Export to MapMyFitness now works

rowers/underarmourstuff.py

@@ -9,6 +9,7 @@ import requests.auth
 import json
 from django.utils import timezone
 from datetime import datetime,timedelta
+import arrow
 import numpy as np
 from dateutil import parser
 import time
@@ -239,7 +240,11 @@ def createunderarmourworkoutdata(w):
     except:
         return 0
     
+    st = w.startdatetime.astimezone(pytz.timezone(w.timezone))
+    start_time = st.isoformat()
+
     averagehr = int(row.df[' HRCur (bpm)'].mean())
+    averagespm = int(row.df[' Cadence (stokes/min)'].mean()/2.)
     maxhr = int(row.df[' HRCur (bpm)'].max())
     duration = w.duration.hour*3600
     duration += w.duration.minute*60
@@ -253,31 +258,42 @@ def createunderarmourworkoutdata(w):
 
     # adding diff, trying to see if this is valid
     #t = row.df.ix[:,'TimeStamp (sec)'].values-10*row.df.ix[0,'TimeStamp (sec)']
-    t = row.df.ix[:,'TimeStamp (sec)'].values-row.df.ix[0,'TimeStamp (sec)']
-    t[0] = t[1]
+    t = row.df.ix[:,'TimeStamp (sec)'].values #-row.df.ix[0,'TimeStamp (sec)']
+
+    # t += arrow.get(st).timestamp
+    
+    # t[0] = t[1]
 
     d = row.df.ix[:,'cum_dist'].values
     d[0] = d[1]
-    t = t.astype(int)
+    t = t.astype(float)
+
+    
+
+    
     d = d.astype(int)
     spm = row.df[' Cadence (stokes/min)'].astype(int)
     spm[0] = spm[1]
     hr = row.df[' HRCur (bpm)'].astype(int)
-
+    speed = row.df[' AverageBoatSpeed (m/s)']
+    speed = speed.replace(np.inf,0)
+    
     haslatlon=1
     
     try:
-	lat = row.df[' latitude'].values
-	lon = row.df[' longitude'].values
+	lat = row.df[' latitude']
+	lon = row.df[' longitude']
         if not lat.std() and not lon.std():
             haslatlon = 0
     except KeyError:
 	haslatlon = 0
 
+        
+        
     # path data
     if haslatlon:
         locdata = [] 
-        for e in zip(t,lat,lon):
+        for e in zip(t,lat.values,lon.values):
             point = {
                      'lat':e[1],
                      'lng':e[2],
@@ -303,8 +319,6 @@ def createunderarmourworkoutdata(w):
     for e in zip(t,spm):
         spmdata.append([e[0],e[1]])
         
-    st = w.startdatetime.astimezone(pytz.timezone(w.timezone))
-    start_time = st.isoformat()
 
     timeseries = {
         "distance": distancedata,
@@ -312,22 +326,32 @@ def createunderarmourworkoutdata(w):
         "cadence": spmdata,
         }
 
-    aggregrates = {
+    
+    aggregates = {
         "elapsed_time_total": int(duration),
+        "active_time_total": int(duration),
         "distance_total": int(max(d)),
         "heartrate_avg": averagehr,
         "heart_rate_min": int(min(hr)),
         "heart_rate_max": int(max(hr)),
+        "speed_min": speed.min().astype(float),
+        "speed_max": speed.max().astype(float),
+        "speed_avg": speed.mean(),
+        "cadence_min": int(min(spm)/2.),
+        "cadence_max": int(max(spm)/2.),
+        "cadence_avg": averagespm,
         }
 
 
-#    if haslatlon:
-#        timeseries["position"] = locdata
+    if haslatlon:
+        timeseries["position"] = locdata
     
     data = {
-        "name": name,
 	"start_datetime": start_time,
+        "name": name,
+        "has_time_series": True,
         "time_series": timeseries,
+        "aggregates": aggregates,
         "start_locale_timezone": "Etc/UTC",
         "activity_type": "/v7.1/activity_type/128/",
         "notes": notes,