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report_gen.py
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report_gen.py
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"""
report_gen v0.01
report generator
Copyright 2011 Brian Monkaba
This file is part of ga-bitbot.
ga-bitbot is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
ga-bitbot is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with ga-bitbot. If not, see <http://www.gnu.org/licenses/>.
"""
#
# Generates GA trade simulation reports using the gene server
# Also calculates & submits the next buy trigger
#
__appversion__ = "0.01a"
print "Genetic Bitcoin Report Generator v%s"%__appversion__
# connect to the xml server
#
import xmlrpclib
import json
import paths
import gene_server_config
import time
__server__ = gene_server_config.__server__
__port__ = str(gene_server_config.__port__)
#make sure the port number matches the server.
server = xmlrpclib.Server('http://' + __server__ + ":" + __port__)
print "Connected to",__server__,":",__port__
from load_config import *
import __main__
#the variable values below are superceded by the configuration loaded from the
#configuration file global_config.json
#!!!!!!!! to change the values edit the json configuration file NOT the variables below !!!!!!!!
max_length = 60 * 24 * 60
enable_flash_crash_protection = True
flash_crash_protection_delay = 180
chart_zoom_periods = 3000
chart_now_periods = 200
win_loss_gate_pct = 0.80
price_format = "%.3f"
chart_type = 0
config_loaded = 0
#load config
try:
__main__ = load_config_file_into_object('global_config.json',__main__)
except:
print "Error detected while loading the configuration. The application will now exit."
import sys
sys.exit()
else:
if config_loaded == False:
print "Configuration failed to load. The application will now exit."
import sys
sys.exit()
else:
print "Configuration loaded."
def generate_empty_charts(quartile):
print "creating empty charts..."
f = open("./report/chart.templ",'r')
templ = f.read()
f.close()
templ = templ.replace('{LAST_UPDATE}','<b>NO ORDERS TO REPORT</b>')
templ = templ.replace('{METRICS_REPORT}','')
templ = templ.replace('{ORDERS_REPORT}','')
f = open("./report/chart_test_%s.html"%str(quartile),'w')
f.write(templ)
f.close()
f = open("./report/chart_test_zoom_%s.html"%str(quartile),'w')
f.write(templ)
f.close()
def load():
#open the history file
#print "loading the data set"
f = open("./datafeed/bcfeed_mtgoxUSD_1min.csv",'r')
#f = open("./datafeed/test_data.csv",'r')
d = f.readlines()
f.close()
if len(d) > max_length:
#truncate the dataset
d = d[max_length * -1:]
#load the backtest dataset
input = []
for row in d[1:]:
r = row.split(',')[1] #last price
t = row.split(',')[0] #time
input.append([int(float(t)),float(r)])
#print "done loading:", str(len(input)),"records."
return input
while 1:
skip_sleep_delay = False #default to sleep delay mode between cycles
#will be set to true (and skip the sleep delay) if target prices are found.
#register as a default client (this will allow remote dynamic configuration of the report generation)
pid = "REPORT_GEN"
gdh = json.loads(server.get_default_gene_def_hash())
print gdh
#load the gene def config
gd = json.loads(server.get_gene_def(gdh))
server.pid_register_client(pid,gdh)
print "_" * 80
print time.ctime()
#load the data set
input = load()
buys = []
targets = []
for quartile in [4,3,2,1]:
#get the high score gene from the gene server
try:
ag = json.loads(server.get(60*60*24*7,quartile,pid))
except:
print "warning: gene server error or no data available."
#if the quartile is active set the buy to 0 to prevent old targets from remaining active
#this is for fault protection as it should never normaly happen:
if quartile == server.get_active_quartile():
p = {'buy':0.00}
server.put_target(json.dumps(p),pid)
#generate empty charts to prevent old data from being reported.
generate_empty_charts(quartile)
else:
if type(ag) == type([]):
ag = ag[0]
#create the trade engine
print "report: loading the fitness function"
ff = None
if gd.has_key('fitness_script'):
ff = __import__(gd['fitness_script'])
else:
ff = __import__('bct')
ff = reload(ff) #make sure we're not using a cached version of the module
te = ff.trade_engine()
te.cache.disable() #dont use cached data for reporting
#apply global configs
te.max_length = max_length
te.enable_flash_crash_protection = enable_flash_crash_protection
te.flash_crash_protection_delay = flash_crash_protection_delay
#load the gene dictionary into the trade engine
te = load_config_into_object({'set':ag},te)
#load the gene def fitness config into the trade engine
if gd.has_key('fitness_config'):
te = load_config_into_object(gd['fitness_config'],te)
#preprocess the data
#current_quartile = te.classify_market(input)
current_quartile = te.initialize()
#update the gene server with the current market quartile
server.put_active_quartile(current_quartile,pid)
#select the quartile to test
te.test_quartile(quartile)
print "_" * 40
if current_quartile == quartile:
print "Quartile:",quartile, "(%.4f)"%ag['score'],"+active"
else:
print "Quartile:",quartile, "(%.4f)"%ag['score']
#feed the input through the trade engine
try:
#for i in input:
# te.input(i[0],i[1])
te.run()
except:
print "Gene Fault"
else:
if len(te.positions) == 0:
#no data to report but the chart reports need to be created to prevent stale data reports or 404 errors.
