Merge branch 'release/empower-physics'
This commit is contained in:
Sander Roosendaal
@@ -344,8 +344,6 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
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wash = rowdatadf.ix[:,'wash']
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catch = rowdatadf.ix[:,'catch']
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finish = rowdatadf.ix[:,'finish']
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peakforce = rowdatadf.ix[:'peakforce']
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averageforce = rowdatadf.ix[:'averageforce']
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peakforceangle = rowdatadf.ix[:,'peakforceangle']
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driveenergy = rowdatadf.ix[:,'driveenergy']
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drivelength = driveenergy/(averageforce*4.44822)
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@@ -355,8 +353,6 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
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slip = savgol_filter(slip,windowsize,3)
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catch = savgol_filter(catch,windowsize,3)
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finish = savgol_filter(finish,windowsize,3)
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peakforce = savgol_filter(peakforce,windowsize,3)
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averageforce = savgol_filter(averageforce,windowsize,3)
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peakforceangle = savgol_filter(peakforceangle,windowsize,3)
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driveenergy = savgol_filter(driveenergy,windowsize,3)
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drivelength = savgol_filter(drivelength,windowsize,3)
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@@ -366,6 +362,7 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
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data['finish'] = finish
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data['peakforceangle'] = peakforceangle
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data['driveenergy'] = driveenergy
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data['drivelength'] = drivelength
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data['peakforce'] = peakforce
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data['averageforce'] = averageforce
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except KeyError:
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389
rowers/dataprepnodjango.py
Normal file
389
rowers/dataprepnodjango.py
Normal file
@@ -0,0 +1,389 @@
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from rowingdata import rowingdata as rrdata
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from rowingdata import rower as rrower
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from rowingdata import main as rmain
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from pandas import DataFrame,Series
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import pandas as pd
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import numpy as np
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import itertools
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from sqlalchemy import create_engine
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import sqlalchemy as sa
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from rowsandall_app.settings import DATABASES
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user = DATABASES['default']['USER']
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password = DATABASES['default']['PASSWORD']
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database_name = DATABASES['default']['NAME']
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host = DATABASES['default']['HOST']
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port = DATABASES['default']['PORT']
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database_url = 'mysql://{user}:{password}@{host}:{port}/{database_name}'.format(
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user=user,
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password=password,
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database_name=database_name,
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host=host,
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port=port,
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)
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database_url_debug = 'sqlite:///'+database_name
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from scipy.signal import savgol_filter
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import datetime
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def niceformat(values):
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out = []
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for v in values:
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formattedv = strfdelta(v)
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out.append(formattedv)
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return out
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def strfdelta(tdelta):
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try:
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minutes,seconds = divmod(tdelta.seconds,60)
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tenths = int(tdelta.microseconds/1e5)
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except AttributeError:
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minutes,seconds = divmod(tdelta.view(np.int64),60e9)
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seconds,rest = divmod(seconds,1e9)
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tenths = int(rest/1e8)
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res = "{minutes:0>2}:{seconds:0>2}.{tenths:0>1}".format(
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minutes=minutes,
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seconds=seconds,
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tenths=tenths,
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)
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return res
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def nicepaceformat(values):
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out = []
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for v in values:
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formattedv = strfdelta(v)
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out.append(formattedv)
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return out
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def timedeltaconv(x):
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if not np.isnan(x):
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dt = datetime.timedelta(seconds=x)
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else:
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dt = datetime.timedelta(seconds=350.)
