def __init__(self, parent=None):
super(SimWidget, self).__init__(parent)
self.setupUi(self)
self.colorEarth = '#009900'
self.colorWater = '#27b6e9'
self.timer = QTimer()
self.time = 500
self.running = False
fig = plt.figure()
self.ax = fig.add_subplot(111)
self.is_plot = False
self.sim = Simulation()
self.prov = load_provinces()
self.countries = load_countries()
#region Buttons
self.worldMapBtn.clicked.connect(self.mapa_mundi)
self.cubaMapBtn.clicked.connect(self.mapa_cuba)
self.initialPopulationBtn.clicked.connect(
self.on_initial_population_clicked)
self.nextStepBtn.clicked.connect(self.on_next_step_clicked)
self.simBtn.clicked.connect(self.on_sim_clicked)
self.stopBtn.clicked.connect(self.on_stop_clicked)
#endregion
self.fill_header_table(self.tableWidget1)
self.fill_header_table(self.tableWidget2)
def get_fund_related_data(request, code, dataname, freq):
comp = sm.Comp(code)
if freq == 'y' or freq == 'a':
table = Company.objects.get(code=code).fund_y_set
else:
table = Company.objects.get(code=code).fund_q_set
ret = {}
ret['labels'] = []
ret['values'] = []
table = table.order_by('date')
for t in table:
date = t.date
ret['labels'].append(date)
v = comp.get_fund_related_data(stuff.MyDate(date), dataname, freq)
if v is None:
v = -1
ret['values'].append(v)
return JsonResponse(ret)
import os, django, sys
sys.path.append('/var/www/stockAnalyzeWeb')
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "stockAnalyzeWeb.settings")
django.setup()
from main.models import *
import main.Simulation as sm
from main.stuff import *
from random import shuffle
dfrom = MyDate('2007-12-03')
dto = MyDate('2017-12-03')
(sim, Sim) = sm.simInit(
num=6,
name='10 years buy 5 lowest PER every year',
detail='Buy 5 companies with lowest PER every 365 days for 10 years',
dfrom=dfrom,
dto=dto)
def strategy(t, comps, wallet, context):
sim.progress = (dfrom.gap(t) / dfrom.gap(dto)) * 100
sim.save()
if 'lastTrade' in context and context['lastTrade'] + 365 > t:
return
tradable = [c for c in comps if c.can_trade(t)]
tradable = [
c for c in tradable
# Variables (see Documentation for description) view = True # To turn on/off the use of SAP, go to Helpers/helpers.py and change the # global variable "SAP_PHYSICS" (defined after the import statements) to True/False. seed = "r@nd0M2" robot_number = 1 maxsteps = 10000 debug = 0 # begin debugging AFTER this timestep. 0 turns off debugging, change to 1 to debug w/ PDB comment = seed # seeding the simulation: turn this on to remove randomness in brain (for debugging) # behavior between runs will be identical. random.seed(seed) # Run the Simulation, input is the random seed Sim = Simulation() Sim.start(view, robot_number) # wrapped in a try/except block to catch errors and immediately begin # pdb at exception's location try: Sim.run_simulation(view,maxsteps,debug,comment) except: _, _, tb = sys.exc_info() traceback.print_exc() pdb.post_mortem(tb) # Display the simulation Sim.run_visualization() #SAP 2000 templates.sdb
class SimWidget(QMainWindow, Ui_SimulationWindow):
def __init__(self, parent=None):
super(SimWidget, self).__init__(parent)
self.setupUi(self)
self.colorEarth = '#009900'
self.colorWater = '#27b6e9'
self.timer = QTimer()
self.time = 500
self.running = False
fig = plt.figure()
self.ax = fig.add_subplot(111)
self.is_plot = False
self.sim = Simulation()
self.prov = load_provinces()
self.countries = load_countries()
#region Buttons
self.worldMapBtn.clicked.connect(self.mapa_mundi)
self.cubaMapBtn.clicked.connect(self.mapa_cuba)
