443 lines
11 KiB
Python
443 lines
11 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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from __future__ import absolute_import
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from rowers.utils import lbstoN
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import numpy as np
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from rowers.models import C2WorldClassAgePerformance
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import pandas as pd
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from scipy import optimize
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from django.utils import timezone
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nometrics = [
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'originalvelo',
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'cumdist',
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'strokes_slsh_min',
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' WorkPerStroke (joules)',
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' activityIdx',
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' lapIdx',
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# ' pointIdx',
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' WorkoutType',
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' IntervalType',
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' WorkoutState',
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' RowingState',
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' WorkoutDurationType',
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' WorkoutIntervalCount',
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'ergpace',
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'ref',
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'id',
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'deltat',
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'workoutid',
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'totalangle',
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'hr_bottom',
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'x_right',
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'Position',
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'Extensions',
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'GPS Speed',
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'Split (IMP)',
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'Speed (IMP)',
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'driveenergy',
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'Distance/Stroke (IMP)',
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'Distance/Stroke (GPS)',
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'Distance (IMP)',
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'equivergpower',
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'cum_dist.1'
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]
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rowingmetrics = (
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('time',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Time',
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'ax_min': 0,
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'ax_max': 1e5,
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'mode':'both',
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'type': 'basic'}),
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('hr',{
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'numtype':'integer',
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'null':True,
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'verbose_name': 'Heart Rate (bpm)',
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'ax_min': 100,
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'ax_max': 200,
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'mode':'both',
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'type': 'basic'}),
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('pace',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Pace (/500m)',
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'ax_min': 1.0e3*210,
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'ax_max': 1.0e3*75,
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'mode':'both',
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'type': 'basic'}),
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('velo',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Boat Speed (m/s)',
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'ax_min': 0,
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'ax_max': 8,
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'default': 0,
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'mode':'both',
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'type':'pro'}),
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('spm',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Stroke Rate (spm)',
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'ax_min': 15,
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'ax_max': 45,
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'mode':'both',
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'type': 'basic'}),
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('driveenergy',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Work Per Stroke (J)',
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'ax_min': 0,
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'ax_max': 1000,
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'mode':'both',
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'type': 'pro'}),
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('power',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Power (W)',
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'ax_min': 0,
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'ax_max': 600,
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'mode':'both',
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'type': 'basic'}),
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('averageforce',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Average Drive Force (N)',
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'ax_min': 0,
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'ax_max': 1200,
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'mode':'both',
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'type': 'pro'}),
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('peakforce',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Peak Drive Force (N)',
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'ax_min': 0,
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'ax_max': 1500,
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'mode':'both',
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'type': 'pro'}),
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('drivelength',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Drive Length (m)',
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'ax_min': 0,
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'ax_max': 2.5,
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'mode':'both',
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'type': 'pro'}),
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('forceratio',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Average/Peak Force Ratio',
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'ax_min': 0,
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'ax_max': 1,
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'mode':'both',
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'type': 'pro'}),
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('distance',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Distance (m)',
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'ax_min': 0,
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'ax_max': 1e5,
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'mode':'both',
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'type': 'basic'}),
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('cumdist',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Cumulative Distance (m)',
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'ax_min': 0,
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'ax_max': 1e5,
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'mode':'both',
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'type': 'basic'}),
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('drivespeed',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Drive Speed (m/s)',
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'ax_min': 0,
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'ax_max': 4,
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'default': 0,
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'mode':'both',
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'type': 'pro'}),
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('catch',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Catch Angle (degrees)',
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'ax_min': -40,
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'ax_max': -75,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('slip',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Slip (degrees)',
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'ax_min': 0,
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'ax_max': 20,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('finish',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Finish Angle (degrees)',
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'ax_min': 20,
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'ax_max': 55,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('wash',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Wash (degrees)',
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'ax_min': 0,
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'ax_max': 30,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('peakforceangle',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Peak Force Angle',