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return dt
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def rdata(file,rower=rrower()):
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try:
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res = rrdata(file,rower=rower)
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except IOError:
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res = 0
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return res
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def delete_strokedata(id,debug=True):
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if debug:
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engine = create_engine(database_url_debug, echo=False)
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else:
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engine = create_engine(database_url, echo=False)
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query = sa.text('DELETE FROM strokedata WHERE workoutid={id};'.format(
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id=id,
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))
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with engine.connect() as conn, conn.begin():
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try:
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result = conn.execute(query)
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except:
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print "Database Locked"
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conn.close()
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engine.dispose()
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def update_strokedata(id,df,debug=True):
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delete_strokedata(id)
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rowdata = dataprep(df,id=id,bands=True,barchart=True,otwpower=True,
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debug=debug)
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def testdata(time,distance,pace,spm):
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t1 = np.issubdtype(time,np.number)
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t2 = np.issubdtype(distance,np.number)
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t3 = np.issubdtype(pace,np.number)
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t4 = np.issubdtype(spm,np.number)
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return t1 and t2 and t3 and t4
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def getsmallrowdata_db(columns,ids=[]):
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prepmultipledata(ids)
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data = read_cols_df_sql(ids,columns)
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return data
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def prepmultipledata(ids,verbose=False,debug=True):
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query = sa.text('SELECT DISTINCT workoutid FROM strokedata')
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if debug:
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engine = create_engine(database_url_debug, echo=False)
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else:
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engine = create_engine(database_url, echo=False)
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with engine.connect() as conn, conn.begin():
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res = conn.execute(query)
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res = list(itertools.chain.from_iterable(res.fetchall()))
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conn.close()
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engine.dispose()
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res = list(set(ids)-set(res))
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for id in res:
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rowdata,row = getrowdata(id=id)
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if verbose:
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print id
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if rowdata:
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data = dataprep(rowdata.df,id=id,bands=True,barchart=True,otwpower=True)
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return res
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def read_cols_df_sql(ids,columns,debug=True):
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columns = list(columns)+['distance','spm']
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columns = [x for x in columns if x != 'None']
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columns = list(set(columns))
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cls = ''
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if debug:
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engine = create_engine(database_url_debug, echo=False)
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else:
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engine = create_engine(database_url, echo=False)
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for column in columns:
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cls += column+', '
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cls = cls[:-2]
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if len(ids) == 0:
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query = sa.text('SELECT {columns} FROM strokedata WHERE workoutid=0'.format(
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columns = cls,
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))
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elif len(ids) == 1:
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query = sa.text('SELECT {columns} FROM strokedata WHERE workoutid={id}'.format(
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id = ids[0],
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columns = cls,
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))
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else:
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query = sa.text('SELECT {columns} FROM strokedata WHERE workoutid IN {ids}'.format(
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columns = cls,
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ids = tuple(ids),
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))
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df = pd.read_sql_query(query,engine)
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engine.dispose()
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return df
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def read_df_sql(id,debug=True):
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if debug:
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engine = create_engine(database_url_debug, echo=False)
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else:
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engine = create_engine(database_url, echo=False)
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df = pd.read_sql_query(sa.text('SELECT * FROM strokedata WHERE workoutid={id}'.format(
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id=id)), engine)
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engine.dispose()
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return df
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def smalldataprep(therows,xparam,yparam1,yparam2):
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df = pd.DataFrame()
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if yparam2 == 'None':
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yparam2 = 'power'
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df[xparam] = []
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df[yparam1] = []
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df[yparam2] = []
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df['distance'] = []
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df['spm'] = []
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for workout in therows:
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f1 = workout.csvfilename
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try:
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rowdata = dataprep(rrdata(f1).df)
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rowdata = pd.DataFrame({xparam: rowdata[xparam],
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yparam1: rowdata[yparam1],
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yparam2: rowdata[yparam2],