self.initialPopulationBtn.clicked.connect(
self.on_initial_population_clicked)
self.nextStepBtn.clicked.connect(self.on_next_step_clicked)
self.simBtn.clicked.connect(self.on_sim_clicked)
self.stopBtn.clicked.connect(self.on_stop_clicked)
#endregion
self.fill_header_table(self.tableWidget1)
self.fill_header_table(self.tableWidget2)
def fill_header_table(self, table):
table.setRowCount(len(name_provinces))
table.setVerticalHeaderLabels(name_provinces)
table.setColumnCount(len(name_provinces))
table.setHorizontalHeaderLabels(short_provinces)
def fill_table(self, table, data):
for i, name in enumerate(name_provinces):
d_name = data[name]
for j, name in enumerate(name_provinces):
value = d_name[name]
item = QTableWidgetItem(str(value))
table.setItem(i, j, item)
def on_stop_clicked(self):
self.running = False
def on_sim_clicked(self):
self.running = True
self.simulate()
def simulate(self):
if self.running:
self.on_next_step_clicked()
self.timer.singleShot(self.time, self.simulate)
def on_initial_population_clicked(self):
self.iteration = 0
self.label.setText("paso:" + str(self.iteration))
population = self.sim.population()
self.iter = self.sim.simulate(10)
self.mapa_cuba()
self.print_population(population)
# self.print_arrow()
def print_arrow(self):
coord_1 = self.prov["La Habana"]
coord_2 = self.prov["Guantánamo"]
x, y = self.m([coord_1[1], coord_2[1]], [coord_1[0], coord_2[0]])
plt.annotate("",
xytext=(x[0], y[0]),
xy=(x[1], y[1]),
arrowprops=dict(arrowstyle='fancy'))
plt.draw()
def on_next_step_clicked(self):
self.iteration += 1
self.label.setText("paso: " + str(self.iteration))
population, migration, living_place = next(self.iter)
pp.pprint(population)
self.mapa_cuba()
self.print_population(population)
self.fill_table(self.tableWidget1, migration)
self.fill_table(self.tableWidget2, living_place)
def print_population(self, population):
lons = []
lats = []
labels = []
for par in population.items():
lons.append(self.prov[par[0]][1])
lats.append(self.prov[par[0]][0])
labels.append(par[1])
x, y = self.m(lons, lats)
# m.plot(x, y, '#000000', markersize=10)
labels = [x for x in population.values()]
for label, xpt, ypt in zip(labels, x, y):
plt.text(xpt, ypt, label)
# plt.show()
plt.draw()
def mapa_mundi(self):
plt.close()
m = Basemap(projection='cyl', resolution='l', area_thresh=1000.0)
m.drawcoastlines()
m.fillcontinents(color=self.colorEarth, lake_color=self.colorWater)
m.drawmapboundary(fill_color=self.colorWater)
m.drawcountries()
m.drawparallels(np.linspace(-90, 90, 7), labels=[1, 0, 0, 0])
m.drawmeridians(np.linspace(0, 360, 9), labels=[0, 0, 1, 0])
selected_countries = [
"Jamaica", "Cuba", "Puerto Rico", "Estados Unidos de América",
"Canadá", "España", "Francia", "Venezuela", "Brasil", "Argentina"
]
lons = [self.countries[x][1] for x in selected_countries]
lats = [self.countries[x][0] for x in selected_countries]
x, y = m(lons, lats)
m.plot(x, y, 'bo', markersize=10)
labels = selected_countries
for label, xpt, ypt in zip(labels, x, y):
plt.text(xpt - 0.3, ypt + 0.1, label, color='b')
# plt.show()
def mapa_cuba(self):
# plt.close()
self.ax.clear()
c_lon, c_lat = -79.5, 21.5
delta_lon, delta_lat = 6, 2.5
self.m = Basemap(projection='cyl',
resolution='i',
area_thresh=0.1,
lat_0=c_lat,
lon_0=c_lon,
llcrnrlat=c_lat - delta_lat,
llcrnrlon=c_lon - delta_lon,
urcrnrlat=c_lat + delta_lat,
urcrnrlon=c_lon + delta_lon)
self.m.drawcoastlines()
self.m.fillcontinents(color=self.colorEarth,
lake_color=self.colorWater)
