working on low level plannedsession

rowers/dataprep.py

@@ -36,7 +36,7 @@ from rowingdata import (
     summarydata, get_file_type,
 )
 
-from rowers.metrics import axes
+from rowers.metrics import axes,calc_trimp
 from async_messages import messages as a_messages
 import os
 import zipfile
@@ -2212,3 +2212,40 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
         conn.close()
         engine.dispose()
     return data
+
+def workout_trimp(workout):
+    r = workout.user
+    df,row = getrowdata_db(id=workout.id)
+    df = clean_df_stats(df)
+    if df.empty:
+        df,row = getrowdata_db(id=workout.id)
+        df = clean_df_stats(df,workstrokesonly=False)
+    trimp = calc_trimp(df,r.sex,r.max,r.rest)
+    trimp = int(trimp)
+
+    return trimp
+
+def workout_rscore(w):
+    r = workout.user
+    df,row = getrowdata_db(id=workout.id)
+    df = clean_df_stats(df)
+    if df.empty:
+        df,row = getrowdata_db(id=workout.id)
+        df = clean_df_stats(df,workstrokesonly=False)
+
+    duration = df['time'].max()-df['time'].min()
+    duration /= 1.0e3
+    pwr4 = df['power']**(4.0)
+    normp = (pwr4.mean())**(0.25)
+    if not np.isnan(normp):
+        ftp = float(r.ftp)
+        if w.workouttype in ('water','coastal'):
+            ftp = ftp*(100.-r.otwslack)/100.
+
+        intensityfactor = df['power'].mean()/float(ftp)
+        intensityfactor = normp/float(ftp)
+        tss = 100.*((duration*normp*intensityfactor)/(3600.*ftp))
+    else:
+        tss = 0
+
+    return tss