Make plot_profit.py flake8 compliant
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@ -1,27 +1,24 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python3
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import sys
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import sys
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import argparse
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import json
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import json
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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import freqtrade.optimize as optimize
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import freqtrade.optimize as optimize
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import freqtrade.misc as misc
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import freqtrade.misc as misc
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import freqtrade.exchange as exchange
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import freqtrade.analyze as analyze
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from freqtrade.strategy.strategy import Strategy
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from freqtrade.strategy.strategy import Strategy
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def plot_parse_args(args ):
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def plot_parse_args(args):
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parser = misc.common_args_parser('Graph utility')
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parser = misc.common_args_parser('Graph utility')
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# FIX: perhaps delete those backtesting options that are not feasible (shows up in -h)
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# FIX: perhaps delete those backtesting options that are not feasible (shows up in -h)
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misc.backtesting_options(parser)
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misc.backtesting_options(parser)
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parser.add_argument(
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parser.add_argument(
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'-p', '--pair',
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'-p', '--pair',
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help = 'Show profits for only this pairs. Pairs are comma-separated.',
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help='Show profits for only this pairs. Pairs are comma-separated.',
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dest = 'pair',
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dest='pair',
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default = None
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default=None
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)
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)
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return parser.parse_args(args)
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return parser.parse_args(args)
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@ -48,7 +45,7 @@ def make_profit_array(data, px, filter_pairs=[]):
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# total profits at each timeframe
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# total profits at each timeframe
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# to accumulated profits
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# to accumulated profits
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pa = 0
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pa = 0
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for x in range(0,len(pg)):
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for x in range(0, len(pg)):
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p = pg[x] # Get current total percent
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p = pg[x] # Get current total percent
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pa += p # Add to the accumulated percent
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pa += p # Add to the accumulated percent
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pg[x] = pa # write back to save memory
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pg[x] = pa # write back to save memory
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@ -104,7 +101,7 @@ def plot_profit(args) -> None:
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# if max_x != n:
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# if max_x != n:
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# raise Exception('Please rerun script. Input data has different lengths %s'
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# raise Exception('Please rerun script. Input data has different lengths %s'
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# %('Different pair length: %s <=> %s' %(max_x, n)))
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# %('Different pair length: %s <=> %s' %(max_x, n)))
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print('max_x: %s' %(max_x))
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print('max_x: %s' % (max_x))
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# We are essentially saying:
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# We are essentially saying:
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# array <- sum dataframes[*]['close'] / num_items dataframes
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# array <- sum dataframes[*]['close'] / num_items dataframes
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@ -114,7 +111,7 @@ def plot_profit(args) -> None:
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for pair, pair_data in dataframes.items():
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for pair, pair_data in dataframes.items():
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close = pair_data['close']
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close = pair_data['close']
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maxprice = max(close) # Normalize price to [0,1]
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maxprice = max(close) # Normalize price to [0,1]
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print('Pair %s has length %s' %(pair, len(close)))
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print('Pair %s has length %s' % (pair, len(close)))
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for x in range(0, len(close)):
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for x in range(0, len(close)):
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avgclose[x] += close[x] / maxprice
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avgclose[x] += close[x] / maxprice
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# avgclose += close
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# avgclose += close
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