Mukai Ven Kyoshiro ven-kyoshiro

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pep8

Exploration is all we need.

ven-kyoshiro / cartpole_pg.py

Last active September 14, 2017 17:10 — forked from shanest/cartpole_pg.py

Policy gradients for reinforcement learning in TensorFlow (OpenAI gym CartPole environment)

	#!/usr/bin/env python

	import gym
	import numpy as np
	import tensorflow as tf


	class PolicyGradientAgent(object):

	def __init__(self, hparams, sess):

ven-kyoshiro / mnist_cnn_bn.py

Created April 7, 2018 07:29 — forked from tomokishii/mnist_cnn_bn.py

MNIST using Batch Normalization - TensorFlow tutorial

	#
	# mnist_cnn_bn.py date. 5/21/2016
	# date. 6/2/2017 check TF 1.1 compatibility
	#

	from __future__ import absolute_import
	from __future__ import division
	from __future__ import print_function

	import os

ven-kyoshiro / outbreak_model.py

Last active May 6, 2018 05:01

This is simple implementation of outbreak model introduced at '情報学修論' at Waseda University graduate school.

ven-kyoshiro / adaboost_test.py

Last active May 9, 2018 00:30

Adaboostの実装ですが，Uを自由に変更できます．(参考文献：情報学習論講義資料)

	# -- coding:utf-8 --
	import numpy as np
	import matplotlib
	matplotlib.use('Agg')
	import matplotlib.pyplot as plt
	import scipy.optimize as optimize
	from multiprocessing import Pool
	import os
	from tqdm import tqdm
	import multiprocessing as multi

ven-kyoshiro / gym_classic_error_in_server.py

Created August 30, 2018 02:43

gym_classic_error_in_server

	import chainer
	import chainer.functions as F
	import chainer.links as L
	import chainerrl
	import gym
	import numpy as np

	# 描画用
	import matplotlib as mpl
	mpl.use('Agg')

ven-kyoshiro / error.py

Created September 5, 2018 12:08

openai gym's render cannot work with matplotlib

	import matplotlib
	# matplotlib.use("TkAgg")
	import matplotlib.pyplot as plt
	import gym
	import numpy as np

	def main():
	env = gym.make('CartPole-v0')
	env.reset()
	_ = env.render(mode='rgb_array')

ven-kyoshiro / tunstall.py

Created December 4, 2018 01:20

tunstall.py

ven-kyoshiro / color_wheel.py

Last active January 23, 2019 08:37

you can convert xy to RGB

	import matplotlib.pyplot as plt
	import math
	def xy2color(x,y):
	norm = min(1.0,(xx + yy)**(1/2))
	rad = math.atan2(x,y)+math.pi
	if rad < math.pi*2/3:
	ratio = rad/(math.pi*2/3)
	r = 1.-ratio
	g = ratio
	b = 0

ven-kyoshiro / multivariable_normal_sigma.py

Created March 14, 2019 14:16

able to plot sigma area of multivariable normal distribution

	import numpy as np
	import matplotlib.pyplot as plt
	import matplotlib.patches as pat
	rot = lambda th:np.array([[np.cos(th),-np.sin(th)],[np.sin(th),np.cos(th)]])

	mu = np.array([0.,0.])
	S = np.array([[1,0],[0,6]]) @ rot(np.pi/3)
	x = np.random.multivariate_normal(mu, S,10000)
	fig = plt.figure(figsize=(10, 10))
	ax = fig.add_subplot(111)

ven-kyoshiro / least_square_polynomial_1d.py

Created May 14, 2019 01:07

This is a sample code of exercise in https://esslab.jp/~ess/ja/teaching/2019/cgo/.

	import pprint
	import numpy as np
	class PolynomialPredictor(object):
	def __init__(self,u,v,n=1,debug=True):
	self.n = n
	u = np.array(u)
	A = np.array([u**i for i in range(self.n,-1,-1)]).T
	b = np.array([v]).T
	self.alpha = np.matmul(np.matmul( np.linalg.inv( np.matmul(A.T,A) ), A.T ), b )
	self.sum_of_se = np.sum((np.matmul(A,np.fliplr(self.alpha))-b)**2)