import pandas as pd
import numpy as np
from scipy.interpolate import griddata

def getsinglecp(df):
    thesecs = df['TimeStamp (sec)'].max()-df['TimeStamp (sec)'].min()
    if thesecs != 0:
        maxt = 2*thesecs
    else:
        maxt = 1000.

    maxlog10 = np.log10(maxt)
    logarr = np.arange(50)*maxlog10/50.
    logarr = [int(10.**(la)) for la in logarr]
    logarr = pd.Series(logarr)
    logarr.drop_duplicates(keep='first',inplace=True)

    logarr = logarr.values


    dfnew = pd.DataFrame({
        'time':1000*(df['TimeStamp (sec)']-df.ix[0,'TimeStamp (sec)']),
        'power':df[' Power (watts)']
    })
    
    dfnew['workoutid'] = 0
    
    dfgrouped = dfnew.groupby(['workoutid'])
    delta,cpvalue,avgpower = getcp(dfgrouped,logarr)

    return delta,cpvalue,avgpower

def getcp(dfgrouped,logarr):
    delta = []
    cpvalue = []
    avgpower = {}
    #avgpower[0] = 0

    for id,group in dfgrouped:
        tt = group['time'].copy()
        ww = group['power'].copy()

        tmax = tt.max()
        if tmax > 500000:
            newlen = int(tmax/5000.)
        else:
            newlen = len(tt)
        if newlen < len(tt):
            newt = np.arange(newlen)*tmax/float(newlen)
            ww = griddata(tt.values,
                          ww.values,
                          newt,method='linear',
                          rescale=True)

            tt = pd.Series(newt)
            ww = pd.Series(ww)

            
        try:
            avgpower[id] = int(ww.mean())
        except ValueError:
            avgpower[id] = '---'
        if not np.isnan(ww.mean()):
            length = len(ww)
            dt = []
            cpw = []
            for i in xrange(length-2):
                deltat,wmax = getmaxwattinterval(tt,ww,i)
                if not np.isnan(deltat) and not np.isnan(wmax):
                    dt.append(deltat)
                    cpw.append(wmax)


            
            dt = pd.Series(dt)
            cpw = pd.Series(cpw)
            if len(dt):
            
                cpvalues = griddata(dt.values,
                                    cpw.values,
                                    logarr,method='linear',
                                    rescale=True)

                for cpv in cpvalues:
                    cpvalue.append(cpv)
                for d in logarr:
                    delta.append(d)
            
    delta = pd.Series(delta,name='Delta')
    cpvalue = pd.Series(cpvalue,name='CP')
    return delta,cpvalue,avgpower

def getmaxwattinterval(tt,ww,i):
    w_roll = ww.rolling(i+2).mean().dropna()
    if len(w_roll):
        # now goes with # data points - should be fixed seconds
        indexmax = w_roll.idxmax(axis=1)
        try:
            t_0 = tt.ix[indexmax]
            t_1 = tt.ix[indexmax-i]
            deltat = 1.0e-3*(t_0-t_1)
            wmax = w_roll.ix[indexmax]
        except KeyError:
            pass
    else:
        wmax = 0
        deltat = 0

    return deltat,wmax