def askCrowd(data, mode):  #for asking a sample from crowd
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    cp.proportion()
    cp.voting()
    feature_dict = {
        i: label
        for i, label in zip(range(3), ('pmid', 'text', 'label'))
    }

    crowddata = (data[[0, 1]].values).tolist()
    label = []
    if mode == 'all':

        for i in range(0, len(data["pmid"])):
            label.append(cp.getvotes()[data['pmid'][i]])

    if mode == '1':
        pidval = data['pmid'].values
        for i in range(0, len(data["pmid"])):

            label.append(cp.getcrowdvotequestion1()[pidval[i]])

    crowdlabel = (np.array([label]).T).tolist()
    data = np.array([t1 + t2 for t1, t2 in zip(crowddata, crowdlabel)])
    columns = [l for i, l in sorted(feature_dict.items())]

    return pd.DataFrame(data, columns=columns)  #make dataframe from M sample
def Cmain():  #for asking whole
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    cp.proportion()
    cp.voting()
    # cp.decisionwriting()
    # return cp.getvotes()
    return cp.getcrowdvotequestion1()
def wallace(pid, y_real):
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    cp.proportion()

    for i in range(1, 6):
        print i
        label = []
        cp.wallaceExpriment(i)
        for item in pid:
            label.append(cp.getvotes()[item])
        cm = confusion_matrix(y_real, label).flatten()
        sensitivity, specificity, precision, loss = compute_measures(*cm)
        print sensitivity
        print specificity
def getcustomizevoting(crowdlist, pid):
    result = defaultdict(list)
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    cp.proportion()

    combinationcrowd = []
    for i in xrange(4, len(crowdlist)):
        combinationcrowd.append(list(itertools.combinations(crowdlist, i)))

    for indexgroup in range(len(combinationcrowd)):  #

        for item in range(len(combinationcrowd[indexgroup])):
            label = []  # convert crowd votes dict to ordered labels
            cp.customizevoting(len(crowdlist),
                               list(combinationcrowd[indexgroup][item]))
            print cp.getvotes()
            for item in pid:
                label.append(
                    cp.getvotes()[item])  # to be add lables in the same order

            result[indexgroup].append(label)

    return result
def updatevote(paperupate):
    print paperupate
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    cp.proportion()
    crowdans = cp.getcrowdAns()
    print crowdans
    for item in paperupate:
        ans = (crowdans[item[0]][item[1]])
        if item[2] == 1:
            new_ans = 'Yes'
        else:
            new_ans = 'No'

        ans = new_ans + ',' + ans.split(',')[1] + ',' + ans.split(
            ',')[2] + ',' + ans.split(',')[3]
        print crowdans[item[0]][item[1]]
        crowdans[item[0]][item[1]] = ans
        print crowdans[item[0]][item[1]]

    cp.voting()
    return cp.crowdvotequestion1
def getworkerdistribution():
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    return cp.workerdist()
def getworkereachpaper():
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    cp.proportion()
    return cp.workerforeachpaper
def getvoteforeachpaper():
    cp = CrowsDis("../data/ProtonBeamCrowddata.txt")
    return cp.getvotesofeachworker()