def dashboard(request, athleteId):
print('getting athlete id...')
athleteId = int(athleteId)
#df = pd.read_pickle(str(path)+"/master_dfs/"+str(athleteId)+"masterDf.txt")
#summaryDf = thresher.getSummaryDf(df)
#summaryDf_json = summaryDf.to_json(orient="records")
print('getting athlete object...')
ath = Athlete.objects.get(athleteId=athleteId)
print('getting run summary from athlete object...')
summaryDf = pd.read_json(ath.runsSummary)
# setting index again for use in rolling
summaryDf = summaryDf.set_index(summaryDf.date)
#print(summaryDf)
summaryDf_json = ath.runsSummary
# making weekly summary
weekSummarySum = summaryDf[['climb', 'easy', 'stamina', 'recovery', 'impulse', 'realMiles', 'totalDist', 'totalTime']].resample('W', how='sum')
# fix variation. this isn't a helpful number
weekSummaryMean = summaryDf[['avgHr', 'variation']].resample('W', how='mean')
weekSummary = pd.concat([weekSummarySum, weekSummaryMean], axis=1)
#ws_json = weekSummary.to_json(orient='records')
#print('weekSummary')
#print(weekSummary)
#### Summary by zone WEEKLY
recovery = DataFrame({'x':weekSummary.index, 'y':weekSummary.recovery})
recovery = recovery.set_index(np.arange(len(recovery)))
recoveryW_json = recovery.to_json(orient="index") # "index" used for stacked specific layout.
easy = DataFrame({'x':weekSummary.index, 'y':weekSummary.easy})
easy = easy.set_index(np.arange(len(easy)))
easyW_json = easy.to_json(orient="index")
stamina = DataFrame({'x':weekSummary.index, 'y':weekSummary.stamina})
stamina = stamina.set_index(np.arange(len(stamina)))
staminaW_json = stamina.to_json(orient="index")
impulse = DataFrame({'x':weekSummary.index, 'y':weekSummary.impulse})
impulse = impulse.set_index(np.arange(len(impulse)))
impulseW_json = impulse.to_json(orient="index")
#### Summary by zone
print('recovery')
recovery = DataFrame({'x':summaryDf.date, 'y':summaryDf.recovery})
recovery = recovery.set_index(np.arange(len(recovery)))
recovery_json = recovery.to_json(orient="index") # "index" used for stacked specific layout.
print recovery_json
print('easy')
easy = DataFrame({'x':summaryDf.date, 'y':summaryDf.easy})
easy = easy.set_index(np.arange(len(easy)))
easy_json = easy.to_json(orient="index")
stamina = DataFrame({'x':summaryDf.date, 'y':summaryDf.stamina})
stamina = stamina.set_index(np.arange(len(stamina)))
stamina_json = stamina.to_json(orient="index")
impulse = DataFrame({'x':summaryDf.date, 'y':summaryDf.impulse})
impulse = impulse.set_index(np.arange(len(impulse)))
impulse_json = impulse.to_json(orient="index")
rList = list(recovery)
eList = list(easy)
sList = list(stamina)
iList = list(impulse)
stackedTester = [rList, eList, sList, iList]
print stackedTester
print('rolling')
### rolling
rollDf = thresher.getRollingSummaryDf(summaryDf)
rollDf =rollDf.fillna(0)
rollingDf_json = rollDf.to_json(orient="records")
rollDfLastFive_json = rollDf.sort_values(['date'], ascending=False)[:5].to_json(orient="records")
print('rollrec')
rollRec = DataFrame({'x':rollDf.date, 'y':rollDf.rollRec})
rollRec["y"] = rollRec.y + 100
rollRec = rollRec.set_index(np.arange(len(rollRec)))
rollRec_json = rollRec.to_json(orient="index")
print('rolleasy')
rollEasy = DataFrame({'x':rollDf.date, 'y':rollDf.rollEasy})
rollEasy = rollEasy.set_index(np.arange(len(rollEasy)))
rollEasy_json = rollEasy.to_json(orient="index")
print('rollstam')
rollStam = DataFrame({'x':rollDf.date, 'y':rollDf.rollStam})
rollStam = rollStam.set_index(np.arange(len(rollStam)))
rollStam_json = rollStam.to_json(orient="index")
print('rollimp')
rollImp = DataFrame({'x':rollDf.date, 'y':rollDf.rollImp})
rollImp = rollImp.set_index(np.arange(len(rollImp)))
rollImp_json = rollImp.to_json(orient="index")
