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import libraries organized.

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This commit is contained in:
misagh 2018-09-23 04:51:53 +02:00
parent f1b4e4b36c
commit 29459d7d30
1 changed files with 10 additions and 19 deletions
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29
freqtrade/edge/__init__.py
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@ -6,11 +6,13 @@ from datetime import datetime, timedelta
from typing import Any, Dict, List, NamedTuple, Optional, Tuple
import arrow
from pandas import DataFrame, to_datetime
from tabulate import tabulate
import numpy as np
from pandas import DataFrame, to_datetime
import pandas as pd
from tabulate import tabulate
import freqtrade.optimize as optimize
from freqtrade.optimize.backtesting import BacktestResult
from freqtrade import DependencyException, constants
from freqtrade.arguments import Arguments
from freqtrade.configuration import Configuration
@ -21,10 +23,12 @@ from freqtrade.strategy.interface import SellType
from freqtrade.strategy.resolver import IStrategy, StrategyResolver
from freqtrade.optimize.backtesting import Backtesting
from collections import OrderedDict
import timeit
from time import sleep
import pdb
import numpy as np
import timeit
import utils_find_1st as utf1st
from time import sleep
from pandas import set_option
logger = logging.getLogger(__name__)
@ -178,8 +182,6 @@ class Edge():
if len(bslap_results_df) > 0: # Only post process a frame if it has a record
bslap_results_df = self.vector_fill_results_table(bslap_results_df)
else:
from freqtrade.optimize.backtesting import BacktestResult
bslap_results_df = []
bslap_results_df = DataFrame.from_records(bslap_results_df, columns=BacktestResult._fields)
@ -207,8 +209,6 @@ class Edge():
:param bslap_results Dataframe
:return: bslap_results Dataframe
"""
import pandas as pd
import numpy as np
debug = self.debug_vector
# stake and fees
@ -247,7 +247,6 @@ class Edge():
def np_get_t_open_ind(self, np_buy_arr, t_exit_ind: int, np_buy_arr_len: int, stop_stops: int,
stop_stops_count: int):
import utils_find_1st as utf1st
"""
The purpose of this def is to return the next "buy" = 1
after t_exit_ind.
@ -373,12 +372,6 @@ class Edge():
return final.reset_index().values
def backslap_pair(self, ticker_data, pair, stoploss):
import pandas as pd
import numpy as np
import timeit
import utils_find_1st as utf1st
from datetime import datetime
### backslap debug wrap
# debug_2loops = False # only loop twice, for faster debug
# debug_timing = False # print timing for each step
@ -388,7 +381,6 @@ class Edge():
debug = self.debug # print values, to check accuracy
# Read Stop Loss Values and Stake
# pdb.set_trace()
#stop = self.stop_loss_value
stop = stoploss
p_stop = (stop + 1) # What stop really means, e.g 0.01 is 0.99 of price
@ -398,7 +390,6 @@ class Edge():
print("p_stop is", p_stop, "value used to multiply to entry price")
if debug:
from pandas import set_option
set_option('display.max_rows', 5000)
set_option('display.max_columns', 8)
pd.set_option('display.width', 1000)