thesamovar

josejimenezluna

import numpy as np
from numpy.linalg import norm, solve
from scipy.spatial.distance import cdist
from sklearn.neighbors import kneighbors_graph


def phi(l, mu):
    return (mu * (np.sqrt(l) - 1)**2)

systemfreund

#!/bin/bash

# dependencies:
# curl
# culicue - curl wrapper to make oauthv1 requests (https://github.com/decklin/curlicue/blob/master/curlicue)
# jq - filter json from twitter api and transform to a structure mattermost is expecting

# credentials file can be created with the curlicue-setup script
credentials=/home/me/credentials.conf
webhook='https://yourmattermost.server/hooks/1mjxx6amd52q8doxzy16o75adh'

ntamas

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Hierarchical link clustering
============================

:Author: Tamás Nepusz

This is an implementation of the hierarchical link clustering algorithm of Ahn
et al. The results provided by this implementation match those of the original