self.m.drawmapboundary(fill_color=self.colorWater)
self.m.drawparallels(np.linspace(c_lat - delta_lat, c_lat + delta_lat,
7),
labels=[1, 0, 0, 0],
fmt='%.2f')
self.m.drawmeridians(np.linspace(c_lon - delta_lon, c_lon + delta_lon,
9),
labels=[0, 0, 1, 0])
lons = [x[1] for x in self.prov.values()]
lats = [x[0] for x in self.prov.values()]
x, y = self.m(lons, lats)
self.m.plot(x, y, 'bo', markersize=6)
labels = self.prov.keys()
for label, xpt, ypt in zip(labels, x, y):
self.ax.text(xpt - 0.3, ypt + 0.1, label, color='w')
if not self.is_plot:
self.is_plot = True
plt.show()
def get_data(stat_func, p,n_sims=1000,k=1):
s = Simulation(set_size=1, q_prob = 1e-3)
stats, _,_ = s.simulation_of_statistic(stat_func, [[p,k*p]],n_sims)
var = np.var(stats)
E = np.mean(stats)
return E, var
mode = 1
start_x = -10
stop_x = 10
periodic_boundary_conditions = True
gif_name = "test"
time_start = 0
# time_stop = 2*np.pi
time_stop = 1
delta_t = 1e-2
gamma = np.array(
[-2 for i in range(int((time_stop - time_start) / delta_t + 1))])
sim = Simulation(x_start=start_x,
x_stop=stop_x,
number_of_psi=number_of_psi,
number_of_spatial_dimensions=number_of_spatial_dimensions,
nonlinear=True)
NLSE = problems.NLSE(gamma,
x_start=start_x,
x_stop=stop_x,
number_of_psi=number_of_psi,
periodic=True)
init_state = NLSE.get_stationary_state()
init_state = 0.7 * np.exp(-NLSE.linspace**2 / 2)
u = NLSE.get_u()
p = NLSE.get_P()
def shooting(x0):
fill='black',
text=str(person.getName()),
font=("Purisa", 10))
def inoculatePeople(self):
self.master.after(2000, self.subInoculate)
def infectPeople(self):
self.time += 1
self.infectedListA, self.infectedListB = simulate.spreadInfection()
A, B = simulate.getDict()
self.master.after(1000, self.subInfect)
self.moveVirus(A, B)
simulate = Simulation()
simulate.secureStart()
clusterA = simulate.populationA.getClusters()
clusterB = simulate.populationB.getClusters()
populationA = simulate.populationA
populationB = simulate.populationB
targetA = simulate.Atargetlist
targetB = simulate.Btargetlist
infectListA = populationA.getLevelsOfInfection()
infectListB = populationB.getLevelsOfInfection()
root = gwaphics.Tk()
app = Application(root)
ButtonThing(root, app)
app.createCanvas()
app.graphSign()
import os, django, sys
sys.path.append('/var/www/stockAnalyzeWeb')
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "stockAnalyzeWeb.settings")
django.setup()
from main.models import *
import main.Simulation as sm
from main.stuff import *
from random import shuffle
dfrom = MyDate('2007-12-03')
dto = MyDate('2017-12-03')
(sim,Sim) = sm.simInit(num=5,
name='10 years naive strategy',
detail = 'Do naive strategy for 10 years',
dfrom = dfrom,
dto = dto)
def strategy(t, comps, wallet, context):
sim.progress = (dfrom.gap(t) / dfrom.gap(dto)) * 100
sim.save()
print('\r' + str(sim.progress)+'%', end='')
if 'lastTrade' in context and context['lastTrade'] + 364 > t:
return
tradable = [c for c in comps if c.can_trade(t)]
if len(tradable) < 5:
from main.models import *
import main.Simulation as sm
from main.stuff import *
from random import shuffle
import main.crawl as cw
dfrom = MyDate('2007-11-30')
dto = MyDate('2018-01-26')
sim = Simulation.objects.get(num=4)
if sim.name == 'New strategy':
sim.name = 'Price getter'
sim.detail = 'Get prices'
sim.save()
log = sm.Logger('/var/www/stockAnalyzeWeb/main/sim_data/f4/log.txt')
try:
def save(comp):
#earliest = comp.price_set.earliest('date').date
#latest = comp.price_set.latest('date').date
new_data = None
for trying in range(5):
