callouts on multiflex

rowers/interactiveplots.py

@@ -1237,12 +1237,29 @@ def interactive_multiflex(datadf,xparam,yparam,groupby,extratitle='',
         )
 
     
-    TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize,hover'
+    TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize'
+
+    if groupby != 'date':
+        hover = HoverTool(names=['data'],
+                          tooltips = [
+                              (groupby,'@groupval{1.1}')
+                          ])
+    else:
+        hover = HoverTool(names=['data'],
+                          tooltips = [
+                              (groupby,'@groupval')
+                          ])
+
+    hover.mode = 'mouse'
+    TOOLS = [SaveTool(),PanTool(),BoxZoomTool(),WheelZoomTool(),
+             ResetTool(),TapTool(),ResizeTool(),hover]
+    
 
     plot = Figure(x_axis_type=x_axis_type,y_axis_type=y_axis_type,
 		  tools=TOOLS,
 		  toolbar_location="above",
 		  toolbar_sticky=False)
+
     # add watermark
     plot.extra_y_ranges = {"watermark": watermarkrange}
     plot.extra_x_ranges = {"watermark": watermarkrange}
@@ -1293,20 +1310,6 @@ def interactive_multiflex(datadf,xparam,yparam,groupby,extratitle='',
 		minutes = ["%M"]
 	    )
 
-    hover = plot.select(dict(type=HoverTool))
-
-    
-    
-    if groupby != 'date':
-        hover.tooltips = OrderedDict([
-	    (groupby,'@groupval{1.1}'),
-	])
-    else:
-        hover.tooltips = OrderedDict([
-            (groupby,'@groupval'),
-        ])
-        
-    hover.mode = 'mouse'
 
     script,div = components(plot)
 

rowers/views.py

@@ -3515,105 +3515,106 @@ def multiflex_view(request,userid=0,
 
         else:
             return HttpResponse("invalid form")
-
-        fieldlist,fielddict = dataprep.getstatsfields()
-        fieldlist = [xparam,yparam,groupby,
-                     'workoutid','spm','driveenergy',
-                     'workoutstate']
-    
-        # prepare data frame
-        datadf = dataprep.read_cols_df_sql(ids,fieldlist)
-        
-        datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
-
-        datadf = dataprep.filter_df(datadf,'spm',spmmin,
-                                    largerthan=True)
-        datadf = dataprep.filter_df(datadf,'spm',spmmax,
-                                    largerthan=False)
-        datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
-                                    largerthan=True)
-        datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
-                                    largerthan=False)
-
-        datadf.dropna(axis=0,how='any',inplace=True)
-        datemapping = {
-            w.id:w.date for w in workouts
-        }
-
-        datadf['date'] = datadf['workoutid']
-        datadf['date'].replace(datemapping,inplace=True)
-
-        today = datetime.date.today()
-        datadf['days ago'] = map(lambda x : x.days, datadf.date - today)
-
-        if groupby != 'date':
-            bins = np.arange(datadf[groupby].min()-binsize,
-                             datadf[groupby].max()+binsize,
-                             binsize)
-            groups = datadf.groupby(pd.cut(datadf[groupby],bins,labels=False))
-        else:
-            bins = np.arange(datadf['days ago'].min()-binsize,
-                             datadf['days ago'].max()+binsize,
-                             binsize,
-            )
-            groups = datadf.groupby(pd.cut(datadf['days ago'], bins,
-                                           labels=False))
-            
-
-        xvalues = groups.mean()[xparam]
-        yvalues = groups.mean()[yparam]
-        xerror = groups.std()[xparam]
-        yerror = groups.std()[yparam]
-        groupsize = groups.count()[xparam]
-        
-        #groupsize = 15.*np.log10(1+99.*groupsize/float(max(groupsize)))
-        groupsize = 30.*np.sqrt(groupsize/float(max(groupsize)))
-                
-        df = pd.DataFrame({
-            xparam:xvalues,
-            yparam:yvalues,
-            'xerror':xerror,
-            'yerror':yerror,
-            'groupsize':groupsize,
-        })
-
-        if groupby != 'date':
-            try:
-                df['groupval'] = groups.mean()[groupby],
-            except ValueError:
-                df['groupval'] =  groups.mean()[groupby].fillna(value=0)
-        else:
-            try:
-                df['groupval'] = [x.strftime("%Y-%m-%d") for x in groups.min()[groupby]]
-            except AttributeError:
-                df['groupval'] = groups.mean()['days ago'].fillna(value=0)
-                    
-        if userid == 0:
-            extratitle = ''
-        else:
-            u = User.objects.get(id=userid)
-            extratitle = ' '+u.first_name+' '+u.last_name
-                
-
-            
-        script,div = interactive_multiflex(df,xparam,yparam,
-                                           groupby,
-                                           extratitle=extratitle,
-                                           ploterrorbars=ploterrorbars)
-                
-            
-
-        return render(request,'multiflex.html',
-                      {'interactiveplot':script,
-                       'the_div':div,
-                       'chartform':chartform,
-                       'userid':userid,
-                       'teams':get_my_teams(request.user),
-                      })
     else:
         url = reverse(user_multiflex_select)
         return HttpResponseRedirect(url)
 
