zh4ngx’s gists

zh4ngx / binary_tree_marshal.py

Created October 10, 2013 02:42

Function to marshal binary tree (represented as dict). Done kind of in a hurry (like 20m)....

	# Arbitary binary tree (integers)
	### 1
	### 2 3
	### 6 4 5
	## {1:{"left":2,"right":{3:{"left":4,"right":5}}}}
	## Goal: -> '{1:{left:2,right:{3:{left:4,right:5}}}}'

	# 1
	# 2 3
	## '{1:{left:2,right:3}}'

zh4ngx / lexical_closure.go

Created October 28, 2013 08:22

Quick demo/reminder of lexical closures (in Go)

	// You can edit this code!
	// Click here and start typing.
	package main

	import "fmt"

	func main() {
	fmt.Println("Hello, 世界")
	f := who()
	g := who()

zh4ngx / interview_debug.py

Last active December 28, 2015 17:39

Simple interview question to test basic debugging & communication skills. May require a live person to answer questions (particularly if the candidate doesn't know Python). TODO: rewrite this in a few languages and put in a repo.

	def foo(a, b):
	"""Please document me.
	What am I supposed to do?
	Rename anything you see fit.
	Also, I think I have bugs. Please debug me.
	"""
	bar = {}
	for x in a:
	bar[x] = True

zh4ngx / karabiner-import.sh

Created February 10, 2015 19:09

Quick settings for OS X Karabiner

	#!/bin/sh

	cli=/Applications/Karabiner.app/Contents/Library/bin/karabiner

	$cli set general.dont_remap_internal 1
	/bin/echo -n .
	$cli set remap.commandL2optionL 1
	/bin/echo -n .
	$cli set general.dont_remap_apple_pointing 1
	/bin/echo -n .

zh4ngx / hill_climb_1

Created July 1, 2017 01:39

Basic Hill Climb with variance reduction for MC Policy Evaluation

	import gym
	import numpy as np
	from gym.wrappers.monitoring import Monitor

	env = gym.make('CartPole-v0')
	env = Monitor(env, 'tmp/cart-pole-hill-climb-1', force=True)

	print("Action space: {0}".format(env.action_space))
	print("Observation space: {0}\n\tLow: {1}\n\tHigh: {2}".format(
	env.observation_space,

zh4ngx / hill_climb_2.py

Created July 1, 2017 02:34

CartPole-v0 Hill Climb with MC(10) Eval + Simulated Annealing

	import gym
	import numpy as np
	from gym.wrappers.monitoring import Monitor

	env = gym.make('CartPole-v0')
	env = Monitor(env, 'tmp/cart-pole-hill-climb-2', force=True)

	print("Action space: {0}".format(env.action_space))
	print("Observation space: {0}\n\tLow: {1}\n\tHigh: {2}".format(
	env.observation_space,

zh4ngx / hill_climb_3.py

Created July 1, 2017 03:20

CartPole-v0 Hill Climb + MC(10) + Gaussian Noise (Sigma 0.5)

	import gym
	import numpy as np
	from gym.wrappers.monitoring import Monitor

	MC_POLICY_EVAL_EP = 10
	BASE_NOISE_FACTOR = 0.5
	NUM_POLICY_EVAL = 500


	env = gym.make('CartPole-v0')

zh4ngx / hill_climb_4

Created July 1, 2017 03:53

CartPole - Hill Climb v4 - Correct hill climb and reduced noise & variance (MC-10)

	import gym
	import numpy as np
	from gym.wrappers.monitoring import Monitor

	MC_POLICY_EVAL_EP = 10
	BASE_NOISE_FACTOR = 0.1
	NUM_POLICY_EVAL = 500

	env = gym.make('CartPole-v0')
	env = Monitor(env, 'tmp/cart-pole-hill-climb-4', force=True)

zh4ngx / cart_pole_cem_2.py

Created July 4, 2017 01:28

CartPole-v0 Cross Entropy Method with no bias

	# Source: http://rl-gym-doc.s3-website-us-west-2.amazonaws.com/mlss/lab1.html
	import gym
	import numpy as np
	from gym.spaces import Discrete, Box
	from gym.wrappers.monitoring import Monitor


	# ================================================================
	# Policies
	# ================================================================

zh4ngx / cart_pole_cem_1

Created July 4, 2017 01:35

CartPole-v0 Cross Entropy Method - Affine Function and Base HyperParams

	# Source: http://rl-gym-doc.s3-website-us-west-2.amazonaws.com/mlss/lab1.html
	import gym
	import numpy as np
	from gym.spaces import Discrete, Box
	from gym.wrappers.monitoring import Monitor


	# ================================================================
	# Policies
	# ================================================================

Andy Zhang zh4ngx