def make_html(request):
"""i knit a bokeh html if asked from AJAX"""
fig = figure()
_=vis_bokeh.draw_1d_hist_from_es("avgMass",0,40,50,es,"run*",ax=fig)
fig.xaxis.axis_label = time.strftime("%H:%M:%S")
fig_html = vis_bokeh.fig_to_html(fig)
return HttpResponse(fig_html)
def knit_html(self,es):
#col1
fig1 = figure(width=250,height=250)
vis_bokeh.draw_1d_hist_from_es("dummy1",0,35,30,es,"run*",ax=fig1) #changes fig1, but also returns it
fig2=figure(width=250,height=250)
xmin,xmax = 0,65
xbins = 20
xname = "hcalEnergy"
ymin,ymax = 0,65
ybins = 20
yname = "muonHits"
vis_bokeh.draw_2d_hist_from_es(xname,xmin,xmax,xbins,yname,ymin,ymax,ybins,es,
index="run*",ax=fig2)
fig_column1 = vplot(fig1,fig2)
#col2
fig3 = figure(width=250,height=250)
fig3=vis_bokeh.draw_1d_hist_from_es("dummy23",0,100,30,es,"run*",ax=fig3,hist_drawer="classic")
fig4 = figure(width=250,height=250)
fig4=vis_bokeh.draw_1d_hist_from_es("dummy45",0,40,30,es,"run*",ax=fig4)
fig_column2 = vplot(fig3,fig4)
fig_grid = hplot(fig_column1,fig_column2)
return vis_bokeh.fig_to_html(fig_grid)
def get_value(self):
fig = figure()
xname = "invariantMass"
xmin,xmax,xbins = -5.,15.,50
index = "run*"
x,counts = vis_bokeh.get_1d_hist(xname,xmin,xmax,xbins,es,index=index)
deltas = np.sqrt(counts)
fig=vis_bokeh.whiskered_histogram(xmin,xmax,xbins,counts,deltas,-deltas)
#fit params
model = mix
model.fit(sample_weight=counts)#,values_init={'sig_weightlog':np.log(0.4),'bck_weightlog':np.log(0.6)})
parameters = model.parameters
w_sig,w_bkg =np.exp(parameters['sig_weightlog']),np.exp(parameters['bck_weightlog'])
w_sum = w_sig+w_bkg
w_sig,w_bkg = w_sig/w_sum,w_bkg/w_sum
n_events = np.sum(counts)
norm = n_events*(xmax-xmin)/xbins
#plot lines
expo = lambda x_arr:st.expon(0,1./parameters['slope']).pdf(x_arr)*w_bkg*norm
gauss = lambda x_arr:st.norm(parameters['mean'],parameters['sigma']).pdf(x_arr)*w_sig*norm
pdf_x = np.arange(1000,dtype='float')/1000.*(xmax-xmin) + xmin
fig.line(pdf_x, expo(pdf_x), legend="Background", line_width=2,color = 'red')
fig.line(pdf_x, gauss(pdf_x), legend="Signal", line_width=2,color='blue')
fig.line(pdf_x, gauss(pdf_x)+expo(pdf_x), legend="Sum", line_width=2,color='green')
fig.xaxis.axis_label = time.strftime("%H:%M:%S")
return vis_bokeh.fig_to_html(fig)
def knit_html(self,es):
figs = []
for i in range(len(self.hists)):
figs.append(
[self.make_figure(hist,model,es,"run*") for hist,model in zip(self.hists[i],self.models[i])]
)
hrows = [hplot(*row) for row in figs]
grid = vplot(*hrows)
return vis_bokeh.fig_to_html(grid)
def get_value(self):
fig = figure()
_=vis_bokeh.draw_1d_hist_from_es("avgMass",0,40,50,es,"run*",ax=fig)
fig.xaxis.axis_label = time.strftime("%H:%M:%S")
fig_html = vis_bokeh.fig_to_html(fig)
return fig_html
def knit_html(self,es):
fig = figure()
_=vis_bokeh.draw_1d_hist_from_es("avgMass",0,70,50,es,"run*",ax=fig)
return vis_bokeh.fig_to_html(fig)
def knit_html(self,es):
hist = Histogram([1,2,3])
return fig_to_html(hist)
