def get_hist_data(self):
"""returns the tuple of arrays (bin_centers,bin_counts),also saves them as self.binx and self.binc"""
es = self.es
index = self.index
xname, xmin, xmax, xbins = self.xname, self.xmin, self.xmax, self.xbins
x, c = get_1d_hist(xname, xmin, xmax, xbins, es, index=index)
x, c = map(np.array, [x, c])
self.binx, self.binc = x, c
return x, c
def draw_1d_hist_from_es(xname,xmin,xmax,xbins,es,index="*",ax=None,hist_drawer="whiskers"):
"""i plot the histogram of a variable xname between xmin,xmax with xbins uniform bins.
i require es to be an elasticsearch.Elasticsearch client.
if hist_drawer == "whiskers", plots a CERNish whiskered histogram
elif hist_drawer == "classic", plots a regular one
else tries to use hist_drawer as a function(xmin,xmax,xbins,counts,fig=<bokeh figure>) -> figure"""
x,c = get_1d_hist(xname,xmin,xmax,xbins,es,index=index)
if hist_drawer == "whiskers":
deltas = np.sqrt(c)
#use whiskered-specific interface
return whiskered_histogram(xmin,xmax,xbins,c,deltas,-deltas,fig=ax)
elif hist_drawer == "classic":
hist_drawer = classic_histogram
return hist_drawer(xmin,xmax,xbins,c,fig=ax)
