[NumPy-Tickets] [NumPy] #1864: arange using float for step and integer dtype results in an array with all values being the same

[NumPy Trac]

#1864: arange using float for step and integer dtype results in an array with all
values being the same
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 Reporter:  bsouthey    |       Owner:  somebody   
     Type:  defect      |      Status:  new        
 Priority:  normal      |   Milestone:  Unscheduled
Component:  numpy.core  |     Version:  devel      
 Keywords:              |  
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Comment(by derek):

 Replying to [comment:2 bsouthey]:

 > Actually that is not the expected output either because it is dropping
 the last element(s) as seen when ignoring the 'dtype' (with numpy
 1.6.1rc1):
 {{{
 >>> np.arange(0,20,1.5, dtype=int)
  array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13])
 }}}

 That's (I think) what I meant by "the length remains the same", or more
 precisely, it still has the same shape as np.arange(0,20,1.5,
 dtype=float).
 >
 > Initially I thought that np.arange(start, stop, step, dtype=int) should
 be the same as np.arange(start, stop, step).astype(int). But really it
 should infer the correct output dtype from all of the inputs and let the
 user recast the dtype as needed.
 >

 You mean it first should compute np.arange(int(start), int(stop),
 int(step)), and leave it to the user to apply astype() afterwards if so
 desired? Still I am not sure this would be more useful behaviour, e.g. in
 your original example you'd get a ZeroDivisionError.

-- 
Ticket URL: <http://projects.scipy.org/numpy/ticket/1864#comment:3>
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