addplot external axes

Author: DanielGoldfarb

examples/external_axes.ipynb

@@ -0,0 +1,29 @@
+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

@@ -1,19 +1,10 @@
 import pandas as pd
 import mplfinance as mpf
-import matplotlib.pyplot as plt
 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',:]
-
-print('len(df)=',len(df))
 
-# fig = mpf.figure(style='default',figsize=(7,8))
-# ax1 = fig.add_subplot(2,1,1)
-# ax2 = fig.add_subplot(3,1,3)
+df = idf.loc['2011-07-01':'2011-12-30',:]
 
 pkwargs=dict(type='candle',mav=(10,20))
 
@@ -24,9 +15,6 @@
 def animate(ival):
     if (20+ival) > len(df):
         print('no more data to plot')
-        #answer = input('Exit (y/n)?')
-        #if answer.lower()[0:1] == 'y':
-        #    exit()
         ani.event_source.interval *= 3
         if ani.event_source.interval > 12000:
             exit()
@@ -36,6 +24,6 @@ def animate(ival):
     ax2.clear()
     mpf.plot(data,ax=ax1,volume=ax2,**pkwargs)
 
-ani = animation.FuncAnimation(fig, animate, interval=250)
+ani = animation.FuncAnimation(fig, animate, interval=200)
 
-plt.show()
+mpf.show()

examples/mpf_animation.py renamed to examples/mpf_animation_demo2.py

@@ -0,0 +1,74 @@
+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()

examples/mpf_animation_macd.py

@@ -2,4 +2,4 @@
 from   mplfinance.plotting  import plot, make_addplot
 from   mplfinance._styles   import make_mpf_style, make_marketcolors, available_styles
 from   mplfinance._version  import __version__
-from   mplfinance._mplwraps import figure
+from   mplfinance._mplwraps import figure, show

src/mplfinance/__init__.py

@@ -22,8 +22,12 @@
           - Figure.add_axes() 
           - Figure.subplot()  (this is analogous to pyplot.subplot() which calls Figure.add_subplot())
           - Figure.subplots() 
+
+     (3) A wrapper to matplot.pyplot.show(), because it happens often enough, when using mplfinance,
+         that sometimes one has to import matplotlib.pyplot *ONLY* for the purpose of calling .show()
 """
 
+show = plt.show  # Not a true wrapper, rather an assignment.
 
 def _check_for_and_apply_style(kwargs):
 

src/mplfinance/_mplwraps.py

@@ -497,21 +497,27 @@ def plot( data, **kwargs ):
 
     addplot = config['addplot']
     if addplot is not None and ptype not in VALID_PMOVE_TYPES:
-        # Calculate the Order of Magnitude Range ('mag')
-        # If addplot['secondary_y'] == 'auto', then: If the addplot['data']
-        # is out of the Order of Magnitude Range, then use secondary_y.
-        # Calculate omrange for Main panel, and for Lower (volume) panel:
-        lo = math.log(max(math.fabs(np.nanmin(lows)),1e-7),10) - 0.5
-        hi = math.log(max(math.fabs(np.nanmax(highs)),1e-7),10) + 0.5
+        # NOTE: If in external_axes_mode, then all code relating
+        #       to panels and secondary_y becomes irrrelevant.
+        #       If the user wants something on a secondary_y then user should
+        #       determine that externally, and pass in the appropriate axes.
 
-        panels['mag'] = [None]*len(panels)  # create 'mag'nitude column
+        if not external_axes_mode:
+            # Calculate the Order of Magnitude Range ('mag')
+            # If addplot['secondary_y'] == 'auto', then: If the addplot['data']
+            # is out of the Order of Magnitude Range, then use secondary_y.
 
-        panels.at[config['main_panel'],'mag'] = {'lo':lo,'hi':hi} # update main panel magnitude range
+            lo = math.log(max(math.fabs(np.nanmin(lows)),1e-7),10) - 0.5
+            hi = math.log(max(math.fabs(np.nanmax(highs)),1e-7),10) + 0.5
 
-        if config['volume']:
-            lo = math.log(max(math.fabs(np.nanmin(volumes)),1e-7),10) - 0.5
-            hi = math.log(max(math.fabs(np.nanmax(volumes)),1e-7),10) + 0.5
-            panels.at[config['volume_panel'],'mag'] = {'lo':lo,'hi':hi}
+            panels['mag'] = [None]*len(panels)  # create 'mag'nitude column
+
+            panels.at[config['main_panel'],'mag'] = {'lo':lo,'hi':hi} # update main panel magnitude range
+
+            if config['volume']:
+                lo = math.log(max(math.fabs(np.nanmin(volumes)),1e-7),10) - 0.5
+                hi = math.log(max(math.fabs(np.nanmax(volumes)),1e-7),10) + 0.5
+                panels.at[config['volume_panel'],'mag'] = {'lo':lo,'hi':hi}
 
         if isinstance(addplot,dict):
             addplot = [addplot,]   # make list of dict to be consistent
@@ -521,11 +527,12 @@ def plot( data, **kwargs ):
 
         for apdict in addplot:
 
