS']],
        'HKO': [],
        'PUS': [['AVS', 'VIC'],['IBC', 'ZNO']]}

    # importantTravellers = [getTeamIdByShortName[ts2] for ts2 in  [ "AVS", "HCB", "DEC", "PUS", "IBC" , "HCI" ] ]   
    # importantTravellers = [getTeamIdByShortName[ts2] for ts2 in  [ "AVS", "HCB", "DEC", "PUS", "IBC" , "HCI" , "VIC" ] ]   

    firstRoundOfChristmas=30
    lastRoundOfChristmas=36
    badweekdayGames=0

    if mathModelName == "ALPS" :
        trips_ICE_raw={
            'EHC': [['JES', 'KFT'],['VCS', 'SWL']],
            'ECB': [['JES', 'KFT'],['VCS', 'SWL']],
            'VEU': [['JES', 'KFT'],['VCS', 'SWL']],
            'VCS': [['ECB', 'EHC'],['VEU', 'KEC'],['ASH', 'SGC', 'RIT', 'GHE', 'WSV', 'FAS', 'HCM']],
            'JES': [['ECB', 'EHC'], ['VEU', 'KEC']],
            'KFT': [['ECB', 'EHC'], ['VEU', 'KEC']],
            'ASH': [['VCS', 'SWL']],
            'SGC': [['VCS', 'SWL']],
            'RIT': [['VCS', 'SWL']],
            'GHE': [['VCS', 'SWL']],
            'WSV': [['VCS', 'SWL']],
            'FAS': [['VCS', 'SWL']],
            'HCM': [['VCS', 'SWL']]
            }
        badweekdayGames = lpSum([ distanceById[t1,t2]* distanceById[t1,t2] * distanceById[t1,t2] /8000000 * x[t1,t2,(r,d)] for (t1,t2) in games for (r,d) in roundDays if getWeekDay[d]=="Thu" and distanceById[t1,t2]>250 ]) 
        firstRoundOfChristmas=25
        lastRoundOfChristmas=29
        firstRoundOfChristmas=27
        lastRoundOfChristmas=28

        importantTravellers = [getTeamIdByShortName[ts2] for ts2 in  [ "EHC", "ECB", "VEU", "VCS", "JES", "KFT", "ASH", "SGC", "RIT", "GHE", "WSV", "FAS", "HCM" ] ]   

    if mathModelName == "ICE Hockey League" :
        importantTravellers = [getTeamIdByShortName[ts2] for ts2 in  ["HCB", "AVS", "DEC", "PUS", "IBC" , "ZNO" , "HCI" , "VIC"] ]   
        importantTravellers = [getTeamIdByShortName[ts2] for ts2 in  [ "DEC", "AVS", "HCB", "VIC", "HCI", "IBC", "PUS"] ]   


    if mathModelName == "ICEYSL" :
        trips_ICE_raw={ t_shortname[t] : [] for t in teams }
        trips_ICE_raw["HCI"] = [['NHA', 'VSV'],['IHC', 'OHE'], ['EAS', 'EAO']]
        importantTravellers = [getTeamIdByShortName[ts2] for ts2 in  ["HCI"] ]   
        badweekdayGames = lpSum([(x[t1,t2,(r,d)]) for (t1,t2) in games for (r,d) in roundDays if getWeekDay[d] in [ "Wed", "Thu" ] and distanceById[t1,t2]>200 ]) 

    short_dist = { t : sorted([ (distanceById[t,t2] ,t2)  for t2 in teams if t2!=t ])  for t in teams }
    maxDist4 = { t : max(210, short_dist[t][3][0])  for t in teams } 
    
    # for t in teams :
        # print (getTeamById[t] , maxDist4[t], short_dist[t])
        # for ds,t2 in short_dist[t]:
            # print (" - " , getTeamById[t2] , ds)
    

    toofarForXmas = [ (t1,t2,(r,d))  for (t1,t2) in games for (r,d) in roundDays if r>= firstRoundOfChristmas and (r<=lastRoundOfChristmas or r>=51 )  and distanceById[t1,t2]> maxDist4[t2]+1  ]
    wayToofarForXmas = [ (t1,t2,(r,d))  for (t1,t2) in games for (r,d) in roundDays if r>= firstRoundOfChristmas and r<=lastRoundOfChristmas and distanceById[t1,t2]> 300 ]

    # kac dec feh sind wichtig                         
    # vci 2 trips hcidec pusboz
            
    cntr = 0 
    trips_ICE = {}
    for ts in trips_ICE_raw.keys():
        t= getTeamIdByShortName[ts]
        for tp in trips_ICE_raw[ts]:
            tps = [getTeamIdByShortName[ts2] for ts2 in tp]                
            trips_ICE[cntr]=(t,tps)      
            # print (trips_ICE)    
            print ("TRIP", cntr, tp, tps)
            cntr+=1
            # for t2 in tps:
                # print (" - " , getTeamById [t2] , " " , distanceById[t,t2] , "km")
        print ()

    print (trips_ICE)

    important_trips_ICE = [ cn for cn in trips_ICE.keys() if trips_ICE[cn][0] in importantTravellers ]
    trips_ICE_by_traveller ={t: [ cn for cn in trips_ICE.keys()  if trips_ICE[cn][0]  == t  ] for t in teams }
    print (trips_ICE_by_traveller)
    

    day1pairs =[ (d1,d2) for d1 in days for d2 in days if getDateTimeDay[d2]-getDateTimeDay[d1] ==datetime.timedelta(days=1)  and getRoundByDay[d1] != getRoundByDay[d2] ]

    toughWeekend_ICE = { (t,d1,d2) : pulp.LpVariable('toughWeekend_ICE_'+str(t)+'_'+str(d1) , lowBound = 0, cat = pulp.LpContinuous) for t in realteams  for (d1,d2) in day1pairs }

    for d1,d2 in day1pairs:
        print (getNiceDay[d1], getNiceDay[d2])
        for t in realteams: 
            print (t,d1,d2 , getTeamById[t],  getNiceDay[d1],getNiceDay[d2])
            model2+= home[(t,d1)] + lpSum([x[(t1,t,rd)] for t1 in teams for rd in getRoundDaysByDay[d2] if distanceById[t,t1]>150] ) <=1+toughWeekend_ICE[t,d1,d2]
            model2+= home[(t,d2)] + lpSum([x[(t1,t,rd)] for t1 in teams for rd in getRoundDaysByDay[d1] if distanceById[t,t1]>150] ) <=1+toughWeekend_ICE[t,d1,d2]

    traveling_ICE = { (tr,d1,d2) : pulp.LpVariable('traveling_ICE_'+str(tr)+'_'+str(d1) , lowBound = 0, cat = pulp.LpContinuous) for tr in trips_ICE.keys() for (d1,d2) in day1pairs }
    notEnoughTravel = { t : pulp.LpVariable('important_travel_'+str(t) , lowBound = 0, cat = pulp.LpContinuous) for t in importantTravellers }

    for (tr,d1,d2) in traveling_ICE.keys():
        t2,tms = trips_ICE[tr]
        model2+= traveling_ICE[(tr,d1,d2)] <= lpSum([x[(t1,t2,rd)] for t1 in tms for rd in getRoundDaysByDay[d1]])
        # if t2 in [getTeamIdByShortName["DEC"] ,getTeamIdByShortName["HCB"]] and nextDay[d2]!=-1:
        if t2 in [] and nextDay[d2]!=-1:
            model2+= traveling_ICE[(tr,d1,d2)] <= lpSum([x[(t1,t2,rd)] for t1 in tms for rd in getRoundDaysByDay[d2]+getRoundDaysByDay[nextDay[d2]]])
        else:
            model2+= traveling_ICE[(tr,d1,d2)] <= lpSum([x[(t1,t2,rd)] for t1 in tms for rd in getRoundDaysByDay[d2]])

    if mathModelName == "ALPS":
        for t in realteams:
            for d1,d2 in day1pairs:
                model2+=  away[(t,d1)] <=  lpSum([ traveling_ICE[(tr,d1,d2)] for tr in trips_ICE_by_traveller[t] ]) +  toughWeekend_ICE[t,d1,d2] 
                print ( "away ",t , getTeamById[t] , " only if travelling ", getNiceDay[d1]  , d2)
    
    for t in importantTravellers:
        model2+=  lpSum([ traveling_ICE[(tr,d1,d2)] for tr in trips_ICE_by_traveller[t] for (d1,d2) in day1pairs])  >=2 - notEnoughTravel[t] 

    notEnoughTravelTotal =   lpSum([ notEnoughTravel[t] for t in notEnoughTravel.keys()  ]) 
    badXmas =   lpSum([ 0.01*distanceById[t1,t2] *x[(t1,t2,rd)] for (t1,t2,rd) in toofarForXmas  ]) + 10 * lpSum([ x[ttrd] for ttrd in wayToofarForXmas  ])  
    toughWeekends =  lpSum([ toughWeekend_ICE[tdd]  for tdd in toughWeekend_ICE.keys() ])  

    # specialObjectives += 0.2*  gew['Trips'] * (-100* lpSum([traveling_ICE[tdd] for tdd in traveling_ICE.keys()]) - 300 * lpSum([traveling_ICE[(tr,d1,d2)] for (tr,d1,d2) in traveling_ICE.keys() if tr in important_trips_ICE ])) + 100*badXmas + 1000 *toughWeekends
    specialObjectives += ( 0.2*  gew['Trips'] * (
                                                -0  * lpSum([traveling_ICE[tdd] for tdd in traveling_ICE.keys()]) 
                                                - 400 * lpSum([traveling_ICE[(tr,d1,d2)] for (tr,d1,d2) in traveling_ICE.keys() if tr in important_trips_ICE ])
                                                )
                            + 100 * badXmas
                            + 1000 * toughWeekends 
                            + 1000*notEnoughTravelTotal 
                            # + 50*badweekdayGames
                            + 200*badweekdayGames
                            )

    for (t,r,c) in tripToCluster.keys():
        model2 +=  tripToCluster[(t,r,c)] == 0   
        
    
if mathModelName=="NBA":

    for (t1,t2,d,channel) in seedTV:
        if previousDay[d]!=-1:                
            model2 +=lpSum([ x_time[(t3,t4,rd,getIdByTime["Late"])] for (t3,t4) in games for rd in getRoundDaysByDay[previousDay[d]] if t1 in [t3,t4] ])+ lpSum([ x_time[(t1,t2,rd,getIdByTime["Early"])] for rd in getRoundDaysByDay[d]]) <=1
            model2 +=lpSum([ x_time[(t3,t4,rd,getIdByTime["Late"])] for (t3,t4) in games for rd in getRoundDaysByDay[previousDay[d]] if t2 in [t3,t4] ])+ lpSum([ x_time[(t1,t2,rd,getIdByTime["Early"])] for rd in getRoundDaysByDay[d]]) <=1
        if nextDay[d]!=-1:                
            model2 +=lpSum([ x_time[(t3,t4,rd,getIdByTime["Early"])] for (t3,t4) in games for rd in getRoundDaysByDay[nextDay[d]] if t1 in [t3,t4] ])+ lpSum([ x_time[(t1,t2,rd,getIdByTime["Late"])] for rd in getRoundDaysByDay[d]]) <=1
            model2 +=lpSum([ x_time[(t3,t4,rd,getIdByTime["Early"])] for (t3,t4) in games for rd in getRoundDaysByDay[nextDay[d]] if t2 in [t3,t4] ])+ lpSum([ x_time[(t1,t2,rd,getIdByTime["Late"])] for rd in getRoundDaysByDay[d]]) <=1

    badRepeater= { (t,r) : pulp.LpVariable('badRepeater_'+str(t)+"_"+str(r) , lowBound = 0, cat = pulp.LpContinuous) for t in teams for r in rounds }
    tooLongTrip_NBA= { (t,r) : pulp.LpVariable('tooLongTrip_NBA_'+str(t)+"_"+str(r) , lowBound = 0, cat = pulp.LpContinuous) for t in teams for r in rounds }
    eastWestTrip_NBA= { (t,r) : pulp.LpVariable('eastWestTrip_NBA_'+str(t)+"_"+str(r) , lowBound = 0, cat = pulp.LpContinuous) for t in teams for r in rounds }

    if nRounds >= 100:        
        for t in realteams:
            if r>=3:
                model2 += break3InRound[(t,r)] +2>= lpSum([ homeInRound[(t,r2)] + awayInRound[(t,r2)] for r2 in [r-2,r-1,r]])

    userepeater= False
    if userepeater:
        for t in realteams: 
            print ("building repeater contraints for " , t)
            for r in rounds:
                # forbid same opponents on successive days
                for t2 in realteams: 
                    if t<t2 and r>2:                        
                        model2 +=  lpSum([ (x[(t,t2,rd )]+x[(t2,t,rd)]) for rd in getRoundDaysByRound[r-2]+getRoundDaysByRound[r-1]+getRoundDaysByRound[r] ]) <= 1 + badRepeater[(t,r)]
                        # badRepeater[(t,r)].upBound=0
                if r>4:                        
                    model2 +=  lpSum([ home [(t,d )] for (r2,d) in roundDays if r2>=r-4 and r2<=r ]) >= 1 - tooLongTrip_NBA[(t,r)]
                    model2 +=  lpSum([ away [(t,d )] for (r2,d) in roundDays if r2>=r-4 and r2<=r ]) >= 1 - tooLongTrip_NBA[(t,r)]        

    b2bmatrix = {"BOS": {"BOS": "G", "TOR": "G", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "R", "NOP": "R", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "R", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "TOR": {"BOS": "Y", "TOR": "G", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "Y", "CHA": "Y", "ATL": "Y", "ORL": "R", "MIA": "R", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "R", "NOP": "R", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "R", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "NYK": {"BOS": "G", "TOR": "G", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "R", "NOP": "R", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "R", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "BKN": {"BOS": "G", "TOR": "G", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "R", "NOP": "R", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "R", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "PHI": {"BOS": "G", "TOR": "G", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "G", "MEM": "Y", "NOP": "Y", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "R", "MIN": "Y", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "WAS": {"BOS": "G", "TOR": "Y", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "Y", "NOP": "R", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "R", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "CHA": {"BOS": "G", "TOR": "Y", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "G", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "G", "HOU": "Y", "DAL": "Y", "SAS": "Y", "OKC": "Y", "MIN": "Y", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "ATL": {"BOS": "Y", "TOR": "Y", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "G", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "G", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "Y", "OKC": "G", "MIN": "Y", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "ORL": {"BOS": "Y", "TOR": "R", "NYK": "Y", "BKN": "Y", "PHI": "Y", "WAS": "Y", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "G", "DET": "Y", "CLE": "Y", "IND": "G", "CHI": "R", "MIL": "R", "MEM": "Y", "NOP": "G", "HOU": "Y", "DAL": "Y", "SAS": "Y", "OKC": "Y", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                    "MIA": {"BOS": "Y", "TOR": "R", "NYK": "Y", "BKN": "Y", "PHI": "Y", "WAS": "Y", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "G", "DET": "Y", "CLE": "Y", "IND": "Y", "CHI": "R", "MIL": "R", "MEM": "Y", "NOP": "G", "HOU": "Y", "DAL": "Y", "SAS": "Y", "OKC": "R", "MIN": "R", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "DET": {"BOS": "G", "TOR": "G", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "R", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "Y", "NOP": "R", "HOU": "R", "DAL": "R", "SAS": "R", "OKC": "Y", "MIN": "G", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "CLE": {"BOS": "G", "TOR": "G", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "Y", "HOU": "R", "DAL": "Y", "SAS": "R", "OKC": "Y", "MIN": "G", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "IND": {"BOS": "Y", "TOR": "Y", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "Y", "HOU": "Y", "DAL": "Y", "SAS": "Y", "OKC": "G", "MIN": "G", "DEN": "X", "UTA": "X", "PHX": "X", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "CHI": {"BOS": "G", "TOR": "G", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "G", "HOU": "Y", "DAL": "G", "SAS": "Y", "OKC": "G", "MIN": "G", "DEN": "R", "UTA": "R", "PHX": "R", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "MIL": {"BOS": "G", "TOR": "G", "NYK": "G", "BKN": "G", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "G", "HOU": "Y", "DAL": "G", "SAS": "Y", "OKC": "G", "MIN": "G", "DEN": "Y", "UTA": "R", "PHX": "R", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "MEM": {"BOS": "Y", "TOR": "Y", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "G", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "G", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "G", "DEN": "Y", "UTA": "R", "PHX": "R", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "NOP": {"BOS": "R", "TOR": "R", "NYK": "R", "BKN": "R", "PHI": "Y", "WAS": "Y", "CHA": "G", "ATL": "G", "ORL": "G", "MIA": "G", "DET": "G", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "Y", "DEN": "R", "UTA": "R", "PHX": "R", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "HOU": {"BOS": "R", "TOR": "R", "NYK": "R", "BKN": "R", "PHI": "R", "WAS": "R", "CHA": "Y", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "Y", "CLE": "Y", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "Y", "DEN": "R", "UTA": "R", "PHX": "Y", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "DAL": {"BOS": "R", "TOR": "R", "NYK": "R", "BKN": "R", "PHI": "R", "WAS": "R", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "Y", "CLE": "G", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "Y", "DEN": "Y", "UTA": "Y", "PHX": "Y", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "SAS": {"BOS": "R", "TOR": "R", "NYK": "R", "BKN": "R", "PHI": "R", "WAS": "R", "CHA": "Y", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "R", "CLE": "Y", "IND": "G", "CHI": "Y", "MIL": "Y", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "Y", "DEN": "Y", "UTA": "Y", "PHX": "Y", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "OKC": {"BOS": "R", "TOR": "R", "NYK": "R", "BKN": "R", "PHI": "R", "WAS": "R", "CHA": "G", "ATL": "G", "ORL": "Y", "MIA": "Y", "DET": "G", "CLE": "Y", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "G", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "G", "DEN": "G", "UTA": "Y", "PHX": "Y", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "MIN": {"BOS": "Y", "TOR": "Y", "NYK": "Y", "BKN": "Y", "PHI": "G", "WAS": "Y", "CHA": "G", "ATL": "G", "ORL": "R", "MIA": "R", "DET": "G", "CLE": "G", "IND": "G", "CHI": "G", "MIL": "G", "MEM": "G", "NOP": "Y", "HOU": "Y", "DAL": "G", "SAS": "Y", "OKC": "G", "MIN": "G", "DEN": "Y", "UTA": "Y", "PHX": "R", "LAC": "X", "LAL": "X", "GSW": "X", "SAC": "X", "POR": "X"}, 
                "DEN": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "Y", "MIL": "G", "MEM": "Y", "NOP": "Y", "HOU": "G", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "G", "DEN": "G", "UTA": "G", "PHX": "G", "LAC": "R", "LAL": "R", "GSW": "Y", "SAC": "Y", "POR": "R"}, 
                "UTA": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "R", "MIL": "Y", "MEM": "Y", "NOP": "R", "HOU": "Y", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "G", "DEN": "G", "UTA": "G", "PHX": "G", "LAC": "G", "LAL": "G", "GSW": "G", "SAC": "G", "POR": "G"}, 
                "PHX": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "R", "MIL": "R", "MEM": "R", "NOP": "R", "HOU": "Y", "DAL": "G", "SAS": "G", "OKC": "G", "MIN": "Y", "DEN": "G", "UTA": "G", "PHX": "G", "LAC": "G", "LAL": "G", "GSW": "G", "SAC": "G", "POR": "Y"}, 
                "LAC": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "X", "MIL": "X", "MEM": "X", "NOP": "X", "HOU": "X", "DAL": "X", "SAS": "X", "OKC": "X", "MIN": "X", "DEN": "G", "UTA": "G", "PHX": "G", "LAC": "G", "LAL": "G", "GSW": "G", "SAC": "G", "POR": "G"}, 
                "LAL": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "X", "MIL": "X", "MEM": "X", "NOP": "X", "HOU": "X", "DAL": "X", "SAS": "X", "OKC": "X", "MIN": "X", "DEN": "G", "UTA": "G", "PHX": "G", "LAC": "G", "LAL": "G", "GSW": "G", "SAC": "G", "POR": "G"}, 
                "GSW": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "X", "MIL": "X", "MEM": "X", "NOP": "X", "HOU": "X", "DAL": "X", "SAS": "X", "OKC": "X", "MIN": "X", "DEN": "Y", "UTA": "G", "PHX": "G", "LAC": "G", "LAL": "G", "GSW": "G", "SAC": "G", "POR": "G"}, 
                "SAC": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "X", "MIL": "X", "MEM": "X", "NOP": "X", "HOU": "X", "DAL": "X", "SAS": "X", "OKC": "X", "MIN": "X", "DEN": "G", "UTA": "G", "PHX": "G", "LAC": "G", "LAL": "G", "GSW": "G", "SAC": "G", "POR": "G"}, 
                "POR": {"BOS": "X", "TOR": "X", "NYK": "X", "BKN": "X", "PHI": "X", "WAS": "X", "CHA": "X", "ATL": "X", "ORL": "X", "MIA": "X", "DET": "X", "CLE": "X", "IND": "X", "CHI": "X", "MIL": "X", "MEM": "X", "NOP": "X", "HOU": "X", "DAL": "X", "SAS": "X", "OKC": "X", "MIN": "X", "DEN": "Y", "UTA": "G", "PHX": "G", "LAC": "Y", "LAL": "Y", "GSW": "G", "SAC": "G", "POR": "G"} 
    }

    bad_travels = [ (getTeamIdByName[teamByShort[t2]],getTeamIdByName[teamByShort[t1]],b2bmatrix[t1][t2]) for t1 in b2bmatrix.keys() for t2 in b2bmatrix.keys() if b2bmatrix[t1][t2]!="G"]

    east_teams = [ t for t in realteams     if                      t_lon[t]>= -87]
    center_teams = [ t for t in realteams   if  -87 > t_lon[t] and t_lon[t]>=-100 ]
    mountain_teams = [ t for t in realteams if -100 > t_lon[t] and t_lon[t]>=-113 ]
    west_teams = [ t for t in realteams if t_lon[t]< -113]

    # print (len (east_teams))
    # print (len (center_teams))
    # print (len (mountain_teams))
    # for t in mountain_teams:
    #     print (" mt " , getTeamById[t])
    # print (len (west_teams))
    

    back2backBlocks += [ (east_teams, mountain_teams+west_teams,1.0), (mountain_teams+west_teams,east_teams,1.0),
                        (center_teams,west_teams,1.0) ,(west_teams,center_teams,1.0),
                        ([getTeamIdByName[teamByShort[ts]] for ts in ["MEM","NOP","HOU","DAL","SAS","OKC","MIN"]],[getTeamIdByName[teamByShort[ts]] for ts in ["BOS", "TOR", "NYK", "BKN", "PHI", "WAS"]],0.05),
                        ([getTeamIdByName[teamByShort[ts]] for ts in ["BOS", "TOR", "NYK", "BKN", "PHI", "WAS"]], [getTeamIdByName[teamByShort[ts]] for ts in ["NOP","HOU","DAL","SAS","OKC"]],0.05),
                        ([getTeamIdByName[teamByShort[ts]] for ts in ["DEN", "UTA", "PHX"]], [getTeamIdByName[teamByShort[ts]] for ts in ["CHI","MIL","MEM","NOP","HOU"]],0.05),
                        ([getTeamIdByName[teamByShort[ts]] for ts in ["ORL", "MIA"]], [getTeamIdByName[teamByShort[ts]] for ts in ["TOR","MIN"]],0.05),
                        ([getTeamIdByName[teamByShort[ts]] for ts in ["NOP", "HOU", "DAL", "SAS"]], [getTeamIdByName[teamByShort[ts]] for ts in ["DET","CLE"]],0.05),
                        ([getTeamIdByName[teamByShort[ts]] for ts in ["TOR", "CHI", "MIL", "MIN","OKC"]], [getTeamIdByName[teamByShort[ts]] for ts in ["ORL","MIA"]],0.05),
                        ([getTeamIdByName[teamByShort[ts]] for ts in [ "CHI", "MIL", "MEM","NOP"]], [getTeamIdByName[teamByShort[ts]] for ts in ["UTA","PHX"]],0.05),
                            ]

    playingAwayEast = { (t,r) : lpSum([ x[(t1,t,rd )] for rd in getRoundDaysByRound[r] for t1 in east_teams ]) for r in rounds for t in realteams }
    playingAwayWest = { (t,r) : lpSum([ x[(t1,t,rd )] for rd in getRoundDaysByRound[r] for t1 in west_teams+mountain_teams ]) for r in rounds for t in realteams }

    for t in realteams:
        for r in rounds:
            if r>1:
                model2 +=  playingAwayEast[(t,r-1)] + playingAwayWest[(t,r)]  <=1 + eastWestTrip_NBA[(t,r)]
                model2 +=  playingAwayWest[(t,r-1)] + playingAwayEast[(t,r)]  <=1 + eastWestTrip_NBA[(t,r)]


    for t in teams:
        for r in rounds:
            if r>2:
                model2 +=  awayInRound[(t,r-1)]  <= awayInRound[(t,r-2)]  + awayInRound[(t,r)]  + 3*eastWestTrip_NBA[(t,r)]


    for t in west_teams+mountain_teams:
        for r in rounds:
            if r>2:
                model2 +=  playingAwayEast[(t,r-1)]  <= playingAwayEast[(t,r-2)]  + playingAwayEast[(t,r)]  + 0.3*eastWestTrip_NBA[(t,r)]

    for t in east_teams:
        for r in rounds:
            if r>2:
                model2 +=  playingAwayWest[(t,r-1)]  <= playingAwayWest[(t,r-2)]  + playingAwayWest[(t,r)]  + 0.3*eastWestTrip_NBA[(t,r)]


    # for t1 in teams:
        # print ("bad travel in ", getTeamById[t1] , bad_travel_in[t1]  )
        # print ("bad travel out ", getTeamById[t1] , bad_travel_out[t1]  )

    # distant_teams = { t: []  for t in realteams}

    # for t in east_teams: 
    #     print ("EAST " , getTeamById[t], t_lon[t])
    #     # distant_teams[t]= mountain_teams+west_teams
    # for t in center_teams: 
    #     print ("CENTER " , getTeamById[t], t_lon[t])
    #     # distant_teams[t]= west_teams
    # for t in mountain_teams: 
    #     print ("MOUNTAIN " , getTeamById[t], t_lon[t])
    #     # distant_teams[t]= east_teams
    # for t in west_teams: 
    #     print ("WEST " , getTeamById[t], t_lon[t])
    #     # distant_teams[t]= center_teams+east_teams

        # print ("building back to back contraints for " , t)
    badRepeater_Total_NBA  = lpSum([badRepeater[(t,r)] for t in teams for r in rounds])
    tooLongTrip_Total_NBA  = lpSum([tooLongTrip_NBA[(t,r)] for t in teams for r in rounds])
    eastWestTrip_Total_NBA  = lpSum([eastWestTrip_NBA[(t,r)] for t in teams for r in rounds])
    specialObjectives+=10*( badRepeater_Total_NBA)+100*tooLongTrip_Total_NBA + 100*eastWestTrip_Total_NBA


if mathModelName=="UCL24" :
    isUEL = thisSeason.nicename[:3]=="UEL"
    show_TV_markets = True

    if runMode=="New" and not playSwissTable:
        # solver warm-start with a feasible assignment
        premodel_time = time.time()
        res_objective, res_games = ucl24_basicmodell(solver,thisScenario,fixedGames,fixedGames2)

        if user_name == "Simulator":                
            sol_simulation = {
                'ucl24_objective':res_objective,
                'ucl24_time':time.time()-premodel_time
            }

        for game in res_games:
            # x_round[game].lowBound = 1
            setLB(x_round[game],1)


    uefa_games = [ (t1,t2) for t1 in teams for t2 in teams if t1<t2 and t_conference[t1]==t_conference[t2] ]
    uefa_games=games
    uefa_interesting_games = [ (t1,t2) for (t1,t2) in uefa_games  if quality_of_game(t1,t2)>4 ]

