title: Difference in output between numpy linspace and numpy logspace
body: <p>Numpy linspace returns evenly spaced numbers over a specified interval. Numpy logspace return numbers spaced evenly on a log scale.</p>
  
  <p>I don't understand why numpy logspace often returns values "out of range" from the bounds I set. Take numbers between <code>0.02</code> and <code>2.0</code>: </p>
  
  <pre><code>import numpy as np
  print np.linspace(0.02, 2.0, num=20)
  print np.logspace(0.02, 2.0, num=20)
  </code></pre>
  
  <p>The output for the first is:</p>
  
  <pre><code>[ 0.02        0.12421053  0.22842105  0.33263158  0.43684211  0.54105263
    0.64526316  0.74947368  0.85368421  0.95789474  1.06210526  1.16631579
    1.27052632  1.37473684  1.47894737  1.58315789  1.68736842  1.79157895
    1.89578947  2.        ]
  </code></pre>
  
  <p>That looks correct. However, the output for <code>np.logspace()</code> is wrong:</p>
  
  <pre><code>[   1.04712855    1.33109952    1.69208062    2.15095626    2.73427446
      3.47578281    4.41838095    5.61660244    7.13976982    9.07600522
     11.53732863   14.66613875   18.64345144   23.69937223   30.12640904
     38.29639507   48.68200101   61.88408121   78.6664358   100.        ]
  </code></pre>
  
  <p>Why does it output <code>1.047</code> to <code>100.0</code>? </p>