janosh

import argparse
import subprocess
from typing import Literal

__author__ = "Janosh Riebesell"
__date__ = "2022-07-04"

description = """
Batch merge bot-created PRs. Uses the GitHub CLI (`brew install gh`) which must be
authenticated, i.e. `gh auth status` must exit 0. By default asks for confirmation

janosh

Compiling VASP on M1 Mac

Written by Alex Ganose @utf and Janosh Riebesell @janosh. Published 2022-03-28. Last updated 2024-03-30.

1. Install Xcode command line tools:

   xcode-select --install

janosh

<script>
  // This component uses the Google Maps Places API to turn user text input into a
  // formatted address and lat/lng coordinates.
  import { onMount } from 'svelte'
  import { session } from '$app/stores'

  export let selectHandler
  export let placeholder = ``
  export let required = false
  export let name = ``

janosh

import os
import sys

_, dirname, prefix = sys.argv

os.chdir(dirname)

files = sorted(f for f in os.listdir() if not f.endswith(".xmp"))

janosh

import marked from 'marked'

// Import and compile markdown files. Adapted from
// https://github.com/xiaofuzi/rollup-plugin-md/blob/master/src/index.js
export function markdown(options = {}) {
  if (options.marked) marked.setOptions(options.marked)

  return {
    name: `markdown`,
    transform(md, id) {

janosh

const argFact = (compareFn) => (array) => array.map((el, idx) => [el, idx]).reduce(compareFn)[1]

const argMax = argFact((min, el) => (el[0] > min[0] ? el : min))
const argMin = argFact((max, el) => (el[0] < max[0] ? el : max))

argMin([42, -5, 3.14, 1e6]) // 1
argMax([42, -5, 3.14, 1e6]) // 3

janosh

#!/bin/sh
# Shell script to upgrade a Python 2 project to Python 3.
# If it's a TensorFlow project consider running afterwards:
# tf_upgrade_v2 --intree . --outtree . --reportfile tf2_report.txt

# [ -x "$(command -v some_binary)" ] checks whether some_binary is
# in path and executable. See https://stackoverflow.com/a/26759734.


if [ -x "$(command -v 2to3)" ]; then

janosh

import * as tf from '@tensorflow/tfjs'

export const tfMultivariateNormal = (mu, sigma) => {
  [mu, sigma] = [tf.tensor(mu), tf.tensor(sigma)]
  const [dim] = mu.shape
  if (!sigma.shape.every(d => d === dim))
    throw new Error(`dimension mismatch in tfMultivariateNormal()`)
  const Z = ((2 * Math.PI) ** dim * tfDet(sigma).arraySync()) ** -0.5
  return x => {
    x = tf.tensor(x)

janosh

#!/bin/bash

find "$1" -name "*.pdf" | while read file; do
  path=${file%/*} 
  basename=${file##*/}
  ext=${basename##*.}
  filename=${basename%.*}
  gs -sDEVICE=pdfwrite -dCompatibilityLevel=1.4 -dPDFSETTINGS=/ebook -dNOPAUSE -dBATCH -dQUIET -sOutputFile="$path/$filename-min.pdf" "$file"
done

janosh

#!/bin/bash

find $1 -type f -iname "*.pdf" -exec sh -c 'convert -density 100 -flatten "$1"[0] "$1".png' x {} \;