Lower bound of Wilson score confidence interval for a Bernoulli parameter
All implementations use 95% probability.
pos
is the number of positive votes, n
is the total number of votes.
const Web3 = require('web3'); | |
const provider = new Web3.providers.HttpProvider('http://localhost:8549'); | |
const web3 = new Web3(provider); | |
let acc = web3.eth.accounts.create(); | |
let last = acc.address[acc.address.length-2]; | |
let last2 = acc.address.slice(acc.address.length - 2, acc.address.length ); | |
console.log(last2); | |
while(last2 != '00' ){ |
""" | |
Exports Issues from a list of specified repository to a CSV file | |
Credits go to https://gist.github.com/unbracketed/3380407#file-export_repo_issues_to_csv-py for the initial work, but I had to adjust it a bit | |
FYI: you need to install 'requests' before, best via pip: "$ sudo pip installs requests" | |
""" | |
import csv | |
import requests |
import discord | |
import asyncio | |
class Bot(discord.Client): | |
def __init__(self, token): | |
super().__init__() | |
self.token = token | |
print('%s->' % token, end='') | |
async def on_ready(self): |
# Published on Docker Hub with above user alexellisio. | |
# If you want to rebuild your own copy, follow below instructions | |
# Build this on each type of machine so you have the correct CPU extensions. | |
FROM alexellisio/boostbase | |
RUN git clone -b Linux https://github.com/nicehash/nheqminer.git | |
RUN cd nheqminer/cpu_xenoncat/Linux/asm/ && sh assemble.sh && cd ../../../Linux_cmake/nheqminer_cpu && cmake . && make | |
ENTRYPOINT ["./nheqminer/Linux_cmake/nheqminer_cpu/nheqminer_cpu"] |
Lower bound of Wilson score confidence interval for a Bernoulli parameter
All implementations use 95% probability.
pos
is the number of positive votes, n
is the total number of votes.
// Node.js implementation of Evan Miller's algorithm for ranking stuff based on upvotes: | |
// http://www.evanmiller.org/how-not-to-sort-by-average-rating.html | |
const stats = require('simple-statistics') | |
const lower_bound = (upvotes, n = 0, confidence = 0.95) => { | |
if (n === 0) return 0 | |
// for performance purposes you might consider memoize the calcuation for z | |
const z = stats.probit(1-(1-confidence)/2) |
db.votes.aggregate([{
$lookup: {
from: "users",
localField: "createdBy",
foreignField: "_id",
#!/bin/bash | |
GARBAGE="/var/lib/docker/aufs/diff" | |
du -hd 1 $GARBAGE | sort -hrk 1 | head -25 | |
find $GARBAGE -maxdepth 1 -name *-removing -exec rm -rf '{}' \; |
<html> | |
<head> | |
<style> | |
*{ | |
font-family: arial; | |
font-size: 11px; | |
} | |
table{ | |
border-collapse: collapse; | |
border: 1px solid silver; |
' Example function call: =BuildHTMLTable(A1:D5) | |
Public Function BuildHTMLTable(rng As Range) As String | |
' Given a Range of Cells, build a Bootstrap HTML table, using the formatting | |
' specified in the Excel cells. If "header" is specified to equal true, assumes | |
' the first row in the table is a header row. | |
Dim last_r As Long: last_r = rng.Cells(1, 1).Row | |
Dim tds As New Collection | |
Dim txt As String | |
Dim isFirstRow As Boolean: isFirstRow = True |