abhishek-ghose

import numpy as np


def kendall_w(scores):
    """
    :param scores: rows correspond to category levels, e.g., for QS this would be unc. sampling, CAL etc, and the
        columns correspond to the scores.
    :return:
    """
    if scores.ndim!=2:

abhishek-ghose

import numpy as np, itertools
import pandas as pd
import ot
from matplotlib import pyplot as plt
from matplotlib.collections import LineCollection
import seaborn as sns; sns.set()
from scipy.stats import multivariate_normal as mvn, norm
from sklearn.cluster import KMeans
import os
from datetime import datetime

abhishek-ghose