From 4550a4fe539fd32898c65544cdd7170d27dc51b5 Mon Sep 17 00:00:00 2001 From: Sander Roosendaal Date: Thu, 26 Nov 2020 09:20:14 +0100 Subject: [PATCH] fixing banister to scale with coggan --- rowers/dataprep.py | 1 - rowers/interactiveplots.py | 15 +++++++-------- 2 files changed, 7 insertions(+), 9 deletions(-) diff --git a/rowers/dataprep.py b/rowers/dataprep.py index 21cfc770..5e7caf0f 100644 --- a/rowers/dataprep.py +++ b/rowers/dataprep.py @@ -2252,7 +2252,6 @@ def getsmallrowdata_db(columns, ids=[], doclean=True,workstrokesonly=True,comput else: try: df = pd.read_parquet(csvfilenames[0],columns=columns) - for c in columns: except (OSError,ArrowInvalid): rowdata,row = getrowdata(id=ids[0]) if rowdata and len(rowdata.df): diff --git a/rowers/interactiveplots.py b/rowers/interactiveplots.py index 75746927..8ede6c38 100644 --- a/rowers/interactiveplots.py +++ b/rowers/interactiveplots.py @@ -1651,13 +1651,10 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None, weight = 0 for w in ws: weight += getattr(w,metricchoice) - if modelchoice == 'tsb': - fatigue = (1-lambda_a)*fatigue+weight*lambda_a - fitness = (1-lambda_c)*fitness+weight*lambda_c - else: - fatigue = fatigue*math.exp(-1./kfatigue) + weight - fitness = fitness*math.exp(-1./kfitness) + weight + fatigue = (1-lambda_a)*fatigue+weight*lambda_a + fitness = (1-lambda_c)*fitness+weight*lambda_c + fatigues.append(fatigue) fitnesses.append(fitness) dates.append(datetime.datetime.combine(date,datetime.datetime.min.time())) @@ -1739,22 +1736,24 @@ def fitnessfit_chart(workouts,user,workoutmode='water',startdate=None, fitlabel = 'PTE (fitness)' fatiguelabel = 'NTE (fatigue)' formlabel = 'Performance' + rightaxlabel = 'Banister PTE/NTE/Performance' else: fitlabel = 'CTL' fatiguelabel = 'ATL' formlabel = 'TSB' + rightaxlabel = 'Coggan CTL/ATL/TSB' plot.circle('date','testpower',source=source,fill_color='green',size=10, legend_label='{fitnesstest} min power'.format(fitnesstest=fitnesstest)) plot.xaxis.axis_label = 'Date' - plot.yaxis.axis_label = 'Power (W)' + plot.yaxis.axis_label = 'Test Power (Watt)' y2rangemin = df.loc[:,['fitness','fatigue','form']].min().min() y2rangemax = df.loc[:,['fitness','fatigue','form']].max().max() plot.extra_y_ranges["yax2"] = Range1d(start=y2rangemin,end=y2rangemax) - plot.add_layout(LinearAxis(y_range_name="yax2",axis_label="Score"),"right") + plot.add_layout(LinearAxis(y_range_name="yax2",axis_label=rightaxlabel),"right") plot.line('date','fitness',source=source,color='blue', legend_label=fitlabel,y_range_name="yax2")