iassael

/**
 * Calculates the remaining inventory, current average buy price, total cost and total gains using FIFO (First In First Out) method.
 * The function expects three parameters: transactionsType, transactionQuantities and transactionPrices sorted by date.
 *
 * Inspired by: https://www.allstacksdeveloper.com/2022/09/fifo-stock-portfolio-google-sheets.html
 * 
 * @param {string[] | string} transactionsType - An array or a single string representing transaction types. Each string should be either 'B' for buy or 'S' for sell.
 * @param {number[] | number} transactionQuantities - An array or a single number representing the quantities for each transaction.
 * @param {number[] | number} transactionPrices - An array or a single number representing the prices for each transaction.
 * @throws Will throw an error if transactionPrices and transactionQuantities are not arrays or if their lengths are not equal.

maxried

This script goes into /etc/kernel/postinst.d. You have to make it executable by root, e.g. chown root:root /etc/kernel/postinst.d/00-signing ; chmod u+rx /etc/kernel/postinst.d/00-signing. It assists you with automatically signing freshly installed kernel images using the machine owner key in a way similar to what dkms does. This is mainly useful if you want to use mainline kernels on Ubuntu on Secure Boot enabled systems. This needs shim-signed to be set up. If you have questions this one might help you: While I made this for Ubuntu 20.04, it should work on current Debian based distributions. YMMV.

dzhuang

import ply.lex, argparse, io

# modified from https://gist.github.com/amerberg/a273ca1e579ab573b499

#Usage
# python stripcomments.py input.tex > output.tex
# python stripcomments.py input.tex -e encoding > output.tex

# Modification:
# 1. Preserve "\n" at the end of line comment

bshillingford

function arxiv-authors() {
    if [ $# -ne 1 ]; then
        echo "Usage: arxiv-authors arxiv_url_or_id"
        echo "Prints authors' names, one per line."
    else
        if [[ $1 == http* ]]; then
            url=$1
        else
            url=http://arxiv.org/abs/$1
        fi

albanD

require 'nn'
require 'stn'

------
-- Prepare your localization network
local localization_network = torch.load('your_locnet.t7')

------
-- prepare both branches of the st
local ct = nn.ConcatTable()

danoneata

import numpy as np
import pdb

from sklearn.datasets import make_classification
from sklearn.mixture import GaussianMixture as GMM


def fisher_vector(xx, gmm):
    """Computes the Fisher vector on a set of descriptors.