# dealing w fitlines
#testLine = Activity.objects.get(act_id=535167099).fitline
aWeekAgo = datetime.datetime.now() - datetime.timedelta(days=7)
last7Days = summaryDf[summaryDf.date > aWeekAgo]
dist7 = round(np.sum(last7Days.totalDist), 1)
try:
var7 = int(round(np.mean(last7Days.variation), 0)) # weight this average
avgHr7 = int(round(np.mean(last7Days.avgHr), 0)) # weight this average
except:
var7 = 0.0
avgHr7 = 0.0
climb7 = int(round(np.sum(last7Days.climb), 0))
time7 = round(np.sum(last7Days.totalTime), 1)
trainingEfficiency7 = (dist7 - np.sum(last7Days.stamina)) / (dist7 +1)
#print "7DAYs"
#print last7Days
#print time7
################################################
# for maf pts
mafPts = summaryDf[['date','mafScore']].dropna().sort_values(['date'], ascending=False)
mafPts_json = mafPts.to_json(orient="records")
mafPts_smoothed = thresher.makeLws(df=mafPts, frac=.20)
mafPts_smoothed['date'] = mafPts_smoothed.date / 1000000 #lws messed up the dates
mafPts_smoothed_json = mafPts_smoothed.to_json(orient="records")
#print mafPts_smoothed_json
print "\n\n"
print "mafPts"
print mafPts
# for maf dash
lastFive = mafPts[:5]
lastFive_json = lastFive.to_json(orient="records")
ath.mafLastFive = lastFive_json
ath.save(update_fields=['mafLastFive'])
print "lastfive"
print lastFive
# current maf score
currentMaf = str(np.round(lastFive.mafScore.iloc[0], 2))
athName = ath.name
print('rendering...')
print summaryDf
"""
taking these out of render package:
'tE7':trainingEfficiency7, 'dist7':dist7, 'var7':var7, 'avgHr7':avgHr7, 'climb7':climb7, 'time7':time7,
'rollingDf_json':rollingDf_json, 'rollRec_json':rollRec_json, 'rollEasy_json':rollEasy_json, 'rollStam_json':rollStam_json, 'rollImp_json':rollImp_json,
'fitlinesAll':ath.fitLines
"""
return render(request, 'stravaChimp/dashboard.html', {'athName':athName, 'stackedTester':stackedTester, 'r5':rollDfLastFive_json, 'summaryDf_json':summaryDf_json, 'recovery_json':recovery_json, 'easy_json':easy_json, 'stamina_json':stamina_json, 'impulse_json':impulse_json,'recoveryW_json':recoveryW_json, 'easyW_json':easyW_json, 'staminaW_json':staminaW_json, 'impulseW_json':impulseW_json, 'athleteId':athleteId, 'ath':ath, 'mafPts_json':mafPts_json, 'currentMaf': currentMaf, 'maf_json':lastFive_json, 'mafPts_smoothed_json': mafPts_smoothed_json, 'datesList':summaryDf['date'].to_json(orient='records')})
def dashboard(request, athleteId):
print('getting athlete id...')
athleteId = int(athleteId)
#df = pd.read_pickle(str(path)+"/master_dfs/"+str(athleteId)+"masterDf.txt")
#summaryDf = thresher.getSummaryDf(df)
#summaryDf_json = summaryDf.to_json(orient="records")
print('getting athlete object...')
ath = Athlete.objects.get(athleteId=athleteId)
print('getting run summary from athlete object...')
summaryDf = pd.read_json(ath.runsSummary)
# setting index again for use in rolling
summaryDf = summaryDf.set_index(summaryDf.date)
#print(summaryDf)
summaryDf_json = ath.runsSummary
# making weekly summary
weekSummarySum = summaryDf[[
'climb', 'easy', 'stamina', 'recovery', 'impulse', 'realMiles',
'totalDist', 'totalTime'
]].resample('W', how='sum')
# fix variation. this isn't a helpful number
weekSummaryMean = summaryDf[['avgHr', 'variation']].resample('W',
how='mean')
weekSummary = pd.concat([weekSummarySum, weekSummaryMean], axis=1)
#ws_json = weekSummary.to_json(orient='records')
#print('weekSummary')
#print(weekSummary)
#### Summary by zone WEEKLY
recovery = DataFrame({'x': weekSummary.index, 'y': weekSummary.recovery})
recovery = recovery.set_index(np.arange(len(recovery)))
recoveryW_json = recovery.to_json(
orient="index") # "index" used for stacked specific layout.