    # best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t1 in teams for t2 in teams for d in days  }
    best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for (t1,t2) in uefa_interesting_games for d in days  }
    best_global_early = { d : pulp.LpVariable('best_global_early_'+str(d), lowBound = 0,  cat = pulp.LpContinuous) for d in days  }

    uefa_interesting_domestic_games = {c:[]  for c in NAS15}
    uefa_interesting_domestic_teams = {c:set([])  for c in NAS15}

    topDomDist = { c : 0 for c in countries }
    lowDomDist = { c : 0 for c in countries }

    tuesdays = [ d  for d in days if getWeekDay[d]=="Tue"]
    wednesdays = [ d  for d in days if getWeekDay[d]=="Wed"]
    if "SpreadDomTopTueWed" in special_wishes_active or "SpreadDomLowTueWed" in special_wishes_active or "AvoidTwoDomTopMD" in special_wishes_active:
        topDomesticGames = { c: [] for c in countries}
        lowDomesticGames = { c: [] for c in countries}
        for (t1,t2) in uefa_games:
            if t_pot[t1]==1:
                topDomesticGames[t_country[t2]].append((t1,t2))
            if t_pot[t2]==1:
                topDomesticGames[t_country[t1]].append((t1,t2))
            if t_pot[t1]==4:
                lowDomesticGames[t_country[t2]].append((t1,t2))
            if t_pot[t2]==4:
                lowDomesticGames[t_country[t1]].append((t1,t2))

    if "SpreadDomTopTueWed" in special_wishes_active:
        topDomDist = { c : pulp.LpVariable('topDomDist_'+str(c), lowBound = 0,  cat = pulp.LpContinuous) for c in countries }
        for c in countries:
            model2+= lpSum([x[t1,t2,rd] for (t1,t2) in topDomesticGames[c] for d in tuesdays   for rd in getRoundDaysByDay[d]]) >= 0.5*len(topDomesticGames[c]) - topDomDist[c]
            model2+= lpSum([x[t1,t2,rd] for (t1,t2) in topDomesticGames[c] for d in wednesdays for rd in getRoundDaysByDay[d]]) >= 0.5*len(topDomesticGames[c]) - topDomDist[c]

    if "SpreadDomLowTueWed" in special_wishes_active:
        lowDomDist = { c : pulp.LpVariable('lowDomDist_'+str(c), lowBound = 0,  cat = pulp.LpContinuous) for c in countries }
        for c in countries:
            model2+= lpSum([x[t1,t2,rd] for (t1,t2) in lowDomesticGames[c] for d in tuesdays   for rd in getRoundDaysByDay[d]]) >= 0.5*len(lowDomesticGames[c]) - lowDomDist[c]
            model2+= lpSum([x[t1,t2,rd] for (t1,t2) in lowDomesticGames[c] for d in wednesdays for rd in getRoundDaysByDay[d]]) >= 0.5*len(lowDomesticGames[c]) - lowDomDist[c]

    if "AvoidTwoDomTopMD" in special_wishes_active:
        twoDomTop = { c : pulp.LpVariable('twoDomTop_'+str(c), lowBound = 0,  cat = pulp.LpContinuous) for c in countries }
        if sw_int1["AvoidTwoDomTopMD"] in rounds:
            for c in countries:
                model2+= lpSum([x[t1,t2,rd] for (t1,t2) in topDomesticGames[c] for rd in getRoundDaysByRound[sw_int1["AvoidTwoDomTopMD"]]]) <= 1 + twoDomTop[c]
                print ("  " , c , " NO MORE THAN 1 TOP GAME IN ROUND " , sw_int1["AvoidTwoDomTopMD"] ,":"  , [x[t1,t2,rd] for (t1,t2) in topDomesticGames[c] for rd in getRoundDaysByRound[sw_int1["AvoidTwoDomTopMD"]]] , [(getTeamById[t1],getTeamById[t2],rd , x[t1,t2,rd] ) for (t1,t2) in topDomesticGames[c] for rd in getRoundDaysByRound[sw_int1["AvoidTwoDomTopMD"]]] )

    # for c in countries:
    #     print (c)
    #     for (t1,t2) in topDomesticGames[c]:
    #         print (" +++  ", getTeamById[t1] , " - " , getTeamById[t2] )
    #     for (t1,t2) in lowDomesticGames[c]:
    #         print (" ---  ", getTeamById[t1] , " - " , getTeamById[t2] )

    for (t1,t2) in uefa_games:
        if quality_of_game_dom(t1, t2,t_country[t1])>=10 and t_country[t1] in NAS15:
            uefa_interesting_domestic_games[t_country[t1]].append((t1,t2))
            uefa_interesting_domestic_teams[t_country[t1]].add(t1)
        if quality_of_game_dom(t2, t1,t_country[t2])>=10 and t_country[t2] in NAS15:
            uefa_interesting_domestic_games[t_country[t2]].append((t1,t2))
            uefa_interesting_domestic_teams[t_country[t2]].add(t2)

    print ("cool domestic  ", uefa_interesting_domestic_games)
    for c in NAS15:
        print (c)
        for (t1,t2) in uefa_interesting_domestic_games[c]:
            print (getTeamById[t1], getTeamById[t2] , quality_of_game_dom(t1, t2, c),quality_of_game_dom(t2, t1, c))
        for t1 in uefa_interesting_domestic_teams[c]:
            print (getTeamById[t1])
    # exit(0)
    best_dom= {(c,t1,t2,d) : pulp.LpVariable('best_dom_'+str(c)+'_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for c in NAS15 for (t1,t2) in uefa_interesting_domestic_games[c] for d in days }
    best_dom_early = { (c,d) : pulp.LpVariable('best_dom_early_'+str(d) + '_'+str(c), lowBound = 0,  cat = pulp.LpContinuous) for d in days for c in NAS15 }


    if thisSeason.nicename[:3]=="UCL" :
        for (t1,t2) in uefa_interesting_games :
            for (r,d) in roundDays:
                model2 += best_glo[(t1,t2,d) ] <= x[(t1,t2,(r,d)) ] + x[(t2,t1,(r,d)) ] 

        for d in days:
            model2+= lpSum( [ best_glo[(t1,t2,d)] for (t1,t2) in uefa_interesting_games]) == 1
            rd =getRoundDaysByDay[d]
            for t in teams: 
                model2+= lpSum( [ quality_of_game(t1,t2)*(x[t1,t2,rd]+ x[t2,t1,rd]) for rd in getRoundDaysByDay[d] for (t1,t2) in uefa_interesting_games if t in [t1,t2]])  \
                            <= lpSum( [ best_glo[(t1,t2,d)]*quality_of_game(t1,t2) for (t1,t2) in uefa_interesting_games ])

            # Avoid the match with the highest global coefficient of the night to be played early (if two matches have the same, one late is enough) (preference)")
            for (t1,t2) in uefa_interesting_games :
                rd= getRoundDaysByDay[d][0]
                model2 += best_glo[(t1,t2,d) ] <= x_time[(t1,t2,rd,getIdByTime["Late"])] + x_time[(t2,t1,rd,getIdByTime["Late"])] + best_global_early[d]


    # TODO 
    # Avoid playing early the match with the highest domestic coefficient in NAs 1-5 if it is 10 or more à priority B
    # nas 5 fran

        for c in NAS15:
            for (t1,t2) in uefa_interesting_domestic_games[c]:
                for (r,d) in roundDays:
                    model2 += best_dom[(c,t1,t2,d) ] <= x[(t1,t2,(r,d)) ] + x[(t2,t1,(r,d)) ] 

            for d in days:
                model2+= lpSum( [ best_dom[(c,t1,t2,d)] for (t1,t2) in uefa_interesting_domestic_games[c]]) <= 1
                rd =getRoundDaysByDay[d]
                for t in uefa_interesting_domestic_teams[c]: 
                    model2+= lpSum( [ quality_of_game_dom(t1,t2,c)*(x[t1,t2,rd]+ x[t2,t1,rd]) for rd in getRoundDaysByDay[d] for (t1,t2) in uefa_interesting_domestic_games[c] if t in [t1,t2]])  \
                                <= lpSum( [ best_dom[(c,t1,t2,d)]*quality_of_game_dom(t1,t2,c) for (t1,t2) in uefa_interesting_domestic_games[c] ])

                # Avoid the match with the highest global coefficient of the night to be played early (if two matches have the same, one late is enough) (preference)")
                for (t1,t2) in uefa_interesting_domestic_games[c]:
                    rd= getRoundDaysByDay[d][0]
                    model2 += best_dom[(c,t1,t2,d)] <= x_time[(t1,t2,rd,getIdByTime["Late"])] + x_time[(t2,t1,rd,getIdByTime["Late"])] + best_dom_early[(c,d)]
    
    specialObjectives= (0.01*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys()])
                        #  Avoid early matches with a global coefficient of 16 and more (60)
                        +0.6*0.2*sw_prio["AvoidEarlyGlobal"]*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys() if quality_of_game(t1,t2)>=sw_int1["AvoidEarlyGlobal"]])
                        # Maximise the average global coefficient of early matches (should stay under 16) à priority C
                        -0.1*sw_prio["MaxAverageEarlyGlobal"]*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys() if quality_of_game(t1,t2)<sw_int1["MaxAverageEarlyGlobal"]])
                        #  Avoid early matches with a domestic coefficient of 25 and more (60)
                        +0.6*0.2*sw_prio["AvoidEarlyDomestic"]*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys() if  quality_of_game_dom(t1,t2,t_country[t1])>=sw_int1["AvoidEarlyDomestic"] or quality_of_game_dom(t1,t2,t_country[t2])>=sw_int1["AvoidEarlyDomestic"] ])
                        -0.1*lpSum([quality_of_game(t1,t2) * best_glo[(t1,t2,d)] for (t1,t2) in uefa_interesting_games  for d in days ])
                        +0.5*0.04*sw_prio["AvoidEarlyHighDomestic"]*lpSum([best_global_early[d] for d in days ]) 
                        +5*0.04*sw_prio["AvoidEarlyHighGlobal"]*lpSum([best_dom_early[(c,d)]  for c in NAS15 for d in days ])
                        )

    if "SpreadDomTopTueWed" in special_wishes_active:
        specialObjectives+= 2*0.04*sw_prio["SpreadDomTopTueWed"]*lpSum([topDomDist[c] for c in countries ])

    if "SpreadDomLowTueWed" in special_wishes_active:
        specialObjectives+= 2*0.04*sw_prio["SpreadDomLowTueWed"]*lpSum([lowDomDist[c] for c in countries ])

    if "AvoidTwoDomTopMD" in special_wishes_active:
        specialObjectives+= 2*0.04*sw_prio["AvoidTwoDomTopMD"]*lpSum([twoDomTop[c] for c in countries ])


    model2+= standardObjectives +specialObjectives


    if "UCL24Patterns" in special_wishes_active:
        pos_patterns = [
            [1,0,1,1,0,0,1,0 ],
            [1,0,1,0,1,0,1,0 ],
            [1,0,1,0,1,0,0,1 ],
            [1,0,1,0,0,1,1,0 ],
            [1,0,1,0,0,1,0,1 ],
            [1,0,0,1,1,0,1,0 ],
            [1,0,0,1,1,0,0,1 ],
            [1,0,0,1,0,1,1,0 ],
            [1,0,0,1,0,1,0,1 ],
        ]

        # add reverse patterns (all those starting with 0,1 )
        pos_patterns+=[ [ 1-p[i] for i in range(8)] for p in pos_patterns ]
        print ("pos_patterns",pos_patterns)

        positions = range (len(pos_patterns))
        # pos= {(t,p) : pulp.LpVariable('pos_'+str(t)+'_'+str(p), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t in teams for p in positions }
        pos= {(t,p) : pulp.LpVariable('pos_'+str(t)+'_'+str(p), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t in teams for p in positions }

        for t in teams:
            model2 += lpSum( [ pos[t,p] for p in positions ]) ==1
            for r in rounds:
                model2 += homeInRound[t,r]<= lpSum( [ pos[t,p] for p in positions if pos_patterns[p][r-1]==1 ])
                model2 += awayInRound[t,r]<= lpSum( [ pos[t,p] for p in positions if pos_patterns[p][r-1]==0 ])


        if runMode!='Improve' and "UCL24Patterns" in special_wishes_active and "extraUEFAPatternRun" in special_wishes_active :
            for p in positions:
                if pos_patterns[p][0]==1:
                    for t in teams:
                        pos[t,p].cat = pulp.LpInteger
            if solver == "CBC":
                model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
            elif solver == "Gurobi":
                model2.solve(GUROBI(MIPGap=0.2, TimeLimit=120, msg=1))
            else:
                model2.solve(XPRESS(msg=1,maxSeconds=60, keepFiles=True, options=["THREADS=12,DEFAULTALG=4,DETERMINISTIC=0,CUTSTRATEGY=0"]))

            for p in positions:                
                for t in teams:                 
                    if pos[(t,p)].value()>0.9:
                        model2 += pos[(t,p)] == pos[(t,p)].value()
                        print(p,t, pos_patterns[p])


if mathModelName=="UEL24" :

    if runMode=="New" and not playSwissTable:  
        # solver warm-start with a feasible assignment
        premodel_time = time.time()
        res_objective, res_games = ueluecl24_basicmodell_v2(solver,thisScenario,fixedGames,fixedGames2)

        if user_name == "Simulator":                
            sol_simulation = {
                'ucl24_objective':res_objective,
                'ucl24_time':time.time()-premodel_time
            }

        for game in res_games:
            # x_round[game].lowBound = 1
            setLB(x_round[game],1)

    isUEL = True
    show_TV_markets = True

    positions = []

    uefa_games = games 
    uefa_interesting_games = [ (t1,t2) for (t1,t2) in uefa_games  if quality_of_game(t1,t2)>4 ]

    # best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t1 in teams for t2 in teams for d in days  }
    best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for (t1,t2) in uefa_interesting_games for d in days  }
    best_global_early = { d : pulp.LpVariable('best_global_early_'+str(d), lowBound = 0,  cat = pulp.LpContinuous) for d in days  }

    uefa_interesting_domestic_games = {c:[]  for c in NAS15}
    uefa_interesting_domestic_teams = {c:set([])  for c in NAS15}

    for (t1,t2) in uefa_games:
        if quality_of_game_dom(t1, t2, t_country[t1])>=10 and t_country[t1] in NAS15:
            uefa_interesting_domestic_games[t_country[t1]].append((t1,t2))
            uefa_interesting_domestic_teams[t_country[t1]].add(t1)
        if quality_of_game_dom(t1, t2, t_country[t2])>=10 and t_country[t2] in NAS15:
            uefa_interesting_domestic_games[t_country[t2]].append((t1,t2))
            uefa_interesting_domestic_teams[t_country[t2]].add(t2)

    for cid in confName.keys():
        if confName[cid]=="UEL":
            for t in confTeams[cid]:
                # print ("UEL", getTeamById[t])
                # model2 += homeInRound[t,1]+homeInRound[t,2]<=1 
                # model2 += homeInRound[t,7]+homeInRound[t,8]<=1 
                for d in days:
                    if getDayById[d]['day']=="2024-12-19":
                        # print (" - not gonna play home on ", getNiceDay[d])
                        model2 += home[(t,d)]==0 

        if confName[cid]=="UECL":
            for t in confTeams[cid]:
                # print ("UECL", getTeamById[t])
                model2 += homeInRound[t,1]==0 
                # model2 += homeInRound[t,2]+homeInRound[t,3]<=1 
                # model2 += homeInRound[t,4]+homeInRound[t,5]<=1 
                # model2 += homeInRound[t,6]+homeInRound[t,7]<=1 
                model2 += homeInRound[t,8]==0 
                for d in days:
                    if getDayById[d]['day'] in ["2024-09-25", "2024-09-26",  "2025-01-23",  "2025-01-30"]:
                        # print (" - not gonna play home on ", getNiceDay[d])
                        model2 += home[(t,d)]==0 


if mathModelName=="UEFA" :

    isUEL = thisSeason.nicename[:3]=="UEL"

    for sw in ["UsePosition14", "UseClassicWeekdayPatterns", "Sync1256", "UseClassicSchedules", "UseRedBlueGroups", "MaxAverageEarlyGlobal", "AvoidEarlyDomestic", "AvoidEarlyGlobal", "AvoidEarlyHighDomestic", "AvoidEarlyHighGlobal", "EachOnce", "3breaks", "firstlegs", "NoThreeTuesdaysWednesdays", "OneTuesdayOneWednesday", "everyEncounterOnceEarly"]:
        if sw not in sw_prio.keys():
            sw_prio[sw]=0
            sw_int1[sw]=0

    show_TV_markets = True

    # model2+=pairingVioTotal==0
    # Sogar hart :  Avoid playing early the match with the highest global coefficient of the night (if two matches have the same, one late is enough) à priority B

    use_classic_schedule= sw_prio['UseClassicSchedules']+sw_prio['UseClassicWeekdayPatterns']>0

    if thisSeason.nicename[:3]=="UEL" :
        for t in teams:
            # model2 += lpSum([home_time[t,d,getIdByTime["Early"]] + away_time[t,d,getIdByTime["Early"]] for d in days ]) == 3
            print ("3 early games for ", getTeamById[t])
            if use_classic_schedule:
                model2 += lpSum([home_time[t,d,getIdByTime["Early"]] + away_time[t,d,getIdByTime["Early"]]  for (r,d) in getRoundDaysByRound[2] ]) == lpSum([home_time[t,d,getIdByTime["Early"]] + away_time[t,d,getIdByTime["Early"]] for (r,d) in getRoundDaysByRound[3] ])  
                model2 += lpSum([home_time[t,d,getIdByTime["Early"]] + away_time[t,d,getIdByTime["Early"]]  for (r,d) in getRoundDaysByRound[2] ]) == lpSum([home_time[t,d,getIdByTime["Early"]] + away_time[t,d,getIdByTime["Early"]] for (r,d) in getRoundDaysByRound[5] ])  


    # for pair in pairings:
    #     t1 = pair['team1_id']            
    #     t2 = pair['team2_id'] 
    #     # print ("+++  " ,t_conference[t1] , t_conference[t2] )
    #     if t_conference[t1].name[:3] != t_conference[t2].name[:3] :
    #         print ("+++  " ,t_conference[t1] , t_conference[t2], " ",  getTeamById[t1] , getTeamById[t2])
    
    uefa_games = [ (t1,t2) for t1 in teams for t2 in teams if t1<t2 and t_conference[t1]==t_conference[t2] ]
    uefa_interesting_games = [ (t1,t2) for (t1,t2) in uefa_games  if quality_of_game(t1,t2)>4 ]

    # best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t1 in teams for t2 in teams for d in days  }
    best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for (t1,t2) in uefa_interesting_games for d in days  }
    best_global_early = { d : pulp.LpVariable('best_global_early_'+str(d), lowBound = 0,  cat = pulp.LpContinuous) for d in days  }

    uefa_interesting_domestic_games = {c:[]  for c in NAS15}
    uefa_interesting_domestic_teams = {c:set([])  for c in NAS15}

    for (t1,t2) in uefa_games:
        if quality_of_game_dom(t1, t2, t_country[t1])>=10 and t_country[t1] in NAS15:
            uefa_interesting_domestic_games[t_country[t1]].append((t1,t2))
            uefa_interesting_domestic_teams[t_country[t1]].add(t1)
        if quality_of_game_dom(t1, t2, t_country[t2])>=10 and t_country[t2] in NAS15:
            uefa_interesting_domestic_games[t_country[t2]].append((t1,t2))
            uefa_interesting_domestic_teams[t_country[t2]].add(t2)

    # print ("cool domestic  ", uefa_interesting_domestic_games)
    # for c in NAS15:
    #     print (c)
    #     for (t1,t2) in uefa_interesting_domestic_games[c]:
    #         print (getTeamById[t1], getTeamById[t2] , quality_of_game_dom(t1, t2),quality_of_game_dom(t2, t1))
    #     for t1 in uefa_interesting_domestic_teams[c]:
    #         print (getTeamById[t1])
    # exit(0)
    best_dom= {(c,t1,t2,d) : pulp.LpVariable('best_dom_'+str(c)+'_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for c in NAS15 for (t1,t2) in uefa_interesting_domestic_games[c] for d in days }
    best_dom_early = { (c,d) : pulp.LpVariable('best_dom_early_'+str(d) + '_'+str(c), lowBound = 0,  cat = pulp.LpContinuous) for d in days for c in NAS15 }


    if thisSeason.nicename[:3]=="UCL" :
        for (t1,t2) in uefa_interesting_games :
            for (r,d) in roundDays:
                model2 += best_glo[(t1,t2,d) ] <= x[(t1,t2,(r,d)) ] + x[(t2,t1,(r,d)) ] 

        for d in days:
            model2+= lpSum( [ best_glo[(t1,t2,d)] for (t1,t2) in uefa_interesting_games]) == 1
            rd =getRoundDaysByDay[d]
            for t in teams: 
                model2+= lpSum( [ quality_of_game(t1,t2)*(x[t1,t2,rd]+ x[t2,t1,rd]) for rd in getRoundDaysByDay[d] for (t1,t2) in uefa_interesting_games if t in [t1,t2]])  \
                            <= lpSum( [ best_glo[(t1,t2,d)]*quality_of_game(t1,t2) for (t1,t2) in uefa_interesting_games ])

            # Avoid the match with the highest global coefficient of the night to be played early (if two matches have the same, one late is enough) (preference)")
            for (t1,t2) in uefa_interesting_games :
                rd= getRoundDaysByDay[d][0]
                model2 += best_glo[(t1,t2,d) ] <= x_time[(t1,t2,rd,getIdByTime["Late"])] + x_time[(t2,t1,rd,getIdByTime["Late"])] + best_global_early[d]


    # TODO 
    # Avoid playing early the match with the highest domestic coefficient in NAs 1-5 if it is 10 or more à priority B
    # nas 5 fran

        for c in NAS15:
            for (t1,t2) in uefa_interesting_domestic_games[c]:
                for (r,d) in roundDays:
                    model2 += best_dom[(c,t1,t2,d) ] <= x[(t1,t2,(r,d)) ] + x[(t2,t1,(r,d)) ] 

            for d in days:
                model2+= lpSum( [ best_dom[(c,t1,t2,d)] for (t1,t2) in uefa_interesting_domestic_games[c]]) <= 1
                rd =getRoundDaysByDay[d]
                for t in uefa_interesting_domestic_teams[c]: 
                    model2+= lpSum( [ quality_of_game_dom(t1,t2,c)*(x[t1,t2,rd]+ x[t2,t1,rd]) for rd in getRoundDaysByDay[d] for (t1,t2) in uefa_interesting_domestic_games[c] if t in [t1,t2]])  \
                                <= lpSum( [ best_dom[(c,t1,t2,d)]*quality_of_game_dom(t1,t2,c) for (t1,t2) in uefa_interesting_domestic_games[c] ])

                # Avoid the match with the highest global coefficient of the night to be played early (if two matches have the same, one late is enough) (preference)")
                for (t1,t2) in uefa_interesting_domestic_games[c]:
                    rd= getRoundDaysByDay[d][0]
                    model2 += best_dom[(c,t1,t2,d)] <= x_time[(t1,t2,rd,getIdByTime["Late"])] + x_time[(t2,t1,rd,getIdByTime["Late"])] + best_dom_early[(c,d)]


    # forall (r in ROUNDS, c in NA14COUNTRIES | 1=1) do 
    #     lpSum(t1, t2 in TEAMS | COUNTRY(t1)=c ) best_dom(t1,t2,r) =1  
    #     forall (t1 in TEAMS | COUNTRY(t1)=c ) do 
    #         sum (t2 in TEAMS| GROUP(t1)=GROUP(t2) and t1<>t2 and quality_of_game_dom(t1,t2)>4 ) quality_of_game_dom(t1,t2)*(x(t1,t2,r)+x(t2,t1,r)) <= lpSum(t3,t4 in TEAMS| COUNTRY(t3)=c and GROUP(t3)=GROUP(t4) and t3<>t4) quality_of_game_dom(t3,t4)*best_dom(t3,t4,r)
    #     end-do
    # end-do


    # writeln ("Avoid the match with the highest domestic coefficient to be played early in NAs 1-5 if it is 10 or more (preference)")
    # forall (c in NA14COUNTRIES, r in ROUNDS ) do 
    #     ! Avoid the match with the highest domestic coefficient in NAs 1-5 if it is 10 or more 50
    #     !   - put the best domestic coeff match late, if value >10 

    #     forall (t1,t2 in TEAMS | exists(x(t1,t2,r)) and COUNTRY(t1)=c )
    #     if ( quality_of_game_dom(t1,t2) >=10 ) then
    #         best_dom(t1,t2,r) <= y(t1,t2,r,1)+ y(t2,t1,r,1) + best_dom_early(r,c)
    #     end-if

    
    specialObjectives= (0.01*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys()])
                        #  Avoid early matches with a global coefficient of 16 and more (60)
                        +0.6*0.2*sw_prio["AvoidEarlyGlobal"]*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys() if quality_of_game(t1,t2)>=sw_int1["AvoidEarlyGlobal"]])
                        # Maximise the average global coefficient of early matches (should stay under 16) à priority C
                        -0.1*sw_prio["MaxAverageEarlyGlobal"]*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys() if quality_of_game(t1,t2)<sw_int1["MaxAverageEarlyGlobal"]])
                        #  Avoid early matches with a domestic coefficient of 25 and more (60)
                        +0.6*0.2*sw_prio["AvoidEarlyDomestic"]*lpSum([quality_of_game(t1,t2) * x_time[(t1,t2,rd,getIdByTime["Early"])] for (t1,t2,rd) in x.keys() if quality_of_game_dom(t1,t2,t_country[t1])>=sw_int1["AvoidEarlyDomestic"] or quality_of_game_dom(t1,t2,t_country[t2])>=sw_int1["AvoidEarlyDomestic"] ])
                        -0.1*lpSum([quality_of_game(t1,t2) * best_glo[(t1,t2,d)] for (t1,t2) in uefa_interesting_games  for d in days ])
                        +0.5*0.04*sw_prio["AvoidEarlyHighDomestic"]*lpSum([best_global_early[d] for d in days ]) 
                        +5*0.04*sw_prio["AvoidEarlyHighGlobal"]*lpSum([best_dom_early[(c,d)]  for c in NAS15 for d in days ])
                        )

    model2+= standardObjectives +specialObjectives


    # todo : MORE PATTERNS
    positions = range (1,9)
    # pos= {(t,p) : pulp.LpVariable('pos_'+str(t)+'_'+str(p), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t in teams for p in positions }
    pos= {(t,p) : pulp.LpVariable('pos_'+str(t)+'_'+str(p), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t in teams for p in positions }

    for c in displayGroups.keys():
        for p in positions:
            model2+= lpSum( [ pos[t,p] for t in displayGroups[c]]) <= 1
        model2+= lpSum( [ pos[t,1]-pos[t,2] for t in displayGroups[c]]) == 0
        model2+= lpSum( [ pos[t,3]-pos[t,4] for t in displayGroups[c]]) == 0
        model2+= lpSum( [ pos[t,5]-pos[t,6] for t in displayGroups[c]]) == 0
        model2+= lpSum( [ pos[t,7]-pos[t,8] for t in displayGroups[c]]) == 0


    for (t1,t2) in uefa_games:
        # Each team has to play each opponent on a Tuesday and on a Wednesday
        print (getTeamById[t1], getTeamById[t2])
        if sw_prio['OneTuesdayOneWednesday']>0 and len([d for d in days if getWeekDay[d]=="Tue"])>0:
            model2+= lpSum([(x[t1,t2,(r,d)]+x[t2,t1,(r,d)]) for (r,d) in roundDays if getWeekDay[d]=="Tue"]) == 1

        if use_classic_schedule:
            # model2 += pos[t1,4] + pos[t2,1] - 1 <= lpSum([x[t1,t2,rd] for rd in getRoundDaysByRound[1]]) 
            # model2 += pos[t2,4] + pos[t1,1] - 1 <= lpSum([x[t2,t1,rd] for rd in getRoundDaysByRound[1]]) 

