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Create generate_plot_graph

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This commit is contained in:
Matthias 2019-06-30 10:31:36 +02:00
parent 0b517584aa
commit c7a4a16eec
2 changed files with 35 additions and 33 deletions
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35
freqtrade/plot/plotting.py
View File

@ -5,9 +5,10 @@ from typing import Any, Dict, List, Optional
import pandas as pd
from freqtrade.arguments import Arguments
from freqtrade.exchange import Exchange
from freqtrade.data import history
from freqtrade.data.btanalysis import load_trades
from freqtrade.data.btanalysis import (combine_tickers_with_mean,
create_cum_profit, load_trades)
from freqtrade.exchange import Exchange
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
logger = logging.getLogger(__name__)
@ -28,6 +29,7 @@ class FTPlots():
self._config = config
self.exchange: Optional[Exchange] = None
# Exchange is only needed when downloading data!
if self._config.get("live", False) or self._config.get("refresh_pairs", False):
self.exchange = ExchangeResolver(self._config.get('exchange', {}).get('name'),
self._config).exchange
@ -258,6 +260,35 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
return fig
def generate_profit_graph(pairs: str, tickers: Dict[str, pd.DataFrame], trades: pd.DataFrame = None,
) -> go.Figure:
# Combine close-values for all pairs, rename columns to "pair"
df_comb = combine_tickers_with_mean(tickers, "close")
# Add combined cumulative profit
df_comb = create_cum_profit(df_comb, trades, 'cum_profit')
# Plot the pairs average close prices, and total profit growth
avgclose = go.Scattergl(
x=df_comb.index,
y=df_comb['mean'],
name='Avg close price',
)
fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
fig.append_trace(avgclose, 1, 1)
fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
for pair in pairs:
profit_col = f'cum_profit_{pair}'
df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col)
fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
store_plot_file(fig, filename='freqtrade-profit-plot.html', auto_open=True)
def generate_plot_filename(pair, ticker_interval) -> str:
"""
Generate filenames per pair/ticker_interval to be used for storing plots

33
scripts/plot_profit.py
View File

@ -8,13 +8,9 @@ import logging
import sys
from typing import Any, Dict, List
import plotly.graph_objs as go
from plotly import tools
from freqtrade.arguments import ARGS_PLOT_PROFIT, Arguments
from freqtrade.data.btanalysis import create_cum_profit, combine_tickers_with_mean
from freqtrade.optimize import setup_configuration
from freqtrade.plot.plotting import FTPlots, store_plot_file, add_profit
from freqtrade.plot.plotting import FTPlots, generate_profit_graph
from freqtrade.state import RunMode
logger = logging.getLogger(__name__)
@ -33,32 +29,7 @@ def plot_profit(config: Dict[str, Any]) -> None:
# Create an average close price of all the pairs that were involved.
# this could be useful to gauge the overall market trend
# Combine close-values for all pairs, rename columns to "pair"
df_comb = combine_tickers_with_mean(plot.tickers, "close")
# Add combined cumulative profit
df_comb = create_cum_profit(df_comb, trades, 'cum_profit')
# Plot the pairs average close prices, and total profit growth
avgclose = go.Scattergl(
x=df_comb.index,
y=df_comb['mean'],
name='Avg close price',
)
fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
fig.append_trace(avgclose, 1, 1)
fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
for pair in plot.pairs:
profit_col = f'cum_profit_{pair}'
df_comb = create_cum_profit(df_comb, trades[trades['pair'] == pair], profit_col)
fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
store_plot_file(fig, filename='freqtrade-profit-plot.html', auto_open=True)
generate_profit_graph(plot.pairs, plot.tickers, trades)
def plot_parse_args(args: List[str]) -> Dict[str, Any]: