280 lines
7.3 KiB
Python
Executable File
280 lines
7.3 KiB
Python
Executable File
# %%
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PROJECT_PATH = '/home/md/Work/ligalytics/leagues_stable/'
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import os, sys
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sys.path.insert(0, PROJECT_PATH)
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os.environ.setdefault("DJANGO_SETTINGS_MODULE", "leagues.settings")
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os.environ["DJANGO_ALLOW_ASYNC_UNSAFE"] = "true"
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from leagues import settings
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# settings.DATABASES['default']['NAME'] = PROJECT_PATH+'/db.sqlite3'
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settings.DATABASES['default']['ENGINE'] = 'django.db.backends.postgresql_psycopg2'
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settings.DATABASES['default']['HOST'] = '0.0.0.0'
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settings.DATABASES['default']['PORT'] = '5432'
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settings.DATABASES['default']['USER'] = 'postgres'
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settings.DATABASES['default']['PASSWORD'] = 'secret123'
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settings.DATABASES['default']['NAME'] = 'mypgsqldb'
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settings.DATABASES['default']['ATOMIC_REQUESTS'] = False
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settings.DATABASES['default']['AUTOCOMMIT'] = True
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settings.DATABASES['default']['CONN_MAX_AGE'] = 0
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settings.DATABASES['default']['CONN_HEALTH_CHECKS'] = False
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settings.DATABASES['default']['OPTIONS'] = {}
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os.environ["XPRESSDIR"] = "/opt/xpressmp"
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os.environ["XPRESS"] = "/opt/xpressmp/bin"
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os.environ["LD_LIBRARY_PATH"] = os.environ["XPRESSDIR"] + "/lib"
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os.environ["DYLD_LIBRARY_PATH"] = os.environ["XPRESSDIR"] + "/lib"
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os.environ["SHLIB_PATH"] = os.environ["XPRESSDIR"] + "/lib"
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os.environ["LIBPATH"] = os.environ["XPRESSDIR"] + "/lib"
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os.environ["PYTHONPATH"] = os.environ["XPRESSDIR"] + "/lib"
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os.environ["CLASSPATH"] = os.environ["XPRESSDIR"] + "/lib/xprs.jar"
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os.environ["CLASSPATH"] = os.environ["XPRESSDIR"] + "/lib/xprb.jar" + os.pathsep + os.environ["CLASSPATH"]
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os.environ["CLASSPATH"] = os.environ["XPRESSDIR"] + "/lib/xprm.jar" + os.pathsep + os.environ["CLASSPATH"]
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os.environ["PATH"] = os.environ["XPRESSDIR"] + "/bin" + os.pathsep + os.environ["PATH"]
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import django
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django.setup()
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from scheduler.models import *
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from pulp import *
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from django.db.models import Q
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from django.template.loader import render_to_string
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from qualifiers.models import *
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from common.models import GlobalTeam, GlobalCountry
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from scheduler.models import Season, Scenario, Team, DayObj, CountryClash, Country
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from qualifiers.draws import groupTeams, optimize_inversions4
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import random
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import time
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import json
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import csv
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import networkx as nx
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import matplotlib.pyplot as plt
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from django.contrib.sessions.models import Session
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scenario = Scenario.objects.get(id=9704)
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from scheduler.solver.tasks.optimize import optimize
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s2 = scenario.id
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user_name = 'md'
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user_is_staff = True
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runMode = 'Improve'
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localsearch_time = 60
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RUN_ENV = 'local'
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SOLVER = 'xpress'
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teams = Team.objects.filter(season=scenario.season,active=True).distinct()
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gamereqs = GameRequirement.objects.filter(scenario=scenario)
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# sol = optimize(task=None, s2=s2, user_name=user_name, user_is_staff=user_is_staff,
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# runMode=runMode, localsearch_time=localsearch_time, RUN_ENV=RUN_ENV, solver=SOLVER)
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def create_graph(pot=None):
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def hex_to_rgb(value):
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value = value.lstrip('#')
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lv = len(value)
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return tuple(int(value[i:i + lv // 3], 16) for i in range(0, lv, lv // 3))
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hex_colors = {
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1: "#ffff99",
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2: "#99ccff",
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3: "#FFcc99",
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4: "#CCFFCC",
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5: "#CCCCFF",
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6: "#9999FF",
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}
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rgb_colors = {}
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for c in hex_colors:
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rgb_colors[c] = hex_to_rgb(hex_colors[c])
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G = nx.Graph()
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node_colors = {}
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node_label = {}
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for t in teams:
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node_label[t] = f"{t.shortname}"
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if pot is None:
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node_color = rgb_colors[t.pot]
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node_colors[node_label[t]] = hex_colors[t.pot]
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else:
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node_color = rgb_colors[pot[t]]
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node_colors[node_label[t]] = hex_colors[pot[t]]
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G.add_node(node_label[t],
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viz = {"color": {"a":0, "r": node_color[0], "g": node_color[1], "b": node_color[2]}, 'size':20})
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# for n in nx.nodes(G):
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# G.nodes[n]["viz"] = {}
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# G.nodes[n]["viz"]["color"] = colors[]
