currepsilon not defined

[oakniiv]

[zoome0215]

This happens when you don't have a file of the youngest year in train_years. You have to either download files (and reshape them) or adjust train_years at around L44.

[oakniiv]

Downloaded whole data from 2000 to 2018 for EUR/USD reshaped it and it still happens, where do I adjust train_years?

[zoome0215]

train_years can be configured at L44 could you insert print('I got data',datanow.exist_data)

after datanow.loaddata(train_year,month,i) in

    for train_year in train_years:
        for month in range(1,13):
            for i in range(0,1000):
                datanow.loaddata(train_year,month,i)

around L91

with correct indentation and tell me the output?

[oakniiv]

[zoome0215]

I think the data files are not in the correct directory. What it is complaining is that class of tradedata in data_util.py is not loading data. There should be the following two lines at around Line 11,

datadir = '../data/tickdata/twosecdata/'
fname=datadir+'data'+str(year) + "-" + str(month).zfill(2) + "-" + str(i).zfill(4)+".out"

you can check to see if the file, fname, exists.

[oakniiv]

I made it work, I simply copied "currepsilon = greed0*np.exp(-numlearns/gamma_epsilon)" on an empty line at the beginning of the code therefore defined what currepsilon is, thank you for you time. May I contact you via email I'd like to talk about binary option itself since I am already a trader I have many strategies and ideas for machine learning?

[zoome0215]

You can send an e-mail to t.hashizume.brisbane@gmail.com so its fixed? I also pushed a workaround.

I think the bug appears when the January of the first year doesn't contain any data (or the usable amount of data). Hope it helped.

[oakniiv]

I made a lot of progress, installed bash for windows made a lot of progress actually, now I have problems installing geckodriver to path to run demotrade_tf.py but that is not important now I'll figure it out. I want to ask about the data, I still can't get it to learn anything, what did you mean with this code I sent you in the picture? Are those folders I should change and put the data in there? How to install those "dependecies" As I understood you made those or?

On 13 January 2018 at 23:08, Tom notifications@github.com wrote:

You can send an e-mail to t.hashizume.brisbane@gmail.com so its fixed? I also pushed a workaround.

I think the bug appears when the January of the first year doesn't contain any data (or the usable amount of data). Hope it helped.

— You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub https://github.com/zoome0215/predictBO/issues/2#issuecomment-357471061, or mute the thread https://github.com/notifications/unsubscribe-auth/Agh4WVsT3rwgIOxzKsEZu0sBmUKSY5TUks5tKSlygaJpZM4RbkBO .

[zoome0215]

Is it possible for you to post a screenshot of some of the files in the /data folder?

Dependencies can be install using pip, (pip3, pip2.7 the number depends on what version of python you are using). If you can go beyond the initial loading scheme (lines resemble from *** import ***) you should be fine.

also it is great to hear that you are making progress!

[oakniiv]

here, after that it runs the ai and says learned 0 times over and over again

On 19 January 2018 at 22:14, Tom notifications@github.com wrote:

Is it possible for you to post a screenshot of some of the files in the /data folder?

Dependencies can be install using pip, (pip3, pip2.7 the number depends on what version of python you are using). If you can go beyond the initial loading scheme (lines resemble from import ) you should be fine.

— You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub https://github.com/zoome0215/predictBO/issues/2#issuecomment-359090614, or mute the thread https://github.com/notifications/unsubscribe-auth/Agh4WYE0aNxE85ox3VANUXzSWwAki-54ks5tMQWbgaJpZM4RbkBO .

[oakniiv]

I also put the data from USD/JPY back, re downloaded makeai, I did everything how it says in readme, and still it's not learning anything

On 20 January 2018 at 10:51, oakniiv mainoakniiv@gmail.com wrote:

here, after that it runs the ai and says learned 0 times over and over again

On 19 January 2018 at 22:14, Tom notifications@github.com wrote:

Is it possible for you to post a screenshot of some of the files in the /data folder?

Dependencies can be install using pip, (pip3, pip2.7 the number depends on what version of python you are using). If you can go beyond the initial loading scheme (lines resemble from import ) you should be fine.

— You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub https://github.com/zoome0215/predictBO/issues/2#issuecomment-359090614, or mute the thread https://github.com/notifications/unsubscribe-auth/Agh4WYE0aNxE85ox3VANUXzSWwAki-54ks5tMQWbgaJpZM4RbkBO .