            # model2 += pos[t1,1] + pos[t2,2] - 1 <= lpSum([x[t1,t2,rd] for rd in getRoundDaysByRound[2]]) 
            # model2 += pos[t2,1] + pos[t1,2] - 1 <= lpSum([x[t2,t1,rd] for rd in getRoundDaysByRound[2]]) 

            # model2 += pos[t1,3] + pos[t2,1] - 1 <= lpSum([x[t1,t2,rd] for rd in getRoundDaysByRound[3]]) 
            # model2 += pos[t2,3] + pos[t1,1] - 1 <= lpSum([x[t2,t1,rd] for rd in getRoundDaysByRound[3]]) 

            model2 += lpSum([ pos[t,p] for t in [t1,t2] for p in [1,4] ])-1 <= lpSum([(x[t1,t2,rd]+x[t2,t1,rd]) for rd in getRoundDaysByRound[1]]) 
            model2 += lpSum([ pos[t,p] for t in [t1,t2] for p in [1,2] ])-1 <= lpSum([(x[t1,t2,rd]+x[t2,t1,rd]) for rd in getRoundDaysByRound[2]]) 
            # model2 += lpSum([ pos[t,p] for t in [t1,t2] for p in [1,3] ])-1 <= lpSum([(x[t1,t2,rd]+x[t2,t1,rd]) for rd in getRoundDaysByRound[3]]) 

            model2 += lpSum([x[t1,t2,rd]+x[t2,t1,rd] for rd in getRoundDaysByRound[1]])  == lpSum([x[t1,t2,rd]+x[t2,t1,rd] for rd in getRoundDaysByRound[5]]) 
            model2 += lpSum([x[t1,t2,rd]+x[t2,t1,rd] for rd in getRoundDaysByRound[2]])  == lpSum([x[t1,t2,rd]+x[t2,t1,rd] for rd in getRoundDaysByRound[6]]) 
            # model2 += lpSum([x[t1,t2,rd]+x[t2,t1,rd] for rd in getRoundDaysByRound[3]])  == lpSum([x[t1,t2,rd]+x[t2,t1,rd] for rd in getRoundDaysByRound[4]]) 

        # every encounter once early once late 
        if sw_prio['everyEncounterOnceEarly']>0 :                
            model2+= lpSum([( x_time[(t1,t2,rd,getIdByTime["Early"])] + x_time[(t2,t1,rd,getIdByTime["Early"])] ) for rd in roundDays ]) == 1


    # implement classic Tue/Wed patterns
    # 1 2   3 4   5 6   7 8   9 10   11 12        
    # x       x     x   x        x    x 
    if sw_prio['UseClassicWeekdayPatterns']>0:
        # print ("using red/blue")
        uefa_group_is_blue = {c : pulp.LpVariable('uefa_groupcolor_'+str(c), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for c in displayGroups.keys() }
        bluetuesdays = [ d  for d in days if  getRoundByDay[d] in [1,4,6] and getWeekDay[d]=="Tue"]
        bluewednesdays = [ d  for d in days if  getRoundByDay[d] in [2,3,5] and getWeekDay[d]=="Wed" ]
        model2+= lpSum([uefa_group_is_blue[c] for c in displayGroups.keys()]) == 0.5*len(displayGroups.keys())
        for t in teams:
            for d in bluetuesdays:
                model2+= home[(t,d)]+away[(t,d)]  ==  uefa_group_is_blue[t_conference[t].id]
            for d in bluewednesdays:
                model2+= home[(t,d)]+away[(t,d)]  ==  uefa_group_is_blue[t_conference[t].id]

    if sw_prio['Sync1256']>0:
        for (t1,t2) in uefa_games:
            for d in days:
                # groups play same days in rounds 1,2,5,6
                if getRoundByDay[d] in [1,2,5,6] + [3,4]:
                    model2+= home[(t1,d)]+away[(t1,d)]  ==  home[(t2,d)]+away[(t2,d)]  

    for t in teams:
        model2 += lpSum( [ pos[t,p] for p in positions ]) ==1
        model2 += homeInRound[t,1]==          pos[t,2]           +pos[t,4]   +pos[t,5]              +pos[t,7] 
        model2 += homeInRound[t,2]== pos[t,1]          +pos[t,3]                       + pos[t,6]               +pos[t,8]
        model2 += homeInRound[t,3]==          pos[t,2] +pos[t,3]                       + pos[t,6]   +pos[t,7]
        model2 += homeInRound[t,4]== pos[t,1]                    +pos[t,4]   +pos[t,5]                          +pos[t,8]
        model2 += homeInRound[t,5]== pos[t,1]          +pos[t,3]             +pos[t,5]              +pos[t,7]
        model2 += homeInRound[t,6]==          pos[t,2]           +pos[t,4]             + pos[t,6]               +pos[t,8]
        if use_classic_schedule or sw_prio['UsePosition14']:
            model2 += pos[t,5]==0
            model2 += pos[t,6]==0
            model2 += pos[t,7]==0
            model2 += pos[t,8]==0
            print ("forbidding " ,t, 5,6,7,8)
        # else:
        #     model2 += pos[t,1]==0
        #     model2 += pos[t,2]==0
        #     model2 += pos[t,3]==0
        #     model2 += pos[t,4]==0

    if sw_prio['NoThreeTuesdaysWednesdays']>0 :
        for t in teams:
            model2+= lpSum([ home[t,d]+away[t,d] for (r,d) in roundDays if getWeekDay[d]=="Tue" and r<=2]) == 1
            model2+= lpSum([ home[t,d]+away[t,d] for (r,d) in roundDays if getWeekDay[d]=="Tue" and r>=5]) == 1

        
    print ("EXTRA UEFA UCL/UEL run")
    writeProgress("Running special model ", thisScenario.id,10)

    print (confTeams.keys())
    print (confName)
    # for cname in ["Group A" ,"Group B" ,"UCL" , "UEL Group D" ,"UEL Group A" ,"UEL Group B" , "UEL Group C", "UEL Group E", "UEL Group F", "UEL" , "UECL" ]:
    for cname in ["Group A" ,"Group B" ,"UCL" , "UEL Group D" ,"UEL Group A" ,"UEL Group B" , "UEL" , "UECL" ]:
    # for cname in ["UCL", "UEL", "UECL"]:
        print ("TRYING ", cname)
        for c in confTeams.keys():
            # print (confName[c],cname,confName[c]==cname)
            if confName[c]==cname :
                print ()
                print ()
                print (confName[c])
                print ("confTeams" , confTeams[c])
                for p in positions:
                    for t in confTeams[c]:                 
                        pos[t,p].cat = pulp.LpInteger

                if runMode!='Improve' and False:
                    if solver == "CBC":
                        model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
                    elif solver == "Gurobi":
                        model2.solve(GUROBI(MIPGap=0.2, TimeLimit=120, msg=1))
                    else:
                        model2.solve(XPRESS(msg=1,maxSeconds=60, keepFiles=True))

                    # posTeam = { p  : t for p in positions for t in confTeams[c] if pos[(t,p)].value()>0.9 } 
                    # print ("posTeam",posTeam)
                    for p in positions:                
                        for t in confTeams[c]:                 
                            if pos[(t,p)].value()>0.9:
                                model2 += pos[(t,p)] == pos[(t,p)].value()
                                print(p,t)

                    for (t1,t2) in uefa_games:
                        if t1 in confTeams[c]:
                            for rd in roundDays:
                                if isUEL:
                                    makeIntVar(x_time[t1,t2,rd,getIdByTime["Early"]])
                                else:
                                    makeIntVar(x[t1,t2,rd])


                    # if solver == "CBC":
                    #     model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
                    # elif solver == "Gurobi":
                    #     model2.solve(GUROBI(MIPGap=0.0, TimeLimit=120, msg=1))
                    # else:
                    #     model2.solve(XPRESS(msg=1,maxSeconds=60, keepFiles=True))

                    # for (t1,t2) in uefa_games:
                    #     if t1 in confTeams[c]:
                    #         for rd in roundDays:
                    #             if getVal(x[t1,t2,rd]):
                    #                 setLB(x[t1,t2,rd],1)

    # model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
    # model2+= lpSum( [ - pos[t,p] for p in positions ])

    # if solver == "CBC":
    #     model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
    # elif solver == "Gurobi":
    #     model2.solve(GUROBI(MIPGap=0.0, TimeLimit=120,msg=1))
    # else:
    #     model2.solve(XPRESS(msg=1,maxSeconds = 80, keepFiles=True))

    # for (t,p) in pos.keys():
    #     if pos[(t,p)].value()>0.9:
    #         print ("position ", p , " for " , t)
    #     model2 += pos[(t,p)] == pos[(t,p)].value()

    # best_glo= {(t1,t2,d) : pulp.LpVariable('best_glo_'+str(t1)+'_'+str(t2)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) 
    if False:
        for d in days:
            print (getNiceDay[d] )
            for (t1,t2) in uefa_interesting_games:
                if best_glo[(t1,t2,d)].value()>0.01:
                    print ("  Best GLO ",quality_of_game(t1,t2), getTeamById[t1] , getTeamById[t2] ,  0.01*int(100*best_glo[(t1,t2,d)].value()) )
            print ()
            for c in NAS15:
                print ( "checking "  , c, uefa_interesting_domestic_games[c] )
                for (t1,t2) in uefa_interesting_domestic_games[c]:
                    print ( " --  "  , getTeamById[t1] , getTeamById[t2] )
                    print ( " ---  "  , (c,t1,t2,d) in best_dom.keys() )
                    print ( " ----  "  , best_dom[(c,t1,t2,d)].value() , best_dom[(c,t1,t2,d)].value() ==None )
                    if not (c,t1,t2,d) in best_dom.keys() :
                        print (c,t1,t2,d, " not in " , best_dom)
                    if best_dom[(c,t1,t2,d)].value() and best_dom[(c,t1,t2,d)].value()>0.01:
                        print ("  Best DOM ",c ,getTeamById[t1] , getTeamById[t2] ,  0.01*int(100*best_dom[(c,t1,t2,d)].value()))


if mathModelName=="EuroLeague Basketball"  :
    show_TV_markets = True

    day2pairs =[ (d1,d2) for d1 in days for d2 in days if getDateTimeDay[d2]-getDateTimeDay[d1] ==datetime.timedelta(days=2)  and getRoundByDay[d1] <37]
    # trip_ebl= {(t,d) : pulp.LpVariable('trip_'+str(t)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t in teams for (d,d2) in day2pairs}

    if thisSeason.name=="2023":
        day2pairs = [ (d1,d2) for (d1,d2) in day2pairs if getRoundByDay[d1]!=26 ]

    print ("day2pairs", day2pairs)

    doubleWeekendDays = { d1 : [d1,d2,d3,d4] for (d1,d2) in day2pairs for (d3,d4) in day2pairs if getDateTimeDay[d3]-getDateTimeDay[d1] ==datetime.timedelta(days=1)  }
    print ("doubleWeekendDays", doubleWeekendDays)

    criticalDayPairs = [ (d1,d2) ]

    getDW = { getDayById[dw]["round"] : dw for dw in doubleWeekendDays.keys()  }
    
    elb_rounds  = getDW.keys()
    elb_rounds1 = [ r for r in elb_rounds if r <= nRounds1] 
    elb_rounds2 = [ r for r in elb_rounds if r > nRounds1] 

    t_bl1= { t: [r for r in rounds if r<=17 and t_blocked_at[(t,r)]==0 ] for t in teams  }
    t_bl2= { t: [r for r in rounds if r>17 and t_blocked_at[(t,r)]==0 ] for t in teams  }
    t_bl3= { t: [ t_blocked_at[t,r]+t_blocked_at[t,r+1] for r in elb_rounds ] for t in teams  }
    for t in teams: 
        print (getTeamById[t], "\t", t_bl3[t] , len(t_bl1[t]) , len(t_bl2[t]) , t_bl1[t] , t_bl2[t] )

    criticalAvailabilities = {r: [] for r in elb_rounds}
    for d1 in doubleWeekendDays.keys():
        dd = doubleWeekendDays[d1]       
        for day in [dd[0],dd[3]]:
            criticalAvailabilities[ getRoundByDay[day] ] =[t for t in teams if available_days[t,day]==0]
    
    canTravel={t:  elb_rounds for t in teams }

    for r in elb_rounds :
        print ("criticalAvailabilities", r, [ getTeamById[t] for t in criticalAvailabilities[r]])

    # closeTeams_EBL_raw={'ALBA Berlin': ['FC Bayern Munich', 'Crvena Zvezda mts Belgrade', 'Zalgiris Kaunas', 'LDLC ASVEL Villeurbanne', 'AX Armani Exchange Milan', 'Zenit St. Petersburg', 'CSKA Moscow', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'FC Barcelona', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul', 'AS Monaco'], 'Anadolu Efes Istanbul': ['Maccabi FOX Tel Aviv', 'Fenerbahce Beko Istanbul', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'CSKA Moscow', 'Crvena Zvezda mts Belgrade', 'UNICS Kazan', 'Zalgiris Kaunas', 'ALBA Berlin', 'FC Bayern Munich', 'AX Armani Exchange Milan'], 'AS Monaco': ['LDLC ASVEL Villeurbanne', 'AX Armani Exchange Milan', 'FC Bayern Munich', 'FC Barcelona', 'Real Madrid', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'TD Systems Baskonia Vitoria-Gasteiz'], 'AX Armani Exchange Milan': ['LDLC ASVEL Villeurbanne', 'FC Bayern Munich', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'FC Barcelona', 'Real Madrid', 'TD Systems Baskonia Vitoria-Gasteiz', 'AS Monaco', 'Zalgiris Kaunas'], 'Crvena Zvezda mts Belgrade': ['ALBA Berlin', 'FC Bayern Munich', 'AX Armani Exchange Milan', 'LDLC ASVEL Villeurbanne', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'Zalgiris Kaunas', 'Maccabi FOX Tel Aviv', 'FC Barcelona', 'CSKA Moscow', 'AS Monaco'], 'CSKA Moscow': ['Zenit St. Petersburg', 'Zalgiris Kaunas', 'FC Bayern Munich', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'UNICS Kazan', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul'], 'FC Barcelona': ['Real Madrid', 'TD Systems Baskonia Vitoria-Gasteiz', 'AS Monaco', 'LDLC ASVEL Villeurbanne', 'AX Armani Exchange Milan', 'FC Bayern Munich', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus'], 'FC Bayern Munich': ['ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Zalgiris Kaunas', 'LDLC ASVEL Villeurbanne', 'AX Armani Exchange Milan', 'AS Monaco', 'Zenit St. Petersburg', 'CSKA Moscow', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'FC Barcelona', 'Real Madrid', 'TD Systems Baskonia Vitoria-Gasteiz', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul'], 'Fenerbahce Beko Istanbul': ['Maccabi FOX Tel Aviv', 'Anadolu Efes Istanbul', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'CSKA Moscow', 'UNICS Kazan', 'Crvena Zvezda mts Belgrade', 'Zalgiris Kaunas', 'ALBA Berlin', 'FC Bayern Munich', 'AX Armani Exchange Milan'], 'LDLC ASVEL Villeurbanne': ['AX Armani Exchange Milan', 'FC Bayern Munich', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'FC Barcelona', 'Real Madrid', 'TD Systems Baskonia Vitoria-Gasteiz', 'AS Monaco', 'Zalgiris Kaunas'], 'Maccabi FOX Tel Aviv': ['Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'Crvena Zvezda mts Belgrade'], 'Olympiacos Piraeus': ['Panathinaikos OPAP Athens', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul', 'Maccabi FOX Tel Aviv', 'Crvena Zvezda mts Belgrade', 'AX Armani Exchange Milan', 'FC Bayern Munich', 'ALBA Berlin', 'FC Barcelona', 'LDLC ASVEL Villeurbanne', 'AS Monaco'], 'Panathinaikos OPAP Athens': ['Olympiacos Piraeus', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul', 'Maccabi FOX Tel Aviv', 'Crvena Zvezda mts Belgrade', 'AX Armani Exchange Milan', 'FC Bayern Munich', 'ALBA Berlin', 'FC Barcelona', 'LDLC ASVEL Villeurbanne', 'AS Monaco'], 'Real Madrid': ['TD Systems Baskonia Vitoria-Gasteiz', 'FC Barcelona', 'LDLC ASVEL Villeurbanne', 'AX Armani Exchange Milan', 'FC Bayern Munich', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus', 'AS Monaco'], 'TD Systems Baskonia Vitoria-Gasteiz': ['Real Madrid', 'FC Barcelona', 'AS Monaco', 'LDLC ASVEL Villeurbanne', 'AX Armani Exchange Milan', 'FC Bayern Munich', 'ALBA Berlin', 'Crvena Zvezda mts Belgrade', 'Panathinaikos OPAP Athens', 'Olympiacos Piraeus'], 'UNICS Kazan': ['CSKA Moscow', 'Zenit St. Petersburg', 'Zalgiris Kaunas', 'Crvena Zvezda mts Belgrade', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul'], 'Zalgiris Kaunas': ['Zenit St. Petersburg', 'CSKA Moscow', 'UNICS Kazan', 'ALBA Berlin', 'FC Bayern Munich', 'AX Armani Exchange Milan', 'LDLC ASVEL Villeurbanne', 'Crvena Zvezda mts Belgrade', 'Anadolu Efes Istanbul', 'Fenerbahce Beko Istanbul'], 'Zenit St. Petersburg': ['CSKA Moscow', 'UNICS Kazan', 'Zalgiris Kaunas', 'ALBA Berlin', 'FC Bayern Munich']}        
    closeTeams_EBL_raw= {
        'ALBA BERLIN': ['FC BAYERN MUNICH','CRVENA ZVEZDA BELGRADE', 'PARTIZAN BELGRADE', 
            'ZALGIRIS KAUNAS', 'LDLC ASVEL VILLEURBANNE', 'VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN',
            'AS MONACO','PANATHINAIKOS OPAP ATHENS' , 'OLYMPIACOS PIRAEUS','ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL',], 
        'ANADOLU EFES ISTANBUL': ['MACCABI PLAYTIKA TEL AVIV', 'FENERBAHCE BEKO ISTANBUL', 'OLYMPIACOS PIRAEUS', 
            'PANATHINAIKOS OPAP ATHENS', 'PARTIZAN BELGRADE', 'CRVENA ZVEZDA BELGRADE', 
            'ZALGIRIS KAUNAS', 'ALBA BERLIN','FC BAYERN MUNICH', 'VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN'], 
        'AS MONACO': ['LDLC ASVEL VILLEURBANNE', 'VIRTUS SEGAFREDO BOLOGNA','EA7 EMPORIO ARMANI MILAN', 'FC BAYERN MUNICH', 'FC BARCELONA',
            'REAL MADRID', 'ALBA BERLIN', 'PARTIZAN BELGRADE', 'CRVENA ZVEZDA BELGRADE','PANATHINAIKOS OPAP ATHENS' , 'OLYMPIACOS PIRAEUS', 'BASKONIA VITORIA-GASTEIZ', 'VALENCIA BASKET', ], 
        'EA7 EMPORIO ARMANI MILAN': ['VIRTUS SEGAFREDO BOLOGNA','LDLC ASVEL VILLEURBANNE', 'FC BAYERN MUNICH', 'ALBA BERLIN', 'CRVENA ZVEZDA BELGRADE', 'PARTIZAN BELGRADE', 
            'ZALGIRIS KAUNAS','PANATHINAIKOS OPAP ATHENS' , 'OLYMPIACOS PIRAEUS', 'FC BARCELONA', 'REAL MADRID', 'BASKONIA VITORIA-GASTEIZ', 'VALENCIA BASKET','AS MONACO'], 
        'CRVENA ZVEZDA BELGRADE': [ 'PARTIZAN BELGRADE', 'ALBA BERLIN', 'FC BAYERN MUNICH', 'VIRTUS SEGAFREDO BOLOGNA',  'EA7 EMPORIO ARMANI MILAN', 
            'LDLC ASVEL VILLEURBANNE','ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL', 'OLYMPIACOS PIRAEUS', 'PANATHINAIKOS OPAP ATHENS','ZALGIRIS KAUNAS','MACCABI PLAYTIKA TEL AVIV' , 'AS MONACO'], 
        'FC BARCELONA': ['REAL MADRID', 'BASKONIA VITORIA-GASTEIZ', 'VALENCIA BASKET', 'AS MONACO', 'EA7 EMPORIO ARMANI MILAN', 'LDLC ASVEL VILLEURBANNE',  'VIRTUS SEGAFREDO BOLOGNA',
            'PARTIZAN BELGRADE', 'CRVENA ZVEZDA BELGRADE', "FC BAYERN MUNICH"], 
        'FC BAYERN MUNICH': ['ALBA BERLIN', 'CRVENA ZVEZDA BELGRADE',  'PARTIZAN BELGRADE','ZALGIRIS KAUNAS',
            'AS MONACO', 'EA7 EMPORIO ARMANI MILAN', 'LDLC ASVEL VILLEURBANNE', 'VIRTUS SEGAFREDO BOLOGNA', 'PANATHINAIKOS OPAP ATHENS' , 'OLYMPIACOS PIRAEUS',
            'FC BARCELONA', 'REAL MADRID', 'BASKONIA VITORIA-GASTEIZ', 'VALENCIA BASKET','ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL'  ], 
        'FENERBAHCE BEKO ISTANBUL': ['MACCABI PLAYTIKA TEL AVIV', 'ANADOLU EFES ISTANBUL', 'OLYMPIACOS PIRAEUS', 
            'PANATHINAIKOS OPAP ATHENS', 'PARTIZAN BELGRADE', 'CRVENA ZVEZDA BELGRADE', 
            'ZALGIRIS KAUNAS', 'ALBA BERLIN','FC BAYERN MUNICH', 'VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN'], 
        'LDLC ASVEL VILLEURBANNE': [ 'AS MONACO', 'VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN','FC BAYERN MUNICH','ALBA BERLIN',
            'PARTIZAN BELGRADE', 'CRVENA ZVEZDA BELGRADE','PANATHINAIKOS OPAP ATHENS' , 'OLYMPIACOS PIRAEUS', 
            'FC BARCELONA',   'REAL MADRID', 'VALENCIA BASKET', 'BASKONIA VITORIA-GASTEIZ',  ], 
        'MACCABI PLAYTIKA TEL AVIV': ['ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL', 'PARTIZAN BELGRADE', 'CRVENA ZVEZDA BELGRADE','PANATHINAIKOS OPAP ATHENS' , 'OLYMPIACOS PIRAEUS', ], 
        'OLYMPIACOS PIRAEUS': [ 'PANATHINAIKOS OPAP ATHENS', 'ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL', 'MACCABI PLAYTIKA TEL AVIV',
                'CRVENA ZVEZDA BELGRADE',  'PARTIZAN BELGRADE','VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN','FC BAYERN MUNICH',
                'ALBA BERLIN','LDLC ASVEL VILLEURBANNE','AS MONACO'], 
        'PANATHINAIKOS OPAP ATHENS': [ 'OLYMPIACOS PIRAEUS', 'ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL', 'MACCABI PLAYTIKA TEL AVIV',
                'CRVENA ZVEZDA BELGRADE',  'PARTIZAN BELGRADE','VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN','FC BAYERN MUNICH',
                'ALBA BERLIN','LDLC ASVEL VILLEURBANNE','AS MONACO'], 
        'PARTIZAN BELGRADE' : [ 'CRVENA ZVEZDA BELGRADE', 'PARTIZAN BELGRADE', 'ALBA BERLIN', 'FC BAYERN MUNICH', 'VIRTUS SEGAFREDO BOLOGNA',  'EA7 EMPORIO ARMANI MILAN', 
            'LDLC ASVEL VILLEURBANNE','ANADOLU EFES ISTANBUL', 'FENERBAHCE BEKO ISTANBUL', 'OLYMPIACOS PIRAEUS', 'PANATHINAIKOS OPAP ATHENS','ZALGIRIS KAUNAS','MACCABI PLAYTIKA TEL AVIV' , 'AS MONACO'], 
        'REAL MADRID': ['BASKONIA VITORIA-GASTEIZ', 'FC BARCELONA','VALENCIA BASKET',  'LDLC ASVEL VILLEURBANNE', 
                'VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN','FC BAYERN MUNICH','CRVENA ZVEZDA BELGRADE', 'PARTIZAN BELGRADE','AS MONACO' ], 
        'BASKONIA VITORIA-GASTEIZ': [ 'REAL MADRID', 'FC BARCELONA', 'VALENCIA BASKET','LDLC ASVEL VILLEURBANNE', 'VIRTUS SEGAFREDO BOLOGNA',
                'EA7 EMPORIO ARMANI MILAN', 'AS MONACO','FC BAYERN MUNICH' ], 
        'VALENCIA BASKET': [ 'REAL MADRID', 'FC BARCELONA', 'BASKONIA VITORIA-GASTEIZ','LDLC ASVEL VILLEURBANNE', 'VIRTUS SEGAFREDO BOLOGNA',
                'EA7 EMPORIO ARMANI MILAN', 'AS MONACO','FC BAYERN MUNICH' ], 
        'VIRTUS SEGAFREDO BOLOGNA': [ 'REAL MADRID', 'FC BARCELONA','VALENCIA BASKET' , 'BASKONIA VITORIA-GASTEIZ','LDLC ASVEL VILLEURBANNE', 
                'EA7 EMPORIO ARMANI MILAN', 'AS MONACO','FC BAYERN MUNICH' , 'ALBA BERLIN','CRVENA ZVEZDA BELGRADE',  'PARTIZAN BELGRADE', 'OLYMPIACOS PIRAEUS', 'PANATHINAIKOS OPAP ATHENS'], 
        'ZALGIRIS KAUNAS': ['ALBA BERLIN','FC BAYERN MUNICH','VIRTUS SEGAFREDO BOLOGNA', 'EA7 EMPORIO ARMANI MILAN','CRVENA ZVEZDA BELGRADE',  'PARTIZAN BELGRADE','ANADOLU EFES ISTANBUL', 
            'FENERBAHCE BEKO ISTANBUL', 'LDLC ASVEL VILLEURBANNE','AS MONACO']
    }

    closeTeams_EBL= { getTeamIdByName[tn] : [ getTeamIdByName[tn2] for tn2 in closeTeams_EBL_raw[tn] ] for tn in closeTeams_EBL_raw.keys() }
    
    singleTrips_EBL = [ (t1,t2,r)  for t2 in teams for t1 in closeTeams_EBL[t2] for r in elb_rounds ] 

    print(elb_rounds)
    
    # for t2 in teams: 
        # for t1 in closeTeams_EBL[t2]:
            # # if not t2 in closeTeams_EBL[t1]:
                # # print (getTeamById[t2] ," not in list of ", getTeamById[t1])
            # for r in canHostSingle[t1]:
                # print (" single trip in round " ,r , " : ", t1 , t2 , "possible" )
                
    print (len (singleTrips_EBL) , " single trips")
        

    conferences_ebl  = [c for c in Conference.objects.filter(scenario=s2,regional=False).exclude(name='REOPT')]
    neighbors_ebl  = [c for c in Conference.objects.filter(scenario=s2,regional=True).exclude(name='REOPT') ]

    print ("conferences_ebl", conferences_ebl)
    print ("neighbors_ebl", neighbors_ebl)

    getConference={}
    getNeighborId={}
    for c in conferences_ebl:
        if len(c.teams.all())>3:
            for t in c.teams.filter(active=True):
                getConference[t.id]=c.id
        else: 
            for (d1,d2) in day2pairs:
                print ("forbid games for " , c.name, " in days" , d1,d2)
                # model2 += lpSum( [x[t1.id, t2.id, rd] for t1 in c.teams.all() for t2 in c.teams.all() for rd in getRoundDaysByDay[d1]+getRoundDaysByDay[d2] if t1.id!=t2.id ]) == 0

