我在 python 中有此代码，我正在尝试修改，但我不断收到错误消息。
File "C:\ProgramData\Anaconda3\lib\threading.py", line 932, in _bootstrap_inner
self.run()
File "C:\ProgramData\Anaconda3\lib\threading.py", line 1254, in run
self.function(*self.args, **self.kwargs)
File "C:\Users\1071396\Downloads\rh-trading-bot_MA_Cross-master\bot.py", line 381, in run
getattr( self.signal, 'sell_' + str( config[ 'trade_strategies' ][ 'sell' ] ) )( a_asset, self.data ) or
File "C:\Users\1071396\Downloads\rh-trading-bot_MA_Cross-master\signals.py", line 78, in sell_sma_crossover_rsi
data.iloc[ -4 ][ asset.ticker + '_SMA_F' ] > data.iloc[ -4 ][ asset.ticker + '_SMA_S' ][ 'sell' ] and
IndexError: invalid index to scalar variable.
这是脚本的样子“signals.py”
from config import config
from math import isnan
# Signals are defined in alphabetical order
class signals:
def buy_sma_crossover_rsi( self, ticker, data ):
# Moving Average Crossover with RSI Filter
# Credits: https://trader.autochartist.com/moving-average-crossover-with-rsi-filter/
# Buy when Fast-SMA crosses Slow-SMA from below, and stays above for 3 consecutive readings, and RSI > buy threshold (50 suggested)
return(
# Make sure the data is valid
not isnan( data.iloc[ -1 ][ ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -2 ][ ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -3 ][ ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -4 ][ ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -1 ][ ticker + '_SMA_S' ] ) and
not isnan( data.iloc[ -2 ][ ticker + '_SMA_S' ] ) and
not isnan( data.iloc[ -3 ][ ticker + '_SMA_S' ] ) and
not isnan( data.iloc[ -4 ][ ticker + '_SMA_S' ] ) and
#not isnan( data.iloc[ -1 ][ ticker + '_RSI' ] ) and
# Fast-SMA crossed Slow-SMA and stays above
data.iloc[ -1 ][ ticker + '_SMA_F' ] >= data.iloc[ -1 ][ ticker + '_SMA_S' ] and
data.iloc[ -2 ][ ticker + '_SMA_F' ] >= data.iloc[ -2 ][ ticker + '_SMA_S' ] and
data.iloc[ -3 ][ ticker + '_SMA_F' ] >= data.iloc[ -3 ][ ticker + '_SMA_S' ] and
data.iloc[ -4 ][ ticker + '_SMA_F' ] < data.iloc[ -4 ][ ticker + '_SMA_S' ][ 'buy' ] # and
)
# ... and they diverge
#data.iloc[ -1 ][ ticker + '_SMA_F' ] - data.iloc[ -1 ][ ticker + '_SMA_S' ] >= data.iloc[ -2 ][ ticker + '_SMA_F' ] - data.iloc[ -2 ][ ticker + '_SMA_S' ][ 'buy' ] # and
# RSI above threshold
#data.iloc[ -1 ][ ticker + '_RSI' ] > config[ 'rsi_threshold' ][ 'buy' ]
#)
def buy_sma_rsi_threshold( self, ticker, data ):
# Simple Fast-SMA and RSI
# Buy when price is below Fast-SMA and RSI is below threshold
return (
not isnan( data.iloc[ -1 ][ ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -1 ][ ticker + '_RSI' ] ) and