easy = DataFrame({'x': weekSummary.index, 'y': weekSummary.easy})
easy = easy.set_index(np.arange(len(easy)))
easyW_json = easy.to_json(orient="index")
stamina = DataFrame({'x': weekSummary.index, 'y': weekSummary.stamina})
stamina = stamina.set_index(np.arange(len(stamina)))
staminaW_json = stamina.to_json(orient="index")
impulse = DataFrame({'x': weekSummary.index, 'y': weekSummary.impulse})
impulse = impulse.set_index(np.arange(len(impulse)))
impulseW_json = impulse.to_json(orient="index")
#### Summary by zone
print('recovery')
recovery = DataFrame({'x': summaryDf.date, 'y': summaryDf.recovery})
recovery = recovery.set_index(np.arange(len(recovery)))
recovery_json = recovery.to_json(
orient="index") # "index" used for stacked specific layout.
print recovery_json
print('easy')
easy = DataFrame({'x': summaryDf.date, 'y': summaryDf.easy})
easy = easy.set_index(np.arange(len(easy)))
easy_json = easy.to_json(orient="index")
stamina = DataFrame({'x': summaryDf.date, 'y': summaryDf.stamina})
stamina = stamina.set_index(np.arange(len(stamina)))
stamina_json = stamina.to_json(orient="index")
impulse = DataFrame({'x': summaryDf.date, 'y': summaryDf.impulse})
impulse = impulse.set_index(np.arange(len(impulse)))
impulse_json = impulse.to_json(orient="index")
rList = list(recovery)
eList = list(easy)
sList = list(stamina)
iList = list(impulse)
stackedTester = [rList, eList, sList, iList]
print stackedTester
print('rolling')
### rolling
rollDf = thresher.getRollingSummaryDf(summaryDf)
rollDf = rollDf.fillna(0)
rollingDf_json = rollDf.to_json(orient="records")
rollDfLastFive_json = rollDf.sort_values(
['date'], ascending=False)[:5].to_json(orient="records")
print('rollrec')
rollRec = DataFrame({'x': rollDf.date, 'y': rollDf.rollRec})
rollRec["y"] = rollRec.y + 100
rollRec = rollRec.set_index(np.arange(len(rollRec)))
rollRec_json = rollRec.to_json(orient="index")
print('rolleasy')
rollEasy = DataFrame({'x': rollDf.date, 'y': rollDf.rollEasy})
rollEasy = rollEasy.set_index(np.arange(len(rollEasy)))
rollEasy_json = rollEasy.to_json(orient="index")
print('rollstam')
rollStam = DataFrame({'x': rollDf.date, 'y': rollDf.rollStam})
rollStam = rollStam.set_index(np.arange(len(rollStam)))
rollStam_json = rollStam.to_json(orient="index")
print('rollimp')
rollImp = DataFrame({'x': rollDf.date, 'y': rollDf.rollImp})
rollImp = rollImp.set_index(np.arange(len(rollImp)))
rollImp_json = rollImp.to_json(orient="index")
# dealing w fitlines
#testLine = Activity.objects.get(act_id=535167099).fitline
aWeekAgo = datetime.datetime.now() - datetime.timedelta(days=7)
last7Days = summaryDf[summaryDf.date > aWeekAgo]
dist7 = round(np.sum(last7Days.totalDist), 1)
try:
var7 = int(round(np.mean(last7Days.variation),
0)) # weight this average
avgHr7 = int(round(np.mean(last7Days.avgHr), 0)) # weight this average
except:
var7 = 0.0
avgHr7 = 0.0
climb7 = int(round(np.sum(last7Days.climb), 0))
time7 = round(np.sum(last7Days.totalTime), 1)
trainingEfficiency7 = (dist7 - np.sum(last7Days.stamina)) / (dist7 + 1)
#print "7DAYs"
#print last7Days
#print time7
################################################
# for maf pts
mafPts = summaryDf[['date',
'mafScore']].dropna().sort_values(['date'],
ascending=False)
mafPts_json = mafPts.to_json(orient="records")
mafPts_smoothed = thresher.makeLws(df=mafPts, frac=.20)
mafPts_smoothed[
'date'] = mafPts_smoothed.date / 1000000 #lws messed up the dates
mafPts_smoothed_json = mafPts_smoothed.to_json(orient="records")
#print mafPts_smoothed_json
print "\n\n"
print "mafPts"
print mafPts
# for maf dash
lastFive = mafPts[:5]
lastFive_json = lastFive.to_json(orient="records")
ath.mafLastFive = lastFive_json
ath.save(update_fields=['mafLastFive'])
print "lastfive"
print lastFive
# current maf score
currentMaf = str(np.round(lastFive.mafScore.iloc[0], 2))
athName = ath.name
print('rendering...')
