data fusion now working ...

rowers/dataprep.py

@@ -959,35 +959,41 @@ def smalldataprep(therows,xparam,yparam1,yparam2):
 # data fusion
 def datafusion(id1,id2,columns,offset):
     df1,w1 = getrowdata_db(id=id1)
-    df1 = df1.drop(['cumdist',
+    df1 = df1.drop([#'cumdist',
                     'hr_ut2',
 		    'hr_ut1',
 		    'hr_at',
 		    'hr_tr',
 		    'hr_an',
-		    'hr_max',],
+		    'hr_max',
+                    'ftime',
+                    'fpace',
+                    'workoutid',
+                    'id'],
                    1,errors='ignore')
-    columns = ['time']+columns
-    df2 = getsmallrowdata_db(columns,ids=[id2],doclean=False)
 
-    print df1['pace'].mean()/1000.,'mies'
+    df2 = getsmallrowdata_db(['time']+columns,ids=[id2],doclean=False)
-    
+    offsetmillisecs = offset.seconds*1000+offset.microseconds/1000.
+    offsetmillisecs += offset.days*(3600*24*1000)
+    df2['time'] = df2['time']+offsetmillisecs
+
     keep1 = {c:c for c in set(df1.columns)}
     for c in columns:
         keep1.pop(c)
-    
+
     for c in df1.columns:
         if not c in keep1:
             df1 = df1.drop(c,1,errors='ignore')
 
     df = pd.concat([df1,df2],ignore_index=True)
     df = df.sort_values(['time'])
-    df = df.interpolate(method='linear',axis=0,limit_direction='both')
+    df = df.interpolate(method='linear',axis=0,limit_direction='both',
+                        limit=10)
     df.fillna(method='bfill',inplace=True)
     
     df['time'] = df['time']/1000.
     df['pace'] = df['pace']/1000.
-    print df['pace'].mean(),'noot'
+    df['cum_dist'] = df['cumdist']
     
     return df
 
@@ -1005,7 +1011,6 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
     rowdatadf.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
 
     p = rowdatadf.ix[:,' Stroke500mPace (sec/500m)']
-    print p.mean(),'aap'
     hr = rowdatadf.ix[:,' HRCur (bpm)']
     spm = rowdatadf.ix[:,' Cadence (stokes/min)']
     cumdist = rowdatadf.ix[:,'cum_dist']

rowers/forms.py

@@ -259,7 +259,8 @@ class WorkoutMultipleCompareForm(forms.Form):
 
 from rowers.interactiveplots import axlabels
 
-axlabels.pop('None')
+formaxlabels = axlabels.copy()
+formaxlabels.pop('None')
 parchoices = list(sorted(axlabels.items(), key = lambda x:x[1]))
 
     
@@ -273,10 +274,16 @@ class ChartParamChoiceForm(forms.Form):
     plottype = forms.ChoiceField(choices=plotchoices,initial='scatter')
     teamid = forms.IntegerField(widget=forms.HiddenInput())
 
-axlabels.pop('time')
+formaxlabels.pop('time')
 metricchoices = list(sorted(axlabels.items(), key = lambda x:x[1]))
     
 class FusionMetricChoiceForm(forms.Form):
+    posneg = (
+        ('pos','Workout 2 starts after Workout 1'),
+        ('neg','Workout 2 starts before Workout 1'),
+        )
     columns = forms.MultipleChoiceField(choices=metricchoices,
                                         initial=[],
                                         widget=forms.CheckboxSelectMultiple())
+    posneg = forms.ChoiceField(choices=posneg,initial='pos')
+    offset = forms.DurationField(label='Time Offset',initial=datetime.timedelta())

rowers/interactiveplots.py

@@ -1291,10 +1291,10 @@ def interactive_flex_chart2(id=0,promember=0,
     y2means = y1means
 
     xlabel = Label(x=100,y=130,x_units='screen',y_units='screen',
-                    text=axlabels[xparam]+": {x1mean:6.2f}".format(x1mean=x1mean),
+                   text=axlabels[xparam]+": {x1mean:6.2f}".format(x1mean=x1mean),
-                    background_fill_alpha=.7,
+                   background_fill_alpha=.7,
-                    text_color='green',
+                   text_color='green',
-    )
+        )
 
     if (xparam != 'time') and (xparam != 'distance') and (xparam != 'cumdist'):
 	plot.add_layout(x1means)
@@ -1325,6 +1325,7 @@ def interactive_flex_chart2(id=0,promember=0,
 
     plot.title.text = row.name
     plot.title.text_font_size=value("1.0em")
+
     plot.xaxis.axis_label = axlabels[xparam]
     plot.yaxis.axis_label = axlabels[yparam1]
 

rowers/views.py

@@ -5017,15 +5017,27 @@ def workout_fusion_view(request,id1=0,id2=1):
         form = FusionMetricChoiceForm(request.POST)
         if form.is_valid():
             cd = form.cleaned_data
-            columns = cd['columns']
+            columns = cd['columns']
+            timeoffset = cd['offset']
+            posneg = cd['posneg']
+            if posneg == 'neg':
+                timeoffset = -timeoffset
             df = dataprep.datafusion(id1,id2,columns,timeoffset)
             idnew,message = dataprep.new_workout_from_df(r,df,
                                                          title='Fused data',
-                                                         parent=w1)
+                                                         parent=w1)
-            url = reverse(workout_edit_view,
+            if message != None:
-                          kwargs={
+                url = reverse(workout_edit_view,
-                              'message':message,
+                              kwargs={
-                              'id':idnew,
+                                  'message':message,
+                                  'id':idnew,
+                              })
+            else:
+                successmessage = 'Data fused'
+                url = reverse(workout_edit_view,
+                              kwargs={
+                                  'successmessage':successmessage,
+                                  'id':idnew,
                               })
 
             return HttpResponseRedirect(url)