    

    getTeamsOfNeighbor={}
    getNameOfNeighbor={}
    getConfId={}
    for c in neighbors_ebl:
        getTeamsOfNeighbor[c.id]=[]
        print (c.id, c.name)
        getConfId[c.name]=c.id
        getNameOfNeighbor[c.id]=c.name
        for t in c.teams.filter(active=True):
            getNeighborId[t.id]=c.id
            getTeamsOfNeighbor[c.id].append(t.id)
            print ( " - " , t.id , "\t",canTravel[t.id], "\t", " " , t.name)
    # otherConference= { t: [ t2 for t2 in teams if getConference[t]!=getConference[t2] ] for t in teams }
    # otherNeighbor= { t: [ t2 for t2 in teams if getNeighborId[t]!=getNeighborId[t2] ] for t in teams if t in getNeighborId.keys()}
    
    # print ("otherConference = ", otherConference)
    # print ("otherNeighbor = ", otherNeighbor)


    getConfOfNeighbor={}
    getNeighborsInConf={ c : set([]) for c in set(getConference.values()) }
    for t in teams :
        # print (getTeamById[t])
        # print ("-",getNeighborId[t])
        # print ("-",getConference[t])

        
        getConfOfNeighbor[getNeighborId[t]]=getConference[t]
        getNeighborsInConf[getConference[t]].add(getNeighborId[t])
        print (getConference[t],getNeighborId[t], getTeamById[t] )

    # tripCands= 

    print ("getConfOfNeighbor = ", getConfOfNeighbor)
    print ("getNeighborsInConf = ", getNeighborsInConf)
            
    possTrips = {}

    for g1 in neighbors_ebl:
        for g2 in neighbors_ebl:
            if getConfOfNeighbor[g1.id]!=getConfOfNeighbor[g2.id] :
                for t1 in getTeamsOfNeighbor[g1.id]:
                    for t2 in getTeamsOfNeighbor[g2.id]:
                        for r in  elb_rounds:
                            if (t2,r,g1.id) not in possTrips.keys():
                                possTrips[t2,r,g1.id]=[]
                            possTrips[t2,r,g1.id].append(t1)

    
    remtrg= [ trg for trg in possTrips.keys() if len(possTrips[trg])==1]

    for trg in remtrg :
        del possTrips[trg]

    # for trg in possTrips.keys():
        # print ("++" , trg, possTrips[trg])

    trips_ebl = [ (t1,t2,r) for (t2,r,g) in possTrips.keys() for t1 in possTrips[(t2,r,g)]]
    
    games_ebl= set([(t1,t2) for (t1,t2,r) in trips_ebl + singleTrips_EBL ])
    
    far_teams = [(t1,t2) for (t1,t2) in games_ebl if t1 not in closeTeams_EBL[t2]]
    far_teams = {t : [ t1 for (t1,t2) in far_teams if t2==t]  for t in teams} 
    
    # print (far_games)
    
    # for t in teams:
        # print (getTeamById[t], " :")
        # for t2  in far_games[t]:
            # print (" -  " , getTeamById[t2])                        
    

    fixed_travels= []
    # fixed_travels= [(283, 15, 'A'), (296, 6, 'A'), (289, 24, 'A'), (293, 31, 'A'), (299, 20, 'A'), (287, 3, 'A'), (288, 10, 'A'), (297, 24, 'A'), (281, 24, 'B'), (283, 6, 'B'), (289, 15, 'B'), (293, 3, 'B'), (299, 6, 'B'), (297, 20, 'B'), (281, 6, 'C'), (296, 31, 'C'), (287, 10, 'C'), (288, 24, 'C'), (286, 20, 'D'), (291, 31, 'D'), (295, 24, 'D'), (282, 20, 'D'), (290, 3, 'D'), (298, 10, 'D'), (294, 15, 'D'), (300, 20, 'D'), (286, 6, 'E'), (291, 3, 'E'), (295, 10, 'E'), (282, 24, 'E'), (298, 31, 'E'), (284, 20, 'E'), (294, 3, 'E'), (300, 10, 'E'), (290, 15, 'F'), (284, 3, 'F')]
    # fixed_travels= [ (getTeamById[t2],r,g)  for (t2,r,g) in fixed_travels]
    # fixed_travels= [('Zenit St. Petersburg', 24, 'A'), ('CSKA Moscow', 10, 'A'), ('Fenerbahce Beko Istanbul', 31, 'A'), ('Anadolu Efes Istanbul', 20, 'A'), ('Panathinaikos OPAP Athens', 3, 'A'), ('Olympiacos Piraeus', 24, 'A'), ('Crvena Zvezda mts Belgrade', 10, 'A'), ('UNICS Kazan', 20, 'B'), ('Zenit St. Petersburg', 15, 'B'), ('CSKA Moscow', 6, 'B'), ('Maccabi FOX Tel Aviv', 3, 'B'), ('Anadolu Efes Istanbul', 3, 'B'), ('Olympiacos Piraeus', 31, 'B'), ('Crvena Zvezda mts Belgrade', 6, 'B'), ('UNICS Kazan', 24, 'C'), ('Maccabi FOX Tel Aviv', 24, 'C'), ('Fenerbahce Beko Istanbul', 10, 'C'), ('Panathinaikos OPAP Athens', 10, 'C'), ('Real Madrid', 6, 'D'), ('TD Systems Baskonia Vitoria-Gasteiz', 6, 'D'), ('LDLC ASVEL Villeurbanne', 20, 'D'), ('AX Armani Exchange Milan', 10, 'D'), ('FC Bayern Munich', 3, 'D'), ('ALBA Berlin', 10, 'D'), ('Real Madrid', 31, 'E'), ('TD Systems Baskonia Vitoria-Gasteiz', 15, 'E'), ('FC Barcelona', 6, 'E'), ('AS Monaco', 10, 'E'), ('LDLC ASVEL Villeurbanne', 24, 'E'), ('AX Armani Exchange Milan', 31, 'E'), ('Zalgiris Kaunas', 6, 'E'), ('ALBA Berlin', 20, 'E'), ('FC Barcelona', 15, 'F'), ('AS Monaco', 24, 'F'), ('Zalgiris Kaunas', 3, 'F'), ('FC Bayern Munich', 15, 'F')]
    
    print (len (games_ebl))

    xxx_travel_rounds = sorted( list(elb_rounds) + [ r+1 for r in elb_rounds ])

    xxx_rounds = xxx_travel_rounds
    # xxx_rounds = rounds
    # xxx_rounds = sorted( list(elb_rounds) + [ r+1 for r in elb_rounds ])

    travel_to_cluster= {(t2,r,g) : pulp.LpVariable('travel_to_cluster_'+str(t2)+'_'+str(r)+'_'+str(g), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for (t2,r,g) in possTrips.keys()}

    if runMode=="New" and len(fixedRounds)==0: 
            
        model8 = pulp.LpProblem(f"{PULP_FOLDER}/League_Scheduling_Model_--_Assign_EBL_Trips_"+str(thisScenario.id), pulp.LpMinimize)             

        xxx = { (t1,t2,r) :  pulp.LpVariable('xxx_'+str(t1)+'_'+str(t2)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for t1 in teams for t2 in teams for r in xxx_rounds }
        toomany = { (t1,r) :  pulp.LpVariable('toomany_'+str(t1)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpContinuous) for t1 in teams for r in rounds }

        for (t1,t2,r) in (singleTrips_EBL+trips_ebl) : 
            xxx[(t1,t2,r)].cat=pulp.LpInteger
            xxx[(t1,t2,r)].upBound=1
    
        home_ebl = { (t1,r) : lpSum([ xxx[(t1,t2,r)] for t2 in teams ]) for t1 in teams for r in xxx_rounds}
        away_ebl = { (t2,r) : lpSum([ xxx[(t1,t2,r)] for t1 in teams ]) for t2 in teams for r in xxx_rounds}
            
        print (home_ebl.keys())

        for t1 in teams:
            for t2 in teams:
                model8+= lpSum([ xxx[(t1,t2,r)]+xxx[(t2,t1,r)] for r in xxx_rounds if r<=17 ]) <= 1
                model8+= lpSum([ xxx[(t1,t2,r)]+xxx[(t2,t1,r)] for r in xxx_rounds if r>=18 ]) <= 1
    
                model8+=lpSum([ xxx[(t1,t2,r)] for (t1,t2) in games_ebl for r in xxx_rounds  ])

        # do not visit two teams in doubleweeks which would result in a B2B
        for r in elb_rounds:
            for t in teams:
                lhs1 = [ xxx[(t1,t,r)] for t1 in criticalAvailabilities[r]  if t!=t1]
                lhs2=  [ xxx[(t2,t,r+1)] for t2 in criticalAvailabilities[r+1]  if t!=t2]
                if len(lhs1)*len(lhs2)>0:
                    model8+= lpSum( lhs1+lhs2 )  <= 1 + toomany[(t,r)]
                if t in criticalAvailabilities[r] and len(lhs2)>0: 
                    model8+=  home_ebl[(t,r)] + lpSum( lhs2 ) <= 1 + toomany[(t,r)]
                if t in criticalAvailabilities[r+1] and len(lhs1)>0: 
                    model8+=  home_ebl[(t,r+1)] + lpSum( lhs1 ) <= 1 + toomany[(t,r)]
                if t in criticalAvailabilities[r] and t in criticalAvailabilities[r+1] : 
                    model8+=  home_ebl[(t,r)] + home_ebl[(t,r+1)] <= 1 + toomany[(t,r)]

        for t1 in teams:                                                
            for r in xxx_rounds:
                model8+=xxx[(t1,t1,r)]==0
                # one game a day1
                model8+= home_ebl[(t1,r)] + away_ebl[(t1,r)] ==1 
            # half of the games played at home
            if len(xxx_rounds) < len(rounds):
                model8+= lpSum ( [ home_ebl[(t1,r)] for r in xxx_rounds ])  == 0.5*len(xxx_rounds)  

                            
        for (t1,t2) in games_ebl:
            model8+=lpSum([ xxx[(t1,t2,r)] for r in xxx_rounds ]) <=1
            if (t2,t1) in games_ebl and t1<t2:
                model8+=lpSum([ xxx[(t1,t2,r)]+ xxx[(t2,t1,r)] for r in xxx_rounds if r<=17 ]) <=1
                model8+=lpSum([ xxx[(t1,t2,r)]+ xxx[(t2,t1,r)] for r in xxx_rounds if r>17 ])  <=1
                model8+=lpSum([ xxx[(t1,t2,r)]+ xxx[(t2,t1,r)] for r in xxx_rounds if  r>=15  and r<=20 ]) <=1

        # model8+=lpSum([ xxx[(t1,t2,r)] for (t1,t2) in games_ebl for r in xxx_rounds  ])
        
        # no_travel_elb = [3,27,31]
        # no_travel_elb = [27]
        # no_travel_elb = [ ("AX Armani Exchange Milan", 13 ) ,  ("AX Armani Exchange Milan", 9 ) ,   ("Baskonia Vitoria-Gasteiz", 9 ) ,
                            # ("Partizan Nis Belgrade", 3 ) , ("ALBA Berlin", 3 ) ,("Crvena Zvezda mts Belgrade", 22) , ("ALBA Berlin", 22 ) , 
                            # ("ALBA Berlin", 27 )  ]
        # # no_travel_elb = [ ("AX Armani Exchange Milan", 13 ) ,  ("AX Armani Exchange Milan", 9 ) ,   ("Baskonia Vitoria-Gasteiz", 9 ) , ("Partizan Nis Belgrade", 3 ) , ("ALBA Berlin", 3 ) ,("Crvena Zvezda mts Belgrade", 22) , ("ALBA Berlin", 22 ) , ("ALBA Berlin", 27 ), ("Anadolu Efes Istanbul", 27 ) ]
        # no_travel_elb = [ ("AX Armani Exchange Milan", 13 ) ,  ("AX Armani Exchange Milan", 9 ) ,   ("Baskonia Vitoria-Gasteiz", 9 ) , 
                            # ("Partizan Nis Belgrade", 3 ) , ("ALBA Berlin", 3 ) ,("Crvena Zvezda mts Belgrade", 22) , ("ALBA Berlin", 22 ) ,     
                            # ("Anadolu Efes Istanbul", 27 ), ("Zalgiris Kaunas", 27 ) ]
        no_travel_elb = []
        fixed_home = []
        fixed_min_home = []
        fixed_home += [('ALBA BERLIN', [2,8,12,27]), ('REAL MADRID', [3,4,5,7,9,10,14,16]), ('ZALGIRIS KAUNAS', [8,9,13,16,30,31])]
        fixed_min_home += [ ('ZALGIRIS KAUNAS', [4,8,9,13,16] ,4)]
        for r in elb_rounds:
            for t in teams:   
                if getTeamById[t] not in [ 'ZALGIRIS KAUNAS'] :
                    ss1 = sum ( t_blocked_at[t,r2] for r2 in [r-2,r-1]  )
                    ss2 = sum ( t_blocked_at[t,r2] for r2 in [r-1,r+2]  )
                    ss3 = sum ( t_blocked_at[t,r2] for r2 in [r+2,r+3]  )
                    if r>3 and sum ( t_blocked_at[t,r2] for r2 in [r-3,r-2,r-1])==3:
                        fixed_home.append((getTeamById[t],[r]))
                    if r+4<=nRounds and sum ( t_blocked_at[t,r2] for r2 in [r+2,r+3,r+4])==3:
                        fixed_home.append((getTeamById[t],[r+1]))
                        
                    print (r, ss1,ss2,ss3, getTeamById[t])
                    urt = max( t_blocked_at[t,r-2]+t_blocked_at[t,r-1] ,  t_blocked_at[t,r-1]+t_blocked_at[t,r+2] ,  t_blocked_at[t,r+2]+t_blocked_at[t,r+3]  )
                    if urt ==2 :
                        print ("DO NOT TRAVEL ")
                        no_travel_elb.append((getTeamById[t],r))

        print ("no_travel_elb",no_travel_elb)
        print ("fixed_home",fixed_home)

        split_travel= True
        travel_elb ={}
        for t in teams:             
            # every team travels to other clusters twice
            model8+= lpSum( [travel_to_cluster[ (t2,r,g)]  for (t2,r,g) in possTrips.keys() if t==t2 ])== 2  
            for r in elb_rounds:
                travel_elb[(t,r)] = lpSum( [travel_to_cluster[ (t2,r2,g)]  for (t2,r2,g) in possTrips.keys() if t==t2 and r==r2 ]) 
                print ("TRAVEL 1 ", t, r, travel_elb[(t,r)])
                model8+= away_ebl[(t,r)] + away_ebl[(t,r+1)] <= 1 + travel_elb[(t,r)]  
                model8+= lpSum([ xxx[(t1,t,r)] for t1 in far_teams[t] ]) <= travel_elb[(t,r)] 
                model8+= lpSum([ xxx[(t1,t,r+1)] for t1 in far_teams[t] ]) <= travel_elb[(t,r)]

            # model8+=  travel_elb[(t,9)] + travel_elb[(t,13)] == 1
            # model8+=  travel_elb[(t,18)] + travel_elb[(t,22)] == 1
            if split_travel:
                model8+=lpSum([ travel_elb[(t,r)] for r in elb_rounds if r<=17 ]) ==1

        for (t,rr) in  fixed_home:
            for r in rr:
                if r in elb_rounds:
                    model8+= home_ebl[(getTeamIdByName[t],r)]==1  
                    
        for (t,rr,m) in  fixed_min_home:
            model8+= lpSum( [home_ebl[(getTeamIdByName[t],r)] for r in rr])>=m  
                                    
        for (t,r) in no_travel_elb :
            model8+=  travel_elb[(getTeamIdByName[t],r)] ==0
            print ("no travel", getTeamIdByName[t],t,r)
            
        for (t2,r,g) in travel_to_cluster.keys():
            model8+= travel_to_cluster[ (t2,r,g)] <= lpSum( [xxx[(t1,t2,r)] for t1 in getTeamsOfNeighbor[g] ] ) 
            model8+= travel_to_cluster[ (t2,r,g)] <= lpSum( [xxx[(t1,t2,r+1)] for t1 in getTeamsOfNeighbor[g] ] ) 
    
        for (t2,r,g) in fixed_travels:
            print ( "fixed_travel "  , t2,r,g)
            model8 += travel_to_cluster[(getTeamIdByName[t2],r,getConfId[g])]==1


        # model8 += home_ebl [(getTeamIdByName["FC Bayern Munich"],24)] + home_ebl[(getTeamIdByName["FC Bayern Munich"],25)]  <= 1
        # model8 += home_ebl [(getTeamIdByName["ALBA Berlin"],31)] +  home_ebl [(getTeamIdByName["ALBA Berlin"],32)] >=1
        # model8 += home_ebl [(getTeamIdByName["Maccabi FOX Tel Aviv"],6)] +  home_ebl [(getTeamIdByName["Maccabi FOX Tel Aviv"],7)] >=1
        # model8 += home_ebl [(getTeamIdByName["Maccabi FOX Tel Aviv"],10)] ==1
        # model8 += home_ebl [(getTeamIdByName["Maccabi FOX Tel Aviv"],11)] ==1
        # model8 += home_ebl [(getTeamIdByName["Zalgiris Kaunas"],21)] ==1
        # model8 += home_ebl [(getTeamIdByName["AS Monaco"],4)] ==1
        # model8 += home_ebl [(getTeamIdByName["AS Monaco"],6)]+  home_ebl [(getTeamIdByName["AS Monaco"],7)]  >=1
                    
        for (t1,t2,r) in xxx.keys():
            if t_blocked_at[(t1,r)] and getTeamById[t2]!="ALBA BERLIN" and False:
                model8 += xxx[(t1,t2,r)]==0

# TEAMS;5;120
# TEAMSROUNDS
# ROUNDS;10
# GROUPS
            


        # model8+=lpSum([ xxx[(t1,t2,r)] for t1 in teams for t2 in teams for r in xxx_rounds ])
        # model8.solve(XPRESS(msg=1,maxSeconds = 160, options=["THREADS=12"], keepFiles=True))
        # for r in xxx_rounds :
            # print ("Round ", r)
            # for (t1,t2) in games_ebl :
                # if xxx[(t1,t2,r)].value()>0.5:
                    # print ("  " ,getTeamById[t1], " - " , getTeamById[t2] )
        # exit(0)
        
        blockvios_ebl=lpSum([ xxx[(t1,t2,r)] for (t1,t2,r) in xxx.keys() if t_blocked_at[(t1,r)] ]) 
        usegames_ebl=lpSum([ xxx[(t1,t2,r)] for (t1,t2,r) in xxx.keys() if (t1,t2) in games_ebl ])
        toomanyaways = lpSum([ toomany[(t,r)]  for (t,r) in toomany.keys() ]) 

        model8+= usegames_ebl == len(teams) /2*len(xxx_rounds)

        # model8+= blockvios_ebl  ==0
        model8+= blockvios_ebl + toomanyaways

        if solver == "CBC":
            model8.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 240, threads = 8,msg=1))
        elif solver == "Gurobi":
            model8.solve(GUROBI( TimeLimit=240,msg=1))
        else:
            model8.solve(XPRESS(msg=1,maxSeconds = 160, options=["THREADS=12"], keepFiles=True))

        for r in xxx_rounds :
            print ("Round ", r)
            for (t1,t2) in games_ebl :
                if xxx[(t1,t2,r)].value()>0.5:
                    print ("  ",xxx[(t1,t2,r)].value() ,getTeamById[t1], " - " , getTeamById[t2] )
        
        print ("blockvios_ebl=", blockvios_ebl.value())
        for t1 in teams:
            bls = [ r for r in xxx_rounds for t2 in teams if xxx[(t1,t2,r)].value()>0.9 and t_blocked_at[(t1,r)] ]
            if len(bls)>0:
                print ( "BLOCKED " , getTeamById[t1] , bls)            
        print ("toomanyaways=", toomanyaways.value())
        
        fixed_travels = [ ( getTeamById[t2],r, getNameOfNeighbor[g]) for (t2,r,g) in possTrips.keys() if travel_to_cluster[(t2,r,g)].value()>0.1 ] 
        print ("fixed_travels=", fixed_travels)

        for t1 in teams:
            model2+= lpSum ( [ homeInRound[(t1,r)] for r in xxx_rounds ])  == 0.5*len(xxx_rounds)  

        tooFarViolation = { (t1,r) :  pulp.LpVariable('tooFarViolation_'+str(t1)+'_'+str(r), lowBound = 0, upBound = 10, cat = pulp.LpContinuous) for t1 in teams for r in xxx_rounds }

        for (t,r) in travel_elb.keys():
            if travel_elb[(t,r)].value()>=0.9:            
                print ("TRAVEL ",r,  getTeamById[t], travel_elb[(t,r)].value())
            else:
                for t1 in far_teams[t]:
                    model2+= x_round[(t1,t,r)]==0
                    model2+= x_round[(t1,t,r+1)]== 0
                    model2+= x_round[(t1,t,r+1)]<= tooFarViolation[(t,r+1)]
                model2+= awayInRound[(t,r)]+awayInRound[(t,r+1)] <=1

        print (len (travel_elb.keys()))
        
        
        specialObjectives =  1000 * lpSum([ tooFarViolation[(t,r)] for (t,r) in tooFarViolation.keys() ]) 


        for (t,r) in toomany.keys():
            if toomany[(t,r)].value()>0.9:
                print ("too many " ,r, " ", getTeamById[t])


        for (t2,r,g) in fixed_travels:
            model2+= lpSum( [x_round[(t1,getTeamIdByName[t2],r)] for t1 in getTeamsOfNeighbor[getConfId[g]] ] ) ==1
            model2+= lpSum( [x_round[(t1,getTeamIdByName[t2],r+1)] for t1 in getTeamsOfNeighbor[getConfId[g]] ] ) ==1

        for r in xxx_rounds:
            print ()
            print ("ROUND ", r)
            for (t1,t2) in games_ebl:
                if xxx[(t1,t2,r)].value()>0.1:
                    bcked = "#### " if t_blocked_at[(t1,r)] else " - " 
                    print (getTeamById[t1] , bcked , getTeamById[t2] , " ", xxx[(t1,t2,r)].value())        
                    model2+= x_round[(t1,t2,r)]==1

        print (blockvios_ebl.value())
        print (toomanyaways.value())   
                                    
    else:
        print ("++++++++++ IMPROVE SOLUTION ++++++++++")
        for t1 in teams:                                                
            # half of the games played at home
            model2+= lpSum ( [ homeInRound[(t1,r)] for r in xxx_rounds ])  == 0.5*len(xxx_rounds)  

        travel_elb ={}
        for t in teams:             
            # every team travels to other clusters twice
            model2+= lpSum( [travel_to_cluster[ (t2,r,g)] for (t2,r,g) in possTrips.keys() if t==t2 ])== 2  
            for r in elb_rounds:
                travel_elb[(t,r)] = lpSum( [travel_to_cluster[ (t2,r2,g)]  for (t2,r2,g) in possTrips.keys() if t==t2 and r==r2 ]) 
                print ("TRAVEL 1 ", t, r, travel_elb[(t,r)])
                model2+= awayInRound[(t,r)] + awayInRound[(t,r+1)] <= 1 + travel_elb[(t,r)]  
                model2+= lpSum([ x_round[(t1,t,r)] for t1 in far_teams[t] ]) <= travel_elb[(t,r)] 
                model2+= lpSum([ x_round[(t1,t,r+1)] for t1 in far_teams[t] ]) <= travel_elb[(t,r)]
            
        for (t2,r,g) in travel_to_cluster.keys():
            model2+= travel_to_cluster[ (t2,r,g)] <= lpSum( [x_round[(t1,t2,r)] for t1 in getTeamsOfNeighbor[g] ] ) 
            model2+= travel_to_cluster[ (t2,r,g)] <= lpSum( [x_round[(t1,t2,r+1)] for t1 in getTeamsOfNeighbor[g] ] ) 
                                
if mathModelName=="UEFA NL" :

    if thisSeason.name=="2024" and False:
        
        clashes_raw =[]
        clashes_raw +=['ARM-AZE','UKR-RUS','GIB-ESP','KOS-BIH','KOS-SRB','KOS-RUS','UKR-BLR']
        # clashes_raw +=['SRB-MKD','SRB-BIH','SRB-ALB','SRB-CRO','MKD-ALB','MKD-GRE','BIH-CRO','TUR-CYP','TUR-ARM','KOS-ARM','KOS-AZE','KOS-BLR','KOS-CYP','KOS-GEO','KOS-GRE','KOS-ISR','KOS-KAZ','KOS-MDA','KOS-ROU','KOS-RUS','KOS-SVK','KOS-ESP','KOS-UKR']
        clashes = [ (c[:3],c[4:]) for c in clashes_raw if c[:3] in cn_shortname.values() and c[4:] in cn_shortname.values() ]
        print ("clashes", clashes)
                    
        print ( thisSeason.name=="2024")

        american_teams = [t for t in teams if t_lon[t] <=-20]
        european_teams = [t for t in teams if t_lon[t] >-20]

        print ("american_teams", american_teams)
        print ("european_teams", european_teams)

        usedWeekdays = set([getWeekDay[d] for d in days])
        # print (getNiceDay[d['id']], getWeekDay[d['id']])

        # print (t_conference)

        day3pairs =[ (d1,d2) for d1 in days for d2 in days if getDateTimeDay[d2]-getDateTimeDay[d1] ==datetime.timedelta(days=3) ]
        print (day3pairs)

        # possGames_UEFA   = [(t1,t2) for t1 in teams for t2 in teams if t1!=t2 and t_conference[t1].name[0]==t_conference[t2].name[0]]
        possGames_UEFA   = [(t1,t2) for t1 in teams for t2 in teams if t1!=t2 and t_conference[t1].name[0]==t_conference[t2].name[0] and not (t_country[t1],t_country[t2]) in clashes  and not (t_country[t2],t_country[t1]) in clashes ]
        nopossGames_UEFA = [(t1,t2) for t1 in teams for t2 in teams if not (t1,t2) in possGames_UEFA ]

        # possGames_UEFA   = [(t1,t2) for t1 in teams for t2 in teams if t1!=t2 and t_conference[t1].name[0]==t_conference[t2].name[0]]
        # nopossGames_UEFA   = [(t1,t2) for t1 in teams for t2 in teams if t1==t2 or t_conference[t1].name[0]!=t_conference[t2].name[0]]

        print ("")
        print (len(possGames_UEFA), "possGames_UEFA")
        print (len(nopossGames_UEFA), "nopossGames_UEFA")
        print ("")

        # for (t1,t2) in possGames_UEFA:
        #     print (getTeamById[t1] , " might play ", getTeamById[t2]  , t_conference[t1].name[0] , t_conference[t2].name[0])

        for (t1,t2) in nopossGames_UEFA:
            for rd in roundDays:
                if (t1,t2,rd) in x.keys():
                    setUB(x[(t1,t2,rd)],0)
                                        
