henrik

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

dearaujoj

git tag -d TagName && git push origin :refs/tags/TagName

pocotan001

• 🎨 when improving the format/structure of the code
• 🚀 when improving performance
• ✏️ when writing docs
• 💡 new idea
• 🚧 work in progress
• ➕ when adding feature
• ➖ when removing feature
• 🔈 when adding logging
• 🔇 when reducing logging
• 🐛 when fixing a bug

matthewmueller

# OSX for Hackers (Mavericks/Yosemite)
#
# Source: https://gist.github.com/brandonb927/3195465

#!/bin/sh

# Some things taken from here
# https://github.com/mathiasbynens/dotfiles/blob/master/.osx

# Ask for the administrator password upfront

chebee7i

from __future__ import division

import numpy as np

def multinomial_ci(counts, alpha):
    """
    Calculate a simultaneous (1-alpha) * 100 percent confidence interval.

    Parameters
    ----------

ghaiklor

iTerm2

NOTE: this gist is outdated, refer to this repository instead - https://github.com/ghaiklor/iterm-fish-fisher-osx

Install iTerm 2

• Download and install iTerm2 (it has better color fidelity than the built in Terminal).

Install Color Scheme

domenic

Redirecting GitHub Pages after a repository move

The problem

You have a repository, call it alice/repo. You would like to transfer it to the user bob, so it will become bob/repo.

However, you make heavy use of the GitHub Pages feature, so that people are often accessing https://alice.github.io/repo/. GitHub will helpfully redirect all of your repository stuff hosted on github.com after the move, but will not redirect the GitHub Pages hosted on github.io.

The solution

rspeer

leferrad

#!/usr/bin/env python
# -*- coding: utf-8 -*-

""""""

import matplotlib
matplotlib.use("TkAgg")

from datetime import datetime as dt
import numpy as np

ncammarata

import scipy.ndimage as nd
from scipy.ndimage import gaussian_filter
import lucid.optvis.transform as transform

def mean_alpha():
    def inner(T):
        input_t = T("input")
        return 1.0 - tf.reduce_mean(input_t[..., 3:])

    return objectives.Objective(inner)