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adding automatic cp calculation for ote

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This commit is contained in:
Sander Roosendaal
2020-10-01 08:51:37 +02:00
parent 287d2da73f
commit 52725cb593
2 changed files with 36 additions and 13 deletions
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14
rowers/dataprep.py
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@@ -96,7 +96,7 @@ queuelow = django_rq.get_queue('low')
queuehigh = django_rq.get_queue('default') queuehigh = django_rq.get_queue('default')
from rowsandall_app.settings import SITE_URL from rowsandall_app.settings import SITE_URL
from rowers.mytypes import otwtypes,otetypes from rowers.mytypes import otwtypes,otetypes,rowtypes
from rowers import mytypes from rowers import mytypes
from rowers.database import * from rowers.database import *
@@ -1434,7 +1434,7 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
isbreakthrough = False isbreakthrough = False
ishard = False ishard = False
if workouttype == 'water': if workouttype in rowtypes:
df = getsmallrowdata_db(['power', 'workoutid', 'time'], ids=[w.id]) df = getsmallrowdata_db(['power', 'workoutid', 'time'], ids=[w.id])
try: try:
powermean = df['power'].mean() powermean = df['power'].mean()
@@ -1451,14 +1451,18 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
filename = 'media/cpdata_{id}.parquet.gz'.format(id=w.id) filename = 'media/cpdata_{id}.parquet.gz'.format(id=w.id)
df.to_parquet(filename,engine='fastparquet',compression='GZIP') df.to_parquet(filename,engine='fastparquet',compression='GZIP')
res, btvalues, res2 = utils.isbreakthrough( if workouttype in otwtypes:
delta, cpvalues, r.p0, r.p1, r.p2, r.p3, r.cpratio) res, btvalues, res2 = utils.isbreakthrough(
delta, cpvalues, r.p0, r.p1, r.p2, r.p3, r.cpratio)
elif workouttype in otetypes:
res, btvalues, res2 = utils.isbreakthrough(
delta, cpvalues, r.ep0, r.ep1, r.ep2, r.ep3, r.ecpratio)
else: else:
res = 0 res = 0
res2 = 0 res2 = 0
if res: if res:
isbreakthrough = True isbreakthrough = True
res = datautils.updatecp(delta, cpvalues, r) res = datautils.updatecp(delta, cpvalues, r,workouttype=workouttype)
if res2 and not isbreakthrough: if res2 and not isbreakthrough:
ishard = True ishard = True

35
rowers/datautils.py
View File

@@ -8,12 +8,24 @@ import numpy as np
from scipy.interpolate import griddata from scipy.interpolate import griddata
from scipy import optimize from scipy import optimize
from rowers.mytypes import otwtypes,otetypes,rowtypes
#p0 = [500,350,10,8000] #p0 = [500,350,10,8000]
p0 = [190,200,33,16000] p0 = [190,200,33,16000]
def updatecp(delta,cpvalues,r): def updatecp(delta,cpvalues,r,workouttype='water'):
cp2 = r.p0/(1+delta/r.p2) if workouttype in otwtypes:
cp2 += r.p1/(1+delta/r.p3) p0 = r.p0
p1 = r.p1
p2 = r.p2
p3 = r.p3
else:
p0 = r.ep0
p1 = r.ep1
p2 = r.ep2
p3 = r.ep3
cp2 = p0/(1+delta/p2)
cp2 += p1/(1+delta/p3)
delta = delta.append(delta) delta = delta.append(delta)
cp = cpvalues.append(cp2) cp = cpvalues.append(cp2)
@@ -31,11 +43,18 @@ def updatecp(delta,cpvalues,r):
res = cpfit(powerdf) res = cpfit(powerdf)
p1 = res[0] p1 = res[0]
r.p0 = p1[0] if workouttype in otwtypes:
r.p1 = p1[1] r.p0 = p1[0]
r.p2 = p1[2] r.p1 = p1[1]
r.p3 = p1[3] r.p2 = p1[2]
r.cpratio = res[3] r.p3 = p1[3]
r.cpratio = res[3]
else:
r.ep0 = p1[0]
r.ep1 = p1[1]
r.ep2 = p1[2]
r.ep3 = p1[3]
r.ecpratio = res[3]
r.save() r.save()