Merge pull request matplotlib#177 from DanielGoldfarb/master

change candle width defaults; add line width to algorithm

src/mplfinance/_version.py

@@ -1,5 +1,5 @@
 
-version_info = (0, 12, 5, 'alpha', 2)
+version_info = (0, 12, 5, 'alpha', 3)
 
 _specifier_ = {'alpha': 'a','beta': 'b','candidate': 'rc','final': ''}
 

src/mplfinance/_widths.py

@@ -10,21 +10,21 @@ def _get_widths_df():
  and observing which numbers gave the "best" appearance.
  '''
  numpoints = [n for n in range(30,241,30)]
- #volume_width = (0.95, 0.90, 0.85, 0.80, 0.75, 0.70, 0.65, 0.60 )
- #volume_width = (0.95, 0.925, 0.90, 0.875, 0.85, 0.825, 0.80, 0.775 )
  volume_width = (0.98, 0.96, 0.95, 0.925, 0.9, 0.9, 0.875, 0.825 )
  volume_linewidth = tuple([0.65]*8)
- candle_width = (0.65, 0.575, 0.50, 0.425, 0.350, 0.312, 0.312, 0.321)
- candle_linewidth = (1.00, 0.875, 0.75, 0.625, 0.500, 0.438, 0.438, 0.438)
+ candle_width = (0.65, 0.575, 0.50, 0.445, 0.435, 0.425, 0.420, 0.415)
+ candle_linewidth = (1.00, 0.875, 0.75, 0.625, 0.500, 0.438, 0.435, 0.435)
  ohlc_tickwidth = tuple([0.35]*8)
  ohlc_linewidth = (1.50, 1.175, 0.85, 0.525, 0.525, 0.525, 0.525, 0.525)
+ line_width = (2.00, 1.600, 1.15, 0.720, 0.715, 0.710, 0.705, 0.700)
  widths = {}
  widths['vw'] = volume_width
  widths['vlw'] = volume_linewidth
  widths['cw'] = candle_width
  widths['clw'] = candle_linewidth
  widths['ow'] = ohlc_tickwidth
  widths['olw'] = ohlc_linewidth
+ widths['lw'] = line_width
  return pd.DataFrame(widths,index=numpoints)
 
 _widths = _get_widths_df()
@@ -39,6 +39,9 @@ def _valid_scale_width_kwargs():
 
  'candle' : { 'Default' : None,
  'Validator' : lambda value: isinstance(value,(float,int)) },
+
+ 'lines' : { 'Default' : None,
+ 'Validator' : lambda value: isinstance(value,(float,int)) },
  }
  _validate_vkwargs_dict(vkwargs)
  return vkwargs
@@ -63,6 +66,9 @@ def _valid_update_width_kwargs():
 
  'candle_linewidth' : { 'Default' : None,
  'Validator' : lambda value: isinstance(value,(float,int)) },
+
+ 'line_width' : { 'Default' : None,
+ 'Validator' : lambda value: isinstance(value,(float,int)) },
  }
  _validate_vkwargs_dict(vkwargs)
  return vkwargs
@@ -91,6 +97,7 @@ def _determine_width_config( xdates, config ):
  width_config['ohlc_linewidth' ] = None
  width_config['candle_width' ] = avg_dist_between_points / 2.0
  width_config['candle_linewidth'] = None
+ width_config['line_width' ] = None
 
  else: # config['width_adjuster_version'] == 'v1'
 
@@ -100,16 +107,19 @@ def _determine_width_config( xdates, config ):
  width_config['ohlc_linewidth' ] = _dfinterpolate(_widths,datalen,'olw')
  width_config['candle_width' ] = _dfinterpolate(_widths,datalen,'cw' ) * adjust
  width_config['candle_linewidth'] = _dfinterpolate(_widths,datalen,'clw')
+ width_config['line_width' ] = _dfinterpolate(_widths,datalen,'lw')
 
  if config['scale_width_adjustment'] is not None:
 
  scale = _process_kwargs(config['scale_width_adjustment'],_valid_scale_width_kwargs())
  if scale['volume'] is not None:
- width_config['volume_width'] *= scale['volume']
+ width_config['volume_width']  *= scale['volume']
  if scale['ohlc'] is not None:
  width_config['ohlc_ticksize'] *= scale['ohlc']
  if scale['candle'] is not None:
- width_config['candle_width'] *= scale['candle']
+ width_config['candle_width'] *= scale['candle']
+ if scale['lines'] is not None:
+ width_config['line_width'] *= scale['lines']
 
 
  if config['update_width_config'] is not None:

src/mplfinance/plotting.py

@@ -306,7 +306,8 @@ def plot( data, **kwargs ):
 
  collections = None
  if ptype == 'line':
- axA1.plot(xdates, closes, color=config['linecolor'])
+ lw = config['_width_config']['line_width']
+ axA1.plot(xdates, closes, color=config['linecolor'], linewidth=lw)
  else:
  collections =_construct_mpf_collections(ptype,dates,xdates,opens,highs,lows,closes,volumes,config,style)
 
@@ -333,16 +334,18 @@ def plot( data, **kwargs ):
 
  # Get rcParams['lines.linewidth'] and scale it
  # according to the deinsity of data??
- 
+
  for mav in mavgs:
  if ptype in VALID_PMOVE_TYPES:
  mavprices = pd.Series(brick_values).rolling(mav).mean().values
  else:
  mavprices = pd.Series(closes).rolling(mav).mean().values
+
+ lw = config['_width_config']['line_width']
  if mavc:
- axA1.plot(xdates, mavprices, color=next(mavc))
+ axA1.plot(xdates, mavprices, linewidth=lw, color=next(mavc))
  else:
- axA1.plot(xdates, mavprices)
+ axA1.plot(xdates, mavprices, linewidth=lw)
 
  avg_dist_between_points = (xdates[-1] - xdates[0]) / float(len(xdates))
  if not config['tight_layout']: