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adding critical stroke rate chart

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This commit is contained in:
Sander Roosendaal
2025-02-04 20:00:44 +01:00
parent 8f7060ead8
commit 03f68aa72e
9 changed files with 364 additions and 76 deletions
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32
rowers/dataprep.py
View File

@@ -553,7 +553,10 @@ def setcp(workout, background=False, recurrance=True):
# check dts
tarr = datautils.getlogarr(4000)
if df['delta'][0] in tarr:
return(df, df['delta'], df['cp'])
try:
return(df, df['delta'], df['cp'], df['cr'])
except KeyError:
return(df, df['delta'], df['cp'], 0*df['cp'])
except Exception as e:
try:
os.remove(filename)
@@ -565,7 +568,7 @@ def setcp(workout, background=False, recurrance=True):
strokesdf = remove_nulls_pl(strokesdf)
if strokesdf.is_empty():
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
totaltime = strokesdf['time'].max()
maxt = totaltime/1000.
@@ -580,7 +583,7 @@ def setcp(workout, background=False, recurrance=True):
elif os.path.exists(csvfilename+'.gz'): # pragma: no cover
csvfile = csvfilename+'.gz'
else: # pragma: no cover
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
csvfile = os.path.abspath(csvfile)
with grpc.insecure_channel(
@@ -593,7 +596,7 @@ def setcp(workout, background=False, recurrance=True):
grpc.channel_ready_future(channel).result(timeout=10)
except grpc.FutureTimeoutError: # pragma: no cover
dologging('metrics.log','grpc channel time out in setcp')
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr':[]}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
stub = metrics_pb2_grpc.MetricsStub(channel)
req = metrics_pb2.CPRequest(filename = csvfile, filetype = "CSV", tarr = logarr)
@@ -602,16 +605,18 @@ def setcp(workout, background=False, recurrance=True):
response = stub.GetCP(req, timeout=60)
except Exception as e:
dologging('metrics.log', traceback.format_exc())
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
delta = pl.Series(np.array(response.delta))
cpvalues = pl.Series(np.array(response.power))
powermean = response.avgpower
spmvalues = pl.Series(np.array(response.spm))
try:
df = pl.DataFrame({
'delta': delta,
'cp': cpvalues,
'cr': spmvalues,
'id': workout.id,
})
@@ -620,7 +625,7 @@ def setcp(workout, background=False, recurrance=True):
except Exception as e:
dologging("metrics.log", "setcp: "+ str(e))
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
#df.to_parquet(filename, engine='fastparquet', compression='GZIP')
@@ -631,7 +636,7 @@ def setcp(workout, background=False, recurrance=True):
workout.goldmedalduration = goldmedalduration
workout.save()
return df, delta, cpvalues
return df, delta, cpvalues, spmvalues # pragma: no cover
@@ -772,7 +777,7 @@ def fetchcp_new(rower, workouts):
data = []
for workout in workouts:
df, delta, cpvalues = setcp(workout)
df, delta, cpvalues, cpvalues_spm = setcp(workout)
df = df.drop('id')
df = df.with_columns((pl.lit(str(workout))).alias("workout"))
df = df.with_columns((pl.lit(workout.url())).alias("url"))
@@ -780,7 +785,7 @@ def fetchcp_new(rower, workouts):
data.append(df)
if len(data) == 0:
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
if len(data) > 1:
df = pl.concat(data)
@@ -791,11 +796,16 @@ def fetchcp_new(rower, workouts):
pl.all().sort_by('cp').last(),
])
except (KeyError, ColumnNotFoundError): # pragma: no cover
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
df = df.filter(pl.col("cp")>20)
return df['delta'], df['cp'], 0, df['workout'], df['url']
try:
testje = df['cr']
except KeyError:
return df['delta'], df['cp'], 0*df['cp'], 0, df['workout'], df['url']
return df['delta'], df['cp'], df['cr'], 0, df['workout'], df['url']

5
rowers/datautils.py
View File

@@ -84,7 +84,10 @@ def cpfit(powerdf, fraclimit=0.0001, nmax=1000):
p1 = p0
thesecs = powerdf['Delta'].to_numpy()
theavpower = powerdf['CP'].to_numpy()
try:
theavpower = powerdf['CP'].to_numpy()
except: # pragma: no cover
theavpower = powerdf['CR'].to_numpy()
if len(thesecs) >= 4:

