ili3p

import pandas as pd
import numpy as np
from numba import jit

def calc_hurst(series: pd.Series, n_wins: int = 300):
    changes = series.diff().dropna().astype(np.float32).values
    max_w = changes.shape[0] - 1

    win_sizes = np.linspace(np.log10(10), np.log10(max_w), num=n_wins)
    win_sizes = np.unique(np.power(10, win_sizes).astype(np.int16))

ili3p

import torch
import time
from scipy.stats import kendalltau

def kendall(x, y):
    n = x.shape[0]
    
    def sub_pairs(x):
        return x.expand(n,n).T.sub(x).sign_()
    

ili3p

local words = torch.load(opt.words) -- it's a tds.Hash
local word2vec = torch.FloatTensor(opt.vocabsz, opt.dim)
local buffsz = 2^13 -- == 8k
local f = io.input(opt.input)
local done = 0
local unk

-- read huge word2vec file with 2,196,017 lines
while true do
    local lines, leftover = f:read(buffsz, '*line')