+    fieldlist,fielddict = dataprep.getstatsfields()
+    fieldlist = [xparam,yparam,groupby,
+                 'workoutid','spm','driveenergy',
+                 'workoutstate']
+    
+    # prepare data frame
+    datadf = dataprep.read_cols_df_sql(ids,fieldlist)
+        
+    datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
+
+    datadf = dataprep.filter_df(datadf,'spm',spmmin,
+                                largerthan=True)
+    datadf = dataprep.filter_df(datadf,'spm',spmmax,
+                                largerthan=False)
+    datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
+                                largerthan=True)
+    datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
+                                largerthan=False)
+
+    datadf.dropna(axis=0,how='any',inplace=True)
+    datemapping = {
+        w.id:w.date for w in workouts
+    }
+
+    datadf['date'] = datadf['workoutid']
+    datadf['date'].replace(datemapping,inplace=True)
+
+    today = datetime.date.today()
+    datadf['days ago'] = map(lambda x : x.days, datadf.date - today)
+
+    if groupby != 'date':
+        bins = np.arange(datadf[groupby].min()-binsize,
+                         datadf[groupby].max()+binsize,
+                         binsize)
+        groups = datadf.groupby(pd.cut(datadf[groupby],bins,labels=False))
+    else:
+        bins = np.arange(datadf['days ago'].min()-binsize,
+                         datadf['days ago'].max()+binsize,
+                         binsize,
+        )
+        groups = datadf.groupby(pd.cut(datadf['days ago'], bins,
+                                           labels=False))
+            
+
+    xvalues = groups.mean()[xparam]
+    yvalues = groups.mean()[yparam]
+    xerror = groups.std()[xparam]
+    yerror = groups.std()[yparam]
+    groupsize = groups.count()[xparam]
+        
+    #groupsize = 15.*np.log10(1+99.*groupsize/float(max(groupsize)))
+    groupsize = 30.*np.sqrt(groupsize/float(max(groupsize)))
+                
+    df = pd.DataFrame({
+        xparam:xvalues,
+        yparam:yvalues,
+        'xerror':xerror,
+        'yerror':yerror,
+        'groupsize':groupsize,
+    })
+    
+    if groupby != 'date':
+        try:
+            df['groupval'] = groups.mean()[groupby],
+        except ValueError:
+            df['groupval'] =  groups.mean()[groupby].fillna(value=0)
+    else:
+        try:
+            df['groupval'] = [x.strftime("%Y-%m-%d") for x in groups.min()[groupby]]
+        except AttributeError:
+            df['groupval'] = groups.mean()['days ago'].fillna(value=0)
+                    
+    if userid == 0:
+        extratitle = ''
+    else:
+        u = User.objects.get(id=userid)
+        extratitle = ' '+u.first_name+' '+u.last_name
+                
+
+            
+    script,div = interactive_multiflex(df,xparam,yparam,
+                                       groupby,
+                                       extratitle=extratitle,
+                                       ploterrorbars=ploterrorbars)
+                
+            
+
+    return render(request,'multiflex.html',
+                  {'interactiveplot':script,
+                   'the_div':div,
+                   'chartform':chartform,
+                   'userid':userid,
+                   'teams':get_my_teams(request.user),
+                  })
+
+
 # Box plots
 @user_passes_test(ispromember,login_url="/",redirect_field_name=None)
 def user_boxplot_select(request,