1
rowers/forms.py
View File

@@ -1299,6 +1299,7 @@ analysischoices = (
('stats', 'Statistics'),
('compare', 'Compare'),
('cp', 'CP chart'),
('cr', 'CR chart'),
)

69
rowers/interactiveplots.py
View File

@@ -1113,6 +1113,75 @@ def interactive_otwcpchart(powerdf, promember=0, rowername="", r=None,
return [script, div, p1, ratio, message]
def interactive_otwcrchart(powerdf, promember=0, rowername="", r=None,
cpfit='data',
title='', type='water'):
powerdf2 = powerdf.filter((pl.col("Delta") > 0) & (pl.col("CR") > 0))
# plot tools
if (promember == 1): # pragma: no cover
TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
else:
TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
x_axis_type = 'log'
deltas = powerdf2['Delta'].apply(lambda x: timedeltaconv(x))
powerdf2 = powerdf2.with_columns(
ftime = deltas.apply(lambda x: strfdelta(x)),
Deltaminutes = pl.col("Delta")/60.
)
# there is no Paul's law for OTW
thesecs = powerdf2['Delta']
theavpower = powerdf2['CR']
p1, fitt, fitpower, ratio = datautils.cpfit(powerdf2)
if cpfit == 'automatic' and r is not None:
if type == 'water':
p1 = [r.r0, r.r1, r.r2, r.r3]
ratio = r.cpratio
elif type == 'erg': # pragma: no cover
p1 = [r.er0, r.er1, r.er2, r.er3]
ratio = r.ecrratio
def fitfunc(pars, x):
return abs(pars[0])/(1+(x/abs(pars[2]))) + abs(pars[1])/(1+(x/abs(pars[3])))
fitpower = fitfunc(p1, fitt)
message = ""
# if len(fitpower[fitpower<0]) > 0:
# message = "CP model fit didn't give correct results"
deltas = fitt.apply(lambda x: timedeltaconv(x))
ftime = niceformat(deltas)
fit_data = pl.DataFrame(dict(
CR=fitpower,
CRmax=ratio*fitpower,
duration=fitt/60.,
ftime=ftime,
))
if not title:
title = "Critical StrokeRate for "+rowername
chart_dict = {
'data': powerdf2.to_dicts(),
'fitdata': fit_data.to_dicts(),
'title': title,
}
script, div = get_chart("/cr", chart_dict)
return [script, div, p1, ratio, message]
def interactive_agegroup_plot(df, distance=2000, duration=None,
sex='male', weightcategory='hwt'):

12
rowers/models.py
View File

@@ -1104,6 +1104,18 @@ class Rower(models.Model):
ep3 = models.FloatField(default=1.0, verbose_name="erg CP p4")
ecpratio = models.FloatField(default=1.0, verbose_name="erg CP fit ratio")
r0 = models.FloatField(default=1.0, verbose_name="CR r1")
r1 = models.FloatField(default=1.0, verbose_name="CR r2")
r2 = models.FloatField(default=1.0, verbose_name="CR r3")
r3 = models.FloatField(default=1.0, verbose_name="CR r4")
crratio = models.FloatField(default=1.0, verbose_name="CR fit ratio")
er0 = models.FloatField(default=1.0, verbose_name="erg CR r1")
er1 = models.FloatField(default=1.0, verbose_name="erg CR r2")
er2 = models.FloatField(default=1.0, verbose_name="erg CR r3")
er3 = models.FloatField(default=1.0, verbose_name="erg CR r4")
ecpratio = models.FloatField(default=1.0, verbose_name="erg CP fit ratio")
cprange = models.IntegerField(default=42, verbose_name="Range for calculation of breakthrough workouts and fitness (CP)",
choices=cppresets)

