fix pnf return calc values per stackoverflow 66991998

src/mplfinance/_utils.py

@@ -855,7 +855,9 @@ def _construct_renko_collections(dates, highs, lows, volumes, config_renko_param
                                     edgecolors=edge_colors,
                                     linewidths=lw
                                     )
-    return [rectCollection,], new_dates, new_volumes, brick_values, brick_size
+    calculated_values = dict(dates=new_dates,volumes=new_volumes,
+                             values=brick_values,size=brick_size)
+    return [rectCollection,], calculated_values
 
 
 def _construct_pointnfig_collections(dates, highs, lows, volumes, config_pointnfig_params, closes, marketcolors=None):
@@ -998,7 +1000,7 @@ def _construct_pointnfig_collections(dates, highs, lows, volumes, config_pointnf
     box_values = [] # y values for the boxes
     circle_patches = [] # list of circle patches to be used to create the cirCollection
     line_seg = [] # line segments that make up the Xs
-    
+
     for index, difference in enumerate(boxes):
         diff = abs(difference)
 
@@ -1007,9 +1009,9 @@ def _construct_pointnfig_collections(dates, highs, lows, volumes, config_pointnf
 
         x = [index] * (diff)
         y = [curr_price + (i * box_size * sign) for i in range(start_iteration, diff+start_iteration)]
-        
+
         curr_price += (box_size * sign * (diff))
-        box_values.append(sum(y) / len(y))
+        box_values.append( y )
 
         for i in range(len(x)): # x and y have the same length
             height = box_size * 0.85
@@ -1036,7 +1038,9 @@ def _construct_pointnfig_collections(dates, highs, lows, volumes, config_pointnf
                                  linewidths=lw,
                                  antialiaseds=useAA
                                  )
-    return [cirCollection, xCollection], new_dates, new_volumes, box_values, box_size
+    calculated_values = dict(dates=new_dates,counts=boxes,values=box_values,
+                             volumes=new_volumes,size=box_size)
+    return [cirCollection, xCollection], calculated_values
 
 
 def _construct_aline_collections(alines, dtix=None):

src/mplfinance/_version.py

@@ -1,5 +1,5 @@
 
-version_info = (0, 12, 7, 'alpha', 11)
+version_info = (0, 12, 7, 'alpha', 12)
 
 _specifier_ = {'alpha': 'a','beta': 'b','candidate': 'rc','final': ''}
 

src/mplfinance/plotting.py

@@ -400,16 +400,25 @@ def plot( data, **kwargs ):
         collections =_construct_mpf_collections(ptype,dates,xdates,opens,highs,lows,closes,volumes,config,style)
 
     if ptype in VALID_PMOVE_TYPES:
-        collections, new_dates, volumes, brick_values, size = collections
-        formatter = IntegerIndexDateTimeFormatter(new_dates, fmtstring)
-        xdates = np.arange(len(new_dates))
+        collections, calculated_values = collections
+        volumes       = calculated_values['volumes']
+        pmove_dates   = calculated_values['dates']
+        pmove_values  = calculated_values['values']
+        if all([isinstance(v,(list,tuple)) for v in pmove_values]):
+            pmove_avgvals = [sum(v)/len(v) for v in pmove_values]
+        else:
+            pmove_avgvals = pmove_values
+        pmove_size    = calculated_values['size']
+        pmove_counts  = calculated_values['counts'] if 'counts' in calculated_values else None
+        formatter = IntegerIndexDateTimeFormatter(pmove_dates, fmtstring)
+        xdates = np.arange(len(pmove_dates))
 
     if collections is not None:
         for collection in collections:
             axA1.add_collection(collection)
 
     if ptype in VALID_PMOVE_TYPES:
-        mavprices = _plot_mav(axA1,config,xdates,brick_values)
+        mavprices = _plot_mav(axA1,config,xdates,pmove_avgvals)
     else:
         mavprices = _plot_mav(axA1,config,xdates,closes)
 
@@ -428,8 +437,8 @@ def plot( data, **kwargs ):
         _lows  = lows
         _highs = highs
     else:
-        _lows  = brick_values
-        _highs = [brick+size for brick in brick_values]
+        _lows  = pmove_avgvals
+        _highs = [value+pmove_size for value in pmove_avgvals]
 
     miny = np.nanmin(_lows)
     maxy = np.nanmax(_highs)
@@ -458,13 +467,17 @@ def plot( data, **kwargs ):
 
     if config['return_calculated_values'] is not None:
         retdict = config['return_calculated_values']
-        if ptype in VALID_PMOVE_TYPES:
-            prekey = ptype
-            retdict[prekey+'_bricks'] = brick_values
-            retdict[prekey+'_dates'] = mdates.num2date(new_dates)
-            retdict[prekey+'_size'] = size
-            if config['volume']:
-                retdict[prekey+'_volumes'] = volumes
+        if ptype == 'renko':
+            retdict['renko_bricks' ] = pmove_values
+            retdict['renko_dates'  ] = mdates.num2date(pmove_dates)
+            retdict['renko_size'   ] = pmove_size
+            retdict['renko_volumes'] = volumes if config['volume'] else None
+        elif ptype == 'pnf':
+            retdict['pnf_dates'    ] = mdates.num2date(pmove_dates)
+            retdict['pnf_counts'   ] = pmove_counts
+            retdict['pnf_values'   ] = pmove_values
+            retdict['pnf_size'     ] = pmove_size
+            retdict['pnf_volumes'  ] = volumes if config['volume'] else None
         if config['mav'] is not None:
             mav = config['mav']
             if len(mav) != len(mavprices):
@@ -480,7 +493,7 @@ def plot( data, **kwargs ):
     # Note: these are NOT mutually exclusive, so the order of this
     #       if/elif is important: VALID_PMOVE_TYPES must be first.
     if ptype in VALID_PMOVE_TYPES:
-        dtix = pd.DatetimeIndex([dt for dt in mdates.num2date(new_dates)])
+        dtix = pd.DatetimeIndex([dt for dt in mdates.num2date(pmove_dates)])
     elif not config['show_nontrading']:
         dtix = data.index
     else: