Júlio César Batista ejulio

## volume-silo.py
# -*- coding: utf-8 -*-
import json
from argparse import ArgumentParser

AREA_QUADRADO = 40 * 40
AREA_SILO = 600 * 320 * 320


def parse_args():
    ap = ArgumentParser()

## 0BOOTSTRAP.md

      
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                ejulio
                / 0BOOTSTRAP.md
            
            
              Created
              October 2, 2017 14:19
                — forked from inventti-silvio/0BOOTSTRAP.md
            
          
    BOOTSTRAP


## dados-e-caracteristicas.py
import numpy as np
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.multiclass import OneVsOneClassifier
from sklearn.svm import SVC
from sklearn import cross_validation
from sklearn.metrics import confusion_matrix
import argparse

## index.html
<!DOCTYPE html>
<html>
	<head>
		<title>The Dolly Zoom Effect</title>
		<style type="text/css">
    		body {
    			margin: 0;
    			padding: 0;
    		}
    	</style>

## codigo-completo.html
<!DOCTYPE html>
<html>
    <head>
    	<meta charset="utf-8">
    	<title>Sistema solar three.js</title>

    	<style type="text/css">
    		body {
    			margin: 0;
    			padding: 0;

## calcular-radianos.js
function calcularRadianos(grau)
{
    return grau * Math.PI / 180;
}

## codigo-final-1.html
<!DOCTYPE html>
<html>
    <head>
        <meta charset="utf-8">
        <title>Sistema solar three.js</title>

        <style type="text/css">
            body {
                margin: 0;
                padding: 0;

## ModelRepresentation.cs
class Person
{
  public int Id { get; set; }
  public string Name { get; set; }
  public int Age { get; set; }

  public string ToString()
  {
    return String.Format("{0}: {1} - {2}", Id, Name, Age);
  }

## Math.js
var arr = [5,8,9,6,3,4,74,85,21,2,3,56,8,5,4,789,465,5454,4,546,4,646,1,64];
Math.min.apply(null, arr);
Math.max.apply(null, arr);

## ImageProcessor.js
self.addEventListener('message', function(evt)
{
    // pegamos a propriedade data onde contém os dados enviados por postMessage(data)
    var data = evt.data;
    // aplicamos o filtro
    ImageProcessor.applyGrayscale(data.data);
    // notificamos a thread principal com o filtro aplicado
    postMessage(data);
});
	# -- coding: utf-8 --
	import json
	from argparse import ArgumentParser

	AREA_QUADRADO = 40 * 40
	AREA_SILO = 600 * 320 * 320


	def parse_args():
	ap = ArgumentParser()
	import numpy as np
	from sklearn.datasets import fetch_20newsgroups
	from sklearn.feature_extraction.text import CountVectorizer
	from sklearn.feature_extraction.text import TfidfTransformer
	from sklearn.multiclass import OneVsOneClassifier
	from sklearn.svm import SVC
	from sklearn import cross_validation
	from sklearn.metrics import confusion_matrix
	import argparse
	<!DOCTYPE html>
	<html>
	<head>
	<title>The Dolly Zoom Effect</title>
	<style type="text/css">
	body {
	margin: 0;
	padding: 0;
	}
	</style>
	function calcularRadianos(grau)
	{
	return grau * Math.PI / 180;
	}
	class Person
	{
	public int Id { get; set; }
	public string Name { get; set; }
	public int Age { get; set; }

	public string ToString()
	{
	return String.Format("{0}: {1} - {2}", Id, Name, Age);
	}
	var arr = [5,8,9,6,3,4,74,85,21,2,3,56,8,5,4,789,465,5454,4,546,4,646,1,64];
	Math.min.apply(null, arr);
	Math.max.apply(null, arr);
	self.addEventListener('message', function(evt)
	{
	// pegamos a propriedade data onde contém os dados enviados por postMessage(data)
	var data = evt.data;
	// aplicamos o filtro
	ImageProcessor.applyGrayscale(data.data);
	// notificamos a thread principal com o filtro aplicado
	postMessage(data);
	});