Merge pull request #454 from gcarq/replace_matplotlib
Replace matplotlib with Plotly
This commit is contained in:
Samuel Husso
GitHub
commit
3b11459a38
@ -5,21 +5,34 @@ This page explains how to plot prices, indicator, profits.
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- [Plot price and indicators](#plot-price-and-indicators)
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- [Plot profit](#plot-profit)
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## Installation
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Plotting scripts use Plotly library. Install/upgrade it with:
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```
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pip install --upgrade plotly
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```
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At least version 2.3.0 is required.
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## Plot price and indicators
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Usage for the price plotter:
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script/plot_dataframe.py [-h] [-p pair]
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```
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script/plot_dataframe.py [-h] [-p pair] [--live]
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```
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Example
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```
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python script/plot_dataframe.py -p BTC_ETH,BTC_LTC
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python script/plot_dataframe.py -p BTC_ETH
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```
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The -p pair argument, can be used to specify what
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The `-p` pair argument, can be used to specify what
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pair you would like to plot.
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**Advanced use**
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To plot the current live price use the --live flag:
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To plot the current live price use the `--live` flag:
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```
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python scripts/plot_dataframe.py -p BTC_ETH --live
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```
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@ -51,19 +64,14 @@ The third graph can be useful to spot outliers, events in pairs
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that makes profit spikes.
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Usage for the profit plotter:
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script/plot_profit.py [-h] [-p pair] [--datadir directory] [--ticker_interval num]
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The -p pair argument, can be used to plot a single pair
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```
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script/plot_profit.py [-h] [-p pair] [--datadir directory] [--ticker_interval num]
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```
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The `-p` pair argument, can be used to plot a single pair
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Example
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```
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python python scripts/plot_profit.py --datadir ../freqtrade/freqtrade/tests/testdata-20171221/ -p BTC_LTC
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```
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**When it goes wrong**
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*** Linux: Can't display**
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If you are inside an python environment, you might want to set the
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DISPLAY variable as so:
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$ DISPLAY=:0 python scripts/plot_dataframe.py
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@ -22,5 +22,4 @@ tabulate==0.8.2
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pymarketcap==3.3.153
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# Required for plotting data
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#matplotlib==2.1.0
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#PYQT5==5.9
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#plotly==2.3.0
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@ -3,14 +3,16 @@
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import sys
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import logging
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import argparse
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import os
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import matplotlib
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# matplotlib.use("Qt5Agg")
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import matplotlib.dates as mdates
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import matplotlib.pyplot as plt
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from pandas import DataFrame
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import talib.abstract as ta
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import plotly
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from plotly import tools
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from plotly.offline import plot
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import plotly.graph_objs as go
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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from freqtrade import exchange, analyze
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from freqtrade.misc import common_args_parser
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@ -36,8 +38,7 @@ def plot_analyzed_dataframe(args) -> None:
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:param pair: pair as str
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:return: None
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"""
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pair = args.pair
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pairs = [pair]
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pair = args.pair.replace('-', '_')
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timerange = misc.parse_timerange(args.timerange)
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# Init strategy
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@ -52,7 +53,7 @@ def plot_analyzed_dataframe(args) -> None:
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exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
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tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
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else:
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tickers = optimize.load_data(args.datadir, pairs=pairs,
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tickers = optimize.load_data(args.datadir, pairs=[pair],
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ticker_interval=tick_interval,
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refresh_pairs=False,
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timerange=timerange)
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@ -62,38 +63,84 @@ def plot_analyzed_dataframe(args) -> None:
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dataframe = analyze.populate_sell_trend(dataframe)
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dates = misc.datesarray_to_datetimearray(dataframe['date'])
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# Two subplots sharing x axis
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fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
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fig.suptitle(pair + " " + str(tick_interval), fontsize=14, fontweight='bold')
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if (len(dataframe.index) > 750):
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logger.warn('Ticker contained more than 750 candles, clipping.')