[oakniiv]

Not sure if you got the pictures from the mail above I sent idk if it was delivered the files may be big

On 21 January 2018 at 10:50, oakniiv mainoakniiv@gmail.com wrote:

I also put the data from USD/JPY back, re downloaded makeai, I did everything how it says in readme, and still it's not learning anything

On 20 January 2018 at 10:51, oakniiv mainoakniiv@gmail.com wrote:

here, after that it runs the ai and says learned 0 times over and over again

On 19 January 2018 at 22:14, Tom notifications@github.com wrote:

Is it possible for you to post a screenshot of some of the files in the /data folder?

Dependencies can be install using pip, (pip3, pip2.7 the number depends on what version of python you are using). If you can go beyond the initial loading scheme (lines resemble from import ) you should be fine.

— You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub https://github.com/zoome0215/predictBO/issues/2#issuecomment-359090614, or mute the thread https://github.com/notifications/unsubscribe-auth/Agh4WYE0aNxE85ox3VANUXzSWwAki-54ks5tMQWbgaJpZM4RbkBO .

[zoome0215]

Did you checkout the minimum.zip I sent you over the e-mail? I think you need them? Everything must be organised as how it is.

and I can't see the picture.

[oakniiv]

[oakniiv]

Today I re-downloaded makeAI-tf.py and put USD/JPY data and still it wouldn't work

[zoome0215]

ah okay. at Line 44 in make-AI.py there is train_years = range(2014,2017) change it to train_years = range(2017,2018) Right now your data folder (data/tickdata/truncateddata) has data from only 2017.

This is not good, because you want to test it on data from 2017 using the data from the years previous to 2017

[oakniiv]

I put the USD/JPY data back, from 2014 01 to 2018 01, changed train_years to 2014 to 2018

it is still not learning anything

[oakniiv]

makeAI-tf.py ""

!/usr/bin/python

from future import division

import numpy as np import os, os.path import sys import time from datetime import datetime import pickle

graphing

import matplotlib matplotlib.use("tkagg") import matplotlib.pyplot as plt

own python dependencies

import data_util import learning_util

upparam = 1 downparam = -1 restparam = 0

############################# cont_learn = False

interval = 15 # min betinterval = 5 # min periodint = 2

outname = 'realuod'+str(interval)+''+str(betinterval)+'_tf'

target_rate = 4 # per hour payrate=2 initmoney = 200 bet = 20

lr0 = 0.000001 greed0= 1.0

lrthresh = 1e-8 epsthresh = 1.0/15.0

gamma_epsilon = 100000.0 #Decay rate : epsilon = greed0 * exp(- numlearns / gamma_epsilon)

train_years = range(2014,2018) Nepochs = 100000000

wait = 5 #min

possibleactions = (downparam,restparam,upparam)

weightactions = np.array([0.2,0.6,0.2])

weightactions = np.array([1/3,1/3,1/3])

if betinterval < 10 : payrate = 1.85

gain = bet*(payrate-1)

print 'tested on', datetime.today() print 'interval of ' , interval ,' min'

Converting the intervals to array length

interval = int(interval60/periodint) betinterval = int(betinterval60/periodint) wait = int(wait*60/2)

making AI

outdir = '../AI/tf/' outname = outdir+outname

learner = learning_util.learn(outname,lr0,possibleactions,weightactions,interval)

load data

datanow = data_util.tradedata()

if cont_learn: print 'AI loaded!' learner.loadmodel(); learner.loadtargetmodel(); else: print 'Making a new AI!'

numdata=0 numtrials = 0 numlearns = 0

currepsilon=0

moneynow=initmoney e = 0 while e < Nepochs : if e%100 ==0: print 'epoch ', e for train_year in train_years: for month in range(1,13): for i in range(0,1000): datanow.loaddata(train_year,month,i) if (not datanow.exist_data) : break jlim = datanow.size()-(interval+max(betinterval,wait)) if jlim > (wait+interval): currepsilon = greed0*np.exp(-numlearns/gamma_epsilon)

                if currepsilon < epsthresh :
                    currepsilon = epsthresh

                learner.set_epsilon(currepsilon)

