From 1092101bfe95a41498596c9859ae3113948621eb Mon Sep 17 00:00:00 2001 From: Sander Roosendaal Date: Wed, 16 Dec 2020 08:39:58 +0100 Subject: [PATCH 1/2] fixing power cleaning --- rowers/dataprep.py | 6 ++++++ rowers/views/workoutviews.py | 2 ++ 2 files changed, 8 insertions(+) diff --git a/rowers/dataprep.py b/rowers/dataprep.py index 4094284d..e6708ae0 100644 --- a/rowers/dataprep.py +++ b/rowers/dataprep.py @@ -683,6 +683,12 @@ def clean_df_stats(datadf, workstrokesonly=True, ignorehr=True, except (KeyError,TypeError): pass + try: + mask = datadf['power'] > 5000 + datadf.mask(mask,inplace=True) + except (KeyError,TypeError): + pass + try: mask = datadf['spm'] > 120 datadf.mask(mask,inplace=True) diff --git a/rowers/views/workoutviews.py b/rowers/views/workoutviews.py index e113b27c..b54f9500 100644 --- a/rowers/views/workoutviews.py +++ b/rowers/views/workoutviews.py @@ -3430,11 +3430,13 @@ def workout_stats_view(request,id=0,message="",successmessage=""): # prepare data frame datadf,row = dataprep.getrowdata_db(id=encoder.decode_hex(id)) + print(datadf.power.mean(),'aap') datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly, ignoreadvanced=False) + print(datadf.power.mean(),'noot') if datadf.empty: datadf,row = dataprep.getrowdata_db(id=encoder.decode_hex(id)) From a20de1f5763c6109c100a37555398a3388643c1c Mon Sep 17 00:00:00 2001 From: Sander Roosendaal Date: Wed, 16 Dec 2020 08:40:24 +0100 Subject: [PATCH 2/2] removing debug code --- rowers/views/workoutviews.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/rowers/views/workoutviews.py b/rowers/views/workoutviews.py index b54f9500..7ed5b9a2 100644 --- a/rowers/views/workoutviews.py +++ b/rowers/views/workoutviews.py @@ -3430,13 +3430,12 @@ def workout_stats_view(request,id=0,message="",successmessage=""): # prepare data frame datadf,row = dataprep.getrowdata_db(id=encoder.decode_hex(id)) - print(datadf.power.mean(),'aap') + datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly, ignoreadvanced=False) - print(datadf.power.mean(),'noot') if datadf.empty: datadf,row = dataprep.getrowdata_db(id=encoder.decode_hex(id))