106 lines
3.0 KiB
Python
106 lines
3.0 KiB
Python
from django.core.exceptions import PermissionDenied
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from rowers.models import C2WorldClassAgePerformance
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from rowers.utils import myqueue
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# The interactions with the Concept2 logbook API
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# All C2 related functions should be defined here
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# (There is still some stuff defined directly in views.py. Need to
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# move that here.)
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import datetime
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from requests import Request, Session
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import rowers.mytypes as mytypes
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from rowers.mytypes import otwtypes
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from rowers.rower_rules import is_workout_user, ispromember
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from iso8601 import ParseError
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import pandas as pd
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import numpy
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import json
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from scipy import optimize
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from json.decoder import JSONDecodeError
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from pytz.exceptions import UnknownTimeZoneError
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from rowers.utils import dologging
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import numpy as np
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from rowsandall_app.settings import (
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C2_CLIENT_ID, C2_REDIRECT_URI, C2_CLIENT_SECRET,
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)
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from rowers.tasks import (
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handle_c2_import_stroke_data, handle_c2_sync,
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)
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from rowers.upload_tasks import handle_c2_async_workout, handle_c2_getworkout
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import django_rq
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queue = django_rq.get_queue('default')
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queuelow = django_rq.get_queue('low')
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queuehigh = django_rq.get_queue('high')
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def getagegrouprecord(age, sex='male', weightcategory='hwt',
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distance=2000, duration=None, indf=pd.DataFrame()):
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if not indf.empty: # pragma: no cover
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if not duration:
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df = indf[indf['distance'] == distance]
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else:
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duration = 60*int(duration)
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df = indf[indf['duration'] == duration]
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else:
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if not duration:
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df = pd.DataFrame(
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list(
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C2WorldClassAgePerformance.objects.filter(
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distance=distance,
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sex=sex,
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weightcategory=weightcategory
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).values()
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)
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)
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else:
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duration = 60*int(duration)
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df = pd.DataFrame(
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list(
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C2WorldClassAgePerformance.objects.filter(
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duration=duration,
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sex=sex,
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weightcategory=weightcategory
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).values()
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)
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)
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if not df.empty:
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ages = df['age']
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powers = df['power']
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def fitfunc(pars, x):
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return np.abs(pars[0])*(1-x/max(120, pars[1]))-np.abs(
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pars[2])*np.exp(-x/np.abs(pars[3]))+np.abs(pars[4])*(np.sin(np.pi*x/max(50, pars[5])))
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def errfunc(pars, x, y):
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return fitfunc(pars, x)-y
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p0 = [700, 120, 700, 10, 100, 100]
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try:
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p1, success = optimize.leastsq(errfunc, p0[:],
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args=(ages, powers))
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except: # pragma: no cover
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p1 = p0
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success = 0
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if success:
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power = fitfunc(p1, float(age))
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power = 0.5*(np.abs(power)+power)
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else: # pragma: no cover
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power = 0
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else:
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power = 0
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return power
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