            # model2 +=  lpSum([x[(t1,t2,rd)] for rd in roundDays]) == 0
            print (getTeamById[t1] , " will not play ", getTeamById[t2]  , t_conference[t1].name[0] , t_conference[t2].name[0])
        

        for (t1,t2) in possGames_UEFA:
            if t1<t2 and t_conference[t1].name[0]!="C":
                model2 +=  lpSum([x[(t1,t2,rd)] + x[(t2,t1,rd)]  for rd in roundDays]) <= 1
                print (getTeamById[t1] , " might play ", getTeamById[t2]  , t_conference[t1].name[0] , t_conference[t2].name[0])

        all_american_games_A  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t1 in american_teams and  t2 in american_teams  and t_conference[t1].name[0]=="A" and t_conference[t2].name[0]=="A"]
        all_american_games_B  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t1 in american_teams and  t2 in american_teams  and t_conference[t1].name[0]=="B" and t_conference[t2].name[0]=="B"]

        if len(all_american_games_A)>0:
            model2 +=  lpSum([x[(t1,t2,(r,d))] for (t1,t2,(r,d)) in  all_american_games_A ]) ==12
        if len(all_american_games_B)>0:
            model2 +=  lpSum([x[(t1,t2,(r,d))] for (t1,t2,(r,d)) in  all_american_games_B ]) == 4 

        for (t1,t2,(r,d)) in all_american_games_A:
            if r in [1,2,7,8]:
                model2 += x[(t1,t2,(r,d))]==0

        for (t1,t2,(r,d)) in all_american_games_B:
            if r in [3,4,5,6,7,8]:
                model2 += x[(t1,t2,(r,d))]==0



        
        for t in teams: 
            if not getTeamById[t] in  ["Iceland", "Faroe Islands"]:
                for rn in [3,4,5,6,7,8]:
                    model2 += break3InRound[(t,rn)]== 0
            # if getTeamById[t]=="Ukraine":
            #     model2 += awayInRound[(t1,7)]== 1
            #     model2 += awayInRound[(t1,8)]== 1

            # model2 +=  lpSum([x[(t,t2,rd)] +x[(t2,t,rd)]  for t2 in teams for rd in roundDays if t_conference[t]!=t_conference[t2]]) == 4
            model2 +=  lpSum([home[(t,d)] for d in days ]) == 4

            for (d1,d2) in day3pairs:
                model2 +=  home[(t,d1)]+away[(t,d1)] == home[(t,d2)]+ away[(t,d2)]

            if t_conference[t].name[0]=="A" :
                for pp in ["A1","A2"]:
                    model2 += lpSum([x[(t,t2,rd)] + x[(t2,t,rd)] for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) == 4 
                    # 2 home matches against pot 1, 2 home matches against pot 2 and 2 away matches against pot 1, 2 away matches against pot 2
                    model2 += lpSum([x[(t,t2,rd)] for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) == 2 

                # if t in american_teams:
                #     model2 += lpSum([(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() 

                #         if t1 in american_teams and  t2 in american_teams  and r in [3,4,5,6]]   [x[(t,t2,rd)] + x[(t2,t,rd)] for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) == 4 



                    # model2 += lpSum([x[(t,t2,rd)] + x[(t2,t,rd)] for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) >= 2 

            # For league B, the 16 European teams are split in 4 pots and the last four CONMEBOL teams (VEN, PAR, ECU, BOL) join them. 
            # The swiss system is still used and each team must play two teams from each pot (8MDs). 
            # For the CONMEBOL teams, two different splits are possible: one team per pot or 2 teams in the two first pots. 
            # Could you please try both options and see which one is the most convenient?
            # In addition, the CONMEBOL teams must play each other but only over one international window 
            #  (let's say in September 2024) as they don't have enough opponents to play 4 MDs against each other.
            if t_conference[t].name[0]=="B" :
                for pp in ["B1","B2","B3","B4"]:
                    model2 += lpSum([x[(t,t2,rd)] + x[(t2,t,rd)] for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) == 2
                    # 1 home match against one team from each pot and 1 away match against one team from each pot
                    model2 += lpSum([x[(t,t2,rd)]  for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) == 1
                    # model2 += lpSum([x[(t,t2,rd)] + x[(t2,t,rd)] for rd in roundDays for t2 in teams if t_conference[t2].name==pp]) >= 1

            # For league C, the format is different and it is not a swiss system anymore. 
            # A proposal would be to have 4 groups of 4 teams but to pair 2 groups together (1A and 1B together, 2A and 2B together). 
            # The four teams from one group (1A) would play home and away the four teams from the other group (1B). 
            # In the excel table, you will see the group proposal.

            for (c1,c2) in [("C1A","C1B"), ("C2A","C2B")]:
                if t_conference[t].name==c1:
                    for t2 in teams :
                        if t_conference[t2].name==c2:
                            model2 += lpSum([x[(t,t2,rd)] for rd in roundDays]) == 1
                            model2 += lpSum([x[(t2,t,rd)] for rd in roundDays]) == 1
                            model2 += lpSum([x[(t,t2,(r,d))] + x[(t2,t,(r,d))] for (r,d) in roundDays if r<=4]) == 1


            # use every weekday at least once:
            # for wd in usedWeekdays:
            #     model2 +=  lpSum([home[(t,d)] + away[(t,d)] for d in days if getWeekDay[d]==wd ]) >= 1

            # for t2 in teams: 
            #     if gameCntr[(t,t2)]+gameCntr[(t2,t)]>0:
            #         print("adding" , t , t2)
            #         model2 +=  lpSum([x[(t,t2,rd)] +x[(t2,t,rd)]  for rd in roundDays if t!=t2]) <= 1
            #     if t_conference[t].name[0]!=t_conference[t2].name[0]:
            #         model2 +=  lpSum([x[(t,t2,rd)] for rd in roundDays if t!=t2]) == 0
            #         # print (getTeamById[t] , " does not play ", getTeamById[t2]  , t_conference[t].name[0] , t_conference[t2].name[0] )

            #     # else:
            #     #     print("ignoring" , t , t2)

        # print ("TESTING")
        # model2.solve(GUROBI(MIPGap=0.0, TimeLimit=40,msg=1))
        # print ("TESTING DONE")
        

        print (t_conference)

        
        # for t in american_teams:                                
        #     for (r,d) in getRoundDaysByRound[3]:
        #         if t!= american_teams[0]:
        #             model2 +=  home[(t,d)]+away[(t,d)] == home[(american_teams[0],d)]+away[(american_teams[0],d)]
                            
        #     for r in [3,4,5,6]:
        #         model2 +=  lpSum([x[(t,t2,rd)] +x[(t2,t,rd)] for t2 in american_teams for rd in getRoundDaysByRound[r] if t!=t2]) == 1
        #     for r in [1,2,7,8]:
        #         model2 +=  lpSum([x[(t,t2,rd)] +x[(t2,t,rd)] for t2 in american_teams for rd in getRoundDaysByRound[r] if t!=t2]) == 0

        # league_A_games  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="A" and t_conference[t2].name[0]=="A" ]
        # league_B_games  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="B" and t_conference[t2].name[0]=="B" ]
        # league_C_games  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="C" and t_conference[t2].name[0]=="C" ]
        league_A1_games  = set([(t1,t2,r) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="A" and t_conference[t2].name[0]=="A" if r in [3,4,5,6] ])
        league_A_games   = set([(t1,t2,r) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="A" and t_conference[t2].name[0]=="A" ])
        league_B_games   = set([(t1,t2,r) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="B" and t_conference[t2].name[0]=="B" ])
        league_B1_games  = set([(t1,t2,r) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="B" and t_conference[t2].name[0]=="B" if r <=4 ])
        league_C_games   = set([(t1,t2,r) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="C" and t_conference[t2].name[0]=="C" ])

        # all_american_games  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t1 in american_teams and  t2 in american_teams  and r in [3,4,5,6]]
        # half_american_games = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t1 in american_teams !=  t2 in american_teams  and r in [1,2,7,8]]
        # all_european_games1  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t1 in european_teams and t2 in european_teams  and r in [1,2,3,4]]
        # all_european_games2  = [(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t1 in european_teams and t2 in european_teams  and r in [5,6,7,8]]

        if runMode=='New':

            # print (len(league_A_games))                
            # print (len(league_B_games))                
            # print (len(league_C_games))                
            

            optIterations = []
            if len(league_C_games)>0:
                optIterations+=[(league_C_games, " league_C_games ","rounds")]
                optIterations+=[(league_A1_games, " league_A1_games ","rounds" )]
                optIterations+=[(league_A_games, " league_A_games " ,"rounds")]
                optIterations+=[(league_B1_games, " league_B1_games " ,"rounds")]
                optIterations+=[(league_B_games, " league_B_games " ,"rounds")]
            else: 
                league_A1_games  = set([(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="A" and t_conference[t2].name[0]=="A" if r in [3,4,5,6] ])
                league_A_games   = set([(t1,t2,(r,d)) for (t1,t2,(r,d)) in x.keys() if t_conference[t1].name[0]=="A" and t_conference[t2].name[0]=="A" ])
                optIterations+=[(league_A1_games, " league_A1_games " ,"days")]
                optIterations+=[(league_A_games, " league_A_games " , "days")]


            # for gms,txt  in [ ( all_american_games, " ALL AMERICAN " ), ( half_american_games, " HALF AMERICAN " ) , ( all_european_games1, " all_european_games1 " ) , ( all_european_games2, " all_european_games2 " ) ] :  
            # for gms,txt  in [ ( all_american_games, " ALL AMERICAN " ),  ( all_european_games1, " all_european_games1 " ) , ( all_european_games2, " all_european_games2 " ) ] :  
            # for gms,txt  in [ ( all_american_games, " ALL AMERICAN " ) ] :  
            for gms,txt,gran  in optIterations :  
                print ("!!!!!!!  PRE RUN  "+txt+"!!!!!!")
                print (len(gms))
                for rr in gms:
                    if gran=="rounds":
                        makeIntVar(x_round[rr])                        
                    else:
                        makeIntVar(x[rr])                        


                if solver == "CBC":
                    model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
                elif solver == "Gurobi":
                    model2.solve(GUROBI(MIPGap=0.1, TimeLimit=240,msg=1))
                else:
                    model2.solve(XPRESS(msg=1,maxSeconds = 140, options=["THREADS=12"], keepFiles=True))

                for rr in gms:
                    if gran=="rounds":
                        model2+= x_round[rr] ==getVal(x_round[rr]) 
                        if getVal(x_round[rr])  >0.1:
                            print (rr , getVal(x_round[rr]))
                    else:
                        model2+= x[rr] ==getVal(x[rr]) 
                        if getVal(x[rr])  >0.1:
                            print (rr , getVal(x[rr]))
        # for t in european_teams:                                
        #     model2 +=  lpSum([x[(t,t2,rd)] +x[(t2,t,rd)] for t2 in american_teams for rd in roundDays ]) >= 1
            # model2 +=  lpSum([x[(t,t2,rd)] +x[(t2,t,rd)] for t2 in american_teams for rd in roundDays ]) <= 2


    else :

        # model2+=gamesTooCloseTotal==0
        specialObjectives+=1000*gamesTooCloseTotal

        # closeTeams_UEFA = {  "Kazakhstan" : [ "Andorra", "England","Faroe Islands","Gibraltar", "Iceland","Malta", "Northern Ireland","Portugal","Republic of Ireland","Scotland","Spain","Wales" ] ,
        closeTeams_UEFA = {  "Kazakhstan" : [ "Andorra", "England","France","Faroe Islands","Gibraltar", "Iceland","Malta",
                                                "Northern Ireland", "Portugal","Republic of Ireland","Scotland","Spain","Wales" ] ,
                        "Azerbaijan" : ["Gibraltar", "Iceland", "Portugal"],
                        "Iceland" : ["Armenia", "Cyprus", "Georgia", "Israel"] }

        # Label to represent both teams (Kazakstan/Modolva - Cyprus/Estonia) to carry both constrains of each pair.
        # closeTeams_UEFA = {  "KAZ/MDA 1" : [ "Andorra", "England","France","Faroe Islands","Gibraltar", "Iceland","Malta", "Northern Ireland","Portugal","Republic of Ireland","Scotland","Spain","Wales" ] ,
        #                      "KAZ/MDA 2" : [ "Andorra", "England","France","Faroe Islands","Gibraltar", "Iceland","Malta", "Northern Ireland","Portugal","Republic of Ireland","Scotland","Spain","Wales" ] ,
        #                      "Azerbaijan" : ["Gibraltar", "Iceland", "Portugal"],
        #                      "Iceland" : ["Armenia", "CYP/EST 1", "CYP/EST 2", "Georgia", "Israel"] }

        # for tn1 in  closeTeams_UEFA.keys(): 
        #     for tn2 in  closeTeams_UEFA[tn1]: 
        #         t1 = getTeamIdByName[tn1]              
        #         t2 = getTeamIdByName[tn2]              
        #         print (t1, t2 , t_conference[t1] ,t_conference[t2] , t_conference[t1]==t_conference[t2] ,  tn1,  tn2 )

        closeTeams_UEFA = [ (getTeamIdByName[tn1],getTeamIdByName[tn2]) for tn1 in closeTeams_UEFA.keys() for tn2 in closeTeams_UEFA[tn1] if t_conference[getTeamIdByName[tn1]]==t_conference[getTeamIdByName[tn2]]  ]
        print ("closeTeams_UEFA", [(getTeamById[t1] ,getTeamById[t2]) for (t1,t2) in closeTeams_UEFA])
        
        # for (tn1,tn2) in closeTeams_UEFA:
            # t1 = getTeamById[tn1]              
            # t2 = getTeamById[tn2]              
            # print (t1, t2 , t_conference[tn1] ,t_conference[tn2] , t_conference[tn1]==t_conference[tn2] ,  tn1,  tn2 )


            # 1234 56
        two_starter_uefa= [5]
        mid_starter_uefa= [2,3]
        three_starter_uefa= [1]

        two_starter_uefa= [1,3,5,7,9]
        mid_starter_uefa= []
        three_starter_uefa= []
        # for t in teams:
            # if noPlayRounds[t] == [7,8]:
                # two_starter_uefa= [7,9]
                # mid_starter_uefa= [2,5]
                # three_starter_uefa= [1,4]

        print ("two_starter_uefa", two_starter_uefa)
        print ("three_starter_uefa", three_starter_uefa)

        # TODO
        # no back to back in md 3 and 4
        # no break in md 5/6 
        # max 3 rest days between games

        day3pairs  =[ (d1,d2) for d1 in days for d2 in days if getDateTimeDay[d2]-getDateTimeDay[d1] ==datetime.timedelta(days=3) ]
        day34pairs ={ d1 : [d2 for d2 in days if getDateTimeDay[d2]-getDateTimeDay[d1] in [datetime.timedelta(days=di) for di in [3,4]]] for d1 in days }
        day345pairs ={ d1 : [d2 for d2 in days if getDateTimeDay[d2]-getDateTimeDay[d1] in [datetime.timedelta(days=di) for di in [3,4,5]]] for d1 in days }

        closeDays_UEFA = two_starter_uefa+mid_starter_uefa+three_starter_uefa
        closeDays_UEFA = []

        if "3DaysForDistantTeams" in special_wishes_active:
            sw_type="3DaysForDistantTeams"
            for (t1,t2) in closeTeams_UEFA:
                # model2 += lpSum( [ x[t1,t2,rd] + x[t2,t1,rd]  for rd in getRoundDaysByRound[4]] ) ==1
                # model2 += lpSum( [ x[t1,t2,rd] + x[t2,t1,rd]  for rd in getRoundDaysByRound[1]] ) ==1
                for (d1,d2) in day3pairs:
                    specialWishVio[(sw_type,t1,t2,d1)]= pulp.LpVariable('specialWishVio_'+sw_type+'_'+str(t1)+"_"+str(t2)+"_"+str(d1), lowBound=0, cat=pulp.LpContinuous)
                    specialWishItems[sw_type].append((t1,t2,d1))
                    for t3 in teams:
                        if t_conference[t1]==t_conference[t3] and not t3 in [t1,t2]:
                            print ("taking care of " , getTeamById[t3] , "'s trip to ",  getTeamById[t1] , " and ",  getTeamById[t2] )
                            model2 += lpSum( [ x[t,t3,rd]  for t in [t1,t2] for rd in getRoundDaysByDay[d1]+getRoundDaysByDay[d2] ] ) <=1 + specialWishVio[(sw_type,t1,t2,d1)]
                    model2 +=  home[t1,d1] + lpSum([x[t2,t1, rd] for rd in getRoundDaysByDay[d2]])   <=1 + specialWishVio[(sw_type,t1,t2,d1)]
                    model2 +=  home[t1,d2] + lpSum([x[t2,t1, rd] for rd in getRoundDaysByDay[d1]])   <=1 + specialWishVio[(sw_type,t1,t2,d1)]
                    model2 +=  home[t2,d1] + lpSum([x[t1,t2, rd] for rd in getRoundDaysByDay[d2]])   <=1 + specialWishVio[(sw_type,t1,t2,d1)]
                    model2 +=  home[t2,d2] + lpSum([x[t1,t2, rd] for rd in getRoundDaysByDay[d1]])   <=1 + specialWishVio[(sw_type,t1,t2,d1)]
            specialObjectives += 1000*lpSum([ sw_prio[sw_type]* specialWishVio[(sw_type,t1,t2,d1)] for (t1,t2,d1) in specialWishItems[sw_type] ])


        # for (t1,t2) in closeTeams_UEFA:
        #     for rn in closeDays_UEFA:
        #         for t3 in teams:
        #             if t_conference[t1]==t_conference[t3] and not t3 in [t1,t2]:
        #                 # print ("taking care of " , getTeamById[t3] , "'s trip to ",  getTeamById[t1] , " and ",  getTeamById[t2] )
        #                 model2 += lpSum( [ x[t1,t3,d] + x[t2,t3,d] for d in getRoundDaysByRound[rn]+getRoundDaysByRound[rn+1] ] ) <=1

        #         # print ("I don't care about " , getTeamById[t1] , "'s trip to ",  getTeamById[t2])
        #         # print ("taking care of " , getTeamById[t1] , "'s trip to ",  getTeamById[t2])
        #         model2 +=  homeInRound[(t1,rn)]   + lpSum([x[t2,t1, rd] for rd in getRoundDaysByRound[rn+1]]) <=1
        #         model2 +=  homeInRound[(t1,rn+1)] + lpSum([x[t2,t1, rd] for rd in getRoundDaysByRound[rn]])   <=1
        #         # print ("taking care of " , getTeamById[t2] , "'s trip to ",  getTeamById[t1])
        #         # if getTeamById[t2]!="France":
        #         model2 +=  homeInRound[(t2,rn)]   + lpSum([x[t1,t2, rd] for rd in getRoundDaysByRound[rn+1]]) <=1
        #         model2 +=  homeInRound[(t2,rn+1)] + lpSum([x[t1,t2, rd] for rd in getRoundDaysByRound[rn]])   <=1
        #         # else:
        #         #     if rn>1:
        #         #         model2 +=  homeInRound[(t2,rn-1)]   + lpSum([x[t1,t2, rd] for rd in getRoundDaysByRound[rn]]) + homeInRound[(t2,rn+1)] <=2

        print ("getRoundDaysByRound", getRoundDaysByRound)

        conferences6  = [c for c in Conference.objects.filter(scenario=s2,regional=False) if len(c.teams.filter(active=True))==6]
        conferences5  = [c for c in Conference.objects.filter(scenario=s2,regional=False) if len(c.teams.filter(active=True))==5]
        conferences4  = [c for c in Conference.objects.filter(scenario=s2,regional=False) if len(c.teams.filter(active=True))==4]
        conferences3  = [c for c in Conference.objects.filter(scenario=s2,regional=False) if len(c.teams.filter(active=True))==3]

        # print ("day34pairs",day34pairs)
        # print (conferences4)
        # print ("confs 3 " , len(conferences3))
        # print ("confs 4 " , len(conferences4))
        # print ("confs 5 " , len(conferences5))
        # print ("confs 6 " , len(conferences6))

        # alltms =set([])

        c4= {(c.id,d) : pulp.LpVariable('c4_'+str(c)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for c in conferences4 for d in days}
        c5= {(c.id,d) : pulp.LpVariable('c5_'+str(c)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for c in conferences5 for d in days}
        c6= {(c.id,d) : pulp.LpVariable('c6_'+str(c)+'_'+str(d), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for c in conferences6 for d in days}


        travelControl_UEFA= False
        travelControl_UEFA= True
        dontPlayOnGamesList_UEFA=  ["2022-06-04", "2022-06-05", "2022-06-08", "2022-06-11", "2022-06-12"]
        if  runMode!='Improve':
            dontPlayOnGamesList_UEFA+= ["2022-06-02"]+ ["2022-06-13"]  + ["2022-06-06","2022-06-09"]
        dontPlayOnGamesList_UEFA = [ parse(dd) for dd in dontPlayOnGamesList_UEFA ]
        print("dontPlayOnGamesList_UEFA",dontPlayOnGamesList_UEFA)
        dontPlayOnGamesList_UEFA = [ getDayByDateTime[dd] for dd in dontPlayOnGamesList_UEFA if dd in getDayByDateTime.keys()]
        print("dontPlayOnGamesList_UEFA",dontPlayOnGamesList_UEFA)
        if travelControl_UEFA :
            for c in conferences4:
                cteams= c.teams.filter(active=True)
                # print ("checking group" , c )
                for t in cteams:
                    # print ("checking team" , t )                    
                    for (t1,t2) in closeTeams_UEFA:
                        if t.id==t1:
                            for d1 in sorted(dontPlayOnGamesList_UEFA ):
                                model2 += c4[(t_conference[t1].id,d1)] == 0
                                print (c.name , " cannot play on ", d1 , " " , getNiceDay[d1])

        for c in conferences3+conferences4:
            cteams= c.teams.filter(active=True)
            for t1 in cteams:
                for t2 in cteams:
                    if t2.id < t1.id:
                        model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for d in getRoundDaysByRound[3]+getRoundDaysByRound[4] ]) <=1

        forbidBackToBack = True

        # when are the next games allowed to be played 
        compNextGames = {   1:[4,5], 2:[5,6], 3:[6,7], 
                            4:[7,8,9], 5:[8,9,10], 6:[9,10], 
                            7:[10,11,12], 
                            8:[11,12], 9:[12,13], 10:[13],
                            14:[17,18], 15:[18,19], 16:[19],
                            }
                            
        compNextGames = {   1:[4,5,6], 2:[5,6], 3:[6], 
                            4:[7,8,9], 5:[7,8,9], 6:[7,8,9], 
                            
                            7:[10,11,12], 8:[11,12], 9:[12],
                            10:[13,14,15], 11:[13,14,15], 12:[13,14,15],
                            
                            13:[16,17,18], 14:[17,18], 15:[18],
                            # 16:[], 17:[], 18:[],
                            }

        if "forbid4DaysOff" in special_wishes_active :    
            compNextGames[1]=[4,5]
            compNextGames[7]=[10,11]
            compNextGames[13]=[16,17]

        # if runMode!='Improve':
            # compNextGames[14]=[17]
            # compNextGames[15]=[18]

        if "3RestDaysBetweenMD2andMD3" in special_wishes_active:
            compNextGames[4]=[8]
            compNextGames[5]=[9]
            compNextGames[6]=[10]

        usedWeekdays = set([getWeekDay[d] for d in days])

        for c in conferences4:
            cteams= c.teams.filter(active=True)
            t1 = cteams.first()
            for t2 in cteams:
                # no b2b between rounds 3 and 4
                # if t2.id != t1.id :
                    # model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for d in getRoundDaysByRound[3]+getRoundDaysByRound[4] ]) <=1
                for d1 in days:
                    model2 += home[(t2.id,d1)]+away[(t2.id,d1)]  ==  c4[(c.id,d1)]
            # adjust pattern abcbca
            # for t1 in cteams:
                # for t2 in cteams:
                    # if t1.id != t2.id:
                        # model2 += lpSum( [ x[t1.id,t2.id,d] for d in getRoundDaysByRound[2]]) == lpSum( [ x[t2.id,t1.id,d] for d in getRoundDaysByRound[4]])
                        # model2 += lpSum( [ x[t1.id,t2.id,d] for d in getRoundDaysByRound[3]]) == lpSum( [ x[t2.id,t1.id,d] for d in getRoundDaysByRound[5]])
            # for (d1,d2) in day3pairs:
            #     if getRoundByDay[d1]>=5:
            #         model2 += c4[(c.id,d1)] == c4[(c.id,d2)]
            for di in compNextGames.keys():
                model2 +=  c4[(c.id,daysSorted[di-1])] <=  lpSum([c4[(c.id,daysSorted[di2-1])] for di2 in compNextGames[di]])   

        for c in conferences6:
            cteams= c.teams.filter(active=True)
            for t2 in cteams:
                # alltms.add(t2.id)
                for d1 in days:
                    model2 += home[(t2.id,d1)]+away[(t2.id,d1)] <= c6[(c.id,d1)]

            if runMode!='Improve' or "alwaysExactlyTwoRestDays" in special_wishes_active:
                for (d1,d2) in day3pairs:
                    model2 += c6[(c.id,d1)] == c6[(c.id,d2)]
            else:
                for d1 in day34pairs.keys():
                    if len(day34pairs[d1])>0:
                        model2 += c6[(c.id,d1)] <= lpSum([c6[(c.id,d2)] for d2 in day34pairs[d1]])

            for r in rounds:
                model2 +=  lpSum( [ c6[(c.id,d)] for d in getDays[r] ] ) == 1

            model2 +=  lpSum( [ c6[(c.id,d)] for d in days ] ) == 10

            if  "everyWeekdayAtLeastOnce" in special_wishes_active:
                for wd in usedWeekdays:
                    model2 +=  lpSum( [ c6[(c.id,d)] for d in days  if getWeekDay[d]==wd] ) >= 1

        c5_repeater={}
        for c in conferences5:
            cteams= c.teams.filter(active=True)
            for t2 in cteams:
                # alltms.add(t2.id)
                for d1 in days:
                    model2 += home[(t2.id,d1)]+away[(t2.id,d1)]  <=  c5[(c.id,d1)]
            if runMode!='Improve' or "alwaysExactlyTwoRestDays" in special_wishes_active:
                for (d1,d2) in day3pairs:
                    model2 += c5[(c.id,d1)] == c5[(c.id,d2)]
            else:
                for d1 in day34pairs.keys():
                    if len(day34pairs[d1])>0:
                        model2 += c5[(c.id,d1)] <= lpSum([c5[(c.id,d2)] for d2 in day34pairs[d1]])

            for r in rounds:
                model2 +=  lpSum( [ c5[(c.id,d)] for d in getDays[r] ] ) == 1

            model2 +=  lpSum( [ c5[(c.id,d)] for d in days ] ) == 10

            if  "everyWeekdayAtLeastOnce" in special_wishes_active:
                for wd in usedWeekdays:
                    model2 +=  lpSum( [ c5[(c.id,d)] for d in days  if getWeekDay[d]==wd] ) >= 1

            for t1 in cteams:
                for t2 in cteams:
                    if t1.id<t2.id and forbidBackToBack :
                        if not t_usePhases[t1.id] and not t_usePhases[t2.id] :
                            c5_repeater[(t1.id,t2.id)] = pulp.LpVariable('c5_repeater_'+str(t1.id)+'_'+str(t2.id), lowBound = 0,  cat = pulp.LpContinuous) 
                            model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for r in [1,2,3,4,5]  for d in getRoundDaysByRound[r] ] ) <=1 + c5_repeater [(t1.id,t2.id)]
                            model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for r in [6,7,8,9,10]  for d in getRoundDaysByRound[r] ] ) <=1 + c5_repeater [(t1.id,t2.id)]

                            # for rn in [1,2,4,6,7,9]:
                            for rn in two_starter_uefa :
                                model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for d in getRoundDaysByRound[rn]+getRoundDaysByRound[rn+1] ] ) <=1
                            for rn in three_starter_uefa:
                                model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for d in getRoundDaysByRound[rn]+getRoundDaysByRound[rn+1]+getRoundDaysByRound[rn+2]  ] ) <=1
                                
                        else:
                            # for rn in [4]:
                            #     model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for d in getRoundDaysByRound[rn]+getRoundDaysByRound[rn+1]+getRoundDaysByRound[rn+2]  ] ) <=1
                            for rn in [5]:
                                model2 += lpSum( [ x[t1.id,t2.id,d] + x[t2.id,t1.id,d] for d in getRoundDaysByRound[rn]+getRoundDaysByRound[rn+1]  ] ) <=1


