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updated OTW CP plot

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This commit is contained in:
Sander Roosendaal
2017-06-08 16:53:30 -07:00
parent 8a9576c55a
commit d4a9060c36
2 changed files with 27 additions and 21 deletions
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12
rowers/interactiveplots.py
View File

@@ -645,10 +645,14 @@ def interactive_otwcpchart(powerdf,promember=0):
# message = "CP model fit didn't give correct results"
deltas = fitt.apply(lambda x: timedeltaconv(x))
ftime = niceformat(deltas)
sourcecomplex = ColumnDataSource(
data = dict(
power = fitpower,
duration = fitt
CP = fitpower,
duration = fitt,
ftime = ftime
)
)
@@ -671,7 +675,7 @@ def interactive_otwcpchart(powerdf,promember=0):
y_range_name = "watermark",
)
plot.line('Delta','CP',source=source,color='red',line_width=5,
plot.circle('Delta','CP',source=source,fill_color='red',size=15,
legend='Power Data')
plot.xaxis.axis_label = "Duration (seconds)"
plot.yaxis.axis_label = "Power (W)"
@@ -689,7 +693,7 @@ def interactive_otwcpchart(powerdf,promember=0):
hover.mode = 'mouse'
plot.line('duration','power',source=sourcecomplex,legend="CP Model",
plot.line('duration','CP',source=sourcecomplex,legend="CP Model",
color='green')
script, div = components(plot)

36
rowers/views.py
View File

@@ -2903,9 +2903,9 @@ def otwrankings_view(request,theuser=0,
else:
maxt = 1000.
maxlog10 = np.log10(maxt)
logarr = np.arange(500)*maxlog10/500.
logarr = np.arange(100)*maxlog10/100.
logarr = [int(10.**(la)) for la in logarr]
logarr = pd.Series(logarr)
logarr.drop_duplicates(keep='first',inplace=True)
@@ -2920,8 +2920,9 @@ def otwrankings_view(request,theuser=0,
dfgrouped = df.groupby(['workoutid'])
for id,group in dfgrouped:
tt = group['time']
ww = group['power']
tt = group['time'].copy()
ww = group['power'].copy()
try:
avgpower[id] = int(ww.mean())
except ValueError:
@@ -2931,19 +2932,20 @@ def otwrankings_view(request,theuser=0,
dt = []
cpw = []
for i in range(length-2):
w_roll = ww.rolling(i+2,min_periods=2).mean()
# now goes with # data points - should be fixed seconds
indexmax = w_roll.idxmax(axis=1)
try:
t_0 = tt.ix[indexmax]
t_1 = tt.ix[indexmax-i-2]
deltat = 1.0e-3*(t_0-t_1)
wmax = w_roll.ix[indexmax]
if not np.isnan(deltat) and not np.isnan(wmax):
dt.append(deltat)
cpw.append(wmax)
except KeyError:
pass
w_roll = ww.rolling(i+2).mean().dropna()
if len(w_roll):
# now goes with # data points - should be fixed seconds
indexmax = w_roll.idxmax(axis=1)
try:
t_0 = tt.ix[indexmax]
t_1 = tt.ix[indexmax-i-2]
deltat = 1.0e-3*(t_0-t_1)
wmax = w_roll.ix[indexmax]
if not np.isnan(deltat) and not np.isnan(wmax):
dt.append(deltat)
cpw.append(wmax)
except KeyError:
pass
dt = pd.Series(dt)