minor

epitopepredict/base.py

@@ -679,8 +679,8 @@ def promiscuous_binders(self, binders=None, name=None, cutoff=.95,
  binders: can provide a precalculated list of binders
  name: specific protein, optional
  value: to pass to get_binders
- cutoff_method: 'default', 'score' or 'rank'
- cutoff: percentile cutoff for get_binders
+ cutoff_method: 'rank', 'score' or 'global'
+ cutoff: cutoff for get_binders (rank, score or percentile)
  n: min number of alleles
  unique_core: removes peptides with duplicate cores and picks the most
  limit: limit the number of peptides per protein, default None

epitopepredict/plotting.py

@@ -421,7 +421,7 @@ def bokeh_plot_sequence(preds, name=None, n=2, cutoff=.95, cutoff_method='defaul
  """
  callback = CustomJS(
  args=dict(x_range=p.x_range,rect=previewrect,text=seqtext,width=p.plot_width), code=jscode)
- slider = RangeSlider (start=0, end=N, value=(0,L), step=10, callback_policy="throttle")
+ slider = RangeSlider (start=0, end=N, value=(0,L), step=10)#, callback_policy="throttle")
  slider.js_on_change('value_throttled', callback)
 
  #callback for plot drag
@@ -659,7 +659,7 @@ def plot_tracks(preds, name, n=1, cutoff=.95, cutoff_method='default', regions=N
  h = round(h*.1+2)
  figsize = (w,h)
  #plt.clf()
- fig = plt.figure(figsize=figsize)
+ fig = plt.figure(figsize=figsize,facecolor='white')
  ax = fig.add_subplot(111)
 
  p = len(preds)