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for gq in gamereqs:
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if gq.team1 in teams and gq.team2 in teams:
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G.add_edge(node_label[gq.team1],node_label[gq.team2], capacity = 1.0)
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SubG = [G.subgraph(c).copy() for c in nx.connected_components(G)]
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# nx.draw(SubG[0], with_labels=True, font_weight='bold')
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sub = SubG[0]
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nx.draw(sub, with_labels=True,
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node_size=400, font_size=6, node_color=[node_colors[g] for g in list(sub.nodes())])
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pos = nx.nx_agraph.graphviz_layout(sub)
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nx.draw_networkx_edge_labels(
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sub, pos=pos, edge_labels={e: "" for e in list(sub.edges())}, font_color='black', font_size=6
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)
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nx.write_gexf(sub, "9704.gexf")
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distance = {}
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max_path = 0
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for t in teams:
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path = nx.shortest_path(G, source=t.shortname)
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for p in path:
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if len(path[p]) <= 2:
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length = 0
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elif len(path[p]) == 3:
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length = 1
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else:
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length = 2
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distance[(teams.get(shortname=t.shortname),teams.get(shortname=p))] = length
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# cut_value, partition = nx.minimum_cut(G, "Manch", "y")
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return distance
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# %%
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distance = create_graph()
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# %%
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# import xpress as xp
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# xp.controls.outputlog = 1
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# model = xp.problem(name='Draws', sense=xp.minimize)
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# model.setControl('maxtime' , 600)
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# distance = {(t1,t2): 1 for t1 in teams for t2 in teams}
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# for g in gamereqs:
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# if (g.team1,g.team2) in distance.keys():
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# distance[(g.team1,g.team2)] = 0
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# groups = range(1,3)
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# x = {}
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# y = {}
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# for g in groups:
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# for t in teams:
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# x[t,g] = xp.var(vartype=xp.binary)
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# for t1,t2 in distance.keys():
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# y[t1,t2] = xp.var(vartype=xp.binary)
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# model.addVariable(x)
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# model.addVariable(y)
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# for t1,t2 in y.keys():
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# for g in groups:
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# model.addConstraint(y[t1,t2] >= x[t1,g] + x[t2,g] - 1)
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# for t in teams:
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# model.addConstraint(xp.Sum(x[t,g] for g in groups) == 1)
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# for g in groups:
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# model.addConstraint(xp.Sum(x[t,g] for t in teams) == len(teams)/len(groups))
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# model.setObjective(xp.Sum(y[t1,t2]*distance[(t1,t2)] for (t1,t2) in y.keys()))
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# start_time = time.time()
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# model.solve()
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# comp_time = time.time()-start_time
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# teams = Team.objects.filter(season=scenario.season,active=True).distinct()
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# import xpress as xp
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# xp.controls.outputlog = 1
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# model = xp.problem(name='Draws', sense=xp.minimize)
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# model.setControl('maxtime' , 600)
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# groups = range(1,5)
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# x = {}
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# y = {}
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# for g in groups:
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# for t in teams:
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# x[t,g] = xp.var(vartype=xp.binary)
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# for gr in gamereqs:
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# y[gr.team1,gr.team2,g] = xp.var(vartype=xp.binary)
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# model.addVariable(x)
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# model.addVariable(y)
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# for t1,t2,g in y.keys():
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# model.addConstraint(y[t1,t2,g] >= (x[t1,g] - x[t2,g]))
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# model.addConstraint(y[t1,t2,g] >= (x[t2,g] - x[t1,g]))
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# for t in teams:
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# model.addConstraint(xp.Sum(x[t,g] for g in groups) == 1)
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# for g in groups:
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# model.addConstraint(xp.Sum(x[t,g] for t in teams) == len(teams)/len(groups))
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# model.setObjective(xp.Sum(y[key] for key in y.keys()))
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# start_time = time.time()
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# model.solve()
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# comp_time = time.time()-start_time
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# # %%
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# pot = {}
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# group_list = {g:[] for g in groups}
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# for g in groups:
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# print("GROUP",g)
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# for t in teams:
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# if model.getSolution(x[t,g]) > 0:
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# print("\t",t.id)
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# group_list[g].append(t.id)
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# pot[t] = g
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# print("")
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# # %%
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# # %%
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# print(group_list)
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# # %%
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# create_graph(pot) |