TypeError: 'str' object cannot be interpreted as an integer when running backtest.start()

[anfederico]

TypeError: 'str' object cannot be interpreted as an integer when running backtest.start()

[BariyaZ]

Hi,
I install all the required libraries for the execution of following code:
from clairvoyant.engine import Backtest
import pandas as pd

features = ["EMA", "SSO"] # Financial indicators of choice
trainStart = 0 # Start of training period
trainEnd = 700 # End of training period
testStart = 701 # Start of testing period
testEnd = 1000 # End of testing period
buyThreshold = 0.65 # Confidence threshold for predicting buy (default = 0.65)
sellThreshold = 0.65 # Confidence threshold for predicting sell (default = 0.65)
continuedTraining = False # Continue training during testing period? (default = false)

Initialize backtester

backtest = Backtest(features, trainStart, trainEnd, testStart, testEnd, buyThreshold, sellThreshold, continuedTraining)

A little bit of pre-processing

data = pd.read_csv("SBUX.csv", date_parser=['date'])
data = data.round(3)

Start backtesting and optionally modify SVC parameters

Available paramaters can be found at: http://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html

backtest.start(data, kernel='rbf', C=1, gamma=10)
backtest.conditions()
backtest.statistics()
backtest.visualize('SBUX')

I got an error at line "backtest.start(data, kernel='rbf', C=1.0, gamma=10)". It says that
TypeError: 'str' object cannot be interpreted as an integer, and KeyError: 'EMA'
I checked the clairvoyant.engine for the solution but I don't know why this happens.

[anfederico]

I didn't include the "SBUX.csv" data which is unfortunately causing a lot of confusion because I use it in the README. I will update this soon. For now, the example data is called "data.csv" and the features are called "X1" and X2". Please update those in your example and it should run.

[Shine119]

Thanks for your reply. Yep, I did use data.csv and X1, X2 as features but all the statistics results are zero.

…

On Sat, Oct 13, 2018 at 10:48 PM anfederico ***@***.***> wrote: I didn't include the "SBUX.csv" data which is unfortunately causing a lot of confusing because I use it in the README. I will update this soon. For now, the example data is called "data.csv" and the features are called "X1" and X2". Please update those in your example and it should run. — You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub <#29 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AQwbB0QdjJKcbYGN8A7hf84DZfJbD_poks5ukf1JgaJpZM4XY1l4> .

[BariyaZ]

Thanks for the responce. I did use data.csv and rename it to SBUX.csv but when I ran the code its giving an error of "IndexError: single positional indexer is out-of-bounds". I am geting this error at line" backtest.start(data, kernel='rbf', C=1, gamma=10)"

[anfederico]

The test data only has 322 data points, try:

trainStart = 0               # Start of training period
trainEnd   = 200             # End of training period
testStart  = 201             # Start of testing period
testEnd    = 321             # End of testing period