linear interpolation in fitnessmetric chart

rowers/interactiveplots.py

@@ -57,6 +57,7 @@ thetimezone = get_current_timezone()
 from scipy.stats import linregress,percentileofscore
 from scipy import optimize
 from scipy.signal import savgol_filter
+from scipy.interpolate import griddata
 
 
 import stravastuff
@@ -646,6 +647,14 @@ def fitnessmetric_chart(fitnessmetrics,user,workoutmode='rower'):
          })
 
 
+    delta = df['power4min'].astype('int').diff()
+
+    mask = delta == 0
+
+    df.loc[mask,'power4min'] = np.nan
+    df.dropna(inplace=True,axis=0,how='any')
+
+    
     df = df[df['power2k']>0]
     df = df[df['mode']==workoutmode]
 
@@ -661,37 +670,70 @@ def fitnessmetric_chart(fitnessmetrics,user,workoutmode='rower'):
             power4min = power4min,
             power2k = power2k,
             date = date,
-            power1hr = power1hr
-            )
+            power1hr = power1hr,
+            fdate=groups['dates'].map(lambda x: x.strftime('%d-%m-%Y'))            )
         )
 
+
+    # fit
+
+    resampled = groups.set_index('dates')
+    resampled.index = pd.to_datetime(resampled.index)
+    resampled = resampled.resample('D').interpolate(
+        method='linear',order=2)
+
+    power4min = resampled['power4min']
+    date = resampled.index.values
+    power2k = resampled['power2k']
+    power1hr = resampled['power1hr']
+
+    source2 = ColumnDataSource(
+        data = dict(
+            power4min = power4min,
+            power2k = power2k,
+            date = date,
+            power1hr = power1hr,
+            fdate=resampled.index.map(lambda x: x.strftime('%d-%m-%Y'))            )
+        )
+
+
+    
+
     TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair'
 
     plot = Figure(tools=TOOLS,toolbar_location="above",
                   toolbar_sticky=False,width=900,
                   x_axis_type='datetime')
 
-#    plot.extra_y_ranges = {"watermark": watermarkrange}
+    # add watermark
+    plot.extra_y_ranges = {"watermark": watermarkrange}
+    plot.extra_x_ranges = {"watermark": watermarkrange}
 
-#    plot.image_url([watermarkurl],1.8*max(thesecs),watermarky,
-#                   watermarkw,watermarkh,
-#                   global_alpha=watermarkalpha,
-#                   w_units='screen',
-#                   h_units='screen',
-#                   anchor=watermarkanchor,
-#                   dilate=True,
-#                   y_range_name = "watermark",
-#                   )
+    plot.image_url([watermarkurl],watermarkx,watermarky,
+                   watermarkw,watermarkh,
+                   global_alpha=watermarkalpha,
+                   w_units='screen',
+                   h_units='screen',
+                   anchor=watermarkanchor,
+                   dilate=True,
+                   x_range_name = "watermark",
+                   y_range_name = "watermark",
+                   )
 
-    plot.circle('date','power2k',source=source,fill_color='red',size=7,
+    plot.circle('date','power2k',source=source,fill_color='red',size=10,
                 legend='2k power')
 
-    plot.circle('date','power1hr',source=source,fill_color='blue',size=7,
+
+    plot.circle('date','power1hr',source=source,fill_color='blue',size=10,
                 legend='1 hr power')
 
-    plot.circle('date','power4min',source=source,fill_color='green',size=7,
+    plot.circle('date','power4min',source=source,fill_color='green',size=10,
                 legend='4 min power')
 
+    plot.line('date','power4min',source=source2,color='green')
+    plot.line('date','power2k',source=source2,color='red')
+    plot.line('date','power1hr',source=source2,color='blue')
+
     plot.xaxis.axis_label = 'Date'
     plot.yaxis.axis_label = 'Power (W)'
 
@@ -712,6 +754,7 @@ def fitnessmetric_chart(fitnessmetrics,user,workoutmode='rower'):
         ('Power 4 minutes','@power4min'),
         ('Power 2000 m','@power2k'),
         ('Power 1 hour','@power1hr'),
+        ('Date','@fdate'),
     ])
     
     script,div = components(plot)

rowers/tasks.py

@@ -743,26 +743,7 @@ def handle_updateergcp(rower_id,workoutfilenames,debug=False,**kwargs):
 
     return 1
 
-@app.task
-def handle_updatefitnessmetric(user_id,mode,workoutids,debug=False,
-                               **kwargs):
-
-    powerfourmin = -1
-    power2k = -1
-    powerhour = -1
-    
-    mdict = {
-        'user_id': user_id,
-        'PowerFourMin': powerfourmin,
-        'PowerTwoK': power2k,
-        'PowerOneHour': powerhour,
-        'workoutmode': mode,
-        'last_workout': max(workoutids),
-        'date': timezone.now().strftime('%Y-%m-%d'),
-             }
-
-    result = fitnessmetric_to_sql(mdict,debug=debug,doclean=False)
-
+def cp_from_workoutids(workoutids,debug=False):
     columns = ['power','workoutid','time']
     df = getsmallrowdata_db(columns,ids=workoutids,debug=debug)
     df.dropna(inplace=True,axis=0)
@@ -821,6 +802,30 @@ def handle_updatefitnessmetric(user_id,mode,workoutids,debug=False,
 
     power2k = fitfunc(p1,t3)
 
+    return powerfourmin,power2k,powerhour
+    
+
+@app.task
+def handle_updatefitnessmetric(user_id,mode,workoutids,debug=False,
+                               **kwargs):
+
+    powerfourmin = -1
+    power2k = -1
+    powerhour = -1
+    
+    mdict = {
+        'user_id': user_id,
+        'PowerFourMin': powerfourmin,
+        'PowerTwoK': power2k,
+        'PowerOneHour': powerhour,
+        'workoutmode': mode,
+        'last_workout': max(workoutids),
+        'date': timezone.now().strftime('%Y-%m-%d'),
+             }
+
+    result = fitnessmetric_to_sql(mdict,debug=debug,doclean=False)
+
+    powerfourmin,power2k,powerhour = cp_from_workoutids(workoutids,debug=debug)
     
     mdict = {
         'user_id': user_id,