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df = dataframe.tail(750)
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ax1.plot(dates, dataframe['close'], label='close')
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# ax1.plot(dates, dataframe['sell'], 'ro', label='sell')
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ax1.plot(dates, dataframe['sma'], '--', label='SMA')
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ax1.plot(dates, dataframe['tema'], ':', label='TEMA')
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ax1.plot(dates, dataframe['blower'], '-.', label='BB low')
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ax1.plot(dates, dataframe['close'] * dataframe['buy'], 'bo', label='buy')
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ax1.plot(dates, dataframe['close'] * dataframe['sell'], 'ro', label='sell')
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candles = go.Candlestick(x=df.date,
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open=df.open,
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high=df.high,
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low=df.low,
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close=df.close,
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name='Price')
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ax1.legend()
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df_buy = df[df['buy'] == 1]
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buys = go.Scattergl(
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x=df_buy.date,
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y=df_buy.close,
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mode='markers',
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name='buy',
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marker=dict(symbol='x-dot')
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)
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df_sell = df[df['sell'] == 1]
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sells = go.Scattergl(
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x=df_sell.date,
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y=df_sell.close,
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mode='markers',
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name='sell',
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marker=dict(symbol='diamond')
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)
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ax2.plot(dates, dataframe['adx'], label='ADX')
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ax2.plot(dates, dataframe['mfi'], label='MFI')
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# ax2.plot(dates, [25] * len(dataframe.index.values))
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ax2.legend()
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bb_lower = go.Scatter(
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x=df.date,
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y=df.bb_lowerband,
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name='BB lower',
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line={'color': "transparent"},
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)
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bb_upper = go.Scatter(
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x=df.date,
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y=df.bb_upperband,
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name='BB upper',
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fill="tonexty",
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fillcolor="rgba(0,176,246,0.2)",
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line={'color': "transparent"},
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)
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ax3.plot(dates, dataframe['fastk'], label='k')
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ax3.plot(dates, dataframe['fastd'], label='d')
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ax3.plot(dates, [20] * len(dataframe.index.values))
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ax3.legend()
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xfmt = mdates.DateFormatter('%d-%m-%y %H:%M') # Dont let matplotlib autoformat date
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ax3.xaxis.set_major_formatter(xfmt)
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macd = go.Scattergl(
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x=df['date'],
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y=df['macd'],
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name='MACD'
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)
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macdsignal = go.Scattergl(
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x=df['date'],
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y=df['macdsignal'],
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name='MACD signal'
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)
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volume = go.Bar(
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x=df['date'],
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y=df['volume'],
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name='Volume'
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)
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fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 4])
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fig.append_trace(candles, 1, 1)
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fig.append_trace(bb_lower, 1, 1)
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fig.append_trace(bb_upper, 1, 1)
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fig.append_trace(buys, 1, 1)
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fig.append_trace(sells, 1, 1)
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fig.append_trace(volume, 2, 1)
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fig.append_trace(macd, 3, 1)
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fig.append_trace(macdsignal, 3, 1)
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fig['layout'].update(title=args.pair)
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fig['layout']['yaxis1'].update(title='Price')
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fig['layout']['yaxis2'].update(title='Volume')
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fig['layout']['yaxis3'].update(title='MACD')
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plot(fig, filename='freqtrade-plot.html')
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# Fine-tune figure; make subplots close to each other and hide x ticks for
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# all but bottom plot.
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fig.subplots_adjust(hspace=0)
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fig.autofmt_xdate() # Rotate the dates
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plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
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plt.show()
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if __name__ == '__main__':
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args = plot_parse_args(sys.argv[1:])
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@ -2,10 +2,13 @@
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import sys
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import json
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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import numpy as np
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import plotly
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from plotly import tools
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from plotly.offline import plot
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import plotly.graph_objs as go
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import freqtrade.optimize as optimize
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import freqtrade.misc as misc
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import freqtrade.exchange as exchange
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@ -122,30 +125,32 @@ def plot_profit(args) -> None:
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# Plot the pairs average close prices, and total profit growth
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#
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fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
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fig.suptitle('total profit')
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avgclose = go.Scattergl(
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x=dates,
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y=avgclose,
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name='Avg close price',
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)
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profit = go.Scattergl(
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x=dates,
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y=pg,
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name='Profit',
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)
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ax1.plot(dates, avgclose, label='avgclose')
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ax2.plot(dates, pg, label='profit')
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ax1.legend(loc='upper left')
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ax2.legend(loc='upper left')
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fig = tools.make_subplots(rows=3, cols=1, shared_xaxes=True, row_width=[1, 1, 1])
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fig.append_trace(avgclose, 1, 1)
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fig.append_trace(profit, 2, 1)
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# FIX if we have one line pair in paris
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# then skip the plotting of the third graph,
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# or change what we plot
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# In third graph, we plot each profit separately
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for pair in pairs:
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pg = make_profit_array(data, max_x, pair)
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ax3.plot(dates, pg, label=pair)
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ax3.legend(loc='upper left')
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# black background to easier see multiple colors
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ax3.set_facecolor('black')
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xfmt = mdates.DateFormatter('%d-%m-%y %H:%M') # Dont let matplotlib autoformat date
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ax3.xaxis.set_major_formatter(xfmt)
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pair_profit = go.Scattergl(
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x=dates,
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y=pg,
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name=pair,
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)
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fig.append_trace(pair_profit, 3, 1)
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fig.subplots_adjust(hspace=0)
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fig.autofmt_xdate() # Rotate the dates
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plt.show()
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plot(fig, filename='freqtrade-profit-plot.html')
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if __name__ == '__main__':
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