                # if not t1.name in  ["Iceland", "Scotland", "Finland", "Faroe Islands"]:
                if not t1.name in  ["Iceland", "Faroe Islands"] and False:
                    for rn in [3,4,5,6]:
                        model2 += break3InRound[(t1.id,rn)]== 0
                        # print ("do not " , lpSum( [ homeInRound[(t1.id,r2)]-awayInRound[(t1.id,r2)] for r2 in [rn-2,rn-1,rn] ]) )
                        model2 += lpSum( [ homeInRound[(t1.id,r2)]-awayInRound[(t1.id,r2)] for r2 in [rn-2,rn-1,rn] ]) <=  1
                        model2 += lpSum( [ homeInRound[(t1.id,r2)]-awayInRound[(t1.id,r2)] for r2 in [rn-2,rn-1,rn] ]) >= -1


        # t_in_French_Group={t4 : False  for t4 in teams}
        # for c in allConferences:
            # tms = [t.id for t in c.teams.filter(active=True)]
            # print ("C " , tms)
            # franceFound = False
            # for tt in tms:
                # if getTeamById[tt]== "France":
                    # franceFound = True
            # if franceFound:
                # for tt in tms:
                    # t_in_French_Group[tt]= True
                    # print ("found french friend " , tt , getTeamById[tt])
        # 

            
        # for t in teams: 
            # if not t_usePhases[t] and not t_in_French_Group[t]:
                # model2 += lpSum([c5_repeater[(t1,t2)] for (t1,t2) in c5_repeater.keys() if t in [t1,t2]]) <=1


        if len(conferences4)>0 :
            for d1 in days:
                model2 +=  lpSum( [ c4[(c.id,d1)] for c in conferences4 ] ) >=0
                model2 +=  lpSum( [ c4[(c.id,d1)] for c in conferences4 ] ) <=5

            # todo: no 3*5 c4 on days 1,2,6 -> spacing for c3 possible 
            # todo: no 3*5 c4 on days 1,5,6 -> spacing for c3 possible

            # model2 +=  lpSum( [ c4[(c.id,daysSorted[di-1])] for c in conferences4 for di in [1,2,6]] ) <=14
            # model2 +=  lpSum( [ c4[(c.id,daysSorted[di-1])] for c in conferences4 for di in [1,5,6]] ) <=14
            # model2 +=  lpSum( [ c4[(c.id,daysSorted[di-1])] for c in conferences4 for di in [8,9,13]] ) <=14
            # model2 +=  lpSum( [ c4[(c.id,daysSorted[di-1])] for c in conferences4 for di in [8,12,13]] ) <=14
            # for di in [1,2,3,4,5,6,  8,9,10,11,12,13]:
            #     model2 +=  lpSum( [ c4[(c.id,daysSorted[di-1])] for c in conferences4 ] ) >=3


        if runMode!='Improve':
            print ("EXTRA UEFA NL run")
            writeProgress("Running special model ", thisScenario.id,10)

            if solver == "CBC":
                model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
            elif solver == "Gurobi":
                model2.solve(GUROBI(MIPGap=0.0, TimeLimit=40,msg=1))
            else:
                model2.solve(XPRESS(msg=1,maxSeconds = 40, options=["THREADS=12"], keepFiles=True))

            for (c,d) in c4.keys():
                model2 += c4[(c,d)] == c4[(c,d)].value()
                if c4[(c,d)].value() >0.9:
                    print ("c4 " , c, getNiceDay[d] )


            for (c,d) in c5.keys():
                model2 += c5[(c,d)] == c5[(c,d)].value()
                if c5[(c,d)].value() >0.01:
                    print (c, d, c5[(c,d)].value() )


print ("thisSeason.useFeatureBackToBack", thisSeason.useFeatureBackToBack)
if thisSeason.useFeatureBackToBack:
    print ("critical_day_pairs", critical_day_pairs)
    print ("back2backBlocks", back2backBlocks)
    fiveDayFourRounds=[]
    for d in days: 
        fiveDays = [  d2 for d2 in days if  getDateTimeDay[d]<= getDateTimeDay[d2] and getDateTimeDay[d2]-getDateTimeDay[d]<=datetime.timedelta(days=4) ]
        fourRounds = [] 
        for d2 in fiveDays:
            fourRounds+=[ r2 for r2 in getRoundsByDay[d2] ]
        fourRounds=list(set(fourRounds))
        # print (d, fiveDays,fourRounds , len(fourRounds)>=4)        
        if len(fourRounds)>=4:
            fiveDayFourRounds.append(fiveDays)

    bad_travel_in = { t : [] for t in teams} 
    bad_travel_out = { t : [] for t in teams} 
    for (t1,t2,c) in bad_travels:
        bad_travel_in[t2].append((t1,color_weight[c]))
        bad_travel_out[t1].append((t2,color_weight[c]))

    for fdfr in fiveDayFourRounds:
        for t in realteams: 
            model2 +=  lpSum([ home[(t,d)] + away[(t,d)] for d in fdfr ]) <= 3  + 0.001*badBackToBack[(t,fdfr[0])]
            # print(t, " cannot play more than three times in ", fdfr)

    for (d1,d2) in critical_day_pairs:
        # print ("no time zone crossings for at days " , getNiceDay[d1]," -> ",getNiceDay[d2],nextCritical[d2])
        for t in realteams: 

            # print ("counting b2b for ", getTeamById[t])
            model2 +=  home[(t,d1)]+home[(t,d2)]+away[(t,d1)]+away[(t,d2)] <= 1 + badBackToBack[(t,d1)]
            rd1s=getRoundDaysByDay[d1]
            rd2s=getRoundDaysByDay[d2]

            if nRounds <= 72 and nextCritical[d2]:
                # print ("no 3 series for " , t , " at days " , d1,d2,nextCritical[d2])
                model2 +=  lpSum([ home[(t,d)] + away[(t,d)] for d in [d1,d2,nextCritical[d2]] ]) <= 2  + 0.0001*badBackToBack[(t,d1)]

            for (tms1,tms2,w) in back2backBlocks:
                model2 += lpSum([x[(t1,t,rd1)] for rd1 in rd1s for t1 in tms1 if gameCntr[(t1,t)]>0]) + lpSum([x[(t2,t,rd2)] for rd2 in rd2s for t2 in tms2 if gameCntr[(t2,t)]>0 ]) <= 1  + 0.001/w*badBackToBack[(t,d1)]

            if currentAwayLocation[(t,d1)] and currentAwayLocation[(t,d2)]:
                t1 = currentAwayLocation[(t,d1)]
                for (t2,w) in bad_travel_out[t1]:
                    if t2==currentAwayLocation[(t,d2)]:
                        print ("TRAVEL BACK TO BACK FOUND WITH WEIGHT ", w, ":", getNiceDay[d1] ,getTeamById[t] , " -> " , getTeamById[currentAwayLocation[(t,d1)]] , " -> " , getTeamById[currentAwayLocation[(t,d2)]] )
                        model2 += lpSum([x[(t1,t,rd1)] for rd1 in rd1s ]) + lpSum([x[(t2,t,rd2)] for rd2 in rd2s ]) <= 1  + 0.001/w*badBackToBack[(t,d1)]

            # todo : add red teams to distant_teams here to take care that trips do not start and end with bad b2b
            # print ("after home game no away game at " , rd1s, rd2s, "for ", t ,  "  in ",  distant_teams[t])
            if not blocked_arena[(t,d1,"----")]:
                model2 +=   home[(t,d1)] + lpSum([ wg*x[(t2,t,rd2)] for rd2 in rd2s for (t2,wg) in bad_travel_out[t] if gameCntr[(t2,t)]>0  ]) <= 1  + 0.001*badBackToBack[(t,d1)]
            if not blocked_arena[(t,d2,"----")]:
                # if d1==32363 and getTeamById[t]=="Cleveland Cavaliers":
                #     print (" ++++ ",getTeamById[t] , rd1s, bad_travel_in[t] )
                #     for t33 in bad_travel_in[t]:
                #         print("+++++ " ,t33, getTeamById[t33] , gameCntr[(t33,t)])
                #     print (" ++++ ",lpSum([ wg*x[(t2,t,rd1)] for rd1 in rd1s for (t2,wg) in bad_travel_in[t] if gameCntr[(t2,t)]>0 ]) )
                model2 +=   lpSum([ wg*x[(t2,t,rd1)] for rd1 in rd1s for (t2,wg) in bad_travel_in[t] if gameCntr[(t2,t)]>0 ]) + home[(t,d2)]  <= 1  + 0.001*badBackToBack[(t,d1)]

    badBackToBack_Total  = lpSum([badBackToBack[(t,d1)] for t in teams for (d1,d2) in critical_day_pairs])
    specialObjectives+= 50*gew['Breaks']* badBackToBack_Total 
# END SPECIAL CONSTRAINTS

model2+= standardObjectives +specialObjectives

print("Model built now solving .... ")

nRuns =1
maxSolveTime = 300

if thisSeason.groupBased:
    maxSolveTime = 40

mipgap=0.01

# print ("######## Testing")
# model2.solve(GUROBI(MIPGap=0.0, TimeLimit=120,msg=1))


use_LP_heuristic= False
print (runMode=='New' , useBasicGames , runHeuristicModelFirst)

if runMode=='New' and useBasicGames and runHeuristicModelFirst:
    print ('Coupling Home Away to patterns', use_LP_heuristic)

    if use_LP_heuristic:
        model2.solve(GUROBI(MIPGap=mipgap, TimeLimit=maxSolveTime,msg=1))
        roundedGames = { (t1,t2,r) :  gameInBasicRound[(t1,t2,r)].value() for r in rounds1 for t1 in realteams for t2 in realteams if t1!=t2 }

        for g in roundedGames:
            if roundedGames[g]>0:
                print (g, " : " ,roundedGames[g])

        model5 = pulp.LpProblem(f"{PULP_FOLDER}/League Scheduling Model -- LP heuristic_"+str(thisScenario.id), pulp.LpMinimize)
        x5={(t1,t2,r) : pulp.LpVariable('x4_'+str(t1)+'_'+str(t2)+'_'+str(r), lowBound = 0, upBound = 1, cat = pulp.LpInteger) for  (t1,t2,r) in roundedGames.keys() }
        for t1 in realteams:
            for t2 in realteams:
                if t1<t2 :
                    model5+= lpSum( x5[(t1,t2,r)] +  x5[(t2,t1,r)] for r in rounds1)== 1
            for r in rounds1:
                model5+= lpSum( x5[(t1,t2,r)] +x5[(t2,t1,r)] for t2 in realteams if t1!=t2 ) ==1

        model5 += sum ( -roundedGames[g] * x5[g] for g in roundedGames.keys())
        model5.solve(GUROBI(MIPGap=0.1, TimeLimit=maxSolveTime,msg=1))

        for (t1,t2,r) in roundedGames.keys() :
            if x5[(t1,t2,r)].value()>0.1:
                print (r, " " , t1," - " , t2,  " : " ,  roundedGames[(t1,t2,r)])
                gameInBasicRound[(t1,t2,r)].lowBound = 1
                gameInBasicRound[(t1,t2,r)].upBound = 1
                gameInBasicRound[(t2,t1,r+nTeams-1)].lowBound = 1
                gameInBasicRound[(t2,t1,r+nTeams-1)].upBound = 1

    else:
    # use2BreakPatterns
        undecidedGames =  gameCntr.copy()
        for t in realteams:
            for r in basicRounds:
                if r > 0 and runHeuristicModelFirst and False:
                    # print ("homeInBasicRound[(",str(t),",",str(r), "  ] == " , int(homePat[(t,r)].value()))
                    # print ("awayInBasicRound[(",str(t),",",str(r), "  ] == " , 1-homePat[(t,r)].value())
                    # homeInBasicRound[(t,r)].lowBound = homePat[(t,r)].value()
                    homeInBasicRound[(t,r)].upBound = homePat[(t,r)].value()
                    # awayInBasicRound[(t,r)].lowBound = 1-homePat[(t,r)].value()
                    awayInBasicRound[(t,r)].upBound = awayPat[(t,r)].value()

        for (t1,t2) in games:
            for r in basicRounds:
                gameInBasicRound[(t1,t2,r)].lowBound = 0
                gameInBasicRound[(t1,t2,r)].upBound = 1
                gameInBasicRound[(t1,t2,r)].upBound = 0

        cntr =0  
        for (t1,t2,r) in chosenGames:
            # print (t1,t2,r)
            homers = [t1] + regionalKids[t1]
            awayers = [t2] + regionalKids[t2]
            # print (" chosen game  " ,r,  homers , awayers, getRoundDaysByBasicRound[r] , getMaxGameOnRoundDaysByBasicRound[r],defaultGameRepetions)
            # print (" chosen game  " , getMaxGameOnRoundDaysByBasicRound[r])
            theseRounds = sorted(list(set([ r2 for (r2,d) in getRoundDaysByBasicRound[r]])))
            if len(theseRounds)>0:
                fr = theseRounds[0]
                lr = theseRounds[-1]
                # print ( "   RDS " , theseRounds , theseRounds[0], min([ r2 for (r2,d) in getRoundDaysByBasicRound[r]]) ) 
                for t11 in homers:
                    for t22 in awayers:
                        #print (" - chosen game  " , getTeamById[t11], getTeamById[t22], getRoundDaysByBasicRound[r] , getMaxGameOnRoundDaysByBasicRound[r])
                        # model2 +=  gameInBasicRound[(t11,t22,r)] >= 1 - 0.9*missingGamesVio[(t11,t22)]
                        if (t11,t22,r) in gameInBasicRound.keys():
                            gameInBasicRound[(t11,t22,r)].lowBound = defaultGameRepetions-1
                            gameInBasicRound[(t11,t22,r)].upBound = defaultGameRepetions
                            # print ("setting ",(t11,t22,r) , defaultGameRepetions-1, defaultGameRepetions )

                            if tripStartHeuristicGroupsize>=2 and False:
                                model2+= x_round[(t11,t22,fr)] == x_round[(t11,t22,fr+1)] 
                                model2+= x_round[(t11,t22,fr+2)] == x_round[(t11,t22,fr+3)] 
    #                            print ("setting " , t11,t22, " twice")
    #                        model2+= x_round[(t1,t2,lr)] == x_round[(t1,t2,lr-1)] 

                            # print  ( t11,t22, (t11,t22) in undecidedGames,  undecidedGames)
                            undecidedGames[(t11,t22)]-=defaultGameRepetions
                            cntr+=1
            else:
                print ("PROBLEM " , theseRounds, homers, awayers, r)
        print (cntr, " games set")
        # print (len(undecidedGames), " undecided Games :", undecidedGames)
        for (t1,t2) in games:
            # if gameCntr[(t1,t2)]>0:
            #     print ("to be scheduled : " , getTeamById[ t1], " --- " , getTeamById[ t2] , gameCntr[(t1,t2)])
            if undecidedGames[(t1,t2)]!=0 and undecidedGames[(t1,t2)]!=-undirectedGameCntr[(t1,t2)]:
                print ("not scheduled yet " , getTeamById[ t1], " --- " , getTeamById[ t2] , undecidedGames[(t1,t2)])
                for r in basicRounds:
                    gameInBasicRound[(t1,t2,r)].upBound = defaultGameRepetions

        for ttr in x.keys():
            makeIntVar(x[ttr])

        if solver == "CBC":
            model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 120, threads = 8,msg=1))
        elif solver == "Gurobi":
            model2.solve(GUROBI(MIPGap=0.3, TimeLimit=180,msg=1))
        else:
            model2.solve(XPRESS(msg=1,maxSeconds = 120, options=["THREADS=12"], keepFiles=True))

        for ttr in x.keys():
            if getVal(x[ttr])>0.9:
                # print ( "SETTING GAME ",  ttr, getVal(x[ttr]) )
                setLB(x[ttr],1)

        for (t1,t2) in games:
            for r in basicRounds:
                gameInBasicRound[(t1,t2,r)].lowBound = 0
                gameInBasicRound[(t1,t2,r)].upBound = defaultGameRepetions
        #         if gameInBasicRound[(t1,t2,r)].value()>0 and  gameInBasicRound[(t1,t2,r)].value()<2  :
        #             print ("??",getTeamById[t1],getTeamById[t2],r, gameInBasicRound[(t1,t2,r)].value())
        



# # TEST START
# for t1 in realteams:
#     for t2 in realteams:
#         if t1!=t2:
#             for r in basicRounds:
#                 gameInBasicRound[(t1,t2,r)].lowBound = 0
#                 gameInBasicRound[(t1,t2,r)].upBound = 0

# cntr =0
# undecidedGames = [ (t1,t2) for t1 in realteams for t2 in realteams if t1!=t2 ]
# for (t1,t2,r) in chosenGames:
#     homers = [t1] + regionalKids[t1]
#     awayers = [t2] + regionalKids[t2]
#     for t11 in homers:
#         for t22 in awayers:
#             gameInBasicRound[(t11,t22,r)].lowBound = 1
#             gameInBasicRound[(t11,t22,r)].upBound = 1
#             undecidedGames.remove((t11,t22))
#             cntr+=1
# print (cntr, " games set")
# print (len(undecidedGames), " undecided Games :", undecidedGames)
# for (t1,t2) in undecidedGames:
#     for r in basicRounds:
#         gameInBasicRound[(t1,t2,r)].upBound = 1

# for ttr in x.keys():
#     x[ttr].cat= LpInteger

# if solver == "CBC":
#     model2.solve(PULP_CBC_CMD(fracGap = 0.0, maxSeconds = 40, threads = 8,msg=1))
# elif solver == "Gurobi":
#     model2.solve(GUROBI(MIPGap=0.0, TimeLimit=120,msg=1))
# else:
#     model2.solve(XPRESS(msg=1,maxSeconds = 25, keepFiles=True))

# for ttr in x.keys():
#     if x[ttr].value()>0.01:
#         print ( ttr, x[ttr].value() )


# # TEST END


else:
    nRuns=nPhases
    # maxSolveTime = 120
    mipgap=0.0
    # mipgap=0.95

# nRuns =1
onlyReopt= True
onlyReopt= False
onlyFewTrips= False
singleTripWeight =10 

if onlyReopt:
    nRuns=0

oldKPIs = { k[0]:k[1] for k in [kk.split("__") for kk in thisScenario.sol_kpis.split("___")]}
    
maxIntRound=nRounds

print (optSteps)

missing_imp=[]    
cntr =0
for st in optSteps:
    print (" - " ,st )
    cntr +=1
    if runMode=='New' and st[0] == "HARDCONSTRAINTS":
        for bl in blockings:
            blockingVio[bl['id']].upBound=0
            print ("blocking tightened : " , getTeamById [bl['team_id']] , bl['day_id']  )                
        for enc in encwishes:
            if enc['seed']:
                encVio[enc['id']].upBound=0
    
    
    if runMode=='New' and len(st)>=1 and st[0] in ["PATTERNS","HOMEAWAY", "BASICGAME", "GAME","GAMES", "GROUP", "TRIPS", "LP-HEURISTIC"]:
        newRounds = []
        print()            
        optTarget = st[0]
        if len(st)>1 :
            for rf in  st[1].split(","):
                rr= rf.split("-")
                if len(rr)==1 :
                    newRounds.append(min(nRounds,int(rr[0])))
                else:
                    for ii in range (int(rr[0]), min(nRounds, int(rr[1]))+1):
                        newRounds.append(ii)                        
            newRoundsString = st[1]
        else : 
            newRounds = rounds
            newRoundsString = "1-"+str(nRounds) 

        optsteptime = maxSolveTime
        optstepgap = mipgap

        if len(st)>=3 and st[2]!="":
            optstepgap = float(st[2])
        if len(st)>=4 and st[3]!="":
            optsteptime = float(st[3])
        
        print (newRounds)

        # if not thisSeason.minBreaks and runMode=='Improve':
        if st[0] == "LP-HEURISTIC":
            print("STARTING LP HEURISTIC")

        if st[0] == "PATTERNS":
            for (p,t,ph) in assignPattern2.keys():
                if ph==0 or not thisSeason.symmetry:
                    assignPattern2[(p,t,ph)].cat = pulp.LpInteger
            

        if st[0] == "HOMEAWAY":
            for t in teams:
                for r in newRounds:
                    homeInRound[(t,r)].cat = pulp.LpInteger

        if st[0] == "BASICGAME":
            for (t1,t2) in games:
                for r in newRounds:
                    gameInBasicRound[(t1,t2,r)].cat = pulp.LpInteger

        if st[0] in ["GAME","GAMES"]:
            for (t,t2) in games:
                for r in newRounds:
                    for rd in getRoundDaysByRound[r]:
                        makeIntVar(x[(t,t2,rd)])
                    # if thisSeason.gamesPerRound=="one day":
                    #     makeIntVar(x[(t,t2,getRoundDaysByRound[r][0])])
                    #     print ("makeintvar " ,t1,t2, getRoundDaysByRound[r][0],getRoundDaysByRound[r])
                    # else:
                    #     for rd in getRoundDaysByRound[r]:
                    #         makeIntVar(x[(t,t2,rd)])
            
        getSingleTripElementsByRound = { r : [] for r in rounds}
        if st[0] in ["TRIP","TRIPS"]:
            singleTripWeight =1000
            # onlyFewTrips= True
            for (t1,d,c) in  tripToSingleTripElement.keys():
                getSingleTripElementsByRound[getRoundByDay[d]].append((t1,d,c))
            for r in newRounds:
                for tdc in getSingleTripElementsByRound[r]:
                    makeIntVar(tripToSingleTripElement[tdc])
            
        if st[0] == "GROUP" and len(st)>=5:
            cfname = st[4].strip()
            if cfname in  conf_teams.keys():              
                optTarget += " "+ cfname
                print ("checking GROUP", st[4].strip())
                for (t1,t2) in games:
                    optstepgap = mipgap
                    if t1 in conf_teams[cfname] and t2 in conf_teams[cfname]:
                        print ("REOPT GROUP ", cfname , t1,t2)
                        for r in newRounds:
                            makeIntVar(x_round[(t1,t2,r)])
                            for rd in getRoundDaysByRound[r]:
                                makeIntVar(x[(t1,t2,rd)])


        # optsteptime= 30

        print ('########################')
        print ('# SOLVING MODEL '+optTarget+'  FOR ROUNDS '+ newRoundsString+' USING GAP ' + str(optstepgap) + ' and MAXTIME ' + str(optsteptime) + ' SOLVER '+solver+' #')
        print ('########################')
        writeProgress("Optimize "+st[0]+"  for rounds  " + newRoundsString, thisScenario.id, int( cntr/len(optSteps)*100 ))

        if RUN_ENV == 'celery' and task: 
            task.update_state(state='Solving Model '+str(st[0]), meta={'timestamp':time.time(),'objective':-1, "user ": user_name, "league ": str(thisLeague)})
        
        if solver == "CBC":
            model2.solve(PULP_CBC_CMD(fracGap = optstepgap, maxSeconds = optsteptime, threads = 8,msg=1))
        elif solver == "Gurobi":
            model2.solve(GUROBI(MIPGap=optstepgap, TimeLimit=optsteptime,msg=1, Method=2,NodeMethod=2))
        elif solver == "Xpress":
            model2.solve(XPRESS(msg=1,targetGap=optstepgap, maxSeconds = optsteptime,  options=["THREADS=12,DEFAULTALG=4,DETERMINISTIC=0,CUTSTRATEGY=0"], keepFiles=True))
        else:
            # for debugging:    
            # with open ("model2.txt", "w") as f:
            #     f.write(model2.__repr__())
            model2.solve(XPRESS_PY(msg=1,gapRel=optstepgap,  timeLimit  = optsteptime))

        if model2.status<0:
            print("Status: " , model2.status)

            if model2.status in [0,-1,-2]:
                report_solverstatus(user_name,thisScenario)

            if solver != "xpress":
                writeProgress("Model infeasible .", thisScenario.id,0)
                if RUN_ENV == 'celery' and task: 
                    print( {'timestamp':time.time(),'objective':-1, "user ": user_name, "league ": str(thisLeague)})
                else:
                    print( 'Model could not be solved')

        if not lowerBoundFound:
            if solver == "XPRESS_PY":
                lowerBoundFound= XPRESS_PY.getAttribute(XPRESS_PY, model2, "bestbound")
                print("LOWER BOUND " ,lowerBoundFound )

        cntr_rnd =0
        if st[0] == "LP-HEURISTIC":
            for (t1,t2) in games:
                for r in newRounds:
                    for rd in getRoundDaysByRound[r]:
                        if getVal(x[(t1,t2,rd)])>0.65:
                            setLB(x[(t1,t2,rd)],1)
                            print ("rounding up " , getTeamById[t1], "-" ,getTeamById[t2], rd , getVal(x[(t1,t2,rd)]))
                            cntr_rnd +=1 
                            # print (t1,t2,rd)
                        # else:
                        #     setUB(x[(t1,t2,rd)],0)
                        # #     print(t1,t2 , " no game ")
                        #     # x[(t1,t2,rd)].upBound = 0
            print ("Totally rounded up " , cntr_rnd)


        if st[0] == "PATTERNS":
            for (p,t,ph) in assignPattern2.keys():
                if ph==0 or not thisSeason.symmetry:
                    if assignPattern2[(p,t,ph)].value() >0.9 :
                        print ('fixing pattern '+ str(p) + ' : '+ getTeamById[t] +"  in phase " + str(ph))
                        assignPattern2[(p,t,ph)].lowBound = 1
                    else:
                        assignPattern2[(p,t,ph)].upBound = 0
            

        if st[0] == "HOMEAWAY":
            print (teams)
            print (newRounds)
            for t in teams:
                for r in newRounds:
                    if homeInRound[(t,r)].value() >0.9 :
                        print ('fixing home '+ str(r) + ' : '+ getTeamById[t] +"  " + str(homeInRound[(t,r)].value()))
                        homeInRound[(t,r)].lowBound = 1
                    else:
                        homeInRound[(t,r)].upBound = 0
            

        if st[0] == "BASICGAME":
            for r in newRounds:
                for (t1,t2) in games:
                    if getTeamById[t1]!="-" and getTeamById[t2]!="-" and  (t1,t2,r) in gameInBasicRound.keys() and type(gameInBasicRound[(t1,t2,r)])!= int:
                        if getVal(gameInBasicRound[(t1,t2,r)])>0.9:
                            gameInBasicRound[(t1,t2,r)].lowBound = 1
                        else:
                            gameInBasicRound[(t1,t2,r)].upBound = 0
                            # print (r, ' : ', getTeamById[t1], ' - ',getTeamById[t2] )

        if st[0] in ["GAME","GAMES"]:
            # crappyGames = [ g for g in fixedGames if fixedGameVio[g].value() >0.9 ]
            feedback = "Optimize games...."
            missing_imp=[]
            for (t1,t2,d) in fixedGames:
                if fixedGameVio[(t1,t2,d)].value() >0.9:
                    feedback += 'Not fixed :' +getDayById[d]['day']  +' : '+getTeamById[t1] + ' - ' + getTeamById[t2] + '<br> '
            for (t1,t2,d) in fixedGames2:
                if fixedGame2Vio[(t1,t2,d)].value() >0.9:
                    feedback += 'Not fixed :' +getDayById[d]['day']  +' : '+getTeamById[t1] + ' - ' + getTeamById[t2] + '<br> '
            for (t1,t2) in realgames:
                if missingGamesVio[(t1,t2)].value() >0.9:
                    feedback += 'Game missing : '+getTeamById[t1] + ' - ' + getTeamById[t2] + ' ' + str(missingGamesVio[(t1,t2)].value()) + '<br> \n'
                    missing_imp += [(1,nRounds,[t1,t2], 50)] 

            print (missing_imp)
            print (feedback)
            print ("number of assigned games : " , sum([getVal(x[ttrd]) for ttrd in x.keys()]))

            for (t1,t2) in games:
                for r in newRounds:
                    for rd in getRoundDaysByRound[r]:
                        if getVal(x[(t1,t2,rd)])>0.9:
                            setLB(x[(t1,t2,rd)],1) 
                            print ("fixing " ,t1,t2,rd, x[(t1,t2,rd)].lowBound )
                        else:
                            setUB(x[(t1,t2,rd)],0)
                        #     print(t1,t2 , " no game ")
                            # x[(t1,t2,rd)].upBound = 0