print summaryDf
"""
taking these out of render package:
'tE7':trainingEfficiency7, 'dist7':dist7, 'var7':var7, 'avgHr7':avgHr7, 'climb7':climb7, 'time7':time7,
'rollingDf_json':rollingDf_json, 'rollRec_json':rollRec_json, 'rollEasy_json':rollEasy_json, 'rollStam_json':rollStam_json, 'rollImp_json':rollImp_json,
'fitlinesAll':ath.fitLines
"""
return render(
request, 'stravaChimp/dashboard.html', {
'athName': athName,
'stackedTester': stackedTester,
'r5': rollDfLastFive_json,
'summaryDf_json': summaryDf_json,
'recovery_json': recovery_json,
'easy_json': easy_json,
'stamina_json': stamina_json,
'impulse_json': impulse_json,
'recoveryW_json': recoveryW_json,
'easyW_json': easyW_json,
'staminaW_json': staminaW_json,
'impulseW_json': impulseW_json,
'athleteId': athleteId,
'ath': ath,
'mafPts_json': mafPts_json,
'currentMaf': currentMaf,
'maf_json': lastFive_json,
'mafPts_smoothed_json': mafPts_smoothed_json,
'datesList': summaryDf['date'].to_json(orient='records')
})
import statsmodels.api as sm
import matplotlib.pyplot as plt
import thresher
from math import radians, cos, sin, asin, sqrt
#urllib3.contrib.pyopenssl.inject_into_urllib3()
df_summary = pd.read_pickle("runsSummary.txt")
df_master = thresher.basicClean(pd.read_pickle("master_dfs/10319226masterDf.txt"))
maf = df_summary[['date', 'mafScore']]
print maf
maf_smoothed = thresher.makeLws(df=maf, frac=.20)
print maf_smoothed
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(maf_smoothed.date, maf_smoothed.mafScore, c='blue', alpha=0.25)
#ax.scatter(df[x], df[y2], c='red', alpha=0.25)
#ax.plot(df['speedLwsX'], df['speedLwsY'], c='blue')
#ax.plot(lwsHatX, lwsHatY, c='red')
#ax.set_title(str(x)+' '+str(y))
#ax.set_ylabel(str(y))
#ax.set_xlabel(str(x))
#ax.set_ylim([0,6])
#ax.set_xlim([0, 1500])
#ax.legend([y, y2])
plt.show()
from pandas import DataFrame, pivot_table
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
import thresher
from math import radians, cos, sin, asin, sqrt
#urllib3.contrib.pyopenssl.inject_into_urllib3()
df_summary = pd.read_pickle("runsSummary.txt")
df_master = thresher.basicClean(
pd.read_pickle("master_dfs/10319226masterDf.txt"))
maf = df_summary[['date', 'mafScore']]
print maf
maf_smoothed = thresher.makeLws(df=maf, frac=.20)
print maf_smoothed
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(maf_smoothed.date, maf_smoothed.mafScore, c='blue', alpha=0.25)
#ax.scatter(df[x], df[y2], c='red', alpha=0.25)
#ax.plot(df['speedLwsX'], df['speedLwsY'], c='blue')
#ax.plot(lwsHatX, lwsHatY, c='red')
#ax.set_title(str(x)+' '+str(y))
#ax.set_ylabel(str(y))
#ax.set_xlabel(str(x))
#ax.set_ylim([0,6])
#ax.set_xlim([0, 1500])
#ax.legend([y, y2])
plt.show()
