RAPTOR v18.4: Исправлена отчетность, активированы выходные

invest-python-master/t_tech/invest/strategies/plotting/plotter.py

@@ -0,0 +1,62 @@
+import abc
+import logging
+from typing import Any, Iterable, List, NewType, Protocol
+
+import matplotlib.pyplot as plt
+import mplfinance as mpf
+from IPython.display import clear_output
+from matplotlib.gridspec import GridSpec
+
+from t_tech.invest.strategies.base.event import StrategyEvent
+
+PlotKwargs = NewType("PlotKwargs", dict)
+
+logger = logging.getLogger(__name__)
+
+
+class IPlotter(Protocol):
+    def plot(self, strategy_events: Iterable[StrategyEvent]) -> None:
+        pass
+
+
+class StrategyPlotter(abc.ABC, IPlotter):
+    @abc.abstractmethod
+    def get_candle_plot_kwargs(
+        self, strategy_events: List[StrategyEvent]
+    ) -> PlotKwargs:
+        pass
+
+    @abc.abstractmethod
+    def get_signal_plot_kwargs(
+        self, strategy_events: List[StrategyEvent]
+    ) -> List[PlotKwargs]:
+        pass
+
+    def get_plot_kwargs(
+        self, strategy_events: Iterable[StrategyEvent], ax: Any
+    ) -> PlotKwargs:
+        strategy_events = list(strategy_events)
+        candle_plot = self.get_candle_plot_kwargs(strategy_events=strategy_events)
+        if signal_plots := self.get_signal_plot_kwargs(strategy_events=strategy_events):
+            add_plots = []
+            for signal_plot in signal_plots:
+                signal_plot.update({"ax": ax})
+                ap = mpf.make_addplot(**signal_plot)
+                add_plots.append(ap)
+
+            candle_plot.update({"addplot": add_plots})
+        return candle_plot
+
+    def plot(self, strategy_events: Iterable[StrategyEvent]) -> None:
+        _fig = plt.figure(figsize=(20, 20))
+        gs = GridSpec(2, 1, height_ratios=[3, 1])
+        _ax1 = plt.subplot(gs[0])
+        _ax2 = plt.subplot(gs[1])
+
+        candle_plot_kwargs = self.get_plot_kwargs(strategy_events, ax=_ax1)
+        candle_plot_kwargs.update({"ax": _ax1, "volume": _ax2})
+        mpf.plot(**candle_plot_kwargs, warn_too_much_data=999999999)
+
+        clear_output(wait=True)
+        _fig.canvas.draw()
+        _fig.canvas.flush_events()