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flex chart work per stroke slider

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This commit is contained in:
Sander Roosendaal
2017-03-02 14:53:18 +01:00
parent 8134d76a07
commit 992224731f
2 changed files with 86 additions and 32 deletions
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20
rowers/dataprep.py
View File

@@ -102,6 +102,11 @@ def clean_df_stats(datadf,workstrokesonly=True,ignorehr=True,
except KeyError:
pass
try:
datadf['hr'] = datadf['hr']+10
except KeyError:
pass
datadf=datadf.clip(lower=0)
datadf.replace(to_replace=0,value=np.nan,inplace=True)
@@ -116,6 +121,11 @@ def clean_df_stats(datadf,workstrokesonly=True,ignorehr=True,
except KeyError:
pass
try:
datadf['hr'] = datadf['hr']-10
except KeyError:
pass
# clean data for useful ranges per column
if not ignorehr:
try:
@@ -222,11 +232,11 @@ def clean_df_stats(datadf,workstrokesonly=True,ignorehr=True,
pass
try:
mask = datadf['catch'] > -30.
datadf.loc[mask,'catch'] = np.nan
except KeyError:
pass
try:
mask = datadf['catch'] > -30.
datadf.loc[mask,'catch'] = np.nan
except KeyError:
pass
workoutstateswork = [1,4,5,8,9,6,7]

