Adriel Santos ADCDS

## designer.html
<link rel="import" href="../core-icon-button/core-icon-button.html">
<link rel="import" href="../core-toolbar/core-toolbar.html">
<link rel="import" href="../core-header-panel/core-header-panel.html">

<polymer-element name="my-element">

  <template>
    <style>
      :host {
        position: absolute;

## Exercício de Álgebra Relacional 1 em ReLax
group: Exercicio1


PACIENTE = {
	idPaciente:number, nomePaciente:string, cidade:string
	1,"João da Silva","Alfenas"
	2,"Rita Duarte","Lavras"
	3,"Marcos Costa","Belo Horizonte"
	4,"Lara Campos","São Paulo"
}

## Algebra Relacional Exercicios Slide 2 ReLax

group: exericicios_slide2


agencia = {
	nome_agencia:string, cidade_agencia:string, ativo:number
}
cliente = {
	nome_cliente:string, rua_cliente:string, cidade_cliente:string
}

## jquery-datatables-webpack
Here's how to make jQuery DataTables work with npm and webpack. This is the simplest way I found to do it.
See the previous revision of this gist for a way to do it with forcing AMD to be disabled if you need that.

Install DT core: npm install datatables.net
Install a DT style: npm install datatables.net-dt

Then to initialize DT in your app, do this in your main entry point:

// you can use import or require
import dt from 'datatables.net';

## multiProcessingGraph.py
# https://pypi.python.org/pypi/Dijkstar
from dijkstar import Graph, find_path
from multiprocessing import Process, Manager
import collections

manager = Manager()
class GraphProxy(Graph):

	def __init__(self, data=None):
		# replaces default _data and _incoming attributes to a equivalent object (dict), but in shared memory

## convert_to_string_map.cpp
#include <stdio.h>
#include <stdlib.h>
#include <map>
#include <functional>
#include <string>
#include <iostream>

template <typename T1, typename T2>
static std::map<std::string, std::string> convert_to_string_map(std::map<T1, T2> _map_in,
        std::function<std::pair<std::string, std::string>(T1, T2) > converter) {

## kmeansExample.py
#############################################################################
# Full Imports

import math
import random

"""
This is a pure Python implementation of the K-Means Clustering algorithmn. The
original can be found here:
http://pandoricweb.tumblr.com/post/8646701677/python-implementation-of-the-k-means-clustering

## kmeans.py
# Copyright Mathieu Blondel December 2011
# License: BSD 3 clause

import numpy as np
import pylab as pl

from sklearn.base import BaseEstimator
from sklearn.utils import check_random_state
from sklearn.cluster import MiniBatchKMeans
from sklearn.cluster import KMeans as KMeansGood

## index.html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Login</title>
</head>
<body>
<button id="login">Login</button>
<div id="fb-root"></div>
<script type="text/javascript" src="main.js"></script>

## data.php
<?php

/*
 * Script:    DataTables server-side script for PHP and MySQL
 * Copyright: 2012 - John Becker, Beckersoft, Inc.
 * Copyright: 2010 - Allan Jardine
 * License:   GPL v2 or BSD (3-point)
 */

class TableData {
	<link rel="import" href="../core-icon-button/core-icon-button.html">
	<link rel="import" href="../core-toolbar/core-toolbar.html">
	<link rel="import" href="../core-header-panel/core-header-panel.html">

	<polymer-element name="my-element">

	<template>
	<style>
	:host {
	position: absolute;
	group: Exercicio1


	PACIENTE = {
	idPaciente:number, nomePaciente:string, cidade:string
	1,"João da Silva","Alfenas"
	2,"Rita Duarte","Lavras"
	3,"Marcos Costa","Belo Horizonte"
	4,"Lara Campos","São Paulo"
	}

	group: exericicios_slide2


	agencia = {
	nome_agencia:string, cidade_agencia:string, ativo:number
	}
	cliente = {
	nome_cliente:string, rua_cliente:string, cidade_cliente:string
	}
	Here's how to make jQuery DataTables work with npm and webpack. This is the simplest way I found to do it.
	See the previous revision of this gist for a way to do it with forcing AMD to be disabled if you need that.

	Install DT core: npm install datatables.net
	Install a DT style: npm install datatables.net-dt

	Then to initialize DT in your app, do this in your main entry point:

	// you can use import or require
	import dt from 'datatables.net';
	# https://pypi.python.org/pypi/Dijkstar
	from dijkstar import Graph, find_path
	from multiprocessing import Process, Manager
	import collections

	manager = Manager()
	class GraphProxy(Graph):

	def __init__(self, data=None):
	# replaces default _data and _incoming attributes to a equivalent object (dict), but in shared memory
	#include <stdio.h>
	#include <stdlib.h>
	#include <map>
	#include <functional>
	#include <string>
	#include <iostream>

	template <typename T1, typename T2>
	static std::map<std::string, std::string> convert_to_string_map(std::map<T1, T2> _map_in,
	std::function<std::pair<std::string, std::string>(T1, T2) > converter) {
	#############################################################################
	# Full Imports

	import math
	import random

	"""
	This is a pure Python implementation of the K-Means Clustering algorithmn. The
	original can be found here:
	http://pandoricweb.tumblr.com/post/8646701677/python-implementation-of-the-k-means-clustering
	# Copyright Mathieu Blondel December 2011
	# License: BSD 3 clause

	import numpy as np
	import pylab as pl

	from sklearn.base import BaseEstimator
	from sklearn.utils import check_random_state
	from sklearn.cluster import MiniBatchKMeans
	from sklearn.cluster import KMeans as KMeansGood
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<title>Login</title>
	</head>
	<body>
	<button id="login">Login</button>
	<div id="fb-root"></div>
	<script type="text/javascript" src="main.js"></script>
	<?php

	/*
	* Script: DataTables server-side script for PHP and MySQL
	* Copyright: 2012 - John Becker, Beckersoft, Inc.
	* Copyright: 2010 - Allan Jardine
	* License: GPL v2 or BSD (3-point)
	*/

	class TableData {