From 3cedace2f6fce431cd5df784b5bcf5ce499bf02d Mon Sep 17 00:00:00 2001
From: xmatthias <xmatthias@outlook.com>
Date: Sat, 23 Jun 2018 19:54:27 +0200
Subject: [PATCH] add plotting for backtested trades

---
 scripts/plot_dataframe.py | 49 +++++++++++++++++++++++++++++++++------
 1 file changed, 42 insertions(+), 7 deletions(-)

diff --git a/scripts/plot_dataframe.py b/scripts/plot_dataframe.py
index 7f9641222..cd41f51b1 100755
--- a/scripts/plot_dataframe.py
+++ b/scripts/plot_dataframe.py
@@ -27,9 +27,12 @@ Example of usage:
 import logging
 import os
 import sys
+import json
+from pathlib import Path
 from argparse import Namespace
 from typing import Dict, List, Any
 
+import pandas as pd
 import plotly.graph_objs as go
 from plotly import tools
 from plotly.offline import plot
@@ -103,10 +106,42 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
             exit()
 
     # Get trades already made from the DB
-    trades: List[Trade] = []
+    trades: pd.DataFrame = pd.DataFrame()
     if args.db_url:
         persistence.init(_CONF)
-        trades = Trade.query.filter(Trade.pair.is_(pair)).all()
+        trades_ = Trade.query.filter(Trade.pair.is_(pair)).all()
+        # columns = ["pair", "profit", "opents", "closets", "index", "duration"]
+        columns = ["pair", "profit", "opents", "closets", "open_rate", "close_rate", "duration"]
+
+        trades = pd.DataFrame([(t.pair, t.calc_profit(),
+                                t.open_date, t.close_date,
+                                t.open_rate, t.close_rate,
+                                t.close_date.timestamp() - t.open_date.timestamp())
+                               for t in trades_], columns=columns)
+
+    if args.exportfilename:
+        file = Path(args.exportfilename)
+        # must align with columns in backtest.py
+        columns = ["pair", "profit", "opents", "closets", "index", "duration",
+                   "open_rate", "close_rate", "open_at_end"]
+        with file.open() as f:
+            data = json.load(f)
+            trades = pd.DataFrame(data, columns=columns)
+        trades = trades.loc[trades["pair"] == pair]
+        if timerange:
+            if timerange.starttype == 'date':
+                trades = trades.loc[trades["opents"] >= timerange.startts]
+            if timerange.stoptype == 'date':
+                trades = trades.loc[trades["opents"] <= timerange.stopts]
+
+        trades['opents'] = pd.to_datetime(trades['opents'],
+                                          unit='s',
+                                          utc=True,
+                                          infer_datetime_format=True)
+        trades['closets'] = pd.to_datetime(trades['closets'],
+                                           unit='s',
+                                           utc=True,
+                                           infer_datetime_format=True)
 
     dataframes = analyze.tickerdata_to_dataframe(tickers)
     dataframe = dataframes[pair]
@@ -126,7 +161,7 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
     plot(fig, filename=os.path.join('user_data', 'freqtrade-plot.html'))
 
 
-def generate_graph(pair, trades, data, args) -> tools.make_subplots:
+def generate_graph(pair, trades: pd.DataFrame, data: pd.DataFrame, args) -> tools.make_subplots:
     """
     Generate the graph from the data generated by Backtesting or from DB
     :param pair: Pair to Display on the graph
@@ -187,8 +222,8 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
     )
 
     trade_buys = go.Scattergl(
-        x=[t.open_date.isoformat() for t in trades],
-        y=[t.open_rate for t in trades],
+        x=trades["opents"],
+        y=trades["open_rate"],
         mode='markers',
         name='trade_buy',
         marker=dict(
@@ -199,8 +234,8 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
         )
     )
     trade_sells = go.Scattergl(
-        x=[t.close_date.isoformat() for t in trades],
-        y=[t.close_rate for t in trades],
+        x=trades["closets"],
+        y=trades["close_rate"],
         mode='markers',
         name='trade_sell',
         marker=dict(