wmmnola

from random import gauss
from random import uniform


def dist2(party, voter):
    progdist = (party.prog - voter.prog)**2
    econdist = (party.econ - voter.econ)**2
    mildist = (party.mil - voter.mil)**2
    return progdist + econdist + mildist

wmmnola

def collatz(n):
  c = n/2 if n % 2==0 else (3*n+1)/2
  return int(c)

def seq(n, func=collatz):
  lst = []
  while(n != 1):
    lst.append(n)
    n = func(n)
  return lst

wmmnola

 def erasto(n):
      primes = [True] * n
      sq = int(math.floor(math.sqrt(n)))
      for i in range(2,sq):
        j = i**2
        while j < n:
          primes[j] = False
          j += i
      return primes

wmmnola

.fizz : .string "Fizz"
.buzz : .string "Buzz"
.endline : .string ":%d \n"
.global main

.newline:
  push %rdi
  push %rsi
  mov $.endline, %rdi
  mov %r8, %rsi

wmmnola

def fizzbuzz(n):
  for i in range(0, n):
    s = "%d : " % i
    s += "fizz" if i % 3 == 0 else ""
    s += "buzz" if i % 5 == 0 else ""
    print(s)
 

wmmnola

import numpy as np

def cheb(n,x):
    if(n == 1): return x
    if(n == 0): return 1
    else: return 2*x*cheb(n-1, x) - cheb(n-2, x)


def add_cheb_distortion(signal, n, ampl = lambda x: 1):
    squash = lambda x,k,L,A: (L-A)/(1+np.exp(k*x))

wmmnola

import numpy as np
import scipy.signal as sig

def dist(s, H, G):
    f = np.linspace(0, 1000, len(s))
    H_seq = [H(f),H(f)]
    inv_fft = np.real(fft.ifft(H_seq))
    final = sig.convolve(s, inv_fft, method='auto')
return G * final

wmmnola

float slowsqrt(float n);
float nestedSqrt(float n, float level);

float slowsqrt(float n){
  float s = 1 + ((n-1)/nestedSqrt(n,0));
  return s;
}

float nestedSqrt(float n, float level){
  if(level < 30){