VictorGarritano

0       963     429     1949    2979    1504    206     2976    3095
     963     0       671     996     2054    1329    802     2013    2142
      429     671     0       1616    2631    1075    233     2684    2799
     1949    996     1616    0       1059    2037    1771    1307    1235
      2979    2054    2631    1059    0       2687    2786    1131    379
     1504    1329    1075    2037    2687    0       1308    3273    3053
      206     802     233     1771    2786    1308    0       2815    2934
     2976    2013    2684    1307    1131    3273    2815    0       808
      3095    2142    2799    1235    379     3053    2934    808     0

VictorGarritano

import numpy as np 

def trapezio(k, n, x0, xn, func, f_aux):
	h = float((xn - x0)) / (n-1)
	xs = np.linspace(x0, xn, n)
	summation = func(f_aux, k, x0) + func(f_aux, k, xn) 
	
	for idx in range(1, n-1):
		summation += 2*func(f_aux, k, xs[idx])

VictorGarritano

import pandas as pd
import numpy as np
from sklearn.model_selection import GridSearchCV
from sklearn import metrics
import matplotlib.pyplot as plt
import xgboost as xgb
from xgboost.sklearn import XGBClassifier

df = pd.read_csv('new_train.csv')
print 'number of features', df.shape[1]

VictorGarritano

def merge_sort(alist):
	'''
	###########
	DIVISAO
	###########
	'''	
	print 'Splitting ', alist

	#Se a lista tiver mais do que um elemento...
	if len(alist) > 1:

VictorGarritano

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

from OpenGL.GL import *
from OpenGL.GLUT import *
from OpenGL.GLU import *
import sys
import copy
from math import cos, sin
from plyfile import PlyData, PlyElement

VictorGarritano

# -*- coding: utf-8 -*-
"""
Queda livre via Diferenças Finitas

a = -g
x'' = - g
.
.
.

VictorGarritano

import numpy as np 

def sigmoid(x):
    return 1.0/(1.0+np.exp(-x))

def sigmoid_prime(x):
    return sigmoid(x)*(1-sigmoid(x))

class neural_net:
    def __init__(self, eta, numrounds, hidden_nodes):

VictorGarritano

import nltk

def ngram(sentence, n):
    input_list = nltk.word_tokenize(sentence)
    return zip(*[input_list[i:] for i in xrange(n)])
	
	"""
x = 'Hi, my name is Eric. I work at Syncano and deeply believe all people have the right to freedom'
ngram(x,3)

VictorGarritano

clear()
function[C] = calculaCosseno(a,b)
    C = (a'*b)/(norm(a)*norm(b));
endfunction

function[] = plota(v_i)
    t = 0:0.1:5
    v_i = v_i/norm(v_i)
    plot(t*v_i(1),t*v_i(2))
endfunction

VictorGarritano

function[C] = calculaCosseno(a,b)
      C = (a'*b)/ (norm(a)*norm(b));
endfunction


function[] = plota(v_i)
    t = 0:0.1:5
    v_i = v_i/norm(v_i)
    plot(t*v_i(1),t*v_i(2))
endfunction