            # for (t1,t2,rd) in x.keys():
            #     if getVal(x[(t1,t2,rd)])>0.9:
            #         print ("setLB(x[",t1,",",t2, "," , rd , "],1)")

        if st[0] in ["TRIP","TRIPS"]:
            for r in newRounds:
                for tdc in getSingleTripElementsByRound[r]:
                    if getVal(tripToSingleTripElement[tdc])>0.9:
                        setLB(tripToSingleTripElement[tdc],1) 
                        print ("fixing " ,tdc, tripToSingleTripElement[tdc] )
                    else:
                        setUB(tripToSingleTripElement[tdc],0) 

        if st[0] == "GROUP" and len(st)>=5:
            print ("fixing GROUP", st[4].strip())
            for (t1,t2) in games:
                if t_conference[t1]!=0 and t_conference[t2]!=0 and st[4].strip() in [ t_conference[t2].name, t_conference[t1].name] : 
                    # print ("checking in group ", t1,t2)                        
                    for r in newRounds:
                        for rd in getRoundDaysByRound[r]:
                            if  getVal(x[(t1,t2,rd)])>0.99:
                            # if x[(t1,t2,rd)].value()>0.99:
                                setLB(x[(t1,t2,rd)],1)
                                # print ("fixing in GROUP",t1,t2,rd)
                                # print (t1,t2,rd)
                            else:
                                setUB(x[(t1,t2,rd)],0)

        for r in basicRounds:
            for t1 in realteams:
                homeInBasicRound[(t1,r)].lowBound = 0
                homeInBasicRound[(t1,r)].upBound  = 10
                awayInBasicRound[(t1,r)].lowBound = 0
                awayInBasicRound[(t1,r)].upBound  = 10
                for t2 in opponents[t1]:
                    if (t1,t2) in games:
                        gameInBasicRound[(t1,t2,r)].cat = pulp.LpContinuous
                        gameInBasicRound[(t1,t2,r)].lowBound = 0

        debug = False
        if debug:
            print (str(blockingVioTotal.value()) , " violated Blockings out of " , nBlockingHome  )
            for bl in blockings :
                if (blockingVio[bl['id']].value()>0.9) and bl['type'] in ["Home", "Hide","Game"] :
                    print (bl )

            print (str(travelVioTotal.value()) , " violated Travel Restrictions out of " , nBlockingAway  )
            for bl in blockings :
                if (blockingVio[bl['id']].value()>0.9) and bl['type']=='Away' :
                    print (bl )

            if gew['Breaks'] > 0:
                print (str(breakVioTotal.value()) , " Breaks :"  )
                for bl in breaks :
                    for t in realteams:
                        if (breakVio[(bl['id'],t)].value()>0.9) :
                            print (bl, ' ' , str(t) )

            if gew['Home-/Away'] > 0:
                print ("Violated HA-Wishes out of " , len(hawishes)  )
                for haw in hawishes :
                    for el in elemHaWishes[haw['id']]:
                        if (HawVioTooLess[el].value()+HawVioTooMuch[el].value() >0.9) :
                            print (haw)

            if gew['Encounters'] > 0:
                print ("Violated Encounter-Wishes out of " , nElemEncWishes )
                for enc in encwishes :
                    if (encVio[enc['id']].value()>0.9) :
                        print (enc)

        
        for t in realteams:
            for r in newRounds:
                homeInRound[(t,r)].cat = pulp.LpContinuous
                for t2 in opponents[t]:
                    for rd in getRoundDaysByRound[r]:
                        # if x[(t,t2,d)].value() >0.1 :
                        #     print ('looking '+ str(r) + ' : '+ getTeamById[t] + ' - '+ getTeamById[t2] + "  " + str(x[(t,t2,d)].value()))
                        if (t,t2) in games and  getVal(x[(t,t2,rd)]) >0.9 :
                            # print ('fixing '+ str(rd) + ' : '+ getTeamById[t] + ' - '+ getTeamById[t2] )
                            setLB(x[(t,t2,rd)], x[(t,t2,rd)].value())
        currentSolution =[ (t1,t2,r,d) for (t1,t2) in realgames for (r,d) in roundDays if getVal(x[(t1,t2,(r,d))]) >0.9 ]

# print ("####################")
# print ("testing feasibility 2")
# print ("####################")
# model2.solve(XPRESS(msg=1,maxSeconds = 10 , keepFiles=True))
# print ("####################")
# print ("testing done")
# print ("####################")

print (impScript)

for r in rounds:
    for t in teams:
        homeInRound[(t,r)].lowBound = 0
        homeInRound[(t,r)].upBound = 1

for (t1,t2) in games:
    for r in rounds:
        for rd in getRoundDaysByRound[r]:
            makeIntVar(x[(t1,t2,rd)])

if runMode!='Improve':
    if mathModelName=="NBA":
        print ("buidling badRepeaters")
        badRepeaters = [ (t,r) for (t,r) in badRepeater.keys() if badRepeater[(t,r)].value()>0.9]
        for (t,r) in badRepeaters :
            print ("bad repeater :",r, getTeamById[t])  

    if thisSeason.useFeatureBackToBack:
        print ("buidling badBackToBackers")
        badBackToBackers = [ (t,r)  for (t,r) in badBackToBack.keys() if  badBackToBack[(t,r)].value()>0.9]
        print ("done buidling badBackToBackers")
        for (t,r) in badBackToBackers :
            print ("bad back to back :", int(badBackToBack[(t,r)].value()) , getNiceDay[r], getTeamById[t] )          

tightenBlockings = nTeams>20 and nRounds>60
if runMode=='Improve':
    if tightenBlockings:
        for bl in blockings:
            if blockingVio[bl['id']].value()==0:
                blockingVio[bl['id']].upBound=0
                print ("blocking tightened : " , bl['team'] , bl['day']  )

print ('Solved Again')
print ('NOW REOPT')

mipgap=0.05        


starweights= sorted([ starweight[t] for t in teams], reverse = True)

localsearch_time = max(0,min(localsearch_time, 0.9*TASK_TIME_LIMIT-(time.time()-start_time)))

if runMode == 'New' and localsearch_time == 0:
    localsearch = False
else:
    localsearch = True

# localsearch_time=10

print (starweights)

nFarTeams = 1
if gew['Trips'] > 5:
    # nFarTeams += gew['Trips'] -5
    nFarTeams = nTeams

nFarTeams = min(nFarTeams,len(starweights)-1)

print ("nFarTeams ", nFarTeams)
print (starweight)

farTeams = [ t for t in teams if starweight[t] > starweights[nFarTeams] ]
print ("farTeams ", farTeams)

# cntr=0
# for (t,t1,t2,r) in tripSaving.keys():
    # if t in farTeams or t1 in farTeams or t2 in farTeams :
        # # print ("consider  trip " ,  (t,t1,t2,r) )
        # cntr+=4
        # tripSaving[(t,t1,t2,r)].upBound =1
        # model2 += tripSaving[(t,t1,t2,r)] <=  lpSum([ (x[(t1,t,(r,d) )]+x[(t2,t,(r,d))]) for d in [  latestDay[r]  ]  ])
        # model2 += tripSaving[(t,t1,t2,r)] <=  lpSum([ (x[(t1,t,(r+1,d))]+x[(t2,t,(r+1,d))]) for d in [earliestDay[r+1]] ])
        # model2 += tripSaving[(t,t1,t2,r)] <=  lpSum([ (x[(t1,t,(r,latestDay[r]))]+x[(t1,t,(r+1,earliestDay[r+1]))]) ])
        # model2 += tripSaving[(t,t1,t2,r)] <=  lpSum([ (x[(t2,t,(r,latestDay[r]))]+x[(t2,t,(r+1,earliestDay[r+1]))]) ])
# print (str(cntr) + ' constraints added' )

local_start =time.time()

last_objective =value(model2.objective)

forbidRepetitions=True
forbidRepetitions=False

useDailyTrips = nRounds*nTeams <=200

print ("useDailyTrips" ,useDailyTrips , nRounds , nTeams )

if localsearch:
    cntr =0
    if thisSeason.useFeatureTrips and initTripsLate:
        if thisSeason.tripMode=="Clusters": 
            if useDailyTrips:            
                for d1 in days:
                    otherTripDays = [ d2 for d2 in days if getDateTimeDay[d1]< getDateTimeDay[d2] and  getDateTimeDay[d2]<=getDateTimeDay[d1]+datetime.timedelta(days=thisSeason.maxDistanceWithinTrip+1) and (len(getRoundsByDay[d1])*len(getRoundsByDay[d2])>1 or  list(getRoundsByDay[d1])!=list(getRoundsByDay[d2]) )]

                    for t in realteams:                 
                        for c in clusters:
                            if gew['Trips']>0  and not c in t_clusters[t] and len(otherTripDays)>0:
                                tripToClusterDaily[(t,d1,c)].upBound=1
            #                            tripToClusterDaily[(t,d1,c)] = pulp.LpVariable('tripToClusterDaily_'+str(t)+'_'+str(d1)+'_'+str(c), lowBound = 0, upBound = 1, cat = pulp.LpContinuous)
                                model2 +=  tripToClusterDaily[(t,d1,c)]  <= away_in_cluster_day[t,d1,c]
                                model2 +=  tripToClusterDaily[(t,d1,c)]  <= lpSum([away_in_cluster_day[t,d2,c] for d2 in otherTripDays ])
            #                            print ('considering trip of ' , getTeamById[t], ' in days ' , getNiceDay[d1] , getNiceDay[otherTripDays[0]] , otherTripDays,' to cluster ' , c , cluster_teams[c])
                                cntr +=2
            else :
                for r in rounds:
                    otherTripRounds = [r2 for r2 in rounds if r2>r and getDateTimeDay[latestDay[r]]<= getDateTimeDay[earliestDay[r2]] and getDateTimeDay[earliestDay[r2]]-getDateTimeDay[latestDay[r]]<=datetime.timedelta(days=thisSeason.maxDistanceWithinTrip+1)]
                    # print ("trip rounds ", r, otherTripRounds)
                    for t in realteams: 
                        # forbid same opponents on successive days
                        for t2 in realteams: 
                            if t!=t2 and r>1 and forbidRepetitions:                        
                                model2 +=  lpSum([ (x[(t,t2,rd )]+x[(t2,t,rd)]) for rd in getRoundDaysByRound[r-1]+getRoundDaysByRound[r] ]) <= 1
                        
                        for c in clusters:
                            if len(otherTripRounds)>0 and gew['Trips']>0  and not c in t_clusters[t] :
                                    tripToCluster[(t,r,c)].upBound=1
                                    model2 +=  tripToCluster[(t,r,c)]  <= away_in_cluster[t,r,c]
                                    model2 +=  tripToCluster[(t,r,c)]  <= lpSum([away_in_cluster[t,r2,c] for r2 in otherTripRounds  ])
                                    # print ('considering trip of ' , getTeamById[t], ' in rounds ' , r , otherTripRounds,' to cluster ' , c )
                                    cntr +=2

            #                        else :
            #                            model2 +=  tripToCluster[(t,r,c)] == 0
        else:
            tripDayPairs = {}
            for d1 in days:
                for d2 in days: 
                    daysBetween = (getDateTimeDay[d2]-getDateTimeDay[d1]).days -1
                    if daysBetween>=0 and getDayMaxGames[d1]>0 and getDayMaxGames[d2]>0 and daysBetween<=thisSeason.maxDistanceWithinTrip and getRoundByDay[d1]!=getRoundByDay[d2]:
                        # print (d1,d2,daysBetween, getNiceDay[d1],  getNiceDay[d2], )
                        if d1 not in tripDayPairs.keys():
                            tripDayPairs[d1]=[]
                        tripDayPairs[d1].append((d2, daysBetween))


            for t in teams:
                # print (getTeamById[t])
                # print (getTeamById[t],tripElements)
                for (c,v1,v2,v3,v4) in tripElements[t]:
                    # if getTeamById[t]=="Regatas":
                    #     print ("POSS TRIP ",getTeamById[t], (c, [ getTeamById[t3] for t3 in v1 ] , v2, [ getTeamById[t3] for t3 in v2 ] , [ getTeamById[t3] for t3 in v3 ] , [ getTeamById[t3] for t3 in v4 ]), trip_minDays[c], trip_maxDays[c])
                    for d1 in tripDayPairs.keys():  
                        if getWeekDay[d1] in trip_weekdays[c] and ( not onlyFewTrips or t%6==d%6 ) :
                            otherTripDays = [d2 for (d2,daysBetween) in tripDayPairs[d1] if daysBetween>=trip_minDays[c] and daysBetween<=trip_maxDays[c]]
                            inBetweenDays = [d2 for (d2,daysBetween) in tripDayPairs[d1] if daysBetween<=trip_minDays[c] ]
                            otherTripDays3 = list(set([d2 for d11 in tripDayPairs.keys() for (d2,daysBetween) in tripDayPairs[d11] if d11 in otherTripDays and daysBetween>=trip_minDays[c] and daysBetween<=trip_maxDays[c]]))
                            otherTripDays4 = list(set([d2 for d11 in tripDayPairs.keys() for (d2,daysBetween) in tripDayPairs[d11] if d11 in otherTripDays3 and daysBetween>=trip_minDays[c] and daysBetween<=trip_maxDays[c]]))
                            # print ("possible? ", getTeamById[t] , getNiceDay[d1], otherTripDays,otherTripDays3,otherTripDays4)
                            if len(otherTripDays)>0 and (thisSeason.tripLength <3 or len (v3)==0 or len(otherTripDays3)>0)  and (thisSeason.tripLength <4 or len (v4)==0 or len(otherTripDays4)>0) :
                                # print ("building trip for " , getTeamById[t], " starting" , getNiceDay[d1] ,  [ getNiceDay[d] for d in otherTripDays ],  [ getNiceDay[d] for d in otherTripDays3 ] , [ getNiceDay[d] for d in otherTripDays4 ] )
                                tripToSingleTripElement[(t,d1,c)].upBound=1
                                model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v1                         for rd in getRoundDaysByDay[d1]])
                                model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v2 for d2 in otherTripDays for rd in getRoundDaysByDay[d2]])
                                for d3 in inBetweenDays:
                                    model2 += tripToSingleTripElement[(t,d1,c)] <= 1- home[t,d3]
                                    model2 += tripToSingleTripElement[(t,d1,c)] <= 1-lpSum([ x[(t2,t,rd)] for t2 in realteams if t2 not in v2 for rd in getRoundDaysByDay[d3]])
                                # if getTeamById[t]=="Regatas":
                                #     print (" ", getNiceDay[d1], [ getNiceDay[d2] for d2 in inBetweenDays ] ,[ getNiceDay[d2] for d2 in otherTripDays ] ," <= ",  [ (t2,t,rd) for t2 in v2 for d2 in otherTripDays for rd in getRoundDaysByDay[d2]])
                                if thisSeason.tripLength >=3 and len(v3)>0:
                                    model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v3 for d2 in set(otherTripDays3) for rd in getRoundDaysByDay[d2]])
                                if thisSeason.tripLength >=4 and len(v4)>0: 
                                    model2 += tripToSingleTripElement[(t,d1,c)] <= lpSum([ x[(t2,t,rd)] for t2 in v4 for d2 in set(otherTripDays4) for rd in getRoundDaysByDay[d2]])
                                if (len(v3)>0 and len(otherTripDays3)==0) or (len(v4)>0 and len(otherTripDays4)==0) :
                                    tripToSingleTripElement[(t,d1,c)].upBound=0
                                else:
                                    cntr +=2

        print ("built ", cntr , " trip constraints late")

    for t1 in realteams:
        for r in rounds:
            homeInRound[(t1,r)].lowBound = 0
            homeInRound[(t1,r)].upBound = 1
            awayInRound[(t1,r)].lowBound = 0
            awayInRound[(t1,r)].upBound = 1
        for rd in roundDays:
            for t2 in opponents[t1]:
                setLB(x[(t1,t2,rd)],0)

    for (t1,t2) in games:
        for r in rounds:
            if (t1,t2,r) in gameInBasicRound.keys():
                gameInBasicRound[(t1,t2,r)].lowBound = 0
                gameInBasicRound[(t1,t2,r)].upBound = 10
                for rd in getRoundDaysByRound[r]:
                    setLB(x[(t1,t2,rd)],0)
                    setUB(x[(t1,t2,rd)],1)

    mipgap=0.00
    # if thisSeason.useFeatureTrips and thisLeague.name not in ["EuroLeague Basketball", "La Liga Argentina"] :
    #     mipgap=0.02

    maxSolveTime= 2000
    nReopt=4
    nReopt=1*nTeams+5
    for (t1,t2) in games:
        for rd in roundDays:
            setLB(x[(t1,t2,rd)],0)

    # restore solution just created
    print ("RESTORING OLD SOLUTION !!!")
    if runMode=='New' :
        use_currentSolution= True

    # print ("TESTING")
    # model2+= lpSum([ fixedGameVio[(t1,t2,d)] for (t1,t2,d) in fixedGames])
    # model2+= standardObjectives
    # for ttr in x.keys():
    #     makeIntVar(x[ttr])
    # model2.solve(GUROBI(MIPGap=0.0, TimeLimit=40,msg=1))
    # for  (t1,t2,d) in fixedGames:
    #     if fixedGameVio[(t1,t2,d)].value() >0.1:
    #         print ("Games missing :  " , getTeamById[t1] ,  getTeamById[t2] , getNiceDay[d])
    # print ("TESTING DONE9")
    

    # print ("\n###############\nTIME TAKEN SO FAR : " , time.time()-start_time, "\n##################\n")

    # startSolution = [(41994, 42001, 3, 69446), (41994, 42172, 6, 69452), (41994, 42177, 8, 69456), (41994, 42235, 2, 69445), (42002, 42085, 2, 69444), (42002, 42203, 3, 69447), (42002, 42181, 7, 69454), (42002, 42065, 5, 69451), (42173, 42175, 8, 69456), (42173, 41998, 2, 69445), (42173, 42166, 5, 69450), (42173, 42030, 6, 69453), (42001, 42002, 8, 69456), (42001, 42008, 4, 69449), (42001, 42179, 2, 69445), (42001, 42236, 6, 69453), (41999, 42173, 4, 69448), (41999, 42176, 7, 69454), (41999, 42006, 2, 69445), (41999, 42009, 6, 69453), (42085, 42040, 5, 69451), (42085, 41997, 1, 69442), (42085, 42158, 4, 69449), (42085, 42082, 7, 69455), (42040, 41999, 1, 69442), (42040, 41996, 6, 69452), (42040, 42039, 8, 69456), (42040, 42238, 3, 69447), (42205, 41994, 1, 69441), (42205, 42036, 4, 69448), (42205, 42207, 7, 69455), (42205, 42180, 6, 69452), (42175, 42205, 3, 69447), (42175, 42004, 1, 69441), (42175, 42041, 7, 69454), (42175, 42237, 6, 69453), (41998, 41994, 4, 69449), (41998, 42036, 5, 69450), (41998, 42179, 7, 69455), (41998, 42082, 1, 69443), (42036, 42085, 6, 69452), (42036, 42176, 3, 69447), (42036, 42166, 1, 69443), (42036, 42238, 7, 69455), (42008, 41999, 8, 69456), (42008, 41996, 3, 69446), (42008, 42177, 6, 69452), (42008, 42009, 1, 69442), (42004, 42001, 7, 69454), (42004, 42008, 5, 69450), (42004, 42039, 3, 69447), (42004, 42065, 2, 69444), (42203, 42040, 2, 69444), (42203, 41998, 8, 69456), (42203, 42158, 6, 69452), (42203, 42030, 4, 69448), (41997, 42175, 5, 69451), (41997, 42172, 2, 69445), (41997, 42181, 4, 69449), (41997, 42237, 7, 69455), (42176, 42002, 6, 69453), (42176, 41997, 8, 69456), (42176, 42207, 4, 69448), (42176, 42180, 1, 69443), (42172, 42173, 1, 69441), (42172, 42203, 5, 69451), (42172, 42006, 7, 69454), (42172, 42235, 4, 69448), (41996, 42205, 5, 69451), (41996, 42004, 8, 69456), (41996, 42041, 4, 69449), (41996, 42236, 2, 69445), (42166, 41994, 7, 69455), (42166, 42172, 3, 69446), (42166, 42158, 2, 69445), (42166, 42235, 6, 69453), (42041, 42205, 2, 69445), (42041, 41997, 3, 69446), (42041, 42166, 8, 69456), (42041, 42065, 6, 69453), (42181, 42001, 5, 69450), (42181, 41998, 3, 69446), (42181, 42207, 2, 69444), (42181, 42030, 8, 69456), (42006, 42173, 3, 69447), (42006, 41996, 1, 69443), (42006, 42181, 6, 69453), (42006, 42009, 8, 69456), (42177, 42040, 7, 69455), (42177, 42176, 2, 69444), (42177, 42039, 5, 69451), (42177, 42237, 3, 69447), (42039, 42175, 4, 69449), (42039, 42008, 2, 69444), (42039, 42179, 6, 69452), (42039, 42180, 7, 69455), (42207, 42085, 8, 69456), (42207, 42004, 6, 69453), (42207, 42177, 1, 69442), (42207, 42082, 3, 69447), (42179, 42002, 4, 69448), (42179, 42203, 1, 69442), (42179, 42006, 5, 69451), (42179, 42236, 8, 69456), (42158, 41999, 3, 69446), (42158, 42036, 8, 69456), (42158, 42041, 1, 69443), (42158, 42238, 5, 69450), (42235, 42002, 1, 69441), (42235, 42176, 5, 69450), (42235, 42158, 7, 69455), (42235, 42009, 3, 69446), (42082, 42175, 2, 69444), (42082, 41997, 6, 69452), (42082, 42166, 4, 69449), (42082, 42065, 8, 69456), (42065, 42001, 1, 69443), (42065, 41996, 7, 69454), (42065, 42177, 4, 69448), (42065, 42236, 3, 69447), (42180, 41999, 5, 69451), (42180, 42172, 8, 69456), (42180, 42179, 3, 69446), (42180, 42238, 2, 69444), (42030, 42085, 3, 69446), (42030, 42008, 7, 69454), (42030, 42207, 5, 69450), (42030, 42237, 2, 69445), (42236, 42040, 4, 69448), (42236, 42203, 7, 69454), (42236, 42181, 1, 69442), (42236, 42082, 5, 69450), (42237, 41994, 5, 69451), (42237, 42004, 4, 69448), (42237, 42039, 1, 69441), (42237, 42235, 8, 69456), (42009, 42173, 7, 69454), (42009, 42036, 2, 69444), (42009, 42041, 5, 69450), (42009, 42180, 4, 69449), (42238, 42205, 8, 69456), (42238, 41998, 6, 69452), (42238, 42006, 4, 69449), (42238, 42030, 1, 69441)]
    # startSolution = [(41994, 42001, 5, 69450), (41994, 42172, 6, 69452), (41994, 42177, 8, 69456), (41994, 42235, 2, 69445), (42002, 42085, 2, 69444), (42002, 42203, 3, 69447), (42002, 42181, 7, 69454), (42002, 42065, 5, 69451), (42173, 42175, 8, 69456), (42173, 41998, 2, 69445), (42173, 42166, 5, 69451), (42173, 42030, 6, 69453), (42001, 42002, 8, 69456), (42001, 42008, 4, 69448), (42001, 42179, 6, 69453), (42001, 42236, 2, 69445), (41999, 42173, 4, 69448), (41999, 42176, 7, 69454), (41999, 42006, 2, 69445), (41999, 42009, 6, 69453), (42085, 42040, 7, 69455), (42085, 41997, 3, 69447), (42085, 42158, 4, 69449), (42085, 42082, 1, 69443), (42040, 41999, 1, 69442), (42040, 41996, 6, 69452), (42040, 42039, 8, 69456), (42040, 42238, 3, 69446), (42205, 41994, 1, 69441), (42205, 42036, 4, 69449), (42205, 42207, 5, 69450), (42205, 42180, 7, 69455), (42175, 42205, 3, 69446), (42175, 42004, 1, 69442), (42175, 42041, 7, 69455), (42175, 42237, 5, 69450), (41998, 41994, 3, 69446), (41998, 42036, 1, 69443), (41998, 42179, 5, 69450), (41998, 42082, 7, 69455), (42036, 42085, 6, 69452), (42036, 42176, 3, 69447), (42036, 42166, 2, 69444), (42036, 42238, 7, 69454), (42008, 41999, 8, 69456), (42008, 41996, 3, 69446), (42008, 42177, 6, 69452), (42008, 42009, 1, 69443), (42004, 42001, 7, 69454), (42004, 42008, 5, 69451), (42004, 42039, 3, 69446), (42004, 42065, 2, 69445), (42203, 42040, 2, 69444), (42203, 41998, 8, 69456), (42203, 42158, 6, 69453), (42203, 42030, 4, 69448), (41997, 42175, 6, 69453), (41997, 42172, 7, 69455), (41997, 42181, 4, 69448), (41997, 42237, 2, 69444), (42176, 42002, 6, 69453), (42176, 41997, 8, 69456), (42176, 42207, 4, 69448), (42176, 42180, 1, 69442), (42172, 42173, 1, 69441), (42172, 42203, 5, 69450), (42172, 42006, 4, 69449), (42172, 42235, 8, 69456), (41996, 42205, 2, 69445), (41996, 42004, 4, 69449), (41996, 42041, 5, 69450), (41996, 42236, 8, 69456), (42166, 41994, 7, 69455), (42166, 42172, 3, 69447), (42166, 42158, 1, 69442), (42166, 42235, 4, 69449), (42041, 42205, 6, 69453), (42041, 41997, 1, 69443), (42041, 42166, 8, 69456), (42041, 42065, 4, 69448), (42181, 42001, 3, 69447), (42181, 41998, 6, 69452), (42181, 42207, 2, 69444), (42181, 42030, 8, 69456), (42006, 42173, 3, 69446), (42006, 41996, 1, 69443), (42006, 42181, 5, 69451), (42006, 42009, 8, 69456), (42177, 42040, 4, 69449), (42177, 42176, 2, 69444), (42177, 42039, 5, 69451), (42177, 42237, 7, 69454), (42039, 42175, 4, 69448), (42039, 42008, 7, 69455), (42039, 42179, 2, 69445), (42039, 42180, 6, 69453), (42207, 42085, 8, 69456), (42207, 42004, 6, 69452), (42207, 42177, 1, 69442), (42207, 42082, 3, 69447), (42179, 42002, 4, 69448), (42179, 42203, 1, 69441), (42179, 42006, 7, 69454), (42179, 42236, 3, 69447), (42158, 41999, 5, 69451), (42158, 42036, 8, 69456), (42158, 42041, 3, 69446), (42158, 42238, 2, 69444), (42235, 42002, 1, 69441), (42235, 42176, 5, 69451), (42235, 42158, 7, 69454), (42235, 42009, 3, 69446), (42082, 42175, 2, 69444), (42082, 41997, 5, 69450), (42082, 42166, 6, 69452), (42082, 42065, 8, 69456), (42065, 42001, 1, 69441), (42065, 41996, 7, 69455), (42065, 42177, 3, 69447), (42065, 42236, 6, 69452), (42180, 41999, 3, 69446), (42180, 42172, 2, 69444), (42180, 42179, 8, 69456), (42180, 42238, 5, 69450), (42030, 42085, 5, 69450), (42030, 42008, 2, 69445), (42030, 42207, 7, 69455), (42030, 42237, 3, 69447), (42236, 42040, 5, 69451), (42236, 42203, 7, 69454), (42236, 42181, 1, 69443), (42236, 42082, 4, 69449), (42237, 41994, 4, 69449), (42237, 42004, 8, 69456), (42237, 42039, 1, 69442), (42237, 42235, 6, 69453), (42009, 42173, 7, 69454), (42009, 42036, 5, 69451), (42009, 42041, 2, 69445), (42009, 42180, 4, 69448), (42238, 42205, 8, 69456), (42238, 41998, 4, 69449), (42238, 42006, 6, 69452), (42238, 42030, 1, 69441)]
    # currentSolution = startSolution
    startSolution = currentSolution


