technical_analysis: refined forecast plotting

src/technical_analysis.py

@@ -5,6 +5,7 @@ import dotenv
 import matplotlib.pyplot as plt
 import matplotlib.dates as mdates
 from matplotlib.axes import Axes
+import numpy as np
 import os
 import pandas as pd
 from ta.volume import volume_weighted_average_price
@@ -307,7 +308,7 @@ class TechnicalAnalysis():
         """
 
         self.logger.info(f'plotting {colstoplot} in {dataset}')
-        colorcycle = ['black', 'blue', 'red', 'green', 'orange']
+        colorcycle = ['black', 'blue', 'green', 'orange']
         for i, col in enumerate(colstoplot):
             ax.plot(
                 df.index,
@@ -324,15 +325,17 @@ class TechnicalAnalysis():
             # Add a transparent shaded region daily lows and highs
             ax.fill_between(df.index, df['Low'], df['High'], color='gray', alpha=0.3, label='Price Range')
             # extract the Price rows for which 'High's are NaN
-            nanind = df.High.isna()
-            df_fcst_close = df.loc[nanind, 'Close']
-            if df_fcst_close.shape[0] > 0:
-                ax.plot(
-                    df_fcst_close.index,
-                    df_fcst_close,
-                    color='red',
-                    marker='*',
-                    label='Forecast')
+            nanind = np.where(df.High.isna())
+            df_fcst = df['Close'].iloc[nanind]
+            if df_fcst.shape[0] > 0:
+                # append the last day before the forecasts
+                nonnanind = np.where(df.High.notna())
+                df_now = df['Close'].iloc[[nonnanind[0][-1]]]
+                df_now_fcst = pd.concat([df_now, df_fcst])
+                # connect the last available day and forecasts with a red line
+                ax.plot(df_now_fcst.index, df_now_fcst, color='red')
+                # plot only the forecasts with markers
+                ax.plot(df_fcst.index, df_fcst, color='red', marker='*', label='Forecast')
         # else:
         #     # plot a transparent line across the full df.index just to make sure that x-axis limits are identical for all panels
         #     ax.plot(df.index, df[col], color='gray', alpha=0.0)