try:
#to = MyDate(earliest)
log.writeline(comp.name)
#og.writeline(str(dfrom) + '~' + str(dto))
new_data = cw.get_kospi(comp.code,
start=dfrom.date,
end=dto.date)
import os, django, sys
sys.path.append('/var/www/stockAnalyzeWeb')
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "stockAnalyzeWeb.settings")
django.setup()
from main.models import *
import main.Simulation as sm
from main.stuff import *
from random import shuffle
dfrom = MyDate('2012-12-03')
dto = MyDate('2017-12-03')
(sim, Sim) = sm.simInit(num=NUM,
name='New strategy',
detail='New strategy created',
dfrom=dfrom,
dto=dto)
def strategy(t, comps, wallet, context):
sim.progress = (dfrom.gap(t) / dfrom.gap(dto)) * 100
sim.save()
return
Sim.run(strategy, startcash=1000000, modelSim=sim)
import os, django, sys
sys.path.append('/var/www/stockAnalyzeWeb')
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "stockAnalyzeWeb.settings")
django.setup()
from main.models import *
import main.Simulation as sm
from main.stuff import *
from random import shuffle
dfrom = MyDate('2012-12-03')
dto = MyDate('2017-12-03')
(sim,Sim) = sm.simInit(num=2,
name='Naive strategy for testing',
detail = 'Buy 5 random companies at each rebalancing period=365',
dfrom = dfrom,
dto = dto)
def strategy(t, comps, wallet, context):
sim.progress = (dfrom.gap(t) / dfrom.gap(dto)) * 100
sim.save()
print('\r' + str(sim.progress)+'%', end='')
if 'lastTrade' in context and context['lastTrade'] + 364 > t:
return
tradable = [c for c in comps if c.can_trade(t)]
if len(tradable) < 5:
# Variables (see Documentation for description)
view = True
# To turn on/off the use of SAP, go to Helpers/helpers.py and change the
# global variable "SAP_PHYSICS" (defined after the import statements) to True/False.
seed = "r@nd0M2"
robot_number = 1
maxsteps = 10000
debug = 0 # begin debugging AFTER this timestep. 0 turns off debugging, change to 1 to debug w/ PDB
comment = seed
# seeding the simulation: turn this on to remove randomness in brain (for debugging)
# behavior between runs will be identical.
random.seed(seed)
# Run the Simulation, input is the random seed
Sim = Simulation()
Sim.start(view, robot_number)
# wrapped in a try/except block to catch errors and immediately begin
# pdb at exception's location
try:
Sim.run_simulation(view, maxsteps, debug, comment)
except:
_, _, tb = sys.exc_info()
traceback.print_exc()
pdb.post_mortem(tb)
# Display the simulation
Sim.run_visualization()
#SAP 2000 templates.sdb
from main import Simulation
from visualization import Visualization
# Variables
view = True
# Run the Simulation
sim = Simulation("Papyrus")
sim.start(view,1)
sim.run_simulation(view,10000)
# Display the simulation
sim.run_visualization()
# TEMP FILE - NOT USED from main import Simulation from visualization import Visualization # Variables (see Documentation for description) view = True seed = "F@st1#lAn3-test" robot_number = 1 maxsteps = 10000 # Run the Simulation, input is the random seed sim = Simulation() sim.start(view, robot_number) sim.run_simulation(view, maxsteps) # Display the simulation sim.run_visualization()
# TEMP FILE - NOT USED from main import Simulation from visualization import Visualization # Variables (see Documentation for description) view = True seed = "F@st1#lAn3-test" robot_number = 1 maxsteps = 10000 # Run the Simulation, input is the random seed sim = Simulation() sim.start(view,robot_number) sim.run_simulation(view,maxsteps) # Display the simulation sim.run_visualization()
