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TS-Optimizer.py
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TS-Optimizer.py
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from __future__ import print_function
from threading import Thread
import time
import datetime
import os, fnmatch
import psutil
import csv
import sys
import numpy as pynum
import pickle
from queue import LifoQueue
cmd = LifoQueue()
# now these are the new values in our array
PriceCol = 0
SignalCol = 1
FdaCol = 2
def run_prog():
#now = datetime.datetime.now()
c = cmd.get()
#print("* " + now.strftime("%Y-%m-%d %H:%M:%S") + " >> " + c + " - STARTED")
os.system(c)
#now = datetime.datetime.now()
#print("* " + now.strftime("%Y-%m-%d %H:%M:%S") + " << " + c + " - FINISHED")
def process_report_regex(regex):
out_file = "optimus-" + regex + ".csv" # format of report: min_fda, max_fda, opt_period, maj_threshold, profit_pips
postfix = "*export1.csv"
listOfFiles = os.listdir('.')
arrReports = [] # this will contain lists for every report
pFile = regex + '-optimizer.pkl'
if (os.path.isfile(pFile)==False):
for report in listOfFiles:
if fnmatch.fnmatch(report, regex+postfix ):
a = readcsv(report)
'''
print("OLD ARRAY \n")
r = 1
while (r < len(a)):
print(a[r][0],a[r][SignalCol])
r += 1
'''
r = 1 # 1 would be header
# convert long/short/cash to 1,-1,0
prev = 0
while (r < len(a)):
if ( a[r][SignalCol]=="" ): # the idea is to fill blank lines with the value of previous signal before the blank lines, even if it's blank )
a[r][SignalCol]=prev
else:
# change cur row to digital and update prev
if (a[r][SignalCol] == "Long"):
a[r][SignalCol] = 1
prev = 1
elif (a[r][SignalCol] == "Short"):
a[r][SignalCol] = -1
prev = -1
elif (a[r][SignalCol] == "Cash"):
a[r][SignalCol] = 0
prev = 0
r += 1
'''
print("NEW NEW ARRAY \n")
r = 1
while (r < len(a)):
print(a[r][0],a[r][SignalCol])
r += 1
exit()
'''
#print("appending: " + report)
# 2. construct array of trading systems
arrReports.append(a) # now it's arrReports[model_id][row][column]
output = open(pFile, 'wb')
pickle.dump(arrReports, output)
output.close()
# fda thershold value
low = 0.54
up = 0.64
fda_step = 0.01
for fda_low in pynum.arange(low, up, fda_step):
for fda_high in pynum.arange(fda_low+fda_step, up, fda_step):
cmd.put( "python ts-group.py " + str(pFile) + " " + str(fda_low) + " " + str(fda_high) )
while (cmd.qsize()>0):
#ts("CPU Utilization = " + str(cpu_util()) + "% // tasks in stack: " + str(cmd.qsize()) )
# start new processes while CPU utilization is less than 89
if (psutil.cpu_percent()<97 and ram_util()<80 ):
thread = Thread(target = run_prog)
thread.start()
#time.sleep(2)
time.sleep(1) # checks once per minute
# TODO: make an option to reproduce the report for this signals in the future for MT4
# Remove the print statements. They force your process to pause and do IO instead of using pure CPU. –
# CHECK THIS!
# print something with timestamp
def ts(s):
now = datetime.datetime.now()
print(now.strftime("%Y-%m-%d %H:%M:%S") + " // " + s)
def ram_util():
return ( float((str(psutil.virtual_memory()).split(",")[2]).replace(" ","").replace("percent=","")) )
def cpu_util():
max_t = 2
t = max_t # so many iterations to measure CPI Utilization
util = 0
while (t>0): # we do it a few times and calc avg to be sure
util += psutil.cpu_percent()
time.sleep(t)
t-=1
return (util/max_t)
def readcsv(filename):
'''
0 Bar,
1 Date,
2 Time,
3 Price,
4 Forecast,
5 Signal,
6 Wealth Distribution,
7 Buy Orders,
8 Sell Orders,
9 VM Trades,
10 VM Trades MA (100),
11 Population Position,
12 Avg Genome Size,
13 Right Forecasted Price Changes,
14 Wrong Forecasted Price Changes,
15 FDA (Trailing 100 bars; Range applied
'''
Price_Col = 3
Signal_Col = 5
Fda_Col = 15
ifile = open(filename, "rU")
reader = csv.reader(ifile, delimiter=",")
a = []
for row in reader:
a.append ( [row[Price_Col],row[Signal_Col],row[Fda_Col],] )
ifile.close()
return a
def analyze(reports):
for f in reports:
print(f)
if __name__ == "__main__":
# python TS-Optimizer.py 01k_10j2_1
r = 1
while (r < len(sys.argv)):
process_report_regex( sys.argv[r] )
r += 1
#print("Done execution, waiting for all threads to continue...")