title: Limits of quad integration in scipy with np.inf
body: <p>Here an example with results:</p>
  
  <p>I integrate through Gaussian distribution(mu=800, sigma=1) with ~ +-2sigma ppf and same integral from <code>-inf</code> to <code>+inf</code>. For some reason second integral results in zero, but in practice it should be more accurate.</p>
  
  <p>Can someone explain, why such anomaly happens or where i made a mistake?</p>
  
  <p>code:</p>
  
  <pre><code>from scipy.integrate import quad
  import numpy as np
  from scipy.stats import norm
  
  def integrand(x):
      return x*norm.pdf(x, 800, 1)
  print quad(integrand, norm.ppf(0.05, 800,1), norm.ppf(0.95, 800,1))
  print quad(integrand, -np.inf, np.inf)
  
  (719.9999999999894, 5.913323331834147e-11)
  (0.0, 0.0) 
  </code></pre>
  
  <p>EDIT: By the way, when mean is small( for example 2) , it works fine - both integrals results are very close.</p>