                numdata+=jlim

                j=0
                while j < jlim :
                    datnowall = datanow.get(j,interval+max(betinterval,wait))
                    state = datnowall[:interval]
                    diff_io = state[-1]-datnowall[interval+betinterval-1]
                    state = data_util.scaling(state)
                    action = learner.select_action(state, learner.exploration)
                    reward = data_util.calcreward(action,diff_io,bet,gain)

                    if action == 0:
                        statenext = datnowall[1:interval+1]
                    else :
                        statenext = datnowall[wait:(interval+wait)]

                    moneynow+= reward

                    if moneynow < 0:
                        terminal=True
                        moneynow = initmoney
                    elif moneynow > initmoney:
                        terminal=False
                        moneynow = initmoney
                    else :
                        terminal=False

                    statenext = data_util.scaling(statenext)
                    learner.storeexperience(state,action,reward,statenext,terminal)

                    if (numtrials%(60*60*1/periodint)) == 0:
                        learner.experience_replay()
                        numlearns+= 1

                    if action == 0:
                        j+= 1
                    else :
                        j+=wait

                    numtrials += 1

        print train_year,month, i, 'learned', numlearns,'times with epsilon =',currepsilon
    learner.saveall()
e += 1

""

[zoome0215]

Did you change anywhere else in make-AI.py?

[zoome0215]

You have to have the data from 2014 and on wards in data/truncateddata/ and has to have a format of data``year-month.txt

[zoome0215]

so basically, you have csv files in data/rawdata/ folder in a form of DAT_NT_USDJPY_T_LAST_yearmonth.csv those will be reshaped by running shapedata/truncatenight.py. The output of this should be in a form of datayear-month-number.out in data/twosecdata/. the output of that python script will be re-shaped further by runningshapedata/shapetwosec.py. Output will be indata/truncateddataand has a form ofdatayear-month.txt`. I have no idea what's wrong with it. There are so many things you could've changed and caused a bug (like changes in any of the python scripts mentioned above could end up making wrong output files).

It is impossible to identify what is causing it. I'm sorry...

[zoome0215]

Also, it seems that your truncatenight.py is not working.

[oakniiv]

Right now I am outputting data with truncatenight i'll try running the whole thing again

On Jan 21, 2018 12:04 PM, "Tom" notifications@github.com wrote:

Also, it seems that your truncatenight.py is not working.

— You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub https://github.com/zoome0215/predictBO/issues/2#issuecomment-359240113, or mute the thread https://github.com/notifications/unsubscribe-auth/Agh4WU0yTE_t34FadZw-l3hfIF1zbvWBks5tMxmugaJpZM4RbkBO .

[zoome0215]

You should delete all the files in data (delete only the files. not the folders!) except for the ones in data/rawdata.

[oakniiv]

Everything is how it's supposed to be now

still not learning

[zoome0215]

did you try executing the files in minimum.zip that I sent you via e-mail and dropbox few days ago? did it work?

also, could you also put the screenshot of the output of make-AI.py?

I have no clue why its not working on your machine (it might be because you have a windows machine.).

[oakniiv]

I replaced files in the folder with those from minimum, I don't have minimum.zip anymore, I'm using bash so the project is using linux ubuntu

https://www.dropbox.com/s/2s6a9ijasqh063z/minimum.zip file not there anymore

[oakniiv]

data_util.py line12 is correct? is it supposed to say .out or .txt? i tried with .txt did not work tho

[zoome0215]

No, you don't have any data in data/twosecdata/ that's the problem.

[oakniiv]

then it is shapetwosec.py making all this trouble?

[zoome0215]

could be. Did you run it?

[oakniiv]

holy shit it is running, first I ran truncated as it should be, now I went back and ran just shapetwosec and I think it is running right now

[oakniiv]

before I ran them together in one command

[zoome0215]

alright hahaha that's good to hear!

Please write exactly what you did wrong and what you did to fix it so that I can update the read me for other people who might encounter the similar problem!

Thanks!

[oakniiv]

First you have to run truncatenight.py and once you have those files in the folder then run the shapetwosec.py

and if changing currency make sure to modify truncatenight.py line 12 to match the file name

[oakniiv]

and could you please write a tutorial once we are done training the ai x times, what then? where is the file stored with all the trained data? how to use it where to put it?

[oakniiv]

also, once i train it for a little bit, can i save the training, load it again and add more data to it?