generate_empty_charts(quartile)
if current_quartile == quartile:
print "no positions, order not submitted"
p = {'buy':0.00}
server.put_target(json.dumps(p),pid)
# Calc the next buy trigger point
elif len(te.positions) > 0:
#get the target trigger price
target = te.get_target()
print "Inverse MACD Result (target): ",target
#if target > te.input_log[-1][1]:
# target = te.input_log[-1][1]
if target > te.history[1]:
target = te.history[1]
#first check to see if the tested input triggered a buy:
if te.positions[-1]['buy_period'] == te.period - 1:
p = te.positions[-1]
target = p['buy']
else:
print "Last buy order was", te.period - te.positions[-1]['buy_period'],"periods ago."
#if not try to calculate the trigger point to get the buy orders in early...
#print "Trying to trigger with: ",target
print "Score: ",te.score()
st = input[-1][0] + 2000
te.input(st,target)
p = te.positions[-1].copy()
if p['buy'] != target:
#print "Order not triggered @",target
p['buy'] = 0.00
p['target'] = 0.00
#te.classify_market(input)
print "creating charts..."
te.chart("./report/chart.templ","./report/chart_test_%s.html"%str(quartile),basic_chart=chart_type)
te.chart("./report/chart.templ","./report/chart_test_zoom_%s.html"%str(quartile),chart_zoom_periods,basic_chart=chart_type)
# te.chart("./report/chart.templ","./report/chart_test_now_%s.html"%str(quartile),chart_now_periods,basic_chart=chart_type)
#print "Evaluating target price"
if current_quartile == quartile:
if ((target >= p['buy']) or (abs(target - p['buy']) < 0.01)) and p['buy'] != 0: #submit the order at or below target
#format the orders
p['buy'] = float(price_format%(p['buy'] - 0.01))
p['target'] = float(price_format%p['target'])
p.update({'stop_age':(60 * te.stop_age)})
if float(te.wins / float(te.wins + te.loss)) > win_loss_gate_pct:
#only submit an order if the win/loss ratio is greater than x%
print "sending target buy order to server @ $" + str(p['buy'])
server.put_target(json.dumps(p),pid)
skip_sleep_delay = True #if target buy orders are active skip the sleep delay
else:
print "underperforming trade strategy, order not submitted"
p['buy'] = 0.00
p['target'] = 0.00
server.put_target(json.dumps(p),pid)
print "-" * 40
print "Quartile :",quartile
print "Buy :$", p['buy']
print "Target :$",p['target']
print "Win Ratio :","%.3f"%((te.wins / float(te.wins + te.loss)) * 100),"%"
print "-" * 40
else:
print "Trigger criteria not met, no order set."
print "Buy :$", p['buy']
print "Target :$",p['target']
print "Input Target :$",target
print "Last Price :$",input[-1][1]
print "MACD Log : ",te.logs.get('macd')[-1][1]
print "MACD Trip : ",te.macd_buy_trip
p.update({'stop_age':(60 * te.stop_age)}) #DEBUG ONLY!! - delete when done.
p['buy'] = 0.00
p['target'] = 0.00
server.put_target(json.dumps(p),pid)
buys.append(p['buy'])
targets.append(p['target'])
#log the orders
#f = open("./report/rg_buys.csv",'a')
#f.write(",".join(map(str,buys)) + ",")
#f.write(",".join(map(str,targets)) + "\n")
#f.close()
#create the gene visualizer report
print "creating the gene visualizer report..."
f = open('./report/gene.templ','r')
template = f.read()
f.close()
for quartile in [1,2,3,4]:
band_l = []
gl = json.loads(server.get_bobs(quartile,pid))
if len(gl) > 0:
#place a band (a small list of gene set to all 1's) in the data to highlight the break between the bobs and high scores
band = "1" * len(gl[0]['gene'])
for i in xrange(3):
band_l.append({'gene':band})
gl += band_l
gl += json.loads(server.get_all(quartile,pid))
l = []
for ag in gl:
l.append(ag['gene'])
qs = '{Q%s}'%str(quartile)
template = template.replace(qs,str(l).replace('u',''))
template = template.replace('{LAST_UPDATE}',time.ctime())
f = open('./report/gene_visualizer.html','w')
f.write(template)
f.close()
if skip_sleep_delay == False:
print "sleeping..."
print "_" * 80
print "\n"
time.sleep(600) #generate a report every n seconds
else:
time.sleep(600)
print "skipping sleep state due to active trigger prices..."
print "_" * 80
print "\n"