Merge branch 'external_axes'

Author: DanielGoldfarb

examples/external_axes.ipynb

@@ -0,0 +1,36 @@
+'''
+This file contains a simple animation demo using mplfinance "external axes mode".
+
+Note that presently mplfinance does not support "blitting" (blitting makes animation
+more efficient).  Nonetheless, the animation is efficient enough to update at least
+once per second, and typically more frequently depending on the size of the plot.
+'''
+import pandas as pd
+import mplfinance as mpf
+import matplotlib.animation as animation
+
+idf = pd.read_csv('data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)
+idf.shape
+idf.head(3)
+idf.tail(3)
+df = idf.loc['2011-07-01':'2011-12-30',:]
+
+fig = mpf.figure(style='charles',figsize=(7,8))
+ax1 = fig.add_subplot(2,1,1)
+ax2 = fig.add_subplot(3,1,3)
+
+def animate(ival):
+    if (20+ival) > len(df):
+        print('no more data to plot')
+        ani.event_source.interval *= 3
+        if ani.event_source.interval > 12000:
+            exit()
+        return
+    data = df.iloc[0:(20+ival)]
+    ax1.clear()
+    ax2.clear()
+    mpf.plot(data,ax=ax1,volume=ax2,type='candle')
+
+ani = animation.FuncAnimation(fig, animate, interval=250)
+
+mpf.show()

examples/mpf_animation_demo1.py

@@ -0,0 +1,45 @@
+'''
+This file contains a simple animation demo using mplfinance "external axes mode".
+
+In this example, instead of creating the Figure and Axes external to mplfiance,
+we allow mplfinance to create the Figure and Axes using its "panel method", and
+set kwarg `returnfig=True` so that mplfinance will return the Figure and Axes.
+
+We then take those Axes and pass them back into mplfinance ("external axes mode")
+as part of the animation.
+
+Note that presently mplfinance does not support "blitting" (blitting makes animation
+more efficient).  Nonetheless, the animation is efficient enough to update at least
+once per second, and typically more frequently depending on the size of the plot.
+'''
+import pandas as pd
+import mplfinance as mpf
+import matplotlib.animation as animation
+
+idf = pd.read_csv('data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)
+
+df = idf.loc['2011-07-01':'2011-12-30',:]
+
+pkwargs=dict(type='candle',mav=(10,20))
+
+fig, axes = mpf.plot(df.iloc[0:20],returnfig=True,volume=True,
+                     figsize=(11,8),panel_ratios=(2,1),
+                     title='\n\nS&P 500 ETF',**pkwargs)
+ax1 = axes[0]
+ax2 = axes[2]
+
+def animate(ival):
+    if (20+ival) > len(df):
+        print('no more data to plot')
+        ani.event_source.interval *= 3
+        if ani.event_source.interval > 12000:
+            exit()
+        return
+    data = df.iloc[0:(20+ival)]
+    ax1.clear()
+    ax2.clear()
+    mpf.plot(data,ax=ax1,volume=ax2,**pkwargs)
+
+ani = animation.FuncAnimation(fig, animate, interval=200)
+
+mpf.show()

examples/mpf_animation_demo2.py

@@ -0,0 +1,90 @@
+'''
+This file contains a animation demo using mplfinance "external axes mode",
+in which animate both the display of candlesticks as well as the display
+of MACD (Moving Average Convergence Divergence) visual analysis.
+
+In this example, instead of creating the Figure and Axes external to mplfiance,
+we allow mplfinance to create the Figure and Axes using its "panel method", and
+set kwarg `returnfig=True` so that mplfinance will return the Figure and Axes.
+
+We then take those Axes and pass them back into mplfinance ("external axes mode")
+as part of the animation.
+
+Note that presently mplfinance does not support "blitting" (blitting makes animation
+more efficient).  Nonetheless, the animation is efficient enough to update at least
+once per second, and typically more frequently depending on the size of the plot.
+'''
+import pandas as pd
+import mplfinance as mpf
+import matplotlib.animation as animation
+
+mpf.__version__
+
+idf = pd.read_csv('data/SPY_20110701_20120630_Bollinger.csv',index_col=0,parse_dates=True)
+idf.shape
+idf.head(3)
+idf.tail(3)
+df = idf.loc['2011-07-01':'2011-12-30',:]
+
+
+# =======
+#  MACD:
+
+df = df.iloc[0:30]
+
+exp12     = df['Close'].ewm(span=12, adjust=False).mean()
+exp26     = df['Close'].ewm(span=26, adjust=False).mean()
+macd      = exp12 - exp26
+signal    = macd.ewm(span=9, adjust=False).mean()
+histogram = macd - signal
+
+apds = [mpf.make_addplot(exp12,color='lime'),
+        mpf.make_addplot(exp26,color='c'),
+        mpf.make_addplot(histogram,type='bar',width=0.7,panel=1,
+                         color='dimgray',alpha=1,secondary_y=False),
+        mpf.make_addplot(macd,panel=1,color='fuchsia',secondary_y=True),
+        mpf.make_addplot(signal,panel=1,color='b',secondary_y=True),
+       ]
+
+s = mpf.make_mpf_style(base_mpf_style='classic',rc={'figure.facecolor':'lightgray'})
+
+fig, axes = mpf.plot(df,type='candle',addplot=apds,figscale=1.5,figratio=(7,5),title='\n\nMACD',
+                     style=s,volume=True,volume_panel=2,panel_ratios=(6,3,2),returnfig=True)
+
+ax_main = axes[0]
+ax_emav = ax_main
+ax_hisg = axes[2]
+ax_macd = axes[3]
+ax_sign = ax_macd
+ax_volu = axes[4]
+
+df =  idf.loc['2011-07-01':'2011-12-30',:]
+
+def animate(ival):
+    if (20+ival) > len(df):
+        print('no more data to plot')
+        ani.event_source.interval *= 3
+        if ani.event_source.interval > 12000:
+            exit()
+        return
+    data = df.iloc[0:(30+ival)]
+    exp12     = data['Close'].ewm(span=12, adjust=False).mean()
+    exp26     = data['Close'].ewm(span=26, adjust=False).mean()
+    macd      = exp12 - exp26
+    signal    = macd.ewm(span=9, adjust=False).mean()
+    histogram = macd - signal
+    apds = [mpf.make_addplot(exp12,color='lime',ax=ax_emav),
+            mpf.make_addplot(exp26,color='c',ax=ax_emav),
+            mpf.make_addplot(histogram,type='bar',width=0.7,
+                             color='dimgray',alpha=1,ax=ax_hisg),
+            mpf.make_addplot(macd,color='fuchsia',ax=ax_macd),
+            mpf.make_addplot(signal,color='b',ax=ax_sign),
+           ]
+
+    for ax in axes:
+        ax.clear()
+    mpf.plot(data,type='candle',addplot=apds,ax=ax_main,volume=ax_volu)
+
+ani = animation.FuncAnimation(fig,animate,interval=100)
+
+mpf.show()