8
rowers/rowing_workout_metrics_pb2.py
View File

@@ -24,7 +24,7 @@ _sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1crowing-workout-metrics.proto\x12\x16rowing_workout_metrics\"\x80\x01\n\x15WorkoutMetricsRequest\x12\x10\n\x08\x66ilename\x18\x01 \x01(\t\x12\x0b\n\x03sex\x18\x02 \x01(\t\x12\x0b\n\x03\x66tp\x18\x03 \x01(\x01\x12\r\n\x05hrftp\x18\x04 \x01(\x01\x12\r\n\x05hrmax\x18\x05 \x01(\x01\x12\r\n\x05hrmin\x18\x06 \x01(\x01\x12\x0e\n\x06wpsavg\x18\x07 \x01(\x01\"\x80\x01\n\x16WorkoutMetricsResponse\x12\x0b\n\x03tss\x18\x01 \x01(\x01\x12\r\n\x05normp\x18\x02 \x01(\x01\x12\r\n\x05trimp\x18\x03 \x01(\x01\x12\r\n\x05hrtss\x18\x04 \x01(\x01\x12\r\n\x05normv\x18\x05 \x01(\x01\x12\r\n\x05normw\x18\x06 \x01(\x01\x12\x0e\n\x06spmtss\x18\x07 \x01(\x01\"=\n\tCPRequest\x12\x10\n\x08\x66ilename\x18\x01 \x01(\t\x12\x10\n\x08\x66iletype\x18\x02 \x01(\t\x12\x0c\n\x04tarr\x18\x03 \x03(\x01\"<\n\nCPResponse\x12\r\n\x05\x64\x65lta\x18\x01 \x03(\x01\x12\r\n\x05power\x18\x02 \x03(\x01\x12\x10\n\x08\x61vgpower\x18\x03 \x01(\x01\x32\xc7\x01\n\x07Metrics\x12l\n\x0b\x43\x61lcMetrics\x12-.rowing_workout_metrics.WorkoutMetricsRequest\x1a..rowing_workout_metrics.WorkoutMetricsResponse\x12N\n\x05GetCP\x12!.rowing_workout_metrics.CPRequest\x1a\".rowing_workout_metrics.CPResponseB\x1aZ\x18./rowing-workout-metricsb\x06proto3')
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x1crowing-workout-metrics.proto\x12\x16rowing_workout_metrics\"\x80\x01\n\x15WorkoutMetricsRequest\x12\x10\n\x08\x66ilename\x18\x01 \x01(\t\x12\x0b\n\x03sex\x18\x02 \x01(\t\x12\x0b\n\x03\x66tp\x18\x03 \x01(\x01\x12\r\n\x05hrftp\x18\x04 \x01(\x01\x12\r\n\x05hrmax\x18\x05 \x01(\x01\x12\r\n\x05hrmin\x18\x06 \x01(\x01\x12\x0e\n\x06wpsavg\x18\x07 \x01(\x01\"\x80\x01\n\x16WorkoutMetricsResponse\x12\x0b\n\x03tss\x18\x01 \x01(\x01\x12\r\n\x05normp\x18\x02 \x01(\x01\x12\r\n\x05trimp\x18\x03 \x01(\x01\x12\r\n\x05hrtss\x18\x04 \x01(\x01\x12\r\n\x05normv\x18\x05 \x01(\x01\x12\r\n\x05normw\x18\x06 \x01(\x01\x12\x0e\n\x06spmtss\x18\x07 \x01(\x01\"=\n\tCPRequest\x12\x10\n\x08\x66ilename\x18\x01 \x01(\t\x12\x10\n\x08\x66iletype\x18\x02 \x01(\t\x12\x0c\n\x04tarr\x18\x03 \x03(\x01\"I\n\nCPResponse\x12\r\n\x05\x64\x65lta\x18\x01 \x03(\x01\x12\r\n\x05power\x18\x02 \x03(\x01\x12\x10\n\x08\x61vgpower\x18\x03 \x01(\x01\x12\x0b\n\x03spm\x18\x04 \x03(\x01\x32\xc7\x01\n\x07Metrics\x12l\n\x0b\x43\x61lcMetrics\x12-.rowing_workout_metrics.WorkoutMetricsRequest\x1a..rowing_workout_metrics.WorkoutMetricsResponse\x12N\n\x05GetCP\x12!.rowing_workout_metrics.CPRequest\x1a\".rowing_workout_metrics.CPResponseB\x1aZ\x18./rowing-workout-metricsb\x06proto3')
_globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@@ -39,7 +39,7 @@ if not _descriptor._USE_C_DESCRIPTORS:
_globals['_CPREQUEST']._serialized_start=318
_globals['_CPREQUEST']._serialized_end=379
_globals['_CPRESPONSE']._serialized_start=381
_globals['_CPRESPONSE']._serialized_end=441
_globals['_METRICS']._serialized_start=444
_globals['_METRICS']._serialized_end=643
_globals['_CPRESPONSE']._serialized_end=454
_globals['_METRICS']._serialized_start=457
_globals['_METRICS']._serialized_end=656
# @@protoc_insertion_point(module_scope)

