evanthebouncy

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hi I am evanthebouncy

evanthebouncy / cross.py

Created July 18, 2019 20:24

cross

	from PIL import Image, ImageDraw
	import numpy as np

	L = 1028

	img = Image.new('RGBA', (L, L), (255, 0, 0, 0))
	center = (L / 2, L / 2)

	def scale_w_by_d(d):
	return int(d / (L / 2) * 32)

evanthebouncy / auto_enc_real.py

Created July 3, 2019 21:57

trying to auto-encode a real number

	import torch
	import torch.nn as nn
	from torch.autograd import Variable
	import numpy as np
	import torch.nn.functional as F
	import random
	from tqdm import tqdm

	if torch.cuda.is_available():
	def to_torch(x, dtype, req = False):

evanthebouncy / beam.py

Created May 21, 2019 03:54

beam search

	import random
	import math
	import numpy as np

	# a random mock-up environment with a single state of a float
	# the goal is to get the float as close to 0 as possible with 2 possible moves
	# x <- x + 1
	# x <- cos(x)
	class Env:
	def __init__(self):

evanthebouncy / dagger.py

Created March 13, 2019 15:38

	def train_dagger(env, teacher, student):
	init_state = env.reset()
	s_a_agg = []

	for i in range(100):

	# learning
	print ("learning . . . ", i)
	trace = get_rollout(env, init_state, student)
	state_sample = [x[0] for x in trace]

evanthebouncy / planet.py

Last active January 30, 2019 19:27

simple planetary simulation

evanthebouncy / is_fair.py

Created September 12, 2018 05:15

	# consider the following game:
	# we each have a coin, and we choose to vote either head or tail
	# if the result is HH or TT, you gain 3 dollars or 1 dollars from me respectively
	# but if the result is HT or TH, you lose 2 dollars to me
	# would you play this game?

	# expectation for a mixture strategy of x probabiliyt of head for u and y probabiliyt of head fo rme
	def f(x,y):
	return 3xy - 2(1-x)y - 2x(1-y) + 1(1-x)(1-y)

evanthebouncy / coin.py

Created June 3, 2018 06:26

python stuff

	import random

	def flip():
	return 'H' if random.random() > 0.5 else 'T'

	def trial():
	flips = [flip() for _ in range(100)]
	for i in range(1, 99):
	last = flips[i]
	lastlast = flips[i-1]

evanthebouncy / try2.py

Created May 18, 2018 01:05

trying to learn pytorch rnn by building a contextualized sequence gneerator

	import cv2
	import torch
	from torch import nn
	import torch.nn.functional as F
	import random

	seq_length = 10
	token_size = 4
	hidden_size = 20
	n_layer = 2

evanthebouncy / battleship.py

Created April 26, 2018 17:23

battleship environment

	# length of board
	L = 10
	boat_shapes = [(2,4), (1,5), (1,3), (1,3), (1,3)]

	def get_board():
	total_mass = sum([x[0]*x[1] for x in boat_shapes])
	def _gen_boats():
	ret = np.zeros([L, L])
	occupied = []
	poses = []

evanthebouncy / do_not_run.html

Last active September 15, 2021 04:35

do not run this

	<!DOCTYPE html>
	<html>
	<body>

	<canvas id="myCanvas" width="800" height="800"
	style="border:1px solid #d3d3d3;">
	Your browser does not support the canvas element.
	</canvas>

	<script>