# Is the current price below the Fast-SMA by the percentage defined in the config file?
data.iloc[ -1 ][ ticker ] <= data.iloc[ -1 ][ ticker + '_SMA_F' ] - ( data.iloc[ -1 ][ ticker + '_SMA_F' ] * config[ 'buy_below_moving_average' ] ) and
# RSI below the threshold
data.iloc[ -1 ][ ticker + '_RSI' ] <= config[ 'rsi_threshold' ][ 'buy' ]
)
def sell_above_buy( self, asset, data ):
# Simple percentage
return (
data.iloc[ -1 ][ asset.ticker ] > asset.price + ( asset.price * config[ 'profit_percentage' ] )
)
def sell_sma_crossover_rsi( self, asset, data ):
# Moving Average Crossover with RSI Filter
# Credits: https://trader.autochartist.com/moving-average-crossover-with-rsi-filter/
return(
# Make sure the data is valid
not isnan( data.iloc[ -1 ][ asset.ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -2 ][ asset.ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -3 ][ asset.ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -3 ][ asset.ticker + '_SMA_F' ] ) and
not isnan( data.iloc[ -1 ][ asset.ticker + '_SMA_S' ] ) and
not isnan( data.iloc[ -2 ][ asset.ticker + '_SMA_S' ] ) and
not isnan( data.iloc[ -3 ][ asset.ticker + '_SMA_S' ] ) and
not isnan( data.iloc[ -3 ][ asset.ticker + '_SMA_S' ] ) and
#not isnan( data.iloc[ -1 ][ asset.ticker + '_RSI' ] ) and
# Fast-SMA crossed Slow-SMA and stays above
data.iloc[ -1 ][ asset.ticker + '_SMA_F' ] <= data.iloc[ -1 ][ asset.ticker + '_SMA_S' ] and
data.iloc[ -2 ][ asset.ticker + '_SMA_F' ] <= data.iloc[ -2 ][ asset.ticker + '_SMA_S' ] and
data.iloc[ -3 ][ asset.ticker + '_SMA_F' ] <= data.iloc[ -3 ][ asset.ticker + '_SMA_S' ] and
data.iloc[ -4 ][ asset.ticker + '_SMA_F' ] > data.iloc[ -4 ][ asset.ticker + '_SMA_S' ][ 'sell' ] and
# ... and they diverge
#data.iloc[ -1 ][ ticker + '_SMA_S' ] - data.iloc[ -1 ][ ticker + '_SMA_F' ] >= data.iloc[ -2 ][ ticker + '_SMA_S' ] - data.iloc[ -2 ][ ticker + '_SMA_F' ] and
# RSI below threshold
#data.iloc[ -1 ][ ticker + '_RSI' ] <= config[ 'rsi_threshold' ][ 'sell' ] and
# Price is greater than purchase price by at least profit percentage
data.iloc[ -1 ][ asset.ticker ] >= asset.price + ( asset.price * config[ 'profit_percentage' ] )
)
我的最终目标是拥有一个快速移动平均线，假设 21 天移动平均线向上穿越 50 天移动平均线将表示买入，反之亦然，21 天移动平均线向下穿越 50 天移动平均线将表示卖出< /p>
编辑::
def buy( self, ticker ):
if ( self.available_cash < config[ 'buy_amount_per_trade' ] or self.is_trading_locked ):
return False
# Values need to be specified to no more precision than listed in min_price_increments.
# Truncate to 7 decimal places to avoid floating point problems way out at the precision limit
price = round( floor( self.data.iloc[ -1 ][ ticker ] / self.min_price_increments[ ticker ] ) * self.min_price_increments[ ticker ], 7 )
# How much to buy depends on the configuration
quantity = ( self.available_cash if ( config[ 'buy_amount_per_trade' ] == 0 ) else config[ 'buy_amount_per_trade' ] ) / price
quantity = round( floor( quantity / self.min_share_increments[ ticker ] ) * self.min_share_increments[ ticker ], 7 )
print( 'Buying ' + str( ticker ) + ' ' + str( quantity ) + ' at $' + str( price ) )
if ( config[ 'trades_enabled' ] and not config[ 'debug_enabled' ] ):
try:
buy_info = rh.order_buy_crypto_limit( str( ticker ), quantity, price )
# Add this new asset to our orders
self.orders[ buy_info[ 'id' ] ] = asset( ticker, quantity, price, buy_info[ 'id' ] )
except:
print( 'Got exception trying to buy, aborting.' )
return False
return True
def sell( self, asset ):
# Do we have enough of this asset to sell?
if ( asset.quantity <= 0.0 or self.is_trading_locked ):
return False
# Values needs to be specified to no more precision than listed in min_price_increments.
# Truncate to 7 decimal places to avoid floating point problems way out at the precision limit
price = round( floor( self.data.iloc[ -1 ][ asset.ticker ] / self.min_price_increments[ asset.ticker ] ) * self.min_price_increments[ asset.ticker ], 7 )
profit = round( ( asset.quantity * price ) - ( asset.quantity * asset.price ), 3 )
print( 'Selling ' + str( asset.ticker ) + ' ' + str( asset.quantity ) + ' for $' + str( price ) + ' (profit: $' + str( profit ) + ')' )
if ( config[ 'trades_enabled' ] and not config[ 'debug_enabled' ] ):
try:
sell_info = rh.order_sell_crypto_limit( str( asset.ticker ), asset.quantity, price )
# Mark this asset as sold, the garbage collector (see 'run' method) will remove it from our orders at the next iteration
self.orders[ asset.order_id ].quantity = 0
except:
print( 'Got exception trying to sell, aborting.' )
return False
return True