20
rowers/templates/otwcr.html Normal file
View File

@@ -0,0 +1,20 @@
{{ the_div|safe }}
<p>
<table width="100%" class="listtable">
<thead>
<tr>
<th> Duration</th>
<th> Stroke Estimate 1</th>
<th> Stroke Estimate 2</th>
<tr>
</thead>
<tbody>
<tr>
<td>{{ duration }}</td>
<td>{{ power }}</td>
<td>{{ upper }}</td>
</tr>
</tbody>
</table>
</p>

154
rowers/templates/user_analysis_select.html
View File

@@ -124,13 +124,13 @@
<script>
// script for chart options form
$(function() {
// Get the form fields and hidden div
var functionfield = $("#id_function");
var plotfield = $("#id_plotfield").parent().parent();
var x_param = $("#id_xparam").parent().parent();
var y_param = $("#id_yparam").parent().parent();
var groupby = $("#id_groupby").parent().parent();
var binsize = $("#id_binsize").parent().parent();
var errorbars = $("#id_ploterrorbars").parent().parent();
@@ -139,17 +139,18 @@
var spmmax = $("#id_spmmax").parent().parent();
var workmin = $("#id_workmin").parent().parent();
var workmax = $("#id_workmax").parent().parent();
var xaxis = $("#id_xaxis").parent().parent();
var yaxis1 = $("#id_yaxis1").parent().parent();
var yaxis2 = $("#id_yaxis2").parent().parent();
var plottype = $("#id_plottype").parent().parent();
var reststrokes = $("#id_includereststrokes").parent().parent();
var trendline = $("#id_trendline").parent().parent();
var piece = $("#id_piece").parent().parent();
var cpfit = $("#id_cpfit").parent().parent();
var cpoverlay = $("#id_cpoverlay").parent().parent();
var reststrokes = $("#id_includereststrokes").parent().parent();
var trendline = $("#id_trendline").parent().parent();
var piece = $("#id_piece").parent().parent();
var cpfit = $("#id_cpfit").parent().parent();
var crfit = $("#id_crfit").parent().parent();
var cpoverlay = $("#id_cpoverlay").parent().parent();
// Hide the fields.
@@ -166,15 +167,15 @@
yaxis1.hide();
yaxis2.hide();
plottype.hide();
// reststrokes.hide();
workmin.hide();
workmax.hide();
spmmin.hide();
spmmax.hide();
cpfit.hide();
cpoverlay.hide();
piece.hide();
trendline.hide();
// reststrokes.hide();
workmin.hide();
workmax.hide();
spmmin.hide();
spmmax.hide();
cpfit.hide();
cpoverlay.hide();
piece.hide();
trendline.hide();
if (functionfield.val() == 'boxplot') {
plotfield.show();
@@ -214,11 +215,16 @@
reststrokes.show();
}
if (functionfield.val() == 'cp') {
cpfit.show();
piece.show();
cpoverlay.show();
}
if (functionfield.val() == 'cp') {
cpfit.show();
piece.show();
cpoverlay.show();
}
if (functionfield.val() == 'cr') {
crfit.show();
piece.show();
}
// Setup an event listener for when the state of the
@@ -241,15 +247,16 @@
palette.hide();
binsize.hide();
errorbars.hide();
trendline.hide();
trendline.hide();
xaxis.hide();
yaxis1.hide();
yaxis2.hide();
plottype.hide();
reststrokes.show();