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'distance': rowdata['distance'],
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'spm': rowdata['spm'],
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}
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)
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df = pd.concat([df,rowdata],ignore_index=True)
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except IOError:
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pass
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return df
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def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
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empower=True,debug=True):
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rowdatadf.set_index([range(len(rowdatadf))],inplace=True)
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t = rowdatadf.ix[:,'TimeStamp (sec)']
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t = pd.Series(t-rowdatadf.ix[0,'TimeStamp (sec)'])
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row_index = rowdatadf.ix[:,' Stroke500mPace (sec/500m)'] > 3000
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rowdatadf.loc[row_index,' Stroke500mPace (sec/500m)'] = 3000.
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p = rowdatadf.ix[:,' Stroke500mPace (sec/500m)']
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hr = rowdatadf.ix[:,' HRCur (bpm)']
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spm = rowdatadf.ix[:,' Cadence (stokes/min)']
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cumdist = rowdatadf.ix[:,'cum_dist']
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power = rowdatadf.ix[:,' Power (watts)']
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averageforce = rowdatadf.ix[:,' AverageDriveForce (lbs)']
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drivelength = rowdatadf.ix[:,' DriveLength (meters)']
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try:
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workoutstate = rowdatadf.ix[:,' WorkoutState']
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except KeyError:
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workoutstate = 0*hr
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peakforce = rowdatadf.ix[:,' PeakDriveForce (lbs)']
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forceratio = averageforce/peakforce
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forceratio = forceratio.fillna(value=0)
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f = rowdatadf['TimeStamp (sec)'].diff().mean()
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windowsize = 2*(int(10./(f)))+1
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if windowsize <= 3:
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windowsize = 5
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if windowsize > 3:
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spm = savgol_filter(spm,windowsize,3)
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hr = savgol_filter(hr,windowsize,3)
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drivelength = savgol_filter(drivelength,windowsize,3)
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forceratio = savgol_filter(forceratio,windowsize,3)
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try:
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t2 = t.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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except TypeError:
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t2 = 0*t
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p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x))
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drivespeed = drivelength/rowdatadf[' DriveTime (ms)']*1.0e3
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drivespeed = drivespeed.fillna(value=0)
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driveenergy = drivelength*averageforce*4.44822
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distance = rowdatadf.ix[:,'cum_dist']
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data = DataFrame(
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dict(
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time = t*1e3,
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hr = hr,
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pace = p*1e3,
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spm = spm,
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cumdist = cumdist,
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ftime = niceformat(t2),
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fpace = nicepaceformat(p2),
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driveenergy=driveenergy,
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power=power,
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workoutstate=workoutstate,
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averageforce=averageforce,
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drivelength=drivelength,
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peakforce=peakforce,
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forceratio=forceratio,
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distance=distance,
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drivespeed=drivespeed,
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)
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)
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if bands:
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# HR bands
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data['hr_ut2'] = rowdatadf.ix[:,'hr_ut2']
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data['hr_ut1'] = rowdatadf.ix[:,'hr_ut1']
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data['hr_at'] = rowdatadf.ix[:,'hr_at']
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data['hr_tr'] = rowdatadf.ix[:,'hr_tr']
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data['hr_an'] = rowdatadf.ix[:,'hr_an']
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data['hr_max'] = rowdatadf.ix[:,'hr_max']
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data['hr_bottom'] = 0.0*data['hr']
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if barchart:
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# time increments for bar chart
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time_increments = rowdatadf.ix[:,' ElapsedTime (sec)'].diff()
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time_increments[0] = time_increments[1]
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time_increments = 0.5*time_increments+0.5*np.abs(time_increments)
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||||
x_right = (t2+time_increments.apply(lambda x:timedeltaconv(x)))
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||||
|
||||
data['x_right'] = x_right
|
||||
|
||||
if empower:
|
||||
try:
|
||||
wash = rowdatadf.ix[:,'wash']
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catch = rowdatadf.ix[:,'catch']
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finish = rowdatadf.ix[:,'finish']
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peakforceangle = rowdatadf.ix[:,'peakforceangle']
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driveenergy = rowdatadf.ix[:,'driveenergy']
|
||||
drivelength = driveenergy/(averageforce*4.44822)
|
||||
slip = rowdatadf.ix[:,'slip']
|
||||
if windowsize > 3:
|
||||
wash = savgol_filter(wash,windowsize,3)
|
||||
slip = savgol_filter(slip,windowsize,3)
|
||||
catch = savgol_filter(catch,windowsize,3)
|
||||
finish = savgol_filter(finish,windowsize,3)
|
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peakforceangle = savgol_filter(peakforceangle,windowsize,3)
|
||||
driveenergy = savgol_filter(driveenergy,windowsize,3)
|
||||
drivelength = savgol_filter(drivelength,windowsize,3)
|
||||
data['wash'] = wash
|
||||
data['catch'] = catch
|
||||
data['slip'] = slip
|
||||
data['finish'] = finish
|
||||
data['peakforceangle'] = peakforceangle
|
||||
data['driveenergy'] = driveenergy
|
||||
data['drivelength'] = drivelength
|
||||
data['peakforce'] = peakforce
|
||||
data['averageforce'] = averageforce
|
||||
except KeyError:
|
||||
pass
|
||||
|
||||
if otwpower:
|
||||
try:
|
||||
nowindpace = rowdatadf.ix[:,'nowindpace']
|
||||
except KeyError:
|
||||
nowindpace = p
|
||||
try:
|
||||
equivergpower = rowdatadf.ix[:,'equivergpower']
|
||||
except KeyError:
|
||||
equivergpower = 0*p+50.
|
||||
|
||||
#nowindpace = nowindpace.apply(lambda x: timedeltaconv(x))
|
||||
ergvelo = (equivergpower/2.8)**(1./3.)
|
||||
|
||||
ergpace = 500./ergvelo
|
||||
ergpace[ergpace == np.inf] = 240.
