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'''
Simple binary/hexadecimal clock written in python.

This programm is an example for my "introduction to numerical analysis class" at Universidad Autonoma de Yucatan.

Feel free to copy/modify at your convenience.
'''
import time

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from math import sqrt, cos

MAX = 1.52097701e8 #km
MIN = 1.47098074e8 #km
A = (MAX + MIN)/2.
C = (MAX - MIN)/2.;
E = C/A
B = sqrt(A**2-C**2)
#theta = var('theta')
def R(theta): return A*(1-E**2)/(1 - E*cos(theta))

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#Initialization
sum = 0
mult = 3


#Sumamos multiplos de 3 que no sean multiplos de 5
while mult < 1000:
    if mult % 5 != 0:
        if mult %3 != 0:
            sum = sum + mult

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import matplotlib as mpl
import numpy as np
import matplotlib.pyplot as plt
import pylab
import scipy.interpolate


#Lo siguiente es para separar la lista de puntos en los de coordenadas x y los de coordenadas y
'''
A=[[950,1090],[850,1290],[810,1450], [758,1705], [320, 2340] , [860, 1950] , [750,2875] , [1090,2090] , [1148,3020] , [1360, 2110] , [1650,2805] , [1580,1910] , [1700,1710] , [2040,2050] , [2000,1790] , [1840,1510] , [1740,1350] , [1610,1150]]

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Description='A wireless connection using a custom network block configuration'
Interface=wlp3s0
Connection=wireless
Security=wpa-configsection
IP=dhcp
WPAConfigSection=(
    'ssid="university-ssid"'
    'scan_ssid=1'
    'key_mgmt=WPA-EAP'
    'identity="username"'

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#This goes in one cell alone
 
class Carpet:
  '''
  This class contains the generator for Carpet fractals generated by regular polygons.
  It generates the carpet vertices recursively, which is not very efficient, but it
  goes along with the mathematical definition.
  '''
  def __init__(self, x, y, sides, r, contraction):
    '''

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def pascal_matrix(size=500, zp=3):
    '''
    Creates a matrix of size x size, whose entries are numbers in zp, such that
    entry M_{ij} is obtained recursively as in pascal triangle. Each diagonal on 
    the matrix corresponds to a row in Pascal's triangle.
    '''
    M = ones_matrix(size,size)
    for i in range(1, size):
        for j in range(1, size):
            M[i, j] = M[i - 1, j] + M[i, j - 1]

ixxra

# -*- coding: utf-8 -*-
# <nbformat>3.0</nbformat>

# <codecell>

a = imread('cmb_greyscale.png')
aa = mean(a, 2)

from math import ceil