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import gym
from gym import wrappers
import numpy as np
import matplotlib.pyplot as plt

"""
 For practicing reinforcement learning

 observation:
    (position,velocity)

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#!/usr/bin/env bash

function _func_create_md(){
	kyo=`date +%y%m%d`
	kyo_md="${kyo}.md"
	if ! [ -e "${kyo_md}" ]; then
		: > "${kyo_md}"
	fi
}

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#!/usr/bin/env bash

mass=`grep ^質量 "$1" | sed -e "s/[^0-9.]//g"`

echo "<mass value=\"$mass\"/>"

# extract ixx, ixy, ixz
temp=`grep Ixx "$1" | sed -e "s/[a-z = A-Z]//g"`

declare xx=() # declare matrix

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

"""
 [summary]
 mm 単位になっているstlファイルを m 単位に変換する

[description]
 python mm_to_m.py sample.stl
 のように実行すると、sample_m.stlという名前の m 単位に変換したファイルを保存する。

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% Simulation of Kalman_Filter
% In this script, error_ellipse function is used. Please download here: 
% https://www.mathworks.com/matlabcentral/fileexchange/4705-error-ellipse

clear; close all;
fig = figure;
hold on;

% Initial State
x0 = [0, 0].';

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% Simulation of Kalman_Filter
% In this script, error_ellipse function is used. Please download here: 
% https://www.mathworks.com/matlabcentral/fileexchange/4705-error-ellipse

clear; close all;
fig = figure;
hold on;

% Initial State
x0 = [0, 0].';

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# after run sh 'build_env_colab.sh', run
# import sys
# sys.path.append('/usr/local/lib/python3.6/site-packages/')
# in the python.

# To run the gym in server, pyvirtualdisplay is the best solution
# see https://qiita.com/ikeyasu/items/ec3c88ce13a2d5e41f26

# install anaconda
wget https://repo.anaconda.com/archive/Anaconda3-5.1.0-Linux-x86_64.sh

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apt update 
apt install -y python-numpy python-dev cmake zlib1g-dev libjpeg-dev xvfb ffmpeg xorg-dev python-opengl libboost-all-dev libsdl2-dev swig

pip3 install pyvirtualdisplay piglet gym torch torchvision
pip3 install "gym[atari]"

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