Np array has wrong dimensions by SIG_94

SIG_94 INVESTOR

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I'm trying to create a simple script to spot candlestick patterns using the TA-Lib library, however I'm not able to pass the correct data even if I'm following the talib instructions as per their github page. The error message I get is 'Input array has wrong dimensions' when passing ohlc prices.

import talib

import numpy as np



class GeekyYellowGreenDinosaur(QCAlgorithm):



    def Initialize(self):

        self.SetStartDate(2020,1,1)  #Set Start Date

        self.SetEndDate(2020,12,31)

        self.SetCash(1000)  # Set Strategy Cash

        

        self.AddForex('EURUSD', Resolution.Hour)

            

        



    def OnData(self, data):

        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.

            Arguments:

                data: Slice object keyed by symbol containing the stock data

        '''

        open_ = np.array(data['EURUSD'].Open)

        

        

        close_ = np.array(data['EURUSD'].Close)

        

        

        high_ = np.array(data['EURUSD'].High)

        

        

        low_ = np.array(data['EURUSD'].Low)



        hammer = talib.CDLHAMMER(open_, high_, low_, close_)

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SIG_94

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Louis Szeto

STAFF ,

It seems to me your input array is 1-D np array, the CDLHAMMER shall use 2-D ones. You can change

low_ = np.array(data['EURUSD'].Low)

into

low_ = np.array(data['EURUSD'].Low).reshape(-1, 1)

similar to the rest of the OHLC

SIG_94

833 ,

Thank you for your reply Louis,

I've tried with your instructions but unfortunately I still get the same error message:

import talib

import numpy as np



class GeekyYellowGreenDinosaur(QCAlgorithm):



    def Initialize(self):

        self.SetStartDate(2020,1,1)  #Set Start Date

        self.SetEndDate(2020,12,31)

        self.SetCash(1000)  # Set Strategy Cash

        

        self.AddForex('EURUSD', Resolution.Hour)

            

        



    def OnData(self, data):

        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.

            Arguments:

                data: Slice object keyed by symbol containing the stock data

        '''

        open_ = np.array(data['EURUSD'].Open).reshape(-1, 1)

        

        

        close_ = np.array(data['EURUSD'].Close).reshape(-1, 1)

        

        

        high_ = np.array(data['EURUSD'].High).reshape(-1, 1)

        

        

        low_ = np.array(data['EURUSD'].Low).reshape(-1, 1)

        

       

       

        pattern = talib.CDLHAMMER(open_, high_, low_, close_)

        if pattern:

            self.Log('Pattern found')

Louis Szeto

STAFF ,

This will work on a 1-d array

Derek Melchin

STAFF ,

Hi Louis and SIG_94,

The algorithm above doesn't log anything because the CDLHAMMER method uses historical candles to determine if the pattern has formed. The source code for the method has the following conditions:

if( TA_REALBODY(i) < TA_CANDLEAVERAGE( BodyShort, BodyPeriodTotal, i ) &&                        // small rb

   TA_LOWERSHADOW(i) > TA_CANDLEAVERAGE( ShadowLong, ShadowLongPeriodTotal, i ) &&              // long lower shadow

   TA_UPPERSHADOW(i) < TA_CANDLEAVERAGE( ShadowVeryShort, ShadowVeryShortPeriodTotal, i ) &&    // very short upper shadow

   min( inClose[i], inOpen[i] ) <= inLow[i-1] + TA_CANDLEAVERAGE( Near, NearPeriodTotal, i-1 )  // rb near the prior candle's lows

)

Note: "rb near the prior candle's lows"

See the attached backtest and notebook for reference.

Best,
Derek Melchin

SIG_94 INVESTOR

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