|
||||
#ergpace = ergpace.apply(lambda x: timedeltaconv(x))
|
||||
|
||||
data['ergpace'] = ergpace
|
||||
data['nowindpace'] = nowindpace
|
||||
data['equivergpower'] = equivergpower
|
||||
data['fergpace'] = nicepaceformat(ergpace)
|
||||
data['fnowindpace'] = nicepaceformat(nowindpace)
|
||||
|
||||
data = data.replace([-np.inf,np.inf],np.nan)
|
||||
data = data.fillna(method='ffill')
|
||||
|
||||
# write data if id given
|
||||
if id != 0:
|
||||
data['workoutid'] = id
|
||||
if debug:
|
||||
engine = create_engine(database_url_debug, echo=False)
|
||||
else:
|
||||
engine = create_engine(database_url, echo=False)
|
||||
with engine.connect() as conn, conn.begin():
|
||||
data.to_sql('strokedata',engine,if_exists='append',index=False)
|
||||
conn.close()
|
||||
engine.dispose()
|
||||
return data
|
||||
@@ -875,6 +875,7 @@ def interactive_flex_chart2(id=0,promember=0,
|
||||
axlabels = {
|
||||
'time': 'Time',
|
||||
'distance': 'Distance (m)',
|
||||
'cumdist': 'Distance (m)',
|
||||
'hr': 'Heart Rate (bpm)',
|
||||
'spm': 'Stroke Rate (spm)',
|
||||
'pace': 'Pace (/500m)',
|
||||
@@ -962,7 +963,7 @@ def interactive_flex_chart2(id=0,promember=0,
|
||||
if xparam=='time':
|
||||
xaxmax = tseconds.max()
|
||||
xaxmin = tseconds.min()
|
||||
elif xparam=='distance':
|
||||
elif xparam=='distance' or xparam=='cumdist':
|
||||
xaxmax = rowdata['x1'].max()
|
||||
xaxmin = rowdata['x1'].min()
|
||||
else:
|
||||
@@ -1043,7 +1044,7 @@ def interactive_flex_chart2(id=0,promember=0,
|
||||
text_color='green',
|
||||
)
|
||||
|
||||
if (xparam != 'time') and (xparam != 'distance'):
|
||||
if (xparam != 'time') and (xparam != 'distance') and (xparam != 'cumdist'):
|
||||
plot.add_layout(x1means)
|
||||
plot.add_layout(xlabel)
|
||||
|
||||
@@ -1080,7 +1081,7 @@ def interactive_flex_chart2(id=0,promember=0,
|
||||
yrange1 = Range1d(start=yaxminima[yparam1],end=yaxmaxima[yparam1])
|
||||
plot.y_range = yrange1
|
||||
|
||||
if (xparam != 'time') and (xparam != 'distance'):
|
||||
if (xparam != 'time') and (xparam != 'distance') and (xparam != 'cumdist'):
|
||||
xrange1 = Range1d(start=yaxminima[xparam],end=yaxmaxima[xparam])
|
||||
plot.x_range = xrange1
|
||||
|
||||
|
||||
@@ -15,6 +15,8 @@ from matplotlib import figure
|
||||
|
||||
import stravalib
|
||||
|
||||
from rowers.dataprepnodjango import update_strokedata
|
||||
|
||||
from django.core.mail import send_mail, BadHeaderError,EmailMessage
|
||||
|
||||
|
||||
@@ -93,7 +95,9 @@ def handle_sendemailcsv(first_name,last_name,email,csvfile):
|
||||
return 1
|
||||
|
||||
@app.task
|
||||
def handle_otwsetpower(f1,boattype,weightvalue,first_name,last_name,email,workoutid):
|
||||
def handle_otwsetpower(f1,boattype,weightvalue,
|
||||
first_name,last_name,email,workoutid,
|
||||
debug=False):
|
||||
rowdata = rdata(f1)
|
||||
weightvalue = float(weightvalue)
|
||||
|
||||
@@ -112,11 +116,19 @@ def handle_otwsetpower(f1,boattype,weightvalue,first_name,last_name,email,workou
|
||||
rg = rowingdata.getrigging('static/rigging/1x.txt')
|
||||
|
||||
# do calculation
|
||||
rowdata.otw_setpower_silent(skiprows=5,mc=weightvalue,rg=rg)
|
||||
powermeasured = False
|
||||
try:
|
||||
w = rowdata.df['wash']
|
||||
powermeasured = True
|
||||
except KeyError:
|
||||
pass
|
||||
|
||||
rowdata.otw_setpower_silent(skiprows=5,mc=weightvalue,rg=rg,
|
||||
powermeasured=powermeasured)
|
||||
|
||||
# save data
|
||||
rowdata.write_csv(f1)
|
||||
dataprep.update_strokedata(workoutid,rowdata.df)
|
||||
update_strokedata(workoutid,rowdata.df,debug=debug)
|
||||
|
||||
# send email
|
||||
fullemail = first_name + " " + last_name + " " + "<" + email + ">"
|
||||
@@ -128,7 +140,7 @@ def handle_otwsetpower(f1,boattype,weightvalue,first_name,last_name,email,workou
|
||||
message += "Rowsandall OTW calculations have not been fully implemented yet.\n"
|
||||
message += "We are now running an experimental version for debugging purposes. \n"
|
||||
message += "Your wind/stream corrected plot is available here: http://rowsandall.com/rowers/workout/"
|
||||
message += workoutid
|
||||
message += str(workoutid)
|
||||
message +="/interactiveotwplot\n\n"
|
||||
# message += "This functionality will be available soon, though.\n\n"
|
||||
message += "Please report any bugs/inconsistencies/unexpected results at rowsandall.slack.com or by reply to this email.\n\n"
|
||||
|
||||
BIN
rowsanda_107501
Normal file
BIN
rowsanda_107501
Normal file
Binary file not shown.
Reference in New Issue
Block a user