#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jul  9 10:30:15 2018

@author: cad6
"""

def tc9010percent():
    #%% extracts the channel, temperature and resistance from .csv file (must be given the path)
    csvFile = input('File Path? ')
    import numpy as np
    import matplotlib.pyplot as plt
    raw = np.loadtxt(open(csvFile,"rb"), delimiter=",", skiprows=1)
    channel = raw[:, 1][0]
    temperatureRaw = raw[:, 2]
    resistanceRaw = raw[:, 3]

    #%% establishes the tuples which hol/home/linaro/Tc Data and Curve Code/2018_07_02/Channel_5_2018_07_02_13_28_42.csvd contextualized data
    resTuple = tuple(resistanceRaw)
    tempTuple = tuple(temperatureRaw)

    #%%Tc50
    resList = list(resistanceRaw)
    tempList = list(temperatureRaw)
    resList.sort()
    tempList.sort()


    temperatureRange =  tempList[-1] - tempList[0]
    rangeVariable = int(len(resistanceRaw)*(.5/temperatureRange))
    maxRes = []
    minRes = []
    for i in range(-rangeVariable , 0) :
        maxRes.append(resList[i])

    for j in range(0, rangeVariable):
        minRes.append(resList[j])

    upperRes = int(np.mean(maxRes))
    lowerRes = int(np.mean(minRes))
    aveRes = .5*(upperRes + lowerRes)


    upperBound = .25*aveRes + aveRes
    lowerBound = -.25*aveRes + aveRes

    newArray = []
    resVals = []
    tempVals = []

    for x in range(0, len(resList)):
        newArray.append(upperBound>resList[x]>lowerBound)

    for r in range(0, len(newArray)):
        if newArray[r] == True:
            resVals.append(resList[r])

    tupleIndex = []
    for h in range(0, len(resVals)) :
        tupleIndex.append(resTuple.index(resVals[h]))


    for g in range(0, len(tupleIndex)):
        tempVals.append(tempTuple[tupleIndex[g]])

    if len(tempVals) %2 == 0:
       tempVals.append(tempVals[-1])

    Tc50 = np.median(tempVals)

    #%%make list without top 10 and bottom 10 percent of values
    largestMinRes = minRes[-1]
    smallestMaxRes = maxRes[0]
    newArray1 = []
    applicableValues1 = []
    for x in range(0, len(resList)):
       newArray1.append(smallestMaxRes>resList[x]>largestMinRes)

    for r in range(0, len(newArray1)):
        if newArray1[r] == True:
            applicableValues1.append(resList[r])

    tupleIndex1 = []
    for h in range(0, len(applicableValues1)):
        tupleIndex1.append(resTuple.index(applicableValues1[h]))

    tempVals = []
    for g in range(0, len(tupleIndex1)):
         tempVals.append(tempTuple[tupleIndex1[g]])

    #extact temperature vals close to 10%
    approxResAtTc10 = np.median(maxRes)*.1
    number = .75
    resTc10 = [x for x in resList if approxResAtTc10 -number*approxResAtTc10 <= x <= approxResAtTc10 + number*approxResAtTc10]
    if resTc10 == []:
        number = 2*number
        resTc10 = [x for x in resList if approxResAtTc10 -number*approxResAtTc10 <= x <= approxResAtTc10 + number*approxResAtTc10]
    tempTc10 = []
    for j in range(0, len(resTc10)):
        tempTc10.append(tempTuple[resTuple.index(resTc10[j])])
    if len(tempTc10) %2 == 0:
        tempTc10.append(tempTc10[-1])
    resRangeTc10 = []
    for h in range(0, len(tempTc10)):
        resRangeTc10.append(resTuple[tempTuple.index(tempTc10[h])])
    Tc10 = max(tempTc10)

    #extract temperature vals close to 90%
    approxResAtTc90 = np.median(maxRes)*.9
    resTc90 = [x for x in resList if approxResAtTc90 -.75<= x <= approxResAtTc90 +.75 ]
    tempTc90 = []
    for i in range(0, len(resTc90)):
        tempTc90.append(tempTuple[resTuple.index(resTc90[i])])
    if len(tempTc90) %2 == 0:
        tempTc90.append(tempTc90[-1])
    resRangeTc90 = []
    for h in range(0, len(tempTc90)):
        resRangeTc90.append(resTuple[tempTuple.index(tempTc90[h])])
    Tc90 = np.median(tempTc90)
    #calculate ΔTc
    ΔTc = Tc90-Tc10
    print('Critical Temperature (10 Percent Measurement) of Channel %d is %f' %(channel, Tc10))
    print('Critical Temperature (90 Percent Measurement) of Channel %d is %f' %(channel, Tc90))
    print('ΔTc of Channel %d is %f' %(channel, ΔTc))

    #%% extreme error check
    if ΔTc<= 0.1 or ΔTc > 1:
        print('ΔTc seems off, error suspected')

    #%%plotting
    plt.title('Resistance vs Temperature for Channel %d' %channel)
    plt.xlabel('Temperature(K)')
    plt.ylabel('Resistance(Ω)')
    plt.axis([Tc10-.5, Tc90+.5, -1, approxResAtTc90+20])
    plt.plot(tempTuple,resTuple, 'k')
    plt.axvline(x= Tc10, color = 'r', label = 'Tc10')
    plt.axvline(x=Tc90, color = 'b', label = 'Tc90')
    plt.axhline(y= .5*(resTuple[tempTuple.index(Tc10)]+resTuple[tempTuple.index(Tc90)]), color = 'g', linestyle = '-.', label = '50% Res')
    plt.axhline(y=resTuple[tempTuple.index(Tc10)], color = 'r', linestyle = '-.', label = 'Res at Tc10')
    plt.axhline(y=resTuple[tempTuple.index(Tc90)], color = 'b', linestyle = '-.', label = 'Res at Tc90')
    plt.legend()
    return;