sanity checks before plotting, cleanup

freqtrade/plot/plotting.py

@@ -25,8 +25,7 @@ def generate_row(fig, row, indicators: List[str], data: pd.DataFrame) -> tools.m
     """
     for indicator in indicators:
         if indicator in data:
-            # TODO: Replace all Scatter with Scattergl for performance!!
-            scattergl = go.Scatter(
+            scattergl = go.Scattergl(
                 x=data['date'],
                 y=data[indicator],
                 mode='lines',
@@ -48,7 +47,7 @@ def plot_trades(fig, trades: pd.DataFrame):
     Plot trades to "fig"
     """
     # Trades can be empty
-    if trades is not None:
+    if trades is not None and len(trades) > 0:
         trade_buys = go.Scatter(
             x=trades["open_time"],
             y=trades["open_rate"],
@@ -123,44 +122,50 @@ def generate_graph(
 
     if 'buy' in data.columns:
         df_buy = data[data['buy'] == 1]
-        buys = go.Scatter(
-            x=df_buy.date,
-            y=df_buy.close,
-            mode='markers',
-            name='buy',
-            marker=dict(
-                symbol='triangle-up-dot',
-                size=9,
-                line=dict(width=1),
-                color='green',
+        if len(df_buy) > 0:
+            buys = go.Scattergl(
+                x=df_buy.date,
+                y=df_buy.close,
+                mode='markers',
+                name='buy',
+                marker=dict(
+                    symbol='triangle-up-dot',
+                    size=9,
+                    line=dict(width=1),
+                    color='green',
+                )
             )
-        )
-        fig.append_trace(buys, 1, 1)
+            fig.append_trace(buys, 1, 1)
+        else:
+            logger.warning("No buy-signals found.")
 
     if 'sell' in data.columns:
         df_sell = data[data['sell'] == 1]
-        sells = go.Scatter(
-            x=df_sell.date,
-            y=df_sell.close,
-            mode='markers',
-            name='sell',
-            marker=dict(
-                symbol='triangle-down-dot',
-                size=9,
-                line=dict(width=1),
-                color='red',
+        if len(df_sell) > 0:
+            sells = go.Scattergl(
+                x=df_sell.date,
+                y=df_sell.close,
+                mode='markers',
+                name='sell',
+                marker=dict(
+                    symbol='triangle-down-dot',
+                    size=9,
+                    line=dict(width=1),
+                    color='red',
+                )
             )
-        )
-        fig.append_trace(sells, 1, 1)
+            fig.append_trace(sells, 1, 1)
+        else:
+            logger.warning("No sell-signals found.")
 
     if 'bb_lowerband' in data and 'bb_upperband' in data:
-        bb_lower = go.Scatter(
+        bb_lower = go.Scattergl(
             x=data.date,
             y=data.bb_lowerband,
             name='BB lower',
             line={'color': 'rgba(255,255,255,0)'},
         )
-        bb_upper = go.Scatter(
+        bb_upper = go.Scattergl(
             x=data.date,
             y=data.bb_upperband,
             name='BB upper',

scripts/plot_dataframe.py

@@ -51,11 +51,18 @@ _CONF: Dict[str, Any] = {}
 timeZone = pytz.UTC
 
 
-def load_trades(args: Namespace, pair: str) -> pd.DataFrame:
-    trades: pd.DataFrame = pd.DataFrame()
-    if args.db_url:
-        persistence.init(args.db_url, clean_open_orders=False)
+def load_trades(db_url: str = None, exportfilename: str = None) -> pd.DataFrame:
+    """
+    Load trades, either from a DB (using dburl) or via a backtest export file.
+    :param db_url: Sqlite url (default format sqlite:///tradesv3.dry-run.sqlite)
+    :param exportfilename: Path to a file exported from backtesting
+    :returns: Dataframe containing Trades
+    """
+    # TODO: Document and move to btanalysis
+    trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS)
 
+    if db_url:
+        persistence.init(db_url, clean_open_orders=False)
         columns = ["pair", "profit", "open_time", "close_time",
                    "open_rate", "close_rate", "duration"]
 
@@ -68,18 +75,15 @@ def load_trades(args: Namespace, pair: str) -> pd.DataFrame:
                                 t.open_rate, t.close_rate,
                                 t.close_date.timestamp() - t.open_date.timestamp()
                                 if t.close_date else None)
-                               for t in Trade.query.filter(Trade.pair.is_(pair)).all()],
+                               for t in Trade.query.all()],
                               columns=columns)
 
-    elif args.exportfilename:
+    elif exportfilename:
 
-        file = Path(args.exportfilename)
+        file = Path(exportfilename)
         if file.exists():
             trades = load_backtest_data(file)
 
-        else:
-            trades = pd.DataFrame([], columns=BT_DATA_COLUMNS)
-
     return trades
 
 
@@ -181,6 +185,7 @@ def extract_trades_of_period(dataframe, trades) -> pd.DataFrame:
     Compare trades and backtested pair DataFrames to get trades performed on backtested period
     :return: the DataFrame of a trades of period
     """
+    # TODO: Document and move to btanalysis (?)
     trades = trades.loc[(trades['open_time'] >= dataframe.iloc[0]['date']) &
                         (trades['close_time'] <= dataframe.iloc[-1]['date'])]
     return trades
@@ -211,7 +216,9 @@ def analyse_and_plot_pairs(args: Namespace):
         tickers[pair] = data
         dataframe = generate_dataframe(strategy, tickers, pair)
 
-        trades = load_trades(args, pair)
+        trades = load_trades(pair, db_url=args.db_url,
+                             exportfilename=args.exportfilename)
+        trades = trades.loc[trades['pair'] == pair]
         trades = extract_trades_of_period(dataframe, trades)
 
         fig = generate_graph(