98
rowers/interactiveplots.py
View File

@@ -139,9 +139,10 @@ def interactive_forcecurve(theworkouts,workstrokesonly=False):
columns = ['catch','slip','wash','finish','averageforce',
'peakforceangle','peakforce','spm','distance',
'workoutstate']
'workoutstate','driveenergy']
rowdata = dataprep.getsmallrowdata_db(columns,ids=ids)
rowdata.dropna(axis=1,how='all',inplace=True)
rowdata.dropna(axis=0,how='any',inplace=True)
workoutstateswork = [1,4,5,8,9,6,7]
@@ -278,6 +279,7 @@ def interactive_forcecurve(theworkouts,workstrokesonly=False):
var y = data['y']
var spm1 = data2['spm']
var distance1 = data2['distance']
var driveenergy1 = data2['driveenergy']
var thresholdforce = y[1]
@@ -293,6 +295,8 @@ def interactive_forcecurve(theworkouts,workstrokesonly=False):
var maxspm = maxspm.value
var mindist = mindist.value
var maxdist = maxdist.value
var minwork = minwork.value
var maxwork = maxwork.value
var catchav = 0
var finishav = 0
@@ -307,14 +311,16 @@ def interactive_forcecurve(theworkouts,workstrokesonly=False):
for (i=0; i<c.length; i++) {
if (spm1[i]>=minspm && spm1[i]<=maxspm) {
if (distance1[i]>=mindist && distance1[i]<=maxdist) {
catchav += c[i]
finishav += finish[i]
slipav += slip[i]
washav += wash[i]
peakforceangleav += peakforceangle[i]
averageforceav += averageforce[i]
peakforceav += peakforce[i]
count += 1
if (driveenergy1[i]>=minwork && driveenergy1[i]<=maxwork) {
catchav += c[i]
finishav += finish[i]
slipav += slip[i]
washav += wash[i]
peakforceangleav += peakforceangle[i]
averageforceav += averageforce[i]
peakforceav += peakforce[i]
count += 1
}
}
}
}
@@ -351,6 +357,15 @@ def interactive_forcecurve(theworkouts,workstrokesonly=False):
title="Max SPM",callback=callback)
callback.args["maxspm"] = slider_spm_max
slider_work_min = Slider(start=0, end=1500,value=0, step=10,
title="Min Work per Stroke",callback=callback)
callback.args["minwork"] = slider_work_min
slider_work_max = Slider(start=0, end=1500,value=1500, step=10,
title="Max Work per Stroke",callback=callback)
callback.args["maxwork"] = slider_work_max
distmax = 100+100*int(rowdata['distance'].max()/100.)
slider_dist_min = Slider(start=0,end=distmax,value=0,step=1,
@@ -363,9 +378,11 @@ def interactive_forcecurve(theworkouts,workstrokesonly=False):
callback.args["maxdist"] = slider_dist_max
layout = layoutrow([layoutcolumn([slider_spm_min,
slider_spm_max,
slider_dist_min,
slider_dist_max,
slider_spm_max,
slider_dist_min,
slider_dist_max,
slider_work_min,
slider_work_max,
],
),
plot])
@@ -897,7 +914,8 @@ def interactive_cum_flex_chart2(theworkouts,promember=0,
# datadf = dataprep.smalldataprep(theworkouts,xparam,yparam1,yparam2)
ids = [int(w.id) for w in theworkouts]
datadf = dataprep.getsmallrowdata_db([xparam,yparam1,yparam2],ids=ids,doclean=False)
columns = [xparam,yparam1,yparam2,'spm','driveenergy','distance']
datadf = dataprep.getsmallrowdata_db(columns,ids=ids,doclean=False)
yparamname1 = axlabels[yparam1]
if yparam2 != 'None':
@@ -1053,6 +1071,7 @@ def interactive_cum_flex_chart2(theworkouts,promember=0,
var y2 = data['y2']
var spm1 = data['spm']
var distance1 = data['distance']
var driveenergy1 = data['driveenergy']
var xname = data['xname'][0]
var yname1 = data['yname1'][0]
var yname2 = data['yname2'][0]
@@ -1061,6 +1080,8 @@ def interactive_cum_flex_chart2(theworkouts,promember=0,
var maxspm = maxspm.value
var mindist = mindist.value
var maxdist = maxdist.value
var minwork = minwork.value
var maxwork = maxwork.value
var xm = 0
var ym1 = 0
var ym2 = 0
@@ -1080,16 +1101,17 @@ def interactive_cum_flex_chart2(theworkouts,promember=0,
for (i=0; i<x1.length; i++) {
if (spm1[i]>=minspm && spm1[i]<=maxspm) {
if (distance1[i]>=mindist && distance1[i]<=maxdist) {
data2['x1'].push(x1[i])
data2['y1'].push(y1[i])
data2['y2'].push(y2[i])
data2['spm'].push(spm1[i])
data2['distance'].push(distance1[i])
xm += x1[i]
ym1 += y1[i]
ym2 += y2[i]
if (driveenergy1[i]>=minwork && driveenergy1[i]<=maxwork) {
data2['x1'].push(x1[i])
data2['y1'].push(y1[i])
data2['y2'].push(y2[i])
data2['spm'].push(spm1[i])
data2['distance'].push(distance1[i])
xm += x1[i]
ym1 += y1[i]
ym2 += y2[i]
}
}
}
}
@@ -1120,6 +1142,15 @@ def interactive_cum_flex_chart2(theworkouts,promember=0,
title="Max SPM",callback=callback)
callback.args["maxspm"] = slider_spm_max
slider_work_min = Slider(start=0.0, end=1500,value=0.0, step=10,
title="Min Work per Stroke",callback=callback)
callback.args["minwork"] = slider_work_min
slider_work_max = Slider(start=0.0, end=1500,value=1500.0, step=10,
title="Max Work per Stroke",callback=callback)
callback.args["maxwork"] = slider_work_max
distmax = 100+100*int(datadf['distance'].max()/100.)
slider_dist_min = Slider(start=0,end=distmax,value=0,step=1,
@@ -1132,9 +1163,11 @@ def interactive_cum_flex_chart2(theworkouts,promember=0,
callback.args["maxdist"] = slider_dist_max
layout = layoutrow([layoutcolumn([slider_spm_min,
slider_spm_max,
slider_dist_min,
slider_dist_max,
slider_spm_max,
slider_dist_min,
slider_dist_max,
slider_work_min,
slider_work_max,
],
),
plot])
@@ -1166,7 +1199,9 @@ def interactive_flex_chart2(id=0,promember=0,
'time','pace','workoutstate']
rowdata = dataprep.getsmallrowdata_db(columns,ids=[id],doclean=True)
rowdata.dropna(axis=1,how='all',inplace=True)
rowdata.dropna(axis=0,how='any',inplace=True)
row = Workout.objects.get(id=id)
if rowdata.empty:
@@ -1492,12 +1527,12 @@ def interactive_flex_chart2(id=0,promember=0,
title="Max SPM",callback=callback)
callback.args["maxspm"] = slider_spm_max
slider_work_min = Slider(start=0.0, end=1000,value=0.0, step=10,
slider_work_min = Slider(start=0.0, end=1500,value=0.0, step=10,
title="Min Work per Stroke",callback=callback)
callback.args["minwork"] = slider_work_min
slider_work_max = Slider(start=0.0, end=1000,value=1000.0, step=10,
slider_work_max = Slider(start=0.0, end=1500,value=1500.0, step=10,
title="Max Work per Stroke",callback=callback)
callback.args["maxwork"] = slider_work_max
@@ -1532,7 +1567,9 @@ def interactive_flex_chart2(id=0,promember=0,
def interactive_bar_chart(id=0,promember=0):
# check if valid ID exists (workout exists)
rowdata,row = dataprep.getrowdata_db(id=id)
rowdata.dropna(axis=1,how='all',inplace=True)
rowdata.dropna(axis=0,how='any',inplace=True)
if rowdata.empty:
return "","No Valid Data Available"
@@ -1630,7 +1667,9 @@ def interactive_multiple_compare_chart(ids,xparam,yparam,plottype='line',
'workoutid']
datadf = dataprep.getsmallrowdata_db(columns,ids=ids)
datadf.dropna(axis=1,how='all',inplace=True)
datadf.dropna(axis=0,how='any',inplace=True)
tseconds = datadf.ix[:,'time']
yparamname = axlabels[yparam]
@@ -1792,8 +1831,11 @@ def interactive_comparison_chart(id1=0,id2=0,xparam='distance',yparam='spm',
rowdata1[n].fillna(value=0,inplace=True)
rowdata2[n].fillna(value=0,inplace=True)
rowdata1.dropna(axis=1,how='all',inplace=True)
rowdata1.dropna(axis=0,how='any',inplace=True)
rowdata2.dropna(axis=1,how='all',inplace=True)
rowdata2.dropna(axis=0,how='any',inplace=True)
row1 = Workout.objects.get(id=id1)
row2 = Workout.objects.get(id=id2)
@@ -1963,7 +2005,9 @@ def interactive_comparison_chart(id1=0,id2=0,xparam='distance',yparam='spm',
def interactive_otw_advanced_pace_chart(id=0,promember=0):
# check if valid ID exists (workout exists)
rowdata,row = dataprep.getrowdata_db(id=id)
rowdata.dropna(axis=1,how='all',inplace=True)
rowdata.dropna(axis=0,how='any',inplace=True)
if rowdata.empty:
return "","No Valid Data Available"