eyecatchup

git commit stats

Commands to get commit statistics for a Git repository from the command line -
using git log, git shortlog and friends.

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d-akara

Experimental Safe JavaScript Navigation

Implemented using ES6 Proxies and Symbols

The purpose of this function is to provide a way to avoid deep nested conditionals when traversing a hierarchy of objects. Some languages use an operator such as '?.' to perform this capability. This is sometimes called safe navigation or null conditional operators.

You can somewhat think of this as how a xpath select works. If any nodes along the path are not found, your result is simply not found without throwing an exception and without needing to check each individual node to see if it exists.

Suggestions for improvements welcome!

thomastweets

import Image
import sys
import glob
import ImageOps

# Trim all png images with white background in a folder
# Usage "python PNGWhiteTrim.py ../someFolder"

try:
    folderName = sys.argv[1]

klaftertief

• Star this gist to see the talk at ReactiveConf 2016.
• Retweet to spread the word.
• Have a look at this blog post to see other proposals.
• Try elm-search to see what this is all about.

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An API search engine in Elm for Elm

Elm is a statically typed functional language that compiles to JavaScript. It's well-known for its developer experience: the compiler provides nice error messages, the package system enforces semantic versioning for all published packages and makes sure every exposed value or type has some documentation and type annotations.

peteflorence

Here's a simple implementation of bilinear interpolation on tensors using PyTorch.

I wrote this up since I ended up learning a lot about options for interpolation in both the numpy and PyTorch ecosystems. More generally than just interpolation, too, it's also a nice case study in how PyTorch magically can put very numpy-like code on the GPU (and by the way, do autodiff for you too).

For interpolation in PyTorch, this open issue calls for more interpolation features. There is now a nn.functional.grid_sample() feature but at least at first this didn't look like what I needed (but we'll come back to this later).

In particular I wanted to take an image, W x H x C, and sample it many times at different random locations. Note also that this is different than upsampling which exhaustively samples and also doesn't give us fle

ardok

/* eslint-disable */
const common = require('../jest-config.common');
module.exports = Object.assign({}, common, {
  "coverageDirectory": "<rootDir>/coverage/browser",
  "testMatch": [
    "**/test/browser/**/*.test.js"
  ],
  "setupFiles": [
    "<rootDir>/src/test/browser/setup.js"
  ]

Francesco149

on linux 4.19, I get

error creating new backup file '/var/lib/dpkg/status-old': Invalid cross-device link

when trying to install stuff on a ubuntu docker container. this seems to be an issue with metacopy https://www.spinics.net/lists/linux-unionfs/msg06109.html

issue can be worked around by running

cobalamin

# I used the commands below not only on the command line, but also set up the aliased commands as global keyboard shortcuts.
# This can be useful if you have a keyboard that lacks media keys, or if the media keys don't behave exactly as you want them to.

# Everything below assumes PulseAudio on top of ALSA.
alias volup="amixer set 'Master' 10%+" # Using amixer because pacmd/pactl can increase beyond 100% volume, which I don't want.
alias voldn="amixer set 'Master' 10%-"
# This assumes sink port #1 and the naming of these ports. Check `pacmd list-sinks` and make adjustments if necessary.
alias outsp='pacmd "set-sink-port 1 analog-output;output-speaker'       # output to speakers
alias outhp='pacmd "set-sink-port 1 analog-output;output-headphones-1'  # output to headphones

fgolemo

import numpy as np
import math

import torch
from torchvision import datasets
import cv2 # OpenCV, this is only used for visualization, see bottom of file

def rotation_matrix(axis, theta):
    """
    Generalized 3d rotation via Euler-Rodriguez formula, https://www.wikiwand.com/en/Euler%E2%80%93Rodrigues_formula

IvanYashchuk

using PyFenicsAD
using Zygote
using PyCall
using Turing
import LinearAlgebra: norm
using Random, Distributions

fenics = pyimport("fenics")
fenics.set_log_level(fenics.LogLevel.ERROR)
fa = pyimport("fenics_adjoint")