    model2 += standardObjectives +specialObjectives

    for (t1,t2,(r,d)) in x.keys():
        setLB(x[(t1,t2,(r,d))],0)
        if (t1,t2,r,d) in currentSolution or [t1,t2,r,d] in currentSolution:                
            setLB(x[(t1,t2,(r,d))],1)

    model2.solve(XPRESS_PY(msg=1,gapRel=0.05,options=["MAXTIME=600"], warmStart=True))

    init_violated_hawishes = []
    init_violated_encwishes = []
    for haw in HAWish.objects.filter(scenario=s2,active=True,prio__in=["Hard","A"]).order_by('prio'):
        if round(hawVio[haw.id].value(),2) > 0:
            print("INIT HA-Wish violated : " , haw.prio, haw.reason , round(hawVio[haw.id].value(),2))   
            init_violated_hawishes.append(haw)     
    for enc in EncWish.objects.filter(scenario=s2,active=True,prio__in=["Hard","A"]).order_by('prio'):
        if round(encVio[enc.id].value(),2) > 0:
            print("INIT Encounter Wish violated : " ,enc.prio, enc.reason , round(encVio[enc.id].value(),2))
            init_violated_encwishes.append(enc)    


    sample_teams = 20
    sample_rounds = 5
    fixTeams = []
    # model2_bak = copy.deepcopy(model2)
    counter = 0
    f = None
    for key in x_round.keys():
        setLB(x_round[key],0)
    for key in x.keys():
        setLB(x[key],0)

    while(True):
        print("I",counter,fixTeams)    
        f = open(f'debug_{counter}.html','w')    
        print ("\n###############\nCUSTOM RUN\n##################\n")
        f.write("<br>###############<br>CUSTOM RUN<br>##################<br>")
        nFixations = 0
        fixedVars = defaultdict(lambda:defaultdict(lambda:0))
        for key in x_round.keys():
            setLB(x_round[key],0)
        for (t1,t2,(r,d)) in x.keys():
            if (t1,t2,r,d) in currentSolution or [t1,t2,r,d] in currentSolution:
                setStart(x[(t1,t2,(r,d))],1)
                if (counter == 0) or (t1 in fixTeams and t2 in fixTeams and r in fixRounds):
                    setLB(x_round[(t1,t2,r)],1)
                    fixedVars[t1][r] = 1
                    fixedVars[t2][r] = 1
                    nFixations += 1
            else:
                setStart(x[(t1,t2,(r,d))],0)

        print(f"FIXED {nFixations} Variables")
        print("NOW SOLVING")
        if counter == 0:
            gapRel = 0
        else:
            gapRel = 0.03
        model2.solve(XPRESS_PY(msg=1,gapRel=gapRel,options=["MAXTIME=7200"], warmStart=True))
        f.write(f"Objective: {value(model2.objective)}<br>")

        if counter == 0:
            start_objective = value(model2.objective)


        currentSolution =[ (t1,t2,r,d) for (t1,t2) in games for (r,d) in roundDays if t1!=t2 and getVal(x[(t1,t2,(r,d))]) >0.9 ]
        for haw in HAWish.objects.filter(scenario=s2,active=True,prio__in=["Hard","A"]).order_by('prio'):
            if round(hawVio[haw.id].value(),2) > 0:
                print("HA-Wish violated : " , haw.prio, haw.reason , round(hawVio[haw.id].value(),2))   
                f.write(f"HA-Wish violated : {haw.prio} {haw.reason} {round(hawVio[haw.id].value(),2)}<br>")
        for enc in EncWish.objects.filter(scenario=s2,active=True,prio__in=["Hard","A"]).order_by('prio'):
            if round(encVio[enc.id].value(),2) > 0:
                print("Encounter Wish violated : " ,enc.prio, enc.reason , round(encVio[enc.id].value(),2)) 
                f.write(f"Encounter Wish violated : {enc.prio} {enc.reason} {round(encVio[enc.id].value(),2)}<br>")
        print ("\n###############\n EVAL RUN\n##################\n")


        f.write("<br>###############<br> EVAL RUN<br>##################<br>")
        model2 += standardObjectives +specialObjectives

        for (t1,t2,(r,d)) in x.keys():
            setLB(x_round[(t1,t2,r)],0)
            if (t1,t2,r,d) in currentSolution or [t1,t2,r,d] in currentSolution:                
                if (counter == 0) or (t1 in fixTeams and t2 in fixTeams and r in fixRounds):
                    # setLB(x_round[(t1,t2,r)],1)
                    pass
                else:
                    setStart(x[(t1,t2,(r,d))],1)
            else:
                setStart(x[(t1,t2,(r,d))],0)



        model2.solve(XPRESS_PY(msg=1,gapRel=gapRel,options=["MAXTIME=7200"], warmStart=True))

        f.write(f"Objective: {value(model2.objective)}<br>")



        season = thisScenario.season
        days = season.day_days.all()
        dates = season.getDatetimeObjects()

        days_header = {
            'months': [],
            'days': [],
        }
        prevY = ""
        prevM = ""
        countM = 0
        for d in dates:        
            a, b, m, d, y = d.strftime('%a;%b;%m;%d;%Y').split(";")

            if prevM == "" or prevM == b:
                countM += 1            
                prevM = b        
                prevY = y
            if b != prevM:
                days_header['months'].append((f"{prevM} {prevY}",countM))
                countM = 1
                prevM = b        
                prevY = y

            days_header['days'].append((f"{a}, {d}.{m}.",1))

        days_header['months'].append((prevM,countM))


        widget_rounds = [
            {'name':r, 'id':-r}
            for r in range(1,season.nRounds+1)
        ]
        teams = season.scheduler_teams.filter(active=True)

        groups = {}
        if season.groupBased:
            for c in Conference.objects.filter(scenario=scenario,display_group=True).order_by('name'):
                groups[c.name] = c.teams.all()

        getTeamById = {
            team.id: team for team in teams
        }

        home_dict = defaultdict(lambda:defaultdict(lambda:""))
        home_dict2 = defaultdict(lambda:defaultdict(lambda:""))
        common_home_dict = defaultdict(lambda:defaultdict(lambda:""))
        away_dict = defaultdict(lambda:defaultdict(lambda:""))
        away_dict2 = defaultdict(lambda:defaultdict(lambda:""))
        common_away_dict = defaultdict(lambda:defaultdict(lambda:""))

        for game in [(d,t1,t2,r) for (t1,t2,r,d) in startSolution]:
            home_dict[int(game[0])][int(game[1])] = getTeamById[int(game[2])].shortname
            away_dict[int(game[0])][int(game[2])] = getTeamById[int(game[1])].shortname
            home_dict[-int(game[3])][int(game[1])] = getTeamById[int(game[2])].shortname
            away_dict[-int(game[3])][int(game[2])] = getTeamById[int(game[1])].shortname

        for game in [(d,t1,t2,r) for (t1,t2,r,d) in currentSolution]:
            home_dict2[int(game[0])][int(game[1])] = getTeamById[int(game[2])].shortname
            away_dict2[int(game[0])][int(game[2])] = getTeamById[int(game[1])].shortname
            home_dict2[-int(game[3])][int(game[1])] = getTeamById[int(game[2])].shortname
            away_dict2[-int(game[3])][int(game[2])] = getTeamById[int(game[1])].shortname

            if home_dict[int(game[0])][int(game[1])] == getTeamById[int(game[2])].shortname:
                common_home_dict[int(game[0])][int(game[1])] = getTeamById[int(game[2])].shortname
            if home_dict[-int(game[3])][int(game[1])] == getTeamById[int(game[2])].shortname:
                common_home_dict[-int(game[3])][int(game[1])] = getTeamById[int(game[2])].shortname

            if away_dict[int(game[0])][int(game[2])] == getTeamById[int(game[1])].shortname:
                common_away_dict[int(game[0])][int(game[2])] = getTeamById[int(game[1])].shortname
            if away_dict[-int(game[3])][int(game[2])] == getTeamById[int(game[1])].shortname:
                common_away_dict[-int(game[3])][int(game[2])] = getTeamById[int(game[1])].shortname

        context = {
            "groups":groups,
            "teams":teams,
            "days":days,
            "days_header":days_header,
            "rounds":widget_rounds,
            "home_dict":home_dict,
            "away_dict":away_dict,
            "home_dict2":home_dict2,
            "away_dict2":away_dict2,
            "common_home_dict":common_home_dict,
            "common_away_dict":common_away_dict,    
            "fixedVars":fixedVars,    
            }
        f.write(render_to_string("widgets/w_comparison_matrix.html", context))

        

        if value(model2.objective) < start_objective - 1:
            f.write(f"FOUND BETTER SOLUTION {value(model2.objective)}")
            print("FOUND BETTER SOLUTION", value(model2.objective))
            print(currentSolution)
            print("#############################")
            currentSolution =[ (t1,t2,r,d) for (t1,t2) in games for (r,d) in roundDays if t1!=t2 and getVal(x[(t1,t2,(r,d))]) >0.9 ]
            violated_hawishes = []
            violated_encwishes = []
            for haw in HAWish.objects.filter(scenario=s2,active=True,prio__in=["Hard","A"]).order_by('prio'):
                if round(hawVio[haw.id].value(),2) > 0:
                    print("HA-Wish violated : " , haw.prio, haw.reason , round(hawVio[haw.id].value(),2))   
                    f.write(f"HA-Wish violated : {haw.prio} {haw.reason} {round(hawVio[haw.id].value(),2)}<br>")
                    violated_hawishes.append(haw)     
            for enc in EncWish.objects.filter(scenario=s2,active=True,prio__in=["Hard","A"]).order_by('prio'):
                if round(encVio[enc.id].value(),2) > 0:
                    print("Encounter Wish violated : " ,enc.prio, enc.reason , round(encVio[enc.id].value(),2))
                    f.write(f"Encounter Wish violated : {enc.prio} {enc.reason} {round(encVio[enc.id].value(),2)}<br>")
                    violated_encwishes.append(enc)   

            startSolution = currentSolution
            start_objective = value(model2.objective)
            init_violated_hawishes = violated_hawishes
            init_violated_encwishes = violated_encwishes

        else:
            f.write(f"USING STARTSOLUTION")
            print(f"USING STARTSOLUTION")
            currentSolution = startSolution
            violated_hawishes = init_violated_hawishes
            violated_encwishes = init_violated_encwishes

        f.close()


        newObjectives = None
        for haw in random.sample(violated_hawishes,min(2,len(violated_hawishes))):
        # for haw in violated_hawishes:
            print("Selected HA-Wish: " , haw.prio, haw.reason)   
            if newObjectives:
                newObjectives += hawVio[haw.id]*10000
            else:
                newObjectives = hawVio[haw.id]*10000

        for enc in random.sample(violated_encwishes,min(2,len(violated_encwishes))):
        # for enc in violated_encwishes:
            print("Selected Encounter Wish: " ,enc.prio, enc.reason)
            if newObjectives:
                newObjectives += encVio[enc.id]*10000
            else:
                newObjectives = encVio[enc.id]*10000

        model2 += standardObjectives +specialObjectives + newObjectives
        print ("\n###############\n END OF \n##################\n")

        if random.randint(0,1) == 0:
            fixTeams = random.sample(realteams,sample_teams)
            fixRounds = rounds
        else:
            fixTeams = realteams
            fixRounds = random.sample([1,2,3,4,5,6,7],sample_rounds)



        # if counter == 1:
        #     exit()

        counter += 1
    exit()












    newRounds = []
    localSearchResults = []        
    while  localsearch and len(impScript)>0:
        print ( (time.time() - local_start) , "  " , localsearch_time, " ", (time.time() - local_start) < localsearch_time) 
        for (impType, firstNewRound,lastNewRound, newTeams, maxTime, par) in impScript:
            if localsearch:
                # if impType != "LOCALAI": 
                #     print ("trying ")                        
                #     if len(newRounds) == 0:
                #         print(lastNewRound)
                #         newRounds = range (firstNewRound,lastNewRound+1)
                if impType == "INIT":
                    impScript = impScript[1:]
                elif impType in ["SMART_TEAMS", "SMART_ROUNDS"]: 
                    newTeams, newRounds = smartNeighbor(impType, int(newTeams), int(lastNewRound), model2, x, hawishes, elemHaWishes, HawVioTooLess, HawVioTooMuch, 
                        elemHaWishTeams,elemHaWishDays, encwishes, elemEncWishes, encVioTooLess, 
                        encVioTooMuch, prioVal, elemEncWishGames,elemEncWishDays,breaks,realteams,
                        breakVio,nRounds,currentSolution,getTeamById)
                    if len(newRounds) == 0:
                        newRounds = range (firstNewRound,nRounds+1)    
                else:
                    newRounds = range (firstNewRound,lastNewRound+1)


                stadium_sharers = []
                for t3 in newTeams:
                    if t3 in realteams:
                        stadium_sharers+=teamsWithSameStadium[t3] 

                print ("newTeams   ", newTeams)
                print ("newTeams++ ",stadium_sharers)
                if len(stadium_sharers)<=3:
                    newTeams = list(set(newTeams+stadium_sharers))
                print ("allTeams  ", newTeams)
                print (newRounds, newTeams, maxTime)
                print ((time.time() - local_start) > localsearch_time)
                print ("STOPCOMPUTATION",Scenario.objects.get(id=thisScenario.id).stopComputation)
                    # if time is up then do a last run sticking to  currentSolution
                if  (time.time() - local_start) > localsearch_time or Scenario.objects.get(id=thisScenario.id).stopComputation:
                    print ("Time is up, restoring best solution found so far\n\n")
                    localsearch=False
                    # firstNewRound=1
                    # lastNewRound=nRounds,
                    newTeams=[]
                    newRounds=[]
                    maxTime=2000
                newDays=[]
                for r in newRounds:
                    for r2 in rounds :
                        if r==r2 or (thisSeason.symmetry and (r2-r)%(nTeams-1)==0 ):
                            # print ("adding round " , r2)
                            newDays+=getDays[r2]

                # print (newDays)
                print ("###################################################")
                print ("REOPT {} ROUNDS {} FOR TEAMS {} IN AT MOST {}s".format(impType,newRounds,[getTeamById[t] for t in newTeams],maxTime))
                print ("###################################################")
                print ( " seconds ", (time.time() - local_start))
                if localsearch_time >0 :
                    pro=min(95,10+ int(90*((time.time() - local_start) )/ localsearch_time )  )
                    print ("§§§§§§§§" ,pro, ' ', (time.time() - local_start)  , ' / ', localsearch_time )
                else:
                    pro = 95
                ntstring =''
                for t in newTeams:
                    ntstring += getTeamById[t] + ', '
                lo = ""
                if isinstance(last_objective,(int,float)):
                    lo= "  (" + str(int(0.01+last_objective-1)) +")"
                # print (task.request)
                # writeProgress("Reoptimize  " +str(firstNewRound)+ " - " + str(lastNewRound ) + " for teams " + ntstring[:-2] + lo, thisScenario.id ,pro)
                if user_is_staff:
                    writeProgress("Reoptimize  " +str(newRounds) + " for teams " + ntstring[:-2] + lo, thisScenario.id ,pro)
                else:
                    writeProgress("Reoptimizing ...  "  + lo, thisScenario.id ,pro)

                print ("len(currentSolution) " ,len(currentSolution), use_currentSolution)

                for (t1,t2,r,d) in currentSolution:                        
                    if (t1,t2,(r,d)) in x.keys():
                        if ((t1 in newTeams or t2 in newTeams) and d in newDays) or not use_currentSolution:
                            setLB(x[(t1,t2,(r,d))],0)
                            setStart(x[(t1,t2,(r,d))],1)
                            if par=="STICKY_HOME" and random.random()<1.0:
                                model2+= home[(t1,d)]>=1
                                # setLB(home[(t1,d)],1)
                                print ( getTeamById[t1] , " stays home on " , getNiceDay[d])
                                # print (type(home[(t1,d)]))
                            if par=="STICKY_ENCOUNTER" and random.random()<1.0:
                                model2+=  x[(t1,t2,(r,d))]+  x[(t2,t1,(r,d))] ==1
                                # setLB(home[(t1,d)],1)
                                print ( getTeamById[t1] , " and " , getTeamById[t2] , " still play on " , getNiceDay[d])
                                # print (type(home[(t1,d)]))
                                
                            # print ("RELEASING ", (t1,t2,d))
                        else:
                            setLB(x[(t1,t2,(r,d))],1)
                            # print ("FIXXING ", (t1,t2,d))

                # if RUN_ENV == 'celery' and task: 
                #     task.update_state(state='PHASE-8', meta={'timestamp':time.time(),'objective':99999999})

                if solver == "CBC":
                    model2.solve(PULP_CBC_CMD(fracGap = mipgap, maxSeconds = maxTime, threads = 8,msg=1)) 
                elif solver == "Gurobi":
                    model2.solve(GUROBI(MIPGap=mipgap, TimeLimit=maxTime, warmStart=False))
                else:
                    try:
                        model2.solve(XPRESS(msg=1,targetGap=mipgap,maxSeconds = -maxTime, options=["THREADS=12,DEFAULTALG=4,DETERMINISTIC=0,CUTSTRATEGY=0"], warmStart=True, keepFiles=True))
                    except:
                        print(" NOT SOLVED ")
                        model2.status = pulp.LpStatusNotSolved

                # print ("RRRR")
                # for (t1,t2,r) in x_round.keys():
                #     if getVal(x_round[(t1,t2,r)])>0.1:
                #         print (t1,t2, getTeamById[t1], getTeamById[t2],  r, getVal(x_round[(t1,t2,r)]))

                print ( "model2.status=",model2.status , pulp.LpStatus[model2.status])
                print ( "model2.objective=",value(model2.objective) )
                print ( " => ",model2.status in [-1,-2]  or not value(model2.objective) )

                # new xpress/pulp sometimes gives status -3 (undefined) even though the solution is fine!!
                if model2.status in [-1,-2] or not value(model2.objective):
                    if localsearch: 
                        continue
                    elif solver != "xpress" or not value(model2.objective):
                        writeProgress("Model could not be solved within " + str(maxTime)+" seconds ....", thisScenario.id,0)
                        if RUN_ENV == 'celery' and task: 
                            print( {'timestamp':time.time(),'objective':-1, "user ": user_name, "league ": str(thisLeague)})
                        else:
                            print( 'Model could not be solved')
                
                if RUN_ENV == 'celery' and task:
                    # reset_stdout(f,filename) 
                    task.update_state(state='Reopt Rounds', meta={'timestamp':time.time(),'objective':value(model2.objective), "user ": user_name, "league ": str(thisLeague)})

                new_currentSolution =[ (t1,t2,r,d) for (t1,t2) in realgames for (r,d) in roundDays if t1!=t2 and getVal(x[(t1,t2,(r,d))]) >0.9999 ]
                        
                print ("status", model2.status, pulp.LpStatus[model2.status], len(new_currentSolution), len(currentSolution), len(new_currentSolution)>=len(currentSolution), not value(model2.objective), value(model2.objective), last_objective)
                
                newLSR = LocalSearchResult(season=thisSeason,
                    created_at=datetime.datetime.now(),
                    searchType=impType,
                    nTeams=len(newTeams),
                    nRounds=len(newRounds),
                    maxTime=maxTime,
                    objective=value(model2.objective),
                    lastObjective=last_objective or 0,
                    nElemEncWishes=nElemEncWishes,
                    nElemHaWishes=nElemHaWishes,
                    nBlockings=(nBlockingHome+nBlockingAway),
                    nGames=nGames,
                    nCols=model2.numVariables(),
                    nRows=model2.numConstraints(),
                    runtime=model2.solutionTime)  
                print ( "model2.status=",model2.status )
                print  (specialGameControl or len(new_currentSolution)>=len(currentSolution) ,   (solver != "xpress" or model2.status not in [-1,-2])  ,  ( not last_objective or value(model2.objective) <= last_objective+0.01))
                if  (specialGameControl or len(new_currentSolution)>=len(currentSolution)) and (solver != "xpress" or model2.status not in [-1,-2])  and ( not last_objective or value(model2.objective) <= last_objective+0.01):
                    print ("now using this solution with objective value " + str(value(model2.objective)) )
                    for (t1,t2,r,d) in currentSolution:
                        if (t1 in newTeams or t2 in newTeams) and d in newDays and False:
                            setStart(x[(t1,t2,(r,d))],0)
                            # x[(t1,t2,(r,d))].start=0
                    currentSolution =[ (t1,t2,r,d) for (t1,t2) in games for (r,d) in roundDays if t1!=t2 and getVal(x[(t1,t2,(r,d))]) >0.9 ]
                    currentSolution =[ (t1,t2,r,d) for (t1,t2,r,d) in currentSolution if getTeamById[t1]!="-"  and  getTeamById[t2]!="-" ]
                    currentLocation = { (t,d) : False for t in teams for d in days} 
                    for (t1,t2,r,d) in currentSolution:
                        currentLocation[(t2,d)]=t1
                        currentLocation[(t1,d)]=t1

                    print ("length of current solution " , len (currentSolution))
                    last_objective=value(model2.objective)
                    print ("Home-/Away : " , gew['Home-/Away'], "*",HawVioTotal.value())
                    print ("Pairings :" , gew['Pairings'], "*", pairingVioTotal.value())
                    print ("Blockings :" , gew['Availabilities'], "*", blockingVioTotal.value() ,"+ " ,  blockingVioTotal2.value() )
                    print ("goodHomesTotal :" , gew['Availabilities'], "*", goodHomesTotal.value() )
                    print ("travelVioTotal :" , gew['Availabilities'], "*", travelVioTotal.value())
                    print ("gamesTooCloseTotal :" , gew['Availabilities'], "*", gamesTooCloseTotal.value())
                    print ("tripSavedTotal2 : -5*" , gew['Trips'], "*", tripSavedTotal2.value())
                    print ("breakVioTotal :" , gew['Breaks'], "*", breakVioTotal.value())
                    print ("break3VioTotal :" , gew['Breaks'], "*", break3VioTotal.value())
                    print ("encVioTotal : 5*" , gew['Encounters'], "*", encVioTotal.value())
                    print ("seedVioTotal : 5* " , gew['Encounters'], "*", seedVioTotal.value())
                    print ("confVioTotal :" , gew['Conferences'], "*", confVioTotal.value())
                    print ("tooManyHomesInStadiumTotal :" , gew['Availabilities'], "*", tooManyHomesInStadiumTotal.value())
                    print ("broadVioTotal :" , gew['Broadcasting'], "*", broadVioTotal.value())
                    print ("derbiesMissingTotal :" , gew['Derbies'], "*", derbiesMissingTotal.value())
                    print ("competitionVioTotal : 5 *", competitionVioTotal.value())
                    print ("tooManyTop4InRowTotal : 0.0 *", tooManyTop4InRowTotal.value())
                    print ("fixedGameVioTotal :" , gew['Availabilities'], "*", fixedGameVioTotal.value())
                    print ("missingGamesVioTotal :" , gew['Availabilities'], "*", missingGamesVioTotal.value())
                    print ("totalAttendance : -0.01*", totalAttendance.value())
                    print ("oldScenGamesTotal : ", -oldScenGamesTotal.value())
                    print ("specialObjectives :" , specialObjectives.value() if specialObjectives else 0)                        
                    if thisSeason.useFeatureBackToBack:
                        greyCntr =0
                        redCntr =0
                        yellowCntr =0
                        allCntr=0
                        for (d1,d2) in critical_day_pairs:
                            print ("no time zone crossings for at days " , getNiceDay[d1],"->",getNiceDay[d2],nextCritical[d2])
                            for t in realteams: 
                                if currentLocation[(t,d1)] and currentLocation[(t,d2)] :
                                    t1 = currentLocation[(t,d1)]
                                    t2 = currentLocation[(t,d2)]
                                    allCntr+=1
                                    if (t2,1.0) in bad_travel_out[t1]:
                                        print ("GREY BACK TO BACK FOUND IN TOUR :", getNiceDay[d1] ,getTeamById[t] , " -> " , getTeamById[t1] , " -> " , getTeamById[t2] )  
                                        greyCntr +=1
                                    if (t2,0.05) in bad_travel_out[t1]:
                                        print ("RED BACK TO BACK FOUND IN TOUR :", getNiceDay[d1] ,getTeamById[t] , " -> " , getTeamById[t1] , " -> " , getTeamById[t2] )
                                        redCntr +=1
                                    if (t2,0.003) in bad_travel_out[t1]:
                                        print ("YELLOW BACK TO BACK FOUND IN TOUR :", getNiceDay[d1] ,getTeamById[t] , " -> " , getTeamById[t1] , " -> " , getTeamById[t2] )
                                        yellowCntr +=1

                        print ("badBackToBack_Total ", badBackToBack_Total.value())
                        b2bvios = [(getTeamById[t],getNiceDay[d], int(0.5+badBackToBack[(t,d)].value())) for t in teams for d in days if (t,d) in badBackToBack.keys() and badBackToBack[(t,d)].value()>0.1 ]
                        greenB2B = [ (t1,t2,w) for (t1,t2,w) in b2bvios if w==1]
                        yellowB2B = [ (t1,t2,w) for (t1,t2,w) in b2bvios if w==3]
                        redB2B = [ (t1,t2,w) for (t1,t2,w) in b2bvios if w==50]
                        greyB2B = [ (t1,t2,w) for (t1,t2,w) in b2bvios if w==1000]
                        print ( len(greyB2B) , " + ",len(redB2B) , " + ",len(yellowB2B) , " + ",len(greenB2B))
                        print ( greyCntr , " + ", redCntr , " + ", yellowCntr , " + green = ", allCntr)
                        print (greyB2B+redB2B)

                    if mathModelName=="NBA":
                        print ("badRepeater_Total_NBA ", badRepeater_Total_NBA.value())
                        print ("tooLongTrip_Total_NBA ", tooLongTrip_Total_NBA.value())                            
                        print ("eastWestTrip_Total_NBA ", eastWestTrip_Total_NBA.value())     
                                
                newRounds = []
                if impType != 'INIT':
                    localSearchResults.append(newLSR)

    LocalSearchResult.objects.bulk_create(localSearchResults)   

mipgap=0.05

if thisSeason.useFeatureKickOffTime and not evalRun:
    for (t1,t2) in games :
        for rd in roundDays:
            if getVal(x[(t1,t2,rd)]) >0.99:
                model2+= x[(t1,t2,rd)]==1
                for tm in times:
                    makeIntVar(x_time[(t1,t2,rd,tm)])
                # makeIntVar(x_time[(t1,t2,rd,getIdByTime["Early"])])

    writeProgress("Refining times ", thisScenario.id , 99)

    print ("######################")
    print ("## REFINING TIMES ####")
    print ("######################")

    if solver == "CBC":
        model2.solve(PULP_CBC_CMD(fracGap = mipgap, maxSeconds = 600, threads = 8,msg=1))
    elif solver == "Gurobi":
        # mipgap = 1.0
        model2.solve(GUROBI(MIPGap=mipgap, TimeLimit=600))
    else:
        try:
            model2.solve(XPRESS(msg=1,maxSeconds = 60, targetGap=mipgap ,options=["THREADS=12"], keepFiles=True))
        except:
            model2.status = pulp.LpStatusNotSolved

    if model2.status<0 or not value(model2.objective):
        if solver!="xpress" or not value(model2.objective):
            writeProgress("Model could not be solved within " + str(maxTime)+" seconds ....", thisScenario.id,0)
            if RUN_ENV == 'celery' and task: 
                print( {'timestamp':time.time(),'objective':-1, "user ": user_name, "league ": str(thisLeague)})
            else:
                print( 'Model could not be solved')
    
    if RUN_ENV == 'celery' and task: 
        task.update_state(state='Reopt Rounds', meta={'timestamp':time.time(),'objective':value(model2.objective), "user ": user_name, "league ": str(thisLeague)})