cpfit.hide();
cpoverlay.hide();
piece.hide();
reststrokes.show();
cpfit.hide();
crfit.hide();
cpoverlay.hide();
piece.hide();
}
else if (Value=='histo') {
plotfield.show();
@@ -262,16 +269,17 @@
groupby.hide();
palette.hide();
binsize.hide();
trendline.hide();
trendline.hide();
errorbars.hide();
xaxis.hide();
yaxis1.hide();
yaxis2.hide();
plottype.hide();
reststrokes.show();
cpfit.hide();
cpoverlay.hide();
piece.hide();
reststrokes.show();
cpfit.hide();
crfit.hide();
cpoverlay.hide();
piece.hide();
}
else if (Value=='trendflex') {
@@ -284,17 +292,18 @@
spmmin.show();
spmmax.show();
workmin.show();
trendline.hide();
trendline.hide();
workmax.show();
plotfield.hide();
xaxis.hide();
yaxis1.hide();
yaxis2.hide();
plottype.hide();
reststrokes.show();
cpfit.hide();
cpoverlay.hide();
piece.hide();
reststrokes.show();
cpfit.hide();
crfit.hide();
cpoverlay.hide();
piece.hide();
}
else if (Value=='flexall') {
@@ -305,7 +314,7 @@
y_param.hide();
groupby.hide();
spmmin.hide();
trendline.show();
trendline.show();
spmmax.hide();
workmin.hide();
workmax.hide();
@@ -314,10 +323,11 @@
binsize.hide();
plottype.hide();
errorbars.hide();
reststrokes.show();
cpfit.hide();
cpoverlay.hide();
piece.hide();
reststrokes.show();
cpfit.hide();
crfit.hide();
cpoverlay.hide();
piece.hide();
}
else if (Value=='stats') {
xaxis.hide();
@@ -331,11 +341,12 @@
binsize.hide();
errorbars.hide();
plottype.hide();
trendline.hide();
reststrokes.show();
cpfit.hide();
cpoverlay.hide();
piece.hide();
trendline.hide();
reststrokes.show();
cpfit.hide();
crfit.hide();
cpoverlay.hide();
piece.hide();
}
else if (Value=='compare') {
xaxis.show();
@@ -350,18 +361,19 @@
workmax.hide();
plotfield.hide();
palette.hide();
trendline.hide();
trendline.hide();
binsize.hide();
plottype.show();
errorbars.hide();
piece.hide();
cpfit.hide();
cpoverlay.hide();
reststrokes.show();
piece.hide();
cpfit.hide();
crfit.hide();
cpoverlay.hide();
reststrokes.show();
}
else if (Value=='cp') {
else if (Value=='cp') {
plotfield.hide();
spmmin.hide();
spmmax.hide();
@@ -369,7 +381,7 @@
workmax.hide();
x_param.hide();
y_param.hide();
trendline.hide();
trendline.hide();
groupby.hide();
palette.hide();
binsize.hide();
@@ -378,10 +390,34 @@
yaxis1.hide();
yaxis2.hide();
plottype.hide();
reststrokes.hide();
cpfit.show();
cpoverlay.hide();
piece.show();
reststrokes.hide();
cpfit.show();
crfit.hide();
cpoverlay.hide();
piece.show();
}
else if (Value=='cr') {
plotfield.hide();
spmmin.hide();
spmmax.hide();
workmin.hide();
workmax.hide();
x_param.hide();
y_param.hide();
trendline.hide();
groupby.hide();
palette.hide();
binsize.hide();
errorbars.hide();
xaxis.hide();
yaxis1.hide();
yaxis2.hide();
plottype.hide();
reststrokes.hide();
cpfit.hide();
crfit.show();
cpoverlay.hide();
piece.show();
}
});
});