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'ax_min': -20,
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'ax_max': 20,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('totalangle',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Drive Length (deg)',
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'ax_min': 40,
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'ax_max': 140,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('effectiveangle',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Effective Drive Length (deg)',
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'ax_min': 40,
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'ax_max': 140,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('rhythm',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Stroke Rhythm',
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'ax_min': 20,
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'ax_max': 55,
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'default': 1.0,
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'mode':'erg',
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'type': 'pro'}),
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('efficiency',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'OTW Efficiency (%)',
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'ax_min': 0,
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'ax_max': 110,
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'default': 0,
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'mode':'water',
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'type': 'pro'}),
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('distanceperstroke',{
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'numtype':'float',
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'null':True,
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'verbose_name': 'Distance per Stroke (m)',
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'ax_min': 0,
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'ax_max': 15,
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'default': 0,
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'mode':'both',
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'type': 'basic'}),
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)
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axesnew = [
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(name,d['verbose_name'],d['ax_min'],d['ax_max'],d['type']) for name,d in rowingmetrics
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]
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axes = tuple(axesnew+[('None','None',0,1,'basic')])
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axlabels = {ax[0]:ax[1] for ax in axes}
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yaxminima = {ax[0]:ax[2] for ax in axes}
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yaxmaxima = {ax[0]:ax[3] for ax in axes}
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defaultfavoritecharts = (
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{
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'yparam1':'pace',
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'yparam2':'spm',
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'xparam':'time',
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'plottype':'line',
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'workouttype':'both',
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'reststrokes':True,
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'notes':"""This chart shows your pace and stroke rate versus time. """,
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},
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{
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'yparam1':'pace',
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'yparam2':'hr',
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'xparam':'time',
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'plottype':'line',
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'workouttype':'both',
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'reststrokes':True,
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'notes':"""This chart shows your pace and heart rate versus time.
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Heart rate values will be shown only when it is in your data, i.e.
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in case you recorded your heart rate during your workout""",
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},
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{
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'yparam1':'distanceperstroke',
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'yparam2':'hr',
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'xparam':'time',
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'plottype':'line',
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'workouttype':'otw',
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'reststrokes':True,
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'notes':"""This chart shows the Distance covered per stroke, and your
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heart rate versus time. """,
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},
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{
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'yparam1':'driveenergy',
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'yparam2':'hr',
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'xparam':'time',
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'plottype':'line',
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'workouttype':'ote',
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'reststrokes':True,
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'notes':"""This chart shows the Work per Stroke and your heart rate
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plotted versus time. """,
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},
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{
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'yparam1':'distanceperstroke',
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'yparam2':'None',
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'xparam':'spm',
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'plottype':'scatter',
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'workouttype':'otw',
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'reststrokes':True,
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'notes':"""This chart shows the Distance per Stroke versus stroke
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stroke rate. You should see a steady decline of the Distance per Stroke
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as you increase stroke rate. Typical values are > 10m for steady state
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dropping to 8m for race pace in the single.""",
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},
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{
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'yparam1':'driveenergy',
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'yparam2':'None',
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'xparam':'spm',
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'plottype':'scatter',
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'workouttype':'ote',
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'reststrokes':True,
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'notes':"""This chart shows the Work per Stroke versus Stroke Rate.
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This value should be fairly constant across all stroke rates.""",
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},
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)
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def calc_trimp(df,sex,hrmax,hrmin,hrftp):
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if sex == 'male':
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f = 1.92
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else:
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f = 1.67
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dt = df['time'].diff()/6.e4
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hrr = (df['hr']-hrmin)/(hrmax-hrmin)
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hrrftp = (hrftp-hrmin)/float(hrmax-hrmin)
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trimp1hr = 60*hrrftp*0.64*np.exp(f*hrrftp)
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trimpdata = dt*hrr*0.64*np.exp(f*hrr)
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trimp = trimpdata.sum()
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hrtss = 100*trimp/trimp1hr
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return trimp,hrtss
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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:
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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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#poly_coefficients = np.polyfit(ages,powers,6)
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fitfunc = lambda pars, x: np.abs(pars[0])*(1-x/max(120,pars[1]))-np.abs(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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errfunc = lambda pars, x,y: 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:
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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 = np.polyval(poly_coefficients,age)
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power = 0.5*(np.abs(power)+power)
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else:
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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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