-            panid = apdict['panel']
-            if   panid == 'main' : panid = 0  # for backwards compatibility
-            elif panid == 'lower': panid = 1  # for backwards compatibility
-            if apdict['y_on_right'] is not None:
-                panels.at[panid,'y_on_right'] = apdict['y_on_right']
+            panid = apdict['panel'] 
+            if not external_axes_mode:
+                if   panid == 'main' : panid = 0  # for backwards compatibility
+                elif panid == 'lower': panid = 1  # for backwards compatibility
+                if apdict['y_on_right'] is not None:
+                    panels.at[panid,'y_on_right'] = apdict['y_on_right']
 
             aptype = apdict['type']
             if aptype == 'ohlc' or aptype == 'candle':
@@ -545,6 +552,8 @@ def plot( data, **kwargs ):
                     ax = _addplot_columns(panid,panels,ydata,apdict,xdates,config)
                     _addplot_apply_supplements(ax,apdict)
 
+    # fill_between is NOT supported for external_axes_mode
+    # (caller can easily call ax.fill_between() themselves).
     if config['fill_between'] is not None and not external_axes_mode:
         fb    = config['fill_between']
         panid = config['main_panel']
@@ -696,6 +705,7 @@ def _addplot_collections(panid,panels,apdict,xdates,config):
 
     apdata = apdict['data']
     aptype = apdict['type']
+    external_axes_mode = apdict['ax'] is not None
 
     #--------------------------------------------------------------#
     # Note: _auto_secondary_y() sets the 'magnitude' column in the
@@ -716,16 +726,21 @@ def _addplot_collections(panid,panels,apdict,xdates,config):
         raise TypeError('addplot type "'+aptype+'" MUST be accompanied by addplot data of type `pd.DataFrame`')
     d,o,h,l,c,v = _check_and_prepare_data(apdata,config)
     collections = _construct_mpf_collections(aptype,d,xdates,o,h,l,c,v,config,config['style'])
-    lo = math.log(max(math.fabs(np.nanmin(l)),1e-7),10) - 0.5
-    hi = math.log(max(math.fabs(np.nanmax(h)),1e-7),10) + 0.5
-    secondary_y = _auto_secondary_y( panels, panid, lo, hi )
-    if 'auto' != apdict['secondary_y']:
-        secondary_y = apdict['secondary_y'] 
-    if secondary_y:
-        ax = panels.at[panid,'axes'][1] 
-        panels.at[panid,'used2nd'] = True
-    else: 
-        ax = panels.at[panid,'axes'][0]
+
+    if not external_axes_mode:
+        lo = math.log(max(math.fabs(np.nanmin(l)),1e-7),10) - 0.5
+        hi = math.log(max(math.fabs(np.nanmax(h)),1e-7),10) + 0.5
+        secondary_y = _auto_secondary_y( panels, panid, lo, hi )
+        if 'auto' != apdict['secondary_y']:
+            secondary_y = apdict['secondary_y'] 
+        if secondary_y:
+            ax = panels.at[panid,'axes'][1] 
+            panels.at[panid,'used2nd'] = True
+        else: 
+            ax = panels.at[panid,'axes'][0]
+    else:
+        ax = apdict['ax']
+
     for coll in collections:
         ax.add_collection(coll)
     if apdict['mav'] is not None:
@@ -734,21 +749,25 @@ def _addplot_collections(panid,panels,apdict,xdates,config):
     return ax
 
 def _addplot_columns(panid,panels,ydata,apdict,xdates,config):
-    secondary_y = False
-    if apdict['secondary_y'] == 'auto':
-        yd = [y for y in ydata if not math.isnan(y)]
-        ymhi = math.log(max(math.fabs(np.nanmax(yd)),1e-7),10)
-        ymlo = math.log(max(math.fabs(np.nanmin(yd)),1e-7),10)
-        secondary_y = _auto_secondary_y( panels, panid, ymlo, ymhi )
+    external_axes_mode = apdict['ax'] is not None
+    if not external_axes_mode:
+        secondary_y = False
+        if apdict['secondary_y'] == 'auto':
+            yd = [y for y in ydata if not math.isnan(y)]
+            ymhi = math.log(max(math.fabs(np.nanmax(yd)),1e-7),10)
+            ymlo = math.log(max(math.fabs(np.nanmin(yd)),1e-7),10)
+            secondary_y = _auto_secondary_y( panels, panid, ymlo, ymhi )
+        else:
+            secondary_y = apdict['secondary_y']
+            #print("apdict['secondary_y'] says secondary_y is",secondary_y)
+
+        if secondary_y:
+            ax = panels.at[panid,'axes'][1] 
+            panels.at[panid,'used2nd'] = True
+        else: 
+            ax = panels.at[panid,'axes'][0]
     else:
-        secondary_y = apdict['secondary_y']
-        #print("apdict['secondary_y'] says secondary_y is",secondary_y)
-
-    if secondary_y:
-        ax = panels.at[panid,'axes'][1] 
-        panels.at[panid,'used2nd'] = True
-    else: 
-        ax = panels.at[panid,'axes'][0]
+        ax = apdict['ax']
 
     aptype = apdict['type']
     if aptype == 'scatter':