139
rowers/views/analysisviews.py
View File

@@ -294,6 +294,8 @@ def analysis_new(request,
df = comparisondata(tw, options)
elif function == 'cp': # pragma: no cover
df = cpdata(tw, options)
elif function == 'cr': # pragma: no cover
df = crdata(tw, options)
options['savedata'] = False
request.session['options'] = options
try:
@@ -661,7 +663,7 @@ def cpdata(workouts, options):
r = u.rower
delta, cpvalue, avgpower, workoutnames, urls = dataprep.fetchcp_new(
delta, cpvalue, crvalue, avgpower, workoutnames, urls = dataprep.fetchcp_new(
r, workouts)
powerdf = pl.DataFrame({
@@ -811,6 +813,139 @@ def cpdata(workouts, options):
return (script, html_content)
def crdata(workouts, options):
start = timezone.now()
userid = options['userid']
cpfit = options['cpfit']
cpoverlay = options['cpoverlay']
u = User.objects.get(id=userid)
r = u.rower
delta, cpvalue, crvalue, avgpower, workoutnames, urls = dataprep.fetchcp_new(
r, workouts)
powerdf = pl.DataFrame({
'Delta': delta,
'CR': crvalue,
'workout': workoutnames,
'url': urls,
})
savedata = options.get('savedata',False)
if savedata: # pragma: no cover
return powerdf.to_pandas()
if powerdf.is_empty(): # pragma: no cover
return('', '<p>No valid data found</p>')
powerdf = powerdf.lazy().filter(pl.col("CR")>0)
powerdf = powerdf.sort(["Delta", "CR"], descending=[False, True])
powerdf = powerdf.unique(subset="Delta", keep="first")
powerdf = powerdf.fill_nan(None).drop_nulls()
powerdf = powerdf.collect()
rowername = r.user.first_name+" "+r.user.last_name
wcdurations = []
wcpower = []
if len(powerdf) != 0:
datefirst = pd.Series(w.date for w in workouts).min()
datelast = pd.Series(w.date for w in workouts).max()
title = 'Critical Stroke Rate chart for {name}, from {d1} to {d2}'.format(
name=rowername,
d1=datefirst,
d2=datelast,
)
wtype = 'water'
if workouts[0].workouttype in mytypes.otetypes: # pragma: no cover
wtype = 'erg'
if workouts[0].workouttype == 'bikeerg': # pragma: no cover
# for Mike
wtype = 'erg'
res = interactive_otwcrchart(powerdf, promember=True, rowername=rowername, r=r,
cpfit=cpfit, title=title, type=wtype,)
script = res[0]
div = res[1]
p1 = res[2]
ratio = res[3]
else: # pragma: no cover
script = ''
div = '<p>No ranking pieces found.</p>'
p1 = [1, 1, 1, 1]
ratio = 1
minutes = options['piece']
if minutes != 0:
# minutes = 77
try:
hourvalue, tvalue = divmod(minutes, 60)
except: # pragma: no cover
hourvalue = 0
tvalue = minutes
# hourvalue = 1, tvalue = 17
try:
hourvalue = int(hourvalue)
except TypeError: # pragma: no cover
hourvalue = 0
try:
minutevalue = int(tvalue)
except TypeError: # pragma: no cover
minutevalue = 0
tvalue = int(60*(tvalue-minutevalue))
if hourvalue >= 24: # pragma: no cover
hourvalue = 23
pieceduration = datetime.time(
minute=minutevalue,
hour=hourvalue,
second=tvalue,
)
pieceseconds = 3600.*pieceduration.hour+60. * \
pieceduration.minute+pieceduration.second
# CP model
pwr = p1[0]/(1+pieceseconds/p1[2])
pwr += p1[1]/(1+pieceseconds/p1[3])
if pwr <= 0: # pragma: no cover
pwr = 50.
if not np.isnan(pwr):
try:
pwr2 = pwr*ratio
except: # pragma: no cover
pwr2 = pwr
duration = timedeltaconv(pieceseconds)
power = int(pwr)
upper = int(pwr2)
else: # pragma: no cover
duration = timedeltaconv(0)
power = 0
upper = 0
htmly = env.get_template('otwcr.html')
html_content = htmly.render({
'script': script,
'the_div': div,
'duration': duration,
'power': power,
'upper': upper,
})
return (script, html_content)
def statsdata(workouts, options):
#try:
@@ -1063,6 +1198,8 @@ def analysis_view_data(request, userid=0):
script, div = comparisondata(workouts, options)
elif function == 'cp': # pragma: no cover
script, div = cpdata(workouts, options)
elif function == 'cr': # pragma: no cover
script, div = crdata(workouts, options)
else: # pragma: no cover
script = ''
div = 'Unknown analysis functions'